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1. Insights into Uromodulin and Blood Pressure

Author: Zhou, Manshi, Mary, Sheon, Delles, Christian, Padmanabhan, Sandosh, Graham, Delyth, McBride, Martin W., and Dominiczak, Anna F.
Published: 2024
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2. Genetic insights into resting heart rate and its role in cardiovascular disease.

Author: van de Vegte, Yordi, Eppinga, Ruben, van der Ende, M, Hagemeijer, Yanick, Mahendran, Yuvaraj, Salfati, Elias, Smith, Albert, Tan, Vanessa, Arking, Dan, Ntalla, Ioanna, Appel, Emil, Schurmann, Claudia, Brody, Jennifer, Rueedi, Rico, Polasek, Ozren, Sveinbjornsson, Gardar, Lecoeur, Cecile, Ladenvall, Claes, Zhao, Jing, Isaacs, Aaron, Wang, Lihua, Luan, Jianan, Hwang, Shih-Jen, Mononen, Nina, Auro, Kirsi, Jackson, Anne, Bielak, Lawrence, Zeng, Linyao, Shah, Nabi, Nethander, Maria, Campbell, Archie, Rankinen, Tuomo, Pechlivanis, Sonali, Qi, Lu, Zhao, Wei, Rizzi, Federica, Tanaka, Toshiko, Robino, Antonietta, Cocca, Massimiliano, Lange, Leslie, Müller-Nurasyid, Martina, Roselli, Carolina, Zhang, Weihua, Kleber, Marcus, Guo, Xiuqing, Lin, Henry, Pavani, Francesca, Galesloot, Tessel, Noordam, Raymond, Milaneschi, Yuri, Schraut, Katharina, den Hoed, Marcel, Degenhardt, Frauke, Trompet, Stella, van den Berg, Marten, Pistis, Giorgio, Tham, Yih-Chung, Weiss, Stefan, Sim, Xueling, Li, Hengtong, van der Most, Peter, Nolte, Ilja, Lyytikäinen, Leo-Pekka, Said, M, Witte, Daniel, Iribarren, Carlos, Launer, Lenore, Ring, Susan, de Vries, Paul, Sever, Peter, Linneberg, Allan, Bottinger, Erwin, Padmanabhan, Sandosh, Psaty, Bruce, Sotoodehnia, Nona, Kolcic, Ivana, Arnar, David, Gudbjartsson, Daniel, Holm, Hilma, Balkau, Beverley, Silva, Claudia, Newton-Cheh, Christopher, Nikus, Kjell, Salo, Perttu, Mohlke, Karen, Peyser, Patricia, Schunkert, Heribert, Lorentzon, Mattias, Lahti, Jari, Rao, Dabeeru, Cornelis, Marilyn, Faul, Jessica, Smith, Jennifer, Stolarz-Skrzypek, Katarzyna, Bandinelli, Stefania, Concas, Maria, Sinagra, Gianfranco, Meitinger, Thomas, Waldenberger, Melanie, and Sinner, Moritz
Subjects: Humans, Cardiovascular Diseases, Risk Factors, Heart Rate, Genetic Predisposition to Disease, Atrial Fibrillation, Mendelian Randomization Analysis, Genome-Wide Association Study, Polymorphism, Single Nucleotide
Abstract: Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.
Published: 2023

3. Genome‐Wide Interaction Analyses of Serum Calcium on Ventricular Repolarization Time in 125 393 Participants

Author: William J. Young, Peter J. van der Most, Traci M. Bartz, Maxime M. Bos, Ginevra Biino, ThuyVy Duong, Luisa Foco, Jesus T. Lominchar, Martina Müller‐Nurasyid, Giuseppe Giovanni Nardone, Alessandro Pecori, Julia Ramirez, Linda Repetto, Katharina Schramm, Xia Shen, Stefan van Duijvenboden, Diana van Heemst, Stefan Weiss, Jie Yao, Jan‐Walter Benjamins, Alvaro Alonso, Beatrice Spedicati, Mary L. Biggs, Jennifer A. Brody, Marcus Dörr, Christian Fuchsberger, Martin Gögele, Xiuqing Guo, M. Arfan Ikram, J. Wouter Jukema, Stefan Kääb, Jørgen K. Kanters, Henry J. Lin, Allan Linneberg, Matthias Nauck, Ilja M. Nolte, Giulia Pianigiani, Aurora Santin, Elsayed Z. Soliman, Paola Tesolin, Simona Vaccargiu, Melanie Waldenberger, Pim van der Harst, Niek Verweij, Dan E. Arking, Maria Pina Concas, Alessandro De Grandi, Giorgia Girotto, Niels Grarup, Maryam Kavousi, Dennis O. Mook‐Kanamori, Pau Navarro, Michele Orini, Sandosh Padmanabhan, Cristian Pattaro, Annette Peters, Mario Pirastu, Peter P. Pramstaller, Susan R. Heckbert, Mortiz Sinner, Harold Snieder, Uwe Völker, James F. Wilson, W. James Gauderman, Pier D. Lambiase, Nona Sotoodehnia, Andrew Tinker, Helen R. Warren, Raymond Noordam, and Patricia B. Munroe
Subjects: calcium, ECG intervals, gene‐lifestyle interaction, genome‐wide association study, ventricular repolarization, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background Ventricular repolarization time (ECG QT and JT intervals) is associated with malignant arrhythmia. Genome‐wide association studies have identified 230 independent loci for QT and JT; however, 50% of their heritability remains unexplained. Previous work supports a causal effect of lower serum calcium concentrations on longer ventricular repolarization time. We hypothesized calcium interactions with QT and JT variant associations could explain a proportion of the missing heritability. Methods and Results We performed genome‐wide calcium interaction analyses for QT and JT intervals. Participants were stratified by their calcium level relative to the study distribution (top or bottom 20%). We performed a 2‐stage analysis (genome‐wide discovery [N=62 532] and replication [N=59 861] of lead variants) and a single‐stage genome‐wide meta‐analysis (N=122 393, [European ancestry N=117 581, African ancestry N=4812]). We also calculated 2‐degrees of freedom joint main and interaction and 1‐degree of freedom interaction P values. In 2‐stage and single‐stage analyses, 50 and 98 independent loci, respectively, were associated with either QT or JT intervals (2‐degrees of freedom joint main and interaction P value
Published: 2024
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4. Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease.

Author: Young, William J, Haessler, Jeffrey, Benjamins, Jan-Walter, Repetto, Linda, Yao, Jie, Isaacs, Aaron, Harper, Andrew R, Ramirez, Julia, Garnier, Sophie, van Duijvenboden, Stefan, Baldassari, Antoine R, Concas, Maria Pina, Duong, ThuyVy, Foco, Luisa, Isaksen, Jonas L, Mei, Hao, Noordam, Raymond, Nursyifa, Casia, Richmond, Anne, Santolalla, Meddly L, Sitlani, Colleen M, Soroush, Negin, Thériault, Sébastien, Trompet, Stella, Aeschbacher, Stefanie, Ahmadizar, Fariba, Alonso, Alvaro, Brody, Jennifer A, Campbell, Archie, Correa, Adolfo, Darbar, Dawood, De Luca, Antonio, Deleuze, Jean-François, Ellervik, Christina, Fuchsberger, Christian, Goel, Anuj, Grace, Christopher, Guo, Xiuqing, Hansen, Torben, Heckbert, Susan R, Jackson, Rebecca D, Kors, Jan A, Lima-Costa, Maria Fernanda, Linneberg, Allan, Macfarlane, Peter W, Morrison, Alanna C, Navarro, Pau, Porteous, David J, Pramstaller, Peter P, Reiner, Alexander P, Risch, Lorenz, Schotten, Ulrich, Shen, Xia, Sinagra, Gianfranco, Soliman, Elsayed Z, Stoll, Monika, Tarazona-Santos, Eduardo, Tinker, Andrew, Trajanoska, Katerina, Villard, Eric, Warren, Helen R, Whitsel, Eric A, Wiggins, Kerri L, Arking, Dan E, Avery, Christy L, Conen, David, Girotto, Giorgia, Grarup, Niels, Hayward, Caroline, Jukema, J Wouter, Mook-Kanamori, Dennis O, Olesen, Morten Salling, Padmanabhan, Sandosh, Psaty, Bruce M, Pattaro, Cristian, Ribeiro, Antonio Luiz P, Rotter, Jerome I, Stricker, Bruno H, van der Harst, Pim, van Duijn, Cornelia M, Verweij, Niek, Wilson, James G, Orini, Michele, Charron, Philippe, Watkins, Hugh, Kooperberg, Charles, Lin, Henry J, Wilson, James F, Kanters, Jørgen K, Sotoodehnia, Nona, Mifsud, Borbala, Lambiase, Pier D, Tereshchenko, Larisa G, and Munroe, Patricia B
Subjects: Humans, Cardiovascular Diseases, Electrocardiography, Risk Factors, Arrhythmias, Cardiac, Atrioventricular Block, Genome-Wide Association Study, Biomarkers, Human Genome, Cardiovascular, Genetics, Heart Disease
Abstract: The 3-dimensional spatial and 2-dimensional frontal QRS-T angles are measures derived from the vectorcardiogram. They are independent risk predictors for arrhythmia, but the underlying biology is unknown. Using multi-ancestry genome-wide association studies we identify 61 (58 previously unreported) loci for the spatial QRS-T angle (N = 118,780) and 11 for the frontal QRS-T angle (N = 159,715). Seven out of the 61 spatial QRS-T angle loci have not been reported for other electrocardiographic measures. Enrichments are observed in pathways related to cardiac and vascular development, muscle contraction, and hypertrophy. Pairwise genome-wide association studies with classical ECG traits identify shared genetic influences with PR interval and QRS duration. Phenome-wide scanning indicate associations with atrial fibrillation, atrioventricular block and arterial embolism and genetically determined QRS-T angle measures are associated with fascicular and bundle branch block (and also atrioventricular block for the frontal QRS-T angle). We identify potential biology involved in the QRS-T angle and their genetic relationships with cardiovascular traits and diseases, may inform future research and risk prediction.
Published: 2023

5. The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

Author: Rahmioglu, Nilufer, Mortlock, Sally, Ghiasi, Marzieh, Møller, Peter L, Stefansdottir, Lilja, Galarneau, Geneviève, Turman, Constance, Danning, Rebecca, Law, Matthew H, Sapkota, Yadav, Christofidou, Paraskevi, Skarp, Sini, Giri, Ayush, Banasik, Karina, Krassowski, Michal, Lepamets, Maarja, Marciniak, Błażej, Nõukas, Margit, Perro, Danielle, Sliz, Eeva, Sobalska-Kwapis, Marta, Thorleifsson, Gudmar, Topbas-Selcuki, Nura F, Vitonis, Allison, Westergaard, David, Arnadottir, Ragnheidur, Burgdorf, Kristoffer S, Campbell, Archie, Cheuk, Cecilia SK, Clementi, Caterina, Cook, James, De Vivo, Immaculata, DiVasta, Amy, Dorien, O, Donoghue, Jacqueline F, Edwards, Todd, Fontanillas, Pierre, Fung, Jenny N, Geirsson, Reynir T, Girling, Jane E, Harkki, Paivi, Harris, Holly R, Healey, Martin, Heikinheimo, Oskari, Holdsworth-Carson, Sarah, Hostettler, Isabel C, Houlden, Henry, Houshdaran, Sahar, Irwin, Juan C, Jarvelin, Marjo-Riitta, Kamatani, Yoichiro, Kennedy, Stephen H, Kepka, Ewa, Kettunen, Johannes, Kubo, Michiaki, Kulig, Bartosz, Kurra, Venla, Laivuori, Hannele, Laufer, Marc R, Lindgren, Cecilia M, MacGregor, Stuart, Mangino, Massimo, Martin, Nicholas G, Matalliotaki, Charoula, Matalliotakis, Michail, Murray, Alison D, Ndungu, Anne, Nezhat, Camran, Olsen, Catherine M, Opoku-Anane, Jessica, Padmanabhan, Sandosh, Paranjpe, Manish, Peters, Maire, Polak, Grzegorz, Porteous, David J, Rabban, Joseph, Rexrode, Kathyrn M, Romanowicz, Hanna, Saare, Merli, Saavalainen, Liisu, Schork, Andrew J, Sen, Sushmita, Shafrir, Amy L, Siewierska-Górska, Anna, Słomka, Marcin, Smith, Blair H, Smolarz, Beata, Szaflik, Tomasz, Szyłło, Krzysztof, Takahashi, Atsushi, Terry, Kathryn L, Tomassetti, Carla, Treloar, Susan A, Vanhie, Arne, Vincent, Katy, Vo, Kim C, Werring, David J, Zeggini, Eleftheria, Zervou, Maria I, and Adachi, Sosuke
Subjects: Biological Sciences, Genetics, Contraception/Reproduction, Clinical Research, Endometriosis, Prevention, Pain Research, Chronic Pain, Infertility, 2.1 Biological and endogenous factors, Aetiology, Female, Humans, Genetic Predisposition to Disease, Genome-Wide Association Study, Pain, Comorbidity, DBDS Genomic Consortium, FinnGen Study, FinnGen Endometriosis Taskforce, Celmatix Research Team, 23andMe Research Team, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract: Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention.
Published: 2023

6. The Association Between Severe Mental Illness and Receipt of Acute Cardiac Care for Myocardial Infarction, and the Impact of the COVID-19 Pandemic

Author: Kelly Fleetwood, Stewart Mercer, Sandosh Padmanabhan, Daniel Smith, and Caroline Jackson
Subjects: Psychiatry, RC435-571
Abstract: Aims To compare receipt of acute cardiac care in people with versus without severe mental illness (SMI) and investigate the impact of the COVID-19 pandemic on any differences in care. We hypothesised that, compared with those without SMI, patients with an SMI are less likely to receive guideline recommended acute cardiac care and that disparities worsened as a result of the pandemic. Methods We conducted a cohort study using data from the CVD-COVID-UK resource, which links electronic health data from multiple sources. Our cohort included 95,125 adults with a non-ST-elevation MI (NSTEMI) recorded in the Myocardial Infarction National Audit Programme (MINAP) dataset between 1 November 2019 and 31 March 2022. We defined SMI as schizophrenia, schizoaffective disorders or bipolar disorder (BD), ascertained through recorded diagnosis in primary care or hospital admission records. We examined receipt of cardiac care standards for NSTEMI, including: admission to a cardiac ward; angiogram eligibility; receipt of angiogram (in those eligible); angiogram within 72 hours; secondary prevention medication prescribing at discharge, and arrangement of post-discharge cardiac rehabilitation. We used logistic regression to obtain odds ratios (ORs) for the association between SMI and receipt of each care indicator, adjusting for age, sex and time period. We tested for an interaction between SMI and time period in order to determine if any disparities had changed since the start of the COVID-19 pandemic. Results Within our cohort, 620 patients (0.6%) had schizophrenia and 575 (0.6%) had BD. Compared with people without SMI and after adjusting for age, sex and period, patients with an SMI were less likely to receive each of the cardiac care standards. For example, compared with those without SMI, those with SMI were less likely to: be admitted to a cardiac ward (schizophrenia: OR 0.72, 95% CI 0.61–0.85; BD: 0.74, 95% CI 0.63–0.88); be eligible for an angiogram (schizophrenia: 0.37, 95% CI 0.29–0.47; BD: 0.52, 95% CI 0.40–0.68); receive an angiogram (schizophrenia: 0.22, 95% CI 0.18–0.28; BD: 0.51, 95% CI 0.39–0.66); and receive an angiogram within 72 hours (schizophrenia: 0.71, 95% CI 0.56–0.90); BD: 0.80, 95% CI 0.64–1.00). We generally found no evidence that disparities had changed since the start of the COVID-19 pandemic. Conclusion We identified marked SMI disparities in receipt of acute cardiac care among people treated in hospital for a NSTEMI. Further research should seek to identify reasons for, and inform interventions to, address these disparities.
Published: 2024
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7. Acute Cardiac Care for People With Severe Mental Illness Following a Myocardial Infarction Among People With a Severe Mental Illness: A Qualitative Study

Author: Amanda Vettini, Debbie Cavers, Sandosh Padmanabhan, Daniel Smith, and Caroline Jackson
Subjects: Psychiatry, RC435-571
Abstract: Aims To understand the challenges and barriers experienced by health-care professionals (HCPs) in providing acute cardiac care to patients with severe mental illness (SMI) (schizophrenia, bipolar disorder or severe depression) admitted to hospital following a myocardial infarction (MI). Methods Semi-structured 1:1 videocall interviews with 12 HCPs in two central-Scotland Health Boards involved in delivering pre-/hospital acute care for a MI (paramedics, cardiology/A&E nurses, cardiology/A&E doctors). Interviewee recruitment was via clinical and research networks and newsletters e.g. the Scottish Ambulance Service, the Royal College of Nursing and Royal College of Physicians and through professional connections. Interviews were audio-recorded, transcribed verbatim and analysed thematically drawing on Braun & Clarke and using NVivo software. Results HCPs identified a number of challenges/barriers to providing optimal post-MI acute cardiac care to patients with a SMI across 3 key themes: patient-related; practitioner-related and system/environment-related. Core patient-related challenges/barriers included: diminished patient history capacities especially relating to chronology; the time-consuming nature of effective HCP-patient communication and engagement; medication and intervention concordance concerns and challenging patient behaviour including physical and verbal aggression or severe distress. Practitioner-related challenges/barriers were: fears of appropriately managing patient behaviour; stigma towards patients with a SMI (putatively arising from knowledge deficits or generational/age-related effects); staff burnout due to length of service and pressures from extreme workloads. Systemic issues included insufficient staffing precluding the additional time required for effective communication and the distressing nature of hospital environments for patients with a SMI. Side rooms were not routinely available even though these were identified as improving the environment for some patients. A core systemic finding, cited by all interviewees, was the lack of adequate training provision on caring for patients with a SMI. Additional system-level findings were degrees of challenges accessing input from the hospital psychiatric team especially outwith standard hours and problems obtaining rarer psychiatric medications potentially impacting patients’ mental health stability. Positive findings included that HCPs are generally enthusiastic about providing high quality care to this patient group and to seek help with this. Some HCPs indicated that caring for mentally stable patients with a SMI does not differ from the general population. Conclusion Although HCPs aspired to providing optimal acute cardiac care for this patient group, patient-level, professional and systemic barriers often make this challenging. A key area for improvement is enhancing staff training in caring for patients with SMI, ideally delivered in-person.
Published: 2024
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8. Genetic insights into resting heart rate and its role in cardiovascular disease

Author: Yordi J. van de Vegte, Ruben N. Eppinga, M. Yldau van der Ende, Yanick P. Hagemeijer, Yuvaraj Mahendran, Elias Salfati, Albert V. Smith, Vanessa Y. Tan, Dan E. Arking, Ioanna Ntalla, Emil V. Appel, Claudia Schurmann, Jennifer A. Brody, Rico Rueedi, Ozren Polasek, Gardar Sveinbjornsson, Cecile Lecoeur, Claes Ladenvall, Jing Hua Zhao, Aaron Isaacs, Lihua Wang, Jian’an Luan, Shih-Jen Hwang, Nina Mononen, Kirsi Auro, Anne U. Jackson, Lawrence F. Bielak, Linyao Zeng, Nabi Shah, Maria Nethander, Archie Campbell, Tuomo Rankinen, Sonali Pechlivanis, Lu Qi, Wei Zhao, Federica Rizzi, Toshiko Tanaka, Antonietta Robino, Massimiliano Cocca, Leslie Lange, Martina Müller-Nurasyid, Carolina Roselli, Weihua Zhang, Marcus E. Kleber, Xiuqing Guo, Henry J. Lin, Francesca Pavani, Tessel E. Galesloot, Raymond Noordam, Yuri Milaneschi, Katharina E. Schraut, Marcel den Hoed, Frauke Degenhardt, Stella Trompet, Marten E. van den Berg, Giorgio Pistis, Yih-Chung Tham, Stefan Weiss, Xueling S. Sim, Hengtong L. Li, Peter J. van der Most, Ilja M. Nolte, Leo-Pekka Lyytikäinen, M. Abdullah Said, Daniel R. Witte, Carlos Iribarren, Lenore Launer, Susan M. Ring, Paul S. de Vries, Peter Sever, Allan Linneberg, Erwin P. Bottinger, Sandosh Padmanabhan, Bruce M. Psaty, Nona Sotoodehnia, Ivana Kolcic, The DCCT/EDIC Research Group, David O. Arnar, Daniel F. Gudbjartsson, Hilma Holm, Beverley Balkau, Claudia T. Silva, Christopher H. Newton-Cheh, Kjell Nikus, Perttu Salo, Karen L. Mohlke, Patricia A. Peyser, Heribert Schunkert, Mattias Lorentzon, Jari Lahti, Dabeeru C. Rao, Marilyn C. Cornelis, Jessica D. Faul, Jennifer A. Smith, Katarzyna Stolarz-Skrzypek, Stefania Bandinelli, Maria Pina Concas, Gianfranco Sinagra, Thomas Meitinger, Melanie Waldenberger, Moritz F. Sinner, Konstantin Strauch, Graciela E. Delgado, Kent D. Taylor, Jie Yao, Luisa Foco, Olle Melander, Jacqueline de Graaf, Renée de Mutsert, Eco J. C. de Geus, Åsa Johansson, Peter K. Joshi, Lars Lind, Andre Franke, Peter W. Macfarlane, Kirill V. Tarasov, Nicholas Tan, Stephan B. Felix, E-Shyong Tai, Debra Q. Quek, Harold Snieder, Johan Ormel, Martin Ingelsson, Cecilia Lindgren, Andrew P. Morris, Olli T. Raitakari, Torben Hansen, Themistocles Assimes, Vilmundur Gudnason, Nicholas J. Timpson, Alanna C. Morrison, Patricia B. Munroe, David P. Strachan, Niels Grarup, Ruth J. F. Loos, Susan R. Heckbert, Peter Vollenweider, Caroline Hayward, Kari Stefansson, Philippe Froguel, Leif Groop, Nicholas J. Wareham, Cornelia M. van Duijn, Mary F. Feitosa, Christopher J. O’Donnell, Mika Kähönen, Markus Perola, Michael Boehnke, Sharon L. R. Kardia, Jeanette Erdmann, Colin N. A. Palmer, Claes Ohlsson, David J. Porteous, Johan G. Eriksson, Claude Bouchard, Susanne Moebus, Peter Kraft, David R. Weir, Daniele Cusi, Luigi Ferrucci, Sheila Ulivi, Giorgia Girotto, Adolfo Correa, Stefan Kääb, Annette Peters, John C. Chambers, Jaspal S. Kooner, Winfried März, Jerome I. Rotter, Andrew A. Hicks, J. Gustav Smith, Lambertus A. L. M. Kiemeney, Dennis O. Mook-Kanamori, Brenda W. J. H. Penninx, Ulf Gyllensten, James F. Wilson, Stephen Burgess, Johan Sundström, Wolfgang Lieb, J. Wouter Jukema, Mark Eijgelsheim, Edward L. M. Lakatta, Ching-Yu Cheng, Marcus Dörr, Tien-Yin Wong, Charumathi Sabanayagam, Albertine J. Oldehinkel, Harriette Riese, Terho Lehtimäki, Niek Verweij, and Pim van der Harst
Subjects: Science
Abstract: Abstract Resting heart rate is associated with cardiovascular diseases and mortality in observational and Mendelian randomization studies. The aims of this study are to extend the number of resting heart rate associated genetic variants and to obtain further insights in resting heart rate biology and its clinical consequences. A genome-wide meta-analysis of 100 studies in up to 835,465 individuals reveals 493 independent genetic variants in 352 loci, including 68 genetic variants outside previously identified resting heart rate associated loci. We prioritize 670 genes and in silico annotations point to their enrichment in cardiomyocytes and provide insights in their ECG signature. Two-sample Mendelian randomization analyses indicate that higher genetically predicted resting heart rate increases risk of dilated cardiomyopathy, but decreases risk of developing atrial fibrillation, ischemic stroke, and cardio-embolic stroke. We do not find evidence for a linear or non-linear genetic association between resting heart rate and all-cause mortality in contrast to our previous Mendelian randomization study. Systematic alteration of key differences between the current and previous Mendelian randomization study indicates that the most likely cause of the discrepancy between these studies arises from false positive findings in previous one-sample MR analyses caused by weak-instrument bias at lower P-value thresholds. The results extend our understanding of resting heart rate biology and give additional insights in its role in cardiovascular disease development.
Published: 2023
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9. OPTIMA-BP: empOwering PaTients in MAnaging Blood Pressure – protocol for a randomised parallel group study comparing use of Kvatchii web-based patient education portal as an addition to home blood pressure monitoring

Author: Sandosh Padmanabhan, Stefanie Lip, Linsay Mccallum, Maggie Rostron, Rebecca Hanna, Nukman Bin Pg Md Salimin, and Sarah Nichol
Subjects: Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Introduction Hypertension is the leading modifiable risk factor for cardiovascular disease and is implicated in half of all strokes and myocardial infarctions. One-third of the adults in Scotland have hypertension yet only a quarter of them have their blood pressure (BP) controlled to target (
Published: 2024
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10. Genetic architecture of spatial electrical biomarkers for cardiac arrhythmia and relationship with cardiovascular disease

Author: William J. Young, Jeffrey Haessler, Jan-Walter Benjamins, Linda Repetto, Jie Yao, Aaron Isaacs, Andrew R. Harper, Julia Ramirez, Sophie Garnier, Stefan van Duijvenboden, Antoine R. Baldassari, Maria Pina Concas, ThuyVy Duong, Luisa Foco, Jonas L. Isaksen, Hao Mei, Raymond Noordam, Casia Nursyifa, Anne Richmond, Meddly L. Santolalla, Colleen M. Sitlani, Negin Soroush, Sébastien Thériault, Stella Trompet, Stefanie Aeschbacher, Fariba Ahmadizar, Alvaro Alonso, Jennifer A. Brody, Archie Campbell, Adolfo Correa, Dawood Darbar, Antonio De Luca, Jean-François Deleuze, Christina Ellervik, Christian Fuchsberger, Anuj Goel, Christopher Grace, Xiuqing Guo, Torben Hansen, Susan R. Heckbert, Rebecca D. Jackson, Jan A. Kors, Maria Fernanda Lima-Costa, Allan Linneberg, Peter W. Macfarlane, Alanna C. Morrison, Pau Navarro, David J. Porteous, Peter P. Pramstaller, Alexander P. Reiner, Lorenz Risch, Ulrich Schotten, Xia Shen, Gianfranco Sinagra, Elsayed Z. Soliman, Monika Stoll, Eduardo Tarazona-Santos, Andrew Tinker, Katerina Trajanoska, Eric Villard, Helen R. Warren, Eric A. Whitsel, Kerri L. Wiggins, Dan E. Arking, Christy L. Avery, David Conen, Giorgia Girotto, Niels Grarup, Caroline Hayward, J.Wouter Jukema, Dennis O. Mook-Kanamori, Morten Salling Olesen, Sandosh Padmanabhan, Bruce M. Psaty, Cristian Pattaro, Antonio Luiz P. Ribeiro, Jerome I. Rotter, Bruno H. Stricker, Pim van der Harst, Cornelia M. van Duijn, Niek Verweij, James G. Wilson, Michele Orini, Philippe Charron, Hugh Watkins, Charles Kooperberg, Henry J. Lin, James F. Wilson, Jørgen K. Kanters, Nona Sotoodehnia, Borbala Mifsud, Pier D. Lambiase, Larisa G. Tereshchenko, and Patricia B. Munroe
Subjects: Science
Abstract: The spatial and frontal QRS-T angles are electrocardiographic (ECG) predictors for arrhythmia. This work used genetic analyses to identify associated loci and pathways, and explore their relationships with other ECG traits and cardiovascular disease.
Published: 2023
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11. Potential Applications of Artificial Intelligence (AI) in Managing Polypharmacy in Saudi Arabia: A Narrative Review

Author: Safaa M. Alsanosi and Sandosh Padmanabhan
Subjects: artificial intelligence, polypharmacy, Saudi Arabia, medication prescription, Medicine
Abstract: Prescribing medications is a fundamental practice in the management of illnesses that necessitates in-depth knowledge of clinical pharmacology. Polypharmacy, or the concurrent use of multiple medications by individuals with complex health conditions, poses significant challenges, including an increased risk of drug interactions and adverse reactions. The Saudi Vision 2030 prioritises enhancing healthcare quality and safety, including addressing polypharmacy. Artificial intelligence (AI) offers promising tools to optimise medication plans, predict adverse drug reactions and ensure drug safety. This review explores AI’s potential to revolutionise polypharmacy management in Saudi Arabia, highlighting practical applications, challenges and the path forward for the integration of AI solutions into healthcare practices.
Published: 2024
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12. Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci

Author: Lisa de las Fuentes, Karen L. Schwander, Michael R. Brown, Amy R. Bentley, Thomas W. Winkler, Yun Ju Sung, Patricia B. Munroe, Clint L. Miller, Hugo Aschard, Stella Aslibekyan, Traci M. Bartz, Lawrence F. Bielak, Jin Fang Chai, Ching-Yu Cheng, Rajkumar Dorajoo, Mary F. Feitosa, Xiuqing Guo, Fernando P. Hartwig, Andrea Horimoto, Ivana Kolčić, Elise Lim, Yongmei Liu, Alisa K. Manning, Jonathan Marten, Solomon K. Musani, Raymond Noordam, Sandosh Padmanabhan, Tuomo Rankinen, Melissa A. Richard, Paul M. Ridker, Albert V. Smith, Dina Vojinovic, Alan B. Zonderman, Maris Alver, Mathilde Boissel, Kaare Christensen, Barry I. Freedman, Chuan Gao, Franco Giulianini, Sarah E. Harris, Meian He, Fang-Chi Hsu, Brigitte Kühnel, Federica Laguzzi, Xiaoyin Li, Leo-Pekka Lyytikäinen, Ilja M. Nolte, Alaitz Poveda, Rainer Rauramaa, Muhammad Riaz, Antonietta Robino, Tamar Sofer, Fumihiko Takeuchi, Bamidele O. Tayo, Peter J. van der Most, Niek Verweij, Erin B. Ware, Stefan Weiss, Wanqing Wen, Lisa R. Yanek, Yiqiang Zhan, Najaf Amin, Dan E. Arking, Christie Ballantyne, Eric Boerwinkle, Jennifer A. Brody, Ulrich Broeckel, Archie Campbell, Mickaël Canouil, Xiaoran Chai, Yii-Der Ida Chen, Xu Chen, Kumaraswamy Naidu Chitrala, Maria Pina Concas, Ulf de Faire, Renée de Mutsert, H. Janaka de Silva, Paul S. de Vries, Ahn Do, Jessica D. Faul, Virginia Fisher, James S. Floyd, Terrence Forrester, Yechiel Friedlander, Giorgia Girotto, C. Charles Gu, Göran Hallmans, Sami Heikkinen, Chew-Kiat Heng, Georg Homuth, Steven Hunt, M. Arfan Ikram, David R. Jacobs, Maryam Kavousi, Chiea Chuen Khor, Tuomas O. Kilpeläinen, Woon-Puay Koh, Pirjo Komulainen, Carl D. Langefeld, Jingjing Liang, Kiang Liu, Jianjun Liu, Kurt Lohman, Reedik Mägi, Ani W. Manichaikul, Colin A. McKenzie, Thomas Meitinger, Yuri Milaneschi, Matthias Nauck, Christopher P. Nelson, Jeffrey R. O’Connell, Nicholette D. Palmer, Alexandre C. Pereira, Thomas Perls, Annette Peters, Ozren Polašek, Olli T. Raitakari, Kenneth Rice, Treva K. Rice, Stephen S. Rich, Charumathi Sabanayagam, Pamela J. Schreiner, Xiao-Ou Shu, Stephen Sidney, Mario Sims, Jennifer A. Smith, John M. Starr, Konstantin Strauch, E. Shyong Tai, Kent D. Taylor, Michael Y. Tsai, André G. Uitterlinden, Diana van Heemst, Melanie Waldenberger, Ya-Xing Wang, Wen-Bin Wei, Gregory Wilson, Deng Xuan, Jie Yao, Caizheng Yu, Jian-Min Yuan, Wei Zhao, Diane M. Becker, Amélie Bonnefond, Donald W. Bowden, Richard S. Cooper, Ian J. Deary, Jasmin Divers, Tõnu Esko, Paul W. Franks, Philippe Froguel, Christian Gieger, Jost B. Jonas, Norihiro Kato, Timo A. Lakka, Karin Leander, Terho Lehtimäki, Patrik K. E. Magnusson, Kari E. North, Ioanna Ntalla, Brenda Penninx, Nilesh J. Samani, Harold Snieder, Beatrice Spedicati, Pim van der Harst, Henry Völzke, Lynne E. Wagenknecht, David R. Weir, Mary K. Wojczynski, Tangchun Wu, Wei Zheng, Xiaofeng Zhu, Claude Bouchard, Daniel I. Chasman, Michele K. Evans, Ervin R. Fox, Vilmundur Gudnason, Caroline Hayward, Bernardo L. Horta, Sharon L. R. Kardia, Jose Eduardo Krieger, Dennis O. Mook-Kanamori, Patricia A. Peyser, Michael M. Province, Bruce M. Psaty, Igor Rudan, Xueling Sim, Blair H. Smith, Rob M. van Dam, Cornelia M. van Duijn, Tien Yin Wong, Donna K. Arnett, Dabeeru C. Rao, James Gauderman, Ching-Ti Liu, Alanna C. Morrison, Jerome I. Rotter, and Myriam Fornage
Subjects: educational attainment, lipids, cholesterol, triglycerides, genome-wide association study, meta-analysis, Genetics, QH426-470
Abstract: Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes.Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: “Some College” (yes/no, for any education beyond high school) and “Graduated College” (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10−8) and suggestive (p < 1 × 10−6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals).Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue.Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.
Published: 2023
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13. Large-scale exome array summary statistics resources for glycemic traits to aid effector gene prioritization [version 1; peer review: 2 approved]

Author: Natasha H. J. Ng, Sara M. Willems, Jian'an Luan, Rebecca S. Fine, Juan Fernandez, Jennifer Wessel, Eleanor Wheeler, Gaelle Marenne, Hidetoshi Kitajima, Hanieh Yaghootkar, Xueling Sim, Ian J. Deary, Sai Chen, Shuai Wang, Yii-Der Ida Chen, Caroline Hayward, Yuning Chen, Jennifer L. Asimit, Claudia Langenberg, Tibor V. Varga, Archie Campbell, Rona J. Strawbridge, Shuang Feng, Tarunveer S. Ahluwalia, Erica L. Kleinbrink, Emil V. Appel, Ping An, Lawrence F. Bielak, Dan E. Arking, Jennifer A. Brody, Nathan A. Bihlmeyer, David Porteous, Ayse Demirkan, Audrey Y. Chu, Franco Giulianini, James S. Floyd, Stefan Gustafsson, Xiuqing Guo, Johanna Jakobsdottir, Anne U. Jackson, Stavroula Kanoni, Richard A. Jensen, Igor Rudan, Man Li, Sirkka Keinanen-Kiukaanniemi, Alisa K. Manning, Yingchang Lu, Karina Meidtner, Jonathan Marten, Giorgio Pistis, Taulant Muka, Kenneth M. Rice, Bram Prins, Albert Vernon Smith, Serena Sanna, Lorraine Southam, Jennifer A. Smith, Vinicius Tragante, Heather M. Stringham, Helen R. Warren, Sander W. van der Laan, Andrianos M. Yiorkas, Jie Yao, Wei Zhao, Weihua Zhang, Heather M. Highland, Mariaelisa Graff, Eirini Marouli, Anne E. Justice, Wesam A. Alhejily, Saima Afaq, Folkert W. Asselbergs, Najaf Amin, Michiel L. Bots, Lori L. Bonnycastle, Ji Chen, Ivan Brandslund, Abbas Dehghan, John Danesh, Tapani Ebeling, Jessica D. Faul, Aliki-Eleni Farmaki, Steve Franks, Paul W. Franks, Anette P. Gjesing, Andreas Fritsche, Göran Hallmans, Mark O. Goodarzi, Karl-Heinz Herzig, Tamara B. Harris, Min A Jhun, Marie-France Hivert, Marit E. Jørgensen, Torben Jørgensen, Eero Kajantie, Pekka Jousilahti, Sharon L.R. Kardia, Maria Karaleftheri, Heikki A. Koistinen, Leena Kinnunen, Peter Kovacs, Pirjo Komulainen, Markku Laakso, Johanna Kuusisto, Aaron Leong, Lenore J. Launer, Jocelyn E. Manning Fox, Jaana Lindström, Nisa M. Maruthur, Satu Männistö, Antonella Mulas, Leena Moilanen, Matthew Neville, Mike A. Nalls, Alison Pattie, James S. Pankow, Hannu Puolijoki, Eva R.B. Petersen, Paul Redmond, Asif Rasheed, Michael Roden, Frida Renström, Juha Saltevo, Danish Saleheen, Sylvain Sebert, Kai Savonen, Alena Stančáková, Kerrin S. Small, Konstantin Strauch, Jakob Stokholm, Betina H. Thuesen, Juha Auvinen, E-Shyong Tai, Emmanouil Tsafantakis, Anke Tönjes, Jaakko Tuomilehto, Tiinamaija Tuomi, Marja Vääräsmäki, Matti Uusitupa, Magdalena Zoledziewska, Ilonca Vaartjes, Beverley Balkau, Goncalo Abecasis, Alexandra I. Blakemore, Hans Bisgaard, Heiner Boeing, Ruth J.F. Loos, Matthias Blüher, Klaus Bønnelykke, Eric Boerwinkle, Mark J. Caulfield, Erwin P. Bottinger, Daniel I. Chasman, John C. Chambers, Francis S. Collins, Ching-Yu Cheng, Francesco Cucca, Josef Coresh, George Dedoussis, Gert J. de Borst, Hester M. den Ruijter, Panos Deloukas, Ele Ferrannini, Michele K. Evans, Harald Grallert, Oscar H. Franco, Arfan Ikram, Joel N. Hirschhorn, Fredrik Karpe, Erik Ingelsson, Wieland Kiess, Carolina Medina-Gomez, Kay-Tee Kaw, Antje Körner, Jaspal S. Kooner, Cecilia M. Lindgren, Timo Lakka, Ching-Ti Liu, Leonard Lipovich, Patrick E. MacDonald, Jun Liu, Andrew D. Morris, Karen L. Mohlke, Alison Murray, Patricia B. Munroe, Gerard Pasterkamp, Colin N. A . Palmer, Patricia A. Peyser, Oluf Pedersen, Paul M. Ridker, Rainer Rauramaa, Patrik Rorsman, Olov Rolandsson, Veikko Salomaa, Frits R. Rosendaal, Robert Sladek, Matthias B. Schulze, Michael Stumvoll, Timothy D. Spector, Mark Walker, Cornelia M. van Duijn, David R. Weir, Nick J. Wareham, Tien Yin Wong, James G. Wilson, Alan B. Zonderman, Eleftheria Zeggini, Andrew P. Morris, Jerome I. Rotter, Jose C. Florez, Michael Boehnke, James B. Meigs, Mark I. McCarthy, Robert A. Scott, Anubha Mahajan, Inês Barroso, Anna L. Gloyn, Michael A. Province, Niels Grarup, Ruifang Li-Gao, Jette Bork-Jensen, Yongmei Liu, Allan Linneberg, Leslie A. Lange, Sandosh Padmanabhan, Gail Davies, Lars Lind, Bruce M. Psaty, Tea Skaaby, Torben Hansen, Ozren Polasek, John M. Starr, Dennis O. Mook-Kanamori, Vilmundur Gudnason, Kent D. Taylor, Marjo-Riitta Järvelin, Renée de Mutsert, Paul Elliott, Josée Dupuis, Blair H. Smith, and Andrew T. Hattersley
Subjects: exome chip, glycaemic traits, genetic discovery, effector genes, summary statistics resources, eng, Medicine, Science
Abstract: Background Genome-wide association studies for glycemic traits have identified hundreds of loci associated with these biomarkers of glucose homeostasis. Despite this success, the challenge remains to link variant associations to genes, and underlying biological pathways. Methods To identify coding variant associations which may pinpoint effector genes at both novel and previously established genome-wide association loci, we performed meta-analyses of exome-array studies for four glycemic traits: glycated hemoglobin (HbA1c, up to 144,060 participants), fasting glucose (FG, up to 129,665 participants), fasting insulin (FI, up to 104,140) and 2hr glucose post-oral glucose challenge (2hGlu, up to 57,878). In addition, we performed network and pathway analyses. Results Single-variant and gene-based association analyses identified coding variant associations at more than 60 genes, which when combined with other datasets may be useful to nominate effector genes. Network and pathway analyses identified pathways related to insulin secretion, zinc transport and fatty acid metabolism. HbA1c associations were strongly enriched in pathways related to blood cell biology. Conclusions Our results provided novel glycemic trait associations and highlighted pathways implicated in glycemic regulation. Exome-array summary statistic results are being made available to the scientific community to enable further discoveries.
Published: 2023
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14. Genetic Determinants of Electrocardiographic P-Wave Duration and Relation to Atrial Fibrillation

Author: Weng, Lu-Chen, Hall, Amelia Weber, Choi, Seung Hoan, Jurgens, Sean J, Haessler, Jeffrey, Bihlmeyer, Nathan A, Grarup, Niels, Lin, Honghuang, Teumer, Alexander, Li-Gao, Ruifang, Yao, Jie, Guo, Xiuqing, Brody, Jennifer A, Müller-Nurasyid, Martina, Schramm, Katharina, Verweij, Niek, van den Berg, Marten E, van Setten, Jessica, Isaacs, Aaron, Ramírez, Julia, Warren, Helen R, Padmanabhan, Sandosh, Kors, Jan A, de Boer, Rudolf A, van der Meer, Peter, Sinner, Moritz F, Waldenberger, Melanie, Psaty, Bruce M, Taylor, Kent D, Völker, Uwe, Kanters, Jørgen K, Li, Man, Alonso, Alvaro, Perez, Marco V, Vaartjes, Ilonca, Bots, Michiel L, Huang, Paul L, Heckbert, Susan R, Lin, Henry J, Kornej, Jelena, Munroe, Patricia B, van Duijn, Cornelia M, Asselbergs, Folkert W, Stricker, Bruno H, van der Harst, Pim, Kääb, Stefan, Peters, Annette, Sotoodehnia, Nona, Rotter, Jerome I, Mook-Kanamori, Dennis O, Dörr, Marcus, Felix, Stephan B, Linneberg, Allan, Hansen, Torben, Arking, Dan E, Kooperberg, Charles, Benjamin, Emelia J, Lunetta, Kathryn L, Ellinor, Patrick T, and Lubitz, Steven A
Subjects: Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Research, Genetics, Heart Disease, Cardiovascular, Human Genome, 2.1 Biological and endogenous factors, Aetiology, Atrial Fibrillation, Cardiac Myosins, Connectin, Electrocardiography, Genetic Variation, Genome-Wide Association Study, Homeodomain Proteins, Humans, Myosin Heavy Chains, NAV1.8 Voltage-Gated Sodium Channel, Quantitative Trait Loci, Transcription Factors, atrial fibrillation, electrophysiology, exome, genetic, genome-wide association studies, population, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract: BackgroundThe P-wave duration (PWD) is an electrocardiographic measurement that represents cardiac conduction in the atria. Shortened or prolonged PWD is associated with atrial fibrillation (AF). We used exome-chip data to examine the associations between common and rare variants with PWD.MethodsFifteen studies comprising 64 440 individuals (56 943 European, 5681 African, 1186 Hispanic, 630 Asian) and ≈230 000 variants were used to examine associations with maximum PWD across the 12-lead ECG. Meta-analyses summarized association results for common variants; gene-based burden and sequence kernel association tests examined low-frequency variant-PWD associations. Additionally, we examined the associations between PWD loci and AF using previous AF genome-wide association studies.ResultsWe identified 21 common and low-frequency genetic loci (14 novel) associated with maximum PWD, including several AF loci (TTN, CAND2, SCN10A, PITX2, CAV1, SYNPO2L, SOX5, TBX5, MYH6, RPL3L). The top variants at known sarcomere genes (TTN, MYH6) were associated with longer PWD and increased AF risk. However, top variants at other loci (eg, PITX2 and SCN10A) were associated with longer PWD but lower AF risk.ConclusionsOur results highlight multiple novel genetic loci associated with PWD, and underscore the shared mechanisms of atrial conduction and AF. Prolonged PWD may be an endophenotype for several different genetic mechanisms of AF.
Published: 2020

15. Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction.

Author: Ntalla, Ioanna, Weng, Lu-Chen, Cartwright, James H, Hall, Amelia Weber, Sveinbjornsson, Gardar, Tucker, Nathan R, Choi, Seung Hoan, Chaffin, Mark D, Roselli, Carolina, Barnes, Michael R, Mifsud, Borbala, Warren, Helen R, Hayward, Caroline, Marten, Jonathan, Cranley, James J, Concas, Maria Pina, Gasparini, Paolo, Boutin, Thibaud, Kolcic, Ivana, Polasek, Ozren, Rudan, Igor, Araujo, Nathalia M, Lima-Costa, Maria Fernanda, Ribeiro, Antonio Luiz P, Souza, Renan P, Tarazona-Santos, Eduardo, Giedraitis, Vilmantas, Ingelsson, Erik, Mahajan, Anubha, Morris, Andrew P, Del Greco M, Fabiola, Foco, Luisa, Gögele, Martin, Hicks, Andrew A, Cook, James P, Lind, Lars, Lindgren, Cecilia M, Sundström, Johan, Nelson, Christopher P, Riaz, Muhammad B, Samani, Nilesh J, Sinagra, Gianfranco, Ulivi, Sheila, Kähönen, Mika, Mishra, Pashupati P, Mononen, Nina, Nikus, Kjell, Caulfield, Mark J, Dominiczak, Anna, Padmanabhan, Sandosh, Montasser, May E, O'Connell, Jeff R, Ryan, Kathleen, Shuldiner, Alan R, Aeschbacher, Stefanie, Conen, David, Risch, Lorenz, Thériault, Sébastien, Hutri-Kähönen, Nina, Lehtimäki, Terho, Lyytikäinen, Leo-Pekka, Raitakari, Olli T, Barnes, Catriona LK, Campbell, Harry, Joshi, Peter K, Wilson, James F, Isaacs, Aaron, Kors, Jan A, van Duijn, Cornelia M, Huang, Paul L, Gudnason, Vilmundur, Harris, Tamara B, Launer, Lenore J, Smith, Albert V, Bottinger, Erwin P, Loos, Ruth JF, Nadkarni, Girish N, Preuss, Michael H, Correa, Adolfo, Mei, Hao, Wilson, James, Meitinger, Thomas, Müller-Nurasyid, Martina, Peters, Annette, Waldenberger, Melanie, Mangino, Massimo, Spector, Timothy D, Rienstra, Michiel, van de Vegte, Yordi J, van der Harst, Pim, Verweij, Niek, Kääb, Stefan, Schramm, Katharina, Sinner, Moritz F, Strauch, Konstantin, Cutler, Michael J, Fatkin, Diane, London, Barry, Olesen, Morten, and Roden, Dan M
Subjects: Humans, Cardiovascular Diseases, Genetic Predisposition to Disease, Electrocardiography, Gene Expression, Multifactorial Inheritance, Quantitative Trait Loci, Female, Male, Arrhythmias, Cardiac, Genetic Variation, Genome-Wide Association Study, Genetic Loci, Endophenotypes, Arrhythmias, Cardiac
Abstract: The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.
Published: 2020

16. Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways

Author: William J. Young, Najim Lahrouchi, Aaron Isaacs, ThuyVy Duong, Luisa Foco, Farah Ahmed, Jennifer A. Brody, Reem Salman, Raymond Noordam, Jan-Walter Benjamins, Jeffrey Haessler, Leo-Pekka Lyytikäinen, Linda Repetto, Maria Pina Concas, Marten E. van den Berg, Stefan Weiss, Antoine R. Baldassari, Traci M. Bartz, James P. Cook, Daniel S. Evans, Rebecca Freudling, Oliver Hines, Jonas L. Isaksen, Honghuang Lin, Hao Mei, Arden Moscati, Martina Müller-Nurasyid, Casia Nursyifa, Yong Qian, Anne Richmond, Carolina Roselli, Kathleen A. Ryan, Eduardo Tarazona-Santos, Sébastien Thériault, Stefan van Duijvenboden, Helen R. Warren, Jie Yao, Dania Raza, Stefanie Aeschbacher, Gustav Ahlberg, Alvaro Alonso, Laura Andreasen, Joshua C. Bis, Eric Boerwinkle, Archie Campbell, Eulalia Catamo, Massimiliano Cocca, Michael J. Cutler, Dawood Darbar, Alessandro De Grandi, Antonio De Luca, Jun Ding, Christina Ellervik, Patrick T. Ellinor, Stephan B. Felix, Philippe Froguel, Christian Fuchsberger, Martin Gögele, Claus Graff, Mariaelisa Graff, Xiuqing Guo, Torben Hansen, Susan R. Heckbert, Paul L. Huang, Heikki V. Huikuri, Nina Hutri-Kähönen, M. Arfan Ikram, Rebecca D. Jackson, Juhani Junttila, Maryam Kavousi, Jan A. Kors, Thiago P. Leal, Rozenn N. Lemaitre, Henry J. Lin, Lars Lind, Allan Linneberg, Simin Liu, Peter W. MacFarlane, Massimo Mangino, Thomas Meitinger, Massimo Mezzavilla, Pashupati P. Mishra, Rebecca N. Mitchell, Nina Mononen, May E. Montasser, Alanna C. Morrison, Matthias Nauck, Victor Nauffal, Pau Navarro, Kjell Nikus, Guillaume Pare, Kristen K. Patton, Giulia Pelliccione, Alan Pittman, David J. Porteous, Peter P. Pramstaller, Michael H. Preuss, Olli T. Raitakari, Alexander P. Reiner, Antonio Luiz P. Ribeiro, Kenneth M. Rice, Lorenz Risch, David Schlessinger, Ulrich Schotten, Claudia Schurmann, Xia Shen, M. Benjamin Shoemaker, Gianfranco Sinagra, Moritz F. Sinner, Elsayed Z. Soliman, Monika Stoll, Konstantin Strauch, Kirill Tarasov, Kent D. Taylor, Andrew Tinker, Stella Trompet, André Uitterlinden, Uwe Völker, Henry Völzke, Melanie Waldenberger, Lu-Chen Weng, Eric A. Whitsel, James G. Wilson, Christy L. Avery, David Conen, Adolfo Correa, Francesco Cucca, Marcus Dörr, Sina A. Gharib, Giorgia Girotto, Niels Grarup, Caroline Hayward, Yalda Jamshidi, Marjo-Riitta Järvelin, J. Wouter Jukema, Stefan Kääb, Mika Kähönen, Jørgen K. Kanters, Charles Kooperberg, Terho Lehtimäki, Maria Fernanda Lima-Costa, Yongmei Liu, Ruth J. F. Loos, Steven A. Lubitz, Dennis O. Mook-Kanamori, Andrew P. Morris, Jeffrey R. O’Connell, Morten Salling Olesen, Michele Orini, Sandosh Padmanabhan, Cristian Pattaro, Annette Peters, Bruce M. Psaty, Jerome I. Rotter, Bruno Stricker, Pim van der Harst, Cornelia M. van Duijn, Niek Verweij, James F. Wilson, Dan E. Arking, Julia Ramirez, Pier D. Lambiase, Nona Sotoodehnia, Borbala Mifsud, Christopher Newton-Cheh, and Patricia B. Munroe
Subjects: Science
Abstract: The QT interval is a heritable electrocardiographic measure associated with arrhythmia risk when prolonged. Here, the authors used a series of genetic analyses to identify genetic loci, pathways, therapeutic targets, and relationships with cardiovascular disease.
Published: 2022
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17. Underrepresentation of ethnic minorities in hypertension research—a survey of enablers and barriers among South Asian and African communities in Glasgow

Author: Stefanie Lip, Georgia Dempster, Sahil Jain, Katriona Brooksbank, Nazim Ghouri, Linsay McCallum, and Sandosh Padmanabhan
Subjects: Blood pressure, Blood pressure measurement, Ethnic minorities, Hypertension, Public engagement, South Asian, Medicine (General), R5-920
Abstract: Abstract Background Hypertension is the biggest contributor to the global cardiovascular burden with evidence for ethnic differences in treatment response and outcomes. Under-representation of ethnic minorities in clinical research is well known, and despite wide-ranging public engagement events by the Glasgow Blood Pressure Clinic team, there was a lack of participation of ethnic minorities in both engagement activities and clinical trials conducted by them. This study aims to explore the awareness and knowledge of hypertension and the facilitators and barriers to participation in hypertension clinical research among South Asian (SA) and African (AFR) communities in Glasgow. Methods A survey questionnaire was co-developed with representatives from South Asian (SA) and African (AFR) patients and community members in Glasgow to understand awareness and knowledge of hypertension and enablers and barriers to participation in clinical research. The survey was distributed to adults (aged > 18) years of SA or AFR ancestry at public engagement events at venues that were frequently visited by these two communities in Glasgow. Results The survey response rate was 337 (67.4%) consisting of 242 (71.8%) South Asian (SA) and 56 (16.9%) African (AFR) respondents. Thirty-nine questionnaires were excluded because of incompletion. Most of the respondents were not born in the UK and were in the 35–53-year group (AFR 29 (51%), SA 113 (47%)). The proportion living in the most deprived (SIMD 1) and least deprived (SIMD 5) was respectively 26 (12.4%) and 34 (16.2%) for SA and 20 (42.6%) and 2 (4.3%) for AFR. There was a considerable recognition that treatment needs to be ethnicity-specific (SA/AFR = 107 (48%)/23 (45.1%)) and that current cardiovascular disease treatment guidelines were not tailored for different ethnicities 84 (38.5%)/23 (45.1%). The key enablers encouraging research participation are enhanced health information, conducting aspects of their clinical research visits/appointments at a location they frequently visited and allowing a family member to accompany them. Barriers included concerns about the use of personal information and side effects of the new treatment. Conclusion Our survey confirmed enablers and barriers to ethnic minority participation in research. We find improving and evolving awareness and beliefs among the ethnic minority population including community leaders. Thus, continual review of researchers’ beliefs and attitudes is also essential to ensure engagement activities keep up with these changing perceptions.
Published: 2022
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18. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

Author: Thomas W. Winkler, Humaira Rasheed, Alexander Teumer, Mathias Gorski, Bryce X. Rowan, Kira J. Stanzick, Laurent F. Thomas, Adrienne Tin, Anselm Hoppmann, Audrey Y. Chu, Bamidele Tayo, Chris H. L. Thio, Daniele Cusi, Jin-Fang Chai, Karsten B. Sieber, Katrin Horn, Man Li, Markus Scholz, Massimiliano Cocca, Matthias Wuttke, Peter J. van der Most, Qiong Yang, Sahar Ghasemi, Teresa Nutile, Yong Li, Giulia Pontali, Felix Günther, Abbas Dehghan, Adolfo Correa, Afshin Parsa, Agnese Feresin, Aiko P. J. de Vries, Alan B. Zonderman, Albert V. Smith, Albertine J. Oldehinkel, Alessandro De Grandi, Alexander R. Rosenkranz, Andre Franke, Andrej Teren, Andres Metspalu, Andrew A. Hicks, Andrew P. Morris, Anke Tönjes, Anna Morgan, Anna I. Podgornaia, Annette Peters, Antje Körner, Anubha Mahajan, Archie Campbell, Barry I. Freedman, Beatrice Spedicati, Belen Ponte, Ben Schöttker, Ben Brumpton, Bernhard Banas, Bernhard K. Krämer, Bettina Jung, Bjørn Olav Åsvold, Blair H. Smith, Boting Ning, Brenda W. J. H. Penninx, Brett R. Vanderwerff, Bruce M. Psaty, Candace M. Kammerer, Carl D. Langefeld, Caroline Hayward, Cassandra N. Spracklen, Cassianne Robinson-Cohen, Catharina A. Hartman, Cecilia M. Lindgren, Chaolong Wang, Charumathi Sabanayagam, Chew-Kiat Heng, Chiara Lanzani, Chiea-Chuen Khor, Ching-Yu Cheng, Christian Fuchsberger, Christian Gieger, Christian M. Shaffer, Christina-Alexandra Schulz, Cristen J. Willer, Daniel I. Chasman, Daniel F. Gudbjartsson, Daniela Ruggiero, Daniela Toniolo, Darina Czamara, David J. Porteous, Dawn M. Waterworth, Deborah Mascalzoni, Dennis O. Mook-Kanamori, Dermot F. Reilly, E. Warwick Daw, Edith Hofer, Eric Boerwinkle, Erika Salvi, Erwin P. Bottinger, E-Shyong Tai, Eulalia Catamo, Federica Rizzi, Feng Guo, Fernando Rivadeneira, Franco Guilianini, Gardar Sveinbjornsson, Georg Ehret, Gerard Waeber, Ginevra Biino, Giorgia Girotto, Giorgio Pistis, Girish N. Nadkarni, Graciela E. Delgado, Grant W. Montgomery, Harold Snieder, Harry Campbell, Harvey D. White, He Gao, Heather M. Stringham, Helena Schmidt, Hengtong Li, Hermann Brenner, Hilma Holm, Holgen Kirsten, Holly Kramer, Igor Rudan, Ilja M. Nolte, Ioanna Tzoulaki, Isleifur Olafsson, Jade Martins, James P. Cook, James F. Wilson, Jan Halbritter, Janine F. Felix, Jasmin Divers, Jaspal S. Kooner, Jeannette Jen-Mai Lee, Jeffrey O’Connell, Jerome I. Rotter, Jianjun Liu, Jie Xu, Joachim Thiery, Johan Ärnlöv, Johanna Kuusisto, Johanna Jakobsdottir, Johanne Tremblay, John C. Chambers, John B. Whitfield, John M. Gaziano, Jonathan Marten, Josef Coresh, Jost B. Jonas, Josyf C. Mychaleckyj, Kaare Christensen, Kai-Uwe Eckardt, Karen L. Mohlke, Karlhans Endlich, Katalin Dittrich, Kathleen A. Ryan, Kenneth M. Rice, Kent D. Taylor, Kevin Ho, Kjell Nikus, Koichi Matsuda, Konstantin Strauch, Kozeta Miliku, Kristian Hveem, Lars Lind, Lars Wallentin, Laura M. Yerges-Armstrong, Laura M. Raffield, Lawrence S. Phillips, Lenore J. Launer, Leo-Pekka Lyytikäinen, Leslie A. Lange, Lorena Citterio, Lucija Klaric, M. Arfan Ikram, Marcus Ising, Marcus E. Kleber, Margherita Francescatto, Maria Pina Concas, Marina Ciullo, Mario Piratsu, Marju Orho-Melander, Markku Laakso, Markus Loeffler, Markus Perola, Martin H. de Borst, Martin Gögele, Martina La Bianca, Mary Ann Lukas, Mary F. Feitosa, Mary L. Biggs, Mary K. Wojczynski, Maryam Kavousi, Masahiro Kanai, Masato Akiyama, Masayuki Yasuda, Matthias Nauck, Melanie Waldenberger, Miao-Li Chee, Miao-Ling Chee, Michael Boehnke, Michael H. Preuss, Michael Stumvoll, Michael A. Province, Michele K. Evans, Michelle L. O’Donoghue, Michiaki Kubo, Mika Kähönen, Mika Kastarinen, Mike A. Nalls, Mikko Kuokkanen, Mohsen Ghanbari, Murielle Bochud, Navya Shilpa Josyula, Nicholas G. Martin, Nicholas Y. Q. Tan, Nicholette D. Palmer, Nicola Pirastu, Nicole Schupf, Niek Verweij, Nina Hutri-Kähönen, Nina Mononen, Nisha Bansal, Olivier Devuyst, Olle Melander, Olli T. Raitakari, Ozren Polasek, Paolo Manunta, Paolo Gasparini, Pashupati P. Mishra, Patrick Sulem, Patrik K. E. Magnusson, Paul Elliott, Paul M. Ridker, Pavel Hamet, Per O. Svensson, Peter K. Joshi, Peter Kovacs, Peter P. Pramstaller, Peter Rossing, Peter Vollenweider, Pim van der Harst, Rajkumar Dorajoo, Ralene Z. H. Sim, Ralph Burkhardt, Ran Tao, Raymond Noordam, Reedik Mägi, Reinhold Schmidt, Renée de Mutsert, Rico Rueedi, Rob M. van Dam, Robert J. Carroll, Ron T. Gansevoort, Ruth J. F. Loos, Sala Cinzia Felicita, Sanaz Sedaghat, Sandosh Padmanabhan, Sandra Freitag-Wolf, Sarah A. Pendergrass, Sarah E. Graham, Scott D. Gordon, Shih-Jen Hwang, Shona M. Kerr, Simona Vaccargiu, Snehal B. Patil, Stein Hallan, Stephan J. L. Bakker, Su-Chi Lim, Susanne Lucae, Suzanne Vogelezang, Sven Bergmann, Tanguy Corre, Tarunveer S. Ahluwalia, Terho Lehtimäki, Thibaud S. Boutin, Thomas Meitinger, Tien-Yin Wong, Tobias Bergler, Ton J. Rabelink, Tõnu Esko, Toomas Haller, Unnur Thorsteinsdottir, Uwe Völker, Valencia Hui Xian Foo, Veikko Salomaa, Veronique Vitart, Vilmantas Giedraitis, Vilmundur Gudnason, Vincent W. V. Jaddoe, Wei Huang, Weihua Zhang, Wen Bin Wei, Wieland Kiess, Winfried März, Wolfgang Koenig, Wolfgang Lieb, Xin Gao, Xueling Sim, Ya Xing Wang, Yechiel Friedlander, Yih-Chung Tham, Yoichiro Kamatani, Yukinori Okada, Yuri Milaneschi, Zhi Yu, Lifelines cohort study, DiscovEHR/MyCode study, VA Million Veteran Program, Klaus J. Stark, Kari Stefansson, Carsten A. Böger, Adriana M. Hung, Florian Kronenberg, Anna Köttgen, Cristian Pattaro, and Iris M. Heid
Subjects: Biology (General), QH301-705.5
Abstract: A large-scale GWAS provides insight on diabetes-dependent genetic effects on the glomerular filtration rate, a common metric to monitor kidney health in disease.
Published: 2022
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19. Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6

Author: Prins, Bram P, Mead, Timothy J, Brody, Jennifer A, Sveinbjornsson, Gardar, Ntalla, Ioanna, Bihlmeyer, Nathan A, van den Berg, Marten, Bork-Jensen, Jette, Cappellani, Stefania, Van Duijvenboden, Stefan, Klena, Nikolai T, Gabriel, George C, Liu, Xiaoqin, Gulec, Cagri, Grarup, Niels, Haessler, Jeffrey, Hall, Leanne M, Iorio, Annamaria, Isaacs, Aaron, Li-Gao, Ruifang, Lin, Honghuang, Liu, Ching-Ti, Lyytikäinen, Leo-Pekka, Marten, Jonathan, Mei, Hao, Müller-Nurasyid, Martina, Orini, Michele, Padmanabhan, Sandosh, Radmanesh, Farid, Ramirez, Julia, Robino, Antonietta, Schwartz, Molly, van Setten, Jessica, Smith, Albert V, Verweij, Niek, Warren, Helen R, Weiss, Stefan, Alonso, Alvaro, Arnar, David O, Bots, Michiel L, de Boer, Rudolf A, Dominiczak, Anna F, Eijgelsheim, Mark, Ellinor, Patrick T, Guo, Xiuqing, Felix, Stephan B, Harris, Tamara B, Hayward, Caroline, Heckbert, Susan R, Huang, Paul L, Jukema, JW, Kähönen, Mika, Kors, Jan A, Lambiase, Pier D, Launer, Lenore J, Li, Man, Linneberg, Allan, Nelson, Christopher P, Pedersen, Oluf, Perez, Marco, Peters, Annette, Polasek, Ozren, Psaty, Bruce M, Raitakari, Olli T, Rice, Kenneth M, Rotter, Jerome I, Sinner, Moritz F, Soliman, Elsayed Z, Spector, Tim D, Strauch, Konstantin, Thorsteinsdottir, Unnur, Tinker, Andrew, Trompet, Stella, Uitterlinden, André, Vaartjes, Ilonca, van der Meer, Peter, Völker, Uwe, Völzke, Henry, Waldenberger, Melanie, Wilson, James G, Xie, Zhijun, Asselbergs, Folkert W, Dörr, Marcus, van Duijn, Cornelia M, Gasparini, Paolo, Gudbjartsson, Daniel F, Gudnason, Vilmundur, Hansen, Torben, Kääb, Stefan, Kanters, Jørgen K, Kooperberg, Charles, Lehtimäki, Terho, Lin, Henry J, Lubitz, Steven A, Mook-Kanamori, Dennis O, Conti, Francesco J, Newton-Cheh, Christopher H, Rosand, Jonathan, Rudan, Igor, and Samani, Nilesh J
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Human Genome, Heart Disease, Cardiovascular, 2.1 Biological and endogenous factors, Aetiology, ADAMTS Proteins, Animals, Black People, Connexin 43, Electrocardiography, Exome, Female, Gene Expression, Gene Expression Profiling, Genetic Loci, Genome-Wide Association Study, Heart Conduction System, Humans, Male, Mice, Middle Aged, Myocardium, Open Reading Frames, Polymorphism, Single Nucleotide, White People, Exome Sequencing, Exome chip, Conduction, ADAMTS6, Meta-analysis, Environmental Sciences, Information and Computing Sciences, Bioinformatics
Abstract: BackgroundGenome-wide association studies conducted on QRS duration, an electrocardiographic measurement associated with heart failure and sudden cardiac death, have led to novel biological insights into cardiac function. However, the variants identified fall predominantly in non-coding regions and their underlying mechanisms remain unclear.ResultsHere, we identify putative functional coding variation associated with changes in the QRS interval duration by combining Illumina HumanExome BeadChip genotype data from 77,898 participants of European ancestry and 7695 of African descent in our discovery cohort, followed by replication in 111,874 individuals of European ancestry from the UK Biobank and deCODE cohorts. We identify ten novel loci, seven within coding regions, including ADAMTS6, significantly associated with QRS duration in gene-based analyses. ADAMTS6 encodes a secreted metalloprotease of currently unknown function. In vitro validation analysis shows that the QRS-associated variants lead to impaired ADAMTS6 secretion and loss-of function analysis in mice demonstrates a previously unappreciated role for ADAMTS6 in connexin 43 gap junction expression, which is essential for myocardial conduction.ConclusionsOur approach identifies novel coding and non-coding variants underlying ventricular depolarization and provides a possible mechanism for the ADAMTS6-associated conduction changes.
Published: 2018

20. Establishing plausibility of cardiovascular adverse effects of immunotherapies using Mendelian randomisation

Author: Nhu Ngoc Le, Tran Quoc Bao Tran, Clea du Toit, Dipender Gill, and Sandosh Padmanabhan
Subjects: GWAS, pleiotropy, Mendelian randomisation, reactome, eQTL, stroke, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Immune checkpoint inhibitors (ICIs) and Janus kinase inhibitors (JAKis) have raised concerns over serious unexpected cardiovascular adverse events. The widespread pleiotropy in genome-wide association studies offers an opportunity to identify cardiovascular risks from in-development drugs to help inform appropriate trial design and pharmacovigilance strategies. This study uses the Mendelian randomization (MR) approach to study the causal effects of 9 cardiovascular risk factors on ischemic stroke risk both independently and by mediation, followed by an interrogation of the implicated expression quantitative trait loci (eQTLs) to determine if the enriched pathways can explain the adverse stroke events observed with ICI or JAKi treatment. Genetic predisposition to higher systolic blood pressure (SBP), diastolic blood pressure (DBP), body mass index (BMI), waist-to-hip ratio (WHR), low-density lipoprotein cholesterol (LDL), triglycerides (TG), type 2 diabetes (T2DM), and smoking index were associated with higher ischemic stroke risk. The associations of genetically predicted BMI, WHR, and TG on the outcome were attenuated after adjusting for genetically predicted T2DM [BMI: 53.15% mediated, 95% CI 17.21%–89.10%; WHR: 42.92% (4.17%–81.67%); TG: 72.05% (10.63%–133.46%)]. JAKis, programmed cell death protein 1 and programmed death ligand 1 inhibitors were implicated in the pathways enriched by the genes related to the instruments for each of SBP, DBP, WHR, T2DM, and LDL. Overall, MR mediation analyses support the role of T2DM in mediating the effects of BMI, WHR, and TG on ischemic stroke risk and follow-up pathway enrichment analysis highlights the utility of this approach in the early identification of potential harm from drugs.
Published: 2023
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21. Survey and Evaluation of Hypertension Machine Learning Research

Author: Clea du Toit, Tran Quoc Bao Tran, Neha Deo, Sachin Aryal, Stefanie Lip, Robert Sykes, Ishan Manandhar, Aristeidis Sionakidis, Leah Stevenson, Harsha Pattnaik, Safaa Alsanosi, Maria Kassi, Ngoc Le, Maggie Rostron, Sarah Nichol, Alisha Aman, Faisal Nawaz, Dhruven Mehta, Ramakumar Tummala, Linsay McCallum, Sandeep Reddy, Shyam Visweswaran, Rahul Kashyap, Bina Joe, and Sandosh Padmanabhan
Subjects: artificial intelligence, hypertension, machine learning, reporting quality, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: Background Machine learning (ML) is pervasive in all fields of research, from automating tasks to complex decision‐making. However, applications in different specialities are variable and generally limited. Like other conditions, the number of studies employing ML in hypertension research is growing rapidly. In this study, we aimed to survey hypertension research using ML, evaluate the reporting quality, and identify barriers to ML's potential to transform hypertension care. Methods and Results The Harmonious Understanding of Machine Learning Analytics Network survey questionnaire was applied to 63 hypertension‐related ML research articles published between January 2019 and September 2021. The most common research topics were blood pressure prediction (38%), hypertension (22%), cardiovascular outcomes (6%), blood pressure variability (5%), treatment response (5%), and real‐time blood pressure estimation (5%). The reporting quality of the articles was variable. Only 46% of articles described the study population or derivation cohort. Most articles (81%) reported at least 1 performance measure, but only 40% presented any measures of calibration. Compliance with ethics, patient privacy, and data security regulations were mentioned in 30 (48%) of the articles. Only 14% used geographically or temporally distinct validation data sets. Algorithmic bias was not addressed in any of the articles, with only 6 of them acknowledging risk of bias. Conclusions Recent ML research on hypertension is limited to exploratory research and has significant shortcomings in reporting quality, model validation, and algorithmic bias. Our analysis identifies areas for improvement that will help pave the way for the realization of the potential of ML in hypertension and facilitate its adoption.
Published: 2023
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22. Genetic analyses of the electrocardiographic QT interval and its components identify additional loci and pathways

Author: Young, William J., Lahrouchi, Najim, Isaacs, Aaron, Duong, ThuyVy, Foco, Luisa, Ahmed, Farah, Brody, Jennifer A., Salman, Reem, Noordam, Raymond, Benjamins, Jan-Walter, Haessler, Jeffrey, Lyytikäinen, Leo-Pekka, Repetto, Linda, Concas, Maria Pina, van den Berg, Marten E., Weiss, Stefan, Baldassari, Antoine R., Bartz, Traci M., Cook, James P., Evans, Daniel S., Freudling, Rebecca, Hines, Oliver, Isaksen, Jonas L., Lin, Honghuang, Mei, Hao, Moscati, Arden, Müller-Nurasyid, Martina, Nursyifa, Casia, Qian, Yong, Richmond, Anne, Roselli, Carolina, Ryan, Kathleen A., Tarazona-Santos, Eduardo, Thériault, Sébastien, van Duijvenboden, Stefan, Warren, Helen R., Yao, Jie, Raza, Dania, Aeschbacher, Stefanie, Ahlberg, Gustav, Alonso, Alvaro, Andreasen, Laura, Bis, Joshua C., Boerwinkle, Eric, Campbell, Archie, Catamo, Eulalia, Cocca, Massimiliano, Cutler, Michael J., Darbar, Dawood, De Grandi, Alessandro, De Luca, Antonio, Ding, Jun, Ellervik, Christina, Ellinor, Patrick T., Felix, Stephan B., Froguel, Philippe, Fuchsberger, Christian, Gögele, Martin, Graff, Claus, Graff, Mariaelisa, Guo, Xiuqing, Hansen, Torben, Heckbert, Susan R., Huang, Paul L., Huikuri, Heikki V., Hutri-Kähönen, Nina, Ikram, M. Arfan, Jackson, Rebecca D., Junttila, Juhani, Kavousi, Maryam, Kors, Jan A., Leal, Thiago P., Lemaitre, Rozenn N., Lin, Henry J., Lind, Lars, Linneberg, Allan, Liu, Simin, MacFarlane, Peter W., Mangino, Massimo, Meitinger, Thomas, Mezzavilla, Massimo, Mishra, Pashupati P., Mitchell, Rebecca N., Mononen, Nina, Montasser, May E., Morrison, Alanna C., Nauck, Matthias, Nauffal, Victor, Navarro, Pau, Nikus, Kjell, Pare, Guillaume, Patton, Kristen K., Pelliccione, Giulia, Pittman, Alan, Porteous, David J., Pramstaller, Peter P., Preuss, Michael H., Raitakari, Olli T., Reiner, Alexander P., Ribeiro, Antonio Luiz P., Rice, Kenneth M., Risch, Lorenz, Schlessinger, David, Schotten, Ulrich, Schurmann, Claudia, Shen, Xia, Shoemaker, M. Benjamin, Sinagra, Gianfranco, Sinner, Moritz F., Soliman, Elsayed Z., Stoll, Monika, Strauch, Konstantin, Tarasov, Kirill, Taylor, Kent D., Tinker, Andrew, Trompet, Stella, Uitterlinden, André, Völker, Uwe, Völzke, Henry, Waldenberger, Melanie, Weng, Lu-Chen, Whitsel, Eric A., Wilson, James G., Avery, Christy L., Conen, David, Correa, Adolfo, Cucca, Francesco, Dörr, Marcus, Gharib, Sina A., Girotto, Giorgia, Grarup, Niels, Hayward, Caroline, Jamshidi, Yalda, Järvelin, Marjo-Riitta, Jukema, J. Wouter, Kääb, Stefan, Kähönen, Mika, Kanters, Jørgen K., Kooperberg, Charles, Lehtimäki, Terho, Lima-Costa, Maria Fernanda, Liu, Yongmei, Loos, Ruth J. F., Lubitz, Steven A., Mook-Kanamori, Dennis O., Morris, Andrew P., O’Connell, Jeffrey R., Olesen, Morten Salling, Orini, Michele, Padmanabhan, Sandosh, Pattaro, Cristian, Peters, Annette, Psaty, Bruce M., Rotter, Jerome I., Stricker, Bruno, van der Harst, Pim, van Duijn, Cornelia M., Verweij, Niek, Wilson, James F., Arking, Dan E., Ramirez, Julia, Lambiase, Pier D., Sotoodehnia, Nona, Mifsud, Borbala, Newton-Cheh, Christopher, and Munroe, Patricia B.
Published: 2022
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23. Underrepresentation of ethnic minorities in hypertension research—a survey of enablers and barriers among South Asian and African communities in Glasgow

Author: Lip, Stefanie, Dempster, Georgia, Jain, Sahil, Brooksbank, Katriona, Ghouri, Nazim, McCallum, Linsay, and Padmanabhan, Sandosh
Published: 2022
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24. Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals

Author: Winkler, Thomas W., Rasheed, Humaira, Teumer, Alexander, Gorski, Mathias, Rowan, Bryce X., Stanzick, Kira J., Thomas, Laurent F., Tin, Adrienne, Hoppmann, Anselm, Chu, Audrey Y., Tayo, Bamidele, Thio, Chris H. L., Cusi, Daniele, Chai, Jin-Fang, Sieber, Karsten B., Horn, Katrin, Li, Man, Scholz, Markus, Cocca, Massimiliano, Wuttke, Matthias, van der Most, Peter J., Yang, Qiong, Ghasemi, Sahar, Nutile, Teresa, Li, Yong, Pontali, Giulia, Günther, Felix, Dehghan, Abbas, Correa, Adolfo, Parsa, Afshin, Feresin, Agnese, de Vries, Aiko P. J., Zonderman, Alan B., Smith, Albert V., Oldehinkel, Albertine J., De Grandi, Alessandro, Rosenkranz, Alexander R., Franke, Andre, Teren, Andrej, Metspalu, Andres, Hicks, Andrew A., Morris, Andrew P., Tönjes, Anke, Morgan, Anna, Podgornaia, Anna I., Peters, Annette, Körner, Antje, Mahajan, Anubha, Campbell, Archie, Freedman, Barry I., Spedicati, Beatrice, Ponte, Belen, Schöttker, Ben, Brumpton, Ben, Banas, Bernhard, Krämer, Bernhard K., Jung, Bettina, Åsvold, Bjørn Olav, Smith, Blair H., Ning, Boting, Penninx, Brenda W. J. H., Vanderwerff, Brett R., Psaty, Bruce M., Kammerer, Candace M., Langefeld, Carl D., Hayward, Caroline, Spracklen, Cassandra N., Robinson-Cohen, Cassianne, Hartman, Catharina A., Lindgren, Cecilia M., Wang, Chaolong, Sabanayagam, Charumathi, Heng, Chew-Kiat, Lanzani, Chiara, Khor, Chiea-Chuen, Cheng, Ching-Yu, Fuchsberger, Christian, Gieger, Christian, Shaffer, Christian M., Schulz, Christina-Alexandra, Willer, Cristen J., Chasman, Daniel I., Gudbjartsson, Daniel F., Ruggiero, Daniela, Toniolo, Daniela, Czamara, Darina, Porteous, David J., Waterworth, Dawn M., Mascalzoni, Deborah, Mook-Kanamori, Dennis O., Reilly, Dermot F., Daw, E. Warwick, Hofer, Edith, Boerwinkle, Eric, Salvi, Erika, Bottinger, Erwin P., Tai, E-Shyong, Catamo, Eulalia, Rizzi, Federica, Guo, Feng, Rivadeneira, Fernando, Guilianini, Franco, Sveinbjornsson, Gardar, Ehret, Georg, Waeber, Gerard, Biino, Ginevra, Girotto, Giorgia, Pistis, Giorgio, Nadkarni, Girish N., Delgado, Graciela E., Montgomery, Grant W., Snieder, Harold, Campbell, Harry, White, Harvey D., Gao, He, Stringham, Heather M., Schmidt, Helena, Li, Hengtong, Brenner, Hermann, Holm, Hilma, Kirsten, Holgen, Kramer, Holly, Rudan, Igor, Nolte, Ilja M., Tzoulaki, Ioanna, Olafsson, Isleifur, Martins, Jade, Cook, James P., Wilson, James F., Halbritter, Jan, Felix, Janine F., Divers, Jasmin, Kooner, Jaspal S., Lee, Jeannette Jen-Mai, O’Connell, Jeffrey, Rotter, Jerome I., Liu, Jianjun, Xu, Jie, Thiery, Joachim, Ärnlöv, Johan, Kuusisto, Johanna, Jakobsdottir, Johanna, Tremblay, Johanne, Chambers, John C., Whitfield, John B., Gaziano, John M., Marten, Jonathan, Coresh, Josef, Jonas, Jost B., Mychaleckyj, Josyf C., Christensen, Kaare, Eckardt, Kai-Uwe, Mohlke, Karen L., Endlich, Karlhans, Dittrich, Katalin, Ryan, Kathleen A., Rice, Kenneth M., Taylor, Kent D., Ho, Kevin, Nikus, Kjell, Matsuda, Koichi, Strauch, Konstantin, Miliku, Kozeta, Hveem, Kristian, Lind, Lars, Wallentin, Lars, Yerges-Armstrong, Laura M., Raffield, Laura M., Phillips, Lawrence S., Launer, Lenore J., Lyytikäinen, Leo-Pekka, Lange, Leslie A., Citterio, Lorena, Klaric, Lucija, Ikram, M. Arfan, Ising, Marcus, Kleber, Marcus E., Francescatto, Margherita, Concas, Maria Pina, Ciullo, Marina, Piratsu, Mario, Orho-Melander, Marju, Laakso, Markku, Loeffler, Markus, Perola, Markus, de Borst, Martin H., Gögele, Martin, Bianca, Martina La, Lukas, Mary Ann, Feitosa, Mary F., Biggs, Mary L., Wojczynski, Mary K., Kavousi, Maryam, Kanai, Masahiro, Akiyama, Masato, Yasuda, Masayuki, Nauck, Matthias, Waldenberger, Melanie, Chee, Miao-Li, Chee, Miao-Ling, Boehnke, Michael, Preuss, Michael H., Stumvoll, Michael, Province, Michael A., Evans, Michele K., O’Donoghue, Michelle L., Kubo, Michiaki, Kähönen, Mika, Kastarinen, Mika, Nalls, Mike A., Kuokkanen, Mikko, Ghanbari, Mohsen, Bochud, Murielle, Josyula, Navya Shilpa, Martin, Nicholas G., Tan, Nicholas Y. Q., Palmer, Nicholette D., Pirastu, Nicola, Schupf, Nicole, Verweij, Niek, Hutri-Kähönen, Nina, Mononen, Nina, Bansal, Nisha, Devuyst, Olivier, Melander, Olle, Raitakari, Olli T., Polasek, Ozren, Manunta, Paolo, Gasparini, Paolo, Mishra, Pashupati P., Sulem, Patrick, Magnusson, Patrik K. E., Elliott, Paul, Ridker, Paul M., Hamet, Pavel, Svensson, Per O., Joshi, Peter K., Kovacs, Peter, Pramstaller, Peter P., Rossing, Peter, Vollenweider, Peter, van der Harst, Pim, Dorajoo, Rajkumar, Sim, Ralene Z. H., Burkhardt, Ralph, Tao, Ran, Noordam, Raymond, Mägi, Reedik, Schmidt, Reinhold, de Mutsert, Renée, Rueedi, Rico, van Dam, Rob M., Carroll, Robert J., Gansevoort, Ron T., Loos, Ruth J. F., Felicita, Sala Cinzia, Sedaghat, Sanaz, Padmanabhan, Sandosh, Freitag-Wolf, Sandra, Pendergrass, Sarah A., Graham, Sarah E., Gordon, Scott D., Hwang, Shih-Jen, Kerr, Shona M., Vaccargiu, Simona, Patil, Snehal B., Hallan, Stein, Bakker, Stephan J. L., Lim, Su-Chi, Lucae, Susanne, Vogelezang, Suzanne, Bergmann, Sven, Corre, Tanguy, Ahluwalia, Tarunveer S., Lehtimäki, Terho, Boutin, Thibaud S., Meitinger, Thomas, Wong, Tien-Yin, Bergler, Tobias, Rabelink, Ton J., Esko, Tõnu, Haller, Toomas, Thorsteinsdottir, Unnur, Völker, Uwe, Foo, Valencia Hui Xian, Salomaa, Veikko, Vitart, Veronique, Giedraitis, Vilmantas, Gudnason, Vilmundur, Jaddoe, Vincent W. V., Huang, Wei, Zhang, Weihua, Wei, Wen Bin, Kiess, Wieland, März, Winfried, Koenig, Wolfgang, Lieb, Wolfgang, Gao, Xin, Sim, Xueling, Wang, Ya Xing, Friedlander, Yechiel, Tham, Yih-Chung, Kamatani, Yoichiro, Okada, Yukinori, Milaneschi, Yuri, Yu, Zhi, Stark, Klaus J., Stefansson, Kari, Böger, Carsten A., Hung, Adriana M., Kronenberg, Florian, Köttgen, Anna, Pattaro, Cristian, and Heid, Iris M.
Published: 2022
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25. UMOD Genotype-Blinded Trial of Ambulatory Blood Pressure Response to Torasemide.

Author: McCallum, Linsay, Lip, Stefanie, McConnachie, Alex, Brooksbank, Katriona, MacIntyre, Iain M., Doney, Alexander, Llano, Andrea, Aman, Alisha, Caparrotta, Thomas M., Ingram, Gareth, Mackenzie, Isla S., Dominiczak, Anna F., MacDonald, Thomas M., Webb, David J., and Padmanabhan, Sandosh
Abstract: BACKGROUND: UMOD (uromodulin) has been linked to hypertension through potential activation of Na+-K+-2Cl- cotransporter (NKCC2), a target of loop diuretics. We posited that hypertensive patients carrying the rs13333226-AA UMOD genotype would demonstrate greater blood pressure responses to loop diuretics, potentially mediated by this UMOD/NKCC2 interaction. METHODS: This prospective, multicenter, genotype-blinded trial evaluated torasemide (torsemide) efficacy on systolic blood pressure (SBP) reduction over 16 weeks in nondiabetic, hypertensive participants uncontrolled on ≥1 nondiuretic antihypertensive for >3 months. The primary end point was the change in 24-hour ambulatory SBP (ABPM SBP) and SBP response trajectories between baseline and 16 weeks by genotype (AA versus AG/GG) due to nonrandomized groups at baseline (ClinicalTrials.gov: NCT03354897). RESULTS: Of 251 enrolled participants, 222 received torasemide and 174 demonstrated satisfactory treatment adherence and had genotype data. The study participants were middle-aged (59±11 years), predominantly male (62%), obese (body mass index, 32±7 kg/m²), with normal eGFR (92±17 mL/min/1.73 m²) and an average baseline ABPM of 138/81 mm Hg. Significant reductions in mean ABPM SBP were observed in both groups after 16 weeks (AA, -6.57 mm Hg [95% CI, -8.44 to -4.69]; P<0.0001; AG/GG, -3.22 [95% CI, -5.93 to -0.51]; P=0.021). The change in mean ABPM SBP (baseline to 16 weeks) showed a difference of -3.35 mm Hg ([95% CI, -6.64 to -0.05]; P=0.048) AA versus AG/GG genotypes. The AG/GG group displayed a rebound in SBP from 8 weeks, differing from the consistent decrease in the AA group (P=0.004 for difference in trajectories). CONCLUSIONS: Our results confirm a plausible interaction between UMOD and NKCC2 and suggest a potential role for genotype-guided use of loop diuretics in hypertension management. [ABSTRACT FROM AUTHOR]
Published: 2024
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26. Cardiovascular precision medicine – A pharmacogenomic perspective

Author: Sandosh Padmanabhan, Clea du Toit, and Anna F. Dominiczak
Subjects: pharmacogenomics, cardiovascular, warfarin, clopidogrel, cytochrome-P-450, Internal medicine, RC31-1245, Therapeutics. Pharmacology, RM1-950
Abstract: Precision medicine envisages the integration of an individual’s clinical and biological features obtained from laboratory tests, imaging, high-throughput omics and health records, to drive a personalised approach to diagnosis and treatment with a higher chance of success. As only up to half of patients respond to medication prescribed following the current one-size-fits-all treatment strategy, the need for a more personalised approach is evident. One of the routes to transforming healthcare through precision medicine is pharmacogenomics (PGx). Around 95% of the population is estimated to carry one or more actionable pharmacogenetic variants and over 75% of adults over 50 years old are on a prescription with a known PGx association. Whilst there are compelling examples of pharmacogenomic implementation in clinical practice, the case for cardiovascular PGx is still evolving. In this review, we shall summarise the current status of PGx in cardiovascular diseases and look at the key enablers and barriers to PGx implementation in clinical practice.
Published: 2023
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27. Introducing Cambridge prisms: Precision medicine

Author: Anna F Dominiczak, Sandosh Padmanabhan, Mark Caulfield, Ken Sutherland, Jiguang Wang, and Jessica K Jones
Subjects: Precision Medicine, Preventive Medicine, Health Economics, Precision Diagnostics, Digital Health, Internal medicine, RC31-1245, Therapeutics. Pharmacology, RM1-950
Published: 2023
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28. ExomeChip-Wide Analysis of 95 626 Individuals Identifies 10 Novel Loci Associated With QT and JT Intervals

Author: Bihlmeyer, Nathan A, Brody, Jennifer A, Smith, Albert Vernon, Warren, Helen R, Lin, Honghuang, Isaacs, Aaron, Liu, Ching-Ti, Marten, Jonathan, Radmanesh, Farid, Hall, Leanne M, Grarup, Niels, Mei, Hao, Müller-Nurasyid, Martina, Huffman, Jennifer E, Verweij, Niek, Guo, Xiuqing, Yao, Jie, Li-Gao, Ruifang, van den Berg, Marten, Weiss, Stefan, Prins, Bram P, van Setten, Jessica, Haessler, Jeffrey, Lyytikäinen, Leo-Pekka, Li, Man, Alonso, Alvaro, Soliman, Elsayed Z, Bis, Joshua C, Austin, Tom, Chen, Yii-Der Ida, Psaty, Bruce M, Harrris, Tamara B, Launer, Lenore J, Padmanabhan, Sandosh, Dominiczak, Anna, Huang, Paul L, Xie, Zhijun, Ellinor, Patrick T, Kors, Jan A, Campbell, Archie, Murray, Alison D, Nelson, Christopher P, Tobin, Martin D, Bork-Jensen, Jette, Hansen, Torben, Pedersen, Oluf, Linneberg, Allan, Sinner, Moritz F, Peters, Annette, Waldenberger, Melanie, Meitinger, Thomas, Perz, Siegfried, Kolcic, Ivana, Rudan, Igor, de Boer, Rudolf A, van der Meer, Peter, Lin, Henry J, Taylor, Kent D, de Mutsert, Renée, Trompet, Stella, Jukema, J Wouter, Maan, Arie C, Stricker, Bruno HC, Rivadeneira, Fernando, Uitterlinden, André, Völker, Uwe, Homuth, Georg, Völzke, Henry, Felix, Stephan B, Mangino, Massimo, Spector, Timothy D, Bots, Michiel L, Perez, Marco, Raitakari, Olli T, Kähönen, Mika, Mononen, Nina, Gudnason, Vilmundur, Munroe, Patricia B, Lubitz, Steven A, van Duijn, Cornelia M, Newton-Cheh, Christopher H, Hayward, Caroline, Rosand, Jonathan, Samani, Nilesh J, Kanters, Jørgen K, Wilson, James G, Kääb, Stefan, Polasek, Ozren, van der Harst, Pim, Heckbert, Susan R, Rotter, Jerome I, Mook-Kanamori, Dennis O, Eijgelsheim, Mark, Dörr, Marcus, Jamshidi, Yalda, Asselbergs, Folkert W, Kooperberg, Charles, Lehtimäki, Terho, Arking, Dan E, and Sotoodehnia, Nona
Subjects: Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Heart Disease, Prevention, Genetics, Cardiovascular, 2.1 Biological and endogenous factors, Aetiology, Antiporters, DNA-Binding Proteins, Electrocardiography, Exome, Genome-Wide Association Study, Humans, Long QT Syndrome, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Receptors, Calcium-Sensing, Transcription Factors, arrhythmias, cardiac, death, sudden, cardiac, genetics, genome, humans, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract: BackgroundQT interval, measured through a standard ECG, captures the time it takes for the cardiac ventricles to depolarize and repolarize. JT interval is the component of the QT interval that reflects ventricular repolarization alone. Prolonged QT interval has been linked to higher risk of sudden cardiac arrest.Methods and resultsWe performed an ExomeChip-wide analysis for both QT and JT intervals, including 209 449 variants, both common and rare, in 17 341 genes from the Illumina Infinium HumanExome BeadChip. We identified 10 loci that modulate QT and JT interval duration that have not been previously reported in the literature using single-variant statistical models in a meta-analysis of 95 626 individuals from 23 cohorts (comprised 83 884 European ancestry individuals, 9610 blacks, 1382 Hispanics, and 750 Asians). This brings the total number of ventricular repolarization associated loci to 45. In addition, our approach of using coding variants has highlighted the role of 17 specific genes for involvement in ventricular repolarization, 7 of which are in novel loci.ConclusionsOur analyses show a role for myocyte internal structure and interconnections in modulating QT interval duration, adding to previous known roles of potassium, sodium, and calcium ion regulation, as well as autonomic control. We anticipate that these discoveries will open new paths to the goal of making novel remedies for the prevention of lethal ventricular arrhythmias and sudden cardiac arrest.
Published: 2018

29. PR interval genome-wide association meta-analysis identifies 50 loci associated with atrial and atrioventricular electrical activity

Author: van Setten, Jessica, Brody, Jennifer A, Jamshidi, Yalda, Swenson, Brenton R, Butler, Anne M, Campbell, Harry, Del Greco, Fabiola M, Evans, Daniel S, Gibson, Quince, Gudbjartsson, Daniel F, Kerr, Kathleen F, Krijthe, Bouwe P, Lyytikäinen, Leo-Pekka, Müller, Christian, Müller-Nurasyid, Martina, Nolte, Ilja M, Padmanabhan, Sandosh, Ritchie, Marylyn D, Robino, Antonietta, Smith, Albert V, Steri, Maristella, Tanaka, Toshiko, Teumer, Alexander, Trompet, Stella, Ulivi, Sheila, Verweij, Niek, Yin, Xiaoyan, Arnar, David O, Asselbergs, Folkert W, Bader, Joel S, Barnard, John, Bis, Josh, Blankenberg, Stefan, Boerwinkle, Eric, Bradford, Yuki, Buckley, Brendan M, Chung, Mina K, Crawford, Dana, den Hoed, Marcel, Denny, Josh C, Dominiczak, Anna F, Ehret, Georg B, Eijgelsheim, Mark, Ellinor, Patrick T, Felix, Stephan B, Franco, Oscar H, Franke, Lude, Harris, Tamara B, Holm, Hilma, Ilaria, Gandin, Iorio, Annamaria, Kähönen, Mika, Kolcic, Ivana, Kors, Jan A, Lakatta, Edward G, Launer, Lenore J, Lin, Honghuang, Lin, Henry J, Loos, Ruth JF, Lubitz, Steven A, Macfarlane, Peter W, Magnani, Jared W, Leach, Irene Mateo, Meitinger, Thomas, Mitchell, Braxton D, Munzel, Thomas, Papanicolaou, George J, Peters, Annette, Pfeufer, Arne, Pramstaller, Peter P, Raitakari, Olli T, Rotter, Jerome I, Rudan, Igor, Samani, Nilesh J, Schlessinger, David, Silva Aldana, Claudia T, Sinner, Moritz F, Smith, Jonathan D, Snieder, Harold, Soliman, Elsayed Z, Spector, Timothy D, Stott, David J, Strauch, Konstantin, Tarasov, Kirill V, Thorsteinsdottir, Unnur, Uitterlinden, Andre G, Van Wagoner, David R, Völker, Uwe, Völzke, Henry, Waldenberger, Melanie, Jan Westra, Harm, Wild, Philipp S, Zeller, Tanja, Alonso, Alvaro, Avery, Christy L, Bandinelli, Stefania, Benjamin, Emelia J, Cucca, Francesco, Dörr, Marcus, and Ferrucci, Luigi
Subjects: Biological Sciences, Genetics, Human Genome, Heart Disease, Biotechnology, Cardiovascular, Aetiology, 2.1 Biological and endogenous factors, Atrial Function, Atrioventricular Node, Electrocardiography, Electrophysiological Phenomena, Female, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Male, Mutation, Missense, Risk Factors
Abstract: Electrocardiographic PR interval measures atrio-ventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. Our genome-wide association study of over 92,000 European-descent individuals identifies 44 PR interval loci (34 novel). Examination of these loci reveals known and previously not-yet-reported biological processes involved in cardiac atrial electrical activity. Genes in these loci are over-represented in cardiac disease processes including heart block and atrial fibrillation. Variants in over half of the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with missense variants. Six additional loci were identified either by meta-analysis of ~105,000 African and European-descent individuals and/or by pleiotropic analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation. These findings implicate developmental pathways, and identify transcription factors, ion-channel genes, and cell-junction/cell-signaling proteins in atrio-ventricular conduction, identifying potential targets for drug development.
Published: 2018

30. Novel genetic associations for blood pressure identified via gene-alcohol interaction in up to 570K individuals across multiple ancestries.

Author: Feitosa, Mary F, Kraja, Aldi T, Chasman, Daniel I, Sung, Yun J, Winkler, Thomas W, Ntalla, Ioanna, Guo, Xiuqing, Franceschini, Nora, Cheng, Ching-Yu, Sim, Xueling, Vojinovic, Dina, Marten, Jonathan, Musani, Solomon K, Li, Changwei, Bentley, Amy R, Brown, Michael R, Schwander, Karen, Richard, Melissa A, Noordam, Raymond, Aschard, Hugues, Bartz, Traci M, Bielak, Lawrence F, Dorajoo, Rajkumar, Fisher, Virginia, Hartwig, Fernando P, Horimoto, Andrea RVR, Lohman, Kurt K, Manning, Alisa K, Rankinen, Tuomo, Smith, Albert V, Tajuddin, Salman M, Wojczynski, Mary K, Alver, Maris, Boissel, Mathilde, Cai, Qiuyin, Campbell, Archie, Chai, Jin Fang, Chen, Xu, Divers, Jasmin, Gao, Chuan, Goel, Anuj, Hagemeijer, Yanick, Harris, Sarah E, He, Meian, Hsu, Fang-Chi, Jackson, Anne U, Kähönen, Mika, Kasturiratne, Anuradhani, Komulainen, Pirjo, Kühnel, Brigitte, Laguzzi, Federica, Luan, Jian'an, Matoba, Nana, Nolte, Ilja M, Padmanabhan, Sandosh, Riaz, Muhammad, Rueedi, Rico, Robino, Antonietta, Said, M Abdullah, Scott, Robert A, Sofer, Tamar, Stančáková, Alena, Takeuchi, Fumihiko, Tayo, Bamidele O, van der Most, Peter J, Varga, Tibor V, Vitart, Veronique, Wang, Yajuan, Ware, Erin B, Warren, Helen R, Weiss, Stefan, Wen, Wanqing, Yanek, Lisa R, Zhang, Weihua, Zhao, Jing Hua, Afaq, Saima, Amin, Najaf, Amini, Marzyeh, Arking, Dan E, Aung, Tin, Boerwinkle, Eric, Borecki, Ingrid, Broeckel, Ulrich, Brown, Morris, Brumat, Marco, Burke, Gregory L, Canouil, Mickaël, Chakravarti, Aravinda, Charumathi, Sabanayagam, Ida Chen, Yii-Der, Connell, John M, Correa, Adolfo, de Las Fuentes, Lisa, de Mutsert, Renée, de Silva, H Janaka, Deng, Xuan, Ding, Jingzhong, Duan, Qing, Eaton, Charles B, and Ehret, Georg
Subjects: InterAct Consortium, Humans, Hypertension, Genetic Predisposition to Disease, Cohort Studies, Pedigree, Alcohol Drinking, Blood Pressure, Polymorphism, Single Nucleotide, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Continental Population Groups, Female, Male, Genome-Wide Association Study, Young Adult, Gene-Environment Interaction, General Science & Technology
Abstract: Heavy alcohol consumption is an established risk factor for hypertension; the mechanism by which alcohol consumption impact blood pressure (BP) regulation remains unknown. We hypothesized that a genome-wide association study accounting for gene-alcohol consumption interaction for BP might identify additional BP loci and contribute to the understanding of alcohol-related BP regulation. We conducted a large two-stage investigation incorporating joint testing of main genetic effects and single nucleotide variant (SNV)-alcohol consumption interactions. In Stage 1, genome-wide discovery meta-analyses in ≈131K individuals across several ancestry groups yielded 3,514 SNVs (245 loci) with suggestive evidence of association (P < 1.0 x 10-5). In Stage 2, these SNVs were tested for independent external replication in ≈440K individuals across multiple ancestries. We identified and replicated (at Bonferroni correction threshold) five novel BP loci (380 SNVs in 21 genes) and 49 previously reported BP loci (2,159 SNVs in 109 genes) in European ancestry, and in multi-ancestry meta-analyses (P < 5.0 x 10-8). For African ancestry samples, we detected 18 potentially novel BP loci (P < 5.0 x 10-8) in Stage 1 that warrant further replication. Additionally, correlated meta-analysis identified eight novel BP loci (11 genes). Several genes in these loci (e.g., PINX1, GATA4, BLK, FTO and GABBR2) have been previously reported to be associated with alcohol consumption. These findings provide insights into the role of alcohol consumption in the genetic architecture of hypertension.
Published: 2018

31. Cardiovascular and Renal Risk Factors and Complications Associated With COVID-19

Author: Rhian M. Touyz, MBBCh, PhD, Marcus O.E. Boyd, Tomasz Guzik, MD, PhD, Sandosh Padmanabhan, MD, PhD, Linsay McCallum, MBChB, Christian Delles, MD, Patrick B. Mark, MBChB, PhD, John R. Petrie, MBChB, PhD, Francisco Rios, PhD, Augusto C. Montezano, PhD, Robert Sykes, MBChB, BMedSci, and Colin Berry, MBChB, PhD
Subjects: Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract: The current COVID-19 pandemic, caused by the severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) virus, represents the largest medical challenge in decades. It has exposed unexpected cardiovascular vulnerabilities at all stages of the disease (pre-infection, acute phase, and subsequent chronic phase). The major cardiometabolic drivers identified as having epidemiologic and mechanistic associations with COVID-19 are abnormal adiposity, dysglycemia, dyslipidemia, and hypertension. Hypertension is of particular interest, because components of the renin–angiotensin system (RAS), which are critically involved in the pathophysiology of hypertension, are also implicated in COVID-19. Specifically, angiotensin-converting enzyme-2 (ACE2), a multifunctional protein of the RAS, which is part of the protective axis of the RAS, is also the receptor through which SARS-CoV-2 enters host cells, causing viral infection. Cardiovascular and cardiometabolic comorbidities not only predispose people to COVID-19, but also are complications of SARS-CoV-2 infection. In addition, increasing evidence indicates that acute kidney injury is common in COVID-19, occurs early and in temporal association with respiratory failure, and is associated with poor prognosis, especially in the presence of cardiovascular risk factors. Here, we discuss cardiovascular and kidney disease in the context of COVID-19 and provide recent advances on putative pathophysiological mechanisms linking cardiovascular disease and COVID-19, focusing on the RAS and ACE2, as well as the immune system and inflammation. We provide up-to-date information on the relationships among hypertension, diabetes, and COVID-19 and emphasize the major cardiovascular diseases associated with COVID-19. We also briefly discuss emerging cardiovascular complications associated with long COVID-19, notably postural tachycardia syndrome (POTS). Résumé: La pandémie actuelle de COVID-19 causée par le coronavirus du syndrome respiratoire aigu sévère 2 (SRAS-CoV-2) est le plus grand enjeu médical des dernières décennies. Elle a mis en évidence des vulnérabilités cardiovasculaires imprévues à tous les stades de la COVID-19 (avant l'infection, pendant la phase aiguë et pendant la phase chronique subséquente). Les principaux facteurs cardiométaboliques dont les associations épidémiologiques et mécanistiques avec la COVID-19 ont été avérées comprennent l'adiposité anormale, la dysglycémie, la dyslipidémie et l'hypertension. L'hypertension suscite un intérêt particulier, car certaines composantes du système rénine-angiotensine (SRA), dont le rôle est crucial dans la physiopathologie de l'hypertension, sont également en cause dans la COVID-19. Plus précisément, l'enzyme de conversion de l'angiotensine 2 (ECA2), une protéine multifonctionnelle du SRA faisant partie de l'axe protecteur du SRA, est également le récepteur permettant au virus SRAS-CoV-2 d'entrer dans les cellules hôtes et de provoquer une infection virale. Les affections cardiovasculaires et cardiométaboliques concomitantes ne font pas que prédisposer les personnes qui en sont atteintes à la COVID-19, elles constituent également des complications de l'infection à SRAS-CoV-2. En outre, de plus en plus de données probantes indiquent que l'atteinte rénale aiguë est fréquente en cas de COVID-19, qu'elle survient tôt et fait l'objet d'une association temporelle avec l'insuffisance respiratoire, et qu'elle est associée à un pronostic sombre, notamment en présence de facteurs de risque cardiovasculaires. Nous discutons ici des maladies cardiovasculaires et rénales dans le contexte de la COVID-19, et présentons les progrès récents sur les mécanismes physiopathologiques en cause dans le lien entre les maladies cardiovasculaires et la COVID-19 en nous attardant sur le SRA et l'ECA2, ainsi que sur le système immunitaire et l'inflammation. Nous présentons de l'information à jour sur les liens entre l'hypertension, le diabète et la COVID-19, et soulignons les principales maladies cardiovasculaires associées à la COVID-19. Nous analysons également brièvement les complications cardiovasculaires émergentes associées à la COVID-19 de longue durée, notamment le syndrome de tachycardie orthostatique posturale (STOP).
Published: 2021
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32. The Global Ambulatory Blood Pressure Monitoring (ABPM) in Heart Failure with Preserved Ejection Fraction (HFpEF) Registry. Rationale, design and objectives

Author: Camafort-Babkowski, Miguel, Adeseye, Akintunde, Coca, Antonio, Damasceno, Albertino, De Simone, Giovanni, Dorobantu, Maria, Jhund, Pardeep S., Kario, Kazuomi, Komori, Takahiro, Lee, Hae young, López-Jaramillo, Patricio, Ogah, Okechukwu, Padmanabahn, Sandosh, Pascual-Figal, Domingo A., Pyun, Wook Bum, Renna, Nicolás Federico, Barroso, Weimar Kunz Sebba, Valdez-Tiburcio, Osiris, and Wyss-Quintana, Fernando Stuardo
Published: 2021
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33. Machine learning integration of multimodal data identifies key features of blood pressure regulation

Author: Panayiotis Louca, Tran Quoc Bao Tran, Clea du Toit, Paraskevi Christofidou, Tim D. Spector, Massimo Mangino, Karsten Suhre, Sandosh Padmanabhan, and Cristina Menni
Subjects: Blood pressure, Machine learning, Genomics, Metabolomics, Diet, Medicine, Medicine (General), R5-920
Abstract: Summary: Background: Association studies have identified several biomarkers for blood pressure and hypertension, but a thorough understanding of their mutual dependencies is lacking. By integrating two different high-throughput datasets, biochemical and dietary data, we aim to understand the multifactorial contributors of blood pressure (BP). Methods: We included 4,863 participants from TwinsUK with concurrent BP, metabolomics, genomics, biochemical measures, and dietary data. We used 5-fold cross-validation with the machine learning XGBoost algorithm to identify features of importance in context of one another in TwinsUK (80% training, 20% test). The features tested in TwinsUK were then probed using the same algorithm in an independent dataset of 2,807 individuals from the Qatari Biobank (QBB). Findings: Our model explained 39·2% [4·5%, MAE:11·32 mmHg (95%CI, +/- 0·65)] of the variance in systolic BP (SBP) in TwinsUK. Of the top 50 features, the most influential non-demographic variables were dihomo-linolenate, cis-4-decenoyl carnitine, lactate, chloride, urate, and creatinine along with dietary intakes of total, trans and saturated fat. We also highlight the incremental value of each included dimension. Furthermore, we replicated our model in the QBB [SBP variance explained = 45·2% (13·39%)] cohort and 30 of the top 50 features overlapped between cohorts. Interpretation: We show that an integrated analysis of omics, biochemical and dietary data improves our understanding of their in-between relationships and expands the range of potential biomarkers for blood pressure. Our results point to potentially key biological pathways to be prioritised for mechanistic studies. Funding: Chronic Disease Research Foundation, Medical Research Council, Wellcome Trust, Qatar Foundation.
Published: 2022
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34. Large-scale GWAS identifies multiple loci for hand grip strength providing biological insights into muscular fitness.

Author: Willems, Sara M, Wright, Daniel J, Day, Felix R, Trajanoska, Katerina, Joshi, Peter K, Morris, John A, Matteini, Amy M, Garton, Fleur C, Grarup, Niels, Oskolkov, Nikolay, Thalamuthu, Anbupalam, Mangino, Massimo, Liu, Jun, Demirkan, Ayse, Lek, Monkol, Xu, Liwen, Wang, Guan, Oldmeadow, Christopher, Gaulton, Kyle J, Lotta, Luca A, Miyamoto-Mikami, Eri, Rivas, Manuel A, White, Tom, Loh, Po-Ru, Aadahl, Mette, Amin, Najaf, Attia, John R, Austin, Krista, Benyamin, Beben, Brage, Søren, Cheng, Yu-Ching, Cięszczyk, Paweł, Derave, Wim, Eriksson, Karl-Fredrik, Eynon, Nir, Linneberg, Allan, Lucia, Alejandro, Massidda, Myosotis, Mitchell, Braxton D, Miyachi, Motohiko, Murakami, Haruka, Padmanabhan, Sandosh, Pandey, Ashutosh, Papadimitriou, Ioannis, Rajpal, Deepak K, Sale, Craig, Schnurr, Theresia M, Sessa, Francesco, Shrine, Nick, Tobin, Martin D, Varley, Ian, Wain, Louise V, Wray, Naomi R, Lindgren, Cecilia M, MacArthur, Daniel G, Waterworth, Dawn M, McCarthy, Mark I, Pedersen, Oluf, Khaw, Kay-Tee, Kiel, Douglas P, GEFOS Any-Type of Fracture Consortium, Pitsiladis, Yannis, Fuku, Noriyuki, Franks, Paul W, North, Kathryn N, van Duijn, Cornelia M, Mather, Karen A, Hansen, Torben, Hansson, Ola, Spector, Tim, Murabito, Joanne M, Richards, J Brent, Rivadeneira, Fernando, Langenberg, Claudia, Perry, John RB, Wareham, Nick J, and Scott, Robert A
Subjects: GEFOS Any-Type of Fracture Consortium, Hand, Humans, Actins, Transforming Growth Factor alpha, Membrane Proteins, Neoplasm Proteins, Nuclear Proteins, Repressor Proteins, Hand Strength, Cohort Studies, Genetics, Population, Polymorphism, Single Nucleotide, Adult, Aged, Middle Aged, European Continental Ancestry Group, Female, Male, Genome-Wide Association Study, Genetic Loci, United Kingdom, Prevention, Genetics, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Musculoskeletal
Abstract: Hand grip strength is a widely used proxy of muscular fitness, a marker of frailty, and predictor of a range of morbidities and all-cause mortality. To investigate the genetic determinants of variation in grip strength, we perform a large-scale genetic discovery analysis in a combined sample of 195,180 individuals and identify 16 loci associated with grip strength (P
Published: 2017

35. Discovery of novel heart rate-associated loci using the Exome Chip

Author: van den Berg, Marten E, Warren, Helen R, Cabrera, Claudia P, Verweij, Niek, Mifsud, Borbala, Haessler, Jeffrey, Bihlmeyer, Nathan A, Fu, Yi-Ping, Weiss, Stefan, Lin, Henry J, Grarup, Niels, Li-Gao, Ruifang, Pistis, Giorgio, Shah, Nabi, Brody, Jennifer A, Müller-Nurasyid, Martina, Lin, Honghuang, Mei, Hao, Smith, Albert V, Lyytikäinen, Leo-Pekka, Hall, Leanne M, van Setten, Jessica, Trompet, Stella, Prins, Bram P, Isaacs, Aaron, Radmanesh, Farid, Marten, Jonathan, Entwistle, Aiman, Kors, Jan A, Silva, Claudia T, Alonso, Alvaro, Bis, Joshua C, de Boer, Rudolf, de Haan, Hugoline G, de Mutsert, Renée, Dedoussis, George, Dominiczak, Anna F, Doney, Alex SF, Ellinor, Patrick T, Eppinga, Ruben N, Felix, Stephan B, Guo, Xiuqing, Hagemeijer, Yanick, Hansen, Torben, Harris, Tamara B, Heckbert, Susan R, Huang, Paul L, Hwang, Shih-Jen, Kähönen, Mika, Kanters, Jørgen K, Kolcic, Ivana, Launer, Lenore J, Li, Man, Yao, Jie, Linneberg, Allan, Liu, Simin, Macfarlane, Peter W, Mangino, Massimo, Morris, Andrew D, Mulas, Antonella, Murray, Alison D, Nelson, Christopher P, Orrú, Marco, Padmanabhan, Sandosh, Peters, Annette, Porteous, David J, Poulter, Neil, Psaty, Bruce M, Qi, Lihong, Raitakari, Olli T, Rivadeneira, Fernando, Roselli, Carolina, Rudan, Igor, Sattar, Naveed, Sever, Peter, Sinner, Moritz F, Soliman, Elsayed Z, Spector, Timothy D, Stanton, Alice V, Stirrups, Kathleen E, Taylor, Kent D, Tobin, Martin D, Uitterlinden, André, Vaartjes, Ilonca, Hoes, Arno W, van der Meer, Peter, Völker, Uwe, Waldenberger, Melanie, Xie, Zhijun, Zoledziewska, Magdalena, Tinker, Andrew, Polasek, Ozren, Rosand, Jonathan, Jamshidi, Yalda, van Duijn, Cornelia M, Zeggini, Eleftheria, Jukema, J Wouter, Asselbergs, Folkert W, Samani, Nilesh J, and Lehtimäki, Terho
Subjects: Biological Sciences, Genetics, Human Genome, Biotechnology, Heart Disease, Prevention, Cardiovascular, Stem Cell Research, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Adult, Alleles, Exome, Female, Gene Frequency, Genetic Loci, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Heart Rate, Humans, Male, Middle Aged, Oligonucleotide Array Sequence Analysis, Polymorphism, Single Nucleotide, Risk Factors, White People, Medical and Health Sciences, Genetics & Heredity
Abstract: Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. Genome-wide association study analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation. This study aims to discover new genetic loci associated with heart rate from Exome Chip meta-analyses.Heart rate was measured from either elecrtrocardiograms or pulse recordings. We meta-analysed heart rate association results from 104 452 European-ancestry individuals from 30 cohorts, genotyped using the Exome Chip. Twenty-four variants were selected for follow-up in an independent dataset (UK Biobank, N = 134 251). Conditional and gene-based testing was undertaken, and variants were investigated with bioinformatics methods.We discovered five novel heart rate loci, and one new independent low-frequency non-synonymous variant in an established heart rate locus (KIAA1755). Lead variants in four of the novel loci are non-synonymous variants in the genes C10orf71, DALDR3, TESK2 and SEC31B. The variant at SEC31B is significantly associated with SEC31B expression in heart and tibial nerve tissue. Further candidate genes were detected from long-range regulatory chromatin interactions in heart tissue (SCD, SLF2 and MAPK8). We observed significant enrichment in DNase I hypersensitive sites in fetal heart and lung. Moreover, enrichment was seen for the first time in human neuronal progenitor cells (derived from embryonic stem cells) and fetal muscle samples by including our novel variants.Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies.
Published: 2017

36. Z-K-R: A Novel Framework in Intrusion Detection system through enhanced techniques

Author: Sandosh, S., Bala, Akila, and Kodipyaka, Nithin
Abstract: Intrusion detection systems (IDS) are an important tool for securing computer networks from various types of cyberattacks. The increasing complexity of network attacks demands more sophisticated approaches to intrusion detection. This paper presents an innovative method for IDS that involves combining Z-Score outlier detection, KMeans clustering, and Random Forest classification techniques. We tested our methodology using the CICIDS2017 dataset, which is a standardization dataset for intrusion detection that is frequently utilized. Our proposed approach first uses Z-Score outlier detection to identify abnormal traffic flows in the network. Next, KMeans clustering is used to group the traffic flows into different clusters based on their similarity. Finally, Random Forest classification is used to classify each traffic flow into normal or abnormal categories. Based on our experimental results, our approach for intrusion detection shows superior performance compared to several other state-of-the-art methods in terms of accuracy and precision. Our proposed method achieved an accuracy rate of 95.75% and a precision of 95.76%, surpassing the performance of KNN, SVM, and decision trees approaches. In conclusion, the proposed Z-K-R approach offers a promising solution for IDS by leveraging the strengths of Z-Score outlier detection, KMeans clustering, and Random Forest classification techniques. This strategy has the potential to increase the efficiency of IDS and boost network security in applications that take place in the real world.
Published: 2024
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37. Genetic and shared couple environmental contributions to smoking and alcohol use in the UK population

Author: Clarke, Toni-Kim, Adams, Mark J., Howard, David M., Xia, Charley, Davies, Gail, Hayward, Caroline, Campbell, Archie, Padmanabhan, Sandosh, Smith, Blair H., Murray, Alison, Porteous, David, Deary, Ian J., and McIntosh, Andrew M.
Published: 2021
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38. Morphology controlled synthesis of one-dimensional CoMn2O4 nanorods for high-performance supercapacitor electrode application

Author: Sandosh, T. Antony and Simi, A.
Published: 2021
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39. Rationale and Design for the LOnger-term effects of SARS-CoV-2 INfection on blood Vessels And blood pRessure (LOCHINVAR): an observational phenotyping study

Author: Colin Berry, Christian Delles, Rhian Touyz, Sandosh Padmanabhan, John D McClure, Tomasz Guzik, Stefanie Lip, and Linsay Mccallum
Subjects: Diseases of the circulatory (Cardiovascular) system, RC666-701
Published: 2022
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40. Genomics of hypertension: the road to precision medicine

Author: Padmanabhan, Sandosh and Dominiczak, Anna F.
Published: 2021
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41. Beyond Genome-Wide Scans: Advancing Hypertension Genomics Into the Future.

Author: Padmanabhan, Sandosh, Delles, Christian, and Dominiczak, Anna F.
Abstract: The article discusses the advancements in hypertension genomics and the challenges in translating genetic findings into clinical applications. It highlights the role of genome-wide association studies (GWAS) in identifying genetic variants associated with blood pressure and the potential for these insights to inform drug discovery and development. The article also emphasizes the importance of functional validation of GWAS-identified variants, decoding multifactorial phenotypes, and making genomics more equitable by including diverse populations in research. It concludes by calling for international collaboration and the establishment of ethical guidelines to promote inclusive and diverse genomic research in hypertension. [Extracted from the article]
Published: 2024
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42. Editorial: Pharmacogenomics: From Bench to Bedside and Back Again

Author: Jeffrey A. Shaman, Chad A. Bousman, Christina Mitropoulou, and Sandosh Padmanabhan
Subjects: pharmacogenomics, cytochrome P450, HLA antigens, incidental findings, clinical practice, clinical implementation, Genetics, QH426-470
Published: 2022
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43. Facile and Cost-Effective CTAB Templated Hydrothermal Synthesis and Characterization of MgCo2O4 Electrode Material for Supercapacitor Application

Author: Sandosh, T. Antony and Simi, A.
Published: 2021
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44. 52 Genetic Loci Influencing Myocardial Mass

Author: van der Harst, Pim, van Setten, Jessica, Verweij, Niek, Vogler, Georg, Franke, Lude, Maurano, Matthew T, Wang, Xinchen, Leach, Irene Mateo, Eijgelsheim, Mark, Sotoodehnia, Nona, Hayward, Caroline, Sorice, Rossella, Meirelles, Osorio, Lyytikäinen, Leo-Pekka, Polašek, Ozren, Tanaka, Toshiko, Arking, Dan E, Ulivi, Sheila, Trompet, Stella, Müller-Nurasyid, Martina, Smith, Albert V, Dörr, Marcus, Kerr, Kathleen F, Magnani, Jared W, Del Greco M., Fabiola, Zhang, Weihua, Nolte, Ilja M, Silva, Claudia T, Padmanabhan, Sandosh, Tragante, Vinicius, Esko, Tõnu, Abecasis, Gonçalo R, Adriaens, Michiel E, Andersen, Karl, Barnett, Phil, Bis, Joshua C, Bodmer, Rolf, Buckley, Brendan M, Campbell, Harry, Cannon, Megan V, Chakravarti, Aravinda, Chen, Lin Y, Delitala, Alessandro, Devereux, Richard B, Doevendans, Pieter A, Dominiczak, Anna F, Ferrucci, Luigi, Ford, Ian, Gieger, Christian, Harris, Tamara B, Haugen, Eric, Heinig, Matthias, Hernandez, Dena G, Hillege, Hans L, Hirschhorn, Joel N, Hofman, Albert, Hubner, Norbert, Hwang, Shih-Jen, Iorio, Annamaria, Kähönen, Mika, Kellis, Manolis, Kolcic, Ivana, Kooner, Ishminder K, Kooner, Jaspal S, Kors, Jan A, Lakatta, Edward G, Lage, Kasper, Launer, Lenore J, Levy, Daniel, Lundby, Alicia, Macfarlane, Peter W, May, Dalit, Meitinger, Thomas, Metspalu, Andres, Nappo, Stefania, Naitza, Silvia, Neph, Shane, Nord, Alex S, Nutile, Teresa, Okin, Peter M, Olsen, Jesper V, Oostra, Ben A, Penninger, Josef M, Pennacchio, Len A, Pers, Tune H, Perz, Siegfried, Peters, Annette, Pinto, Yigal M, Pfeufer, Arne, Pilia, Maria Grazia, Pramstaller, Peter P, Prins, Bram P, Raitakari, Olli T, Raychaudhuri, Soumya, Rice, Ken M, Rossin, Elizabeth J, Rotter, Jerome I, Schafer, Sebastian, Schlessinger, David, and Schmidt, Carsten O
Subjects: Medical Physiology, Biomedical and Clinical Sciences, Genetics, Heart Disease - Coronary Heart Disease, Cardiovascular, Heart Disease, Biotechnology, Human Genome, 2.1 Biological and endogenous factors, Animals, Cardiomegaly, Genetic Loci, Genome-Wide Association Study, Humans, electrocardiogram, genetic association study, heart failure, left ventricular hypertrophy, QRS, Cardiorespiratory Medicine and Haematology, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology
Abstract: BackgroundMyocardial mass is a key determinant of cardiac muscle function and hypertrophy. Myocardial depolarization leading to cardiac muscle contraction is reflected by the amplitude and duration of the QRS complex on the electrocardiogram (ECG). Abnormal QRS amplitude or duration reflect changes in myocardial mass and conduction, and are associated with increased risk of heart failure and death.ObjectivesThis meta-analysis sought to gain insights into the genetic determinants of myocardial mass.MethodsWe carried out a genome-wide association meta-analysis of 4 QRS traits in up to 73,518 individuals of European ancestry, followed by extensive biological and functional assessment.ResultsWe identified 52 genomic loci, of which 32 are novel, that are reliably associated with 1 or more QRS phenotypes at p < 1 × 10(-8). These loci are enriched in regions of open chromatin, histone modifications, and transcription factor binding, suggesting that they represent regions of the genome that are actively transcribed in the human heart. Pathway analyses provided evidence that these loci play a role in cardiac hypertrophy. We further highlighted 67 candidate genes at the identified loci that are preferentially expressed in cardiac tissue and associated with cardiac abnormalities in Drosophila melanogaster and Mus musculus. We validated the regulatory function of a novel variant in the SCN5A/SCN10A locus in vitro and in vivo.ConclusionsTaken together, our findings provide new insights into genes and biological pathways controlling myocardial mass and may help identify novel therapeutic targets.
Published: 2016

45. An Empirical Comparison of Joint and Stratified Frameworks for Studying G × E Interactions: Systolic Blood Pressure and Smoking in the CHARGE Gene‐Lifestyle Interactions Working Group

Author: Sung, Yun Ju, Winkler, Thomas W, Manning, Alisa K, Aschard, Hugues, Gudnason, Vilmundur, Harris, Tamara B, Smith, Albert V, Boerwinkle, Eric, Brown, Michael R, Morrison, Alanna C, Fornage, Myriam, Lin, Li-An, Richard, Melissa, Bartz, Traci M, Psaty, Bruce M, Hayward, Caroline, Polasek, Ozren, Marten, Jonathan, Rudan, Igor, Feitosa, Mary F, Kraja, Aldi T, Province, Michael A, Deng, Xuan, Fisher, Virginia A, Zhou, Yanhua, Bielak, Lawrence F, Smith, Jennifer, Huffman, Jennifer E, Padmanabhan, Sandosh, Smith, Blair H, Ding, Jingzhong, Liu, Yongmei, Lohman, Kurt, Bouchard, Claude, Rankinen, Tuomo, Rice, Treva K, Arnett, Donna, Schwander, Karen, Guo, Xiuqing, Palmas, Walter, Rotter, Jerome I, Alfred, Tamuno, Bottinger, Erwin P, Loos, Ruth JF, Amin, Najaf, Franco, Oscar H, van Duijn, Cornelia M, Vojinovic, Dina, Chasman, Daniel I, Ridker, Paul M, Rose, Lynda M, Kardia, Sharon, Zhu, Xiaofeng, Rice, Kenneth, Borecki, Ingrid B, Rao, Dabeeru C, Gauderman, W James, and Cupples, L Adrienne
Subjects: Epidemiology, Biological Sciences, Health Sciences, Genetics, Clinical Research, Human Genome, Blood Pressure, Cohort Studies, Databases, Factual, Family, Gene Frequency, Gene-Environment Interaction, Genome-Wide Association Study, Genotype, Humans, Phenotype, Smoking, gene-environment interaction, meta-analysis, low-frequency variants, Public Health and Health Services
Abstract: Studying gene-environment (G × E) interactions is important, as they extend our knowledge of the genetic architecture of complex traits and may help to identify novel variants not detected via analysis of main effects alone. The main statistical framework for studying G × E interactions uses a single regression model that includes both the genetic main and G × E interaction effects (the "joint" framework). The alternative "stratified" framework combines results from genetic main-effect analyses carried out separately within the exposed and unexposed groups. Although there have been several investigations using theory and simulation, an empirical comparison of the two frameworks is lacking. Here, we compare the two frameworks using results from genome-wide association studies of systolic blood pressure for 3.2 million low frequency and 6.5 million common variants across 20 cohorts of European ancestry, comprising 79,731 individuals. Our cohorts have sample sizes ranging from 456 to 22,983 and include both family-based and population-based samples. In cohort-specific analyses, the two frameworks provided similar inference for population-based cohorts. The agreement was reduced for family-based cohorts. In meta-analyses, agreement between the two frameworks was less than that observed in cohort-specific analyses, despite the increased sample size. In meta-analyses, agreement depended on (1) the minor allele frequency, (2) inclusion of family-based cohorts in meta-analysis, and (3) filtering scheme. The stratified framework appears to approximate the joint framework well only for common variants in population-based cohorts. We conclude that the joint framework is the preferred approach and should be used to control false positives when dealing with low-frequency variants and/or family-based cohorts.
Published: 2016

46. Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Author: van Leeuwen, Elisabeth M, Sabo, Aniko, Bis, Joshua C, Huffman, Jennifer E, Manichaikul, Ani, Smith, Albert V, Feitosa, Mary F, Demissie, Serkalem, Joshi, Peter K, Duan, Qing, Marten, Jonathan, van Klinken, Jan B, Surakka, Ida, Nolte, Ilja M, Zhang, Weihua, Mbarek, Hamdi, Li-Gao, Ruifang, Trompet, Stella, Verweij, Niek, Evangelou, Evangelos, Lyytikäinen, Leo-Pekka, Tayo, Bamidele O, Deelen, Joris, van der Most, Peter J, van der Laan, Sander W, Arking, Dan E, Morrison, Alanna, Dehghan, Abbas, Franco, Oscar H, Hofman, Albert, Rivadeneira, Fernando, Sijbrands, Eric J, Uitterlinden, Andre G, Mychaleckyj, Josyf C, Campbell, Archie, Hocking, Lynne J, Padmanabhan, Sandosh, Brody, Jennifer A, Rice, Kenneth M, White, Charles C, Harris, Tamara, Isaacs, Aaron, Campbell, Harry, Lange, Leslie A, Rudan, Igor, Kolcic, Ivana, Navarro, Pau, Zemunik, Tatijana, Salomaa, Veikko, Study, The LifeLines Cohort, Kooner, Angad S, Kooner, Jaspal S, Lehne, Benjamin, Scott, William R, Tan, Sian-Tsung, de Geus, Eco J, Milaneschi, Yuri, Penninx, Brenda WJH, Willemsen, Gonneke, de Mutsert, Renée, Ford, Ian, Gansevoort, Ron T, Segura-Lepe, Marcelo P, Raitakari, Olli T, Viikari, Jorma S, Nikus, Kjell, Forrester, Terrence, McKenzie, Colin A, de Craen, Anton JM, de Ruijter, Hester M, Group, CHARGE Lipids Working, Pasterkamp, Gerard, Snieder, Harold, Oldehinkel, Albertine J, Slagboom, P Eline, Cooper, Richard S, Kähönen, Mika, Lehtimäki, Terho, Elliott, Paul, van der Harst, Pim, Jukema, J Wouter, Mook-Kanamori, Dennis O, Boomsma, Dorret I, Chambers, John C, Swertz, Morris, Ripatti, Samuli, van Dijk, Ko Willems, Vitart, Veronique, Polasek, Ozren, Hayward, Caroline, Wilson, James G, Wilson, James F, Gudnason, Vilmundur, Rich, Stephen S, Psaty, Bruce M, Borecki, Ingrid B, Boerwinkle, Eric, Rotter, Jerome I, Cupples, L Adrienne, and van Duijn, Cornelia M
Subjects: Biological Sciences, Genetics, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Angiopoietin-Like Protein 4, Angiopoietins, Exons, Fasting, Female, Genome, Human, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, LifeLines Cohort Study, CHARGE Lipids Working Group, Complex traits, Epidemiology, Genome-wide, circulating lipid levels, Medical and Health Sciences, Genetics & Heredity, Clinical sciences
Abstract: BackgroundSo far, more than 170 loci have been associated with circulating lipid levels through genome-wide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels.MethodsWe used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ∼60 000 individuals in the discovery stage and ∼90 000 samples in the replication stage.ResultsOur study resulted in the identification of five new associations with circulating lipid levels at four loci. All four loci are within genes that can be linked biologically to lipid metabolism. One of the variants, rs116843064, is a damaging missense variant within the ANGPTL4 gene.ConclusionsThis study illustrates that GWAS with high-scale imputation may still help us unravel the biological mechanism behind circulating lipid levels.
Published: 2016

47. Facile Cetyl Trimethyl Ammonium Bromide-assisted Hydrothermal Synthesis of Spinel NiCo2O4 Nanoplates as an Electrode Material for Supercapacitor Application

Author: Sandosh, Thiruthuvadevaraj Antony, Simi, Albert, Doss, Francisxavier Paul Arokia, Adaikalaraj, Chinnappan, and Nikson, Savariappan Albert
Published: 2020
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48. Blood pressure–lowering activity of statins: a systematic literature review and meta-analysis of placebo-randomized controlled trials

Author: Alghamdi, Jahad, Alqadi, Abdulziz, Alharf, Adel, Almuzzaini, Bader, Mahmud, Azra, Barhoumi, Tlili, Badreldin, Hisham A, Alaamery, Manal, and Padmanabhan, Sandosh
Published: 2020
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49. Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction

Author: Ioanna Ntalla, Lu-Chen Weng, James H. Cartwright, Amelia Weber Hall, Gardar Sveinbjornsson, Nathan R. Tucker, Seung Hoan Choi, Mark D. Chaffin, Carolina Roselli, Michael R. Barnes, Borbala Mifsud, Helen R. Warren, Caroline Hayward, Jonathan Marten, James J. Cranley, Maria Pina Concas, Paolo Gasparini, Thibaud Boutin, Ivana Kolcic, Ozren Polasek, Igor Rudan, Nathalia M. Araujo, Maria Fernanda Lima-Costa, Antonio Luiz P. Ribeiro, Renan P. Souza, Eduardo Tarazona-Santos, Vilmantas Giedraitis, Erik Ingelsson, Anubha Mahajan, Andrew P. Morris, Fabiola Del Greco M, Luisa Foco, Martin Gögele, Andrew A. Hicks, James P. Cook, Lars Lind, Cecilia M. Lindgren, Johan Sundström, Christopher P. Nelson, Muhammad B. Riaz, Nilesh J. Samani, Gianfranco Sinagra, Sheila Ulivi, Mika Kähönen, Pashupati P. Mishra, Nina Mononen, Kjell Nikus, Mark J. Caulfield, Anna Dominiczak, Sandosh Padmanabhan, May E. Montasser, Jeff R. O’Connell, Kathleen Ryan, Alan R. Shuldiner, Stefanie Aeschbacher, David Conen, Lorenz Risch, Sébastien Thériault, Nina Hutri-Kähönen, Terho Lehtimäki, Leo-Pekka Lyytikäinen, Olli T. Raitakari, Catriona L. K. Barnes, Harry Campbell, Peter K. Joshi, James F. Wilson, Aaron Isaacs, Jan A. Kors, Cornelia M. van Duijn, Paul L. Huang, Vilmundur Gudnason, Tamara B. Harris, Lenore J. Launer, Albert V. Smith, Erwin P. Bottinger, Ruth J. F. Loos, Girish N. Nadkarni, Michael H. Preuss, Adolfo Correa, Hao Mei, James Wilson, Thomas Meitinger, Martina Müller-Nurasyid, Annette Peters, Melanie Waldenberger, Massimo Mangino, Timothy D. Spector, Michiel Rienstra, Yordi J. van de Vegte, Pim van der Harst, Niek Verweij, Stefan Kääb, Katharina Schramm, Moritz F. Sinner, Konstantin Strauch, Michael J. Cutler, Diane Fatkin, Barry London, Morten Olesen, Dan M. Roden, M. Benjamin Shoemaker, J. Gustav Smith, Mary L. Biggs, Joshua C. Bis, Jennifer A. Brody, Bruce M. Psaty, Kenneth Rice, Nona Sotoodehnia, Alessandro De Grandi, Christian Fuchsberger, Cristian Pattaro, Peter P. Pramstaller, Ian Ford, J. Wouter Jukema, Peter W. Macfarlane, Stella Trompet, Marcus Dörr, Stephan B. Felix, Uwe Völker, Stefan Weiss, Aki S. Havulinna, Antti Jula, Katri Sääksjärvi, Veikko Salomaa, Xiuqing Guo, Susan R. Heckbert, Henry J. Lin, Jerome I. Rotter, Kent D. Taylor, Jie Yao, Renée de Mutsert, Arie C. Maan, Dennis O. Mook-Kanamori, Raymond Noordam, Francesco Cucca, Jun Ding, Edward G. Lakatta, Yong Qian, Kirill V. Tarasov, Daniel Levy, Honghuang Lin, Christopher H. Newton-Cheh, Kathryn L. Lunetta, Alison D. Murray, David J. Porteous, Blair H. Smith, Bruno H. Stricker, André Uitterlinden, Marten E. van den Berg, Jeffrey Haessler, Rebecca D. Jackson, Charles Kooperberg, Ulrike Peters, Alexander P. Reiner, Eric A. Whitsel, Alvaro Alonso, Dan E. Arking, Eric Boerwinkle, Georg B. Ehret, Elsayed Z. Soliman, Christy L. Avery, Stephanie M. Gogarten, Kathleen F. Kerr, Cathy C. Laurie, Amanda A. Seyerle, Adrienne Stilp, Solmaz Assa, M. Abdullah Said, M. Yldau van der Ende, Pier D. Lambiase, Michele Orini, Julia Ramirez, Stefan Van Duijvenboden, David O. Arnar, Daniel F. Gudbjartsson, Hilma Holm, Patrick Sulem, Gudmar Thorleifsson, Rosa B. Thorolfsdottir, Unnur Thorsteinsdottir, Emelia J. Benjamin, Andrew Tinker, Kari Stefansson, Patrick T. Ellinor, Yalda Jamshidi, Steven A. Lubitz, and Patricia B. Munroe
Subjects: Science
Abstract: On the electrocardiogram, the PR interval reflects conduction from the atria to ventricles and also serves as risk indicator of cardiovascular morbidity and mortality. Here, the authors perform genome-wide meta-analyses for PR interval in multiple ancestries and identify 141 previously unreported genetic loci.
Published: 2020
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50. Incremental Value of a Panel of Serum Metabolites for Predicting Risk of Atherosclerotic Cardiovascular Disease

Author: Ana Nogal, Panayiotis Louca, Tran Quoc Bao Tran, Ruth C. Bowyer, Paraskevi Christofidou, Claire J. Steves, Sarah E. Berry, Kari Wong, Jonathan Wolf, Paul W. Franks, Massimo Mangino, Tim D. Spector, Ana M. Valdes, Sandosh Padmanabhan, and Cristina Menni
Subjects: atherosclerosis, biomarkers, cardiovascular disease risk, machine learning, serum metabolites, Diseases of the circulatory (Cardiovascular) system, RC666-701
Published: 2022
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