Author: "Tanck, A" / Topic: genetics - Searchworks@Jio Institute Digital Library Search Results

86 results on '"Tanck, A"'

1. FCGR2/3 polymorphisms are associated with susceptibility to Kawasaki disease but do not predict intravenous immunoglobulin resistance and coronary artery aneurysms

Author: Uittenbogaard, Paula, Netea, Stejara A, Tanck, Michael WT, Geissler, Judy, Buda, Piotr, Kowalczyk-Domagała, Monika, Okarska-Napierała, Magdalena, van Stijn, Diana, Tacke, Carline E, Consortium, Kawasaki Disease Genetics, Burgner, David P, Shimizu, Chisato, Burns, Jane C, Kuipers, Irene M, Kuijpers, Taco W, and Nagelkerke, Sietse Q
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Human Genome, Cardiovascular, Heart Disease - Coronary Heart Disease, Genetic Testing, Autoimmune Disease, Rare Diseases, Immunization, Infectious Diseases, Heart Disease, Pediatric, 2.1 Biological and endogenous factors, Humans, Mucocutaneous Lymph Node Syndrome, Receptors, IgG, Immunoglobulins, Intravenous, Genetic Predisposition to Disease, Coronary Aneurysm, Male, Polymorphism, Single Nucleotide, Female, Child, Preschool, Drug Resistance, Child, Infant, Case-Control Studies, DNA Copy Number Variations, Kawasaki disease, IVIg, CAA, FCGR2, FCGR3, genetics, FCGR2Ap.His166Arg, US Kawasaki Disease Genetics Consortium, Immunology, Medical Microbiology, Biochemistry and cell biology
Abstract: IntroductionKawasaki disease (KD) is a pediatric vasculitis that can result in coronary artery aneurysm (CAA) formation, which is a dangerous complication. Treatment with intravenous immunoglobulin (IVIg) significantly decreases the risk of CAA, possibly through competitive binding to Fc-gamma receptors (FcγRs), which reduces the binding of pathological immune complexes. However, ~20% of children have recrudescence of fever and have an increased risk of CAA. Therefore, we aimed to identify genetic markers at the FCGR2/3 locus associated with susceptibility to KD, IVIg resistance, or CAA.Materials and methodsWe investigated the association of single-nucleotide polymorphisms (SNPs) and copy number variations (CNVs) at the FCGR2/3 locus with KD susceptibility, IVIg resistance, and CAA risk using a family-based test (KD susceptibility) and case-control analyses (IVIg resistance and CAA risk) in different cohorts, adding up to a total of 1,167 KD cases. We performed a meta-analysis on IVIg resistance and CAA risk including all cohorts supplemented by previous studies identified through a systematic search.ResultsFCGR2A-p.166His was confirmed to be strongly associated with KD susceptibility (Z = 3.17, p = 0.0015). In case-control analyses, all of the investigated genetic variations at the FCGR2/3 locus were generally not associated with IVIg resistance or with CAA risk, apart from a possible association in a Polish cohort for the FCGR3B-NA2 haplotype (OR = 2.15, 95% CI = 1.15-4.01, p = 0.02). Meta-analyses of all available cohorts revealed no significant associations of the FCGR2/3 locus with IVIg resistance or CAA risk.DiscussionFCGR2/3 polymorphisms are associated with susceptibility to KD but not with IVIg resistance and CAA formation. Currently known genetic variations at the FCGR2/3 locus are not useful in prediction models for IVIg resistance or CAA risk.
Published: 2024

2. FCGR2/3 polymorphisms are associated with susceptibility to Kawasaki disease but do not predict intravenous immunoglobulin resistance and coronary artery aneurysms

Author: Paula Uittenbogaard, Stejara A. Netea, Michael W. T. Tanck, Judy Geissler, Piotr Buda, Monika Kowalczyk-Domagała, Magdalena Okarska-Napierała, Diana van Stijn, Carline E. Tacke, US Kawasaki Disease Genetics Consortium, David P. Burgner, Chisato Shimizu, Jane C. Burns, Irene M. Kuipers, Taco W. Kuijpers, and Sietse Q. Nagelkerke
Subjects: Kawasaki disease, IVIg, CAA, FCGR2, FCGR3, genetics, Immunologic diseases. Allergy, RC581-607
Abstract: IntroductionKawasaki disease (KD) is a pediatric vasculitis that can result in coronary artery aneurysm (CAA) formation, which is a dangerous complication. Treatment with intravenous immunoglobulin (IVIg) significantly decreases the risk of CAA, possibly through competitive binding to Fc-gamma receptors (FcγRs), which reduces the binding of pathological immune complexes. However, ~20% of children have recrudescence of fever and have an increased risk of CAA. Therefore, we aimed to identify genetic markers at the FCGR2/3 locus associated with susceptibility to KD, IVIg resistance, or CAA.Materials and methodsWe investigated the association of single-nucleotide polymorphisms (SNPs) and copy number variations (CNVs) at the FCGR2/3 locus with KD susceptibility, IVIg resistance, and CAA risk using a family-based test (KD susceptibility) and case–control analyses (IVIg resistance and CAA risk) in different cohorts, adding up to a total of 1,167 KD cases. We performed a meta-analysis on IVIg resistance and CAA risk including all cohorts supplemented by previous studies identified through a systematic search.ResultsFCGR2A-p.166His was confirmed to be strongly associated with KD susceptibility (Z = 3.17, p = 0.0015). In case–control analyses, all of the investigated genetic variations at the FCGR2/3 locus were generally not associated with IVIg resistance or with CAA risk, apart from a possible association in a Polish cohort for the FCGR3B-NA2 haplotype (OR = 2.15, 95% CI = 1.15–4.01, p = 0.02). Meta-analyses of all available cohorts revealed no significant associations of the FCGR2/3 locus with IVIg resistance or CAA risk.DiscussionFCGR2/3 polymorphisms are associated with susceptibility to KD but not with IVIg resistance and CAA formation. Currently known genetic variations at the FCGR2/3 locus are not useful in prediction models for IVIg resistance or CAA risk.
Published: 2024
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3. Novel risk predictor of arrhythmias for patients with potassium channel–related congenital long QT syndrome

Author: Krijger Juárez, Christian, Proost, Virginnio M., Tanck, Michael W., Dittmann, Sven, Bos, J. Martijn, Crotti, Lia, Barc, Julien, van den Berg, Maarten P., Mujkanovic, Jasmin, Rickert, Corinna, Lopes Neves, Raquel Almeida, Musu, Giulia, Dagradi, Federica, Giovenzana, Fulvio L.F., Clédel, Aurélien, Thollet, Aurélie, Giudicessi, John R., Tfelt-Hansen, Jacob, Probst, Vincent, Schwartz, Peter J., Ackerman, Michael J., Schulze-Bahr, Eric, Bezzina, Connie R., and Wilde, Arthur A.M.
Published: 2024
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4. Extensive Ethnic Variation and Linkage Disequilibrium at the FCGR2/3 Locus: Different Genetic Associations Revealed in Kawasaki Disease

Author: Nagelkerke, Sietse Q, Tacke, Carline E, Breunis, Willemijn B, Tanck, Michael WT, Geissler, Judy, Png, Eileen, Hoang, Long T, van der Heijden, Joris, Naim, Ahmad NM, Yeung, Rae SM, Levin, Michael L, Wright, Victoria J, Burgner, David P, Ponsonby, Anne-Louise, Ellis, Justine A, Cimaz, Rolando, Shimizu, Chisato, Burns, Jane C, Fijnvandraat, Karin, van der Schoot, C Ellen, van den Berg, Timo K, de Boer, Martin, Davila, Sonia, Hibberd, Martin L, Kuijpers, Taco W, Consortium, The International Kawasaki Disease Genetics, Dahdah, Nagib, and Kone-Paut, Isabelle
Subjects: Pharmacology and Pharmaceutical Sciences, Biological Sciences, Biomedical and Clinical Sciences, Genetics, Autoimmune Disease, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Alleles, Case-Control Studies, DNA Copy Number Variations, Ethnicity, Gene Expression Profiling, Gene Frequency, Genetic Association Studies, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Haplotypes, Humans, Linkage Disequilibrium, Mucocutaneous Lymph Node Syndrome, Odds Ratio, Polymorphism, Single Nucleotide, Receptors, IgG, Fc-gamma receptor, FCGR polymorphism, linkage disequilibrium, Kawasaki disease, immunogenetics, International Kawasaki Disease Genetics Consortium, Immunology, Medical Microbiology, Biochemistry and cell biology
Abstract: The human Fc-gamma receptors (FcγRs) link adaptive and innate immunity by binding immunoglobulin G (IgG). All human low-affinity FcγRs are encoded by the FCGR2/3 locus containing functional single nucleotide polymorphisms (SNPs) and gene copy number variants. This locus is notoriously difficult to genotype and high-throughput methods commonly used focus on only a few SNPs. We performed multiplex ligation-dependent probe amplification for all relevant genetic variations at the FCGR2/3 locus in >4,000 individuals to define linkage disequilibrium (LD) and allele frequencies in different populations. Strong LD and extensive ethnic variation in allele frequencies was found across the locus. LD was strongest for the FCGR2C-ORF haplotype (rs759550223+rs76277413), which leads to expression of FcγRIIc. In Europeans, the FCGR2C-ORF haplotype showed strong LD with, among others, rs201218628 (FCGR2A-Q27W, r 2 = 0.63). LD between these two variants was weaker (r 2 = 0.17) in Africans, whereas the FCGR2C-ORF haplotype was nearly absent in Asians (minor allele frequency
Published: 2019

5. A comprehensive evaluation of the genetic architecture of sudden cardiac arrest

Author: Ashar, Foram N, Mitchell, Rebecca N, Albert, Christine M, Newton-Cheh, Christopher, Brody, Jennifer A, Müller-Nurasyid, Martina, Moes, Anna, Meitinger, Thomas, Mak, Angel, Huikuri, Heikki, Junttila, M Juhani, Goyette, Philippe, Pulit, Sara L, Pazoki, Raha, Tanck, Michael W, Blom, Marieke T, Zhao, XiaoQing, Havulinna, Aki S, Jabbari, Reza, Glinge, Charlotte, Tragante, Vinicius, Escher, Stefan A, Chakravarti, Aravinda, Ehret, Georg, Coresh, Josef, Li, Man, Prineas, Ronald J, Franco, Oscar H, Kwok, Pui-Yan, Lumley, Thomas, Dumas, Florence, McKnight, Barbara, Rotter, Jerome I, Lemaitre, Rozenn N, Heckbert, Susan R, O’Donnell, Christopher J, Hwang, Shih-Jen, Tardif, Jean-Claude, VanDenburgh, Martin, Uitterlinden, André G, Hofman, Albert, Stricker, Bruno HC, de Bakker, Paul IW, Franks, Paul W, Jansson, Jan-Hakan, Asselbergs, Folkert W, Halushka, Marc K, Maleszewski, Joseph J, Tfelt-Hansen, Jacob, Engstrøm, Thomas, Salomaa, Veikko, Virmani, Renu, Kolodgie, Frank, Wilde, Arthur AM, Tan, Hanno L, Bezzina, Connie R, Eijgelsheim, Mark, Rioux, John D, Jouven, Xavier, Kääb, Stefan, Psaty, Bruce M, Siscovick, David S, Arking, Dan E, and Sotoodehnia, Nona
Subjects: Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Heart Disease - Coronary Heart Disease, Cardiovascular, Genetics, Human Genome, Prevention, Heart Disease, Clinical Research, 2.1 Biological and endogenous factors, Good Health and Well Being, Arrhythmias, Cardiac, Body Mass Index, Coronary Artery Disease, Death, Sudden, Cardiac, Female, Genome-Wide Association Study, Heart Conduction System, Humans, Male, Mendelian Randomization Analysis, Polymorphism, Single Nucleotide, Risk Assessment, Risk Factors, Sex Factors, Sudden cardiac arrest, Genome-wide association study, Mendelian randomization, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract: AimsSudden cardiac arrest (SCA) accounts for 10% of adult mortality in Western populations. We aim to identify potential loci associated with SCA and to identify risk factors causally associated with SCA.Methods and resultsWe carried out a large genome-wide association study (GWAS) for SCA (n = 3939 cases, 25 989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization (MR) methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA. No variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (i) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (ii) height and BMI, and (iii) electrical instability traits (QT and atrial fibrillation), suggesting aetiologic roles for these traits in SCA risk.ConclusionsOur findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in high-risk populations and the general community.
Published: 2018

6. Translational strategies to uncover the etiology of congenital anomalies of the kidney and urinary tract.

Author: Vendrig, Lisanne M., ten Hoor, Mayke A. C., König, Benthe H., Lekkerkerker, Iris, Renkema, Kirsten Y., Schreuder, Michiel F., van der Zanden, Loes F. M., van Eerde, Albertien M., Groen in 't Woud, Sander, Mulder, Jaap, Westland, Rik, Klomp, L. S., Mak-Nienhuis, L. M., Marsman, R. F. J., Groen, L. A., Bourjouane, D., Tanck, M. W. T., Groothoff, J. W., Levtchenko, E., and Brooks, A. S.
Abstract: While up to 50% of children requiring kidney replacement therapy have congenital anomalies of the kidney and urinary tract (CAKUT), they represent only a fraction of the total patient population with CAKUT. The extreme variability in clinical outcome underlines the fundamental need to devise personalized clinical management strategies for individuals with CAKUT. Better understanding of the pathophysiology of abnormal kidney and urinary tract development provides a framework for precise diagnoses and prognostication of patients, the identification of biomarkers and disease modifiers, and, thus, the development of personalized strategies for treatment. In this review, we provide a state-of-the-art overview of the currently known genetic causes, including rare variants in kidney and urinary tract development genes, genomic disorders, and common variants that have been attributed to CAKUT. Furthermore, we discuss the impact of environmental factors and their interactions with developmental genes in kidney and urinary tract malformations. Finally, we present multi-angle translational modalities to validate candidate genes and environmental factors and shed light on future strategies to better understand the molecular underpinnings of CAKUT. [ABSTRACT FROM AUTHOR]
Published: 2025
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7. Familial multiple discoid fibromas is linked to a locus on chromosome 5 including the FNIP1 gene

Author: Irma van de Beek, Iris E. Glykofridis, Michael W. T. Tanck, Monique N. H. Luijten, Theo M. Starink, Jesper A. Balk, Paul C. Johannesma, Eric Hennekam, Maurice J. B. van den Hoff, Quinn D. Gunst, Johan J. P. Gille, Abeltje M. Polstra, Pieter E. Postmus, Maurice A. M. van Steensel, Alex V. Postma, Rob M. F. Wolthuis, Fred H. Menko, Arjan C. Houweling, Quinten Waisfisz, Human Genetics, Epidemiology and Data Science, Medical Biology, ACS - Heart failure & arrhythmias, CCA - Cancer biology and immunology, Amsterdam Reproduction & Development (AR&D), Human genetics, Cancer Center Amsterdam, APH - Methodology, Dermatology, CCA - Cancer Treatment and quality of life, and ACS - Atherosclerosis & ischemic syndromes
Subjects: Genetics, Genetics (clinical)
Abstract: Previously, we reported a series of families presenting with trichodiscomas, inherited in an autosomal dominant pattern. The phenotype was named familial multiple discoid fibromas (FMDF). The genetic cause of FMDF remained unknown so far. Trichodiscomas are skin lesions previously reported to be part of the same spectrum as the fibrofolliculoma observed in Birt-Hogg-Dubé syndrome (BHD), an inherited disease caused by pathogenic variants in the FLCN gene. Given the clinical and histological differences with BHD and the exclusion of linkage with the FLCN locus, the phenotype was concluded to be distinct from BHD. We performed extensive clinical evaluations and genetic testing in ten families with FMDF. We identified a FNIP1 frameshift variant in nine families and genealogical studies showed common ancestry for eight families. Using whole exome sequencing, we identified six additional rare variants in the haplotype surrounding FNIP1, including a missense variant in the PDGFRB gene that was found to be present in all tested patients with FMDF. Genome-wide linkage analysis showed that the locus on chromosome 5 including FNIP1 was the only region reaching the maximal possible LOD score. We concluded that FMDF is linked to a haplotype on chromosome 5. Additional evaluations in families with FMDF are required to unravel the exact genetic cause underlying the phenotype. When evaluating patients with multiple trichodisomas without a pathogenic variant in the FLCN gene, further genetic testing is warranted and can include analysis of the haplotype on chromosome 5.
Published: 2023
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8. Genome-wide association analyses identify novel Brugada syndrome risk loci and highlight a new mechanism of sodium channel regulation in disease susceptibility

Author: Barc, Julien, Tadros, Rafik, Glinge, Charlotte, Chiang, David Y., Jouni, Mariam, Simonet, Floriane, Jurgens, Sean J., Baudic, Manon, Nicastro, Michele, Potet, Franck, Offerhaus, Joost A., Walsh, Roddy, Choi, Seung Hoan, Verkerk, Arie O., Mizusawa, Yuka, Anys, Soraya, Minois, Damien, Arnaud, Marine, Duchateau, Josselin, Wijeyeratne, Yanushi D., Muir, Alison, Papadakis, Michael, Castelletti, Silvia, Torchio, Margherita, Ortuño, Cristina Gil, Lacunza, Javier, Giachino, Daniela F., Cerrato, Natascia, Martins, Raphaël P., Campuzano, Oscar, Van Dooren, Sonia, Thollet, Aurélie, Kyndt, Florence, Mazzanti, Andrea, Clémenty, Nicolas, Bisson, Arnaud, Corveleyn, Anniek, Stallmeyer, Birgit, Dittmann, Sven, Saenen, Johan, Noël, Antoine, Honarbakhsh, Shohreh, Rudic, Boris, Marzak, Halim, Rowe, Matthew K., Federspiel, Claire, Le Page, Sophie, Placide, Leslie, Milhem, Antoine, Barajas-Martinez, Hector, Beckmann, Britt-Maria, Krapels, Ingrid P., Steinfurt, Johannes, Winkel, Bo Gregers, Jabbari, Reza, Shoemaker, Moore B., Boukens, Bas J., Škorić-Milosavljević, Doris, Bikker, Hennie, Manevy, Federico, Lichtner, Peter, Ribasés, Marta, Meitinger, Thomas, Müller-Nurasyid, Martina, Strauch, Konstantin, Peters, Annette, Schulz, Holger, Schwettmann, Lars, Leidl, Reiner, Heier, Margit, Veldink, Jan H., van den Berg, Leonard H., Van Damme, Philip, Cusi, Daniele, Lanzani, Chiara, Rigade, Sidwell, Charpentier, Eric, Baron, Estelle, Bonnaud, Stéphanie, Lecointe, Simon, Donnart, Audrey, Le Marec, Hervé, Chatel, Stéphanie, Karakachoff, Matilde, Bézieau, Stéphane, London, Barry, Tfelt-Hansen, Jacob, Roden, Dan, Odening, Katja E., Cerrone, Marina, Chinitz, Larry A., Volders, Paul G., van de Berg, Maarten P., Laurent, Gabriel, Faivre, Laurence, Antzelevitch, Charles, Kääb, Stefan, Arnaout, Alain Al, Dupuis, Jean-Marc, Pasquie, Jean-Luc, Billon, Olivier, Roberts, Jason D., Jesel, Laurence, Borggrefe, Martin, Lambiase, Pier D., Mansourati, Jacques, Loeys, Bart, Leenhardt, Antoine, Guicheney, Pascale, Maury, Philippe, Schulze-Bahr, Eric, Robyns, Tomas, Breckpot, Jeroen, Babuty, Dominique, Priori, Silvia G., Napolitano, Carlo, Defaye, Pascal, Anselme, Frédéric, Darmon, Jean Philippe, Wiart, François, de Asmundis, Carlo, Brugada, Pedro, Brugada, Ramon, Arbelo, Elena, Brugada, Josep, Mabo, Philippe, Behar, Nathalie, Giustetto, Carla, Molina, Maria Sabater, Gimeno, Juan R., Hasdemir, Can, Schwartz, Peter J., Crotti, Lia, McKeown, Pascal P., Sharma, Sanjay, Behr, Elijah R., Haissaguerre, Michel, Sacher, Frédéric, Rooryck, Caroline, Tan, Hanno L., Remme, Carol A., Postema, Pieter G., Delmar, Mario, Ellinor, Patrick T., Lubitz, Steven A., Gourraud, Jean-Baptiste, Tanck, Michael W., George, Alfred L., MacRae, Calum A., Burridge, Paul W., Dina, Christian, Probst, Vincent, Wilde, Arthur A., Schott, Jean-Jacques, Redon, Richard, Bezzina, Connie R., KORA-Study Group, Nantes Referral Ctr Inherited Card, unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Nantes Université - UFR de Médecine et des Techniques Médicales (Nantes Univ - UFR MEDECINE), Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), Centre de recherche Cardio-Thoracique de Bordeaux [Bordeaux] (CRCTB), Université Bordeaux Segalen - Bordeaux 2-CHU Bordeaux [Bordeaux]-Institut National de la Santé et de la Recherche Médicale (INSERM), CHU Pontchaillou [Rennes], Laboratoire Traitement du Signal et de l'Image (LTSI), Université de Rennes (UR)-Institut National de la Santé et de la Recherche Médicale (INSERM), Santé - François Bonamy, Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche en Santé de l'Université de Nantes (IRS-UN)-Centre hospitalier universitaire de Nantes (CHU Nantes), Physiologie & médecine expérimentale du Cœur et des Muscles [U 1046] (PhyMedExp), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM), Centre Hospitalier Régional Universitaire [Montpellier] (CHRU Montpellier), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Laboratoire Maladies Rares: Génétique et Métabolisme (Bordeaux) (U1211 INSERM/MRGM), Université de Bordeaux (UB)-Groupe hospitalier Pellegrin-Institut National de la Santé et de la Recherche Médicale (INSERM), Amsterdam UMC - Amsterdam University Medical Center, The MINE study (J.H.V.) has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement no. 772376—EScORIAL). The collaboration project is cofunded by the PPP Allowance made available by Health~Holland, Top Sector Life Sciences & Health, to stimulate public–private partnerships. This study makes use of data generated by the Wellcome Trust Case-Control Consortium. A full list of the investigators who contributed to the generation of the data is available from www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113, 085475 and 090355. The KORA research platform (KORA, Cooperative Research in the Region of Augsburg) was initiated and financed by the Helmholtz Zentrum München—German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research and by the State of Bavaria. Furthermore, KORA research was supported within the Munich Center of Health Sciences (MC Health), Ludwig-Maximilians-Universität, as part of LMUinnovativ. J. Barc is supported by the research program Etoiles montantes des Pays de la Loire REGIOCARD RPH081-U1087-REG-PDL, ANR JCJC LEARN (R21006NN, RPV21014NNA) and by the H2020-MSCA-IF-2014 Program of the European Commission (RISTRAD-661617). R.T. is supported by the Canadian Heart Rhythm Society’s George Mines Award, the European Society of Cardiology research award, and the Philippa and Marvin Carsley Cardiology Chair. D.Y.C. is supported by Fondation Leducq and National Institutes of Health (NIH) NHGRI T32 (no. 1T32HG010464-01). M. Baudic was supported by IRP—VERACITIES—New Mechanisms for VEntricular ARrhythmia And CardIomeTabolic DIseasES, an I-SITE NExT health and engineering initiative (Ecole Centrale and Nantes University) and by the IRP—GAINES—Genetic Architecture IN cardiovascular disEaSes funded by INSERM and CNRS. R.W. is supported by an Amsterdam Cardiovascular Sciences fellowship. S.C. is supported by the NHLBI BioData Catalyst Fellows Program. C.A.R. is supported by Fondation Leducq, the Dutch Heart Foundation (CVON PREDICT2) and the Innovational Research Incentives Scheme Vidi grant from the Netherlands Organisation for Health Research and Development (ZonMw, 91714371). Y.D.W. is supported by the Robert Lancaster Memorial Fund. M.P. is supported by Cardiac Risk in the Young. S.V.D. is supported by Wetenschappelijk Fonds Willy Gepts VUB-UZ Brussel, project ‘Unravelling the molecular genetic pathways of Brugada Syndrome by cardiomics research’, VUB IRP project ‘IMAGica: an Integrative personalized Medical Approach for Genetic diseases, Inherited Cardia Arrhythmias as a model’ and Innoviris BRIDGE 2017, project ‘IGenCare: Integrated Personalised Medical Genomics Care Solution for Patients with Rare Genetic Diseases’. S.H. is supported by the Barts BRC. B.R. is supported by the DZHK (German Centre for Cardiovascular Research) and by the BMBF (German Ministry of Education and Research). B.G.W. is supported by the Danish Heart Foundation. M.B.S. is supported by K23HL127704. Project MinE Belgium was supported by a grant from IWT (no. 140935), the ALS Liga België, the National Lottery of Belgium and the KU Leuven Opening the Future Fund. D.C. and C.L. are supported by HYPERGENES (HEALTH-F4-2007). D.R. is supported by R01 HL149826, P50 GM115305. P.J.S. acknowledges the support of Leducq Foundation for Cardiovascular Research grant 18CVD05. P.V.D. is supported by the Netherlands CardioVascular Research Initiative (CVON PREDICT2). C.A. is supported by NIH HL47678 and HL138103, W.W. Smith Charitable Trust and Wistar Morris Fund. M.B. is Supported by the DZHK (German Centre for Cardiovascular Research) and by the BMBF (German Ministry of Education and Research). P.D.L. is supported by UCL/UCLH Biomedicine NIHR and Barts BRC. B.L. is supported by GOA—Antigone 33933. J.B. is supported by a Senior Clinical Fellowship of the Flemish Science Foundation (FWO). E.B. is supported by the British Heart Foundation including BHF Clinical Research Training Fellowship (FS/11/71/28918: Future diagnostic role and new genetic loci in SADS), Cardiac Risk in the Young and Robert Lancaster Memorial fund sponsored by McColl’s Ltd. Retail Group. H.L.T. is supported by the European Union’s Horizon 2020 research and innovation program under acronym ESCAPE-NET, registered under grant agreement no. 733381, and the Dutch Heart Foundation (CVON RESCUED and PREDICT2 projects). M.D. is supported by NIH-RO1 HL134328. P.T.E. was supported by the Fondation Leducq (14CVD01), the NIH (1RO1HL092577, R01HL128914, K24HL105780), the American Heart Association (18SFRN34110082) and by a research grant from Bayer AG to the Broad Institute. S.A.L. is supported by NIH grant 1R01HL139731 and American Heart Association 18SFRN34250007. J.-B.G. received a grant from the Fédération Française de Cardiologie (PREVENT project). A.L.G. is supported by the Fondation Leducq. C.A.M.R. is supported by the Leducq Foundation and Burroughs Wellecome Fund. A.A.W. is supported by the Dutch Heart Foundation (CVON PREDICT2 project). J.-J.S. is supported by the Fondation pour la Recherche Médicale (DEQ20140329545). R.R. and P.G. are supported by the National Agency for Research (ANR-GENSUD-14-CE10-0001). C.R.B. is supported by the Dutch Heart Foundation (CVON PREDICT2 project), the Netherlands Organization for Scientific Research (VICI fellowship, 016.150.610) and Fondation Leducq (17CVD02)., Barc, J, Tadros, R, Glinge, C, Chiang, D, Jouni, M, Simonet, F, Jurgens, S, Baudic, M, Nicastro, M, Potet, F, Offerhaus, J, Walsh, R, Hoan Choi, S, Verkerk, A, Mizusawa, Y, Anys, S, Minois, D, Arnaud, M, Duchateau, J, Wijeyeratne, Y, Muir, A, Papadakis, M, Castelletti, S, Torchio, M, Gil Ortuño, C, Lacunza, J, Giachino, D, Cerrato, N, Martins, R, Campuzano, O, Van Dooren, S, Thollet, A, Kyndt, F, Mazzanti, A, Clémenty, N, Bisson, A, Corveleyn, A, Stallmeyer, B, Dittmann, S, Saenen, J, Noël, A, Honarbakhsh, S, Rudic, B, Marzak, H, Rowe, M, Federspiel, C, Le Page, S, Placide, L, Milhem, A, Barajas-Martinez, H, Beckmann, B, Krapels, I, Steinfurt, J, Gregers Winkel, B, Jabbari, R, Shoemaker, M, Boukens, B, Škorić-Milosavljević, D, Bikker, H, Manevy, F, Lichtner, P, Ribasés, M, Meitinger, T, Müller-Nurasyid, M, Group, K, Veldink, J, van den Berg, L, Van Damme, P, Cusi, D, Lanzani, C, Rigade, S, Charpentier, E, Baron, E, Bonnaud, S, Lecointe, S, Donnart, A, Le Marec, H, Chatel, S, Karakachoff, M, Bézieau, S, London, B, Tfelt-Hansen, J, Roden, D, Odening, K, Cerrone, M, Chinitz, L, Volders, P, van de Berg, M, Laurent, G, Faivre, L, Antzelevitch, C, Kääb, S, Al Arnaout, A, Dupuis, J, Pasquie, J, Billon, O, Roberts, J, Jesel, L, Borggrefe, M, Lambiase, P, Mansourati, J, Loeys, B, Leenhardt, A, Guicheney, P, Maury, P, Schulze-Bahr, E, Robyns, T, Breckpot, J, Babuty, D, Priori, S, Napolitano, C, Referral Center for inherited cardiac arrhythmia, N, de Asmundis, C, Brugada, P, Brugada, R, Arbelo, E, Brugada, J, Mabo, P, Behar, N, Giustetto, C, Sabater Molina, M, Gimeno, J, Hasdemir, C, Schwartz, P, Crotti, L, Mckeown, P, Sharma, S, Behr, E, Haissaguerre, M, Sacher, F, Rooryck, C, Tan, H, Remme, C, Postema, P, Delmar, M, Ellinor, P, Lubitz, S, Gourraud, J, Tanck, M, L. George Jr., A, Macrae, C, Burridge, P, Dina, C, Probst, V, Wilde, A, Schott, J, Redon &amp, R, Bezzina, C, Cardiology, Graduate School, Medical Biology, ACS - Amsterdam Cardiovascular Sciences, ACS - Heart failure & arrhythmias, Human Genetics, ACS - Pulmonary hypertension & thrombosis, ARD - Amsterdam Reproduction and Development, APH - Methodology, Epidemiology and Data Science, MUMC+: DA KG Polikliniek (9), RS: Carim - H02 Cardiomyopathy, Cardiologie, MUMC+: MA Med Staf Spec Cardiologie (9), RS: Carim - H04 Arrhythmogenesis and cardiogenetics, and Cardiovascular Centre (CVC)
Subjects: EXPRESSION, [SDV]Life Sciences [q-bio], DIAGNOSIS, GUIDELINES, ANNOTATION, Article, NAV1.5 Voltage-Gated Sodium Channel, Young Adult, MANAGEMENT, Genetics, GWAS, Humans, Genetic Predisposition to Disease, 610 Medicine & health, SCN5A, Alleles, Brugada Syndrome, Allele, [SDV.GEN]Life Sciences [q-bio]/Genetics, HERITABILITY, Microtubule-Associated Protein, Brugada Syndrome, GWAS, SNPs, COMMON VARIANTS, Mutation, Disease Susceptibility, Human medicine, ENRICHMENT, Microtubule-Associated Proteins, SNPs, Human, GENERATION, Genome-Wide Association Study
Abstract: Brugada syndrome (BrS) is a cardiac arrhythmia disorder associated with sudden death in young adults. With the exception of SCN5A, encoding the cardiac sodium channel Na(V)1.5, susceptibility genes remain largely unknown. Here we performed a genome-wide association meta-analysis comprising 2,820 unrelated cases with BrS and 10,001 controls, and identified 21 association signals at 12 loci (10 new). Single nucleotide polymorphism (SNP)-heritability estimates indicate a strong polygenic influence. Polygenic risk score analyses based on the 21 susceptibility variants demonstrate varying cumulative contribution of common risk alleles among different patient subgroups, as well as genetic associations with cardiac electrical traits and disorders in the general population. The predominance of cardiac transcription factor loci indicates that transcriptional regulation is a key feature of BrS pathogenesis. Furthermore, functional studies conducted on MAPRE2, encoding the microtubule plus-end binding protein EB2, point to microtubule-related trafficking effects on Na(V)1.5 expression as a new underlying molecular mechanism. Taken together, these findings broaden our understanding of the genetic architecture of BrS and provide new insights into its molecular underpinnings. Genome-wide association analyses identify new susceptibility loci for Brugada syndrome. Functional studies implicate microtubule-related trafficking effects on sodium channel expression as an underlying molecular mechanism., European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program [772376-EScORIAL]; Health~Holland; Top Sector Life Sciences Health; Wellcome Trust [076113, 085475, 090355]; Helmholtz Zentrum Munchen-German Research Center for Environmental Health - German Federal Ministry of Education and Research; State of Bavaria; Munich Center of Health Sciences (MC Health), Ludwig-Maximilians-Universitat, as part of LMUinnovativ; research program Etoiles montantes des Pays de la Loire [REGIOCARD RPH081-U1087-REG-PDL]; ANR JCJC LEARN [R21006NN, RPV21014NNA]; H2020-MSCA-IF-2014 Program of the European Commission [RISTRAD-661617]; Canadian Heart Rhythm Society's George Mines Award; European Society of Cardiology research award; Philippa and Marvin Carsley Cardiology Chair; Fondation Leducq; National Institutes of Health (NIH) NHGRI T32 [1T32HG010464-01]; IRP-VERACITIES-New Mechanisms for VEntricular ARrhythmia And CardIomeTabolic DIseasES an I-SITE NExT health and engineering initiative (Ecole Centrale); IRP-VERACITIES-New Mechanisms for VEntricular ARrhythmia And CardIomeTabolic DIseasES an I-SITE NExT health and engineering initiative (Nantes University); IRP-GAINES-Genetic Architecture IN cardiovascular disEaSes - INSERM; CNRS; Amsterdam Cardiovascular Sciences fellowship; NHLBI BioData Catalyst Fellows Program; Dutch Heart Foundation [CVON PREDICT2]; Innovational Research Incentives Scheme Vidi grant from the Netherlands Organisation for Health Research and Development (ZonMw) [91714371]; Robert Lancaster Memorial Fund; Cardiac Risk in the Young; Wetenschappelijk Fonds Willy Gepts VUB-UZ Brussel; VUB IRP project `IMAGica: an Integrative personalized Medical Approach for Genetic diseases, Inherited Cardia Arrhythmias as a model' and Innoviris BRIDGE 2017; project `IGenCare: Integrated Personalised Medical Genomics Care Solution for Patients with Rare Genetic Diseases'; Barts BRC; DZHK (German Centre for Cardiovascular Research); BMBF (German Ministry of Education and Research); Danish Heart Foundation; IWT [140935]; ALS Liga Belgie; National Lottery of Belgium; KU Leuven Opening the Future Fund; HYPERGENES [HEALTH-F4-2007]; Leducq Foundation for Cardiovascular Research grant [18CVD05]; Netherlands CardioVascular Research Initiative [CVON PREDICT2]; NIH [HL47678, HL138103, 1RO1HL092577, R01HL128914, K24HL105780]; W.W. Smith Charitable Trust; Wistar Morris Fund; GOA-Antigone [33933]; Senior Clinical Fellowship of the Flemish Science Foundation (FWO); British Heart Foundation; BHF Clinical Research Training Fellowship [FS/11/71/28918]; Cardiac Risk in the Young and Robert Lancaster Memorial fund - McColl's Ltd. Retail Group; European Union's Horizon 2020 research and innovation program under acronym ESCAPE-NET [733381]; Dutch Heart Foundation; Fondation Leducq [14CVD01, 17CVD02]; American Heart Association [18SFRN34110082, 18SFRN34250007]; Bayer AG; NIH grant [1R01HL139731]; Federation Francaise de Cardiologie (PREVENT project); Leducq Foundation; Burroughs Wellecome Fund; Fondation pour la Recherche Medicale [DEQ20140329545]; National Agency for Research [ANR-GENSUD-14-CE10-0001]; Netherlands Organization for Scientific Research (VICI fellowship) [016.150.610]; [K23HL127704]; [R01 HL149826]; [P50 GM115305]; [NIH-RO1 HL134328], We are greatly indebted to the patients included in the study. We thank V. Cotard, C. Goutsmedt, M.-F. Le Cunff and N. Bourgeais for assistance in patient recruitment and L. Beekman for his technical support. We thank the biological resource centre for biobanking (CHU Nantes, Nantes Universite, Centre de ressources biologiques (BB0033-00040), F-44000 Nantes, France) for applying the following guidelines68. We are most grateful to the Genomics and Bioinformatics Core Facility of Nantes (GenoBiRD, Biogenouest, IFB) for its technical support. This research has been conducted using the UK Biobank resource; we are grateful to UK Biobank participants. The MINE study (J.H.V.) has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program (grant agreement no. 772376-EScORIAL). The collaboration project is cofunded by the PPP Allowance made available by Health~Holland, Top Sector Life Sciences & Health, to stimulate public-private partnerships. This study makes use of data generated by the Wellcome Trust Case-Control Consortium. A full list of the investigators who contributed to the generation of the data is available from www.wtccc.org.uk.Funding for the project was provided by the Wellcome Trust under award 076113, 085475 and 090355. The KORA research platform (KORA, Cooperative Research in the Region of Augsburg) was initiated and financed by the Helmholtz Zentrum Munchen-German Research Center for Environmental Health, which is funded by the German Federal Ministry of Education and Research and by the State of Bavaria. Furthermore, KORA research was supported within the Munich Center of Health Sciences (MC Health), Ludwig-Maximilians-Universitat, as part of LMUinnovativ. J. Barc is supported by the research program Etoiles montantes des Pays de la Loire REGIOCARD RPH081-U1087-REG-PDL, ANR JCJC LEARN (R21006NN, RPV21014NNA) and by the H2020-MSCA-IF-2014 Program of the European Commission (RISTRAD-661617). R.T. is supported by the Canadian Heart Rhythm Society's George Mines Award, the European Society of Cardiology research award, and the Philippa and Marvin Carsley Cardiology Chair. D.Y.C. is supported by Fondation Leducq and National Institutes of Health (NIH) NHGRI T32 (no. 1T32HG010464-01). M. Baudic was supported by IRP-VERACITIES-New Mechanisms for VEntricular ARrhythmia And CardIomeTabolic DIseasES, an I-SITE NExT health and engineering initiative (Ecole Centrale and Nantes University) and by the IRP-GAINES-Genetic Architecture IN cardiovascular disEaSes funded by INSERM and CNRS. R.W. is supported by an Amsterdam Cardiovascular Sciences fellowship. S.C. is supported by the NHLBI BioData Catalyst Fellows Program. C.A.R. is supported by Fondation Leducq, the Dutch Heart Foundation (CVON PREDICT2) and the Innovational Research Incentives Scheme Vidi grant from the Netherlands Organisation for Health Research and Development (ZonMw; 91714371). Y.D.W. is supported by the Robert Lancaster Memorial Fund. M.P. is supported by Cardiac Risk in the Young. S.V.D. is supported by Wetenschappelijk Fonds Willy Gepts VUB-UZ Brussel, project `Unravelling the molecular genetic pathways of Brugada Syndrome by cardiomics research', VUB IRP project `IMAGica: an Integrative personalized Medical Approach for Genetic diseases, Inherited Cardia Arrhythmias as a model' and Innoviris BRIDGE 2017, project `IGenCare: Integrated Personalised Medical Genomics Care Solution for Patients with Rare Genetic Diseases'. S.H. is supported by the Barts BRC. B.R.; is supported by the DZHK (German Centre for Cardiovascular Research) and by the BMBF (German Ministry of Education and Research). B.G.W. is supported by the Danish Heart Foundation. M.B.S. is supported by K23HL127704. Project MinE Belgium was supported by a grant from IWT (no. 140935), the ALS Liga Belgie, the National Lottery of Belgium and the KU Leuven Opening the Future Fund. D.C. and C.L. are supported by HYPERGENES (HEALTH-F4-2007). D.R. is supported by R01 HL149826, P50 GM115305. P.J.S. acknowledges the support of Leducq Foundation for Cardiovascular Research grant 18CVD05. P.V.D. is supported by the Netherlands CardioVascular Research Initiative (CVON PREDICT2). C.A. is supported by NIH HL47678 and HL138103, W.W. Smith Charitable Trust and Wistar Morris Fund. M.B. is Supported by the DZHK (German Centre for Cardiovascular Research) and by the BMBF (German Ministry of Education and Research). P.D.L. is supported by UCL/UCLH Biomedicine NIHR and Barts BRC. B.L. is supported by GOA-Antigone 33933. J.B. is supported by a Senior Clinical Fellowship of the Flemish Science Foundation (FWO). E.B. is supported by the British Heart Foundation including BHF Clinical Research Training Fellowship (FS/11/71/28918: Future diagnostic role and new genetic loci in SADS), Cardiac Risk in the Young and Robert Lancaster Memorial fund sponsored by McColl's Ltd. Retail Group. H.L.T. is supported by the European Union's Horizon 2020 research and innovation program under acronym ESCAPE-NET, registered under grant agreement no. 733381, and the Dutch Heart Foundation (CVON RESCUED and PREDICT2 projects). M.D. is supported by NIH-RO1 HL134328. P.T.E. was supported by the Fondation Leducq (14CVD01), the NIH (1RO1HL092577, R01HL128914, K24HL105780), the American Heart Association (18SFRN34110082) and by a research grant from Bayer AG to the Broad Institute. S.A.L. is supported by NIH grant 1R01HL139731 and American Heart Association 18SFRN34250007. J.-B.G. received a grant from the Federation Francaise de Cardiologie (PREVENT project). A.L.G. is supported by the Fondation Leducq. C.A.M.R. is supported by the Leducq Foundation and Burroughs Wellecome Fund. A.A.W. is supported by the Dutch Heart Foundation (CVON PREDICT2 project). J.-J.S. is supported by the Fondation pour la Recherche Medicale (DEQ20140329545). R.R. and P.G. are supported by the National Agency for Research (ANR-GENSUD-14-CE10-0001). C.R.B. is supported by the Dutch Heart Foundation (CVON PREDICT2 project), the Netherlands Organization for Scientific Research (VICI fellowship, 016.150.610) and Fondation Leducq (17CVD02).
Published: 2022
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9. Mapping the human genetic architecture of COVID-19

Author: Niemi, MEK, Karjalainen, J, Liao, RG, Neale, BM, Daly, M, Ganna, A, Pathak, GA, Andrews, SJ, Kanai, M, Veerapen, K, Fernandez-Cadenas, I, Schulte, EC, Striano, P, Marttila, M, Minica, C, Marouli, E, Karim, MA, Wendt, FR, Savage, J, Sloofman, L, Butler-Laporte, G, Kim, H-N, Kanoni, S, Okada, Y, Byun, J, Han, Y, Uddin, MJ, Smith, GD, Willer, CJ, Buxbaum, JD, Mehtonen, J, Finucane, H, Cordioli, M, Martin, AR, Zhou, W, Pasaniuc, B, Julienne, H, Aschard, H, Shi, H, Yengo, L, Polimanti, R, Ghoussaini, M, Schwartzentruber, J, Dunham, I, Chwialkowska, K, Francescatto, M, Trankiem, A, Balaconis, MK, Davis, L, Lee, S, Priest, J, Renieri, A, Sankaran, VG, van Heel, D, Deelen, P, Richards, JB, Nakanishi, T, Biesecker, L, Kerchberger, VE, Kenneth, J, Mari, F, Bernasconi, A, Ceri, S, Canakoglu, A, Wolford, B, Faucon, A, Dutta, AK, Schurmann, C, Harry, E, Birney, E, Nguyen, H, Nasir, J, Kaunisto, M, Solomonson, M, Dueker, N, Vadgama, N, Limou, S, Rahmouni, S, Mbarek, H, Darwish, D, Uddin, MM, Albertos, R, Perez-Tur, J, Li, R, Folkersen, L, Moltke, I, Koelling, N, Teumer, A, Kousathanas, A, Utrilla, A, Verdugo, RA, Zarate, R, Medina-Gomez, C, Gomez-Cabrero, D, Carnero-Montoro, E, Cadilla, CL, Moreno-Estrada, A, Garmendia, A, Moya, L, Sedaghati-Khayat, B, Boua, PR, Fave, M-J, Francioli, L, Lemacon, A, Migeotte, I, Patel, S, Varnai, R, Szentpeteri, JL, Sipeky, C, Colombo, F, von Hohenstaufen, K, Lio, P, Vallerga, C, Wang, Q, Tanigawa, Y, Im, H, Han, C, Song, H, Lim, J, Lee, Y, Kim, S, Im, S, Atanasovska, B, Ahmad, HF, Boer, C, Jansen, P, Franke, L, Kaja, E, Pasko, D, Kennis-Szilagyi, I, Kornilov, SA, Prijatelj, V, Prokic, I, Sivanadhan, I, Perumal, S, Esmaeeli, S, Pearson, NM, Auton, A, Shelton, JF, Shastri, AJ, Filshtein-Sonmez, T, Coker, D, Symons, A, Esparza-Gordillo, J, Aslibekyan, S, O'Connell, J, Ye, C, Weldon, CH, Perera, M, O'Leary, K, Tuck, M, O'Brien, T, Meltzer, D, O'Donnell, P, Nutescu, E, Yang, G, Alarcon, C, Herrmann, S, Mazurek, S, Banagan, J, Hamidi, Z, Barbour, A, Raffat, N, Moreno, D, Friedman, P, Ferwerda, B, van de Beek, D, Brouwer, MC, Vlaar, APJ, Wiersinga, WJ, Posthuma, D, Tissink, E, Zwinderman, AHK, Uffelmann, E, van Agtmael, M, Algera, AG, van Baarle, F, Bax, D, Beudel, M, Bogaard, HJ, Bomers, M, Bonta, PI, Bos, L, Botta, M, de Brabander, J, de Bree, G, de Bruin, S, Bugiani, M, Bulle, E, Chouchane, O, Cloherty, A, Dongelmans, D, Elbers, P, Fleuren, L, Geerlings, S, Geerts, B, Geijtenbeek, T, Girbes, A, Goorhuis, B, Grobusch, MP, Hafkamp, F, Hagens, L, Hamann, J, Harris, V, Hemke, R, Hermans, SM, Heunks, L, Hollmann, M, Horn, J, Hovius, JW, de Jong, MD, Koning, R, van Mourik, N, Nellen, J, Nossent, EJ, Paulus, F, Peters, E, van der Poll, T, Preckel, B, Prins, JM, Raasveld, J, Reijnders, T, Schinkel, M, Schultz, MJ, Schuurman, A, Sigaloff, K, Smit, M, Stijnis, CS, Stilma, W, Teunissen, C, Thoral, P, Tsonas, A, van der Valk, M, Veelo, D, de Vries, H, van Vugt, M, Wouters, D, Minnaar, RP, Kromhout, A, van Uffelen, KWJ, Wolterman, RA, Roberts, G, Park, D, Ball, CA, Coignet, M, McCurdy, S, Knight, S, Partha, R, Rhead, B, Zhang, M, Berkowitz, N, Gaddis, M, Noto, K, Ruiz, L, Pavlovic, M, Hong, EL, Rand, K, Girshick, A, Guturu, H, Baltzell, AH, Guntz, J, Beguin, Y, Pigazzini, S, Nkambule, L, Bouysran, Y, Busson, A, Peyrassol, X, Wilkin, F, Pichon, B, Smits, G, Vandernoot, I, Goffard, J-C, Georges, M, Moutschen, M, Misset, B, Darcis, G, Guiot, J, Jadot, L, Azarzar, S, Dellot, P, Gofflot, S, Claassen, S, Bertrand, A, Parzibut, G, Clarinval, M, Moermans, C, Malaise, O, El Kandoussi, K, Thonon, R, Huynen, P, Mesdagh, A, Melo, S, Jacques, N, Di Valentin, E, Giroule, F, Collignon, A, Radermecker, C, Lebrun, M, Peree, H, Latour, S, Barada, O, Sanchez, J, Josse, C, Boujemla, B, Meunier, M, Mariavelle, E, Anania, S, Gazon, H, Juszczak, D, Fadeur, M, Camby, S, Meuris, C, Thys, M, Jacques, J, Henket, M, Leonard, P, Frippiat, F, Giot, J-B, Sauvage, A-S, Von Frenckell, C, Mni, M, Wery, M, Staderoli, A, Belhaj, Y, 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Mandalà, Marco, Zucchi, Patrizia, Giannattasio, Ferdinando, Coviello, Domenico A., Mussini, Cristina, Bosio, Giancarlo, Tavecchia, Luisa, Crotti, Lia, Rizzi, Marco, La Rovere, Maria Teresa, Sarzi-Braga, Simona, Bussotti, Maurizio, Ravaglia, Sabrina, Artuso, Rosangela, Perrella, Antonio, Romani, Davide, Bergomi, Paola, Catena, Emanuele, Vincenti, Antonella, Ferri, Claudio, Grassi, Davide, Pessina, Gloria, Tumbarello, Mario, Di Pietro, Massimo, Sabrina, Ravaglia, Luchi, Sauro, Barbieri, Chiara, Acquilini, Donatella, Andreucci, Elena, Paciosi, Francesco, Segala, Francesco Vladimiro, Tiseo, Giusy, Falcone, Marco, Lista, Mirjam, Poscente, Monica, De Vivo, Oreste, Petrocelli, Paola, Guarnaccia, Alessandra, Baroni, Silvia, Perticaroli, Valentina, Furini, Simone, Dei, Simona, Benetti, Elisa, Picchiotti, Nicola, Sanarico, Maurizio, Ceri, Stefano, Pinoli, Pietro, Raimondi, Francesco, Biscarini, Filippo, Stella, Alessandra, Bergomi, Mattia, Zguro, Kristina, Capitani, Katia, Tanfoni, Marco, 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Piacentini, Paolo, Desanctis, Elena, Cappelli, Silvia, Verzuri, Agnese, Anemoli, Valentina, Pancrazi, Alessandro, Lorubbio, Maria, Merlini, Esther, Miraglia, Federica Gaia, Venturelli, Sophie, Cossarizza, Andrea, Vergori, Alessandra, Gabrieli, Arianna, Riva, Agostino, Andretta, Francesca, Gatti, Francesca, Parisi, Saverio Giuseppe, Baratti, Stefano, Piscopo, Carmelo, Russo, Roberta, Andolfo, Immacolata, Iolascon, Achille, Carella, Massimo, Merla, Giuseppe, Squeo, Gabriella Maria, Raggi, Pamela, Marciano, Carmen, Perna, Rita, Bassetti, Matteo, Sanguinetti, Maurizio, Giorli, Alessia, Salerni, Lorenzo, Parravicini, Pierpaolo, Menatti, Elisabetta, Trotta, Tullio, Coiro, Gabriella, Lena, Fabio, Martinelli, Enrico, Mancarella, Sandro, Gabbi, Chiara, Maggiolo, Franco, Ripamonti, Diego, Bachetti, Tiziana, Suardi, Claudia, Parati, Gianfranco, Bottà, Giordano, Di Domenico, Paolo, Rancan, Ilaria, Bianchi, Francesco, Colombo, Riccardo, van Heel, David A., Hunt, Karen A., Trembath, Richard C., Huang, Qin Qin, Martin, Hilary C., Mason, Dan, Trivedi, Bhavi, Wright, John, Finer, Sarah, Griffiths, Christopher J., Akhtar, Shaheen, Anwar, Mohammad, Arciero, Elena, Ashraf, Samina, Breen, Gerome, Chung, Raymond, Curtis, Charles J., Chowdhury, Maharun, Colligan, Grainne, Deloukas, Pano, Durham, Ceri, Griffiths, Chri, Hurles, Matt, Hussain, Shapna, Islam, Kamrul, Khan, Ahsan, Khan, Amara, Lavery, Cath, Lee, Sang Hyuck, Lerner, Robin, Macarthur, Daniel, Maclaughlin, Bev, Martin, Hilary, Miah, Shefa, Newman, Bill, Safa, Nishat, Tahmasebi, Farah, Smith, Albert V., Boughton, Andrew P., Li, Kevin W., Lefaive, Jonathon, Annis, Aubrey, Jannes, Cinthia E., Krieger, Jose E., Pereira, Alexandre C., Velho, Mariliza, Marques, Emanuelle, Lima, Isabella Ramo, Tada, Mauricio Teruo, Valino, Karina, Mccarthy, Mark, Rosenberger, Carrie, Lee, Jong Eun, Chang, Diana, Hammer, Christian, Hunkapiller, Julie, Mahajan, Anubha, Pendergrass, Sarah, Sucheston-Campbell, Lara, Yaspan, Brian, Lee, Hyun Soo, Shin, Eunsoon, Jang, Hye Yoon, Kim, Sunmie, Kym, Sungmin, Kim, Yeon-Sook, Jeong, Hyeongseok, Kwon, Ki Tae, Kim, Shin-Woo, Kim, Jin Yong, Jang, Young Rock, Kim, Hyun ah, Lee, Ji Yeon, Lee, Jeong Eun, Lee, Shinwon, Choe, Kang-Won, Kang, Yu Min, Jee, Sun Ha, Jung, Keum Ji, Parikh, Victoria, Ashley, Euan, Wheeler, Matthew, Rivas, Manuel, Bustamante, Carlo, Pinksy, Benjamin, Febbo, Phillip, Farh, Kyle, Schroth, Gary P., Desouza, Franci, Dalton, Karen, Christle, Jeff, Deboever, Christopher, Szalma, Sándor, Rubinacci, Simone, Delaneau, Olivier, Gorzynski, John, de Jong, Hannah, Sutton, Shirley, Youlton, Nathan, Joshi, Ruchi, Jimenez-Morales, David, Hughes, Christopher, Amar, David, Ioannidis, Alex, Hershman, Steve, Kirillova, Anna, Seo, Kinya, Huang, Yong, Shoura, Massa, Hammond, Nathan, Watson, Nathaniel, Raja, Archana, Huang, Chunhong, Sahoo, Malaya, Wang, Hannah, Zhen, Jimmy, Rakitko, Alexander, Ilinsky, Valery, Yermakovich, Danat, Popov, Iaroslav, Chernitsov, Alexander, Kovalenko, Elena, Krasnenko, Anna, Plotnikov, Nikolay, Stetsenko, Ivan, Kim, Anna, Cirulli, Elizabeth T., Schiabor Barrett, Kelly M., Bolze, Alexandre, White, Simon, Washington, Nicole L., Lu, James T., Riffle, Stephen, Tanudjaja, Francisco, Wang, Xueqing, Ramirez, Jimmy M., Leonetti, Nicole, Sandoval, Efren, Neveux, Iva, Dabe, Shaun, Grzymski, Joseph J., Esteban Miñano, Juan Ignacio, Aguirre, Luis A., López-Collazo, Eduardo, de la Mata Pazos, Manuel, Cerrato, Luciano, Lozano-Rodríguez, Roberto, Avendaño-Ortiz, José, Arcos, Verónica Terrón, Montalbán-Hernández, Karla Marina, Quiroga, Jaime Valentín, Pascual-Iglesias, Alejandro, Maroun-Eid, Charbel, Martín-Quirós, Alejandro, Namkoong, Ho, Imoto, Seiya, Katayama, Kazuhiko, Fukunaga, Koichi, Kitagawa, Yuko, Sato, Toshiro, Hasegawa, Naoki, Kumanogoh, Atsushi, Kimura, Akinori, Ai, Masumi, Tokunaga, Katsushi, Kanai, Takanori, Miyano, Satoru, Ogawa, Seishi, Edahiro, Ryuya, Sonehara, Kyuto, Shirai, Yuya, Ishii, Makoto, Kabata, Hiroki, Masaki, Katsunori, Kamata, Hirofumi, Ikemura, Shinnosuke, Chubachi, Shotaro, Okamori, Satoshi, Terai, Hideki, Tanaka, Hiromu, Morita, Atsuho, Lee, Ho, Asakura, Takanori, Sasaki, Junichi, Morisaki, Hiroshi, Uwamino, Yoshifumi, Nanki, Kosaku, Mikami, Yohei, Tomono, Kazunori, Kato, Kazuto, Matsuda, Fumihiko, Takahashi, Meiko, Hizawa, Nobuyuki, Takeda, Yoshito, Hirata, Haruhiko, Shiroyama, Takayuki, Miyawaki, Satoru, Suzuki, Ken, Maeda, Yuichi, Nii, Takuro, Noda, Yoshimi, Niitsu, Takayuki, Adachi, Yuichi, Enomoto, Takatoshi, Amiya, Saori, Hara, Reina, Takahashi, Kunihiko, Anzai, Tatsuhiko, Hasegawa, Takanori, Ito, Satoshi, Koike, Ryuji, Endo, Akifumi, Uchimura, Yuji, Miyazaki, Yasunari, Honda, Takayuki, Tateishi, Tomoya, Tohda, Shuji, Ichimura, Naoya, Sonobe, Kazunari, Sassa, Chihiro, Nakajima, Jun, Nannya, Yasuhito, Omae, Yosuke, Takahashi, Kazuhisa, Harada, Norihiro, Hiki, Makoto, Takagi, Haruhi, Nakamura, Ai, Tagaya, Etsuko, Kawana, Masatoshi, Arimura, Ken, Ishiguro, Takashi, Takayanagi, Noboru, Isono, Taisuke, Takaku, Yotaro, Takano, Kenji, Anan, Ryusuke, Nakajima, Yukiko, Nakano, Yasushi, Nishio, Kazumi, Ueda, Soichiro, Hayashi, Reina, Tateno, Hiroki, Hase, Isano, Yoshida, Shuichi, Suzuki, Shoji, Mitamura, Keiko, Saito, Fumitake, Ueda, Tetsuya, Azuma, Masanori, Nagasaki, Tadao, Yasui, Yoshinori, Hasegawa, Yoshinori, Mutoh, Yoshikazu, Yoshiyama, Takashi, Shoko, Tomohisa, Kojima, Mitsuaki, Adachi, Tomohiro, Ishikawa, Motonao, Takahashi, Kenichiro, Watanabe, Kazuyoshi, Manabe, Tadashi, Ito, Fumimaro, Fukui, Takahiro, Funatsu, Yohei, Koh, Hidefumi, Hirai, Yoshihiro, Kawashima, Hidetoshi, Narita, Atsuya, Niwa, Kazuki, Sekikawa, Yoshiyuki, Saito, Fukuki, Yoshiya, Kazuhisa, Yoshihara, Tomoyuki, Suzuki, Yusuke, Nakayama, Sohei, Masuzawa, Keita, Nishi, Koichi, Nishitsuji, Masaru, Tani, Maiko, Inoue, Takashi, Hirano, Toshiyuki, Kobayashi, Keigo, Miyazawa, Naoki, Kimura, Yasuhiro, Sado, Reiko, Ogura, Takashi, Kitamura, Hideya, Murohashi, Kota, Nakachi, Ichiro, Baba, Rie, Arai, Daisuke, Fuke, Satoshi, Saito, Hiroshi, Kuwahara, Naota, Fujiwara, Akiko, Okada, Takenori, Baba, Tomoya, Noda, Junya, Mashimo, Shuko, Yagi, Kazuma, Shiomi, Tetsuya, Hashiguchi, Mizuha, Odani, Toshio, Mochimaru, Takao, Oyamada, Yoshitaka, Mori, Nobuaki, Izumi, Namiki, Nagata, Kaoru, Taki, Reiko, Murakami, Koji, Yamada, Mitsuhiro, Sugiura, Hisatoshi, Hayashi, Kentaro, Shimizu, Tetsuo, Gon, Yasuhiro, Fujitani, Shigeki, Tsuchida, Tomoya, Yoshida, Toru, Kagaya, Takashi, Kita, Toshiyuki, Sakagami, Satoru, Kimizuka, Yoshifumi, Kawana, Akihiko, Nakamura, Yoshihiko, Ishikura, Hiroyasu, Takata, Tohru, Kikuchi, Takahide, Taniyama, Daisuke, Nakamura, Morio, Kodama, Nobuhiro, Kaneyama, Yasunari, Maeda, Shunsuke, Nagasaki, Yoji, Okamoto, Masaki, Ishihara, Sayoko, Ito, Akihiro, Chihara, Yusuke, Takeuchi, Mayumi, Onoi, Keisuke, Hashimoto, Naozumi, Wakahara, Keiko, Ando, Akira, Masuda, Makoto, Wakabayashi, Aya, Watanabe, Hiroki, Sageshima, Hisako, Nakada, Taka-Aki, Abe, Ryuzo, Shimada, Tadanaga, Kawamura, Kodai, Ichikado, Kazuya, Nishiyama, Kenta, Yamasaki, Masaki, Hashimoto, Satoru, Kusaka, Yu, Ohba, Takehiko, Isogai, Susumu, Takada, Minoru, Kanda, Hidenori, Komase, Yuko, Sano, Fumiaki, Asano, Koichiro, Oguma, Tsuyoshi, Harada, Masahiro, Takahashi, Takeshi, Shibusawa, Takayuki, Abe, Shinji, Kono, Yuta, Togashi, Yuki, Izumo, Takehiro, Inomata, Minoru, Awano, Nobuyasu, Ogawa, Shinichi, Ogata, Tomouki, Ishihara, Shoichiro, Kanehiro, Arihiko, Ozaki, Shinji, Fuchimoto, Yasuko, Kitagawa, Yuichiro, Yoshida, Shozo, Ogura, Shinji, Nishiyama, Kei, Yoshida, Kousuke, Beppu, Satoru, Fukuyama, Satoru, Eriguchi, Yoshihiro, Yonekawa, Akiko, Inoue, Yoshiaki, Yamagata, Kunihiro, Chiba, Shigeru, Narumoto, Osamu, Nagai, Hideaki, Ooshima, Nobuharu, Motegi, Mitsuru, Sagara, Hironori, Tanaka, Akihiko, Ohta, Shin, Shibata, Yoko, Tanino, Yoshinori, Sato, Yuki, Yamada, Yuichiro, Hashino, Takuya, Shinoki, Masato, Iwagoe, Hajime, Imamura, Tomonori, Umeda, Akira, Shimada, Hisato, Endo, Mayu, Hayashi, Shinichi, Takahashi, Mai, Nakano, Shigefumi, Yatomi, Masakiyo, Maeno, Toshitaka, Ishii, Tomoo, Utsugi, Mitsuyoshi, Ono, Akihiro, Kanaoka, Kensuke, Ihara, Shoichi, Komuta, Kiyoshi, Boezen, Marike, Claringbould, Annique, Lopera, Esteban, Warmerdam, Robert, Vonk, Judith. M., van Blokland, Irene, Lanting, Pauline, Ori, Anil P. 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F., Nadkarni, Girish N., Do, Ron, O’Reilly, Paul, Huckins, Laura M., Ferreira, Manuel A. R., Abecasis, Goncalo R., Leader, Joseph B., Cantor, Michael N., Justice, Anne E., Carey, Dave J., Chittoor, Geetha, Josyula, Navya Shilpa, Kosmicki, Jack A., Horowitz, Julie E., Baras, Ari, Gass, Matthew C., Yadav, Ashish, Mirshahi, Tooraj, Jan Hottenga, Jouke, Bartels, Meike, de Geus, Eco J. C., Nivard, Michel G., Verma, Anurag, Ritchie, Marylyn D., Rader, Daniel, Li, Binglan, Verma, Shefali S., Lucas, Anastasia, Bradford, Yuki, Zara, Federico, Salpietro, Vincenzo, Scala, Marcello, Iacomino, Michele, Scudieri, Paolo, Bocciardi, Renata, Minetti, Carlo, Riva, Antonella, Vari, Maria Stella, Rahier, Jean-Françoi, Giorgio, Elisa, Carli, Diana, Louis, Edouad, Bulik, Cynthia M., Landén, Mikael, Brusco, Alfredo, Ferrero, Giovanni Battista, Madia, Francesca, Fundín, Bengt, Ismail, Said I., Saad, Chadi, Al-Sarraj, Yaser, Badji, Radja Messai, Al-Muftah, Wadha, Al Thani, Asma, Afifi, Nahla, Klovins, Jani, Rovite, Vita, Rescenko, Raimond, Peculis, Raiti, Ustinova, Monta, Zeberg, Hugo, Frithiof, Robert, Hultström, Michael, Lipcsey, Miklo, Johnson, Ruth, Geschwind, Daniel H., Freimer, Nelson, Butte, Manish J., Ding, Yi, Chiu, Alec, Chang, Timothy S., Boutros, Paul, Moutsianas, Louka, Caulfield, Mark J., Scott, Richard H., Walker, Susan, Stuckey, Alex, Odhams, Christopher A., Rhodes, Daniel, Fowler, Tom, Rendon, Augusto, Chan, Georgia, Arumugam, Prabhu, Karczewski, Konrad J., Wilson, Daniel J., Spencer, Chris A., Crook, Derrick W., Wyllie, David H., O’Connell, Anne Marie, Atkinson, Elizabeth G., Tsuo, Kristin, Baya, Nikola, Turley, Patrick, Gupta, Rahul, Walters, Raymond K., Palmer, Duncan S., Sarma, Gopal, Cheng, Nathan, Lu, Wenhan, Churchhouse, Claire, Goldstein, Jacqueline I., King, Daniel, Seed, Cotton, Daly, Mark J., Bryant, Sam, Satterstrom, F. Kyle, Band, Gavin, Earle, Sarah G., Lin, Shang-Kuan, Arning, Nicola, Armstrong, Jacob, Rudkin, Justine K., Callier, Shawneequa, Cusick, Caroline, Soranzo, Nicole, Zhao, Jing Hua, Danesh, John, Di Angelantonio, Emanuele, Butterworth, Adam S., Sun, Yan V., Huffman, Jennifer E., Cho, Kelly, O’Donnell, Christopher J., Tsao, Phil, Gaziano, J. Michael, Peloso, Gina, Ho, Yuk-Lam, Mian, Michael, Scaggiante, Federica, Chang, Xiao, Glessner, Joseph R., Hakonarson, Hakon, Mcguigan, Peter J., Prockter Moore, Luke Stephen, Vizcaychipi, Marcela Paola, Hall, Kathryn, Campbell, Andy, Nichol, Ailstair, Ward, Geraldine, Page, Valerie Joan, Semple, Malcolm G., Adeniji, Kayode, Agranoff, Daniel, Agwuh, Ken, Ail, Dhiraj, Aldera, Erin L., Alegria, Ana, Angus, Brian, Ashish, Abdul, Atkinson, Dougal, Bari, Shahedal, Barlow, Gavin, Barnass, Stella, Barrett, Nichola, Bassford, Christopher, Basude, Sneha, Baxter, David, Beadsworth, Michael, Bernatoniene, Jolanta, Berridge, John, Best, Nicola, Bothma, Pieter, Chadwick, David, Brittain-Long, Robin, Bulteel, Naomi, Burden, Tom, Burtenshaw, Andrew, Caruth, Vikki, Chambler, Duncan, Chee, Nigel, Child, Jenny, Chukkambotla, Srikanth, Clark, Tom, Collini, Paul, Cosgrove, Catherine, Cupitt, Jason, Cutino-Moguel, Maria-Teresa, Dark, Paul, Dawson, Chri, Dervisevic, Samir, Donnison, Phil, Douthwaite, Sam, Drummond, Andrew, Durand, Ingrid, Dushianthan, Ahilanadan, Dyer, Tristan, Evans, Cariad, Eziefula, Chi, Fegan, Christopher, Finn, Adam, Fullerton, Duncan, Garg, Sanjeev, Garg, Atul, Gkrania-Klotsas, Effrossyni, Godden, Jo, Goldsmith, Arthur, Graham, Clive, Hardy, Elaine, Hartshorn, Stuart, Harvey, Daniel, Havalda, Peter, Hawcutt, Daniel B., Hobrok, Maria, Hodgson, Luke, Hormis, Anil, Jacobs, Michael, Jain, Susan, Jennings, Paul, Kaliappan, Agilan, Kasipandian, Vidya, Kegg, Stephen, Kelsey, Michael, Kendall, Jason, Kerrison, Caroline, Kerslake, Ian, Koch, Oliver, Koduri, Gouri, Koshy, George, Laha, Shondipon, Laird, Steven, Larkin, Susan, Leiner, Tama, Lillie, Patrick, Limb, Jame, Linnett, Vanessa, Little, Jeff, Lyttle, Mark, Macmahon, Michael, Macnaughton, Emily, Mankregod, Ravish, Masson, Huw, Matovu, Elijah, Mccullough, Katherine, Mcewen, Ruth, Meda, Manjula, Mills, Gary H., Minton, Jane, Ward, Karl, Mirfenderesky, Mariyam, Mohandas, Kavya, Mok, Quen, Moon, Jame, Moore, Elinoor, Morgan, Patrick, Morris, Craig, Mortimore, Katherine, Moses, Samuel, Mpenge, Mbiye, Mulla, Rohinton, Murphy, Michael, Nagel, Megan, Nagarajan, Thapa, Nelson, Mark, O’Shea, Matthew K., Otahal, Igor, Ostermann, Marlie, Pais, Mark, Panchatsharam, Selva, Papakonstantinou, Danai, Paraiso, Hassan, Patel, Brij, Pattison, Natalie, Pepperell, Justin, Peters, Mark, Phull, Mandeep, Pintus, Stefania, Pooni, Jagtur Singh, Post, Frank, Price, David, Prout, Rachel, Rae, Nikola, Reschreiter, Henrik, Reynolds, Tim, Richardson, Neil, Roberts, Mark, Roberts, Devender, Rose, Alistair, Rousseau, Guy, Ryan, Brendan, Saluja, Taranprit, Shah, Aarti, Shanmuga, Prad, Sharma, Anil, Shawcross, Anna, Sizer, Jeremy, Shankar-Hari, Manu, Smith, Richard, Snelson, Catherine, Spittle, Nick, Staines, Nikki, Stambach, Tom, Stewart, Richard, Subudhi, Pradeep, Szakmany, Tama, Tatham, Kate, Thomas, Jo, Thompson, Chri, Thompson, Robert, Tridente, Ascanio, Tupper-Carey, Darell, Twagira, Mary, Ustianowski, Andrew, Vallotton, Nick, Vincent-Smith, Lisa, Visuvanathan, Shico, Vuylsteke, Alan, Waddy, Sam, Wake, Rachel, Walden, Andrew, Welters, Ingeborg, Whitehouse, Tony, Whittaker, Paul, Whittington, Ashley, Papineni, Padmasayee, Wijesinghe, Meme, Williams, Martin, Wilson, Lawrence, Cole, Sarah, Winchester, Stephen, Wiselka, Martin, Wolverson, Adam, Wooton, Daniel G., Workman, Andrew, Yates, Bryan, Young, Peter, Beale, Rupert, Bretherick, Andrew D., Clohisey, Sara, Fourman, Max Head, Furniss, Jame, Gountouna, Elvina, Grimes, Graeme, Haley, Chri, Harrison, David, Hayward, Caroline, Keating, Sean, Klaric, Lucija, Klenerman, Paul, Law, Andy, Meynert, Alison M., Millar, Jonathan, Pairo-Castineira, Erola, Parkinson, Nichola, Ponting, Chris P., Porteous, David J., Rawlik, Konrad, Richmond, Anne, Rowan, Kathy, Russell, Clark D., Shen, Xia, Shih, Barbara, Tenesa, Albert, Vitart, Veronique, Wang, Bo, Wilson, James F., Wu, Yang, Yang, Jian, Yang, Zhijian, Zechner, Marie, Zhai, Ranran, Zheng, Chenqing, Norman, Lisa, Pius, Riinu, Drake, Thomas M., Fairfield, Cameron J., Knight, Stephen R., Mclean, Kenneth A., Murphy, Derek, Shaw, Catherine A., Dalton, Jo, Girvan, Michelle, Saviciute, Egle, Roberts, Stephanie, Harrison, Janet, Marsh, Laura, Connor, Marie, Halpin, Sophie, Jackson, Clare, Gamble, Carrol, Leeming, Gary, Law, Andrew, Wham, Murray, Hendry, Ro, Scott-Brown, Jame, Begg, Colin, Hinds, Charle, Wai Ho, Antonia Ying, Horby, Peter W., Knight, Julian, Ling, Lowell, Maslove, David, Mcauley, Danny, Montgomery, Hugh, Nichol, Alistair, Openshaw, Peter J. M., Summers, Charlotte, Walsh, Timothy, Armstrong, Lisa, Bates, Hayley, Dooks, Emma, Farquhar, Fiona, Hairsine, Brigid, Mcparland, C., Packham, Sophie, Alldis, Zoe, Astin-Chamberlain, Raine, Bibi, Fatima, Biddle, Jack, Blow, Sarah, Bolton, Matthew, Borra, Catherine, Bowles, Ruth, Burton, Maudrian, Choudhury, Yasmin, Collier, David, Cox, Amber, Easthope, Amy, Ebano, Patrizia, Fotiadis, Stavro, Gurasashvili, Jana, Halls, Rosslyn, Hartridge, Pippa, Kallon, Delordson, Kassam, Jamila, Lancoma-Malcolm, Ivone, Matharu, Maninderpal, May, Peter, Mitchelmore, Oliver, Newman, Tabitha, Patel, Mital, Pheby, Jane, Pinzuti, Irene, Prime, Zoe, Prysyazhna, Oleksandra, Shiel, Julian, Taylor, Melanie, Tierney, Carey, Wood, Suzanne, Zak, Anne, Zongo, Olivier, Forsey, Miranda, Nicholson, Anne, Riches, Joanne, Vertue, Mark, Wasson, Christopher, Finn, Stephanie, Green, Jackie, Collins, Erin, King, Bernadette, Grauslyte, Lina, Hussain, Musarat, Pogreban, Tatiana, Rosaroso, Lace, Salciute, Erika, Franke, George, Wong, Joanna, George, Aparna, Akeroyd, Louise, Bano, Shereen, Bromley, Matt, Gurr, Lucy, Lawton, Tom, Morgan, Jame, Sellick, Kirsten, Warren, Deborah, Wilkinson, Brian, Mcgowan, Janet, Ledgard, Camilla, Stacey, Amelia, Pye, Kate, Bellwood, Ruth, Bentley, Michael, Loosley, Ronda, Mcguinness, Heather, Tench, Helen, Wolf-Roberts, Rebecca, Gibson, Sian, Lyle, Amanda, Mcneela, Fiona, Radhakrishnan, Jayachandran, Hughes, Alistair, Ali, Asifa, Brady, Megan, Dale, Sam, Dance, Annalisa, Gledhill, Lisa, Greig, Jill, Hanson, Kathryn, Holdroyd, Kelly, Home, Marie, Kelly, Diane, Kitson, Ro, Matapure, Lear, Melia, Deborah, Mellor, Samantha, Nortcliffe, Tonicha, Pinnell, Jez, Robinson, Matthew, Shaw, Lisa, Shaw, Ryan, Thomis, Lesley, Wilson, Alison, Wood, Tracy, Bayo, Lee-Ann, Merwaha, Ekta, Ishaq, Tahira, Hanley, Sarah, Antcliffe, David, Banach, Dorota, Brett, Stephen, Coghlan, Phoebe, Fernandez, Ziortza, Gordon, Anthony, Rojo, Roceld, Arias, Sonia Sousa, Templeton, Maie, Jha, Rajeev, Krishnamurthy, Vinodh, Lim, Lai, Bi, Rehana, Scholefield, Barney, Ashton, Lydia, Williams, Alison, Cheyne, Claire, Saunderson, Anne, Allan, Angela, Anderson, Felicity, Kaye, Callum, Liew, Jade, Medhora, Jasmine, Scott, Teresa, Trumper, Erin, Botello, Adriana, Polgarova, Petra, Stroud, Katerina, Meaney, Eoghan, Jones, Megan, Ng, Anthony, Agrawal, Shruti, Pathan, Nazima, White, Deborah, Daubney, Esther, Elston, Kay, Parker, Robert, Reddy, Amie, Turner-Bone, Ian, Wilding, Laura, Harding, Peter, Jacob, Reni, Jones, Cathy, Denmade, Craig, Croft, Maria, White, Ian, Lim, Li, Griffin, Denise, Muchenje, Nycola, Mupudzi, Mcdonald, Partridge, Richard, Conyngham, Jo-Anna, Thomas, Rachel, Wright, Mary, Corral, Maria Alvarez, Bastion, Victoria, Clarke, Daphene, David, Beena, Kent, Harriet, Lorusso, Rachel, Lubimbi, Gamu, Murdoch, Sophie, Penacerrada, Melchizedek, Thomas, Alastair, Valentine, Jennifer, Vochin, Ana, Wulandari, Retno, Djeugam, Brice, Dawson, Joy, Garrioch, Sweyn, Tolson, Melanie, Aldridge, Jonathan, de Almeida Martins, Laura Gome, Carungcong, Jaime, Beavis, Sarah, Dale, Katie, Gascoyne, Rachel, Hawes, Joanne, Pritchard, Kelly, Stevenson, Lesley, Whileman, Amanda, Cowley, Anne, Highgate, Judith, Crawley, Rikki, Crew, Abigail, Cunningham, Mishell, Daniels, Allison, Harrison, Laura, Hope, Susan, Inweregbu, Ken, Jones, Sian, Lancaster, Nicola, Matthews, Jamie, Nicholson, Alice, Wray, Gemma, Benham, Leonie, Bradshaw, Zena, Brown, Joanna, Caswell, Melanie, Melling, Sarah, Preston, Stephen, Slawson, Nicola, Stoddard, Emma, Warden, Scott, Combes, Edward, Joefield, Teishel, Monnery, Sonja, Beech, Valerie, Trotman, Sallyanne, Hopkins, Bridget, Scriven, Jame, Thrasyvoulou, Laura, Willis, Heather, Anderson, Susan, Birch, Janine, Collins, Emma, Hammerton, Kate, O’Leary, Ryan, Abernathy, Caroline, Foster, Louise, Gratrix, Andrew, Martinson, Vicky, Parkinson, Priyai, Stones, Elizabeth, Carbral-Ortega, Llucia, Kapoor, Ritoo, Loader, David, Castle, Karen, Brandwood, Craig, Smith, Lara, Clark, Richard, Birchall, Katie, Kolakaluri, Laurel, Baines, Deborah, Sukumaran, Anila, Mapfunde, Isheunesu, Meredith, Megan, Morris, Lucy, Ryan, Lucy, Clark, Amy, Sampson, Julia, Peters, Cecilia, Dent, Martin, Langley, Margaret, Ashraf, Saima, Wei, Shuying, Andrew, Angela, Chablani, Manish, Kirkby, Amy, Netherton, Kimberley, Bates, Michelle, Dasgin, Jo, Gill, Jaspret, Nilsson, Annette, Apetri, Elena, Basikolo, Cathrine, Blackledge, Bethan, Catlow, Laura, Charles, Bethan, Doonan, Reece, Harris, Jade, Harvey, Alice, Horner, Daniel, Knowles, Karen, Lee, Stephanie, Lomas, Diane, Lyons, Chloe, Marsden, Tracy, Mclaughlan, Danielle, Mcmorrow, Liam, Pendlebury, Jessica, Perez, Jane, Poulaka, Maria, Proudfoot, Nicola, Slaughter, Melanie, Slevin, Kathryn, Thomas, Vicky, Walker, Danielle, Michael, Angiy, Collis, Matthew, Clark, Martyn, Coulding, Martina, Jude, Edward, Mccormick, Jacqueline, Mercer, Oliver, Potla, Darsh, Rehman, Hafiz, Savill, Heather, Turner, Victoria, Davey, Miriam, Golden, David, Seaman, Rebecca, Hunt, Jodie, Dearden, Joy, Dobson, Emma, Mulcahy, Michelle, Munt, Sheila, O’Connor, Grainne, Philbin, Jennifer, Rishton, Chloe, Tully, Redmond, Winnard, Sarah, Cagova, Lenka, Fofano, Adama, Garner, Lucie, Holcombe, Helen, Mepham, Sue, Mitchell, Alice Michael, Mwaura, Lucy, Praman, K., Vuylsteke, Alain, Zamikula, Julie, Bercades, Georgia, Brealey, David, Hass, Ingrid, Maccallum, Niall, Martir, Glady, Raith, Eamon, Reyes, Anna, Smyth, Deborah, Taylor, Abigail, Hughes, Rachel Anne, Thomas, Helen, Rees, Alun, Duskova, Michaela, Phipps, Janet, Brooks, Suzanne, Edwards, Michelle, Alexander, Peter, Allen, Schvearn, Bradley-Potts, Joanne, Brantwood, Craig, Egan, Jasmine, Felton, Timothy, Padden, Grace, Ward, Luke, Moss, Stuart, Glasgow, Susannah, Beesley, Kate, Board, Sarah, Kubisz-Pudelko, Agnieszka, Lewis, Alison, Perry, Je, Pippard, Lucy, Wood, Di, Buckley, Clare, Brown, Alison, Gregory, Jane, O’Connell, Susan, Smith, Tim, Belagodu, Zakaula, Fuller, Bridget, Gherman, Anca, Olufuwa, Olumide, Paramsothy, Remi, Stuart, Carmel, Oakley, Naomi, Kamundi, Charlotte, Tyl, David, Collins, Katy, Silva, Pedro, Taylor, June, King, Laura, Coates, Charlotte, Crowley, Maria, Wakefield, Phillipa, Beadle, Jane, Johnson, Laura, Sargeant, Janet, Anderson, Madeleine, Jardine, Catherine, Williams, Dewi, Parris, Victoria, Quaid, Sheena, Watson, Ekaterina, Melville, Julie, Naisbitt, Jay, Joseph, Rosane, Lazo, Maria, Walton, Olivia, Neal, Alan, Hill, Michaela, Kannan, Thogulava, Wild, Laura, Allan, Elizabeth, Darlington, Kate, Davies, Ffyon, Easton, Jack, Kumar, Sumit, Lean, Richard, Menzies, Daniel, Pugh, Richard, Qiu, Xinyi, Davies, Llino, Williams, Hannah, Scanlon, Jeremy, Davies, Gwyneth, Mackay, Callum, Lewis, Joannne, Rees, Stephanie, Coetzee, Samantha, Gales, Alistair, Raj, Meena, Sell, Craig, Langton, Helen, Watters, Malcolm, Novis, Catherine, Arbane, Gill, Bociek, Aneta, Campos, Sara, Grau, Neu, Jones, Tim Owen, Lim, Rosario, Marotti, Martina, Whitton, Christopher, Barron, Anthony, Collins, Ciara, Kaul, Sundeep, Passmore, Heather, Prendergast, Claire, Reed, Anna, Rogers, Paula, Shokkar, Rajvinder, Woodruff, Meriel, Middleton, Hayley, Polgar, Oliver, Nolan, Claire, Thwaites, Vicky, Mahay, Kanta, Sri-Chandana, Chunda, Scherewode, Joslan, Stephenson, Lorraine, Marsh, Sarah, Bancroft, Hollie, Bellamy, Mary, Carmody, Margaret, Daglish, Jacqueline, Moore, Faye, Rhodes, Joanne, Sangombe, Mirriam, Kadiri, Salma, Ayers, Amanda, Harrison, Wendy, North, Julie, Cavazza, Anna, Cockrell, Maeve, Corcoran, Eleanor, Depante, Maria, Finney, Clare, Jerome, Ellen, Mcphail, Mark, Nayak, Monalisa, Noble, Harriet, O’Reilly, Kevin, Pappa, Evita, Saha, Rohit, Saha, Sian, Smith, John, Knighton, Abigail, Gill, Mandy, Paul, Paul, Ratnam, Valli, Shelton, Sarah, Wynter, Inez, Baptista, David, Crowe, Rebecca, Fernandes, Rita, Herdman-Grant, Rosaleen, Joseph, Anna, Loveridge, Adam, Mckenley, India, Morino, Eriko, Naranjo, Andre, Simms, Richard, Sollesta, Kathryn, Swain, Andrew, Venkatesh, Harish, Khera, Jacyntha, Fox, Jonathan, Barber, Russell, Hewitt, Claire, Hilldrith, Annette, Jackson-Lawrence, Karen, Shepardson, Sarah, Wills, Maryanne, Butler, Susan, Tavares, Silvia, Cunningham, Amy, Hindale, Julia, Arif, Sarwat, George, Linsha, Twiss, Sophie, Wright, David, Holland, Maureen, Keenan, Natalie, Lyons, Marc, Wassall, Helen, Marsh, Chri, Mahenthran, Mervin, Carter, Emma, Kong, Thoma, Adanini, Oluronke, Bhatia, Nikhil, Msiska, Maine, Mew, Louise, Mwaura, Esther, Williams, Felicity, Wren, Lynn, Sutherland, Sara-Beth, Battle, Ceri, Brinkworth, Elaine, Harford, Rachel, Murphy, Carl, Newey, Luke, Rees, Tabitha, Williams, Marie, Arnold, Sophie, Hardy, John, Houlden, Henry, Moncur, Eleanor, Tariq, Ambreen, Tucci, Arianna, Convery, Karen, Fottrell-Gould, Deirdre, Hudig, Lisa, Keshet-Price, Jocelyn, Randell, Georgina, Stammers, Katie, Abdelrazik, Marwa, Bakthavatsalam, Dhanalakshmi, Elhassan, Munzir, Ganesan, Arunkumar, Haldeos, Anne, Moreno-Cuesta, Jeronimo, Purohit, Dharam, Vincent, Rachel, Xavier, Kugan, Rohit, Kumar, Alasdair, Frater, Saleem, Malik, David, Carter, Jenkins, Samuel, Lamond, Zoe, Wall, Alanna, Reynolds, Jessica, Campbell, Helen, Thompsom, Maria, Dodds, Steve, Duffy, Stacey, Butcher, Deborah, O’Sullivan, Susie, Butterworth-Cowin, Nicola, Deacon, Bethan, Hibbert, Meg, Pothecary, Carla, Tetla, Dariusz, Woodford, Christopher, Durga, Latha, Kennard-Holden, Gareth, de Gordoa, Laura Ortiz-Ruiz, Peasgood, Emily, Phillips, Claire, Skinner, Denise, Gaylard, Jane, Mullan, Dee, Newman, Julie, Davies, Ellie, Roche, Lisa, Sathe, Sonia, Brimfield, Lutece, Daly, Zoe, Pogson, David, Rose, Steve, Collins, Amy, Khaliq, Waqa, Gude, Estefania Treu, Allen, Louise, Beranova, Eva, Crisp, Nikki, Deery, Joanne, Hazelton, Tracy, Knight, Alicia, Price, Carly, Tilbey, Sorrell, Turki, Salah, Turney, Sharon, Giles, Julian, Booth, Simon, Bell, Gillian, English, Katy, Katary, Amro, Wilcox, Louise, Campbell, Rachael, Clarke, Noreen, Whiteside, Jonathan, Mascarenhas, Mairi, Donaldson, Avril, Matheson, Joanna, Barrett, Fiona, O’Hara, Marianne, O’Keefe, Laura, Bradley, Clare, Collier, Dawn, Walker, Rachel, Maynard, Victoria, Patel, Tahera, Smith, Matthew, Kazi, Aayesha, Hartley, Janice, Dykes, Joseph, Hijazi, Muhammad, Keith, Sarah, Khan, Meherunnisa, Ryan-Smith, Janet, Springle, Philippa, Thomas, Jacqueline, Truman, Nick, Saad, Samuel, Coleman, Dabheoc, Fine, Christopher, Matt, Roseanna, Gay, Bethan, Dalziel, Jack, Ali, Syamlan, Goodchild, Drew, Harling, Rhiannan, Bhatterjee, Ravi, Goddard, Wendy, Davison, Chloe, Duberly, Stephen, Hargreaves, Jeanette, Bolton, Rachel, Verlander, Mark, Williams, Alexandra, Blackman, Helen, Creagh-Brown, Ben, Donlon, Sinead, Michalak-Glinska, Natalia, Mtuwa, Sheila, Pristopan, Veronika, Salberg, Armorel, Smith, Eleanor, Stone, Sarah, Piercy, Charle, Verula, Jerik, Burda, Dorota, Montaser, Rugia, Harden, Lesley, Mayangao, Irving, Marriott, Cheryl, Bradley, Paul, Harris, Celia, Cooper, Joshua, Finch, Cheryl, Liderth, Sarah, Quinn, Alison, Waddington, Natalia, Fidler, Katy, Tagliavini, Emma, Donnelly, Kevin, Abel, Lynn, Brett, Michael, Digby, Brian, Gemmell, Lisa, Hornsby, Jame, Macgoey, Patrick, O’Neil, Pauline, Price, Richard, Rodden, Natalie, Rooney, Kevin, Sundaram, Radha, Thomson, Nicola, Flanagan, Rebecca, Hughes, Gareth, Latham, Scott, Mckenna, Emma, Anderson, Jennifer, Hull, Robert, Rhead, Kat, Branney, Debbie, Frankham, Jordan, Pitts, Sally, White, Nigel, Cristiano, Daniele, Dormand, Natalie, Farzad, Zohreh, Gummadi, Mahitha, Liyanage, Kamal, Patel, Brijesh V., Salmi, Sara, Sloane, Geraldine, Varghese, Mathew, Zborowski, Anelise C., Bean, Sarah, Burt, Karen, Spivey, Michael, Eastgate-Jackson, Christine, Filipe, Helder, Martin, Daniel, Maharajh, Amitaa, Garcia, Sara Mingo, De Neef, Mark, Lynch, Ceri, Howe, Gwenllian Sera, Singh, Jayaprakash, Turner, Keri, Ellis, Hannah, Stroud, Natalie, Cherian, Shiney, Cutler, Sean, Heron, Anne Emma, Roynon-Reed, Anna, Williams, Gemma, Richards, Owen, Cheema, Yusuf, Ahmad, Norfaizan, Barker, Joann, Bauchmuller, Kri, Bird, Sarah, Cawthron, Kay, Harrington, Kate, Jackson, Yvonne, Kibutu, Faith, Lenagh, Becky, Masuko, Shamiso, Raithatha, Ajay, Wiles, Matthew, Willson, Jayne, Newell, Helen, Lye, Alison, Nwafor, Lorenza, Jarman, Claire, Rowland-Jones, Sarah, Foote, David, Cole, Joby, Thompson, Roger, Watson, Jame, Hesseldon, Lisa, Macharia, Irene, Chetam, Luke, Smith, Jacqui, Ford, Amber, Anderson, Samantha, Birchall, Kathryn, Housley, Kay, Walker, Sara, Milner, Leanne, Hanratty, Helena, Trower, Helen, Phillips, Patrick, Oxspring, Simon, Donne, Ben, Bevan, Emily, Martin, Jane, Trodd, Dawn, Watson, Geoff, Brown, Caroline Wrey, Bunni, Lara, Jennings, Claire, Latif, Monica, Marshall, Rebecca, Subramanian, Gayathri, Bandla, Nageswar, Gellamucho, Minnie, Davies, Michelle, Thompson, Christopher, Trim, Fiona, Eapen, Beena, Ahmed, Cecilia, Baines, Balvinder, Clamp, Sarah, Colley, Julie, Haq, Risna, Hayes, Anne, Hulme, Jonathan, Hussain, Samia, Joseph, Sibet, Kumar, Rita, Maqsood, Zahira, Purewal, Manjit, Chandler, Ben, Elliott, Kerry, Mallinson, Janine, Turnbull, Alison, Dent, Kathy, Horsley, Elizabeth, Akhtar, Muhmmad Nauman, Pearson, Sandra, Potoczna, Dorota, Spencer, Sue, Blakemore, Hayley, Borislavova, Borislava, Faulkner, Beverley, Gendall, Emma, Goff, Elizabeth, Hayes, Kati, Thomas, Matt, Worner, Ruth, Smith, Kerry, Stephens, Deanna, Delgado, Carlos Castro, Dawson, Deborah, Ding, Lijun, Durrant, Georgia, Ezeobu, Obiageri, Farnell-Ward, Sarah, Harrison, Abiola, Kanu, Rebecca, Leaver, Susannah, Maccacari, Elena, Manna, Soumendu, Saluzzio, Romina Peperman, Queiroz, Joana, Samakomva, Tinashe, Sicat, Christine, Texeira, Joana, Da Gloria, Edna Fernande, Lisboa, Ana, Rawlins, John, Mathew, Jisha, Kinch, Ashley, Hurt, William Jame, Shah, Nirav, Clark, Victoria, Thanasi, Maria, Yun, Nikki, Patel, Kamal, Crickmore, Vikki, Debreceni, Gabor, Wilkins, Joy, Nicol, Liz, Burn, Iona, Hambrook, Geraldine, Manso, Katarina, Penn, Ruth, Shanmugasundaram, Pradeep, Tebbutt, Julie, Thornton, Danielle, Rostron, Anthony, Roy, Alistair, Woods, Lindsey, Cornell, Sarah, Wakinshaw, Fiona, Rogerson, Kimberley, Jarmain, Jordan, Anderson, Peter, Archer, Katie, Austin, Karen, Davis, Caroline, Durie, Alison, Kelsall, Olivia, Thrush, Jessica, Vigurs, Charlie, Wood, Hannah-Louise, Tranter, Helen, Harrison, Alison, Cowley, Nichola, Mcalindon, Michael, Digby, Stephen, Low, Emma, Morgan, Aled, Cother, Naiara, Rankin, Tobia, Clayton, Sarah, Mccurdy, Alex, Allibone, Suzanne, Mary-Genetu, Roman, Patel, Amit, Mac, Ainhi, Murphy, Anthony, Mahjoob, Parisa, Nazari, Roonak, Worsley, Lucy, Fagan, Andrew, Mohamed Ali, Inthakab Ali, Beaumont, Karen, Blunt, Mark, Coton, Zoe, Curgenven, Hollie, Elsaadany, Mohamed, Fernandes, Kay, Ally, Sameena Mohamed, Rangarajan, Harini, Sarathy, Varun, Selvanayagam, Sivarupan, Vedage, Dave, White, Matthew, Fernandez-Roman, Jaime, Hamilton, David O., Johnson, Emily, Johnston, Brian, Martinez, Maria Lopez, Mulla, Suleman, Shaw, David, Waite, Alicia A. C., Waugh, Victoria, Welters, Ingeborg D., Williams, Karen, Bemand, Thoma, Black, Ethel, Rosa, Arnold Dela, Howle, Ryan, Jhanji, Shaman, Baikady, Ravishankar Rao, Tatham, Kate Colette, Thomas, Benjamin, Halkes, Matthew, Mercer, Pauline, Thornton, Lorraine, West, Joe, Baird, Tracy, Ruddy, Jim, Reece-Anthony, Rosie, Birt, Mark, Cowton, Amanda, Kay, Andrea, Kent, Melanie, Potts, Kathryn, Wilkinson, Ami, Naylor, Suzanne, Brown, Ellen, Clark, Michele, Purvis, Sarah, Cole, Jade, Davies, Rhy, Duffin, Donna, Hill, Helen, Player, Ben, Thomas, Emma, Williams, Angharad, Beith, Claire Marie, Black, Karen, Clements, Suzanne, Morrison, Alan, Strachan, Dominic, Taylor, Margaret, Clarkson, Michelle, D’Sylva, Stuart, Norman, Kathryn, Coventry, Tina, Fowler, Susan, Mcgregor, Amanda, Brady, Ailbhe, Chan, Rebekah, Mcivor, Shane, Prady, Helena, Whittle, Helen, Mathew, Bijoy, Clapham, Melanie, Harper, Rosemary, Poultney, Una, Rice, Polly, Mutch, Rachel, Baird, Yolanda, Butler, Aaron, Chadbourn, Indra, Folkes, Linda, Fox, Heather, Gardner, Amy, Gomez, Raquel, Hobden, Gillian, King, Kirsten, Margarson, Michael, Martindale, Tim, Meadows, Emma, Raynard, Dana, Thirlwall, Yvette, Helm, David, Margalef, Jordi, Greer, Sandra, Shuker, Karen, Smuts, Sara, Duffield, Joseph, Smith, Oliver, Mallon, Lewi, Claire, Watkin, Birkinshaw, Isobel, Carter, Joseph, Howard, Kate, Ingham, Joanne, Joy, Rosie, Pearson, Harriet, Roche, Samantha, Scott, Zoe, Knights, Ellen, Price, Alicia, Thomas, Alice, Thorpe, Chri, Abraheem, Azmerelda, Bamford, Peter, Cawley, Kathryn, Dunmore, Charlie, Faulkner, Maria, Girach, Rumanah, Jeffrey, Helen, Jones, Rhianna, London, Emily, Nagra, Imrun, Nasir, Farah, Sainsbury, Hannah, Smedley, Clare, Khade, Reena, Sundar, Ashok, Tsinaslanidis, George, Behan, Teresa, Burnett, Caroline, Hatton, Jonathan, Heeney, Elaine, Mitra, Atideb, Newton, Maria, Pollard, Rachel, Stead, Rachael, Birch, Jenny, Bough, Laura, Goodsell, Josie, Tutton, Rebecca, Williams, Patricia, Williams, Sarah, Winter-Goodwin, Barbara, Auld, Fiona, Donnachie, Joanne, Edmond, Ian, Prentice, Lynn, Runciman, Nikole, Salutous, Dario, Symon, Lesley, Todd, Anne, Turner, Patricia, Short, Abigail, Sweeney, Laura, Murdoch, Euan, Senaratne, Dhaneesha, Burns, Karen, Higham, Andrew, Anderson, Taya, Hawcutt, Dan, O’Malley, Laura, Rad, Laura, Rogers, Naomi, Saunderson, Paula, Allison, Kathryn Sian, Afolabi, Deborah, Whitbread, Jennifer, Jones, Dawn, Dore, Rachael, Lankester, Liana, Nikitas, Nikita, Wells, Colin, Stowe, Bethan, Spencer, Kayleigh, Cathcart, Susanne, Duffy, Katharine, Puxty, Alex, Puxty, Kathryn, Turner, Lynne, Ireland, Jane, Semple, Gary, Barry, Peter, Hilltout, Paula, Evitts, Jayne, Tyler, Amanda, Waldron, Joanne, Irvine, Val, Shelley, Benjamin, Akinkugbe, Olugbenga, Bamford, Alasdair, Beech, Emily, Belfield, Holly, Bell, Michael, Davies, Charlene, Jones, Gareth A. L., Mchugh, Tara, Meghari, Hamza, O’Neill, Lauran, Peters, Mark J., Ray, Samiran, Tomas, Ana Luisa, Gorman, Claire, Gupta, Abhinav, Timlick, Elizabeth, Brady, Rebecca, Bonner, Stephen, Hugill, Keith, Jones, Jessica, Liggett, Steven, Bashyal, Archana, Davidson, Neil, Hutton, Paula, Mckechnie, Stuart, Wilson, Jean, Flint, Neil, Rekha, Patel, Hales, Dawn, Cruz, Carina, Gopal, Shameer, Harris, Nichola, Lake, Victoria, Metherell, Stella, Radford, Elizabeth, Clement, Ian, Patel, Bijal, Gulati, A., Hays, Carole, Webster, K., Hudson, Anne, Webster, Andrea, Stephenson, Elaine, Mccormack, Louise, Slater, Victoria, Nixon, Rachel, Hanson, Helen, Fearby, Maggie, Kelly, Sinead, Bridgett, Victoria, Robinson, Philip, Almaden-Boyle, Christine, Austin, Pauline, Cabrelli, Louise, Cole, Stephen, Casey, Matt, Chapman, Susan, Whyte, Clare, Brayne, Adam, Fisher, Emma, Hunt, Jane, Jackson, Peter, Kaye, Duncan, Love, Nichola, Parkin, Juliet, Tuckey, Victoria, van Koutrik, Lynne, Carter, Sasha, Andrew, Benedict, Findlay, Louise, Adams, Katie, Bruce, Michelle, Connolly, Karen, Duncan, Tracy, T. -Michael, Helen, Lindergard, Gabriella, Hey, Samuel, Fox, Claire, Alfonso, Jordan, Durrans, Laura Jayne, Guerin, Jacinta, Hruska, Martin, Eltayeb, Ayaa, Lamb, Thoma, Hodgkiss, Tracey, Cooper, Lisa, Rothwell, Joanne, Dennis, Catherine, Mcgregor, Alastair, Srikaran, Sinduya, Sukha, Anisha, Davies, Kim, O’Brien, Linda, Omar, Zohra, Perkins, Emma, Lewis, Tracy, Sutherland, Isobel, Brooke, Hollie, Buckley, Sarah, Suarez, Jose Cebrian, Charlesworth, Ruth, Hansson, Karen, Norris, John, Poole, Alice, Rose, Alastair, Sandhu, Rajdeep, Sloan, Brendan, Smithson, Elizabeth, Thirumaran, Muthu, Wagstaff, Veronica, Metcalfe, Alexandra, Camsooksai, Julie, Humphrey, Charlotte, Jenkins, Sarah, Wadams, Beverley, Death, Yasmin, Adams, Colene, Agasou, Anita, Arden, Tracie, Bowes, Amy, Boyle, Pauline, Beekes, Mandy, Button, Heather, Capps, Nigel, Carnahan, Mandy, Carter, Anne, Childs, Danielle, Donaldson, Denise, Hard, Kelly, Hurford, Fran, Hussain, Yasmin, Javaid, Ayesha, Jones, Jame, Jose, Sanal, Leigh, Michael, Martin, Terry, Millward, Helen, Motherwell, Nichola, Rikunenko, Rachel, Stickley, Jo, Summers, Julie, Ting, Louise, Tivenan, Helen, Tonks, Louise, Wilcox, Rebecca, Bokhari, Maria, Lucas, Rachael, Mccormick, Wendy, Ritzema, Jenny, Sanderson, Amanda, Wild, Helen, Baxter, Nicola, Henderson, Steven, Kennedy-Hay, Sophie, Mcparland, Christopher, Rooney, Laura, Sim, Malcolm, Mccreath, Gordan, Brunton, Mark, Caterson, Je, Coles, Holly, Frise, Matthew, Rai, Sabi Gurung, Keating, Liza, Tilney, Emma, Bartley, Shauna, Bhuie, Parminder, Downes, Charlotte, Holding, Kathleen, Riches, Katie, Hilton, Mary, Hayman, Mel, Subramanian, Deepak, Daniel, Priya, Zitter, Letizia, Benyon, Sarah, Marriott, Suzie, Park, Linda, Keenan, Samantha, Gordon, Elizabeth, Quinn, Helen, Baines, Kizzy, Andrew, Gillian, Barclay, Lucy, Callaghan, Marie, Clark, Sarah, Hope, Dave, Marshall, Lucy, Mcculloch, Corrienne, Briton, Kate, Singleton, Jo, Birch, Sophie, Simpson, Kerry, Craig, Jayne, Demetriou, Carrie, Eckbad, Charlotte, Hierons, Sarah, Howie, Lucy, Mitchard, Sarah, Ramos, Lidia, Serrano-Ruiz, Alfredo, White, Katie, Kelly, Fiona, Amin, Vishal, Anastasescu, Elena, Anumakonda, Vikram, Karthik, Komala, Kausar, Rizwana, Reid, Karen, Smith, Jacqueline, Imeson-Wood, Janet, Bellini, Arianna, Bryant, Jade, Mayer, Anton, Pickard, Amy, Roe, Nichola, Sowter, Jason, Howlett, Alex, Criste, Kristine, Cusack, Rebecca, Golder, Kim, Golding, Hannah, Jones, Oliver, Leggett, Samantha, Male, Michelle, Marani, Martyna, Prager, Kirsty, Williams, Toran, Roberts, Belinda, Salmon, Karen, Gondo, Prisca, Hadebe, B., Kayani, Abdul, Masunda, Bridgett, Ahmed, Ashar, Morris, Anna, Jakkula, Sriniva, Long, Kate, Whiteley, Simon, Wilby, Elizabeth, Ogg, Bethan, Moultrie, Sam, Odam, M., Bewley, Jeremy, Garland, Zoe, Grimmer, Lisa, Gumbrill, Bethany, Johnson, Rebekah, Sweet, Katie, Webster, Denise, Efford, Georgia, Bennett, Sara, Goodwin, Emma, Jackson, Matthew, Kent, Alissa, Tibke, Clare, Woodyatt, Wiesia, Zaki, Ahmed, Daniel, Amelia, Finn, Joanne, Saha, Rajnish, Bremmer, Pamela, Allan, J., Geary, T., Houston, Gordon, Meikle, A., O’Brien, P., Bell, Dina, Boyle, Rosalind, Douglas, Katie, Glass, Lynn, Lee, Emma, Lennon, Liz, Rattray, Austin, Charnock, Rob, Mcfarland, Denise, Cosgrove, Denise, Attwood, Ben, Parsons, Penny, Carmody, Siobhain, Oblak, Metod, Popescu, Monica, Thankachen, Mini, Baruah, Rosie, Morris, Sheila, Ferguson, Susie, Shepherd, Amy, Altabaibeh, Abdelhakim, Alvaro, Ana, Gilbert, Kayleigh, Ma, Louise, Mostoles, Loreta, Parmar, Chetan, Simpson, Kathryn, Jetha, Champa, Booker, Lauren, Pratley, Anezka, Cosier, Tracey, Millen, Gemma, Schumacher, Natasha, Weston, Heather, Rand, Jame, Alex, Beatrice, Bach, Benjamin, Barclay, Wendy S., Bogaert, Debby, Chand, Meera, Cooke, Graham S., Docherty, Annemarie B., Dunning, Jake, da Silva Filipe, Ana, Fletcher, Tom, Green, Christoper A., Harrison, Ewen M., Hiscox, Julian A., Ijaz, Samreen, Khoo, Saye, Lim, Wei Shen, Mentzer, Alexander J., Merson, Laura, Noursadeghi, Mahdad, Moore, Shona C., Palmarini, Massimo, Paxton, William A., Pollakis, Georgio, Price, Nichola, Rambaut, Andrew, Robertson, David L., Sancho-Shimizu, Vanessa, Scott, Janet T., de Silva, Thushan, Sigfrid, Louise, Solomon, Tom, Sriskandan, Shiranee, Stuart, David, Tedder, Richard S., Thomson, Emma C., Roger Thompson, A. A., Thwaites, Ryan S., Turtle, Lance C. W., Gupta, Rishi K., Palmieri, Carlo, Swann, Olivia V., Zambon, Maria, Dumas, Marc-Emmanuel, Griffin, Julian L., Takats, Zoltan, Chechi, Kanta, Andrikopoulos, Petro, Osagie, Anthonia, Olanipekun, Michael, Liggi, Sonia, Lewis, Matthew R., Correia, Gonçalo dos Santo, Sands, Caroline J., Takis, Panteleimon, Maslen, Lynn, Greenhalf, William, Shaw, Victoria, Mcdonald, Sarah E., Keating, Seán, Ahmed, Katie A., Armstrong, Jane A., Ashworth, Milton, Asiimwe, Innocent G., Bakshi, Siddharth, Barlow, Samantha L., Booth, Laura, Brennan, Benjamin, Bullock, Katie, Catterall, Benjamin W. A., Clark, Jordan J., Clarke, Emily A., Cooper, Louise, Cox, Helen, Davis, Christopher, Dincarslan, Oslem, Dunn, Chri, Dyer, Philip, Elliott, Angela, Evans, Anthony, Finch, Lorna, Fisher, Lewis W. S., Foster, Terry, Garcia-Dorival, Isabel, Gunning, Philip, Hartley, Catherine, Jensen, Rebecca L., Jones, Christopher B., Jones, Trevor R., Khandaker, Shadia, King, Katharine, Kiy, Robyn T., Koukorava, Chrysa, Lake, Annette, Lant, Suzannah, Latawiec, Diane, Lavelle-Langham, Lara, Lefteri, Daniella, Lett, Lauren, Livoti, Lucia A., Mancini, Maria, Mcdonald, Sarah, Mcevoy, Laurence, Mclauchlan, John, Metelmann, Soeren, Miah, Nahida S., Middleton, Joanna, Mitchell, Joyce, Murphy, Ellen G., Penrice-Randal, Rebekah, Pilgrim, Jack, Prince, Tessa, Reynolds, Will, Ridley, P. Matthew, Sales, Debby, Shaw, Victoria E., Shears, Rebecca K., Small, Benjamin, Subramaniam, Krishanthi S., Szemiel, Agnieska, Taggart, Aislynn, Tanianis-Hughes, Jolanta, Thomas, Jordan, Trochu, Erwan, van Tonder, Libby, Wilcock, Eve, Zhang, J. Eunice, Flaherty, Lisa, Maziere, Nicole, Cass, Emily, Carracedo, Alejandra Doce, Carlucci, Nicola, Holmes, Anthony, Massey, Hannah, Murphy, Lee, Wrobel, Nicola, Mccafferty, Sarah, Morrice, Kirstie, Maclean, Alan, Armstrong, Ruth, Boz, Ceilia, Brown, Adam, Coutts, Audrey, Cullum, Louise, Day, Nicky, Donnelly, Lorna, Duncan, Esther, Fawkes, Angie, Finernan, Paul, Gilchrist, Tammy, Golightly, Ailsa, Hafezi, Katarzyna, Law, Dawn, Law, Rachel, Law, Sarah, Macgillivray, Louise, Mal, Hanning, Mcmaster, Ellie, Meikle, Jen, Oosthuyzen, Wilna, Paterson, Trevor, Stenhouse, Andrew, Swets, Maaike, Szoor-McElhinney, Helen, Taneski, Filip, Wackett, Tony, Ward, Mairi, Weaver, Jane, Coyle, Judy, Gallagher, Bernadette, Lidstone-Scott, Rebecca, Hamilton, Debbie, Schon, Katherine, Furlong, Anita, Biggs, Heather, Griffiths, Fiona, Andrews, Eleanor, Brickell, Kathy, Smyth, Michelle, Murphy, Lorna, Carson, Gail, Hardwick, Hayley, Donohue, Chloe, Pérez-Tur, Jordi [0000-0002-9111-1712], Martín, Javier [0000-0002-2202-0622], Institute for Molecular Medicine Finland [Helsinki] (FIMM), Helsinki Institute of Life Science (HiLIFE), University of Helsinki-University of Helsinki, Broad Institute of MIT and Harvard (BROAD INSTITUTE), Harvard Medical School [Boston] (HMS)-Massachusetts Institute of Technology (MIT)-Massachusetts General Hospital [Boston], Massachusetts General Hospital [Boston], A list of authors and their affiliations appears in the Supplementary Information, Helsingin yliopisto = Helsingfors universitet = University of Helsinki-Helsingin yliopisto = Helsingfors universitet = University of Helsinki, ANR-20-CO11-0001,AABIFNCOV,Bases génétiques et immunologiques des auto-anticorps contre les interférons de type I prédisposant aux formes sévères de COVID-19.(2020), ANR-20-COVI-0003,GENCOVID,Identification des défauts monogéniques de l'immunité responsables des formes sévères de COVID-19 chez les patients précédemment en bonne santé(2020), ANR-21-COVR-0039,GenMIS-C,Recherche des Déficits immunitaires innées monogéniques prédisposant au syndrome inflammatoire multisystémique chez l'enfant.(2021), UCL - SSS/IREC/GAEN - Pôle d'Hépato-gastro-entérologie, UCL - (MGD) Service de gastro-entérologie, Niemi, M, Karjalainen, J, Liao, R, Neale, B, Daly, M, Ganna, A, Pathak, G, Andrews, S, Kanai, M, Veerapen, K, Fernandez-Cadenas, I, Schulte, E, Striano, P, Marttila, M, Minica, C, Marouli, E, Karim, M, Wendt, F, Savage, J, Sloofman, L, Butler-Laporte, G, Kim, H, Kanoni, S, Okada, Y, Byun, J, Han, Y, Uddin, M, Smith, G, Willer, C, Buxbaum, J, Mehtonen, J, Finucane, H, Cordioli, M, Martin, A, Zhou, W, Pasaniuc, B, Julienne, H, Aschard, H, Shi, H, Yengo, L, Polimanti, R, Ghoussaini, M, Schwartzentruber, J, Dunham, I, Chwialkowska, K, Francescatto, M, Trankiem, A, Balaconis, M, Davis, L, Lee, S, Priest, J, Renieri, A, Sankaran, V, van Heel, D, Deelen, P, Richards, J, Nakanishi, T, Biesecker, L, Kerchberger, V, Baillie, J, Mari, F, Bernasconi, A, Baillie, S, Canakoglu, A, 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[0000-0003-1513-6077], Apollo - University of Cambridge Repository, Stem Cell Aging Leukemia and Lymphoma (SALL), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Life Course Epidemiology (LCE), Groningen Research Institute for Asthma and COPD (GRIAC), Guided Treatment in Optimal Selected Cancer Patients (GUTS), AII - Infectious diseases, Amsterdam Neuroscience - Neuroinfection & -inflammation, Neurology, Infectious diseases, Center of Experimental and Molecular Medicine, APH - Aging & Later Life, APH - Global Health, APH - Quality of Care, Amsterdam institute for Infection and Immunity, APH - Health Behaviors & Chronic Diseases, Global Health, APH - Methodology, Graduate School, ACS - Heart failure & arrhythmias, Anesthesiology, ACS - Diabetes & metabolism, APH - Digital Health, APH - Personalized Medicine, ACS - Microcirculation, Niemi, M. E. K., Liao, R. G., Neale, B. M., Pathak, G. A., Andrews, S. J., Schulte, E. C., Karim, M. A., Wendt, F. R., Kim, H. -N., Uddin, M. J., Smith, G. D., Willer, C. J., Buxbaum, J. D., Martin, A. R., Balaconis, M. K., Sankaran, V. G., Brent Richards, J., Eric Kerchberger, V., Kenneth Baillie, J., Dutta, A. K., Uddin, M. M., Perez-Tur, J., Verdugo, R. A., Zarate, R., Medina-Gomez, C., Gomez-Cabrero, D., Cadilla, C. L., Boua, P. R., Fave, M. -J., Lemacon, A., Szentpeteri, J. L., Ahmad, H. F., Kornilov, S. A., Prokic, I., Pearson, N. M., Shelton, J. F., Shastri, A. J., Weldon, C. H., Brouwer, M. C., Vlaar, A. P. J., Joost Wiersinga, W., Algera, A. G., Bogaard, H. J., Bonta, P. I., Grobusch, M. P., Hermans, S. M., Hovius, J. W., de Jong, M. D., Nossent, E. J., Prins, J. M., Schultz, M. J., Stijnis, C. S., Minnaar, R. P., van Uffelen, K. W. J., Wolterman, R. A., Ball, C. A., Mccurdy, S., Hong, E. L., Baltzell, A. H., Goffard, J. -C., Peree, H., Leonard, P., Giot, J. -B., Sauvage, A. -S., Wery, M., Morrison, D. R., Chasse, M., Kaufmann, D. E., Mark Lathrop, G., Davis, L. K., Cox, N. J., Below, J. E., Sealock, J. M., Faucon, A. B., Shuey, M. M., Polikowsky, H. G., Petty, L. E., Shaw, D. M., Chen, H. -H., Ludwig, K. U., Schroder, J., Nothen, M. M., Jensen, B. -E. O., Altmuller, J., Berger, M. M., Gogele, M., Gignoux, C. R., Wicks, S. J., Barnes, K. C., Goldstein, D. B., Reilly, M. P., Gharavi, A. G., O'Byrne, S. M., So, Y. S., Park, S. -K., Kim, H. -L., Kang, C. K., Lee, H. -J., Song, K. -H., Yoon, K. J., Paik, N. -J., Joo, E. -J., Park, W. B., Park, J. S., Park, K. U., Ham, S. Y., Kim, E. S., Kim, H. B., Caceres, M., Lenz, T. L., Julia, A., Holter, J. C., Fernandez, J., Sander, L. E., Banales, J. M., Romero-Gomez, M., Hov, J. R., Karlsen, T. H., Wacker, E. M., Elabd, H., Ruhlemann, M. C., Vadla, M. S., Lenning, O. B., Ozer, O., Kassens, J., Figuera Basso, M. E., Ortiz, A. B., Chercoles, A. G., Holten, A. R., Kildal, A. B., Gluck, A., Nolla, A. C., Dyrhol-Riise, A. M., Spinner, C. D., Hoff, D. A. L., Jimenez, D., Pestana, D., Helbig, E. T., Paraboschi, E. M., Sanchez, F. G., Hernandez, I., Galvan-Femenia, I., Badia, J. R., Muller, K. E., Gaede, K. I., Lippert, L. J., Tellez, L., Gutierrez-Stampa, M. A., Vehreschild, M. J. G. T., Marquie, M., Seilmaier, M. J., Rodriguez-Gandia, M., Ayo, N. I., Martinez, N., Cornely, O. A., Rodrigues, P. M., Espana, P. P., Garcia-Fernandez, A. -E., Fracanzani, A. L., Muniz-Diaz, E., Calderon, E. J., Solligard, E., Medrano, F. J., Muller, F., Afset, J. E., Damas, J. K., Ferrusquia-Acosta, J., Quero, J. H., Guerrero, J. M., Bettini, L. R., Gustad, L. T., Valsecchi, M. G., D'Angio, M., Gallego-Duran, R., Cejudo, T. G., Grimsrud, M. M., Gudbjartsson, D. F., Moore, K. H. S., Alarcon-Riquelme, M. E., Martinez-Bueno, M., Rello, S. R., Lall, K., Bochud, P. -Y., Nussle, S. G., Meyer zu Bentrup, F., Merlet Viollet, R., Guery, B., Hugli, O., Gonseth Nussle, S., Estoppey Younes, S., Rochat Negro, T., Mercader, J. M., Castano-Vinyals, G., Dobano, C., Mondelli, M. U., Mazzei, M. A., Caldarelli, G. P., Monforte, A. D., Scotton, P. G., Monica, M. D., Mandala, M., Coviello, D. A., La Rovere, M. T., Segala, F. V., Mencarelli, M. A., Pinto, A. M., Carriero, M. L., Ann Belli, M., Antoni, M. D., Miraglia, F. G., Parisi, S. G., Squeo, G. M., Botta, G., Hunt, K. A., Trembath, R. C., Martin, H. C., Griffiths, C. J., Curtis, C. J., Huang, Q. Q., Lee, S. H., Macarthur, D., Maclaughlin, B., Smith, A. V., Boughton, A. P., Li, K. W., Lefaive, J., Jannes, C. E., Krieger, J. E., Pereira, A. C., Lima, I. R., Tada, M. T., Mccarthy, M., Lee, J. E., Lee, H. S., Jang, H. Y., Kim, Y. -S., Kwon, K. T., Kim, S. -W., Kim, J. Y., Jang, Y. R., Kim, H., Lee, J. Y., Choe, K. -W., Kang, Y. M., Jee, S. H., Jung, K. J., Schroth, G. P., Desouza, F., Cirulli, E. T., Schiabor Barrett, K. M., Washington, N. L., Lu, J. T., Ramirez, J. M., Grzymski, J. J., Minano, J. I. E., Aguirre, L. A., Lopez-Collazo, E., Lozano-Rodriguez, R., Avendano-Ortiz, J., Arcos, V. T., Montalban-Hernandez, K. M., Quiroga, J. V., Martin-Quiros, A., Nakada, T. -A., Vonk, J. M., Ori, A. P. S., Hernandez Cordero, A. I., Sin, D. D., Bosse, Y., Feng, Y. -C. A., Weiss, S. T., Karlson, E. W., Smoller, J. W., Murphy, S. N., Meigs, J. B., Woolley, A. E., Green, R. C., Perez, E. F., Zollner, S., Sloofman, L. G., Sebra, R. P., Collins, B. L., Sealfon, S. C., Jordan, D. M., Thompson, R. C., Belbin, G. M., Underwood, S. J., Hiester, L. L., Charney, A. W., Beckmann, N. D., Schadt, E. E., Abul-Husn, N. S., Cho, J. H., Kenny, E. E., Loos, R. J. F., Nadkarni, G. N., Huckins, L. M., Ferreira, M. A. R., Abecasis, G. R., Leader, J. B., Cantor, M. N., Justice, A. E., Carey, D. J., Josyula, N. S., Kosmicki, J. A., Horowitz, J. E., Gass, M. C., Hottenga, J. J., de Geus, E. J. C., Nivard, M. G., Ritchie, M. D., Verma, S. S., Vari, M. S., Rahier, J. -F., Bulik, C. M., Landen, M., Ferrero, G. B., Fundin, B., Ismail, S. I., Badji, R. M., Hultstrom, M., Geschwind, D. H., Butte, M. J., Chang, T. S., Caulfield, M. J., Scott, R. H., Odhams, C. A., Karczewski, K. J., Wilson, D. J., Spencer, C. A., Crook, D. W., Wyllie, D. H., O'Connell, A. M., Atkinson, E. G., Walters, R. K., Palmer, D. S., Goldstein, J. I., Kyle Satterstrom, F., Earle, S. G., Lin, S. -K., Rudkin, J. K., Zhao, J. H., Butterworth, A. S., Sun, Y. V., Huffman, J. E., O'Donnell, C. J., Michael Gaziano, J., Ho, Y. -L., Glessner, J. R., Mcguigan, P. J., Moore, L. S. P., Vizcaychipi, M. P., Page, V. J., Aldera, E. L., Cutino-Moguel, M. -T., Durand, I., Hawcutt, D. B., Macmahon, M., Macnaughton, E., Mccullough, K., Mcewen, R., O'Shea, M. K., Pooni, J. S., Wooton, D. G., Bretherick, A. D., Fourman, M. H., Meynert, A. M., Ponting, C. P., Porteous, D. J., Russell, C. D., Wilson, J. F., Drake, T. M., Fairfield, C. J., Knight, S. R., Mclean, K. A., Shaw, C. A., Ho, A. Y. W., Horby, P. W., Mcauley, D., Openshaw, P. J. M., Semple, M. G., Mcgowan, J., Mcguinness, H., Mcneela, F., Bayo, L. -A., Arias, S. S., Conyngham, J. -A., Corral, M. A., de Almeida Martins, L. G., Mclaughlan, D., Mcmorrow, L., Mccormick, J., Mitchell, A. M., Maccallum, N., Hughes, R. A., Jones, T. O., Mcphail, M., Mckenley, I., Sutherland, S. -B., de Gordoa, L. O. -R., Gude, E. T., Macgoey, P., Mckenna, E., Patel, B. V., Zborowski, A. C., Garcia, S. M., Howe, G. S., Heron, A. E., Mills, G. H., Brown, C. W., Akhtar, M. N., Delgado, C. C., Saluzzio, R. P., Da Gloria, E. F., Hurt, W. J., Wood, H. -L., Mcalindon, M., Mccurdy, A., Ali, I. A. M., Ally, S. M., Hamilton, D. O., Lopez Martinez, M., Waite, A. A. C., Welters, I. D., Rosa, A. D., Baikady, R. R., Tatham, K. C., Beith, C. M., Mcgregor, A., Mcivor, S., Allison, K. S., Jones, G. A. L., Mchugh, T., Peters, M. J., Tomas, A. L., Mckechnie, S., Mccormack, L., Michael, H. T., Durrans, L. J., Suarez, J. C., Death, Y., Mccormick, W., Mccreath, G., Rai, S. G., Mcculloch, C., Mcfarland, D., Barclay, W. S., Cooke, G. S., Docherty, A. B., Green, C. A., Harrison, E. M., Hiscox, J. A., Lim, W. S., Mentzer, A. J., Paxton, W. A., Robertson, D. L., Scott, J. T., Tedder, R. S., Thomson, E. C., Thwaites, R. S., Gupta, R. K., Swann, O. V., Dumas, M. -E., Griffin, J. L., Lewis, M. R., dos Santos Correia, G., Sands, C. J., Mcdonald, S. E., Ahmed, K. A., Armstrong, J. A., Asiimwe, I. G., Barlow, S. L., Catterall, B. W. A., Clark, J. J., Clarke, E. A., Fisher, L. W. S., Jensen, R. L., Jones, C. B., Jones, T. R., Kiy, R. T., Livoti, L. A., Mcdonald, S., Mcevoy, L., Mclauchlan, J., Miah, N. S., Moore, S. C., Murphy, E. G., Matthew Ridley, P., Shaw, V. E., Shears, R. K., Subramaniam, K. S., Eunice Zhang, J., Carracedo, A. D., Mccafferty, S., Turtle, L. C. W., Data Science Genetic Epidemiology Lab, Institute for Molecular Medicine Finland, HUS Helsinki and Uusimaa Hospital District, University of Helsinki, Research Programs Unit, Doctoral Programme in Population Health, Centre of Excellence in Complex Disease Genetics, Aarno Palotie / Principal Investigator, Genomics of Neurological and Neuropsychiatric Disorders, and University of Zurich
Subjects: Male, 45/43, Autoimmunity, Autoimmunity/genetics, Body Mass Index, COVID-19/genetics, COVID-19/virology, Critical Illness, Female, Genetic Loci/genetics, Genetic Predisposition to Disease, Genome-Wide Association Study, Geographic Mapping, Hospitalization, Host-Pathogen Interactions/genetics, Humans, Inflammation/complications, Information Dissemination, Multifactorial Inheritance, Racial Groups/genetics, SARS-CoV-2/pathogenicity, Smoking, environmental risk factors, Q1, 631/208, 0302 clinical medicine, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Genetics, Genome-wide association studies, SARS-CoV-2, Viral infection, GWAS, Aetiology, Lung, QC, 0303 health sciences, HERITABILITY, 3. Good health, covid-19, Science & Technology - Other Topics, Identification (biology), Infection, Human, 631/208/205/2138, Settore BIO/11 - Biologia Molecolare, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Clinical Research, Biodefense, Genetics, GENOME-WIDE ASSOCIATION, Medisinske Fag: 700::Basale medisinske, odontologiske og veterinærmedisinske fag: 710::Medisinsk genetikk: 714 [VDP], METAANALYSIS, 1000 Multidisciplinary, [SDV.GEN]Life Sciences [q-bio]/Genetics, Science & Technology, Prevention, Racial Groups, Pneumonia, genetic architecture, Human genetics, Genetic Loci, genetic factors, 570 Life sciences, biology, 030217 neurology & neurosurgery, Medizin, Infektionsmedicin, Genome-wide association studies, Settore BIO/12 - BIOCHIMICA CLINICA E BIOLOGIA MOLECOLARE CLINICA, Pandemic, 2.1 Biological and endogenous factors, pandemi, Multidisciplinary, article, Public Health, Global Health, Social Medicine and Epidemiology, Racial Group, 10124 Institute of Molecular Life Sciences, Host-Pathogen Interaction, Multidisciplinary Sciences, Infectious Diseases, Host-Pathogen Interactions, Critical Illne, COVID-19, GWAS, genetic factors, environmental risk factors, therapy, Infectious Medicine, Coronavirus disease 2019 (COVID-19), SUSCEPTIBILITY LOCI, General Science & Technology, Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Computational biology, Biology, Vaccine Related, 692/699/255/2514, Environmental risk, Mendelian randomization, COVID-19 Host Genetics Initiative, QH426, 631/326/596/4130, 030304 developmental biology, Inflammation, therapy, SARS-CoV-2, Human Genome, COVID-19, Genetic architecture, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, Emerging Infectious Diseases, Good Health and Well Being, Viral infection, 3111 Biomedicine
Abstract: Niemi, Mari E. K. et al. 39 páginas, figuras y tablas. Contiene material suplementario., The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3-7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease.
Published: 2021
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10. Common and rare susceptibility genetic variants predisposing to Brugada syndrome in Thailand

Author: Peter Lichtner, Pharawee Wandee, John Mauleekoonphairoj, Apichai Khongphatthanayothin, Pattarapong Makarawate, Yong Poovorawan, Thomas Meitinger, Dujdao Sahasatas, Somchai Prechawat, Rungroj Krittayaphong, Boosamas Sutjaporn, Charlotte Glinge, Ahmad S. Amin, Arthur A.M. Wilde, Fleur V.Y. Tjong, Montawatt Amnueypol, Alisara Anannab, Rafik Tadros, Tachapong Ngarmukos, Connie R. Bezzina, Krystien V.V. Lieve, Duangdao Wichadakul, Roddy Walsh, Gumpanart Veerakul, Michael W.T. Tanck, Sunchai Payungporn, Jacob Tfelt-Hansen, Wanwarang Wongcharoen, Koonlawee Nademanee, Cardiology, ACS - Heart failure & arrhythmias, Graduate School, APH - Methodology, and Epidemiology and Data Science
Subjects: Adult, Male, Genome-wide association study, DNA Mutational Analysis, Locus (genetics), 030204 cardiovascular system & hematology, NAV1.5 Voltage-Gated Sodium Channel, 03 medical and health sciences, Rare Diseases, 0302 clinical medicine, Gene Frequency, Physiology (medical), Genetic variation, Genetics, medicine, Humans, Genetic Predisposition to Disease, Brugada syndrome, 030212 general & internal medicine, HEY2, SCN5A, Retrospective Studies, business.industry, Incidence, fungi, Genetic variants, Genetic Variation, DNA, Odds ratio, Middle Aged, Thailand, medicine.disease, Minor allele frequency, Phenotype, Mutation, Female, Cardiology and Cardiovascular Medicine, business
Abstract: BACKGROUND: Mutations in SCN5A are rarely found in Thai patients with Brugada syndrome (BrS). Recent evidence suggested that common genetic variations may underlie BrS in a complex inheritance model. OBJECTIVE: The purpose of this study was to find common and rare/low-frequency genetic variants predisposing to BrS in persons in Thailand. METHODS: We conducted a genome-wide association study (GWAS) to explore the association of common variants in 154 Thai BrS cases and 432 controls. We sequenced SCN5A in 131 cases and 205 controls. Variants were classified according to current guidelines, and case-control association testing was performed for rare and low-frequency variants. RESULTS: Two loci were significantly associated with BrS. The first was near SCN5A/SCN10A (lead marker rs10428132; odds ratio [OR] 2.4; P = 3 × 10-10). Conditional analysis identified a novel independent signal in the same locus (rs6767797; OR 2.3; P = 2.7 × 10-10). The second locus was near HEY2 (lead marker rs3734634; OR 2.5; P = 7 × 10-9). Rare (minor allele frequency [MAF] 0.0001) variants also was observed in cases, with 1 variant (SCN5A: p.Arg965Cys) detected in 4.6% of Thai BrS patients vs 0.5% in controls (P = 0.015; OR 9.8; 95% CI 1.2-82.3). CONCLUSION: The genetic basis of BrS in Thailand includes a wide spectrum of variant frequencies and effect sizes. As previously shown in European and Japanese populations, common variants near SCN5A and HEY2 are associated with BrS in the Thai population, confirming the transethnic transferability of these 2 major BrS loci.
Published: 2020
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11. SCN5A Mutation Type and a Genetic Risk Score Associate Variably with Brugada Syndrome Phenotype in SCN5A Families

Author: Peter Lichtner, Thomas Meitinger, Wataru Shimizu, Alison Muir, F. Kyndt, Michael W.T. Tanck, Seiko Ohno, Martina Muggenthaler, Michael J. Ackerman, Vincent Probst, Stephen P. Page, Jean-Jacques Schott, Silvia Castelletti, Hariharan Raju, Jean-Baptiste Gourraud, Joseph Galvin, Taisuke Ishikawa, Eline A. Nannenberg, Dan M. Roden, Doris Škorić-Milosavljević, Kazuhiro Takahashi, Pascal P. McKeown, Federica Dagradi, Lia Crotti, Yanushi D. Wijeyeratne, Julien Barc, Yuka Mizusawa, Peter J. Schwartz, Michael Papadakis, Margherita Torchio, Sanjay Sharma, Velislav N. Batchvarov, Naomasa Makita, Richard Redon, Christian Veltmann, Elijah R. Behr, Takeshi Aiba, Martin Borggrefe, Rafik Tadros, Connie R. Bezzina, J. Martijn Bos, David J. Tester, Isabelle Denjoy, Minoru Horie, Arthur A.M. Wilde, St George's, University of London, Academic Medical Center - Academisch Medisch Centrum [Amsterdam] (AMC), University of Amsterdam [Amsterdam] (UvA), unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Centro Cardiologico Monzino [Milano], Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS)-Dpt di Scienze Cliniche e di Comunità [Milano] (DISCCO), Università degli Studi di Milano [Milano] (UNIMI)-Università degli Studi di Milano [Milano] (UNIMI), Mayo Clinic [Rochester], Belfast Health and Social Care Trust, Hannover Medical School [Hannover] (MHH), University of Shiga Prefecture, National Cerebral and Cardiovascular Center (NCCC - OSAKA), Osaka University [Osaka], Leeds Teaching Hospitals NHS Trust, University of Dublin, Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Helmholtz-Zentrum München (HZM), Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Iwate Prefectural University [Takizawa], Vanderbilt University School of Medicine [Nashville], University of Heidelberg, Medical Faculty, Wijeyeratne, Y, Tanck, M, Mizusawa, Y, Batchvarov, V, Barc, J, Crotti, L, Bos, J, Tester, D, Muir, A, Veltmann, C, Ohno, S, Page, S, Galvin, J, Tadros, R, Muggenthaler, M, Raju, H, Denjoy, I, Schott, J, Gourraud, J, Skoric-Milosavljevic, D, Nannenberg, E, Redon, R, Papadakis, M, Kyndt, F, Dagradi, F, Castelletti, S, Torchio, M, Meitinger, T, Lichtner, P, Ishikawa, T, Wilde, A, Takahashi, K, Sharma, S, Roden, D, Borggrefe, M, Mckeown, P, Shimizu, W, Horie, M, Makita, N, Aiba, T, Ackerman, M, Schwartz, P, Probst, V, Bezzina, C, Behr, E, Unité de recherche de l'institut du thorax (ITX-lab), Dpt di Scienze Cliniche e di Comunità [Milano] (DISCCO), Università degli Studi di Milano = University of Milan (UNIMI)-Università degli Studi di Milano = University of Milan (UNIMI)-Istituti di Ricovero e Cura a Carattere Scientifico (IRCCS), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Helmholtz Zentrum München = German Research Center for Environmental Health, HAL-SU, Gestionnaire, Epidemiology and Data Science, APH - Methodology, Graduate School, ACS - Heart failure & arrhythmias, Amsterdam Reproduction & Development (AR&D), Human Genetics, Cardiology, ACS - Pulmonary hypertension & thrombosis, and ACS - Atherosclerosis & ischemic syndromes
Subjects: genetics, human, congenital, hereditary, and neonatal diseases and abnormalities, Scn5a gene, phenotype, BIO/18 - GENETICA, 030204 cardiovascular system & hematology, risk score, 03 medical and health sciences, 0302 clinical medicine, Brugada Syndrome, Genetics, Human, Penetrance, Phenotype, Risk Score, Medicine, genetics, Brugada syndrome, 030212 general & internal medicine, human, cardiovascular diseases, Genetic risk, penetrance, Genetics, Framingham Risk Score, [SDV.MHEP] Life Sciences [q-bio]/Human health and pathology, business.industry, fungi, General Medicine, Original Articles, MED/11 - MALATTIE DELL'APPARATO CARDIOVASCOLARE, medicine.disease, Human genetics, 3. Good health, Brugada ECG Pattern, ComputingMethodologies_DOCUMENTANDTEXTPROCESSING, cardiovascular system, business, [SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
Abstract: Supplemental Digital Content is available in the text., Background: Brugada syndrome (BrS) is characterized by the type 1 Brugada ECG pattern. Pathogenic rare variants in SCN5A (mutations) are identified in 20% of BrS families in whom incomplete penetrance and genotype-negative phenotype-positive individuals are observed. E1784K-SCN5A is the most common SCN5A mutation identified. We determined the association of a BrS genetic risk score (BrS-GRS) and SCN5A mutation type on BrS phenotype in BrS families with SCN5A mutations. Methods: Subjects with a spontaneous type 1 pattern or positive/negative drug challenge from cohorts harboring SCN5A mutations were recruited from 16 centers (n=312). Single nucleotide polymorphisms previously associated with BrS at genome-wide significance were studied in both cohorts: rs11708996, rs10428132, and rs9388451. An additive linear genetic model for the BrS-GRS was assumed (6 single nucleotide polymorphism risk alleles). Results: In the total population (n=312), BrS-GRS ≥4 risk alleles yielded an odds ratio of 4.15 for BrS phenotype ([95% CI, 1.45–11.85]; P=0.0078). Among SCN5A-positive individuals (n=258), BrS-GRS ≥4 risk alleles yielded an odds ratio of 2.35 ([95% CI, 0.89–6.22]; P=0.0846). In SCN5A-negative relatives (n=54), BrS-GRS ≥4 alleles yielded an odds ratio of 22.29 ([95% CI, 1.84–269.30]; P=0.0146). Among E1784K-SCN5A positive family members (n=79), hosting ≥4 risk alleles gave an odds ratio=5.12 ([95% CI, 1.93–13.62]; P=0.0011). Conclusions: Common genetic variation is associated with variable expressivity of BrS phenotype in SCN5A families, explaining in part incomplete penetrance and genotype-negative phenotype-positive individuals. SCN5A mutation genotype and a BrS-GRS associate with BrS phenotype, but the strength of association varies according to presence of a SCN5A mutation and severity of loss of function.
Published: 2020
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12. Transethnic Genome-Wide Association Study Provides Insights in the Genetic Architecture and Heritability of Long QT Syndrome

Author: Yvonne M. Hoedemaekers, M. Ben Shoemaker, Pascale Guicheney, Antoine Leenhardt, Andrea Mazzanti, Minoru Horie, Jan H. Veldink, Isabelle Denjoy, Yu Kucho, Chiea Chuen Khor, Tomas Robyns, Carlo Napolitano, Peter Weeke, J. Martijn Bos, David J. Tester, Hanno L. Tan, Annika Rydberg, Patrick T. Ellinor, Pilar Galan, Taisuke Ishikawa, Seiko Ohno, Peter J. Schwartz, Masao Yoshinaga, Thomas Werge, Marta Ribasés, Bart Loeys, Jean-Jacques Schott, Jacob Tfelt-Hansen, Ulla-Britt Diamant, Marko Ernsting, Georgia Sarquella-Brugada, Yuka Mizusawa, Michael Christiansen, Pyotr G. Platonov, Annika Winbo, Thomas Meitinger, Keiko Shimamoto, Cristina Barlassina, Pieter G. Postema, Takeru Makiyama, Maarten P. van den Berg, Yanushi D. Wijeyeratne, Wataru Shimizu, Charles Antzelevitch, Christopher Newton-Cheh, Martina Müller-Nurasyid, Dan M. Roden, Vincent Probst, Takeshi Aiba, Lia Crotti, Daniele Cusi, Britt M. Beckmann, Johan Saenen, Peter Lichtner, Oscar Campuzano, Tin Aung, Nynke Hofman, Morten S. Olesen, Matteo Pedrazzini, Elijah R. Behr, Karen E. Morrison, Najim Lahrouchi, Katja E. Odening, Andrew D. Krahn, Kari L. Turkowski, J. Peter van Tintelen, Steven A. Lubitz, Federica Dagradi, Josep Brugada, Julien Barc, Birgit Stallmeyer, Stefan Kääb, Sven Zumhagen, Jonathan R. Skinner, Michael W.T. Tanck, Christopher Shaw, Brianna Davies, Eric Schulze-Bahr, Mineo Ozaki, Roddy Walsh, Antoine Andorin, Leonard H. van den Berg, Silvia G. Priori, Johannes Steinfurt, Jean-Baptiste Gourraud, Eline A. Nannenberg, Mark Lathrop, Rafik Tadros, Ramon Brugada, Leander Beekman, Peter M. Andersen, Ryan Pfeiffer, Boris Rudic, Reza Jabbari, Kanae Hasegawa, Jeroen Breckpot, Naomasa Makita, Michael J. Ackerman, Arthur A.M. Wilde, Hideki Itoh, Martin Borggrefe, Elena Arbelo, Connie R. Bezzina, Pamela J. Shaw, Ammar Al-Chalabi, Markus Munter, Cardiology, Graduate School, ACS - Heart failure & arrhythmias, ACS - Amsterdam Cardiovascular Sciences, Human Genetics, Epidemiology and Data Science, APH - Methodology, ACS - Atherosclerosis & ischemic syndromes, Heart Center, Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences. Amsterdam University Medical Center, University of Amsterdam, European Reference Network for Rare, Low Prevalence, and Complex Diseases of the Heart (ERN GUARD-Heart), Institut de Cardiologie de Montreal, Université de Montréal (UdeM), Istituto Auxologico Italiano, Shiga University of Medical Science, University of Fukui [Bunkyo], Equipe 3: EREN- Equipe de Recherche en Epidémiologie Nutritionnelle (CRESS - U1153), Université Sorbonne Paris Nord-Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Institute of cardiometabolism and nutrition (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), CIC - CHU Bichat, Institut National de la Santé et de la Recherche Médicale (INSERM), Lahrouchi, N, Tadros, R, Crotti, L, Mizusawa, Y, Postema, P, Beekman, L, Walsh, R, Hasegawa, K, Barc, J, Ernsting, M, Turkowski, K, Mazzanti, A, Beckmann, B, Shimamoto, K, Diamant, U, Wijeyeratne, Y, Kucho, Y, Robyns, T, Ishikawa, T, Arbelo, E, Christiansen, M, Winbo, A, Jabbari, R, Lubitz, S, Steinfurt, J, Rudic, B, Loeys, B, Shoemaker, M, Weeke, P, Pfeiffer, R, Davies, B, Andorin, A, Hofman, N, Dagradi, F, Pedrazzini, M, Tester, D, Bos, J, Sarquella-Brugada, G, Campuzano, Ó, Platonov, P, Stallmeyer, B, Zumhagen, S, Nannenberg, E, Veldink, J, van den Berg, L, Al-Chalabi, A, Shaw, C, Shaw, P, Morrison, K, Andersen, P, Müller-Nurasyid, M, Cusi, D, Barlassina, C, Galan, P, Lathrop, M, Munter, M, Werge, T, Ribasés, M, Aung, T, Khor, C, Ozaki, M, Lichtner, P, Meitinger, T, van Tintelen, J, Hoedemaekers, Y, Denjoy, I, Leenhardt, A, Napolitano, C, Shimizu, W, Schott, J, Gourraud, J, Makiyama, T, Ohno, S, Itoh, H, Krahn, A, Antzelevitch, C, Roden, D, Saenen, J, Borggrefe, M, Odening, K, Ellinor, P, Tfelt-Hansen, J, Skinner, J, van den Berg, M, Olesen, M, Brugada, J, Brugada, R, Makita, N, Breckpot, J, Yoshinaga, M, Behr, E, Rydberg, A, Aiba, T, Kääb, S, Priori, S, Guicheney, P, Tan, H, Newton-Cheh, C, Ackerman, M, Schwartz, P, Schulze-Bahr, E, Probst, V, Horie, M, Wilde, A, Tanck, M, Bezzina, C, and Cardiovascular Centre (CVC)
Subjects: Multifactorial Inheritance, [SDV]Life Sciences [q-bio], Genome-wide association study, 030204 cardiovascular system & hematology, Severity of Illness Index, Sudden cardiac death, Electrocardiography, 0302 clinical medicine, inheritance pattern, Medicine, Cardiac and Cardiovascular Systems, Age of Onset, Genetics, 0303 health sciences, Kardiologi, Genetic disorder, genome-wide association study, Prognosis, 3. Good health, Phenotype, Medical genetics, Cardiology and Cardiovascular Medicine, Adult, medicine.medical_specialty, congenital, hereditary, and neonatal diseases and abnormalities, Adolescent, Genotype, Long QT syndrome, 610 Medicine & health, BIO/18 - GENETICA, QT interval, Polymorphism, Single Nucleotide, 03 medical and health sciences, Young Adult, Physiology (medical), long QT syndrome, Humans, Genetic Predisposition to Disease, cardiovascular diseases, Alleles, Genetic Association Studies, MED/01 - STATISTICA MEDICA, 030304 developmental biology, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], business.industry, inheritance patterns, MED/11 - MALATTIE DELL'APPARATO CARDIOVASCOLARE, Heritability, medicine.disease, Genetic architecture, Genome-wide Association Study, Inheritance Patterns, Long Qt Syndrome, Case-Control Studies, Human medicine, business
Abstract: Background: Long QT syndrome (LQTS) is a rare genetic disorder and a major preventable cause of sudden cardiac death in the young. A causal rare genetic variant with large effect size is identified in up to 80% of probands (genotype positive) and cascade family screening shows incomplete penetrance of genetic variants. Furthermore, a proportion of cases meeting diagnostic criteria for LQTS remain genetically elusive despite genetic testing of established genes (genotype negative). These observations raise the possibility that common genetic variants with small effect size contribute to the clinical picture of LQTS. This study aimed to characterize and quantify the contribution of common genetic variation to LQTS disease susceptibility. Methods: We conducted genome-wide association studies followed by transethnic meta-analysis in 1656 unrelated patients with LQTS of European or Japanese ancestry and 9890 controls to identify susceptibility single nucleotide polymorphisms. We estimated the common variant heritability of LQTS and tested the genetic correlation between LQTS susceptibility and other cardiac traits. Furthermore, we tested the aggregate effect of the 68 single nucleotide polymorphisms previously associated with the QT-interval in the general population using a polygenic risk score. Results: Genome-wide association analysis identified 3 loci associated with LQTS at genome-wide statistical significance ( P −8 ) near NOS1AP , KCNQ1 , and KLF12 , and 1 missense variant in KCNE1 (p.Asp85Asn) at the suggestive threshold ( P −6 ). Heritability analyses showed that ≈15% of variance in overall LQTS susceptibility was attributable to common genetic variation ( h2SNP 0.148; standard error 0.019). LQTS susceptibility showed a strong genome-wide genetic correlation with the QT-interval in the general population (r g =0.40; P =3.2×10 −3 ). The polygenic risk score comprising common variants previously associated with the QT-interval in the general population was greater in LQTS cases compared with controls ( P P Conclusions: This work establishes an important role for common genetic variation in susceptibility to LQTS. We demonstrate overlap between genetic control of the QT-interval in the general population and genetic factors contributing to LQTS susceptibility. Using polygenic risk score analyses aggregating common genetic variants that modulate the QT-interval in the general population, we provide evidence for a polygenic architecture in genotype negative LQTS.
Published: 2020
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13. Shared genetic pathways contribute to risk of hypertrophic and dilated cardiomyopathies with opposite directions of effect

Author: Antonio de Marvao, Roddy Walsh, Jean-Claude Tardif, R. Thomas Lumbers, Eric Villard, Rafik Tadros, Peter Lichtner, Catherine Francis, Julie Amyot, Michelle Michels, Hugh Watkins, Julia Cadrin-Tourigny, Najim Lahrouchi, Rudolf A. de Boer, Patrick Garceau, Karin J. H. Verweij, Paul M. Matthews, Paul Elliott, S. Matthijs Boekholdt, Folkert W. Asselbergs, Declan P. O'Regan, Benjamin Meder, Joost A. Offerhaus, Nicola Whiffin, Jacco C. Karper, Jason D. Roberts, Marie-Pierre Dubé, Hideaki Suzuki, James S. Ware, Yigal M. Pinto, Thomas Meitinger, Guillaume Lettre, Hannah G. van Velzen, Arthur A.M. Wilde, Marjon van Slegtenhorst, Francesco Mazzarotto, Wouter P. te Rijdt, Paul J.R. Barton, Sanjay K Prasad, A. John Baksi, Michael W.T. Tanck, Mario Talajic, Roy Huurman, J. Peter van Tintelen, Connie R. Bezzina, Antonis Pantazis, Robert A. Hegele, Jentien M Vermeulen, Rachel Buchan, Imke Christiaans, Jan H. Veldink, Edgar T. Hoorntje, Elham Kayvanpour, Pascale Richard, Geneviève Giraldeau, Flavie Ader, Andrew Thain, Philippe L. L’Allier, Xiao Xu, Leander Beekman, David McCarty, Alexa M.C. Vermeer, Geraldine Sloane, Wenjia Bai, Andrew R. Harper, Jolanda van der Velden, Stuart A. Cook, Ken Kelu Bisabu, Philippe Charron, Deborah Schneider-Luftman, Human Genetics, ACS - Heart failure & arrhythmias, Cardiology, Adult Psychiatry, APH - Mental Health, ANS - Complex Trait Genetics, ANS - Compulsivity, Impulsivity & Attention, ANS - Mood, Anxiety, Psychosis, Stress & Sleep, ACS - Amsterdam Cardiovascular Sciences, Epidemiology and Data Science, APH - Methodology, ACS - Atherosclerosis & ischemic syndromes, Human genetics, Physiology, Cardiovascular Centre (CVC), Clinical Genetics, Wellcome Trust, Department of Health, British Heart Foundation, Engineering & Physical Science Research Council (EPSRC), UK DRI Ltd, The Academy of Medical Sciences, and Imperial College Healthcare NHS Trust- BRC Funding
Subjects: Linkage disequilibrium, Cardiomyopathy, Dilated/genetics, Left, Cardiomyopathy, Genome-wide association study, Kaplan-Meier Estimate, VARIANTS, Ventricular Function, Left, Linkage Disequilibrium, 0302 clinical medicine, Gene Frequency, Dilated, Ventricular Function, 11 Medical and Health Sciences, Cardiomyopathy, Hypertrophic/genetics, Genetics & Heredity, 0303 health sciences, HERITABILITY, Single Nucleotide, MENDELIAN RANDOMIZATION, Cardiology, cardiovascular system, HEART, Life Sciences & Biomedicine, Ventricular Function, Left/genetics, Cardiomyopathy, Dilated, medicine.medical_specialty, Heart Ventricles, Quantitative Trait Loci, Biology, Quantitative trait locus, Sudden death, Polymorphism, Single Nucleotide, Article, Heart Ventricles/physiopathology, 03 medical and health sciences, Internal medicine, Mendelian randomization, Genetics, medicine, Humans, Genetic Predisposition to Disease, cardiovascular diseases, GENOME-WIDE ASSOCIATION, Polymorphism, 030304 developmental biology, Genetic association, Science & Technology, Hypertrophic/genetics, Left/genetics, Case-control study, CONTRACTILITY, 06 Biological Sciences, Cardiomyopathy, Hypertrophic, medicine.disease, Hypertrophic, Dilated/genetics, Case-Control Studies, Genome-Wide Association Study, 030217 neurology & neurosurgery, Developmental Biology
Abstract: The heart muscle diseases hypertrophic (HCM) and dilated (DCM) cardiomyopathies are leading causes of sudden death and heart failure in young, otherwise healthy, individuals. We conducted genome-wide association studies and multi-trait analyses in HCM (1,733 cases), DCM (5,521 cases) and nine left ventricular (LV) traits (19,260 UK Biobank participants with structurally normal hearts). We identified 16 loci associated with HCM, 13 with DCM and 23 with LV traits. We show strong genetic correlations between LV traits and cardiomyopathies, with opposing effects in HCM and DCM. Two-sample Mendelian randomization supports a causal association linking increased LV contractility with HCM risk. A polygenic risk score explains a significant portion of phenotypic variability in carriers of HCM-causing rare variants. Our findings thus provide evidence that polygenic risk score may account for variability in Mendelian diseases. More broadly, we provide insights into how genetic pathways may lead to distinct disorders through opposing genetic effects.
Published: 2021
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14. Genome-wide association study identifies 18 new susceptibility variants loci associated with Brugada Syndrome

Author: J Barc, R Trados, C Glinge, F Simonet, D Chiang, M Jouni, S Jurgens, B.R.S The Brugada Syndrome Genetic Consortium, M Tanck, C Dina, V Probst, A Wilde, R Redon, J.J Schott, and C Bezzina
Subjects: Genetics, Mutation, Genetic inheritance, Scn5a gene, business.industry, Genome-wide association study, medicine.disease, medicine.disease_cause, Genome, medicine, Epigenetics, Cardiology and Cardiovascular Medicine, business, Gene, Brugada syndrome
Abstract: The Brugada Syndrome (BrS) is characterized by ST-segment elevation in the right precordial leads and is associated with an increased risk of sudden cardiac death. The disorder was initially described as a monogenic primary cardiac electrical disease. However, mutations in SCN5A, encoding the cardiac sodium channel (NaV1.5), which is the major gene associated with the disorder are found in only around 20% of cases and are associated with low penetrance. Furthermore many cases did not display familial aggregation. Based on a previous GWAS conducted on 312 BrS patients and the discovery of the unexpected strong effect of 3 common variants, we proposed that the BrS may comprise a more complex inheritance model. We conducted a genome-wide association study on 2820 individuals with BrS and 10001 ancestry-matched controls to uncover additional genetic loci that modulate susceptibility to BrS, to characterize further the BrS genetic architecture and to uncover new molecular mechanisms. We identified 21 susceptibility variants that passed the genome-wide statistical significance threshold (P We identified 18 new susceptibility variants associated with BrS and uncovered a new pathophysiological molecular mechanism underlying BrS susceptibility. We provided further support for a complex genetic architecture underlying susceptibility for the disorder. Funding Acknowledgement Type of funding source: Public Institution(s). Main funding source(s): H2020 - Marie Sklodowska Curie IF grant, Rising star grant from the Pays de la Loire regional council
Published: 2020
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15. Dissection of a quantitative trait locus for PR interval duration identifies Tnni3k as a novel modulator of cardiac conduction.

Author: Elisabeth M Lodder, Brendon P Scicluna, Annalisa Milano, Albert Y Sun, Hao Tang, Carol Ann Remme, Perry D Moerland, Michael W T Tanck, Geoffrey S Pitt, Douglas A Marchuk, and Connie R Bezzina
Subjects: Genetics, QH426-470
Abstract: Atrio-ventricular conduction disease is a common feature in Mendelian rhythm disorders associated with sudden cardiac death and is characterized by prolongation of the PR interval on the surface electrocardiogram (ECG). Prolongation of the PR interval is also a strong predictor of atrial fibrillation, the most prevalent sustained cardiac arrhythmia. Despite the significant genetic component in PR duration variability, the genes regulating PR interval duration remain largely elusive. We here aimed to dissect the quantitative trait locus (QTL) for PR interval duration that we previously mapped in murine F2 progeny of a sensitized 129P2 and FVBN/J cross. To determine the underlying gene responsible for this QTL, genome-wide transcriptional profiling was carried out on myocardial tissue from 109 F2 mice. Expression QTLs (eQTLs) were mapped and the PR interval QTL was inspected for the co-incidence of eQTLs. We further determined the correlation of each of these transcripts to the PR interval. Tnni3k was the only eQTL, mapping to the PR-QTL, with an established abundant cardiac-specific expression pattern and a significant correlation to PR interval duration. Genotype inspection in various inbred mouse strains revealed the presence of at least three independent haplotypes at the Tnni3k locus. Measurement of PR interval duration and Tnni3k mRNA expression levels in six inbred lines identified a positive correlation between the level of Tnni3k mRNA and PR interval duration. Furthermore, in DBA/2J mice overexpressing hTNNI3K, and in DBA.AKR.hrtfm2 congenic mice, which harbor the AKR/J "high-Tnni3k expression" haplotype in the DBA/2J genetic background, PR interval duration was prolonged as compared to DBA/2J wild-type mice ("low-Tnni3k expression" haplotype). Our data provide the first evidence for a role of Tnni3k in controlling the electrocardiographic PR interval indicating a function of Tnni3k in atrio-ventricular conduction.
Published: 2012
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16. A comprehensive evaluation of the genetic architecture of sudden cardiac arrest

Author: Barbara McKnight, Martina Müller-Nurasyid, Raha Pazoki, Michael W.T. Tanck, Thomas Engstrøm, Arthur A.M. Wilde, Man Li, Martin VanDenburgh, Marieke T. Blom, Reza Jabbari, Thomas Meitinger, Philippe Goyette, Anna Moes, Rebecca N. Mitchell, Christine M. Albert, Aravinda Chakravarti, Dan E. Arking, Jean-Claude Tardif, Rozenn N. Lemaitre, Foram N. Ashar, Pui-Yan Kwok, Frank D. Kolodgie, Jacob Tfelt-Hansen, Renu Virmani, Susan R. Heckbert, Angel C.Y. Mak, David S. Siscovick, Vinicius Tragante, Xavier Jouven, Hanno L. Tan, John D. Rioux, Mark Eijgelsheim, Ronald J. Prineas, Nona Sotoodehnia, Xiaoqing Zhao, Stefan A. Escher, Heikki V. Huikuri, Bruce M. Psaty, Charlotte Glinge, Albert Hofman, Oscar H. Franco, Florence Dumas, Bruno H. Stricker, M. Juhani Junttila, Folkert W. Asselbergs, Josef Coresh, Christopher J. O'Donnell, Paul W. Franks, Shih-Jen Hwang, Veikko Salomaa, Jan-Håkan Jansson, Stefan Kääb, Christopher Newton-Cheh, Joseph J. Maleszewski, Paul I.W. de Bakker, Jennifer A. Brody, Aki S. Havulinna, André G. Uitterlinden, Georg Ehret, Jerome I. Rotter, Thomas Lumley, Connie R. Bezzina, Marc K. Halushka, Sara L. Pulit, Epidemiology, Internal Medicine, Ehret, Georg Benedikt, Cardiology, Epidemiology and Data Science, APH - Methodology, ACS - Heart failure & arrhythmias, and APH - Health Behaviors & Chronic Diseases
Subjects: Male, Genome-wide association study, Coronary Artery Disease, Cardiorespiratory Medicine and Haematology, Arrhythmias, 030204 cardiovascular system & hematology, VARIANTS, Cardiovascular, Bioinformatics, Body Mass Index, Sudden cardiac death, Coronary artery disease, 0302 clinical medicine, Risk Factors, 2.1 Biological and endogenous factors, Medicine, 030212 general & internal medicine, Family history, Aetiology, Cardiac/genetics/physiopathology, reproductive and urinary physiology, POPULATION, 0303 health sciences, education.field_of_study, Coronary Artery Disease/genetics, ATHEROSCLEROSIS-RISK, DEATH, hemic and immune systems, Mendelian Randomization Analysis, Single Nucleotide, 3. Good health, Death, Heart Disease, MENDELIAN RANDOMIZATION, Medical genetics, Female, FIBRILLATION, medicine.symptom, Cardiology and Cardiovascular Medicine, Cardiac, Cardiac/etiology, medicine.medical_specialty, Clinical Sciences, Population, Single-nucleotide polymorphism, 610 Medicine & health, Biology, Genetic correlation, Polymorphism, Single Nucleotide, Risk Assessment, Heart Conduction System/physiopathology, 03 medical and health sciences, Sex Factors, Sudden cardiac arrest, Clinical Research, Heart Conduction System, 360 Social problems & social services, RISK-FACTOR, Mendelian randomization, Genetics, Journal Article, Humans, INTERVAL, Polymorphism, Risk Assessment/methods, education, Heart Disease - Coronary Heart Disease, 030304 developmental biology, business.industry, Prevention, Human Genome, Arrhythmias, Cardiac, medicine.disease, Sudden, Genetic architecture, Good Health and Well Being, Death, Sudden, Cardiac, Cardiovascular System & Hematology, business
Abstract: BackgroundSudden cardiac arrest (SCA) accounts for 10% of adult mortality in Western populations. While several risk factors are observationally associated with SCA, the genetic architecture of SCA in the general population remains unknown. Furthermore, understanding which risk factors are causal may help target prevention strategies.MethodsWe carried out a large genome-wide association study (GWAS) for SCA (n=3,939 cases, 25,989 non-cases) to examine common variation genome-wide and in candidate arrhythmia genes. We also exploited Mendelian randomization methods using cross-trait multi-variant genetic risk score associations (GRSA) to assess causal relationships of 18 risk factors with SCA.ResultsNo variants were associated with SCA at genome-wide significance, nor were common variants in candidate arrhythmia genes associated with SCA at nominal significance. Using cross-trait GRSA, we established genetic correlation between SCA and (1) coronary artery disease (CAD) and traditional CAD risk factors (blood pressure, lipids, and diabetes), (2) height and BMI, and (3) electrical instability traits (QT and atrial fibrillation), suggesting etiologic roles for these traits in SCA risk.ConclusionsOur findings show that a comprehensive approach to the genetic architecture of SCA can shed light on the determinants of a complex life-threatening condition with multiple influencing factors in the general population. The results of this genetic analysis, both positive and negative findings, have implications for evaluating the genetic architecture of patients with a family history of SCA, and for efforts to prevent SCA in highrisk populations and the general community.
Published: 2018
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17. Subsequent Event Risk in Individuals With Established Coronary Heart Disease Design and Rationale of the GENIUS-CHD Consortium

Author: Patel, Riyaz, Tragante, Vinicius, Schmidt, Amand F., McCubrey, Raymond O., Holmes, Michael V., Howe, Laurence J., Direk, Kenan, Åkerblom, Axel, Leander, Karin, Virani, Salim S., Kaminski, Karol A., Muehlschlegel, Jochen D., Allayee, Hooman, Almgren, Peter, Alver, Maris, Baranova, Ekaterina V., Behlouli, Hassan, Boeckx, Bram, Braund, Peter S., Breitling, Lutz P., Delgado, Graciela, Duarte, Nubia E., Dubé, Marie-Pierre, Dufresne, Line, Eriksson, Niclas, Foco, Luisa, Scholz, Markus, Gijsberts, Crystel M., Glinge, Charlotte, Gong, Yan, Hartiala, Jaana, Heydarpour, Mahyar, Hubacek, Jaroslav A., Kleber, Marcus, Kofink, Daniel, Kotti, Salma, Kuukasjärvi, Pekka, Lee, Vei-Vei, Leiherer, Andreas, Lenzini, Petra A., Levin, Daniel, Lyytikäinen, Leo-Pekka, Martinelli, Nicola, Mons, Ute, Nelson, Christopher P., Nikus, Kjell, Pilbrow, Anna P., Ploski, Rafal, Sun, Yan V., Tanck, Michael W.T., Tang, W H Wilson, Trompet, Stella, van der Laan, Sander W., Van Setten, Jessica, Vilmundarson, Ragnar O., Viviani Anselmi, Chiara, Vlachopoulou, Efthymia, Al Ali, Lawien, Boerwinkle, Eric, Briguori, Carlo, Carlquist, John F., Carruthers, Kathryn F., Casu, Gavino, Deanfield, John, Deloukas, Panos, Dudbridge, Frank, Engström, Thomas, Fitzpatrick, Natalie, Fox, Kim, Gigante, Bruna, James, Stefan, Lokki, Marja-Liisa, Lotufo, Paulo A., Marziliano, Nicola, Mordi, Ify R., Muhlestein, Joseph B., Newton-Cheh, Christopher, Pitha, Jan, Saely, Christoph H., Samman-Tahhan, Ayman, Sandesara, Pratik B., Teren, Andrej, Timmis, Adam, Van de Werf, Frans, Wauters, Els, Wilde, Arthur A.M., Ford, Ian, Stott, David J., Algra, Ale, Andreassi, Maria G., Ardissino, Diego, Arsenault, Benoit J., Ballantyne, Christie M., Bergmeijer, Thomas O., Bezzina, Connie R., Body, Simon C., Boersma, Eric H., Bogaty, Peter, Bots, Michiel, Brenner, Hermann, Brugts, Jasper J., Burkhardt, Ralph, Carpeggiani, Clara, Condorelli, Gianluigi, Cooper-DeHoff, Rhonda M., Cresci, Sharon, Danchin, Nicolas, de Faire, Ulf, Doughty, Robert N., Drexel, Heinz, Engert, James C., Fox, Keith A.A., Girelli, Domenico, Grobbee, Diederick E., Hagström, Emil, Hazen, Stanley L., Held, Claes, Hemingway, Harry, Hoefer, Imo E., Hovingh, G. Kees, Jabbari, Reza, Johnson, Julie A., Jukema, J. Wouter, Kaczor, Marcin P., Kähönen, Mika, Kettner, Jiri, Kiliszek, Marek, Klungel, Olaf H., Lagerqvist, Bo, Lambrechts, Diether, Laurikka, Jari O., Lehtimäki, Terho, Lindholm, Daniel, Mahmoodi, B.K., Maitland-van der Zee, Anke H., McPherson, Ruth, Melander, Olle, Metspalu, Andres, Niemcunowicz-Janica, Anna, Olivieri, Oliviero, Opolski, Grzegorz, Palmer, Colin N., Pasterkamp, Gerard, Pepine, Carl J., Pereira, Alexandre C., Pilote, Louise, Quyyumi, Arshed A., Richards, A. Mark, Sanak, Marek, Siegbahn, Agneta, Simon, Tabassome, Sinisalo, Juha, Smith, J. Gustav, Spertus, John A., Stender, Steen, Stewart, Alexandre F.R., Szczeklik, Wojciech, Szpakowicz, Anna, Tardif, Jean-Claude, Ten Berg, Jurriën M., Tfelt-Hansen, Jacob, Thanassoulis, George, Thiery, Joachim, Torp-Pedersen, Christian, van der Graaf, Yolanda, Visseren, Frank L.J., Waltenberger, Johannes, Weeke, Peter E., Van der Harst, Pim, Lang, Chim C., Sattar, Naveed, Cameron, Vicky A., Anderson, Jeffrey L., Brophy, James M., Paré, Guillaume, Horne, Benjamin D., März, Winfried, Wallentin, Lars, Samani, Nilesh J., Hingorani, Aroon D., Asselbergs, Folkert W., and Cardiovascular Centre (CVC)
Subjects: Adult, Male, Cardiac & Cardiovascular Systems, CARDIOVASCULAR MORTALITY, Coronary Disease, BIOBANK, Article, Sex Factors, Risk Factors, Journal Article, Humans, ARTERY-DISEASE, Cardiac and Cardiovascular Systems, genetics, Aged, Proportional Hazards Models, Genetics & Heredity, Kardiologi, Science & Technology, Smoking, Age Factors, Middle Aged, BODY-MASS INDEX, myocardial infarction, MYOCARDIAL-INFARCTION, PUBLIC-HEALTH, Cardiovascular System & Cardiology, Female, prognosis, Life Sciences & Biomedicine, coronary artery disease, secondary prevention
Abstract: BACKGROUND: The Genetics of Subsequent Coronary Heart Disease (GENIUS-CHD) consortium was established to facilitate discovery and validation of genetic variants and biomarkers for risk of subsequent CHD events, in individuals with established CHD. METHODS: The consortium currently includes 57 studies from 18 countries, recruiting 185 614 participants with either acute coronary syndrome, stable CHD, or a mixture of both at baseline. All studies collected biological samples and followed-up study participants prospectively for subsequent events. RESULTS: Enrollment into the individual studies took place between 1985 to present day with a duration of follow-up ranging from 9 months to 15 years. Within each study, participants with CHD are predominantly of self-reported European descent (38%-100%), mostly male (44%-91%) with mean ages at recruitment ranging from 40 to 75 years. Initial feasibility analyses, using a federated analysis approach, yielded expected associations between age (hazard ratio, 1.15; 95% CI, 1.14-1.16) per 5-year increase, male sex (hazard ratio, 1.17; 95% CI, 1.13-1.21) and smoking (hazard ratio, 1.43; 95% CI, 1.35-1.51) with risk of subsequent CHD death or myocardial infarction and differing associations with other individual and composite cardiovascular endpoints. CONCLUSIONS: GENIUS-CHD is a global collaboration seeking to elucidate genetic and nongenetic determinants of subsequent event risk in individuals with established CHD, to improve residual risk prediction and identify novel drug targets for secondary prevention. Initial analyses demonstrate the feasibility and reliability of a federated analysis approach. The consortium now plans to initiate and test novel hypotheses as well as supporting replication and validation analyses for other investigators. ispartof: CIRCULATION-GENOMIC AND PRECISION MEDICINE vol:12 issue:4 ispartof: location:United States status: published
Published: 2019
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18. Heritability in genetic heart disease: The role of genetic background

Author: Jasper J. van der Smagt, Juan R. Gimeno, Maarten P. van den Berg, Arthur A.M. Wilde, Heikki Swan, Alexa M.C. Vermeer, Joeri A. Jansweijer, Philippe Charron, Yigal M. Pinto, Iacopo Olivotto, J. Martijn Bos, Karin Y. van Spaendonck-Zwarts, Arthur J. Moss, S. G. Priori, Michael J. Ackerman, Imke Christiaans, Annika Rydberg, J. Peter van Tintelen, Jacob Tfelt-Hansen, Michael W.T. Tanck, ACS - Heart failure & arrhythmias, Cardiovascular Centre (CVC), HUS Heart and Lung Center, Kardiologian yksikkö, Department of Medicine, Graduate School, Epidemiology and Data Science, APH - Methodology, Human Genetics, and Cardiology
Subjects: medicine.medical_specialty, Heart disease, Cardiomyopathy, MONOZYGOTIC TWINS, Disease, Twin Study, 030204 cardiovascular system & hematology, Biology, 03 medical and health sciences, 0302 clinical medicine, Channelopathy, IDENTICAL-TWINS, Idiopathic dilated cardiomyopathy, medicine, Genetics, Journal Article, 030304 developmental biology, Medicinsk genetik, 0303 health sciences, HYPERTROPHIC CARDIOMYOPATHY, QT INTERVAL, Hypertrophic cardiomyopathy, Correction, LEFT-VENTRICULAR NONCOMPACTION, Heritability, medicine.disease, Twin study, IDIOPATHIC DILATED CARDIOMYOPATHY, 3121 General medicine, internal medicine and other clinical medicine, ONSET, Medical genetics, Cardiology and Cardiovascular Medicine, Medical Genetics
Abstract: BackgroundMutations in genes encoding ion channels or sarcomeric proteins are an important cause of hereditary cardiac disease. However, the severity of the resultant disease varies considerably even among those with an identical mutation. Such clinical variation is often thought to be explained largely by differences in genetic background or ‘modifier genes’. We aimed to test the prediction that identical genetic backgrounds result in largely similar clinical expression of a cardiac disease causing mutation, by studying the clinical expression of mutations causing cardiac disease in monozygotic twins.MethodsWe compared first available clinical information on 46 monozygotic twin pairs and 59 control pairs that had either a hereditary cardiomyopathy or channelopathy.ResultsDespite limited power of this study, we found significant heritability for corrected QT interval (QTc) in long QT syndrome (LQTS). We could not detect significant heritability for structural traits, but found a significant environmental effect on thickness of the interventricular septum in hypertrophic cardiomyopathy.ConclusionsOur study confirms previously found robust heritability for electrical traits like QTc in LQTS, and adds information on low or lacking heritability for structural traits in heritable cardiomyopathies. This may steer the search for genetic modifiers in heritable cardiac disease.
Published: 2019
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19. Extensive Ethnic Variation and Linkage Disequilibrium at the FCGR2/3 Locus: Different Genetic Associations Revealed in Kawasaki Disease

Author: Sietse Q. Nagelkerke, Carline E. Tacke, Willemijn B. Breunis, Michael W. T. Tanck, Judy Geissler, Eileen Png, Long T. Hoang, Joris van der Heijden, Ahmad N. M. Naim, Rae S. M. Yeung, Michael L. Levin, Victoria J. Wright, David P. Burgner, Anne-Louise Ponsonby, Justine A. Ellis, Rolando Cimaz, Chisato Shimizu, Jane C. Burns, Karin Fijnvandraat, C. Ellen van der Schoot, Timo K. van den Berg, Martin de Boer, Sonia Davila, Martin L. Hibberd, Taco W. Kuijpers, The International Kawasaki Disease Genetics Consortium, Nagib Dahdah, Isabelle Kone-Paut, Molecular cell biology and Immunology, Pediatric surgery, APH - Aging & Later Life, General Paediatrics, Paediatric Oncology, Epidemiology and Data Science, APH - Methodology, Paediatric Haematology, ARD - Amsterdam Reproduction and Development, Landsteiner Laboratory, General Internal Medicine, and Paediatric Infectious Diseases / Rheumatology / Immunology
Subjects: lcsh:Immunologic diseases. Allergy, 0301 basic medicine, Linkage disequilibrium, GAMMA RECEPTOR POLYMORPHISMS, MONOCLONAL-ANTIBODY, FCGR3A, Immunology, IDENTIFIES 3, Single-nucleotide polymorphism, Locus (genetics), Genome-wide association study, SUSCEPTIBILITY, Biology, IGG RECEPTORS, 03 medical and health sciences, 0302 clinical medicine, Immunology and Allergy, SYSTEMIC-LUPUS-ERYTHEMATOSUS, GENOME-WIDE ASSOCIATION, Allele, Allele frequency, COPY NUMBER VARIATION, Genetics, Science & Technology, Haplotype, Fc-gamma receptor, immunogenetics, Minor allele frequency, 030104 developmental biology, FCGR polymorphism, Kawasaki disease (KD), RISK-FACTORS, International Kawasaki Disease Genetics Consortium, lcsh:RC581-607, Life Sciences & Biomedicine, linkage disequilibrium, 030215 immunology
Abstract: The human Fc-gamma receptors (FcγRs) link adaptive and innate immunity by binding immunoglobulin G (IgG). All human low-affinity FcγRs are encoded by the FCGR2/3 locus containing functional single nucleotide polymorphisms (SNPs) and gene copy number variants. This locus is notoriously difficult to genotype and high-throughput methods commonly used focus on only a few SNPs. We performed multiplex ligation-dependent probe amplification for all relevant genetic variations at the FCGR2/3 locus in >4,000 individuals to define linkage disequilibrium (LD) and allele frequencies in different populations. Strong LD and extensive ethnic variation in allele frequencies was found across the locus. LD was strongest for the FCGR2C-ORF haplotype (rs759550223+rs76277413), which leads to expression of FcγRIIc. In Europeans, the FCGR2C-ORF haplotype showed strong LD with, among others, rs201218628 (FCGR2A-Q27W, r 2 = 0.63). LD between these two variants was weaker (r 2 = 0.17) in Africans, whereas the FCGR2C-ORF haplotype was nearly absent in Asians (minor allele frequency 2 = 0.08) in Europeans. We evaluated the importance of ethnic variation and LD in Kawasaki Disease (KD), an acute vasculitis in children with increased incidence in Asians. An association of rs1801274 with KD was previously shown in ethnically diverse genome-wide association studies. Now, we show in 1,028 European KD patients that the FCGR2C-ORF haplotype, although nearly absent in Asians, was more strongly associated with susceptibility to KD than rs1801274 in Europeans. Our data illustrate the importance of interpreting findings of association studies concerning the FCGR2/3 locus with knowledge of LD and ethnic variation.
Published: 2019
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20. Associations between single nucleotide polymorphisms and erythrocyte parameters in humans:A systematic literature review

Author: C. Ellen van der Schoot, Katja van den Hurk, Joost G. Daams, Elisabeth M.J. Huis In 'T Veld, Tiffany C. Timmer, Barbera Veldhuisen, Wim L.A.M. de Kort, and Michael W.T. Tanck
Subjects: 0301 basic medicine, Erythrocyte Indices, Candidate gene, Erythrocytes, Health, Toxicology and Mutagenesis, Population, HEMOCHROMATOSIS, HFE MUTATIONS, Physiology, Single-nucleotide polymorphism, Genome-wide association study, Biology, Hematocrit, Polymorphism, Single Nucleotide, 03 medical and health sciences, Hemoglobins, 0302 clinical medicine, AGE, Genetics, medicine, Animals, Humans, Hemoglobin, GENOME-WIDE ASSOCIATION, education, Genetic association, education.field_of_study, medicine.diagnostic_test, RED-CELL INDICES, Red cell indices, respiratory system, GENE, IRON-DEFICIENCY, 030104 developmental biology, DIFFERENTIATION, HEMOGLOBIN LEVELS, 030220 oncology & carcinogenesis, WHOLE-BLOOD DONORS, Systematic review, DONATION, Red cell count, hormones, hormone substitutes, and hormone antagonists, Genome-Wide Association Study
Abstract: Individual variations in erythrocyte parameters are influenced by factors like sex, age, diet and season. Genetic variations have also been associated with erythrocyte parameters. The aim of this systematic review is to provide an overview of associations between single nucleotide polymorphisms (SNPs) and erythrocyte parameters in humans. A systematic review protocol was published at the international prospective register of systematic reviews (registration number CRD42016053052). Literature searches were conducted in Medline and Embase. Studies were included if: investigating a(n) causality/association/correlation; population-based; investigating a human population of Caucasian/mixed-ethnic descent; and written in English, Dutch or German. Study quality was assessed using the quality of genetic association studies tool. In total, 4385 studies were screened on title/abstract and 194 studies were screened on full text. Inclusion criteria were met by 13 candidate gene studies (n = 126–49,488) and eight genome-wide association studies (GWASes, n = 1664–116,666). One moderate and six good quality GWAS(es) identified 1237 SNPs located in/near 241 genes. SNPs in/near ten genes were found to be associated with one or more erythrocyte parameter(s) by multiple GWASes, namely HIST1H2AC, MPST, SLC17A1 and SLC17A3 with mean cell hemoglobin (MCH), HIST1H1T and KCTD17 with MCH and mean cell volume (MCV), HBS1L and MYB with MCH, MCV and red cell count (RCC), HFE with MCH, MCV and hemoglobin, and TMPRSS6 with MCH, MCV, hemoglobin and mean cell hemoglobin concentration (MCHC). Four genes were found across multiple erythrocyte parameters by one study in each parameter. Fourteen SNPs were associated with one or more erythrocyte parameter(s) in multiple cohorts, namely rs129128, rs17342717, rs228129 and rs5756504 (MCH), rs4895441, rs7775698, rs9376092 and rs9494145 (MCH, MCV, RCC), rs6569992 (MCH, RCC), rs1800562 (hemoglobin, MCH, MCV), rs130624 and rs198846 (MCH, MCV), rs4820268 and rs855791 (MCH, MCV, MCHC). Further research on these fourteen genes in erythropoiesis is recommended, especially eight whose role in erythropoiesis is unclear.
Published: 2019
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21. A founder effect for p47phox Trp193Ter chronic granulomatous disease in Kavkazi Jews

Author: Mark Stoneking, Karl Skorecki, Shay Tzur, Karin van Leeuwen, Baruch Wolach, Ivane Nasidze, Ronit Gavrieli, Paula C.D. Dencher, Michael W.T. Tanck, Dirk Roos, Martin de Boer, Amsterdam Public Health, Epidemiology and Data Science, and Landsteiner Laboratory
Subjects: Male, Genotype, DNA Mutational Analysis, Population, Single-nucleotide polymorphism, Biology, Granulomatous Disease, Chronic, Compound heterozygosity, Chronic granulomatous disease, Gene Frequency, Gene Order, medicine, Humans, education, Molecular Biology, Allele frequency, Alleles, Genetics, education.field_of_study, Haplotype, NADPH Oxidases, Cell Biology, Hematology, medicine.disease, Founder Effect, Pedigree, Haplotypes, Genetic Loci, Jews, Mutation, Mutation (genetic algorithm), Molecular Medicine, Female, Microsatellite Repeats, Founder effect
Abstract: Chronic granulomatous disease (CGD) is a rare congenital immune deficiency caused by mutations in any of the five genes encoding NADPH oxidase subunits. One of these genes is NCF1, encoding the p47(phox) protein. A group of 39 patients, 14 of whom are of Kavkazi Jewish descent, was investigated for a founder effect for the mutation c.579G>A (p.Trp193Ter) in NCF1. We analyzed various genetic markers in the NCF1 region, including two single nucleotide polymorphisms (SNPs) in NCF1 and two short tandem repeats (STRs) located near NCF1. Most patients were homozygous for the c.579G>A mutation, but three patients were hemizygotes, with a deletion of NCF1 on the other allele, and three patients were compound heterozygotes with another mutation in NCF1. All Kavkazi Jewish patients had a c.295G_c.345T SNP combination in NCF1 and shared a common number of repeats in STR3. In addition, 90% of the Kavkazi Jewish patients shared a common number of repeats in STR1. This uniformity indicates that the c.579G>A mutation in NCF1 was introduced some 1200-2300 years ago in the Kavkazi Jewish population. Variation amongst the other investigated populations from the Middle East indicates that this mutation exists in these non-Kavkazi populations already for more than 5000 years.
Published: 2015
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22. Estimating effects of rare haplotypes on failure time using a penalized Cox proportional hazards regression model

Author: Tanck Michael WT, Jukema J Wouter, Zwinderman Aeilko H, and Souverein Olga W
Subjects: Genetics, QH426-470
Abstract: Abstract Background This paper describes a likelihood approach to model the relation between failure time and haplotypes in studies with unrelated individuals where haplotype phase is unknown, while dealing with the problem of unstable estimates due to rare haplotypes by considering a penalized log-likelihood. Results The Cox model presented here incorporates the uncertainty related to the unknown phase of multiple heterozygous individuals as weights. Estimation is performed with an EM algorithm. In the E-step the weights are estimated, and in the M-step the parameter estimates are estimated by maximizing the expectation of the joint log-likelihood, and the baseline hazard function and haplotype frequencies are calculated. These steps are iterated until the parameter estimates converge. Two penalty functions are considered, namely the ridge penalty and a difference penalty, which is based on the assumption that similar haplotypes show similar effects. Simulations were conducted to investigate properties of the method, and the association between IL10 haplotypes and risk of target vessel revascularization was investigated in 2653 patients from the GENDER study. Conclusion Results from simulations and real data show that the penalized log-likelihood approach produces valid results, indicating that this method is of interest when studying the association between rare haplotypes and failure time in studies of unrelated individuals.
Published: 2008
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23. The Impact of Selection Bias on Estimation of Subsequent Event Risk

Author: Yi-Juan Hu, Amand F. Schmidt, Frank Dudbridge, Michael V. Holmes, James M. Brophy, Vinicius Tragante, Ziyi Li, Peizhou Liao, Arshed A. Quyyumi, Raymond O. McCubrey, Benjamin D. Horne, Aroon D. Hingorani, Folkert W. Asselbergs, Riyaz S. Patel, Qi Long, Axel Åkerblom, Ale Algra, Hooman Allayee, Peter Almgren, Jeffrey L. Anderson, Maria G. Andreassi, Chiara V. Anselmi, Diego Ardissino, Benoit J. Arsenault, Christie M. Ballantyne, Ekaterina V. Baranova, Hassan Behloui, Thomas O. Bergmeijer, Connie R. Bezzina, Eythor Bjornsson, Simon C. Body, Bram Boeckx, Eric (H.) Boersma, Eric Boerwinkle, Peter Bogaty, Peter S. Braund, Lutz P. Breitling, Hermann Brenner, Carlo Briguori, Jasper J. Brugts, Ralph Burkhardt, Vicky A. Cameron, John F. Carlquist, Clara Carpeggiani, Kathryn F. Carruthers, Gavino Casu, Gianluigi Condorelli, Sharon Cresci, Nicolas Danchin, Ulf de Faire, John Deanfield, Graciela Delgado, Panos Deloukas, Kenan Direk, Robert N. Doughty, Heinz Drexel, Nubia E. Duarte, Marie-Pierre Dubé, Line Dufresne, James C. Engert, Niclas Eriksson, Natalie Fitzpatrick, Luisa Foco, Ian Ford, Keith A.A. Fox, Bruna Gigante, Crystel M. Gijsberts, Domenico Girelli, Yan Gong, Daniel F. Gudbjartsson, Emil Hagström, Jaana Hartiala, Stanley L. Hazen, Claes Held, Anna Helgadottir, Harry Hemingway, Mahyar Heydarpour, Imo E. Hoefer, Kees Hovingh, Jaroslav A. Hubacek, Stefan James, Julie A. Johnson, J. Wouter Jukema, Marcin P. Kaczor, Karol A. Kaminski, Jiri Kettner, Marek Kiliszek, Marcus Kleber, Olaf H. Klungel, Daniel Kofink, Mika Kohonen, Salma Kotti, Pekka Kuukasjärvi, Bo Lagerqvist, Diether Lambrechts, Chim C. Lang, Jari O. Laurikka, Karin Leander, Vei-Vei Lee, Terho Lehtimäki, Andreas Leiherer, Petra A. Lenzini, Daniel Levin, Daniel Lindholm, Marja-Liisa Lokki, Paulo A. Lotufo, Leo-Pekka Lyytikäinen, B. Khan Mahmoodi, Anke H. Maitland-van der Zee, Nicola Martinelli, Winfried März, Nicola Marziliano, Ruth McPherson, Olle Melander, Ute Mons, Jochen D. Muehlschlegel, Joseph B. Muhlestein, Cristopher P. Nelson, Chris Newton Cheh, Oliviero Olivieri, Grzegorz Opolski, Colin N. Palmer, Guillaume Pare, Gerard Pasterkamp, Carl J. Pepine, Witold Pepinski, Alexandre C. Pereira, Anna P. Pilbrow, Louise Pilote, Jan Pitha, Rafal Ploski, A. Mark Richards, Christoph H. Saely, Nilesh J. Samani, Ayman Samman-Tahhan, Marek Sanak, Pratik B. Sandesara, Naveed Sattar, Markus Scholz, Agneta Siegbahn, Tabassome Simon, Juha Sinisalo, J. Gustav Smith, John A. Spertus, Kari Stefansson, Alexandre F.R. Stewart, David J. Stott, Wojciech Szczeklik, Anna Szpakowicz, Michael W.T. Tanck, Wilson H. Tang, Jean-Claude Tardif, Jur M. ten Berg, Andrej Teren, George Thanassoulis, Joachim Thiery, Gudmundur Thorgeirsson, Gudmar Thorleifsson, Unnur Thorsteinsdottir, Adam Timmis, Stella Trompet, Frans van de Werf, Yolanda van der Graaf, Pim van der Haarst, Sander W. van der Laan, Ragnar O. Vilmundarson, Salim S. Virani, Frank L.J. Visseren, Efthymia Vlachopoulou, Lars Wallentin, Johannes Waltenberger, Els Wauters, Arthur A.M. Wilde, Erasmus MC other, Cardiology, Department of Marketing Management, Pathology, Clinical Genetics, PharmacoTherapy, -Epidemiology and -Economics, and ACS - Heart failure & arrhythmias
Subjects: COLLIDER BIAS, genetic association studies, media_common.quotation_subject, Coronary Disease, Disease, Genetic Diseases, Inborn/genetics, HEART-DISEASE, 030204 cardiovascular system & hematology, OBESITY PARADOX, Article, EXPLANATION, 03 medical and health sciences, 0302 clinical medicine, Genetic, Bias, Models, Statistics, Genetics, Medicine, Humans, selection bias, Genetics(clinical), False Positive Reactions, 030212 general & internal medicine, Genetics (clinical), Selection (genetic algorithm), confidence intervals, Selection Bias, Event (probability theory), Genetic association, media_common, risk, Selection bias, Observer Variation, Models, Genetic, business.industry, Hazard ratio, Genetic Diseases, Inborn, ASSOCIATION, Confidence interval, sample size, Inborn/genetics, Sample size determination, CARDIOVASCULAR-DISEASE, Genetic Diseases, alleles, INDEX-EVENT, business, Cardiology and Cardiovascular Medicine
Abstract: Background— Studies of recurrent or subsequent disease events may be susceptible to bias caused by selection of subjects who both experience and survive the primary indexing event. Currently, the magnitude of any selection bias, particularly for subsequent time-to-event analysis in genetic association studies, is unknown. Methods and Results— We used empirically inspired simulation studies to explore the impact of selection bias on the marginal hazard ratio for risk of subsequent events among those with established coronary heart disease. The extent of selection bias was determined by the magnitudes of genetic and nongenetic effects on the indexing (first) coronary heart disease event. Unless the genetic hazard ratio was unrealistically large (>1.6 per allele) and assuming the sum of all nongenetic hazard ratios was Conclusions— In most empirical settings, selection bias is expected to have a limited impact on genetic effect estimates of subsequent event risk. Nevertheless, because of undercoverage increasing with sample size, most confidence intervals will be over precise (not wide enough). When there is no effect modification by history of coronary heart disease, the false-positive rates of association tests will be close to nominal.
Published: 2017

24. Integrative Genomic Approach Identifies Multiple Genes Involved in Cardiac Collagen Deposition

Author: Michael W.T. Tanck, Perry D. Moerland, Connie R. Bezzina, Brendon P. Scicluna, Leander Beekman, Danny Arends, Elisabeth M. Lodder, Michiel E. Adriaens, Amsterdam Cardiovascular Sciences, Cardiology, Amsterdam institute for Infection and Immunity, Amsterdam Public Health, Epidemiology and Data Science, and Medical Biology
Subjects: Genotype, Heart Ventricles, Quantitative Trait Loci, Gene regulatory network, Gene Expression, Mice, Transgenic, Disease, Integrin alpha6, Biology, Bioinformatics, Fibroblast growth factor, medicine.disease_cause, NAV1.5 Voltage-Gated Sodium Channel, Receptors, G-Protein-Coupled, Contractility, Mice, Fibrosis, Gene expression, Genetics, medicine, Animals, Gene Regulatory Networks, Cells, Cultured, Genetics (clinical), Mutation, Genome, Microfilament Proteins, Chromosome Mapping, Fibroblasts, LIM Domain Proteins, FGF1, medicine.disease, Recombinant Proteins, Cell biology, Fibroblast Growth Factor 1, Collagen, Cardiology and Cardiovascular Medicine
Abstract: Background— With aging and in cardiac disease, fibrosis caused by collagen deposition is increased, impairing contractility and providing a substrate for arrhythmia. In this study, we set out to identify genetic modifiers of collagen deposition in the heart by exploiting the genetic variability among F2 progeny of 129P2 and FVBN/J mice carrying the Scn5a tm1Care/+ mutation. Methods and Results— Relative amounts of collagen were determined in left ventricular myocardium of 65 F2-mice and combined with genome-wide genotypic and cardiac expression data to identify collagen quantitative trait loci (QTLs) and overlapping expression QTLs (eQTLs). A significant collagen QTL was identified on mouse Chr8; an additional collagen QTL was identified on mouse Chr2 after correction for a genetic covariate uncovered on Chr18 using multiple QTL mapping. Of the 24 eQTLs colocalizing with the Chr8-collagen QTL, 6 transcripts were correlated with relative collagen amount. Similarly, of the 7 eQTLs colocalizing with the Chr2-collagen QTL, 1 transcript, Gpr158 , correlated with relative collagen. Of the 12 transcripts with an eQTLs in the Chr18-covariate region, only Fgf1 correlated with relative collagen amount. Furthermore, 2 of the transcripts, Pdlim3 (Chr8) and Itga6 (Chr2), with eQTLs overlapping with collagen QTLs, had a genetic covariate on Chr18 that coincided with the Chr18 collagen covariate locus. Application of recombinant human FGF1 to isolated cardiac fibroblasts in culture affected the level of expression of Pdlim3 , Itga6 , and Gpr158 . Conclusions— We here mapped a possible novel genetic network modulating collagen deposition in mouse left ventricular myocardium.
Published: 2014
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25. Common genetic variants do not associate with CAD in familial hypercholesterolemia

Author: Marcel Levi, Mieke D. Trip, Nicole Soranzo, Suthesh Sivapalaratnam, Jennifer G. Sambrook, Erik P A Van Iperen, John J.P. Kastelein, S. Matthijs Boekholdt, Aeilko H. Zwinderman, Michael W.T. Tanck, Stephanie Maiwald, Willem H. Ouwehand, Jonathan Stephens, G. Kees Hovingh, Amsterdam Public Health, Epidemiology and Data Science, Graduate School, Vascular Medicine, Amsterdam Cardiovascular Sciences, Cardiology, and Other departments
Subjects: Male, Oncology, medicine.medical_specialty, Genotype, Single-nucleotide polymorphism, Locus (genetics), Coronary Artery Disease, Familial hypercholesterolemia, Biology, Bioinformatics, Polymorphism, Single Nucleotide, Risk Assessment, Disease-Free Survival, Article, Hyperlipoproteinemia Type II, Gene Frequency, Risk Factors, Internal medicine, Genetics, medicine, Humans, SNP, Genetic Predisposition to Disease, cardiovascular diseases, Allele frequency, Genetics (clinical), Aged, Proportional Hazards Models, Proportional hazards model, Hazard ratio, DNA Helicases, Nuclear Proteins, Middle Aged, medicine.disease, Cohort, Female, Transcription Factors
Abstract: In recent years, multiple loci dispersed on the genome have been shown to be associated with coronary artery disease (CAD). We investigated whether these common genetic variants also hold value for CAD prediction in a large cohort of patients with familial hypercholesterolemia (FH). We genotyped a total of 41 single-nucleotide polymorphisms (SNPs) in 1701 FH patients, of whom 482 patients (28.3%) had at least one coronary event during an average follow up of 66 years. The association of each SNP with event-free survival time was calculated with a Cox proportional hazard model. In the cardiovascular disease risk factor adjusted analysis, the most significant SNP was rs1122608:G>T in the SMARCA4 gene near the LDL-receptor (LDLR) gene, with a hazard ratio for CAD risk of 0.74 (95% CI 0.49–0.99; P-value 0.021). However, none of the SNPs reached the Bonferroni threshold. Of all the known CAD loci analyzed, the SMARCA4 locus near the LDLR had the strongest negative association with CAD in this high-risk FH cohort. The effect is contrary to what was expected. None of the other loci showed association with CAD.
Published: 2014
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26. ABCG5/G8 polymorphisms and markers of cholesterol metabolism: systematic review and meta-analysis

Author: Michael W.T. Tanck, Barbara A. Hutten, Geesje M. Dallinga-Thie, Maud N. Vissers, Lily Jakulj, John J.P. Kastelein, and Frans Stellaard
Subjects: Adult, medicine.medical_specialty, Genotype, Lipoproteins, Campesterol, Hypercholesterolemia, Lathosterol, Single-nucleotide polymorphism, QD415-436, HEART-DISEASE, Biology, Biochemistry, polymorphism, chemistry.chemical_compound, Endocrinology, Internal medicine, BINDING CASSETTE TRANSPORTER, medicine, Humans, LDL-cholesterol, ATP Binding Cassette Transporter, Subfamily G, Member 5, Allele, Research Articles, DIETARY-CHOLESTEROL, Genetics, Polymorphism, Genetic, PLANT STEROLS, medicine.diagnostic_test, Cholesterol, ATP Binding Cassette Transporter, Subfamily G, Member 8, plant sterol, Cell Biology, Middle Aged, SIGNIFICANT ASSOCIATION, Sterol, GALLSTONE DISEASE, chemistry, DENSITY-LIPOPROTEIN CHOLESTEROL, SINGLE NUCLEOTIDE POLYMORPHISMS, ATP-Binding Cassette Transporters, Lipid profile, ABCG8 GENES, LIPID-LEVELS
Abstract: Genetic variation at the ABCG5/G8 locus has been associated with markers of cholesterol homeostasis. As data originate from small-scale studies, we performed a meta-analysis to study these associations in a large dataset. We first investigated associations between five common ABCG5/G8 polymorphisms (p.Q604E, p.D19H, p.Y54C, p.T400K, and p.A632V) and plasma sterol levels in 245 hypercholesterolaemic individuals. No significant associations were found. Subsequently, our data were pooled into a meta-analysis that comprised 3,364 subjects from 16 studies (weighted mean age, 46.7 +/- 10.5 years; BMI, 23.9 +/- 3.5 kg/m(2)). Presence of the minor 632V allele correlated with reduced LDL-C concentrations (n = 367) compared with homozygosity for the 632A variant [n = 614; -0.11 mmol/l (95% CI, range: -0.20 to -0.02 mmol/l); P = 0.01]. The remaining polymorphisms were not associated with plasma lipid levels. Carriers of the 19H allele exhibited lower campesterol/TC (n = 83; P
Published: 2010
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27. Haplotype-Sharing Analysis Implicates Chromosome 7q36 Harboring DPP6 in Familial Idiopathic Ventricular Fibrillation

Author: Pieter G. Postema, Leander Beekman, Arthur A.M. Wilde, Peter Loh, Karel T. Koch, Tamara T. Koopmann, Michael W.T. Tanck, Katja Zeppenfeld, Marcel M.A.M. Mannens, Connie R. Bezzina, Sophie Demolombe, Imke Christiaans, Marielle Alders, ACS - Amsterdam Cardiovascular Sciences, AGEM - Amsterdam Gastroenterology Endocrinology Metabolism, Other Research, Human Genetics, Cardiology, APH - Amsterdam Public Health, Epidemiology and Data Science, and ARD - Amsterdam Reproduction and Development
Subjects: Adult, Male, Proband, Potassium Channels, Heart disease, Gene Expression, Nerve Tissue Proteins, Disease, Biology, Bioinformatics, Polymorphism, Single Nucleotide, Sudden cardiac death, Electrocardiography, Young Adult, Risk Factors, Report, Genetics, medicine, Humans, Genetics(clinical), RNA, Messenger, Family history, Dipeptidyl-Peptidases and Tripeptidyl-Peptidases, Genetics (clinical), Myocardium, Haplotype, Chromosome Mapping, Chromosome, Middle Aged, medicine.disease, Penetrance, Pedigree, Death, Sudden, Cardiac, Haplotypes, Case-Control Studies, Ventricular Fibrillation, Female, Chromosomes, Human, Pair 7, Genome-Wide Association Study, Peptide Hydrolases
Abstract: Idiopathic Ventricular Fibrillation (IVF) is defined as spontaneous VF without any known structural or electrical heart disease. A family history is present in up to 20% of probands with the disorder, suggesting that at least a subset of IVF is hereditary. A genome-wide haplotype-sharing analysis was performed for identification of the responsible gene in three distantly related families in which multiple individuals died suddenly or were successfully resuscitated at young age. We identified a haplotype, on chromosome 7q36, that was conserved in these three families and was also shared by 7 of 42 independent IVF patients. The shared chromosomal segment harbors part of the DPP6 gene, which encodes a putative component of the transient outward current in the heart. We demonstrated a 20-fold increase in DPP6 mRNA levels in the myocardium of carriers as compared to controls. Clinical evaluation of 84 risk-haplotype carriers and 71 noncarriers revealed no ECG or structural parameters indicative of cardiac disease. Penetrance of IVF was high; 50% of risk-haplotype carriers experienced (aborted) sudden cardiac death before the age of 58 years. We propose DPP6 as a gene for IVF and increased DPP6 expression as the likely pathogenetic mechanism.
Published: 2009
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28. Type of SCN5A mutation determines clinical severity and degree of conduction slowing in loss-of-function sodium channelopathies

Author: Paola G. Meregalli, Zahurul A. Bhuiyan, Hervé Le Marec, Philippe Mabo, Arthur A.M. Wilde, Tamara T. Koopmann, Frederic Sacher, Hanno L. Tan, Jean-Jacques Schott, Florence Kyndt, Vincent Probst, Michael W.T. Tanck, Connie R. Bezzina, Juliette Albuisson, Department of Cardiology [Amsterdam], University of Amsterdam [Amsterdam] (UvA)-Academic Medical Center - Academisch Medisch Centrum [Amsterdam] (AMC), University of Amsterdam [Amsterdam] (UvA), Institut du thorax, Université de Nantes (UN)-IFR26-Institut National de la Santé et de la Recherche Médicale (INSERM), Cardiopathies et mort subite [ERL 3147], Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes (UN), Academic Medical Center - Academisch Medisch Centrum [Amsterdam] (AMC), Département de cardiologie, CHU Bordeaux [Bordeaux]-Hôpital Haut-Lévêque [CHU Bordeaux], CHU Bordeaux [Bordeaux], Service de génétique médicale - Unité de génétique clinique [Nantes], Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes), Service de cardiologie et maladies vasculaires [Rennes] = Cardiac, Thoracic, and Vascular Surgery [Rennes], CHU Pontchaillou [Rennes], University of Amsterdam [Amsterdam] (UvA)-University of Amsterdam [Amsterdam] (UvA), Université de Nantes (UN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Service de cardiologie et maladies vasculaires, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Hôpital Pontchaillou-CHU Pontchaillou [Rennes], ACS - Amsterdam Cardiovascular Sciences, Cardiology, APH - Amsterdam Public Health, and Epidemiology and Data Science
Subjects: Male, Proband, Muscle Proteins, MESH: Codon, Terminator, 030204 cardiovascular system & hematology, MESH: Risk Assessment, medicine.disease_cause, Sodium Channels, NAV1.5 Voltage-Gated Sodium Channel, MESH: Brugada Syndrome, MESH: Heart Conduction System, 0302 clinical medicine, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Missense mutation, Brugada syndrome, Genetics, 0303 health sciences, Mutation, MESH: Middle Aged, Middle Aged, Penetrance, 3. Good health, MESH: Arrhythmias, Cardiac, Phenotype, Codon, Terminator, Female, [SDV.IB]Life Sciences [q-bio]/Bioengineering, Cardiology and Cardiovascular Medicine, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Arrhythmia, Sodium Channel Blockers, Adult, medicine.medical_specialty, MESH: Mutation, Mutation, Missense, MESH: Phenotype, Risk Assessment, MESH: Sodium Channels, MESH: Muscle Proteins, 03 medical and health sciences, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, Heart Conduction System, Physiology (medical), Internal medicine, Cardiac conduction, medicine, Humans, cardiovascular diseases, Expressivity (genetics), PR interval, 030304 developmental biology, MESH: Mutation, Missense, MESH: Humans, business.industry, Arrhythmias, Cardiac, MESH: Adult, MESH: NAV1.5 Voltage-Gated Sodium Channel, MESH: Death, Sudden, Cardiac, medicine.disease, MESH: Male, Death, Sudden, Cardiac, Endocrinology, MESH: Sodium Channel Blockers, business, MESH: Female, Conduction disorders
Abstract: International audience; BACKGROUND: Patients carrying loss-of-function SCN5A mutations linked to Brugada syndrome (BrS) or progressive cardiac conduction disease (PCCD) are at risk of sudden cardiac death at a young age. The penetrance and expressivity of the disease are highly variable, and new tools for risk stratification are needed. OBJECTIVES: We aimed to establish whether the type of SCN5A mutation correlates with the clinical and electrocardiographic phenotype. METHODS: We studied BrS or PCCD probands and their relatives who carried a SCN5A mutation. Mutations were divided into 2 main groups: missense mutations (M) or mutations leading to premature truncation of the protein (T). The M group was subdivided according to available biophysical properties: M mutations with 90% (M(inactive)) peak I(Na) reduction were analyzed separately. RESULTS: The study group was composed of 147 individuals with 32 different mutations. No differences in age and sex distribution were found between the groups. Subjects carrying a T mutation had significantly more syncopes than those with an M(active) mutation (19 of 75 versus 2 of 35, P = .03). Also, mutations associated with drastic peak I(Na) reduction (T and M(inactive) mutants) had a significantly longer PR interval, compared with M(active) mutations. All other electrocardiographic parameters were comparable. After drug provocation testing, both PR and QRS intervals were significantly longer in the T and M(inactive) groups than in the M(active) group. CONCLUSION: In loss-of-function SCN5A channelopathies, patients carrying T and M(inactive) mutations develop a more severe phenotype than those with M(active) mutations. This is associated with more severe conduction disorders. This is the first time that genetic data are proposed for risk stratification in BrS.
Published: 2009
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29. Multiple Imputation of Missing Genotype Data for Unrelated Individuals

Author: Olga W. Souverein, Michael W.T. Tanck, and A. H. Zwinderman
Subjects: Word error rate, Regression analysis, Polytomous Rasch model, Missing data, Logistic regression, Quantitative Biology::Genomics, Standard error, Statistics, Genetics, Statistics::Methodology, Imputation (statistics), Allele frequency, Genetics (clinical), Mathematics
Abstract: The objective of this study was to investigate the performance of multiple imputation of missing genotype data for unrelated individuals using the polytomous logistic regression model, focusing on different missingness mechanisms, percentages of missing data, and imputation models. A complete dataset of 581 individuals, each analysed for eight biallelic polymorphisms and the quantitative phenotype HDL-C, was used. From this dataset one hundred replicates with missing data were created, in different ways for different scenarios. The performance was assessed by comparing the mean bias in parameter estimates, the root mean squared standard errors, and the genotype-imputation error rates. Overall, the mean bias was small in all scenarios, and in most scenarios the mean did not differ significantly from 'no bias'. Including polymorphisms that are highly correlated in the imputation model reduced the genotype-imputation error rate and increased precision of the parameter estimates. The method works well for data that are missing completely at random, and for data that are missing at random. In conclusion, our results indicate that multiple imputation with the polytomous logistic regression model can be used for association studies to deal with the problem of missing genotype data, when attention is paid to the imputation model and the percentage of missing data.
Published: 2008
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30. Children with hypercholesterolemia of unknown cause: Value of genetic risk scores

Author: Sigrid W. Fouchier, Albert Wiegman, John J.P. Kastelein, G. Kees Hovingh, Barbara Sjouke, Barbara A. Hutten, Joep C. Defesche, Michael W.T. Tanck, Vascular Medicine, Amsterdam Public Health, Epidemiology and Data Science, Medical Biochemistry, Amsterdam Cardiovascular Sciences, Human Genetics, and Paediatric Metabolic Diseases
Subjects: 0301 basic medicine, Apolipoprotein E, Oncology, Male, medicine.medical_specialty, Apolipoprotein B, Adolescent, Endocrinology, Diabetes and Metabolism, Hypercholesterolemia, Single-nucleotide polymorphism, Familial hypercholesterolemia, 030204 cardiovascular system & hematology, Polymorphism, Single Nucleotide, Risk Assessment, 03 medical and health sciences, 0302 clinical medicine, Internal medicine, Genotype, Internal Medicine, Medicine, Humans, Genetic Predisposition to Disease, Child, Apolipoproteins B, Genetics, Nutrition and Dietetics, biology, business.industry, PCSK9, medicine.disease, 030104 developmental biology, Phenotype, Receptors, LDL, Child, Preschool, Mutation (genetic algorithm), biology.protein, Population study, Female, lipids (amino acids, peptides, and proteins), Proprotein Convertase 9, Cardiology and Cardiovascular Medicine, business
Abstract: Background Familial hypercholesterolemia (FH) is caused by mutations in LDLR , APOB , or PCSK9 , and in a previous study, we identified a causative mutation in these FH genes in 95% (255 of 269) of children with the FH phenotype. It has been hypothesized that a polygenic form of hypercholesterolemia is present in FH patients in whom no mutation is identified in the 3 FH genes. Objective To address whether a polygenic form of hypercholesterolemia, defined as high-weighted effect of low-density lipoprotein cholesterol (LDL-C) raising SNPs expressed as the genetic risk score (GRS), is present in the remaining 14 children. Methods and results On reassessment of the molecular diagnosis and clinical phenotype, 8 FH kindreds met the criteria for hypercholesterolemia of unknown cause and were included in this study. We calculated a weighted GRS comprising 10 established LDL-C–associated SNPs and the APOE genotype in these index cases and evaluated whether the index cases were characterized by an increased GRS compared to 26 first-degree relatives. Phenotypically affected and unaffected individuals could not be distinguished based on any of the risk scores. Conclusions In this and our previous study, we show that a causal mutation in LDLR , APOB , and PCSK9 can be identified in almost all children with a definite clinical diagnosis of FH. In the small group of patients without a mutation, we did not observe a higher GRS compared with unaffected relatives, which suggests that the FH phenotype is not caused by the aggregate of LDL-C increasing SNPs. Our data imply that application of the GRS is not instrumental as a diagnostic tool to individually define clinically diagnosed FH patients with polygenic hypercholesterolemia in our study population.
Published: 2016

31. Common variants of multiple genes that control reverse cholesterol transport together explain only a minor part of the variation of HDL cholesterol levels

Author: A. H. Zwinderman, E. E. van der Wall, R I G Peters, Pieter H. Reitsma, Jan Albert Kuivenhoven, J.J.P. Kastelein, Johan Wouter Jukema, P M H Schiffers, P. A. Doevendans, Olga W. Souverein, Hans Jansen, G.K. Hovingh, S.M. Boekholdt, and Michael W.T. Tanck
Subjects: medicine.medical_specialty, Lipoprotein lipase, Apolipoprotein B, biology, Cholesterol, Reverse cholesterol transport, chemistry.chemical_compound, Endocrinology, chemistry, Internal medicine, Genetic variation, Cholesterylester transfer protein, Genetics, biology.protein, medicine, lipids (amino acids, peptides, and proteins), Hepatic lipase, Allele, Genetics (clinical)
Abstract: It is assumed that the combined effects of multiple common genetic variants explain a large part of variation of high-density lipoprotein cholesterol (HDL-C) plasma levels, but little evidence exists to corroborate this assumption. It was our objective to study the contribution of multiple common genetic variants of HDL-C-related genes to variation of HDL-C plasma levels. A well-characterized cohort of 546 Caucasian men with documented coronary artery disease was genotyped for common functional variants in genes that control reverse cholesterol transport: ATP-binding cassette transporter A1, apolipoprotein A-I and apolipoprotein-E, cholesteryl ester transfer protein, hepatic lipase, lecithin : cholesterol-acyl transferase, lipoprotein lipase, and scavenger receptor class B type 1. Multivariate linear regression showed that these variants, in conjunction, explain 12.4% (95% confidence interval: 6.9-17.9%) of variation in HDL-C plasma levels. When the covariates smoking and body mass index were taken into account, the explained variation increased to 15.3% (9.4-21.2%), and when 10 two-way interactions were incorporated, this percentage rose to 25.2% (18.9-31.5%). This study supports the hypothesis that multiple, mildly penetrant, but highly prevalent genetic variants explain part of the variation of HDL-C plasma levels, albeit to a very modest extent. Multiple environmental and genetic influences on HDL-C plasma levels still have to be elucidated.
Published: 2006
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32. Simultaneous estimation of gene-gene and gene-environment interactions for numerous loci using double penalized log–likelihood

Author: Aeilko H. Zwinderman, Michael W.T. Tanck, J. Wouter Jukema, Amsterdam Public Health, and Epidemiology and Data Science
Subjects: Genetic Markers, Genetic Linkage, Epidemiology, Population, Locus (genetics), Computational biology, Environment, Biology, Gene interaction, Lasso (statistics), Humans, Computer Simulation, Genetic Predisposition to Disease, Allele, education, Gene, Alleles, Genetics (clinical), Genetics, Likelihood Functions, education.field_of_study, Models, Statistical, Polymorphism, Genetic, Models, Genetic, Genetic Diseases, Inborn, Log likelihood, Genetics, Population, Phenotype, Selection operator
Abstract: Many common human diseases are considered to be caused by complex multifactorial processes. For these diseases, it is expected that numerous genetic and environmental factors and, possibly, their interactions play a role. Therefore, simultaneously analyzing the effects of numerous genes and environmental factors is a more realistic approach compared to single gene analyses, but the large number of genes and environmental factors pose a challenge, not in the least due to the limitations created by the tools available for analyzing such high-dimensional models. In the present manuscript we propose a method that is capable of identifying "true" interactions in a setting where the number of effects to be estimated is very large and can even surpass the number of observations. Basically, all possible (interaction) effects are entered in a double penalized model, where main effects are ridge penalized, whereas the interactions are subjected to a least absolute shrinkage and selection operator (lasso) penalty. Results from the simulations and real data show that the proposed method is capable of detecting interactions even with relative small effect sizes.
Published: 2006
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33. Estimating haplotype effects on dichotomous outcome for unphased genotype data using a weighted penalized log-likelihood approach

Author: Aeilko H. Zwinderman, Michael W.T. Tanck, Olga W. Souverein, Amsterdam Public Health, and Epidemiology and Data Science
Subjects: Likelihood Functions, Models, Statistical, Genotype, Models, Genetic, fungi, Haplotype, food and beverages, Log likelihood, Outcome (probability), Gene Frequency, Haplotypes, Statistics, Expectation–maximization algorithm, Genetics, Humans, Regression Analysis, Penalty method, Algorithms, Genetics (clinical), Mathematics
Abstract: Objective: To develop a method to estimate haplotype effects on dichotomous outcomes when phase is unknown, that can also estimate reliable effects of rare haplotypes. Methods: In short, the method uses a logistic regression approach, with weights attached to all possible haplotype combinations of an individual. An EM-algorithm was used: in the E-step the weights are estimated, and the M-step consists of maximizing the joint log-likelihood. When rare haplotypes were present, a penalty function was introduced. We compared four different penalties. To investigate statistical properties of our method, we performed a simulation study for different scenarios. The evaluation criteria are the mean bias of the parameter estimates, the root of the mean squared error, the coverage probability, power, Type I error rate and the false discovery rate. Results: For the unpenalized approach, mean bias was small, coverage probabilities were approximately 95%, power ranged from 15.2 to 44.7% depending on haplotype frequency, and Type I error rate was around 5%. All penalty functions reduced the standard errors of the rare haplotypes, but introduced bias. This trade-off decreased power. Conclusion: The unpenalized weighted log-likelihood approach performs well. A penalty function can help to estimate an effect for rare haplotypes.
Published: 2006
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34. Polymorphisms in APOA1 and LPL genes are statistically independently associated with fasting TG in men with CAD

Author: J. Wouter Jukema, S. Matthijs Boekholdt, Aeilko H. Zwinderman, Michael W.T. Tanck, Olga W. Souverein, Cardiology, Vascular Medicine, Amsterdam Public Health, and Epidemiology and Data Science
Subjects: Male, Apolipoprotein E, medicine.medical_specialty, Multivariate analysis, Genotype, Single-nucleotide polymorphism, Coronary Artery Disease, Biology, Polymorphism, Single Nucleotide, Placebos, chemistry.chemical_compound, Double-Blind Method, Gene Frequency, Polymorphism (computer science), Internal medicine, Genetics, medicine, Humans, Genetic Predisposition to Disease, Allele frequency, Triglycerides, Genetics (clinical), Apolipoprotein A-I, Triglyceride, Fasting, Middle Aged, Lipoprotein Lipase, Endocrinology, chemistry, lipids (amino acids, peptides, and proteins), Analysis of variance
Abstract: The objective of this paper was to identify the single nucleotide polymorphisms ( SNPs) that show unshared effects on plasma triglyceride (TG) levels and to investigate whether these SNPs show statistically independent effects on plasma TG levels. In total, 59 polymorphisms in 20 genes involved in lipid metabolism were investigated. Polymorphisms were selected for a multivariate ANOVA model if they showed an univariate association with TG ( after adjustment for HDL-C and LDL-C) in more than 50% of bootstrap samples that were made from the original data. The multivariate model included 512 men with coronary artery disease from the REGRESS study who were completely genotyped for eight polymorphisms selected in the univariate procedure (ie, APOA1 G( - 75) A, ABCA1 C( - 477) T, ABCA1 G1051A, APOC3 T3206G, APOE Arg158Cys, LIPC C( - 514) T, LPL Asn291Ser and LPL Ser447Stop). The gene variants APOA1 G( - 75) A ( P = 0.04) and LPL Asn291Ser ( P = 0.03) were significantly associated with plasma TG levels in this multivariate analysis. The eight polymorphisms explained 8.9% of the variation in plasma TG levels. In conclusion, this study showed statistically independent effects of gene variants in the APOA1 and LPL genes on fasting plasma levels of TG. Nevertheless, only a small part of variation in TG levels could be explained by the polymorphisms
Published: 2005
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35. Estimation of Multilocus Haplotype Effects Using Weighted Penalised Log-Likelihood: Analysis of Five Sequence Variations at the Cholesteryl Ester Transfer Protein Gene Locus

Author: Michael W.T. Tanck, J.J.P. Kastelein, P. de Knijff, A. H. Zwinderman, Anke H.E.M. Klerkx, Joop Jukema, Amsterdam Public Health, Epidemiology and Data Science, Amsterdam Cardiovascular Sciences, and Vascular Medicine
Subjects: Heterozygote, Linkage disequilibrium, Genotype, Population, Locus (genetics), Biology, Linkage Disequilibrium, Modal haplotype, Gene Frequency, Genetic variation, Genetics, Humans, education, Allele frequency, Alleles, Genetics (clinical), Glycoproteins, education.field_of_study, Models, Statistical, Polymorphism, Genetic, Models, Genetic, Haplotype, Genetic Variation, DNA, Cholesterol Ester Transfer Proteins, Phenotype, Haplotypes, Carrier Proteins, Lipoproteins, HDL
Abstract: Direct analyses of haplotype effects can be used to identify those specific combinations of alleles that are associated with a specific phenotype. We introduce a method for direct haplotype analysis that solves two problems that arise when haplotypes are analysed in populations of unrelated subjects. Instead of assigning a single, most likely, haplotype pair to multiple heterozygous subjects, all haplotype pairs compatible with their genotype were determined and the posterior probabilities of these pairs were calculated using Bayes' theorem and estimated haplotype frequencies. For the individual patients, all possible haplotype pairs were included in the statistical analysis using the posterior probabilities as weights, which were re-estimated in an iterative process together with the haplotype effects. The second problem of unstable haplotype effect estimates, due to the numerous haplotypes and the low frequency at which some occur, was solved by assuming that haplotypes sharing the same alleles show a similar effect and that the extent of this similarity relates to the number of alleles shared. These assumptions were incorporated in a weighted log-likelihood model by introducing a penalty, where differences in effects of similar haplotypes were penalised. Using CETP gene haplotypes, consisting of five closely linked polymorphisms, and baseline CETP and HDL-C concentrations from the REGRESS population, we demonstrated that the model resulted in more stable effects than estimates based on unambiguous patients only.
Published: 2003
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36. Analysis for Genetic Modifiers of Disease Severity in Patients With Long-QT Syndrome Type 2

Author: Stefan Kääb, Sven Zumhagen, Julien Barc, Thomas Meitinger, Jean-Jacques Schott, Nynke Hofman, Pieter G. Postema, Arthur A.M. Wilde, Peter Lichtner, Nanette H. Bishopric, Connie R. Bezzina, Robert J. Myerburg, Dan M. Roden, A. Pfeufer, Tamara T. Koopmann, Anja Husemann, Birgit Stallmeyer, Moritz F. Sinner, Eric Schulze-Bahr, Iris C. R. M. Kolder, Michael W.T. Tanck, Britt M. Beckmann, APH - Amsterdam Public Health, Epidemiology and Data Science, ACS - Amsterdam Cardiovascular Sciences, Cardiology, Human Genetics, unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Academic Medical Center - Academisch Medisch Centrum [Amsterdam] (AMC), University of Amsterdam [Amsterdam] (UvA), Genetics of Heart Diseases, University Hospital Münster - Universitaetsklinikum Muenster [Germany] (UKM), Interdisziplinary Clinical Research Center (IZKF), Institute of Human Genetics, German Research Center for Environmental Health, and Helmholtz-Zentrum München (HZM)
Subjects: Male, Genotype, Long QT syndrome, [SDV]Life Sciences [q-bio], Adrenergic beta-Antagonists, Genome-wide association study, Biology, Arrhythmias, Bioinformatics, Severity of Illness Index, Article, Ion Channels, Electrocardiography, Polymorphism (computer science), Risk Factors, Severity of illness, Genetics, medicine, Odds Ratio, long QT syndrome, Allele, Polymorphism, humans, Genetics (clinical), Alleles, Arrhythmia, Association Study, Genetic Risk Score, Ion Channel, Long Qt Syndrome, Polymorphism Genetics, Case-control study, Signal Transducing, Adaptor Proteins, Odds ratio, Single Nucleotide, medicine.disease, Case-Control Studies, KCNQ1 Potassium Channel, Female, Cardiology and Cardiovascular Medicine, Cardiac, Genome-Wide Association Study
Abstract: Background— Considerable interest exists in the identification of genetic modifiers of disease severity in the long-QT syndrome (LQTS) as their identification may contribute to refinement of risk stratification. Methods and Results— We searched for single-nucleotide polymorphisms (SNPs) that modulate the corrected QT (QTc)-interval and the occurrence of cardiac events in 639 patients harboring different mutations in KCNH2 . We analyzed 1201 SNPs in and around 18 candidate genes, and in another approach investigated 22 independent SNPs previously identified as modulators of QTc-interval in genome-wide association studies in the general population. In an analysis for quantitative effects on the QTc-interval, 3 independent SNPs at NOS1AP (rs10494366, P =9.5×10 −8 ; rs12143842, P =4.8×10 −7 ; and rs2880058, P =8.6×10 −7 ) were strongly associated with the QTc-interval with marked effects (>12 ms/allele). Analysis of patients versus general population controls uncovered enrichment of QTc-prolonging alleles in patients for 2 SNPs, located respectively at NOS1AP (rs12029454; odds ratio, 1.85; 95% confidence interval, 1.32–2.59; P =3×10 −4 ) and KCNQ1 (rs12576239; odds ratio, 1.84; 95% confidence interval, 1.31–2.60; P =5×10 −4 ). An analysis of the cumulative effect of the 6 NOS1AP SNPs by means of a multilocus genetic risk score (GRS NOS1AP ) uncovered a strong linear relationship between GRS NOS1AP and the QTc-interval ( P =4.2×10 −7 ). Furthermore, patients with a GRS NOS1AP in the lowest quartile had a lower relative risk of cardiac events compared with patients in the other quartiles combined ( P =0.039). Conclusions— We uncovered unexpectedly large effects of NOS1AP SNPs on the QTc-interval and a trend for effects on risk of cardiac events. For the first time, we linked common genetic variation at KCNQ1 with risk of long-QT syndrome.
Published: 2015
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37. Exploring the genetic background of stress using isogenic progenies of common carp selected for high or low stress-related cortisol response

Author: H. Bovenhuis, T Claes, M.W.T. Tanck, and J. Komen
Subjects: Fight-or-flight response, Low stress, Genetics, Common carp, Animal science, Plasma cortisol, Trait, Additive genetic effects, Aquatic Science, Biology, Selective breeding, Crossbreed
Abstract: Four homozygous (HomIso) and eight heterozygous isogenic (HetIso) strains of common carp were used in two separate experiments to examine the genetic background of a stress-related cortisol response due to a rapid temperature decrease. The homozygous sires (two high and two low) and dams (high and low) used to obtain the strains were selected based on their estimated breeding value for this trait at an age of 15 months (EBV15). In both experiments, the strains were subjected to a 9 °C cold shock at an age of 5 months. The ranking in plasma cortisol levels of the HomIso strains was identical to the ranking in EBV15 of the sires and the maximal difference of 350 nmol l−1 was similar to the expected difference based on these EBV15's. Differences between the HetIso strains were smaller than expected, and influence of non-additive genetic effects could not be detected (PDS=0.14). Estimated breeding values based on the performance of the androgenetic progeny (EBV5) in experiment 1 and general combining abilities (GCA) of the sires and dams calculated in experiment 2 were positively correlated with the EBV15 (r not significantly different from 1), providing no evidence that the stress response at 5 and 15 months are different traits. Based on the results of these experiments, it can be argued that the best method to change the stress responsiveness of common carp would be through selective breeding (exploiting additive genetic effects) rather than through crossbreeding (exploiting non-additive genetic effects).
Published: 2002
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38. Segregation of microsatellite alleles and residual heterozygosity at single loci in homozygous androgenetic common carp (Cyprinus carpio L.)

Author: M.W.T. Tanck, A.P. Palstra, M. van de Weerd, C.P. Leffering, J.J. van der Poel, H. Bovenhuis, and J. Komen
Subjects: Genetics, General Medicine, Molecular Biology, Biotechnology
Published: 2001
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39. Association Tests of Striatal DAT Availability and SNPs That Impact a Novel Splice Variant in the DAT Gene

Author: Chowdari Kodavali, Wim van den Brink, Michael W.T. Tanck, Maartje M.L. de Win, Vishwajit L. Nimgaonkar, Frank Baas, Elsmarieke van de Giessen, Annie M. Watson, Jan Booij, Amsterdam Neuroscience, Genome Analysis, Neurology, Amsterdam Public Health, Epidemiology and Data Science, Radiology and Nuclear Medicine, Adult Psychiatry, and Nuclear Medicine
Subjects: Genetics, Dopamine Plasma Membrane Transport Proteins, Association test, business.industry, Alternative splicing, Transporter, Single-nucleotide polymorphism, Human brain, Biology, Polymorphism, Single Nucleotide, Neostriatum, Young Adult, medicine.anatomical_structure, Text mining, nervous system, parasitic diseases, mental disorders, medicine, Humans, Protein Isoforms, Radiology, Nuclear Medicine and imaging, Allele, business, Gene
Abstract: TO THE EDITOR: The level of striatal dopamine transporter (DAT) availability in the human brain has been associated with polymorphisms in the gene encoding for DAT ( SLC6A3 ) ([1][1]). We have shown that a specific allele combination for polymorphisms in the 5′ and 3′ ends of the gene affects
Published: 2012
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40. High levels of protein C are determined by PROCR haplotype 3

Author: Michael W.T. Tanck, Sara Roshani, Pieter H. Reitsma, C. Tieken, M. de Visser, Maria Carolina Pintao, Joost C. M. Meijers, F. R. Rosendaal, Iris M Wichers, Saskia Middeldorp, Amsterdam Public Health, Epidemiology and Data Science, Amsterdam Cardiovascular Sciences, Vascular Medicine, Amsterdam institute for Infection and Immunity, and Center of Experimental and Molecular Medicine
Subjects: Adult, Male, Candidate gene, Genetic Linkage, Thrombomodulin, Chromosomes, Human, Pair 20, Receptors, Cell Surface, Single-nucleotide polymorphism, Locus (genetics), Biology, protein C, endothelial protein C receptor, genetic determinants, Exon, plasma levels, Antigens, CD, Humans, Promoter Regions, Genetic, 3' Untranslated Regions, Gene, Molecular epidemiology Aetiology, screening and detection [NCEBP 1], Genetics, Endothelial protein C receptor, Haplotype, Hormonal regulation [IGMD 6], Genetic Variation, PROCR, Exons, Hematology, Molecular biology, Pedigree, Haplotypes, Child, Preschool, EDEM2, Female, Chromosome 20
Abstract: Contains fulltext : 95956.pdf (Publisher’s version ) (Closed access) BACKGROUND: Genetic determinants of plasma levels of protein C (PC) are poorly understood. Recently, we identified a locus on chromosome 20 determining high PC levels in a large Dutch pedigree with unexplained thrombophilia. Candidate genes in the LOD-1 support interval included FOXA2, THBD and PROCR. OBJECTIVES: To examine these candidate genes and their influence on plasma levels of PC. PATIENTS/METHODS: Exons, promoter and 3'UTR of the candidate genes were sequenced in 12 family members with normal to high PC levels. Four haplotypes of PROCR, two SNPs in the neighboring gene EDEM2 and critical SNPs encountered during resequencing were genotyped in the family and in a large group of healthy individuals (the Leiden Thrombophilia Study (LETS) controls). Soluble endothelial protein C receptor (sEPCR) and soluble thrombomodulin (sTM) plasma levels were measured in the family. RESULTS: PROCR haplotype 3 (H3) and FOXA2 rs1055080 were associated with PC levels in the family but only PROCR H3 was also associated with plasma levels in the healthy individuals. Carriers of both variants had higher PC levels than carriers of only PROCR H3 in the family but not in healthy individuals, suggesting that a second determinant is present. EDEM2 SNPs were associated with PC levels, but their effect was small. PC and sEPCR levels were associated in both studies. sTM was not associated with variations of THBD or PC levels. CONCLUSIONS: Chromosome 20 harbors genetic determinants of PC and sEPCR levels and the analysis of candidate genes suggests that the PROCR locus is responsible.
Published: 2011

41. Genome-wide association study identifies a susceptibility locus at 21q21 for ventricular fibrillation in acute myocardial infarction

Author: J. Wouter Jukema, Lukas R.C. Dekker, Roos F. Marsman, Arthur A.M. Wilde, Sumeet S. Chugh, Jonas S.S.G. de Jong, Dan M. Roden, Raha Pazoki, Michael W.T. Tanck, Hanno L. Tan, Navin R. Bindraban, Stefan Kääb, Peter Lichtner, Nanette H. Bishopric, Robert J. Myerburg, Xavier Jouven, Brendon P. Scicluna, Connie R. Bezzina, Arne Pfeufer, Marieke T. Blom, Abdennasser Bardai, Thomas Meitinger, ACS - Amsterdam Cardiovascular Sciences, Cardiology, Epidemiology and Data Science, Medical Biology, APH - Amsterdam Public Health, Center of Experimental and Molecular Medicine, and Other departments
Subjects: Male, medicine.medical_specialty, Myocarditis, Myocardial Infarction, Biology, Article, Sudden cardiac death, Internal medicine, Cardiac conduction, Genetics, medicine, Odds Ratio, Humans, Myocardial infarction, cardiovascular diseases, Anterior Wall Myocardial Infarction, Aged, Netherlands, sudden cardiac death qt interval duration common variants risk-factor cardiomyopathy adenoviruses netherlands disruption sequences genetics, Dilated cardiomyopathy, Arrhythmias, Cardiac, Odds ratio, Middle Aged, medicine.disease, Heart Arrest, Death, Sudden, Cardiac, Ventricular fibrillation, Acute Disease, Ventricular Fibrillation, Cardiology, cardiovascular system, Female, Disease Susceptibility, Genome-Wide Association Study
Abstract: Sudden cardiac death from ventricular fibrillation during acute myocardial infarction is a leading cause of total and cardiovascular mortality. To our knowledge, we here report the first genome-wide association study for this trait, conducted in a set of 972 individuals with a first acute myocardial infarction, 515 of whom had ventricular fibrillation and 457 of whom did not, from the Arrhythmia Genetics in The Netherlands (AGNES) study. The most significant association to ventricular fibrillation was found at 21q21 (rs2824292, odds ratio = 1.78, 95% CI 1.47-2.13, P = 3.3 × 10 -10). The association of rs2824292 with ventricular fibrillation was replicated in an independent case-control set consisting of 146 out-of-hospital cardiac arrest individuals with myocardial infarction complicated by ventricular fibrillation and 391 individuals who survived a myocardial infarction (controls) (odds ratio = 1.49, 95% CI 1.14-1.95, P = 0.004). The closest gene to this SNP is CXADR, which encodes a viral receptor previously implicated in myocarditis and dilated cardiomyopathy and which has recently been identified as a modulator of cardiac conduction. This locus has not previously been implicated in arrhythmia susceptibility.
Published: 2010
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42. Quantitative trait locus for protein C in a family with thrombophilia

Author: Harry R. Büller, Saskia Middeldorp, Joost C. M. Meijers, Pieter H. Reitsma, Michael W.T. Tanck, Iris M Wichers, Amsterdam Public Health, Epidemiology and Data Science, Amsterdam Cardiovascular Sciences, Vascular Medicine, Amsterdam institute for Infection and Immunity, and Center of Experimental and Molecular Medicine
Subjects: Genetics, Adult, Adolescent, business.industry, Quantitative Trait Loci, Vascular biology, Hematology, Quantitative trait locus, Middle Aged, Thrombophilia, medicine.disease, Young Adult, Immunology, Medicine, Humans, Family, Lod Score, business, Protein C, medicine.drug, Aged
Published: 2010

43. Quantitative trait loci for electrocardiographic parameters and arrhythmia in the mouse

Author: Ruben Coronel, Leander Beekman, Connie R. Bezzina, Michael W.T. Tanck, Arthur A.M. Wilde, Carol Ann Remme, Brendon P. Scicluna, Amsterdam institute for Infection and Immunity, Amsterdam Public Health, Epidemiology and Data Science, Amsterdam Cardiovascular Sciences, and Cardiology
Subjects: medicine.medical_specialty, Multifactorial Inheritance, Mice, 129 Strain, Genotype, Population, Quantitative Trait Loci, Single-nucleotide polymorphism, Mice, Transgenic, Quantitative trait locus, Biology, Sudden death, Polymorphism, Single Nucleotide, Sudden cardiac death, QRS complex, Electrocardiography, Mice, Heart Rate, Internal medicine, medicine, Repolarization, Animals, Genetic Predisposition to Disease, cardiovascular diseases, education, Molecular Biology, Flecainide, Crosses, Genetic, Genetics, education.field_of_study, Chromosome Mapping, Arrhythmias, Cardiac, medicine.disease, Mice, Mutant Strains, Haplotypes, Models, Animal, Cardiology, Regression Analysis, Cardiology and Cardiovascular Medicine, medicine.drug
Abstract: Cardiac arrhythmias associated with sudden death are influenced by multiple biological pathways and are modulated by numerous genetic and environmental factors. Elevated heart rate and prolonged ECG indices of conduction and repolarization have been associated with risk of sudden death. Insight into the genetic underpinnings of these parameters thus provides an important means to the dissection of the genetic components modulating risk of sudden cardiac death. In this study we mapped quantitative trait loci (QTL) modulating heart rate, ECG indices of conduction and repolarization, and susceptibility to arrhythmia, in a conduction disease-sensitized F-2 mouse population. Heart rate, P-duration, PR-, QRS- and QT-interval were measured at baseline (n = 502) and after flecainide administration (n = 370) in mutant F2 progeny (F-2-MUT) resulting from the FVB/NJ-Scn5a1798(insD/+) X 129P2-Scn5a1798(insD/+) mouse cross. Episodes of sinus arrhythmia and ventricular tachyarrhythmia occurring post-flecainide were treated as binary traits. F2-MUT mice were genotyped using a genome-wide 768 single nucleotide polymorphism (SNP) panel. Interval mapping uncovered multiple QTL for ECG parameters and arrhythmia. A sex-interacting scan identified QTL displaying sex-dependency, and a two-dimensional QTL scan unmasked locus-locus (epistasis) interactions influencing ECG traits. A number of QTL coincided at specific chromosomal locations, suggesting pleiotropic effects at these loci. Through transcript profiling in myocardium from the parental mouse strains we identified genes co-localizing at the identified QTL that constitute highly relevant candidates for the observed effects. The detection of QTL influencing ECG indices and arrhythmia is an essential step towards identifying genetic networks for sudden, arrhythmic, cardiac death. (C) 2010 Elsevier Ltd. All rights reserved
Published: 2010

44. CAG repeat length variation in the polymerase gamma (POLG) gene: effect on semen quality

Author: F. van der Veen, G.H. Westerveld, Michael W.T. Tanck, L. Kaaij-Visser, Sjoerd Repping, Cancer Center Amsterdam, Radiotherapy, Amsterdam Public Health, Epidemiology and Data Science, Amsterdam Reproduction & Development (AR&D), and Center for Reproductive Medicine
Subjects: Adult, Male, Embryology, Genotype, media_common.quotation_subject, Fertility, Semen, DNA-Directed DNA Polymerase, Length variation, Andrology, Semen quality, Trinucleotide Repeats, Genetics, Humans, Molecular Biology, Polymerase, media_common, biology, Obstetrics and Gynecology, Genetic Variation, Cell Biology, Middle Aged, DNA Polymerase gamma, Reproductive Medicine, Cohort, biology.protein, Spermatogenesis, Developmental Biology
Abstract: Several case – control studies have investigated the effect of CAG repeat length variation in the POLG gene on male fertility and semen quality. Some described an association between the homozygous not10 CAG-repeat genotype and male subfertility and/or reduced semen quality, whereas others did not. The aim of our study was to investigate whether the not10/not10 variant is associated with spermatogenic failure. By direct sequencing methods, we determined the CAG repeat length of POLG in a cohort of 700 consecutive included men with variable degrees of spermatogenesis to investigate its effect on semen quality. The frequency of the not10/not10 variant in our cohort was 4.7%. There were no differences in semen quality between groups with various POLG genotypes. There was a significant difference in frequency of the three CAG-repeat genotypes between ethnic subgroups. In conclusion, the not10/not10 POLG variant is not associated with clinically significant decreases in semen quality, but its frequency is dependent on ethnic background.
Published: 2008

45. Estimating effects of rare haplotypes on failure time using a penalized Cox proportional hazards regression model

Author: Aeilko H. Zwinderman, Michael W.T. Tanck, J. Wouter Jukema, Olga W. Souverein, Amsterdam Public Health, and Epidemiology and Data Science
Subjects: Hazard (logic), lcsh:QH426-470, Kaplan-Meier Estimate, Biology, Polymorphism, Single Nucleotide, Coronary Restenosis, Expectation–maximization algorithm, Confidence Intervals, Genetics, Humans, Genetics(clinical), Treatment Failure, Angioplasty, Balloon, Coronary, Genetics (clinical), Proportional Hazards Models, Proportional hazards model, Methodology Article, Haplotype, Function (mathematics), Confidence interval, Interleukin-10, lcsh:Genetics, Haplotypes, Iterated function
Abstract: Background This paper describes a likelihood approach to model the relation between failure time and haplotypes in studies with unrelated individuals where haplotype phase is unknown, while dealing with the problem of unstable estimates due to rare haplotypes by considering a penalized log-likelihood. Results The Cox model presented here incorporates the uncertainty related to the unknown phase of multiple heterozygous individuals as weights. Estimation is performed with an EM algorithm. In the E-step the weights are estimated, and in the M-step the parameter estimates are estimated by maximizing the expectation of the joint log-likelihood, and the baseline hazard function and haplotype frequencies are calculated. These steps are iterated until the parameter estimates converge. Two penalty functions are considered, namely the ridge penalty and a difference penalty, which is based on the assumption that similar haplotypes show similar effects. Simulations were conducted to investigate properties of the method, and the association between IL10 haplotypes and risk of target vessel revascularization was investigated in 2653 patients from the GENDER study. Conclusion Results from simulations and real data show that the penalized log-likelihood approach produces valid results, indicating that this method is of interest when studying the association between rare haplotypes and failure time in studies of unrelated individuals.
Published: 2008

46. Familial sudden death is an important risk factor for primary ventricular fibrillation: a case-control study in acute myocardial infarction patients

Author: A. E. R. Arnold, Michael W.T. Tanck, Anton P.M. Gorgels, Arthur A.M. Wilde, Lukas R.C. Dekker, Menko-Jan de Boer, Marco Alings, H. Rolf Michels, Felix Zijlstra, Connie R. Bezzina, Karel T. Koch, Freek W.A. Verheugt, José P.S. Henriques, Agnes Verkerk, ACS - Amsterdam Cardiovascular Sciences, Cardiology, APH - Amsterdam Public Health, Epidemiology and Data Science, and Faculteit Medische Wetenschappen/UMCG
Subjects: Male, PROGNOSIS, Heart disease, Myocardial Infarction, Infarction, Electrocardiography, Risk Factors, CARDIAC-ARREST, HISTORY, genetics, Myocardial infarction, Heart, lung and circulation [UMCN 2.1], death, sudden, POPULATION, Netherlands, education.field_of_study, Cardiovascular diseases [NCEBP 14], Middle Aged, Primary ventricular fibrillation, Survival Rate, Phenotype, Ventricular Fibrillation, Cardiology, Female, Cardiology and Cardiovascular Medicine, Adult, medicine.medical_specialty, Population, infarction, ischemia, arrhythmia, Sudden death, Risk Assessment, MECHANISMS, death, Physiology (medical), Internal medicine, medicine, Humans, cardiovascular diseases, Risk factor, fibrillation, education, Aged, sudden, ARRHYTHMIAS, business.industry, Arrhythmias, Cardiac, medicine.disease, Death, Sudden, Cardiac, Case-Control Studies, Myocardial infarction complications, business, FOLLOW-UP, heart arrest
Abstract: Background— Primary ventricular fibrillation (VF) accounts for the majority of deaths during the acute phase of myocardial infarction. Identification of patients at risk for primary VF remains very poor. Methods and Results— We performed a case-control study in patients with a first ST-elevation myocardial infarction (STEMI) to identify independent risk factors for primary VF. A total of 330 primary VF survivors (cases) and 372 controls were included; patients with earlier infarcts or signs of structural heart disease were excluded. Baseline characteristics, including age, gender, drug use, and ECG parameters registered well before the index infarction, as well as medical history, were not different. Infarct size and location, culprit coronary artery, and presence of multivessel disease were similar between groups. Analysis of ECGs performed at hospital admission for the index STEMI revealed that cumulative ST deviation was significantly higher among cases (OR per 10-mm ST deviation 1.59, 95% CI 1.25 to 2.02). Analysis of medical histories among parents and siblings showed that the prevalence of cardiovascular disease was similar between cases and controls (73.1% and 73.0%, respectively); however, familial sudden death occurred significantly more frequently among cases than controls (43.1% and 25.1%, respectively; OR 2.72, 95% CI 1.84 to 4.03). Conclusions— In a population of STEMI patients, the risk of primary VF is determined by cumulative ST deviation and family history of sudden death.
Published: 2006

47. Functional interaction between -629C/A, -971G/A and -1337C/T polymorphisms in the CETP gene is a major determinant of promoter activity and plasma CETP concentration in the REGRESS Study

Author: John J.P. Kastelein, Anke H.E.M. Klerkx, Eric Frisdal, Maryse Guerin, Michael W.T. Tanck, Jean-Pierre Lagarde, M. John Chapman, Wilfried Le Goff, J. Wouter Jukema, Amsterdam Public Health, Epidemiology and Data Science, Amsterdam Cardiovascular Sciences, and Vascular Medicine
Subjects: Male, Genotype, Electrophoretic Mobility Shift Assay, Coronary Artery Disease, Biology, Linkage Disequilibrium, Gene Frequency, Cholesterylester transfer protein, Genetics, Humans, Allele, Promoter Regions, Genetic, Molecular Biology, Gene, Allele frequency, Genetics (clinical), Cells, Cultured, Aged, DNA Primers, Glycoproteins, Netherlands, Reporter gene, Polymorphism, Genetic, Cholesterol, HDL, General Medicine, Transfection, Sequence Analysis, DNA, Major gene, Molecular biology, Cholesterol Ester Transfer Proteins, carbohydrates (lipids), Gene Expression Regulation, Haplotypes, Liver, biology.protein, lipids (amino acids, peptides, and proteins), Carrier Proteins, Lipoprotein
Abstract: Cholesteryl ester transfer protein (CETP) plays a key role in the determination of high-density lipoprotein (HDL) levels via its action on intravascular HDL metabolism. The TaqIB polymorphism of the CETP gene is associated with plasma CETP and high-density lipoprotein cholesterol (HDL-C) levels and with premature coronary artery disease. Such associations appear to result from linkage disequilibrium between TaqIB and other functional polymorphisms. To date, only one functional promoter variant, which may explain the effects of TaqIB, has been identified at position 2629 in the CETP gene. Here we describe a C/T polymorphism located at position 21337 in the human CETP gene (C allele frequency: 0.684), which is significantly associated with plasma HDL-C and CETP levels (P 5 0.0001 and P < 0.0001, respectively). Transient transfection of a reporter gene construct containing the CETP promoter from 21707/ 1 28 in liver cells (HepG2) revealed that the 21337T allele was expressed to a significantly lower degree (234%, P < 0.0001) than the 21337C allele. In addition, we clearly demonstrated that the 2971G/A polymorphism is functional and that its functionality is intimately linked to the presence of the 21337 site. In vitro evaluation of potential interaction between 21337C/T and other functional variants of the CETP gene (2971G/A and 2629C/A) demonstrated that these three functional CETP promoter polymorphisms can interact together to determine the overall activity of the CETP gene and thus contribute significantly to variation in plasma CETP mass concentration.
Published: 2005

48. Genetic determinants of plasma HDL-cholesterol levels in familial hypercholesterolemia

Author: Angelique C.M. Jansen, Michael W.T. Tanck, John J.P. Kastelein, Joep C. Defesche, Emily S. van Aalst-Cohen, Marcel Fontecha, S. Matthijs Boekholdt, Suzanne Cheng, Jan Albert Kuivenhoven, Jia Li, Cardiology, Vascular Medicine, APH - Amsterdam Public Health, Epidemiology and Data Science, ACS - Amsterdam Cardiovascular Sciences, and Experimental Vascular Medicine
Subjects: Apolipoprotein E, Adult, Male, medicine.medical_specialty, Apolipoprotein B, Alcohol Drinking, Genotype, Familial hypercholesterolemia, Biology, Body Mass Index, Cohort Studies, Hyperlipoproteinemia Type II, chemistry.chemical_compound, Sex Factors, Internal medicine, Cholesterylester transfer protein, Genetics, medicine, Humans, Apolipoproteins C, Genetics (clinical), Apolipoproteins A, Glycoproteins, Lipoprotein lipase, Apolipoprotein C-III, Polymorphism, Genetic, Cholesterol, Cholesterol, HDL, Smoking, Middle Aged, medicine.disease, Cholesterol Ester Transfer Proteins, Lipoprotein Lipase, Endocrinology, chemistry, biology.protein, ATP-Binding Cassette Transporters, Female, lipids (amino acids, peptides, and proteins), Hepatic lipase, Carrier Proteins, Lipoprotein, ATP Binding Cassette Transporter 1
Abstract: The objective of this study was to determine the extent to which common genetic variants can explain the variation of high-density lipoprotein cholesterol (HDL-C) plasma levels in familial hypercholesterolemia (FH). FH is characterized by elevated low-density lipoprotein cholesterol levels and premature cardiovascular disease (CVD). Although low HDL-C levels have been shown to affect the severity of the clinical phenotype, little is known about the factors that determine HDL-C levels in these patients. A cohort of 1002 heterozygous FH patients was genotyped for polymorphisms in the genes encoding for ATP-binding cassette transporter A1, apolipoprotein (apo) AIV, apoCIII, apoE, cholesteryl transfer ester protein, hepatic lipase, lipoprotein lipase, and two paraoxonases. Multiple linear regression showed that, together, these polymorphisms explain only 3.9% of the variation of HDL-C plasma levels. When significant two-way interactions between the polymorphisms were also taken into account, the explained variation rose to 12.5%. In a regression model that also incorporated sex, smoking, alcohol use, body mass index, and concomitant beta-blocker use as covariates, the explained variation of HDL-C plasma levels even increased to 32.5%. This study provides direct evidence that multiple, modestly penetrant, but highly prevalent, polymorphisms can explain a substantial part of the variation of HDL-C plasma levels in a representative large cohort of heterozygous FH patients.
Published: 2005

49. Study of a new PPARgamma2 promoter polymorphism and haplotype analysis in a French population

Author: Johan Auwerx, Caroline Janot, Lluis Fajas, Jean Dallongeville, Nicole Helbecque, Aline Meirhaeghe, Dominique Cottel, Philippe Amouyel, Michael W.T. Tanck, Amsterdam Public Health, Epidemiology and Data Science, Epidémiologie des maladies chroniques: impact des intéractions gène environnement sur la santé des populations, Institut Pasteur de Lille, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lille, Droit et Santé-Centre Hospitalier Régional Universitaire [Lille] (CHRU Lille), Endocrinologie moléculaire et cellulaire des cancers, Université Montpellier 1 (UM1)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de génétique et biologie moléculaire et cellulaire (IGBMC), Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Louis Pasteur - Strasbourg I, and Université Louis Pasteur - Strasbourg I-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: Male, Endocrinology, Diabetes and Metabolism, Electrophoretic Mobility Shift Assay, Biochemistry, Linkage Disequilibrium, Exon, 0302 clinical medicine, Endocrinology, Polymorphism (computer science), Chlorocebus aethiops, MESH: Animals, Promoter Regions, Genetic, 0303 health sciences, education.field_of_study, MESH: Middle Aged, GATA2, GATA3, MESH: Transcription Factors, Middle Aged, MESH: COS Cells, DNA-Binding Proteins, GATA2 Transcription Factor, MESH: Promoter Regions (Genetics), MESH: Linkage Disequilibrium, COS Cells, Female, France, MESH: Cholesterol, LDL, Adult, MESH: Trans-Activators, Population, 030209 endocrinology & metabolism, GATA3 Transcription Factor, Biology, Promoter Regions, 03 medical and health sciences, Genetic, MESH: GATA3 Transcription Factor, MESH: Polymorphism, Genetic, Genetics, Animals, Humans, Electrophoretic mobility shift assay, Allele, Polymorphism, education, Molecular Biology, Alleles, 030304 developmental biology, MESH: Humans, Polymorphism, Genetic, MESH: Alleles, Haplotype, Body Weight, MESH: Adult, [SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular biology, MESH: Haplotypes, Cholesterol, LDL, Molecular biology, MESH: Cercopithecus aethiops, MESH: Male, MESH: Body Weight, MESH: France, PPAR gamma, MESH: PPAR gamma, Haplotypes, MESH: Electrophoretic Mobility Shift Assay, Trans-Activators, MESH: GATA2 Transcription Factor, MESH: Female, MESH: DNA-Binding Proteins, Transcription Factors
Abstract: International audience; Peroxisome proliferator-activated receptor-gamma (PPARgamma) plays a role in adipocyte differentiation and insulin sensitization. We identified and characterized a new C/T substitution at position -689 (-689C>T) in the P2 promoter of PPARgamma in a putative GATA binding site. By electrophoretic mobility shift assay, both GATA2 and GATA3 proteins could bind weakly to the wild-type P2 -689 GATA binding site but not to the mutated site. Neither GATA2 nor GATA3 was able to regulate significantly the P2 promoter activity in a reporter-luciferase assay, whatever the allele at position -689 was, suggesting that the -689 putative GATA site was probably not a functional target for GATAs. However, the presence of the -689T allele rendered the P2 promoter less active at the basal state. We genotyped a population of 1155 men and women for the -689C>T polymorphism and looked for possible associations with anthropometric and lipid variables. The carriers of the -689T allele had elevated body weight and LDL-cholesterol concentrations compared with the homozygous for the common allele. Haplotype analyses including the -681C>G (P3 promoter), -689C>T (P2 promoter), and Pro12Ala (exon B) polymorphisms were performed. Carriers of the G-T-Ala haplotype (corresponding to the P3 -681C>G, P2 -689C>T and Pro12Ala polymorphisms in this order) had elevated LDL-cholesterol concentrations and body weight compared with C-C-Pro individuals. In conclusion, we identified a new polymorphism in the P2 promoter of PPARgamma. The P3 -681C>G, P2 -689C>T, and Pro12Ala polymorphisms and related haplotypes were associated with higher body weight and plasma LDL-cholesterol concentrations.
Published: 2004
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50. Chromosomal region 11p15 is associated with male factor subfertility

Author: Marcel M.A.M. Mannens, Marielle Alders, Jan A.M. Kremer, Fulco van der Veen, Jolande A. Land, Michael W.T. Tanck, M. Paola Lombardi, L.H. Hoefsloot, Nico J. Leschot, Mariëtte J.V. Hoffer, Judith Gianotten, Obstetrics and Gynaecology, Center for Reproductive Medicine, Human Genetics, Other Research, Amsterdam Public Health, Epidemiology and Data Science, Amsterdam Cardiovascular Sciences, and Amsterdam Reproduction & Development (AR&D)
Subjects: Male, Embryology, DNA Mutational Analysis, Physiology, Single-nucleotide polymorphism, Biology, Polymorphism, Single Nucleotide, Gene Frequency, Genetics, Humans, Point Mutation, Allele, Molecular Biology, Allele frequency, Gene, Infertility, Male, Endocrinology and reproduction [UMCN 5.2], Chromosomes, Human, Pair 11, Haplotype, Effective Hospital Care [EBP 2], Obstetrics and Gynecology, Cell Biology, DNA-Binding Proteins, Reproductive Medicine, Haplotypes, Genetic defects of metabolism [UMCN 5.1], Case-Control Studies, Chromosomal region, Mutation testing, Etiology, Developmental Biology
Abstract: Item does not contain fulltext The molecular aetiology of male factor subfertility, due to impaired spermatogenesis, is still unknown in the majority of cases. It is thought to be a complex disorder in which multiple genes are implicated. Cryptorchidism and reduced fecundity are symptoms in male Beckwith-Wiedemann patients and the ZNF214 and ZNF215 genes, localized on chromosomal region 11p15, are associated with this syndrome. We hypothesized that the ZNF214 and ZNF215 genes, which are predominantly expressed in the testis, could be involved in male factor subfertility in patients with idiopathic impaired spermatogenesis or in patients with impaired spermatogenesis due to cryptorchidism. Male partners of subfertile couples with idiopathic azoo- or severe oligozoospermia, male partners with azoo- or severe oligozoospermia and cryptorchidism in their medical history and men with normozoospermia were screened for nine single nucleotide polymorphisms in the ZNF214 and ZNF215 genes. An association study was performed based on allele and estimated haplotype frequencies. Statistically significant differences in allele frequencies and in estimated haplotype frequencies were found in both patient groups compared with controls. Thereafter, both genes were screened for mutations in all patients by PCR and single strand conformation polymorphism analysis. Aberrant patterns were confirmed by DNA sequencing. Mutation analysis in ZNF214 and ZNF215 revealed five new variants in the patients that were not present in the controls. At least three of these mutations were inherited from the mother. Our results suggest that chromosomal region 11p15 is associated with male factor subfertility due to impaired spermatogenesis with and without cryptorchidism.
Published: 2003

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