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Start Over Author "SCHOLZ, MARKUS" Publisher escholarship, university of california
15 results on '"SCHOLZ, MARKUS"'

1. Genetic variants for head size share genes and pathways with cancer

Author

Knol, Maria J, Poot, Raymond A, Evans, Tavia E, Satizabal, Claudia L, Mishra, Aniket, Sargurupremraj, Muralidharan, van der Auwera, Sandra, Duperron, Marie-Gabrielle, Jian, Xueqiu, Hostettler, Isabel C, van Dam-Nolen, Dianne HK, Lamballais, Sander, Pawlak, Mikolaj A, Lewis, Cora E, Carrion-Castillo, Amaia, van Erp, Theo GM, Reinbold, Céline S, Shin, Jean, Scholz, Markus, Håberg, Asta K, Kämpe, Anders, Li, Gloria HY, Avinun, Reut, Atkins, Joshua R, Hsu, Fang-Chi, Amod, Alyssa R, Lam, Max, Tsuchida, Ami, Teunissen, Mariël WA, Aygün, Nil, Patel, Yash, Liang, Dan, Beiser, Alexa S, Beyer, Frauke, Bis, Joshua C, Bos, Daniel, Bryan, R Nick, Bülow, Robin, Caspers, Svenja, Catheline, Gwenaëlle, Cecil, Charlotte AM, Dalvie, Shareefa, Dartigues, Jean-François, DeCarli, Charles, Enlund-Cerullo, Maria, Ford, Judith M, Franke, Barbara, Freedman, Barry I, Friedrich, Nele, Green, Melissa J, Haworth, Simon, Helmer, Catherine, Hoffmann, Per, Homuth, Georg, Ikram, M Kamran, Jack, Clifford R, Jahanshad, Neda, Jockwitz, Christiane, Kamatani, Yoichiro, Knodt, Annchen R, Li, Shuo, Lim, Keane, Longstreth, WT, Macciardi, Fabio, Consortium, The Cohorts for Heart and Aging Research in Genomic Epidemiology, Amouyel, Philippe, Arfanakis, Konstantinos, Aribisala, Benjamin S, Bastin, Mark E, Chauhan, Ganesh, Chen, Christopher, Cheng, Ching-Yu, de Jager, Philip L, Deary, Ian J, Fleischman, Debra A, Gottesman, Rebecca F, Gudnason, Vilmundur, Hilal, Saima, Hofer, Edith, Janowitz, Deborah, Jukema, J Wouter, Liewald, David CM, Lopez, Lorna M, Lopez, Oscar, Luciano, Michelle, Martinez, Oliver, Niessen, Wiro J, Nyquist, Paul, Rotter, Jerome I, Rundek, Tatjana, Sacco, Ralph L, Schmidt, Helena, Tiemeier, Henning, Trompet, Stella, van der Grond, Jeroen, Völzke, Henry, Wardlaw, Joanna M, Yanek, Lisa, Yang, Jingyun, and Consortium, The Enhancing NeuroImaging Genetics through Meta-Analysis

Subjects
Biomedical and Clinical Sciences, Biotechnology, Genetics, Stem Cell Research, Neurosciences, Human Genome, Cancer, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Neurological, Humans, Genome-Wide Association Study, Head, Neoplasms, Female, Male, Polymorphism, Single Nucleotide, Genetic Variation, Organ Size, Signal Transduction, Adult, Genetic Predisposition to Disease, Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium, cancer, genetics, genome-wide association study, head circumference, head size, intracranial volume, meta-analysis, Biomedical and clinical sciences
Abstract

The size of the human head is highly heritable, but genetic drivers of its variation within the general population remain unmapped. We perform a genome-wide association study on head size (N = 80,890) and identify 67 genetic loci, of which 50 are novel. Neuroimaging studies show that 17 variants affect specific brain areas, but most have widespread effects. Gene set enrichment is observed for various cancers and the p53, Wnt, and ErbB signaling pathways. Genes harboring lead variants are enriched for macrocephaly syndrome genes (37-fold) and high-fidelity cancer genes (9-fold), which is not seen for human height variants. Head size variants are also near genes preferentially expressed in intermediate progenitor cells, neural cells linked to evolutionary brain expansion. Our results indicate that genes regulating early brain and cranial growth incline to neoplasia later in life, irrespective of height. This warrants investigation of clinical implications of the link between head size and cancer.

Published
2024

2. X-chromosome and kidney function: evidence from a multi-trait genetic analysis of 908,697 individuals reveals sex-specific and sex-differential findings in genes regulated by androgen response elements.

Author

Scholz, Markus, Horn, Katrin, Pott, Janne, Wuttke, Matthias, Kühnapfel, Andreas, Nasr, M, Kirsten, Holger, Li, Yong, Hoppmann, Anselm, Gorski, Mathias, Ghasemi, Sahar, Li, Man, Tin, Adrienne, Chai, Jin-Fang, Cocca, Massimiliano, Wang, Judy, Nutile, Teresa, Akiyama, Masato, Åsvold, Bjørn, Bansal, Nisha, Biggs, Mary, Boutin, Thibaud, Brenner, Hermann, Brumpton, Ben, Burkhardt, Ralph, Cai, Jianwen, Campbell, Archie, Campbell, Harry, Chalmers, John, Chasman, Daniel, Chee, Miao, Chen, Xu, Cheng, Ching-Yu, Cifkova, Renata, Daviglus, Martha, Delgado, Graciela, Dittrich, Katalin, Edwards, Todd, Endlich, Karlhans, Michael Gaziano, J, Giri, Ayush, Giulianini, Franco, Gordon, Scott, Gudbjartsson, Daniel, Hallan, Stein, Hamet, Pavel, Hartman, Catharina, Hayward, Caroline, Heid, Iris, Hellwege, Jacklyn, Holleczek, Bernd, Holm, Hilma, Hutri-Kähönen, Nina, Hveem, Kristian, Isermann, Berend, Jonas, Jost, Joshi, Peter, Kamatani, Yoichiro, Kanai, Masahiro, Kastarinen, Mika, Khor, Chiea, Kiess, Wieland, Kleber, Marcus, Körner, Antje, Kovacs, Peter, Krajcoviechova, Alena, Kramer, Holly, Krämer, Bernhard, Kuokkanen, Mikko, Kähönen, Mika, Lange, Leslie, Lash, James, Lehtimäki, Terho, Li, Hengtong, Lin, Bridget, Liu, Jianjun, Loeffler, Markus, Lyytikäinen, Leo-Pekka, Magnusson, Patrik, Martin, Nicholas, Matsuda, Koichi, Milaneschi, Yuri, Mishra, Pashupati, Mononen, Nina, Montgomery, Grant, Mook-Kanamori, Dennis, Mychaleckyj, Josyf, März, Winfried, Nauck, Matthias, Nikus, Kjell, Nolte, Ilja, Noordam, Raymond, Okada, Yukinori, Olafsson, Isleifur, Oldehinkel, Albertine, Penninx, Brenda, Perola, Markus, Pirastu, Nicola, and Polasek, Ozren

Subjects
Humans, Male, Female, Androgens, Genome-Wide Association Study, Kidney, Chromosomes, Human, X, Response Elements, Polymorphism, Single Nucleotide, Genetic Predisposition to Disease, Tetraspanins
Abstract

X-chromosomal genetic variants are understudied but can yield valuable insights into sexually dimorphic human traits and diseases. We performed a sex-stratified cross-ancestry X-chromosome-wide association meta-analysis of seven kidney-related traits (n = 908,697), identifying 23 loci genome-wide significantly associated with two of the traits: 7 for uric acid and 16 for estimated glomerular filtration rate (eGFR), including four novel eGFR loci containing the functionally plausible prioritized genes ACSL4, CLDN2, TSPAN6 and the female-specific DRP2. Further, we identified five novel sex-interactions, comprising male-specific effects at FAM9B and AR/EDA2R, and three sex-differential findings with larger genetic effect sizes in males at DCAF12L1 and MST4 and larger effect sizes in females at HPRT1. All prioritized genes in loci showing significant sex-interactions were located next to androgen response elements (ARE). Five ARE genes showed sex-differential expressions. This study contributes new insights into sex-dimorphisms of kidney traits along with new prioritized gene targets for further molecular research.

Published
2024

3. Genome-wide association study and functional characterization identifies candidate genes for insulin-stimulated glucose uptake

Author

Williamson, Alice, Norris, Dougall M, Yin, Xianyong, Broadaway, K Alaine, Moxley, Anne H, Vadlamudi, Swarooparani, Wilson, Emma P, Jackson, Anne U, Ahuja, Vasudha, Andersen, Mette K, Arzumanyan, Zorayr, Bonnycastle, Lori L, Bornstein, Stefan R, Bretschneider, Maxi P, Buchanan, Thomas A, Chang, Yi-Cheng, Chuang, Lee-Ming, Chung, Ren-Hua, Clausen, Tine D, Damm, Peter, Delgado, Graciela E, de Mello, Vanessa D, Dupuis, Josée, Dwivedi, Om P, Erdos, Michael R, Silva, Lilian Fernandes, Frayling, Timothy M, Gieger, Christian, Goodarzi, Mark O, Guo, Xiuqing, Gustafsson, Stefan, Hakaste, Liisa, Hammar, Ulf, Hatem, Gad, Herrmann, Sandra, Højlund, Kurt, Horn, Katrin, Hsueh, Willa A, Hung, Yi-Jen, Hwu, Chii-Min, Jonsson, Anna, Kårhus, Line L, Kleber, Marcus E, Kovacs, Peter, Lakka, Timo A, Lauzon, Marie, Lee, I-Te, Lindgren, Cecilia M, Lindström, Jaana, Linneberg, Allan, Liu, Ching-Ti, Luan, Jian’an, Aly, Dina Mansour, Mathiesen, Elisabeth, Moissl, Angela P, Morris, Andrew P, Narisu, Narisu, Perakakis, Nikolaos, Peters, Annette, Prasad, Rashmi B, Rodionov, Roman N, Roll, Kathryn, Rundsten, Carsten F, Sarnowski, Chloé, Savonen, Kai, Scholz, Markus, Sharma, Sapna, Stinson, Sara E, Suleman, Sufyan, Tan, Jingyi, Taylor, Kent D, Uusitupa, Matti, Vistisen, Dorte, Witte, Daniel R, Walther, Romy, Wu, Peitao, Xiang, Anny H, Zethelius, Björn, Ahlqvist, Emma, Bergman, Richard N, Chen, Yii-Der Ida, Collins, Francis S, Fall, Tove, Florez, Jose C, Fritsche, Andreas, Grallert, Harald, Groop, Leif, Hansen, Torben, Koistinen, Heikki A, Komulainen, Pirjo, Laakso, Markku, Lind, Lars, Loeffler, Markus, März, Winfried, Meigs, James B, Raffel, Leslie J, Rauramaa, Rainer, Rotter, Jerome I, Schwarz, Peter EH, and Stumvoll, Michael

Subjects
Biochemistry and Cell Biology, Genetics, Biological Sciences, Diabetes, Clinical Research, Human Genome, Prevention, Nutrition, 2.1 Biological and endogenous factors, Aetiology, 5.1 Pharmaceuticals, Development of treatments and therapeutic interventions, Metabolic and endocrine, Humans, Insulin, Genome-Wide Association Study, Insulin Resistance, Diabetes Mellitus, Type 2, Glucose, Blood Glucose, Meta-Analysis of Glucose and Insulin-related Traits Consortium, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Distinct tissue-specific mechanisms mediate insulin action in fasting and postprandial states. Previous genetic studies have largely focused on insulin resistance in the fasting state, where hepatic insulin action dominates. Here we studied genetic variants influencing insulin levels measured 2 h after a glucose challenge in >55,000 participants from three ancestry groups. We identified ten new loci (P

Published
2023

4. Genome-wide meta-analyses reveal novel loci for verbal short-term memory and learning

Author

Lahti, Jari, Tuominen, Samuli, Yang, Qiong, Pergola, Giulio, Ahmad, Shahzad, Amin, Najaf, Armstrong, Nicola J, Beiser, Alexa, Bey, Katharina, Bis, Joshua C, Boerwinkle, Eric, Bressler, Jan, Campbell, Archie, Campbell, Harry, Chen, Qiang, Corley, Janie, Cox, Simon R, Davies, Gail, De Jager, Philip L, Derks, Eske M, Faul, Jessica D, Fitzpatrick, Annette L, Fohner, Alison E, Ford, Ian, Fornage, Myriam, Gerring, Zachary, Grabe, Hans J, Grodstein, Francine, Gudnason, Vilmundur, Simonsick, Eleanor, Holliday, Elizabeth G, Joshi, Peter K, Kajantie, Eero, Kaprio, Jaakko, Karell, Pauliina, Kleineidam, Luca, Knol, Maria J, Kochan, Nicole A, Kwok, John B, Leber, Markus, Lam, Max, Lee, Teresa, Li, Shuo, Loukola, Anu, Luck, Tobias, Marioni, Riccardo E, Mather, Karen A, Medland, Sarah, Mirza, Saira S, Nalls, Mike A, Nho, Kwangsik, O’Donnell, Adrienne, Oldmeadow, Christopher, Painter, Jodie, Pattie, Alison, Reppermund, Simone, Risacher, Shannon L, Rose, Richard J, Sadashivaiah, Vijay, Scholz, Markus, Satizabal, Claudia L, Schofield, Peter W, Schraut, Katharina E, Scott, Rodney J, Simino, Jeannette, Smith, Albert V, Smith, Jennifer A, Stott, David J, Surakka, Ida, Teumer, Alexander, Thalamuthu, Anbupalam, Trompet, Stella, Turner, Stephen T, van der Lee, Sven J, Villringer, Arno, Völker, Uwe, Wilson, Robert S, Wittfeld, Katharina, Vuoksimaa, Eero, Xia, Rui, Yaffe, Kristine, Yu, Lei, Zare, Habil, Zhao, Wei, Ames, David, Attia, John, Bennett, David A, Brodaty, Henry, Chasman, Daniel I, Goldman, Aaron L, Hayward, Caroline, Ikram, M Arfan, Jukema, J Wouter, Kardia, Sharon LR, Lencz, Todd, Loeffler, Markus, Mattay, Venkata S, Palotie, Aarno, Psaty, Bruce M, and Ramirez, Alfredo

Subjects
Biological Psychology, Psychology, Genetics, Human Genome, Dementia, Behavioral and Social Science, Brain Disorders, Acquired Cognitive Impairment, Mental Health, Biotechnology, Aging, Clinical Research, Neurosciences, Basic Behavioral and Social Science, Aetiology, 2.1 Biological and endogenous factors, Neurological, Mental health, Memory, Short-Term, Learning, Verbal Learning, Multifactorial Inheritance, Brain, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Understanding the genomic basis of memory processes may help in combating neurodegenerative disorders. Hence, we examined the associations of common genetic variants with verbal short-term memory and verbal learning in adults without dementia or stroke (N = 53,637). We identified novel loci in the intronic region of CDH18, and at 13q21 and 3p21.1, as well as an expected signal in the APOE/APOC1/TOMM40 region. These results replicated in an independent sample. Functional and bioinformatic analyses supported many of these loci and further implicated POC1. We showed that polygenic score for verbal learning associated with brain activation in right parieto-occipital region during working memory task. Finally, we showed genetic correlations of these memory traits with several neurocognitive and health outcomes. Our findings suggest a role of several genomic loci in verbal memory processes.

Published
2022

5. Meta-GWAS of PCSK9 levels detects two novel loci at APOB and TM6SF2

Author

Pott, Janne, Gadin, Jesper, Theusch, Elizabeth, Kleber, Marcus E, Delgado, Graciela E, Kirsten, Holger, Hauck, Stefanie M, Burkhardt, Ralph, Scharnagl, Hubert, Krauss, Ronald M, Loeffler, Markus, März, Winfried, Thiery, Joachim, Silveira, Angela, Hooft, Ferdinand M Vant, and Scholz, Markus

Subjects
Digestive Diseases, Heart Disease, Atherosclerosis, Human Genome, Genetics, Cardiovascular, Heart Disease - Coronary Heart Disease, 2.1 Biological and endogenous factors, Aetiology, Apolipoproteins B, Cholesterol, LDL, Coronary Artery Disease, Genome-Wide Association Study, Humans, Membrane Proteins, Proprotein Convertase 9, Receptors, LDL, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

BackgroundProprotein convertase subtilisin/kexin type 9 (PCSK9) is a key player in lipid metabolism, as it degrades low-density lipoprotein (LDL) receptors from hepatic cell membranes. So far, only variants of the PCSK9 gene locus were found to be associated with PCSK9 levels. Here we aimed to identify novel genetic loci that regulate PCSK9 levels and how they relate to other lipid traits. Additionally, we investigated to what extend the causal effect of PCSK9 on coronary artery disease (CAD) is mediated by low-density lipoprotein-cholesterol (LDL-C).Methods and resultsWe performed a genome-wide association study meta-analysis of PCSK9 levels in up to 12 721 samples of European ancestry. The estimated heritability was 10.3%, which increased to 12.6% using only samples from patients without statin treatment. We successfully replicated the known PCSK9 hit consisting of three independent signals. Interestingly, in a study of 300 African Americans, we confirmed the locus with a different PCSK9 variant. Beyond PCSK9, our meta-analysis detected three novel loci with genome-wide significance. Co-localization analysis with cis-eQTLs and lipid traits revealed biologically plausible candidate genes at two of them: APOB and TM6SF2. In a bivariate Mendelian Randomization analysis, we detected a strong effect of PCSK9 on LDL-C, but not vice versa. LDL-C mediated 63% of the total causal effect of PCSK9 on CAD.ConclusionOur study identified novel genetic loci with plausible candidate genes affecting PCSK9 levels. Ethnic heterogeneity was observed at the PCSK9 locus itself. Although the causal effect of PCSK9 on CAD is mainly mediated by LDL-C, an independent direct effect also occurs.

Published
2022

6. Meta-analysis uncovers genome-wide significant variants for rapid kidney function decline

Author

Gorski, Mathias, Jung, Bettina, Li, Yong, Matias-Garcia, Pamela R, Wuttke, Matthias, Coassin, Stefan, Thio, Chris HL, Kleber, Marcus E, Winkler, Thomas W, Wanner, Veronika, Chai, Jin-Fang, Chu, Audrey Y, Cocca, Massimiliano, Feitosa, Mary F, Ghasemi, Sahar, Hoppmann, Anselm, Horn, Katrin, Li, Man, Nutile, Teresa, Scholz, Markus, Sieber, Karsten B, Teumer, Alexander, Tin, Adrienne, Wang, Judy, Tayo, Bamidele O, Ahluwalia, Tarunveer S, Almgren, Peter, Bakker, Stephan JL, Banas, Bernhard, Bansal, Nisha, Biggs, Mary L, Boerwinkle, Eric, Bottinger, Erwin P, Brenner, Hermann, Carroll, Robert J, Chalmers, John, Chee, Miao-Li, Chee, Miao-Ling, Cheng, Ching-Yu, Coresh, Josef, de Borst, Martin H, Degenhardt, Frauke, Eckardt, Kai-Uwe, Endlich, Karlhans, Franke, Andre, Freitag-Wolf, Sandra, Gampawar, Piyush, Gansevoort, Ron T, Ghanbari, Mohsen, Gieger, Christian, Hamet, Pavel, Ho, Kevin, Hofer, Edith, Holleczek, Bernd, Foo, Valencia Hui Xian, Hutri-Kähönen, Nina, Hwang, Shih-Jen, Ikram, M Arfan, Josyula, Navya Shilpa, Kähönen, Mika, Khor, Chiea-Chuen, Koenig, Wolfgang, Kramer, Holly, Krämer, Bernhard K, Kühnel, Brigitte, Lange, Leslie A, Lehtimäki, Terho, Lieb, Wolfgang, Loos, Ruth JF, Lukas, Mary Ann, Lyytikäinen, Leo-Pekka, Meisinger, Christa, Meitinger, Thomas, Melander, Olle, Milaneschi, Yuri, Mishra, Pashupati P, Mononen, Nina, Mychaleckyj, Josyf C, Nadkarni, Girish N, Nauck, Matthias, Nikus, Kjell, Ning, Boting, Nolte, Ilja M, O’Donoghue, Michelle L, Orho-Melander, Marju, Pendergrass, Sarah A, Penninx, Brenda WJH, Preuss, Michael H, Psaty, Bruce M, Raffield, Laura M, Raitakari, Olli T, Rettig, Rainer, Rheinberger, Myriam, Rice, Kenneth M, Rosenkranz, Alexander R, Rossing, Peter, Rotter, Jerome I, Sabanayagam, Charumathi, Schmidt, Helena, and Schmidt, Reinhold

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Prevention, Human Genome, Kidney Disease, Rare Diseases, Genetics, Aetiology, 2.1 Biological and endogenous factors, Renal and urogenital, AMP-Activated Protein Kinases, Creatinine, Genome-Wide Association Study, Glomerular Filtration Rate, Humans, Kidney, Protein Disulfide-Isomerases, United Kingdom, acute kidney injury, end-stage kidney disease, genome-wide association study, rapid eGFRcrea decline, Lifelines Cohort Study, Regeneron Genetics Center, Urology & Nephrology, Clinical sciences
Abstract

Rapid decline of glomerular filtration rate estimated from creatinine (eGFRcrea) is associated with severe clinical endpoints. In contrast to cross-sectionally assessed eGFRcrea, the genetic basis for rapid eGFRcrea decline is largely unknown. To help define this, we meta-analyzed 42 genome-wide association studies from the Chronic Kidney Diseases Genetics Consortium and United Kingdom Biobank to identify genetic loci for rapid eGFRcrea decline. Two definitions of eGFRcrea decline were used: 3 mL/min/1.73m2/year or more ("Rapid3"; encompassing 34,874 cases, 107,090 controls) and eGFRcrea decline 25% or more and eGFRcrea under 60 mL/min/1.73m2 at follow-up among those with eGFRcrea 60 mL/min/1.73m2 or more at baseline ("CKDi25"; encompassing 19,901 cases, 175,244 controls). Seven independent variants were identified across six loci for Rapid3 and/or CKDi25: consisting of five variants at four loci with genome-wide significance (near UMOD-PDILT (2), PRKAG2, WDR72, OR2S2) and two variants among 265 known eGFRcrea variants (near GATM, LARP4B). All these loci were novel for Rapid3 and/or CKDi25 and our bioinformatic follow-up prioritized variants and genes underneath these loci. The OR2S2 locus is novel for any eGFRcrea trait including interesting candidates. For the five genome-wide significant lead variants, we found supporting effects for annual change in blood urea nitrogen or cystatin-based eGFR, but not for GATM or LARP4B. Individuals at high compared to those at low genetic risk (8-14 vs. 0-5 adverse alleles) had a 1.20-fold increased risk of acute kidney injury (95% confidence interval 1.08-1.33). Thus, our identified loci for rapid kidney function decline may help prioritize therapeutic targets and identify mechanisms and individuals at risk for sustained deterioration of kidney function.

Published
2021

7. Genome-wide analysis identifies novel susceptibility loci for myocardial infarction

Author

Hartiala, Jaana A, Han, Yi, Jia, Qiong, Hilser, James R, Huang, Pin, Gukasyan, Janet, Schwartzman, William S, Cai, Zhiheng, Biswas, Subarna, Trégouët, David-Alexandre, Smith, Nicholas L, Consortium, The INVENT, Group, The CHARGE Consortium Hemostasis Working, Consortium, The GENIUS-CHD, Seldin, Marcus, Pan, Calvin, Mehrabian, Margarete, Lusis, Aldons J, Bazeley, Peter, Sun, Yan V, Liu, Chang, Quyyumi, Arshed A, Scholz, Markus, Thiery, Joachim, Delgado, Graciela E, Kleber, Marcus E, März, Winfried, Howe, Laurence J, Asselbergs, Folkert W, van Vugt, Marion, Vlachojannis, Georgios J, Patel, Riyaz S, Lyytikäinen, Leo-Pekka, Kähönen, Mika, Lehtimäki, Terho, Nieminen, Tuomo VM, Kuukasjärvi, Pekka, Laurikka, Jari O, Chang, Xuling, Heng, Chew-Kiat, Jiang, Rong, Kraus, William E, Hauser, Elizabeth R, Ferguson, Jane F, Reilly, Muredach P, Ito, Kaoru, Koyama, Satoshi, Kamatani, Yoichiro, Komuro, Issei, Japan, Biobank, Stolze, Lindsey K, Romanoski, Casey E, Khan, Mohammad Daud, Turner, Adam W, Miller, Clint L, Aherrahrou, Redouane, Civelek, Mete, Ma, Lijiang, Björkegren, Johan LM, Kumar, S Ram, Tang, WH Wilson, Hazen, Stanley L, and Allayee, Hooman

Subjects
Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Cardiovascular, Heart Disease, Clinical Research, Heart Disease - Coronary Heart Disease, Human Genome, Genetics, Aging, Atherosclerosis, Aetiology, 2.1 Biological and endogenous factors, Coronary Artery Disease, Endothelial Cells, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Japan, Myocardial Infarction, Polymorphism, Single Nucleotide, Risk Factors, Myocardial infarction, Genetic factors, Genome-wide association study, Meta-analysis, SLC44A3, INVENT Consortium, CHARGE Consortium Hemostasis Working Group, GENIUS-CHD Consortium, Biobank Japan, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract

AimsWhile most patients with myocardial infarction (MI) have underlying coronary atherosclerosis, not all patients with coronary artery disease (CAD) develop MI. We sought to address the hypothesis that some of the genetic factors which establish atherosclerosis may be distinct from those that predispose to vulnerable plaques and thrombus formation.Methods and resultsWe carried out a genome-wide association study for MI in the UK Biobank (n∼472 000), followed by a meta-analysis with summary statistics from the CARDIoGRAMplusC4D Consortium (n∼167 000). Multiple independent replication analyses and functional approaches were used to prioritize loci and evaluate positional candidate genes. Eight novel regions were identified for MI at the genome wide significance level, of which effect sizes at six loci were more robust for MI than for CAD without the presence of MI. Confirmatory evidence for association of a locus on chromosome 1p21.3 harbouring choline-like transporter 3 (SLC44A3) with MI in the context of CAD, but not with coronary atherosclerosis itself, was obtained in Biobank Japan (n∼165 000) and 16 independent angiography-based cohorts (n∼27 000). Follow-up analyses did not reveal association of the SLC44A3 locus with CAD risk factors, biomarkers of coagulation, other thrombotic diseases, or plasma levels of a broad array of metabolites, including choline, trimethylamine N-oxide, and betaine. However, aortic expression of SLC44A3 was increased in carriers of the MI risk allele at chromosome 1p21.3, increased in ischaemic (vs. non-diseased) coronary arteries, up-regulated in human aortic endothelial cells treated with interleukin-1β (vs. vehicle), and associated with smooth muscle cell migration in vitro.ConclusionsA large-scale analysis comprising ∼831 000 subjects revealed novel genetic determinants of MI and implicated SLC44A3 in the pathophysiology of vulnerable plaques.

Published
2021

8. Genetic correlations and genome-wide associations of cortical structure in general population samples of 22,824 adults.

Author

Hofer, Edith, Roshchupkin, Gennady V, Adams, Hieab HH, Knol, Maria J, Lin, Honghuang, Li, Shuo, Zare, Habil, Ahmad, Shahzad, Armstrong, Nicola J, Satizabal, Claudia L, Bernard, Manon, Bis, Joshua C, Gillespie, Nathan A, Luciano, Michelle, Mishra, Aniket, Scholz, Markus, Teumer, Alexander, Xia, Rui, Jian, Xueqiu, Mosley, Thomas H, Saba, Yasaman, Pirpamer, Lukas, Seiler, Stephan, Becker, James T, Carmichael, Owen, Rotter, Jerome I, Psaty, Bruce M, Lopez, Oscar L, Amin, Najaf, van der Lee, Sven J, Yang, Qiong, Himali, Jayandra J, Maillard, Pauline, Beiser, Alexa S, DeCarli, Charles, Karama, Sherif, Lewis, Lindsay, Harris, Mat, Bastin, Mark E, Deary, Ian J, Veronica Witte, A, Beyer, Frauke, Loeffler, Markus, Mather, Karen A, Schofield, Peter R, Thalamuthu, Anbupalam, Kwok, John B, Wright, Margaret J, Ames, David, Trollor, Julian, Jiang, Jiyang, Brodaty, Henry, Wen, Wei, Vernooij, Meike W, Hofman, Albert, Uitterlinden, André G, Niessen, Wiro J, Wittfeld, Katharina, Bülow, Robin, Völker, Uwe, Pausova, Zdenka, Bruce Pike, G, Maingault, Sophie, Crivello, Fabrice, Tzourio, Christophe, Amouyel, Philippe, Mazoyer, Bernard, Neale, Michael C, Franz, Carol E, Lyons, Michael J, Panizzon, Matthew S, Andreassen, Ole A, Dale, Anders M, Logue, Mark, Grasby, Katrina L, Jahanshad, Neda, Painter, Jodie N, Colodro-Conde, Lucía, Bralten, Janita, Hibar, Derrek P, Lind, Penelope A, Pizzagalli, Fabrizio, Stein, Jason L, Thompson, Paul M, Medland, Sarah E, ENIGMA consortium, Sachdev, Perminder S, Kremen, William S, Wardlaw, Joanna M, Villringer, Arno, van Duijn, Cornelia M, Grabe, Hans J, Longstreth, William T, Fornage, Myriam, Paus, Tomas, Debette, Stephanie, Ikram, M Arfan, Schmidt, Helena, Schmidt, Reinhold, and Seshadri, Sudha

Subjects
ENIGMA consortium, Brain, Chromosome Structures, Humans, Neurodegenerative Diseases, Cognition, Mental Disorders, Genomics, Aging, Phenotype, Polymorphism, Single Nucleotide, Adult, Aged, Aged, 80 and over, Middle Aged, Female, Male, Genome-Wide Association Study, Genetics, Neurosciences, Human Genome, Brain Disorders, Biotechnology, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Neurological
Abstract

Cortical thickness, surface area and volumes vary with age and cognitive function, and in neurological and psychiatric diseases. Here we report heritability, genetic correlations and genome-wide associations of these cortical measures across the whole cortex, and in 34 anatomically predefined regions. Our discovery sample comprises 22,824 individuals from 20 cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank. We identify genetic heterogeneity between cortical measures and brain regions, and 160 genome-wide significant associations pointing to wnt/β-catenin, TGF-β and sonic hedgehog pathways. There is enrichment for genes involved in anthropometric traits, hindbrain development, vascular and neurodegenerative disease and psychiatric conditions. These data are a rich resource for studies of the biological mechanisms behind cortical development and aging.

Published
2020

9. Common Genetic Variation Indicates Separate Causes for Periventricular and Deep White Matter Hyperintensities

Author

Armstrong, Nicola J, Mather, Karen A, Sargurupremraj, Muralidharan, Knol, Maria J, Malik, Rainer, Satizabal, Claudia L, Yanek, Lisa R, Wen, Wei, Gudnason, Vilmundur G, Dueker, Nicole D, Elliott, Lloyd T, Hofer, Edith, Bis, Joshua, Jahanshad, Neda, Li, Shuo, Logue, Mark A, Luciano, Michelle, Scholz, Markus, Smith, Albert V, Trompet, Stella, Vojinovic, Dina, Xia, Rui, Alfaro-Almagro, Fidel, Ames, David, Amin, Najaf, Amouyel, Philippe, Beiser, Alexa S, Brodaty, Henry, Deary, Ian J, Fennema-Notestine, Christine, Gampawar, Piyush G, Gottesman, Rebecca, Griffanti, Ludovica, Jack, Clifford R, Jenkinson, Mark, Jiang, Jiyang, Kral, Brian G, Kwok, John B, Lampe, Leonie, C.M. Liewald, David, Maillard, Pauline, Marchini, Jonathan, Bastin, Mark E, Mazoyer, Bernard, Pirpamer, Lukas, Rafael Romero, José, Roshchupkin, Gennady V, Schofield, Peter R, Schroeter, Matthias L, Stott, David J, Thalamuthu, Anbupalam, Trollor, Julian, Tzourio, Christophe, van der Grond, Jeroen, Vernooij, Meike W, Witte, Veronica A, Wright, Margaret J, Yang, Qiong, Morris, Zoe, Siggurdsson, Siggi, Psaty, Bruce, Villringer, Arno, Schmidt, Helena, Haberg, Asta K, van Duijn, Cornelia M, Jukema, J Wouter, Dichgans, Martin, Sacco, Ralph L, Wright, Clinton B, Kremen, William S, Becker, Lewis C, Thompson, Paul M, Mosley, Thomas H, Wardlaw, Joanna M, Ikram, M Arfan, Adams, Hieab HH, Seshadri, Sudha, Sachdev, Perminder S, Smith, Stephen M, Launer, Lenore, Longstreth, William, DeCarli, Charles, Schmidt, Reinhold, Fornage, Myriam, Debette, Stephanie, and Nyquist, Paul A

Subjects
Epidemiology, Health Sciences, Brain Disorders, Biotechnology, Neurosciences, Cerebrovascular, Stroke, Neurodegenerative, Dementia, Vascular Cognitive Impairment/Dementia, Alzheimer's Disease Related Dementias (ADRD), Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Human Genome, Aging, Genetics, Acquired Cognitive Impairment, 2.1 Biological and endogenous factors, Aged, Brain, Cerebral Small Vessel Diseases, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Male, Middle Aged, White Matter, brain, genome-wide association study, neuroimaging, risk factors, white matter, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Neurology & Neurosurgery, Clinical sciences, Allied health and rehabilitation science
Abstract

Background and purposePeriventricular white matter hyperintensities (WMH; PVWMH) and deep WMH (DWMH) are regional classifications of WMH and reflect proposed differences in cause. In the first study, to date, we undertook genome-wide association analyses of DWMH and PVWMH to show that these phenotypes have different genetic underpinnings.MethodsParticipants were aged 45 years and older, free of stroke and dementia. We conducted genome-wide association analyses of PVWMH and DWMH in 26,654 participants from CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology), ENIGMA (Enhancing Neuro-Imaging Genetics Through Meta-Analysis), and the UKB (UK Biobank). Regional correlations were investigated using the genome-wide association analyses -pairwise method. Cross-trait genetic correlations between PVWMH, DWMH, stroke, and dementia were estimated using LDSC.ResultsIn the discovery and replication analysis, for PVWMH only, we found associations on chromosomes 2 (NBEAL), 10q23.1 (TSPAN14/FAM231A), and 10q24.33 (SH3PXD2A). In the much larger combined meta-analysis of all cohorts, we identified ten significant regions for PVWMH: chromosomes 2 (3 regions), 6, 7, 10 (2 regions), 13, 16, and 17q23.1. New loci of interest include 7q36.1 (NOS3) and 16q24.2. In both the discovery/replication and combined analysis, we found genome-wide significant associations for the 17q25.1 locus for both DWMH and PVWMH. Using gene-based association analysis, 19 genes across all regions were identified for PVWMH only, including the new genes: CALCRL (2q32.1), KLHL24 (3q27.1), VCAN (5q27.1), and POLR2F (22q13.1). Thirteen genes in the 17q25.1 locus were significant for both phenotypes. More extensive genetic correlations were observed for PVWMH with small vessel ischemic stroke. There were no associations with dementia for either phenotype.ConclusionsOur study confirms these phenotypes have distinct and also shared genetic architectures. Genetic analyses indicated PVWMH was more associated with ischemic stroke whilst DWMH loci were implicated in vascular, astrocyte, and neuronal function. Our study confirms these phenotypes are distinct neuroimaging classifications and identifies new candidate genes associated with PVWMH only.

Published
2020

10. Genetic architecture of subcortical brain structures in 38,851 individuals

Author

Satizabal, Claudia L, Adams, Hieab HH, Hibar, Derrek P, White, Charles C, Knol, Maria J, Stein, Jason L, Scholz, Markus, Sargurupremraj, Muralidharan, Jahanshad, Neda, Roshchupkin, Gennady V, Smith, Albert V, Bis, Joshua C, Jian, Xueqiu, Luciano, Michelle, Hofer, Edith, Teumer, Alexander, van der Lee, Sven J, Yang, Jingyun, Yanek, Lisa R, Lee, Tom V, Li, Shuo, Hu, Yanhui, Koh, Jia Yu, Eicher, John D, Desrivières, Sylvane, Arias-Vasquez, Alejandro, Chauhan, Ganesh, Athanasiu, Lavinia, Rentería, Miguel E, Kim, Sungeun, Hoehn, David, Armstrong, Nicola J, Chen, Qiang, Holmes, Avram J, den Braber, Anouk, Kloszewska, Iwona, Andersson, Micael, Espeseth, Thomas, Grimm, Oliver, Abramovic, Lucija, Alhusaini, Saud, Milaneschi, Yuri, Papmeyer, Martina, Axelsson, Tomas, Ehrlich, Stefan, Roiz-Santiañez, Roberto, Kraemer, Bernd, Håberg, Asta K, Jones, Hannah J, Pike, G Bruce, Stein, Dan J, Stevens, Allison, Bralten, Janita, Vernooij, Meike W, Harris, Tamara B, Filippi, Irina, Witte, A Veronica, Guadalupe, Tulio, Wittfeld, Katharina, Mosley, Thomas H, Becker, James T, Doan, Nhat Trung, Hagenaars, Saskia P, Saba, Yasaman, Cuellar-Partida, Gabriel, Amin, Najaf, Hilal, Saima, Nho, Kwangsik, Mirza-Schreiber, Nazanin, Arfanakis, Konstantinos, Becker, Diane M, Ames, David, Goldman, Aaron L, Lee, Phil H, Boomsma, Dorret I, Lovestone, Simon, Giddaluru, Sudheer, Le Hellard, Stephanie, Mattheisen, Manuel, Bohlken, Marc M, Kasperaviciute, Dalia, Schmaal, Lianne, Lawrie, Stephen M, Agartz, Ingrid, Walton, Esther, Tordesillas-Gutierrez, Diana, Davies, Gareth E, Shin, Jean, Ipser, Jonathan C, Vinke, Louis N, Hoogman, Martine, Jia, Tianye, Burkhardt, Ralph, Klein, Marieke, Crivello, Fabrice, Janowitz, Deborah, Carmichael, Owen, Haukvik, Unn K, Aribisala, Benjamin S, and Schmidt, Helena

Subjects
Biological Sciences, Genetics, Brain Disorders, Mental Health, Neurosciences, Human Genome, 2.1 Biological and endogenous factors, Neurological, Adult, Aged, Animals, Brain, Cohort Studies, Drosophila melanogaster, Genetic Variation, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Middle Aged, Neurodevelopmental Disorders, Organ Size, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

Published
2019

11. Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Author

Davies, Gail, Lam, Max, Harris, Sarah E, Trampush, Joey W, Luciano, Michelle, Hill, W David, Hagenaars, Saskia P, Ritchie, Stuart J, Marioni, Riccardo E, Fawns-Ritchie, Chloe, Liewald, David CM, Okely, Judith A, Ahola-Olli, Ari V, Barnes, Catriona LK, Bertram, Lars, Bis, Joshua C, Burdick, Katherine E, Christoforou, Andrea, DeRosse, Pamela, Djurovic, Srdjan, Espeseth, Thomas, Giakoumaki, Stella, Giddaluru, Sudheer, Gustavson, Daniel E, Hayward, Caroline, Hofer, Edith, Ikram, M Arfan, Karlsson, Robert, Knowles, Emma, Lahti, Jari, Leber, Markus, Li, Shuo, Mather, Karen A, Melle, Ingrid, Morris, Derek, Oldmeadow, Christopher, Palviainen, Teemu, Payton, Antony, Pazoki, Raha, Petrovic, Katja, Reynolds, Chandra A, Sargurupremraj, Muralidharan, Scholz, Markus, Smith, Jennifer A, Smith, Albert V, Terzikhan, Natalie, Thalamuthu, Anbupalam, Trompet, Stella, van der Lee, Sven J, Ware, Erin B, Windham, B Gwen, Wright, Margaret J, Yang, Jingyun, Yu, Jin, Ames, David, Amin, Najaf, Amouyel, Philippe, Andreassen, Ole A, Armstrong, Nicola J, Assareh, Amelia A, Attia, John R, Attix, Deborah, Avramopoulos, Dimitrios, Bennett, David A, Böhmer, Anne C, Boyle, Patricia A, Brodaty, Henry, Campbell, Harry, Cannon, Tyrone D, Cirulli, Elizabeth T, Congdon, Eliza, Conley, Emily Drabant, Corley, Janie, Cox, Simon R, Dale, Anders M, Dehghan, Abbas, Dick, Danielle, Dickinson, Dwight, Eriksson, Johan G, Evangelou, Evangelos, Faul, Jessica D, Ford, Ian, Freimer, Nelson A, Gao, He, Giegling, Ina, Gillespie, Nathan A, Gordon, Scott D, Gottesman, Rebecca F, Griswold, Michael E, Gudnason, Vilmundur, Harris, Tamara B, Hartmann, Annette M, Hatzimanolis, Alex, Heiss, Gerardo, Holliday, Elizabeth G, Joshi, Peter K, Kähönen, Mika, Kardia, Sharon LR, Karlsson, Ida, and Kleineidam, Luca

Abstract

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.

Published
2019

12. GWAS and colocalization analyses implicate carotid intima-media thickness and carotid plaque loci in cardiovascular outcomes.

Author

Franceschini, Nora, Giambartolomei, Claudia, de Vries, Paul S, Finan, Chris, Bis, Joshua C, Huntley, Rachael P, Lovering, Ruth C, Tajuddin, Salman M, Winkler, Thomas W, Graff, Misa, Kavousi, Maryam, Dale, Caroline, Smith, Albert V, Hofer, Edith, van Leeuwen, Elisabeth M, Nolte, Ilja M, Lu, Lingyi, Scholz, Markus, Sargurupremraj, Muralidharan, Pitkänen, Niina, Franzén, Oscar, Joshi, Peter K, Noordam, Raymond, Marioni, Riccardo E, Hwang, Shih-Jen, Musani, Solomon K, Schminke, Ulf, Palmas, Walter, Isaacs, Aaron, Correa, Adolfo, Zonderman, Alan B, Hofman, Albert, Teumer, Alexander, Cox, Amanda J, Uitterlinden, André G, Wong, Andrew, Smit, Andries J, Newman, Anne B, Britton, Annie, Ruusalepp, Arno, Sennblad, Bengt, Hedblad, Bo, Pasaniuc, Bogdan, Penninx, Brenda W, Langefeld, Carl D, Wassel, Christina L, Tzourio, Christophe, Fava, Cristiano, Baldassarre, Damiano, O'Leary, Daniel H, Teupser, Daniel, Kuh, Diana, Tremoli, Elena, Mannarino, Elmo, Grossi, Enzo, Boerwinkle, Eric, Schadt, Eric E, Ingelsson, Erik, Veglia, Fabrizio, Rivadeneira, Fernando, Beutner, Frank, Chauhan, Ganesh, Heiss, Gerardo, Snieder, Harold, Campbell, Harry, Völzke, Henry, Markus, Hugh S, Deary, Ian J, Jukema, J Wouter, de Graaf, Jacqueline, Price, Jacqueline, Pott, Janne, Hopewell, Jemma C, Liang, Jingjing, Thiery, Joachim, Engmann, Jorgen, Gertow, Karl, Rice, Kenneth, Taylor, Kent D, Dhana, Klodian, Kiemeney, Lambertus ALM, Lind, Lars, Raffield, Laura M, Launer, Lenore J, Holdt, Lesca M, Dörr, Marcus, Dichgans, Martin, Traylor, Matthew, Sitzer, Matthias, Kumari, Meena, Kivimaki, Mika, Nalls, Mike A, Melander, Olle, Raitakari, Olli, Franco, Oscar H, Rueda-Ochoa, Oscar L, Roussos, Panos, Whincup, Peter H, Amouyel, Philippe, and Giral, Philippe

Subjects
MEGASTROKE Consortium, Humans, Coronary Disease, Genetic Predisposition to Disease, Amino Acid Oxidoreductases, Protein-Lysine 6-Oxidase, Risk Factors, Lod Score, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Genome-Wide Association Study, Plaque, Atherosclerotic, Carotid Intima-Media Thickness, ADAMTS9 Protein, Plaque, Atherosclerotic, Polymorphism, Single Nucleotide
Abstract

Carotid artery intima media thickness (cIMT) and carotid plaque are measures of subclinical atherosclerosis associated with ischemic stroke and coronary heart disease (CHD). Here, we undertake meta-analyses of genome-wide association studies (GWAS) in 71,128 individuals for cIMT, and 48,434 individuals for carotid plaque traits. We identify eight novel susceptibility loci for cIMT, one independent association at the previously-identified PINX1 locus, and one novel locus for carotid plaque. Colocalization analysis with nearby vascular expression quantitative loci (cis-eQTLs) derived from arterial wall and metabolic tissues obtained from patients with CHD identifies candidate genes at two potentially additional loci, ADAMTS9 and LOXL4. LD score regression reveals significant genetic correlations between cIMT and plaque traits, and both cIMT and plaque with CHD, any stroke subtype and ischemic stroke. Our study provides insights into genes and tissue-specific regulatory mechanisms linking atherosclerosis both to its functional genomic origins and its clinical consequences in humans.

Published
2018

13. Genome-wide association study of 23,500 individuals identifies 7 loci associated with brain ventricular volume.

Author

Vojinovic, Dina, Adams, Hieab H, Jian, Xueqiu, Yang, Qiong, Smith, Albert Vernon, Bis, Joshua C, Teumer, Alexander, Scholz, Markus, Armstrong, Nicola J, Hofer, Edith, Saba, Yasaman, Luciano, Michelle, Bernard, Manon, Trompet, Stella, Yang, Jingyun, Gillespie, Nathan A, van der Lee, Sven J, Neumann, Alexander, Ahmad, Shahzad, Andreassen, Ole A, Ames, David, Amin, Najaf, Arfanakis, Konstantinos, Bastin, Mark E, Becker, Diane M, Beiser, Alexa S, Beyer, Frauke, Brodaty, Henry, Bryan, R Nick, Bülow, Robin, Dale, Anders M, De Jager, Philip L, Deary, Ian J, DeCarli, Charles, Fleischman, Debra A, Gottesman, Rebecca F, van der Grond, Jeroen, Gudnason, Vilmundur, Harris, Tamara B, Homuth, Georg, Knopman, David S, Kwok, John B, Lewis, Cora E, Li, Shuo, Loeffler, Markus, Lopez, Oscar L, Maillard, Pauline, El Marroun, Hanan, Mather, Karen A, Mosley, Thomas H, Muetzel, Ryan L, Nauck, Matthias, Nyquist, Paul A, Panizzon, Matthew S, Pausova, Zdenka, Psaty, Bruce M, Rice, Ken, Rotter, Jerome I, Royle, Natalie, Satizabal, Claudia L, Schmidt, Reinhold, Schofield, Peter R, Schreiner, Pamela J, Sidney, Stephen, Stott, David J, Thalamuthu, Anbupalam, Uitterlinden, Andre G, Valdés Hernández, Maria C, Vernooij, Meike W, Wen, Wei, White, Tonya, Witte, A Veronica, Wittfeld, Katharina, Wright, Margaret J, Yanek, Lisa R, Tiemeier, Henning, Kremen, William S, Bennett, David A, Jukema, J Wouter, Paus, Tomas, Wardlaw, Joanna M, Schmidt, Helena, Sachdev, Perminder S, Villringer, Arno, Grabe, Hans Jörgen, Longstreth, WT, van Duijn, Cornelia M, Launer, Lenore J, Seshadri, Sudha, Ikram, M Arfan, and Fornage, Myriam

Subjects
Lateral Ventricles, Humans, Organ Size, Genome, Human, Aged, Middle Aged, Genome-Wide Association Study, Human Genome, Aging, Genetics, 2.1 Biological and endogenous factors, Neurological
Abstract

The volume of the lateral ventricles (LV) increases with age and their abnormal enlargement is a key feature of several neurological and psychiatric diseases. Although lateral ventricular volume is heritable, a comprehensive investigation of its genetic determinants is lacking. In this meta-analysis of genome-wide association studies of 23,533 healthy middle-aged to elderly individuals from 26 population-based cohorts, we identify 7 genetic loci associated with LV volume. These loci map to chromosomes 3q28, 7p22.3, 10p12.31, 11q23.1, 12q23.3, 16q24.2, and 22q13.1 and implicate pathways related to tau pathology, S1P signaling, and cytoskeleton organization. We also report a significant genetic overlap between the thalamus and LV volumes (ρgenetic = -0.59, p-value = 3.14 × 10-6), suggesting that these brain structures may share a common biology. These genetic associations of LV volume provide insights into brain morphology.

Published
2018

14. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Author

Davies, Gail, Lam, Max, Harris, Sarah E, Trampush, Joey W, Luciano, Michelle, Hill, W David, Hagenaars, Saskia P, Ritchie, Stuart J, Marioni, Riccardo E, Fawns-Ritchie, Chloe, Liewald, David CM, Okely, Judith A, Ahola-Olli, Ari V, Barnes, Catriona LK, Bertram, Lars, Bis, Joshua C, Burdick, Katherine E, Christoforou, Andrea, DeRosse, Pamela, Djurovic, Srdjan, Espeseth, Thomas, Giakoumaki, Stella, Giddaluru, Sudheer, Gustavson, Daniel E, Hayward, Caroline, Hofer, Edith, Ikram, M Arfan, Karlsson, Robert, Knowles, Emma, Lahti, Jari, Leber, Markus, Li, Shuo, Mather, Karen A, Melle, Ingrid, Morris, Derek, Oldmeadow, Christopher, Palviainen, Teemu, Payton, Antony, Pazoki, Raha, Petrovic, Katja, Reynolds, Chandra A, Sargurupremraj, Muralidharan, Scholz, Markus, Smith, Jennifer A, Smith, Albert V, Terzikhan, Natalie, Thalamuthu, Anbupalam, Trompet, Stella, van der Lee, Sven J, Ware, Erin B, Windham, B Gwen, Wright, Margaret J, Yang, Jingyun, Yu, Jin, Ames, David, Amin, Najaf, Amouyel, Philippe, Andreassen, Ole A, Armstrong, Nicola J, Assareh, Amelia A, Attia, John R, Attix, Deborah, Avramopoulos, Dimitrios, Bennett, David A, Böhmer, Anne C, Boyle, Patricia A, Brodaty, Henry, Campbell, Harry, Cannon, Tyrone D, Cirulli, Elizabeth T, Congdon, Eliza, Conley, Emily Drabant, Corley, Janie, Cox, Simon R, Dale, Anders M, Dehghan, Abbas, Dick, Danielle, Dickinson, Dwight, Eriksson, Johan G, Evangelou, Evangelos, Faul, Jessica D, Ford, Ian, Freimer, Nelson A, Gao, He, Giegling, Ina, Gillespie, Nathan A, Gordon, Scott D, Gottesman, Rebecca F, Griswold, Michael E, Gudnason, Vilmundur, Harris, Tamara B, Hartmann, Annette M, Hatzimanolis, Alex, Heiss, Gerardo, Holliday, Elizabeth G, Joshi, Peter K, Kähönen, Mika, Kardia, Sharon LR, Karlsson, Ida, and Kleineidam, Luca

Subjects
Humans, Neurodegenerative Diseases, Genetic Predisposition to Disease, Cognition, Reaction Time, Mental Disorders, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Young Adult, Genetic Loci, Neurodevelopmental Disorders, Prevention, Behavioral and Social Science, Mental Health, Neurosciences, Biotechnology, Genetics, Human Genome, Neurological, Mental health
Abstract

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P

Published
2018

15. Population-genetic comparison of the Sorbian isolate population in Germany with the German KORA population using genome-wide SNP arrays

Author

Gross, Arnd, Tönjes, Anke, Kovacs, Peter, Veeramah, Krishna R, Ahnert, Peter, Roshyara, Nab R, Gieger, Christian, Rueckert, Ina-Maria, Loeffler, Markus, Stoneking, Mark, Wichmann, Heinz-Erich, Novembre, John, Stumvoll, Michael, and Scholz, Markus

Abstract

Abstract Background The Sorbs are an ethnic minority in Germany with putative genetic isolation, making the population interesting for disease mapping. A sample of N = 977 Sorbs is currently analysed in several genome-wide meta-analyses. Since genetic differences between populations are a major confounding factor in genetic meta-analyses, we compare the Sorbs with the German outbred population of the KORA F3 study (N = 1644) and other publically available European HapMap populations by population genetic means. We also aim to separate effects of over-sampling of families in the Sorbs sample from effects of genetic isolation and compare the power of genetic association studies between the samples. Results The degree of relatedness was significantly higher in the Sorbs. Principal components analysis revealed a west to east clustering of KORA individuals born in Germany, KORA individuals born in Poland or Czech Republic, Half-Sorbs (less than four Sorbian grandparents) and Full-Sorbs. The Sorbs cluster is nearest to the cluster of KORA individuals born in Poland. The number of rare SNPs is significantly higher in the Sorbs sample. FST between KORA and Sorbs is an order of magnitude higher than between different regions in Germany. Compared to the other populations, Sorbs show a higher proportion of individuals with runs of homozygosity between 2.5 Mb and 5 Mb. Linkage disequilibrium (LD) at longer range is also slightly increased but this has no effect on the power of association studies. Oversampling of families in the Sorbs sample causes detectable bias regarding higher FST values and higher LD but the effect is an order of magnitude smaller than the observed differences between KORA and Sorbs. Relatedness in the Sorbs also influenced the power of uncorrected association analyses. Conclusions Sorbs show signs of genetic isolation which cannot be explained by over-sampling of relatives, but the effects are moderate in size. The Slavonic origin of the Sorbs is still genetically detectable. Regarding LD structure, a clear advantage for genome-wide association studies cannot be deduced. The significant amount of cryptic relatedness in the Sorbs sample results in inflated variances of Beta-estimators which should be considered in genetic association analyses.

Published
2011

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