151
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Merino J, Jablonski KA, Mercader JM, Kahn SE, Chen L, Harden M, Delahanty LM, Araneta MRG, Walford GA, Jacobs SB, Ibebuogu UN, Franks PW, Knowler WC, Florez JC. Interaction Between Type 2 Diabetes Prevention Strategies and Genetic Determinants of Coronary Artery Disease on Cardiometabolic Risk Factors. Diabetes 2020; 69:112-120. [PMID: 31636172 PMCID: PMC6925585 DOI: 10.2337/db19-0097] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Accepted: 10/17/2019] [Indexed: 01/09/2023]
Abstract
Coronary artery disease (CAD) is more frequent among individuals with dysglycemia. Preventive interventions for diabetes can improve cardiometabolic risk factors (CRFs), but it is unclear whether the benefits on CRFs are similar for individuals at different genetic risk for CAD. We built a 201-variant polygenic risk score (PRS) for CAD and tested for interaction with diabetes prevention strategies on 1-year changes in CRFs in 2,658 Diabetes Prevention Program (DPP) participants. We also examined whether separate lifestyle behaviors interact with PRS and affect changes in CRFs in each intervention group. Participants in both the lifestyle and metformin interventions had greater improvement in the majority of recognized CRFs compared with placebo (P < 0.001) irrespective of CAD genetic risk (P interaction > 0.05). We detected nominal significant interactions between PRS and dietary quality and physical activity on 1-year change in BMI, fasting glucose, triglycerides, and HDL cholesterol in individuals randomized to metformin or placebo, but none of them achieved the multiple-testing correction for significance. This study confirms that diabetes preventive interventions improve CRFs regardless of CAD genetic risk and delivers hypothesis-generating data on the varying benefit of increasing physical activity and improving diet on intermediate cardiovascular risk factors depending on individual CAD genetic risk profile.
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Affiliation(s)
- Jordi Merino
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
- Research Unit on Lipids and Atherosclerosis, CIBERDEM, Institut d’Investigació Sanitària Pere Virgili, Universitat Rovira i Virgili, Reus, Spain
| | - Kathleen A. Jablonski
- The Biostatistics Center, Department of Epidemiology and Biostatistics, Milken Institute School of Public Health, The George Washington University, Rockville, MD
| | - Josep M. Mercader
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA
| | - Steven E. Kahn
- Division of Metabolism, Endocrinology and Nutrition, VA Puget Sound Health Care System and University of Washington, Seattle, WA
| | - Ling Chen
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA
| | - Maegan Harden
- Genomics Platform, Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA
| | - Linda M. Delahanty
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
- Department of Medicine, Harvard Medical School, Boston, MA
| | - Maria Rosario G. Araneta
- Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA
| | - Geoffrey A. Walford
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
| | - Suzanne B.R. Jacobs
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA
| | - Uzoma N. Ibebuogu
- Division of Cardiovascular Diseases, Department of Medicine, The University of Tennessee Health Science Center, Memphis, TN
| | - Paul W. Franks
- Genetic & Molecular Epidemiology Unit, Lund University Diabetes Centre, Malmo, Sweden
- Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - William C. Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Jose C. Florez
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA
- Programs in Metabolism and Medical and Population Genetics, Eli and Edythe L. Broad Institute of MIT and Harvard, Cambridge, MA
- Department of Medicine, Harvard Medical School, Boston, MA
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152
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Nakato R, Wada Y, Nakaki R, Nagae G, Katou Y, Tsutsumi S, Nakajima N, Fukuhara H, Iguchi A, Kohro T, Kanki Y, Saito Y, Kobayashi M, Izumi-Taguchi A, Osato N, Tatsuno K, Kamio A, Hayashi-Takanaka Y, Wada H, Ohta S, Aikawa M, Nakajima H, Nakamura M, McGee RC, Heppner KW, Kawakatsu T, Genno M, Yanase H, Kume H, Senbonmatsu T, Homma Y, Nishimura S, Mitsuyama T, Aburatani H, Kimura H, Shirahige K. Comprehensive epigenome characterization reveals diverse transcriptional regulation across human vascular endothelial cells. Epigenetics Chromatin 2019; 12:77. [PMID: 31856914 PMCID: PMC6921469 DOI: 10.1186/s13072-019-0319-0] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Accepted: 12/03/2019] [Indexed: 01/19/2023] Open
Abstract
Background Endothelial cells (ECs) make up the innermost layer throughout the entire vasculature. Their phenotypes and physiological functions are initially regulated by developmental signals and extracellular stimuli. The underlying molecular mechanisms responsible for the diverse phenotypes of ECs from different organs are not well understood. Results To characterize the transcriptomic and epigenomic landscape in the vascular system, we cataloged gene expression and active histone marks in nine types of human ECs (generating 148 genome-wide datasets) and carried out a comprehensive analysis with chromatin interaction data. We developed a robust procedure for comparative epigenome analysis that circumvents variations at the level of the individual and technical noise derived from sample preparation under various conditions. Through this approach, we identified 3765 EC-specific enhancers, some of which were associated with disease-associated genetic variations. We also identified various candidate marker genes for each EC type. We found that the nine EC types can be divided into two subgroups, corresponding to those with upper-body origins and lower-body origins, based on their epigenomic landscape. Epigenomic variations were highly correlated with gene expression patterns, but also provided unique information. Most of the deferentially expressed genes and enhancers were cooperatively enriched in more than one EC type, suggesting that the distinct combinations of multiple genes play key roles in the diverse phenotypes across EC types. Notably, many homeobox genes were differentially expressed across EC types, and their expression was correlated with the relative position of each organ in the body. This reflects the developmental origins of ECs and their roles in angiogenesis, vasculogenesis and wound healing. Conclusions This comprehensive analysis of epigenome characterization of EC types reveals diverse transcriptional regulation across human vascular systems. These datasets provide a valuable resource for understanding the vascular system and associated diseases.
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Affiliation(s)
- Ryuichiro Nakato
- Laboratory of Computational Genomics, Institute for Quantitative Biosciences, The University of Tokyo, Tokyo, 113-0032, Japan.,Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan
| | - Youichiro Wada
- Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan. .,Isotope Science Center, The University of Tokyo, Tokyo, 113-0032, Japan.
| | - Ryo Nakaki
- Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, 153-8904, Japan
| | - Genta Nagae
- Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan.,Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, 153-8904, Japan
| | - Yuki Katou
- Laboratory of Genome Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, Tokyo, 113-0032, Japan
| | - Shuichi Tsutsumi
- Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, 153-8904, Japan
| | - Natsu Nakajima
- Laboratory of Computational Genomics, Institute for Quantitative Biosciences, The University of Tokyo, Tokyo, 113-0032, Japan
| | - Hiroshi Fukuhara
- Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan
| | - Atsushi Iguchi
- Department of Cardiovascular Surgery, Saitama Medical University International Medical Center, Saitama, 350-1298, Japan
| | - Takahide Kohro
- Department of Clinical Informatics, Jichi Medical University School of Medicine, Shimotsuke, 329-0498, Japan
| | - Yasuharu Kanki
- Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan.,Isotope Science Center, The University of Tokyo, Tokyo, 113-0032, Japan
| | - Yutaka Saito
- Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan.,Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan.,Computational Bio Big-Data Open Innovation Laboratory (CBBD-OIL), National Institute of Advanced Industrial Science and Technology (AIST), 3-4-1 Okubo, Shinjuku-ku, Tokyo, 169-8555, Japan
| | - Mika Kobayashi
- Isotope Science Center, The University of Tokyo, Tokyo, 113-0032, Japan
| | | | - Naoki Osato
- Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan.,Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, 153-8904, Japan
| | - Kenji Tatsuno
- Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, 153-8904, Japan
| | - Asuka Kamio
- Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, 153-8904, Japan
| | - Yoko Hayashi-Takanaka
- Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan.,Cell Biology Center, Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, 226-8503, Japan
| | - Hiromi Wada
- Isotope Science Center, The University of Tokyo, Tokyo, 113-0032, Japan.,Brain Attack Center, Ohta Memorial Hospital, Fukuyama, 720-0825, Japan
| | - Shinzo Ohta
- Brain Attack Center, Ohta Memorial Hospital, Fukuyama, 720-0825, Japan
| | - Masanori Aikawa
- The Center for Excellence in Vascular Biology and the Center for Interdisciplinary Cardiovascular Sciences, Cardiovascular Division and Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Hiroyuki Nakajima
- Department of Cardiovascular Surgery, Saitama Medical University International Medical Center, Saitama, 350-1298, Japan
| | - Masaki Nakamura
- Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan
| | | | | | - Tatsuo Kawakatsu
- Bio-Medical Department, Kurabo Industries Ltd., Neyagawa, Osaka, 572-0823, Japan
| | - Michiru Genno
- Bio-Medical Department, Kurabo Industries Ltd., Neyagawa, Osaka, 572-0823, Japan
| | - Hiroshi Yanase
- Bio-Medical Department, Kurabo Industries Ltd., Neyagawa, Osaka, 572-0823, Japan
| | - Haruki Kume
- Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan
| | - Takaaki Senbonmatsu
- Department of Cardiology, Saitama Medical University International Medical Center, Saitama, 350-1298, Japan
| | - Yukio Homma
- Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo, 113-8655, Japan
| | - Shigeyuki Nishimura
- Department of Cardiology, Saitama Medical University International Medical Center, Saitama, 350-1298, Japan
| | - Toutai Mitsuyama
- Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan.,Artificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-4-7 Aomi, Koto-ku, Tokyo, 135-0064, Japan
| | - Hiroyuki Aburatani
- Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan.,Genome Science Division, Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, 153-8904, Japan
| | - Hiroshi Kimura
- Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan. .,Cell Biology Center, Institute of Innovative Research, Tokyo Institute of Technology, Yokohama, 226-8503, Japan. .,Laboratory of Functional Nuclear Imaging, Institute for Quantitative Biosciences, The University of Tokyo, Tokyo, 113-0032, Japan.
| | - Katsuhiko Shirahige
- Japan Agency for Medical Research and Development (AMED-CREST), AMED, 1-7-1 Otemachi, Chiyoda-ku, Tokyo, 100-0004, Japan. .,Laboratory of Genome Structure and Function, Institute for Quantitative Biosciences, The University of Tokyo, Tokyo, 113-0032, Japan.
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153
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Benjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Das SR, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Jordan LC, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, O'Flaherty M, Pandey A, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Spartano NL, Stokes A, Tirschwell DL, Tsao CW, Turakhia MP, VanWagner LB, Wilkins JT, Wong SS, Virani SS. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Circulation 2019; 139:e56-e528. [PMID: 30700139 DOI: 10.1161/cir.0000000000000659] [Citation(s) in RCA: 5401] [Impact Index Per Article: 1080.2] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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154
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Abstract
The kidney harbours different types of endothelia, each with specific structural and functional characteristics. The glomerular endothelium, which is highly fenestrated and covered by a rich glycocalyx, participates in the sieving properties of the glomerular filtration barrier and in the maintenance of podocyte structure. The microvascular endothelium in peritubular capillaries, which is also fenestrated, transports reabsorbed components and participates in epithelial cell function. The endothelium of large and small vessels supports the renal vasculature. These renal endothelia are protected by regulators of thrombosis, inflammation and complement, but endothelial injury (for example, induced by toxins, antibodies, immune cells or inflammatory cytokines) or defects in factors that provide endothelial protection (for example, regulators of complement or angiogenesis) can lead to acute or chronic renal injury. Moreover, renal endothelial cells can transition towards a mesenchymal phenotype, favouring renal fibrosis and the development of chronic kidney disease. Thus, the renal endothelium is both a target and a driver of kidney and systemic cardiovascular complications. Emerging therapeutic strategies that target the renal endothelium may lead to improved outcomes for both rare and common renal diseases.
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155
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Sun D, Zhou T, Li X, Heianza Y, Liang Z, Bray GA, Sacks FM, Qi L. Genetic Susceptibility, Dietary Protein Intake, and Changes of Blood Pressure: The POUNDS Lost Trial. Hypertension 2019; 74:1460-1467. [PMID: 31656094 PMCID: PMC6854315 DOI: 10.1161/hypertensionaha.119.13510] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Accepted: 07/18/2019] [Indexed: 02/06/2023]
Abstract
High blood pressure (BP) is closely related to obesity, and weight loss lowers BP. Evidence has shown considerable interpersonal variation of changes in BP among people experiencing weight loss, and such variation might be partly determined by genetic factors. We assessed the changes in systolic and diastolic BP (SBP/DBP) among 692 participants randomly assigned to 1 of 4 diets varying in macronutrient content for 2 years. Two separate polygenic scores (SBP/DBP-PGS derived from 52/50 single nucleotide polymorphisms) were built for each participant based on 66 BP-associated single nucleotide polymorphisms. During a 2-year intervention, participants in the bottom versus upper tertile of SBP/DBP-PGS had a greater decrease in SBP (△SBP at 6, 12, and 24 months: -3.84 versus -1.61, -4.76 versus -2.75, -2.49 versus -1.63; P=0.001) or in DBP (△DBP at 6, 12, and 24 months: -3.09 versus -1.34, -2.69 versus -1.44, -1.82 versus -0.53; P<0.001). We also found gene-diet interaction on changes in SBP from baseline to 24 months (Pinteraction=0.009). Among participants assigned to a high-protein diet, those with a lower SBP-polygenic scores had greater decreases in SBP at months 6 (P=0.018), months 12 (P=0.007), and months 24 (P=0.089); while no significant difference was observed across the SBP-polygenic scores tertile groups among those assigned to an average-protein diet (all P values >0.05). Our data indicate that genetic susceptibility may affect BP changes in response to weight-loss diet interventions, and protein intake may modify the genetic associations with changes in BP. This trial was registered at URL: http://www.clinicaltrials.gov. Unique identifier: NCT00072995.
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Affiliation(s)
- Dianjianyi Sun
- From the Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA (D.S., T.Z., X.L., Y.H., Z.L., L.Q.)
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China (D.S.)
| | - Tao Zhou
- From the Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA (D.S., T.Z., X.L., Y.H., Z.L., L.Q.)
| | - Xiang Li
- From the Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA (D.S., T.Z., X.L., Y.H., Z.L., L.Q.)
| | - Yoriko Heianza
- From the Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA (D.S., T.Z., X.L., Y.H., Z.L., L.Q.)
| | - Zhaoxia Liang
- From the Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA (D.S., T.Z., X.L., Y.H., Z.L., L.Q.)
- Department of Obstetrics, Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China (Z.L.)
- Key Laboratory of Reproductive Genetics, Ministry of Education, China (Z.L.)
| | - George A Bray
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA (G.A.B.)
| | - Frank M Sacks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA (F.M.S., L.Q.)
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (F.M.S., L.Q.)
| | - Lu Qi
- From the Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA (D.S., T.Z., X.L., Y.H., Z.L., L.Q.)
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA (F.M.S., L.Q.)
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA (F.M.S., L.Q.)
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156
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Mabillard H, Sayer JA. The Molecular Genetics of Gordon Syndrome. Genes (Basel) 2019; 10:genes10120986. [PMID: 31795491 PMCID: PMC6947027 DOI: 10.3390/genes10120986] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 11/22/2019] [Accepted: 11/25/2019] [Indexed: 12/12/2022] Open
Abstract
Gordon syndrome is a rare inherited monogenic form of hypertension, which is associated with hyperkalaemia and metabolic acidosis. Since the recognition of this predominantly autosomal dominant condition in the 1960s, the study of families with Gordon syndrome has revealed four genes WNK1, WNK4, KLHL3, and CUL3 to be implicated in its pathogenesis after a phenotype–genotype correlation was realised. The encoded proteins Kelch-like 3 and Cullin 3 interact to form a ring-like complex to ubiquitinate WNK-kinase 4, which, in normal circumstances, interacts with the sodium chloride co-symporter (NCC), the epithelial sodium channel (ENaC), and the renal outer medullary potassium channel (ROMK) in an inhibitory manner to maintain normokalaemia and normotension. WNK-kinase 1 has an inhibitory action on WNK-kinase 4. Mutations in WNK1, WNK4, KLHL3, and CUL3 all result in the accumulation of WNK-kinase 4 and subsequent hypertension, hyperkalaemia, and metabolic acidosis. This review explains the clinical aspects, disease mechanisms, and molecular genetics of Gordon syndrome.
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Affiliation(s)
- Holly Mabillard
- Renal Services, The Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne NE7 7DN, UK;
| | - John A. Sayer
- Renal Services, The Newcastle Hospitals NHS Foundation Trust, Newcastle upon Tyne NE7 7DN, UK;
- Translational and Clinical Research Institute, Faculty of Medical Sciences, Institute of Genetic Medicine, Newcastle University, International Centre for Life, Central Parkway, Newcastle upon Tyne NE1 3BZ, UK
- NIHR Newcastle Biomedical Research Centre, Newcastle University, Newcastle upon Tyne NE4 5PL, UK
- Correspondence: ; Tel.: +44-191-2418608
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157
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Cabrera CP, Ng FL, Nicholls HL, Gupta A, Barnes MR, Munroe PB, Caulfield MJ. Over 1000 genetic loci influencing blood pressure with multiple systems and tissues implicated. Hum Mol Genet 2019; 28:R151-R161. [PMID: 31411675 PMCID: PMC6872427 DOI: 10.1093/hmg/ddz197] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 07/26/2019] [Accepted: 08/05/2019] [Indexed: 12/12/2022] Open
Abstract
High blood pressure (BP) remains the major heritable and modifiable risk factor for cardiovascular disease. Persistent high BP, or hypertension, is a complex trait with both genetic and environmental interactions. Despite swift advances in genomics, translating new discoveries to further our understanding of the underlying molecular mechanisms remains a challenge. More than 500 loci implicated in the regulation of BP have been revealed by genome-wide association studies (GWAS) in 2018 alone, taking the total number of BP genetic loci to over 1000. Even with the large number of loci now associated to BP, the genetic variance explained by all loci together remains low (~5.7%). These genetic associations have elucidated mechanisms and pathways regulating BP, highlighting potential new therapeutic and drug repurposing targets. A large proportion of the BP loci were discovered and reported simultaneously by multiple research groups, creating a knowledge gap, where the reported loci to date have not been investigated in a harmonious way. Here, we review the BP-associated genetic variants reported across GWAS studies and investigate their potential impact on the biological systems using in silico enrichment analyses for pathways, tissues, gene ontology and genetic pleiotropy.
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Affiliation(s)
- Claudia P Cabrera
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Centre for Translational Bioinformatics, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Fu Liang Ng
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Hannah L Nicholls
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Centre for Translational Bioinformatics, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Ajay Gupta
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Michael R Barnes
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Centre for Translational Bioinformatics, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Mark J Caulfield
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
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158
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Zhao Q, Miljkovic I. Weight Loss and Blood Pressure Changes, Roles Played by Genetic Susceptibility and Macronutrients. Hypertension 2019; 74:1300-1301. [PMID: 31656100 DOI: 10.1161/hypertensionaha.119.13677] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Qian Zhao
- From the Department of Biostatistics, FMD K&L, Fort Washington, PA (Q.Z.)
| | - Iva Miljkovic
- Department of Epidemiology, Graduate School of Public Health, Pittsburgh, PA (I.M.)
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159
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Wang X, Mo X, Zhang H, Zhang Y, Shen Y. Identification of Phosphorylation Associated SNPs for Blood Pressure, Coronary Artery Disease and Stroke from Genome-wide Association Studies. Curr Mol Med 2019; 19:731-738. [PMID: 31456518 DOI: 10.2174/1566524019666190828151540] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 08/07/2019] [Accepted: 08/09/2019] [Indexed: 12/30/2022]
Abstract
PURPOSE Phosphorylation-related SNP (phosSNP) is a non-synonymous SNP that might influence protein phosphorylation status. The aim of this study was to assess the effect of phosSNPs on blood pressure (BP), coronary artery disease (CAD) and ischemic stroke (IS). METHODS We examined the association of phosSNPs with BP, CAD and IS in shared data from genome-wide association studies (GWAS) and tested if the disease loci were enriched with phosSNPs. Furthermore, we performed quantitative trait locus analysis to find out if the identified phosSNPs have impacts on gene expression, protein and metabolite levels. RESULTS We found numerous phosSNPs for systolic BP (count=148), diastolic BP (count=206), CAD (count=20) and IS (count=4). The most significant phosSNPs for SBP, DBP, CAD and IS were rs1801131 in MTHFR, rs3184504 in SH2B3, rs35212307 in WDR12 and rs3184504 in SH2B3, respectively. Our analyses revealed that the associated SNPs identified by the original GWAS were significantly enriched with phosSNPs and many well-known genes predisposing to cardiovascular diseases contain significant phosSNPs. We found that BP, CAD and IS shared for phosSNPs in loci that contain functional genes involve in cardiovascular diseases, e.g., rs11556924 (ZC3HC1), rs1971819 (ICA1L), rs3184504 (SH2B3), rs3739998 (JCAD), rs903160 (SMG6). Four phosSNPs in ADAMTS7 were significantly associated with CAD, including the known functional SNP rs3825807. Moreover, the identified phosSNPs seemed to have the potential to affect transcription regulation and serum levels of numerous cardiovascular diseases-related proteins and metabolites. CONCLUSION The findings suggested that phosSNPs may play important roles in BP regulation and the pathological mechanisms of CAD and IS.
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Affiliation(s)
- Xingchen Wang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu 215123, China.,Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu 215123, China.,Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu 215123
| | - Xingbo Mo
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu 215123, China.,Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu 215123, China.,Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu 215123
| | - Huan Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu 215123, China.,Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu 215123
| | - Yonghong Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu 215123, China.,Department of Epidemiology, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu 215123
| | - Yueping Shen
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu 215123, China.,Department of Biostatistics, School of Public Health, Medical College of Soochow University, Suzhou, Jiangsu 215123, China
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160
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Zhu Y, Swanson KM, Rojas RL, Wang Z, St Sauver JL, Visscher SL, Prokop LJ, Bielinski SJ, Wang L, Weinshilboum R, Borah BJ. Systematic review of the evidence on the cost-effectiveness of pharmacogenomics-guided treatment for cardiovascular diseases. Genet Med 2019; 22:475-486. [PMID: 31591509 PMCID: PMC7056639 DOI: 10.1038/s41436-019-0667-y] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 09/23/2019] [Indexed: 02/08/2023] Open
Abstract
PURPOSE To examine the evidence on the cost-effectiveness of implementing pharmacogenomics (PGx) in cardiovascular disease (CVD) care. METHODS We conducted a systematic review using multiple databases from inception to 2018. The titles and abstracts of cost-effectiveness studies on PGx-guided treatment in CVD care were screened, and full texts were extracted. RESULTS We screened 909 studies and included 46 to synthesize. Acute coronary syndrome and atrial fibrillation were the predominantly studied conditions (59%). Most studies (78%) examined warfarin-CYP2C9/VKORC1 or clopidogrel-CYP2C19. A payer's perspective was commonly used (39%) for cost calculations, and most studies (46%) were US-based. The majority (67%) of the studies found PGx testing to be cost-effective in CVD care, but cost-effectiveness varied across drugs and conditions. Two studies examined PGx panel testing, of which one examined pre-emptive testing strategies. CONCLUSION We found mixed evidence on the cost-effectiveness of PGx in CVD care. Supportive evidence exists for clopidogrel-CYP2C19 and warfarin-CYP2C9/VKORC1, but evidence is limited in other drug-gene combinations. Gaps persist, including unclear explanation of perspective and cost inputs, underreporting of study design elements critical to economic evaluations, and limited examination of PGx panel and pre-emptive testing for their cost-effectiveness. This review identifies the need for further research on economic evaluations of PGx implementation.
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Affiliation(s)
- Ye Zhu
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.,Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Kristi M Swanson
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | - Ricardo L Rojas
- Division of Biomedical Statistics and Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Zhen Wang
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.,Evidence-Based Practice Center, Mayo Clinic, Rochester, MN, USA
| | - Jennifer L St Sauver
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA.,Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Sue L Visscher
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA
| | - Larry J Prokop
- Library Public Services, Mayo Clinic, Rochester, MN, USA
| | - Suzette J Bielinski
- Division of Epidemiology, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Liewei Wang
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Richard Weinshilboum
- Division of Clinical Pharmacology, Department of Molecular Pharmacology and Experimental Therapeutics, Mayo Clinic, Rochester, MN, USA
| | - Bijan J Borah
- Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic, Rochester, MN, USA. .,Division of Health Care Policy and Research, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.
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161
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Lule SA, Mentzer AJ, Namara B, Muwenzi AG, Nassanga B, kizito D, Akurut H, Lubyayi L, Tumusiime J, Zziwa C, Akello F, Gurdasani D, Sandhu M, Smeeth L, Elliott AM, Webb EL. A genome-wide association and replication study of blood pressure in Ugandan early adolescents. Mol Genet Genomic Med 2019; 7:e00950. [PMID: 31469255 PMCID: PMC6785527 DOI: 10.1002/mgg3.950] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 04/30/2019] [Accepted: 06/14/2019] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Genetic association studies of blood pressure (BP) have mostly been conducted in non-African populations. Using the Entebbe Mother and Baby Study (EMaBS), we aimed to identify genetic variants associated with BP among Ugandan adolescents. METHODS Systolic and diastolic BP were measured among 10- and 11-year olds. Whole-genome genotype data were generated using Illumina omni 2.5M arrays and untyped variants were imputed. Genome-wide association study (GWAS) was conducted using linear mixed model regression to account for population structure. Linear regression analysis was used to assess whether variants previously associated with BP (p < 5.0 × 10-8 ) in published BP GWASs were replicated in our study. RESULTS Of the 14 million variants analyzed among 815 adolescents, none reached genome-wide significance (p < 5.0×10-8 ) for association with systolic or diastolic BP. The most strongly associated variants were rs181430167 (p = 6.8 × 10-7 ) for systolic BP and rs12991132 (p = 4.0 × 10-7 ) for diastolic BP. Thirty-three (17 single nucleotide polymorphisms (SNPs) for systolic BP, 15 SNPs for diastolic BP and one SNP for both) of 330 variants previously identified as associated with BP were replicated in this study, but none remained significant after accounting for multiple testing. CONCLUSION Variants showing suggestive associations are worthy of future investigation. Replication results suggest that variants influencing adolescent BP may overlap somewhat with those already established in previous studies, largely based on adults in Western settings.
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Affiliation(s)
- Swaib A. Lule
- London School of Hygiene and Tropical MedicineLondonUK
- MRC/UVRI & LSHTM Uganda Research UnitEntebbeUganda
| | - Alexander J. Mentzer
- Wellcome Trust Centre for Human GeneticsUniversity of OxfordOxfordUK
- Big Data Institute, Li Ka Shing Centre for Health Information and DiscoveryUniversity of OxfordOxfordUK
| | | | | | | | | | - Helen Akurut
- MRC/UVRI & LSHTM Uganda Research UnitEntebbeUganda
| | | | | | | | | | - Deept Gurdasani
- Wellcome Trust Sanger InstituteCambridgeUK
- University of CambridgeCambridgeUK
| | - Manjinder Sandhu
- Wellcome Trust Sanger InstituteCambridgeUK
- University of CambridgeCambridgeUK
| | - Liam Smeeth
- London School of Hygiene and Tropical MedicineLondonUK
| | - Alison M. Elliott
- London School of Hygiene and Tropical MedicineLondonUK
- MRC/UVRI & LSHTM Uganda Research UnitEntebbeUganda
| | - Emily L. Webb
- London School of Hygiene and Tropical MedicineLondonUK
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162
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Samorodskaya NA, Polischuk LV, Eliseeva LN. Complex assessment of blood pressure regulation system in hypertension patients. RESEARCH RESULTS IN PHARMACOLOGY 2019. [DOI: 10.3897/rrpharmacology.5.39130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Introduction. There are almost no studies characterizing the integrative level of blood pressure (BP) regulation.
Materials and methods. 277 people of both genders aged 58.6±6.4 with stage II hypertension disease were randomized into six groups. The monotherapy of hypertension disease was conducted in five groups, using nebivolol, lisinopril, indapamide, amlodipine, and losartan. The sixth group had a combined therapy (lisinopril/indapamide). The therapy effectiveness was assessed at four levels of blood pressure regulation, using the following methods: 1) laser Doppler flowmetry, determination of the level of tumor necrosis factor-α and interleukin-10; 2) echocardiography and Doppler sonography, ultrasound examination of the renal blood flow, ECG, Holter monitoring of ECG; 3) an examination of the heart rate variability level and a quantitative assessment of beta-adrenoreception of erythrocyte cell membranes; 4) the regulatory and adaptive status was assessed, using the method of cardio-respiratory synchronism.
Results and discussion. A more significant BP decrease was revealed during a combination therapy (by 20.4% of the baseline daily value). At the integrative level, an index of the regulatory and adaptive status (iRAS) increased in the treatment with lisinopril/indapamide combination (by 40.5%), amlodipine (by 40.5%), losartan (by 35.3%), and lisinopril (by 30.2%). Nebivolol administration resulted in a 13.5% decrease in iRAS. Indapamide therapy had no significant effect on iRAS.
Conclusion. A comprehensive assessment of the blood pressure regulation system makes it possible to control the effectiveness of the therapy not only on a target organ or function, but also on the condition of the organism as an integral system.
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163
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Ehret G. Measured and Genotyped Differences in Blood Pressure and the Usefulness of Precise Extreme Phenotypes Based on Cardiovascular Magnetic Resonance. Hypertension 2019; 74:747-748. [PMID: 31476914 DOI: 10.1161/hypertensionaha.119.13238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Georg Ehret
- From the Division of Cardiology, Geneva University Hospitals, Switzerland
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164
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Hendriks T, Said MA, Janssen LMA, van der Ende MY, van Veldhuisen DJ, Verweij N, van der Harst P. Effect of Systolic Blood Pressure on Left Ventricular Structure and Function: A Mendelian Randomization Study. Hypertension 2019; 74:826-832. [PMID: 31476911 DOI: 10.1161/hypertensionaha.119.12679] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
We aimed to estimate the effects of a lifelong exposure to high systolic blood pressure (SBP) on left ventricular (LV) structure and function using Mendelian randomization. A total of 5596 participants of the UK Biobank were included for whom cardiovascular magnetic resonance imaging and genetic data were available. Major exclusion criteria included nonwhite ethnicity, major cardiovascular disease, and body mass index >30 or <18.5 kg/m2. A genetic risk score to estimate genetically predicted SBP (gSBP) was constructed based on 107 previously established genetic variants. Manual cardiovascular magnetic resonance imaging postprocessing analyses were performed in 300 individuals at the extremes of gSBP (150 highest and lowest). Multivariable linear regression analyses of imaging biomarkers were performed using gSBP as continuous independent variable. All analyses except myocardial strain were validated using previously derived imaging parameters in 2530 subjects. The mean (SD) age of the study population was 62 (7) years, and 52% of subjects were female. Corrected for age, sex, and body surface area, each 10 mm Hg increase in gSBP was significantly (P<0.0056) associated with 4.01 g (SE, 1.28; P=0.002) increase in LV mass and with 2.80% (SE, 0.97; P=0.004) increase in LV global radial strain. In the validation cohort, after correction for age, sex, and body surface area, each 10 mm Hg increase in gSBP was associated with 5.27 g (SE, 1.50; P<0.001) increase in LV mass. Our study provides a novel line of evidence for a causal relationship between SBP and increased LV mass and with increased LV global radial strain.
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Affiliation(s)
- Tom Hendriks
- From the Department of Cardiology, University of Groningen, University Medical Center Groningen, the Netherlands
| | - M Abdullah Said
- From the Department of Cardiology, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Lara M A Janssen
- From the Department of Cardiology, University of Groningen, University Medical Center Groningen, the Netherlands
| | - M Yldau van der Ende
- From the Department of Cardiology, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Dirk J van Veldhuisen
- From the Department of Cardiology, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Niek Verweij
- From the Department of Cardiology, University of Groningen, University Medical Center Groningen, the Netherlands
| | - Pim van der Harst
- From the Department of Cardiology, University of Groningen, University Medical Center Groningen, the Netherlands
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165
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Singh S, El Rouby N, McDonough CW, Gong Y, Bailey KR, Boerwinkle E, Chapman AB, Gums JG, Turner ST, Cooper‐DeHoff RM, Johnson JA. Genomic Association Analysis Reveals Variants Associated With Blood Pressure Response to Beta-Blockers in European Americans. Clin Transl Sci 2019; 12:497-504. [PMID: 31033190 PMCID: PMC6742943 DOI: 10.1111/cts.12643] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2019] [Accepted: 03/19/2019] [Indexed: 12/13/2022] Open
Abstract
European Americans (EA) have a better antihypertensive response to β-blockers when compared with African Americans, albeit with some variability. We undertook a genomewide association study to elucidate the underlying genetic determinants in EA contributing to this variability in blood pressure (BP) response. A discovery genomewide association study of change in BP post-metoprolol treatment was performed in EA participants (n = 201) from the Pharmacogenomic Evaluation of Antihypertensive Responses-2 (PEAR-2) study and tested for replication in the atenolol-treated EA from the PEAR study (n = 233). Rs294610 in the FGD5, which encodes for FYVE, RhoGEF and PH Domain Containing 5, (expression quantitative trait loci for FGD5 in the small intestine) was significantly associated with increased diastolic BP response to β-blockers in the PEAR-2 study (P = 3.41 × 10-6 , β = -2.70) and replicated (P = 0.01, β = -1.17) in the PEAR study. Post-meta-analysis of these studies, an additional single nucleotide polymorphism rs45545233 in the SLC4A1, encoding for Solute Carrier Family 4 Member 1, (expression quantitative trait loci for dual specificity phosphatase 3 in the artery tibial) was identified that was significantly associated with a poor response to β-blockers (P = 3.43 × 10-6 , β = 4.57) and was replicated in the atenolol add-on cohort (P = 0.007, β = 4.97). We identified variants in FGD5 and SLC4A1, which have been previously cited as candidate genes for hypertension, to be associated with a β-blocker BP response in EA. Further elucidation is warranted of the underlying mechanisms of these variants and genes by which they influence the BP response to β-blockers.
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Affiliation(s)
- Sonal Singh
- Department of Pharmacotherapy and Translational Research and Center for PharmacogenomicsUniversity of FloridaGainesvilleFloridaUSA
| | - Nihal El Rouby
- Department of Pharmacotherapy and Translational Research and Center for PharmacogenomicsUniversity of FloridaGainesvilleFloridaUSA
| | - Caitrin W. McDonough
- Department of Pharmacotherapy and Translational Research and Center for PharmacogenomicsUniversity of FloridaGainesvilleFloridaUSA
| | - Yan Gong
- Department of Pharmacotherapy and Translational Research and Center for PharmacogenomicsUniversity of FloridaGainesvilleFloridaUSA
| | - Kent R. Bailey
- Department of Health Sciences ResearchDivision of BiostatisticsMayo ClinicRochesterMinnesotaUSA
| | - Eric Boerwinkle
- Human Genetics and Institute of Molecular MedicineUniversity of Texas Health Science CenterHoustonTexasUSA
| | | | - John G. Gums
- Department of Pharmacotherapy and Translational Research and Center for PharmacogenomicsUniversity of FloridaGainesvilleFloridaUSA
| | - Stephen T. Turner
- Division of Nephrology and HypertensionMayo ClinicRochesterMinnesotaUSA
| | - Rhonda M. Cooper‐DeHoff
- Department of Pharmacotherapy and Translational Research and Center for PharmacogenomicsUniversity of FloridaGainesvilleFloridaUSA
- Department of MedicineDivision of Cardiovascular MedicineUniversity of FloridaGainesvilleFloridaUSA
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research and Center for PharmacogenomicsUniversity of FloridaGainesvilleFloridaUSA
- Department of MedicineDivision of Cardiovascular MedicineUniversity of FloridaGainesvilleFloridaUSA
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166
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D'Haens GR, Jobin C. Fecal Microbial Transplantation for Diseases Beyond Recurrent Clostridium Difficile Infection. Gastroenterology 2019; 157:624-636. [PMID: 31220424 PMCID: PMC7179251 DOI: 10.1053/j.gastro.2019.04.053] [Citation(s) in RCA: 65] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2018] [Revised: 04/15/2019] [Accepted: 04/20/2019] [Indexed: 02/08/2023]
Abstract
As microbiome research has moved from associative to mechanistic studies, the activities of specific microbes and their products have been investigated in the development of inflammatory bowel diseases, cancer, metabolic syndrome, and neuropsychiatric disorders. Findings from microbiome research have already been applied to the clinic, such as in fecal microbiota transplantation for treatment of recurrent Clostridium difficile infection. We review the evidence for associations between alterations in the intestinal microbiome and gastrointestinal diseases and findings from clinical trials of fecal microbiota transplantation. We discuss opportunities for treatment of other diseases with fecal microbiota transplantation, based on findings from small clinical and preclinical studies.
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Affiliation(s)
- Geert R D'Haens
- Department of Gastroenterology, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Christian Jobin
- Departments of Medicine, Anatomy and Cell Biology, and Infectious Diseases and Immunology, University of Florida, Gainesville, Florida.
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167
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When drug treatments bias genetic studies: Mediation and interaction. PLoS One 2019; 14:e0221209. [PMID: 31461463 PMCID: PMC6713387 DOI: 10.1371/journal.pone.0221209] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Accepted: 08/01/2019] [Indexed: 11/19/2022] Open
Abstract
Background Increasingly, genetic analyses are conducted using information from subjects with established disease, who often receive concomitant treatment. We determined when treatment may bias genetic associations with a quantitative trait. Methods Graph theory and simulated data were used to explore the impact of drug prescriptions on (longitudinal) genetic effect estimates. Analytic derivations of longitudinal genetic effects are presented, accounting for the following scenarios: 1) treatment allocated independently of a genetic variant, 2) treatment that mediates the genetic effect, 3) treatment that modifies the genetic effect. We additionally evaluate treatment modelling strategies on bias, the root mean squared error (RMSE), coverage, and rejection rate. Results We show that in the absence of treatment by gene effect modification or mediation, genetic effect estimates will be unbiased. In simulated data we found that conditional models accounting for treatment, confounding, and effect modification were generally unbiased with appropriate levels of confidence interval coverage. Ignoring the longitudinal nature of treatment prescription, however (e.g. because of incomplete records in longitudinal data), biased these conditional models to a similar degree (or worse) as simply ignoring treatment. Conclusion The mere presence of (drug) treatment affecting a GWAS phenotype is insufficient to bias genetic associations with quantitative traits. While treatment may bias associations through effect modification and mediation, this might not occur frequently enough to warrant general concern at the presence of treated subjects in GWAS. Should treatment by gene effect modification or mediation be present however, current GWAS approaches attempting to adjust for treatment insufficiently account for the multivariable and longitudinal nature of treatment trajectories and hence genetic estimates may still be biased.
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168
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Vandenwijngaert S, Ledsky CD, Lahrouchi N, Khan MAF, Wunderer F, Ames L, Honda T, Diener JL, Bezzina CR, Buys ES, Bloch DB, Newton-Cheh C. Blood Pressure-Associated Genetic Variants in the Natriuretic Peptide Receptor 1 Gene Modulate Guanylate Cyclase Activity. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2019; 12:e002472. [PMID: 31430210 DOI: 10.1161/circgen.119.002472] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
BACKGROUND Human genetic variation in the NPR1 (natriuretic peptide receptor 1 gene, encoding NPR-A, atrial natriuretic peptide receptor 1) was recently shown to affect blood pressure (BP). NPR-A catalyzes the intracellular conversion of guanosine triphosphate to cGMP (cyclic 3',5'-guanosine monophosphate) on binding of ANP, BNP (atrial or brain natriuretic peptide). Increased levels of cGMP decrease BP by inducing natriuresis, diuresis, and vasodilation. METHODS We performed a meta-analysis of low-frequency and rare NPR1 variants for BP association in up to 491 584 unrelated individuals. To examine whether the identified BP-associated variants affect NPR-A function, the cGMP response to ANP and BNP was measured in cells expressing wild-type NPR1 and cells expressing the NPR1 variants. RESULTS In this study, we identified BP associations of 3 amino acid altering variants of NPR1. The minor alleles of rs35479618 (p.E967K, gnomAD non-Finnish European allele frequency 0.017) and rs116245325 (p.L1034F, allele frequency 0.0007) were associated with higher BP (P=4.0×10-25 and P=9.9×10-8, respectively), while the minor allele of rs61757359 (p.G541S, allele frequency 0.003) was associated with lower BP (P=1.8×10-9). Cells transiently expressing 967K or 1034F NPR-A displayed decreased cGMP production in response to ANP and BNP (all P<10-6), while cells expressing 541S NPR-A produced more cGMP compared with cells expressing wild-type NPR-A (P≤4.13×10-5 for ANP and P≤4.24×10-3 for BNP). CONCLUSIONS In summary, the loss or gain of guanylate cyclase activity for these NPR1 allelic variants could explain the higher or lower BP observed for carriers in large population-based studies.
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Affiliation(s)
- Sara Vandenwijngaert
- Department of Anesthesia, Critical Care, and Pain Medicine (S.V., C.D.L., F.W., E.S.B., D.B.B.), Massachusetts General Hospital Research Institute and Harvard Medical School, Boston
| | - Clara D Ledsky
- Department of Anesthesia, Critical Care, and Pain Medicine (S.V., C.D.L., F.W., E.S.B., D.B.B.), Massachusetts General Hospital Research Institute and Harvard Medical School, Boston
| | - Najim Lahrouchi
- Center for Genomic Medicine (N.L., C.N.-C.), Massachusetts General Hospital Research Institute and Harvard Medical School, Boston.,Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, the Netherlands (N.L., M.A.F.K., C.R.B.)
| | - Mohsin A F Khan
- Amsterdam UMC, University of Amsterdam, Heart Center (M.A.F.K., C.R.B.).,Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, the Netherlands (N.L., M.A.F.K., C.R.B.)
| | - Florian Wunderer
- Department of Anesthesia, Critical Care, and Pain Medicine (S.V., C.D.L., F.W., E.S.B., D.B.B.), Massachusetts General Hospital Research Institute and Harvard Medical School, Boston.,Department of Anesthesiology, Intensive Care Medicine and Pain Therapy, UniversityHospital Frankfurt, Germany (F.W.)
| | - Lisa Ames
- Novartis Institutes for BioMedical Research (L.A., T.H., J.L.D.)
| | - Toshiyuki Honda
- Novartis Institutes for BioMedical Research (L.A., T.H., J.L.D.)
| | - John L Diener
- Novartis Institutes for BioMedical Research (L.A., T.H., J.L.D.)
| | - Connie R Bezzina
- Amsterdam UMC, University of Amsterdam, Heart Center (M.A.F.K., C.R.B.).,Department of Clinical and Experimental Cardiology, Amsterdam Cardiovascular Sciences, the Netherlands (N.L., M.A.F.K., C.R.B.)
| | - Emmanuel S Buys
- Department of Anesthesia, Critical Care, and Pain Medicine (S.V., C.D.L., F.W., E.S.B., D.B.B.), Massachusetts General Hospital Research Institute and Harvard Medical School, Boston
| | - Donald B Bloch
- Department of Anesthesia, Critical Care, and Pain Medicine (S.V., C.D.L., F.W., E.S.B., D.B.B.), Massachusetts General Hospital Research Institute and Harvard Medical School, Boston.,Division of Rheumatology, Allergy and Immunology, Department of Medicine (D.B.B.), Massachusetts General Hospital Research Institute and Harvard Medical School, Boston
| | - Christopher Newton-Cheh
- Center for Genomic Medicine (N.L., C.N.-C.), Massachusetts General Hospital Research Institute and Harvard Medical School, Boston.,Cardiovascular Research Center, Department of Medicine (C.N.-C.), Massachusetts General Hospital Research Institute and Harvard Medical School, Boston.,Program in Medical and Population Genetics, Broad Institute, Cambridge, MA (C.N.-C.)
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Sung YJ, de las Fuentes L, Winkler TW, Chasman DI, Bentley AR, Kraja AT, Ntalla I, Warren HR, Guo X, Schwander K, Manning AK, Brown MR, Aschard H, Feitosa MF, Franceschini N, Lu Y, Cheng CY, Sim X, Vojinovic D, Marten J, Musani SK, Kilpeläinen TO, Richard MA, Aslibekyan S, Bartz TM, Dorajoo R, Li C, Liu Y, Rankinen T, Smith AV, Tajuddin SM, Tayo BO, Zhao W, Zhou Y, Matoba N, Sofer T, Alver M, Amini M, Boissel M, Chai JF, Chen X, Divers J, Gandin I, Gao C, Giulianini F, Goel A, Harris SE, Hartwig FP, He M, Horimoto ARVR, Hsu FC, Jackson AU, Kammerer CM, Kasturiratne A, Komulainen P, Kühnel B, Leander K, Lee WJ, Lin KH, Luan J, Lyytikäinen LP, McKenzie CA, Nelson CP, Noordam R, Scott RA, Sheu WHH, Stančáková A, Takeuchi F, van der Most PJ, Varga TV, Waken RJ, Wang H, Wang Y, Ware EB, Weiss S, Wen W, Yanek LR, Zhang W, Zhao JH, Afaq S, Alfred T, Amin N, Arking DE, Aung T, Barr RG, Bielak LF, Boerwinkle E, Bottinger EP, Braund PS, Brody JA, Broeckel U, Cade B, Campbell A, Canouil M, Chakravarti A, Cocca M, Collins FS, Connell JM, de Mutsert R, de Silva HJ, Dörr M, Duan Q, Eaton CB, Ehret G, Evangelou E, Faul JD, Forouhi NG, Franco OH, Friedlander Y, Gao H, Gigante B, Gu CC, Gupta P, Hagenaars SP, Harris TB, He J, Heikkinen S, Heng CK, Hofman A, Howard BV, Hunt SC, Irvin MR, Jia Y, Katsuya T, Kaufman J, Kerrison ND, Khor CC, Koh WP, Koistinen HA, Kooperberg CB, Krieger JE, Kubo M, Kutalik Z, Kuusisto J, Lakka TA, Langefeld CD, Langenberg C, Launer LJ, Lee JH, Lehne B, Levy D, Lewis CE, Li Y, Lim SH, Liu CT, Liu J, Liu J, Liu Y, Loh M, Lohman KK, Louie T, Mägi R, Matsuda K, Meitinger T, Metspalu A, Milani L, Momozawa Y, Mosley, Jr TH, Nalls MA, Nasri U, O'Connell JR, Ogunniyi A, Palmas WR, Palmer ND, Pankow JS, Pedersen NL, Peters A, Peyser PA, Polasek O, Porteous D, Raitakari OT, Renström F, Rice TK, Ridker PM, Robino A, Robinson JG, Rose LM, Rudan I, Sabanayagam C, Salako BL, Sandow K, Schmidt CO, Schreiner PJ, Scott WR, Sever P, Sims M, Sitlani CM, Smith BH, Smith JA, Snieder H, Starr JM, Strauch K, Tang H, Taylor KD, Teo YY, Tham YC, Uitterlinden AG, Waldenberger M, Wang L, Wang YX, Wei WB, Wilson G, Wojczynski MK, Xiang YB, Yao J, Yuan JM, Zonderman AB, Becker DM, Boehnke M, Bowden DW, Chambers JC, Chen YDI, Weir DR, de Faire U, Deary IJ, Esko T, Farrall M, Forrester T, Freedman BI, Froguel P, Gasparini P, Gieger C, Horta BL, Hung YJ, Jonas JB, Kato N, Kooner JS, Laakso M, Lehtimäki T, Liang KW, Magnusson PKE, Oldehinkel AJ, Pereira AC, Perls T, Rauramaa R, Redline S, Rettig R, Samani NJ, Scott J, Shu XO, van der Harst P, Wagenknecht LE, Wareham NJ, Watkins H, Wickremasinghe AR, Wu T, Kamatani Y, Laurie CC, Bouchard C, Cooper RS, Evans MK, Gudnason V, Hixson J, Kardia SLR, Kritchevsky SB, Psaty BM, van Dam RM, Arnett DK, Mook-Kanamori DO, Fornage M, Fox ER, Hayward C, van Duijn CM, Tai ES, Wong TY, Loos RJF, Reiner AP, Rotimi CN, Bierut LJ, Zhu X, Cupples LA, Province MA, Rotter JI, Franks PW, Rice K, Elliott P, Caulfield MJ, Gauderman WJ, Munroe PB, Rao DC, Morrison AC. A multi-ancestry genome-wide study incorporating gene-smoking interactions identifies multiple new loci for pulse pressure and mean arterial pressure. Hum Mol Genet 2019; 28:2615-2633. [PMID: 31127295 PMCID: PMC6644157 DOI: 10.1093/hmg/ddz070] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Revised: 03/25/2019] [Accepted: 03/26/2019] [Indexed: 12/24/2022] Open
Abstract
Elevated blood pressure (BP), a leading cause of global morbidity and mortality, is influenced by both genetic and lifestyle factors. Cigarette smoking is one such lifestyle factor. Across five ancestries, we performed a genome-wide gene-smoking interaction study of mean arterial pressure (MAP) and pulse pressure (PP) in 129 913 individuals in stage 1 and follow-up analysis in 480 178 additional individuals in stage 2. We report here 136 loci significantly associated with MAP and/or PP. Of these, 61 were previously published through main-effect analysis of BP traits, 37 were recently reported by us for systolic BP and/or diastolic BP through gene-smoking interaction analysis and 38 were newly identified (P < 5 × 10-8, false discovery rate < 0.05). We also identified nine new signals near known loci. Of the 136 loci, 8 showed significant interaction with smoking status. They include CSMD1 previously reported for insulin resistance and BP in the spontaneously hypertensive rats. Many of the 38 new loci show biologic plausibility for a role in BP regulation. SLC26A7 encodes a chloride/bicarbonate exchanger expressed in the renal outer medullary collecting duct. AVPR1A is widely expressed, including in vascular smooth muscle cells, kidney, myocardium and brain. FHAD1 is a long non-coding RNA overexpressed in heart failure. TMEM51 was associated with contractile function in cardiomyocytes. CASP9 plays a central role in cardiomyocyte apoptosis. Identified only in African ancestry were 30 novel loci. Our findings highlight the value of multi-ancestry investigations, particularly in studies of interaction with lifestyle factors, where genomic and lifestyle differences may contribute to novel findings.
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Affiliation(s)
- Yun Ju Sung
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Lisa de las Fuentes
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
- Cardiovascular Division, Department of Medicine, Washington University, St. Louis, MO, USA
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Daniel I Chasman
- Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Amy R Bentley
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Aldi T Kraja
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Ioanna Ntalla
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Helen R Warren
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, London, UK
| | - Xiuqing Guo
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Karen Schwander
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Alisa K Manning
- Center for Human Genetics Research, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Hugues Aschard
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
- Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Institut Pasteur, Paris, France
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Nora Franceschini
- Epidemiology, University of North Carolina Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - Yingchang Lu
- Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
| | - Ching-Yu Cheng
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
| | - Dina Vojinovic
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Jonathan Marten
- Medical Research Council Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Solomon K Musani
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Environmental Medicine and Public Health, The Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Melissa A Richard
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Stella Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Biostatistics and Medicine, University of Washington, Seattle, WA, USA
| | - Rajkumar Dorajoo
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - Changwei Li
- Epidemiology and Biostatistics, University of Georgia at Athens College of Public Health, Athens, GA, USA
| | - Yongmei Liu
- Public Health Sciences, Epidemiology and Prevention, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Albert Vernon Smith
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Salman M Tajuddin
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Bamidele O Tayo
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Yanhua Zhou
- Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Nana Matoba
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Tamar Sofer
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Maris Alver
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Marzyeh Amini
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen RB, The Netherlands
| | - Mathilde Boissel
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille, France
| | - Jin Fang Chai
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
| | - Xu Chen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Stockholm, Sweden
| | - Jasmin Divers
- Biostatistical Sciences, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Ilaria Gandin
- Department of Medical Sciences, University of Trieste, Trieste, Italy
| | - Chuan Gao
- Molecular Genetics and Genomics Program, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | - Anuj Goel
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, UK
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine and MRC Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh, UK
| | - Fernando P Hartwig
- Postgraduate Programme in Epidemiology, Federal University of Pelotas, Pelotas, RS, Brazil
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Meian He
- Lab Genetics and Molecular Cardiology, Cardiology, Heart Institute, University of Sao Paulo, Sao Paulo, CA, USA
| | - Andrea R V R Horimoto
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Fang-Chi Hsu
- Biostatistical Sciences, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Anne U Jackson
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Candace M Kammerer
- Department of Public Health, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - Anuradhani Kasturiratne
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Pirjo Komulainen
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Brigitte Kühnel
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Karin Leander
- Medical Research, Taichung Veterans General Hospital, Department of Social Work, Tunghai University, Taichung, Taiwan
| | - Wen-Jane Lee
- Ophthalmology, Taichung Veterans General Hospital, Taichung, Taiwan
| | - Keng-Hung Lin
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Jian’an Luan
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center—Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
- Tropical Metabolism Research Unit, Tropical Medicine Research Institute, University of the West Indies, Mona, Jamaica
| | - Colin A McKenzie
- School of Public Health, Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, Tongi Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Christopher P Nelson
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Raymond Noordam
- Internal Medicine, Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - Robert A Scott
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Wayne H H Sheu
- Endocrinology and Metabolism, Internal Medicine, Taichung Veterans General Hospital, Taichung, Taiwan
- School of Medicine, National Yang-ming University, Taipei, Taiwan
- School of Medicine, National Defense Medical Center, Taipei, Taiwan
- Institute of Medical Technology, National Chung-Hsing University, Taichung, Taiwan
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Fumihiko Takeuchi
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Peter J van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen RB, The Netherlands
| | - Tibor V Varga
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
| | - Robert J Waken
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Heming Wang
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Yajuan Wang
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - Erin B Ware
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Stefan Weiss
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Ernst Moritz Arndt University Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Health), Partner Site Greifswald, Greifswald, Germany
| | - Wanqing Wen
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Lisa R Yanek
- General Internal Medicine, GeneSTAR Research Program, Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Weihua Zhang
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, Middlesex, UK
| | - Jing Hua Zhao
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Saima Afaq
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Tamuno Alfred
- Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Tin Aung
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - R Graham Barr
- Departments of Medicine and Epidemiology, Columbia University Medical Center, New York, NY, USA
| | - Lawrence F Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Erwin P Bottinger
- Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
| | - Peter S Braund
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Medicine, University of Washington, Seattle, WA, USA
| | - Ulrich Broeckel
- Section of Genomic Pediatrics, Department of Pediatrics, Medicine and Physiology, Medical College of Wisconsin, Milwaukee, WI, USA
| | - Brian Cade
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Archie Campbell
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Mickaël Canouil
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille, France
| | - Aravinda Chakravarti
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | | | - Francis S Collins
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - John M Connell
- Ninewells Hospital & Medical School, University of Dundee, Dundee, Scotland, UK
| | - Renée de Mutsert
- Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
| | - H Janaka de Silva
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - Marcus Dörr
- DZHK (German Centre for Cardiovascular Health), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Qing Duan
- Department of Genetics, University of North Carolina, Chapel Hill, USA
| | - Charles B Eaton
- Department of Family Medicine and Epidemiology, Alpert Medical School of Brown University, Providence, RI, USA
| | - Georg Ehret
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Cardiology, Department of Specialties of Medicine, Geneva University Hospital, Geneva, Switzerland
| | - Evangelos Evangelou
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Greece
| | - Jessica D Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Nita G Forouhi
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Oscar H Franco
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Yechiel Friedlander
- Braun School of Public Health, Hebrew University-Hadassah Medical Center, Jerusalem, Israel
| | - He Gao
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Bruna Gigante
- Medical Research, Taichung Veterans General Hospital, Department of Social Work, Tunghai University, Taichung, Taiwan
| | - C Charles Gu
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Preeti Gupta
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Saskia P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Psychology, The University of Edinburgh, Edinburgh, UK
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Jiang He
- Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Medicine, Tulane University School of Medicine, New Orleans, LA, USA
| | - Sami Heikkinen
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Finland
| | - Chew-Kiat Heng
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Khoo Teck Puat—National University Children’s Medical Institute, National University Health System, Singapore, Singapore
| | - Albert Hofman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Barbara V Howard
- MedStar Health Research Institute, Hyattsville, MD, USA
- Center for Clinical and Translational Sciences and Department of Medicine, Georgetown–Howard Universities, Washington, DC, USA
| | - Steven C Hunt
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
- Department of Genetic Medicine, Weill Cornell Medicine, Doha, Qatar
| | - Marguerite R Irvin
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Yucheng Jia
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Tomohiro Katsuya
- Department of Clinical Gene Therapy, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Geriatric Medicine and Nephrology, Osaka University Graduate School of Medicine, Suita, Japan
| | - Joel Kaufman
- Epidemiology, Occupational and Environmental Medicine Program, University of Washington, Seattle, WA, USA
| | - Nicola D Kerrison
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Department of Biochemistry, National University of Singapore, Singapore, Singapore
| | - Woon-Puay Koh
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
- Health Services and Systems Research, Duke–NUS Medical School, Singapore, Singapore
| | - Heikki A Koistinen
- Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland
- Department of Medicine and Abdominal Center: Endocrinology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Biomedicum 2U, Helsinki Finland
| | - Charles B Kooperberg
- Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle, WA, USA
| | - Jose E Krieger
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Michiaki Kubo
- RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Zoltan Kutalik
- Institute of Social Preventive Medicine, Lausanne University Hospital, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Timo A Lakka
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Biomedicine, School of Medicine, University of Eastern Finland, Kuopio Campus, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Carl D Langefeld
- Biostatistical Sciences, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Joseph H Lee
- Sergievsky Center, College of Physicians and Surgeons, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Benjamin Lehne
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Daniel Levy
- NHLBI Framingham Heart Study, Framingham, MA, USA
- The Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Cora E Lewis
- Department of Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Yize Li
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Sing Hui Lim
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Ching-Ti Liu
- Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jianjun Liu
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
| | - Jingmin Liu
- WHI CCC, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Yeheng Liu
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Marie Loh
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Translational Laboratory in Genetic Medicine, Agency for Science, Technology and Research, Singapore
| | - Kurt K Lohman
- Biostatistical Sciences, Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Tin Louie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Reedik Mägi
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Koichi Matsuda
- Laboratory for Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Minato-ku, Japan
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, Technische Universität München, Munich, Germany
| | - Andres Metspalu
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Lili Milani
- Cardiovascular Division, Department of Medicine, Washington University, St. Louis, MO, USA
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Ubaydah Nasri
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jeff R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | | | | | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Stockholm, Sweden
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Neuherberg, Germany
| | - Patricia A Peyser
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Ozren Polasek
- Department of Public Health, Department of Medicine, University of Split, Split, Croatia
- Psychiatric Hospital ‘Sveti Ivan’, Zagreb, Croatia
- Gen-info Ltd, Zagreb, Croatia
| | - David Porteous
- Centre for Genomic & Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Frida Renström
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
- Department of Biobank Research, Umeå University, Umeå, Västerbotten, Sweden
| | - Treva K Rice
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Paul M Ridker
- Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Antonietta Robino
- Institute for Maternal and Child Health—IRCCS ‘Burlo Garofolo’, Trieste, Italy
| | - Jennifer G Robinson
- Department of Epidemiology and Medicine, University of Iowa, Iowa City, IA, USA
| | - Lynda M Rose
- Preventive Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Charumathi Sabanayagam
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | | | - Kevin Sandow
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Carsten O Schmidt
- DZHK (German Centre for Cardiovascular Health), Partner Site Greifswald, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - William R Scott
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Peter Sever
- International Centre for Circulatory Health, Imperial College London, London, UK
| | - Mario Sims
- Jackson Heart Study, Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Colleen M Sitlani
- Cardiovascular Health Research Unit, Medicine, University of Washington, Seattle, WA, USA
| | - Blair H Smith
- Division of Population Health Sciences, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen RB, The Netherlands
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Alzheimer Scotland Dementia Research Centre, The University of Edinburgh, Edinburgh, UK
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Genetic Epidemiology, IBE, Faculty of Medicine, LMU, Munich, Germany
| | - Hua Tang
- Department of Genetics, Stanford University, Stanford, CA, USA
| | - Kent D Taylor
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Yik Ying Teo
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
- NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
| | - Yih Chung Tham
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- MRC Epidemiology Unit, University of Cambridge, Cambridge, UK
| | - Lihua Wang
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Ya Xing Wang
- Beijing Institute of Ophthalmology, Beijing Tongren Eye Center, Beijing Ophthalmology and Visual Science Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Wen Bin Wei
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Gregory Wilson
- Jackson Heart Study, School of Public Health, Jackson State University, Jackson, MS, USA
| | - Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Yong-Bing Xiang
- State Key Laboratory of Oncogene and Related Genes & Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, P.R. China
| | - Jie Yao
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jian-Min Yuan
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alan B Zonderman
- Behavioral Epidemiology Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Diane M Becker
- General Internal Medicine, GeneSTAR Research Program, Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Donald W Bowden
- Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - John C Chambers
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, Middlesex, UK
| | - Yii-Der Ida Chen
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Ulf de Faire
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, The University of Edinburgh, Edinburgh, UK
- Psychology, The University of Edinburgh, Edinburgh, UK
| | - Tõnu Esko
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Boston, MA, USA
| | - Martin Farrall
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, UK
| | - Terrence Forrester
- Tropical Metabolism Research Unit, Tropical Medicine Research Institute, University of the West Indies, Mona, Jamaica
| | - Barry I Freedman
- Nephrology, Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Philippe Froguel
- CNRS UMR 8199, European Genomic Institute for Diabetes (EGID), Institut Pasteur de Lille, University of Lille, Lille, France
- Department of Genomics of Common Disease, Imperial College London, London, UK
| | - Paolo Gasparini
- Department of Medical Sciences, University of Trieste, Trieste, Italy
- Department of Genetic Medicine, Weill Cornell Medicine, Doha, Qatar
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - Bernardo Lessa Horta
- Postgraduate Programme in Epidemiology, Federal University of Pelotas, Pelotas, RS, Brazil
| | - Yi-Jen Hung
- Endocrinology and Metabolism, Tri-Service General Hospital, National Defense Medical Center, Taipei City, Taipei, Taiwan
| | - Jost Bruno Jonas
- Beijing Tongren Eye Center, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Department of Ophthalmology, Medical Faculty Mannheim, University Heidelberg, Mannheim, Germany
| | - Norihiro Kato
- Department of Gene Diagnostics and Therapeutics, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, Middlesex, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
- Department of Clinical Chemistry, Finnish Cardiovascular Research Center—Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland
| | - Kae-Woei Liang
- School of Medicine, National Yang-ming University, Taipei, Taiwan
- Cardiovascular Center, Taichung Veterans General Hospital, Taichung, Taiwan
- Department of Medicine, China Medical University, Taichung, Taiwan
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Stockholm, Sweden
| | - Albertine J Oldehinkel
- Department of Psychiatry, University of Groningen, University Medical Center Groningen, Groningen RB, The Netherlands
| | - Alexandre C Pereira
- Lab Genetics and Molecular Cardiology, Cardiology, Heart Institute, University of Sao Paulo, Sao Paulo, CA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Thomas Perls
- Geriatrics Section, Boston University Medical Center, Boston, MA, USA
| | - Rainer Rauramaa
- Foundation for Research in Health Exercise and Nutrition, Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Rainer Rettig
- DZHK (German Centre for Cardiovascular Health), Partner Site Greifswald, Greifswald, Germany
- Institute of Physiology, University of Medicine Greifswald, Greifswald, Germany
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
- NIHR Leicester Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - James Scott
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen RB, The Netherlands
| | - Lynne E Wagenknecht
- Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, Oxfordshire, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, Oxfordshire, UK
| | | | - Tangchun Wu
- School of Public Health, Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, Tongi Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Cathy C Laurie
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA, USA
| | - Richard S Cooper
- Department of Public Health Sciences, Loyola University Chicago, Maywood, IL, USA
| | - Michele K Evans
- Health Disparities Research Section, Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - James Hixson
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Stephen B Kritchevsky
- Department of Internal Medicine, Section on Gerontology and Geriatric Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Epidemiology, Medicine and Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Donna K Arnett
- Dean’s Office, University of Kentucky College of Public Health, Lexington, KY, USA
| | - Dennis O Mook-Kanamori
- Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands
- Public Health and Primary Care, Leiden University Medical Center, Leiden, The Netherlands
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Ervin R Fox
- Cardiology, Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - E Shyong Tai
- Saw Swee Hock School of Public Health, National University Health System and National University of Singapore, Singapore, Singapore
- Health Services and Systems Research, Duke–NUS Medical School, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Tien Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Ruth J F Loos
- Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
- Icahn School of Medicine at Mount Sinai, The Mindich Child Health and Development Institute, New York, NY, USA
| | - Alex P Reiner
- Fred Hutchinson Cancer Research Center, University of Washington School of Public Health, Seattle, WA, USA
| | - Charles N Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Laura J Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Xiaofeng Zhu
- Department of Epidemiology and Biostatistics, Case Western Reserve University, Cleveland, OH, USA
| | - L Adrienne Cupples
- Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Jerome I Rotter
- Division of Genomic Outcomes, Department of Pediatrics, The Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Paul W Franks
- Department of Clinical Sciences, Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Skåne University Hospital, Malmö, Sweden
- Harvard T. H. Chan School of Public Health, Department of Nutrition, Harvard University, Boston, MA, USA
- Department of Public Health & Clinical Medicine, Umeå University, Umeå, Västerbotten, Sweden
| | - Kenneth Rice
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Paul Elliott
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Mark J Caulfield
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, London, UK
| | - W James Gauderman
- Biostatistics, Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
- NIHR Barts Cardiovascular Biomedical Research Centre, Queen Mary University of London, London, London, UK
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
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Analysis of polygenic risk score usage and performance in diverse human populations. Nat Commun 2019; 10:3328. [PMID: 31346163 PMCID: PMC6658471 DOI: 10.1038/s41467-019-11112-0] [Citation(s) in RCA: 544] [Impact Index Per Article: 108.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 06/18/2019] [Indexed: 12/11/2022] Open
Abstract
A historical tendency to use European ancestry samples hinders medical genetics research, including the use of polygenic scores, which are individual-level metrics of genetic risk. We analyze the first decade of polygenic scoring studies (2008–2017, inclusive), and find that 67% of studies included exclusively European ancestry participants and another 19% included only East Asian ancestry participants. Only 3.8% of studies were among cohorts of African, Hispanic, or Indigenous peoples. We find that predictive performance of European ancestry-derived polygenic scores is lower in non-European ancestry samples (e.g. African ancestry samples: t = −5.97, df = 24, p = 3.7 × 10−6), and we demonstrate the effects of methodological choices in polygenic score distributions for worldwide populations. These findings highlight the need for improved treatment of linkage disequilibrium and variant frequencies when applying polygenic scoring to cohorts of non-European ancestry, and bolster the rationale for large-scale GWAS in diverse human populations. Predominant participation of European-ancestry individuals in genetic studies has hindered the better understanding of genetic risk in non-European ancestry individuals. Here, Duncan et al. quantify polygenic risk score use and performance in worldwide populations.
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171
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Wang X, Williams C, Liu ZH, Croghan J. Big data management challenges in health research-a literature review. Brief Bioinform 2019; 20:156-167. [PMID: 28968677 DOI: 10.1093/bib/bbx086] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Indexed: 12/12/2022] Open
Abstract
Big data management for information centralization (i.e. making data of interest findable) and integration (i.e. making related data connectable) in health research is a defining challenge in biomedical informatics. While essential to create a foundation for knowledge discovery, optimized solutions to deliver high-quality and easy-to-use information resources are not thoroughly explored. In this review, we identify the gaps between current data management approaches and the need for new capacity to manage big data generated in advanced health research. Focusing on these unmet needs and well-recognized problems, we introduce state-of-the-art concepts, approaches and technologies for data management from computing academia and industry to explore improvement solutions. We explain the potential and significance of these advances for biomedical informatics. In addition, we discuss specific issues that have a great impact on technical solutions for developing the next generation of digital products (tools and data) to facilitate the raw-data-to-knowledge process in health research.
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Affiliation(s)
- Xiaoming Wang
- National Institute of Infectious and Allergy Diseases, NIH, Rockville, Maryland, USA
| | - Carolyn Williams
- National Institute of Infectious and Allergy Diseases, NIH, Rockville, Maryland, USA
| | | | - Joe Croghan
- National Institute of Infectious and Allergy Diseases, NIH, Rockville, Maryland, USA
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172
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Improved detection of common variants in coronary artery disease and blood pressure using a pleiotropy cFDR method. Sci Rep 2019; 9:10340. [PMID: 31316127 PMCID: PMC6637206 DOI: 10.1038/s41598-019-46808-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 07/04/2019] [Indexed: 11/24/2022] Open
Abstract
Plenty of genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms (SNPs) for coronary artery disease (CAD) and blood pressure (BP). However, these SNPs only explain a small proportion of the heritability of two traits/diseases. Although high BP is a major risk factor for CAD, the genetic intercommunity between them remain largely unknown. To recognize novel loci associated with CAD and BP, a genetic-pleiotropy-informed conditional false discovery rate (cFDR) method was applied on two summary statistics of CAD and BP from existing GWASs. Stratified Q-Q and fold enrichment plots showed a high pleiotropic enrichment of SNPs associated with two traits. Adopting a cFDR of 0.05 as a threshold, 55 CAD-associated loci (25 variants being novel) and 47 BP loci (18 variants being novel) were identified, 25 of which were pleiotropic loci (13 variants being novel) for both traits. Among the 32 genes these 25 SNPs were annotated to, 20 genes were newly detected compared to previous GWASs. This study showed the cFDR approach could improve gene discovery by incorporating GWAS datasets of two related traits. These findings may provide novel understanding of etiology relationships between CAD and BP.
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173
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Zilbermint M, Gaye A, Berthon A, Hannah‐Shmouni F, Faucz FR, Lodish MB, Davis AR, Gibbons GH, Stratakis CA. ARMC 5 Variants and Risk of Hypertension in Blacks: MH- GRID Study. J Am Heart Assoc 2019; 8:e012508. [PMID: 31266387 PMCID: PMC6662143 DOI: 10.1161/jaha.119.012508] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Accepted: 05/29/2019] [Indexed: 12/31/2022]
Abstract
Background We recently found that ARMC 5 variants may be associated with primary aldosteronism in blacks. We investigated a cohort from the MH - GRID (Minority Health Genomics and Translational Research Bio-Repository Database) and tested the association between ARMC 5 variants and blood pressure in black s. Methods and Results Whole exome sequencing data of 1377 black s were analyzed. Target single-variant and gene-based association analyses of hypertension were performed for ARMC 5, and replicated in a subset of 3015 individuals of African descent from the UK Biobank cohort. Sixteen rare variants were significantly associated with hypertension ( P=0.0402) in the gene-based (optimized sequenced kernel association test) analysis; the 16 and one other, rs116201073, together, showed a strong association ( P=0.0003) with blood pressure in this data set. The presence of the rs116201073 variant was associated with lower blood pressure. We then used human embryonic kidney 293 and adrenocortical H295R cells transfected with an ARMC 5 construct containing rs116201073 (c.*920T>C). The latter was common in both the discovery ( MH - GRID ) and replication ( UK Biobank) data and reached statistical significance ( P=0.044 [odds ratio, 0.7] and P=0.007 [odds ratio, 0.76], respectively). The allele carrying rs116201073 increased levels of ARMC5 mRNA , consistent with its protective effect in the epidemiological data. Conclusions ARMC 5 shows an association with hypertension in black s when rare variants within the gene are considered. We also identified a protective variant of the ARMC 5 gene with an effect on ARMC 5 expression confirmed in vitro. These results extend our previous report of ARMC 5's possible involvement in the determination of blood pressure in blacks.
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Affiliation(s)
- Mihail Zilbermint
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
- Division of Endocrinology, Diabetes, and MetabolismJohns Hopkins University School of MedicineBaltimoreMD
- Johns Hopkins Community Physicians at Suburban HospitalBethesdaMD
- Johns Hopkins University Carey Business SchoolBaltimoreMD
| | - Amadou Gaye
- Genomics of Metabolic, Cardiovascular and Inflammatory Disease Branch, Cardiovascular SectionNational Human Genome Research InstituteBethesdaMD
| | - Annabel Berthon
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
| | - Fady Hannah‐Shmouni
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
| | - Fabio R. Faucz
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
| | - Maya B. Lodish
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
| | - Adam R. Davis
- Technological Research and InnovationUniformed Services UniversityBethesdaMD
| | - Gary H. Gibbons
- Genomics of Metabolic, Cardiovascular and Inflammatory Disease Branch, Cardiovascular SectionNational Human Genome Research InstituteBethesdaMD
- National Heart, Lung, and Blood InstituteBethesdaMD
| | - Constantine A. Stratakis
- Section on Endocrinology and GeneticsEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institutes of HealthBethesdaMD
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174
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Zaiou M. Circular RNAs in hypertension: challenges and clinical promise. Hypertens Res 2019; 42:1653-1663. [PMID: 31239534 DOI: 10.1038/s41440-019-0294-7] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Revised: 05/03/2019] [Accepted: 05/29/2019] [Indexed: 12/14/2022]
Abstract
Hypertension (HT), or high blood pressure (BP), is a chronic disease that is common among populations worldwide. The occurrence of HT is one of the leading causes of cardiovascular morbidity and mortality in adults. Although multiple studies have stressed the multifactorial and multigenic nature of HT, uncertainties about its etiology persist, and current diagnostic biomarkers can explain only a small part of the phenotypic variance of BP. Hence, the search for novel biomarkers that enable early disease prevention and guided therapy is warranted. Regulatory circRNAs have emerged as the newest player in HT-related gene networks and hold promise for improving the accuracy of diagnosis. These RNAs are genome products that are formed through back-splicing of specific regions of pre-mRNAs. Evidence suggests that these RNA species are involved in various metabolic diseases. Recent studies have revealed that aberrant expression of circRNAs is relevant to the occurrence and development of HT. Accordingly, circRNAs are proposed as a new generation of predictive biomarkers and potential therapeutic targets for different forms of HT, including pulmonary hypertension and preeclampsia. This paper presents an overview of the findings from current research focusing on the emerging role of circRNAs in the pathogenesis of hypertension. Furthermore, some of the challenges encountered by circRNA studies are highlighted, and perspectives are provided on the future of research in this area.
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Affiliation(s)
- Mohamed Zaiou
- University of Lorraine, Department of Biochemistry and Molecular Biology, 7 Avenue de la Foret de Haye, BP 90170, 54505, Vandoeuvre les Nancy Cedex, France.
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Abstract
OBJECTIVES Prior studies suggest that hypertensive target organ damage (TOD) is a heritable trait. However, the risk that parental TOD confers on propensity for TOD in their offspring, and how hypertensive TOD clusters in the context of parental versus offspring hypertension status remain unclear. METHODS We studied 3238 Framingham Heart Study participants (mean age 39 ± 8 years, 53% women) with available parental data on TOD. Parents and offspring underwent measurements for left ventricular hypertrophy, increased relative wall thickness, albuminuria and conventional risk factors. RESULTS Prevalence of any TOD (left ventricular hypertrophy or albuminuria) in participants with zero and at least one parents with any TOD was 7 and 13%, respectively (P < 0.001 for difference). Having at least one parent with TOD was associated with greater odds of TOD in offspring than individuals without parental TOD [multivariable-adjusted odds ratio (OR), 1.65; 95% confidence interval (95% CI), 1.27-2.14]. Similarly, parental left ventricular hypertrophy was associated with offspring left ventricular hypertrophy (OR, 2.73; 95% CI 1.92-3.89), parental increased relative wall thickness conferred increased odds of increased relative wall thickness in the offspring (OR, 1.54; 95% CI 1.16-2.04) and parental albuminuria was related to offspring albuminuria (OR, 1.49; 95% CI 1.03-2.16). These associations remained significant upon adjustment for other risk factors, including blood pressure, and in analyses of subgroups defined according to parental or offspring hypertension status. CONCLUSION Overall, our data suggest that familial clustering of TOD in the community is independent of blood pressure. Additional studies are warranted to confirm our observations.
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176
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Mopidevi B, Kaw MK, Sivankutty I, Jain S, Perla SK, Kumar A. A polymorphism in intron I of the human angiotensinogen gene ( hAGT) affects binding by HNF3 and hAGT expression and increases blood pressure in mice. J Biol Chem 2019; 294:11829-11839. [PMID: 31201268 DOI: 10.1074/jbc.ra119.007715] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2019] [Revised: 06/12/2019] [Indexed: 12/12/2022] Open
Abstract
Angiotensinogen (AGT) is the precursor of one of the most potent vasoconstrictors, peptide angiotensin II. Genome-wide association studies have shown that two A/G polymorphisms (rs2493134 and rs2004776), located at +507 and +1164 in intron I of the human AGT (hAGT) gene, are associated with hypertension. Polymorphisms of the AGT gene result in two main haplotypes. Hap-I contains the variants -217A, -6A, +507G, and +1164A and is pro-hypertensive, whereas Hap-II contains the variants -217G, -6G, +507A, and +1164G and does not affect blood pressure. The nucleotide sequence of intron I of the hAGT gene containing the +1164A variant has a stronger homology with the hepatocyte nuclear factor 3 (HNF3)-binding site than +1164G. Here we found that an oligonucleotide containing +1164A binds HNF3β more strongly than +1164G and that Hap-I-containing reporter gene constructs have increased basal and HNF3- and glucocorticoid-induced promoter activity in transiently transfected liver and kidney cells. Using a knock-in approach at the hypoxanthine-guanine phosphoribosyltransferase locus, we generated a transgenic mouse model containing the human renin (hREN) gene and either Hap-I or Hap-II. We show that transgenic animals containing Hap-I have increased blood pressure compared with those containing Hap-II. Moreover, the transcription factors glucocorticoid receptor, CCAAT enhancer-binding protein β, and HNF3β bound more strongly to chromatin obtained from the liver of transgenic animals containing Hap-I than to liver chromatin from Hap-II-containing animals. These findings suggest that, unlike Hap-II variants, Hap-I variants of the hAGT gene have increased transcription rates, resulting in elevated blood pressure.
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Affiliation(s)
| | - Meenakshi K Kaw
- Department of Physiology and Pharmacology, University of Toledo, Toledo, Ohio 43614
| | - Indu Sivankutty
- Department of Pathology, New York Medical College, Valhalla, New York 10595
| | - Sudhir Jain
- Department of Pathology, New York Medical College, Valhalla, New York 10595
| | - Sravan Kumar Perla
- Department of Pathology, New York Medical College, Valhalla, New York 10595
| | - Ashok Kumar
- Department of Pathology, New York Medical College, Valhalla, New York 10595
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177
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Examination of the associations between m6A-associated single-nucleotide polymorphisms and blood pressure. Hypertens Res 2019; 42:1582-1589. [DOI: 10.1038/s41440-019-0277-8] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Revised: 04/25/2019] [Accepted: 05/06/2019] [Indexed: 01/10/2023]
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178
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Li J, Cechova S, Wang L, Isakson BE, Le TH, Shi W. Loss of reticulocalbin 2 lowers blood pressure and restrains ANG II-induced hypertension in vivo. Am J Physiol Renal Physiol 2019; 316:F1141-F1150. [PMID: 30943068 PMCID: PMC6620588 DOI: 10.1152/ajprenal.00567.2018] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2018] [Revised: 03/19/2019] [Accepted: 03/25/2019] [Indexed: 12/11/2022] Open
Abstract
Hypertension affects over 1 billion people worldwide and increases the risk for heart failure, stroke, and chronic kidney disease. Despite high prevalence and devastating impact, its etiology still remains poorly understood for most hypertensive cases. Rcn2, which encodes reticulocalbin 2, is a candidate gene for atherosclerosis that we have previously reported in mice. Here, we identified Rcn2 as a novel regulator of blood pressure in mice. Rcn2 was abundantly expressed in the endothelium and adventitia of normal arteries and was dramatically upregulated in the medial layer of the artery undergoing structural remodeling. Deletion of Rcn2 lowered basal blood pressure and attenuated ANG II-induced hypertension in C57BL/6 mice. siRNA knockdown of Rcn2 dramatically increased production of the nitric oxide (NO) breakdown products nitrite and nitrate by endothelial cells but not by smooth muscle cells. Isolated carotid arteries from Rcn2-/- mice showed an increased sensitivity to the ACh-induced NO-mediated relaxant response compared with arteries of Rcn2+/+ mice. Analysis of a recent meta-data set showed associations of genetic variants near RCN2 with blood pressure in humans. These data suggest that Rcn2 regulates blood pressure and contributes to hypertension through actions on endothelial NO synthase.
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Affiliation(s)
- Jing Li
- Department of Radiology and Medical Imaging, University of Virginia , Charlottesville, Virginia
| | - Sylvia Cechova
- Department of Medicine, University of Virginia , Charlottesville, Virginia
| | - Lina Wang
- Department of Medicine, University of Virginia , Charlottesville, Virginia
- Department of Pulmonary Medicine, Qingdao University Hospital , Qingdao , China
| | - Brant E Isakson
- Robert M. Berne Cardiovascular Research Center, University of Virginia , Charlottesville, Virginia
| | - Thu H Le
- Department of Medicine, University of Virginia , Charlottesville, Virginia
| | - Weibin Shi
- Department of Radiology and Medical Imaging, University of Virginia , Charlottesville, Virginia
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179
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2017 Roadmap for Innovation-ACC Health Policy Statement on Healthcare Transformation in the Era of Digital Health, Big Data, and Precision Health: A Report of the American College of Cardiology Task Force on Health Policy Statements and Systems of Care. J Am Coll Cardiol 2019; 70:2696-2718. [PMID: 29169478 DOI: 10.1016/j.jacc.2017.10.018] [Citation(s) in RCA: 70] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
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180
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Profile of Aravinda Chakravarti. Proc Natl Acad Sci U S A 2019; 116:10608-10610. [DOI: 10.1073/pnas.1906109116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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181
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Saul MC, Philip VM, Reinholdt LG, Chesler EJ. High-Diversity Mouse Populations for Complex Traits. Trends Genet 2019; 35:501-514. [PMID: 31133439 DOI: 10.1016/j.tig.2019.04.003] [Citation(s) in RCA: 102] [Impact Index Per Article: 20.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 04/19/2019] [Accepted: 04/22/2019] [Indexed: 12/21/2022]
Abstract
Contemporary mouse genetic reference populations are a powerful platform to discover complex disease mechanisms. Advanced high-diversity mouse populations include the Collaborative Cross (CC) strains, Diversity Outbred (DO) stock, and their isogenic founder strains. When used in systems genetics and integrative genomics analyses, these populations efficiently harnesses known genetic variation for precise and contextualized identification of complex disease mechanisms. Extensive genetic, genomic, and phenotypic data are already available for these high-diversity mouse populations and a growing suite of data analysis tools have been developed to support research on diverse mice. This integrated resource can be used to discover and evaluate disease mechanisms relevant across species.
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Affiliation(s)
- Michael C Saul
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
| | - Vivek M Philip
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA
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- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA; UNC Chapel Hill, Chapel Hill, NC, USA; SUNY Binghamton, Binghamton, NY, USA; Pittsburgh University, Pittsburgh, PA, USA
| | - Elissa J Chesler
- The Jackson Laboratory for Mammalian Genetics, Bar Harbor, ME, USA.
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182
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Gallo JE, Misas E, McEwen JG, Clay OK. Toward Multiple SNP Motif Analyses of Loci Associated With Phenotypic Traits. J Am Coll Cardiol 2019; 70:1539-1540. [PMID: 28911523 DOI: 10.1016/j.jacc.2017.05.080] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 05/30/2017] [Indexed: 11/17/2022]
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183
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Touyz RM, Montezano AC, Rios F, Widlansky ME, Liang M. Redox Stress Defines the Small Artery Vasculopathy of Hypertension: How Do We Bridge the Bench-to-Bedside Gap? Circ Res 2019; 120:1721-1723. [PMID: 28546356 DOI: 10.1161/circresaha.117.310672] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Affiliation(s)
- Rhian M Touyz
- From the Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (R.M.T., A.C.M., F.R.); and Division of Cardiovascular Medicine, Department of Medicine (M.E.W.) and Center of Systems Molecular Medicine, Department of Physiology (M.L.), Medical College of Wisconsin, Milwaukee.
| | - Augusto C Montezano
- From the Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (R.M.T., A.C.M., F.R.); and Division of Cardiovascular Medicine, Department of Medicine (M.E.W.) and Center of Systems Molecular Medicine, Department of Physiology (M.L.), Medical College of Wisconsin, Milwaukee
| | - Francisco Rios
- From the Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (R.M.T., A.C.M., F.R.); and Division of Cardiovascular Medicine, Department of Medicine (M.E.W.) and Center of Systems Molecular Medicine, Department of Physiology (M.L.), Medical College of Wisconsin, Milwaukee
| | - Michael E Widlansky
- From the Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (R.M.T., A.C.M., F.R.); and Division of Cardiovascular Medicine, Department of Medicine (M.E.W.) and Center of Systems Molecular Medicine, Department of Physiology (M.L.), Medical College of Wisconsin, Milwaukee
| | - Mingyu Liang
- From the Institute of Cardiovascular and Medical Sciences, University of Glasgow, United Kingdom (R.M.T., A.C.M., F.R.); and Division of Cardiovascular Medicine, Department of Medicine (M.E.W.) and Center of Systems Molecular Medicine, Department of Physiology (M.L.), Medical College of Wisconsin, Milwaukee
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184
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Genetic variation in CADM2 as a link between psychological traits and obesity. Sci Rep 2019; 9:7339. [PMID: 31089183 PMCID: PMC6517397 DOI: 10.1038/s41598-019-43861-9] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 05/02/2019] [Indexed: 12/12/2022] Open
Abstract
CADM2 has been associated with a range of behavioural and metabolic traits, including physical activity, risk-taking, educational attainment, alcohol and cannabis use and obesity. Here, we set out to determine whether CADM2 contributes to mechanisms shared between mental and physical health disorders. We assessed genetic variants in the CADM2 locus for association with phenotypes in the UK Biobank, IMPROVE, PROCARDIS and SCARFSHEEP studies, before performing meta-analyses. A wide range of metabolic phenotypes were meta-analysed. Psychological phenotypes analysed in UK Biobank only were major depressive disorder, generalised anxiety disorder, bipolar disorder, neuroticism, mood instability and risk-taking behaviour. In UK Biobank, four, 88 and 172 genetic variants were significantly (p < 1 × 10−5) associated with neuroticism, mood instability and risk-taking respectively. In meta-analyses of 4 cohorts, we identified 362, 63 and 11 genetic variants significantly (p < 1 × 10−5) associated with BMI, SBP and CRP respectively. Genetic effects on BMI, CRP and risk-taking were all positively correlated, and were consistently inversely correlated with genetic effects on SBP, mood instability and neuroticism. Conditional analyses suggested an overlap in the signals for physical and psychological traits. Many significant variants had genotype-specific effects on CADM2 expression levels in adult brain and adipose tissues. CADM2 variants influence a wide range of both psychological and metabolic traits, suggesting common biological mechanisms across phenotypes via regulation of CADM2 expression levels in adipose tissue. Functional studies of CADM2 are required to fully understand mechanisms connecting mental and physical health conditions.
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185
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Carey RM, Calhoun DA, Bakris GL, Brook RD, Daugherty SL, Dennison-Himmelfarb CR, Egan BM, Flack JM, Gidding SS, Judd E, Lackland DT, Laffer CL, Newton-Cheh C, Smith SM, Taler SJ, Textor SC, Turan TN, White WB. Resistant Hypertension: Detection, Evaluation, and Management: A Scientific Statement From the American Heart Association. Hypertension 2019; 72:e53-e90. [PMID: 30354828 DOI: 10.1161/hyp.0000000000000084] [Citation(s) in RCA: 589] [Impact Index Per Article: 117.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Resistant hypertension (RH) is defined as above-goal elevated blood pressure (BP) in a patient despite the concurrent use of 3 antihypertensive drug classes, commonly including a long-acting calcium channel blocker, a blocker of the renin-angiotensin system (angiotensin-converting enzyme inhibitor or angiotensin receptor blocker), and a diuretic. The antihypertensive drugs should be administered at maximum or maximally tolerated daily doses. RH also includes patients whose BP achieves target values on ≥4 antihypertensive medications. The diagnosis of RH requires assurance of antihypertensive medication adherence and exclusion of the "white-coat effect" (office BP above goal but out-of-office BP at or below target). The importance of RH is underscored by the associated risk of adverse outcomes compared with non-RH. This article is an updated American Heart Association scientific statement on the detection, evaluation, and management of RH. Once antihypertensive medication adherence is confirmed and out-of-office BP recordings exclude a white-coat effect, evaluation includes identification of contributing lifestyle issues, detection of drugs interfering with antihypertensive medication effectiveness, screening for secondary hypertension, and assessment of target organ damage. Management of RH includes maximization of lifestyle interventions, use of long-acting thiazide-like diuretics (chlorthalidone or indapamide), addition of a mineralocorticoid receptor antagonist (spironolactone or eplerenone), and, if BP remains elevated, stepwise addition of antihypertensive drugs with complementary mechanisms of action to lower BP. If BP remains uncontrolled, referral to a hypertension specialist is advised.
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186
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Affiliation(s)
- Riyaz S Patel
- Institute of Cardiovascular Science, University College London, UK
| | - Stefano Masi
- Institute of Cardiovascular Science, University College London, UK.,Department of Clinical and Experimental Medicine, University of Pisa, Italy
| | - Stefano Taddei
- Department of Clinical and Experimental Medicine, University of Pisa, Italy
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187
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Liu HM, Hu Q, Zhang Q, Su GY, Xiao HM, Li BY, Shen WD, Qiu X, Lv WQ, Deng HW. Causal Effects of Genetically Predicted Cardiovascular Risk Factors on Chronic Kidney Disease: A Two-Sample Mendelian Randomization Study. Front Genet 2019; 10:415. [PMID: 31130989 PMCID: PMC6509563 DOI: 10.3389/fgene.2019.00415] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2019] [Accepted: 04/16/2019] [Indexed: 11/13/2022] Open
Abstract
Observational studies have demonstrated that cardiovascular risk factors are associated with chronic kidney disease (CKD). However, these observational associations are potentially influenced by the residual confounding, including some unmeasured lifestyle factors and interaction risk factors. Two-sample mendelian randomization analysis was conducted in this study to evaluate whether genetically predicted cardiovascular risk factors have a causal effect on the risk of CKD. We selected genetic variants associated with cardiovascular risk factors and extracted the corresponding effect sizes from the largest GWAS summary-level dataset of CKD. Cardiovascular risk factors contain high density lipoprotein (HDL) cholesterol, low density lipoprotein (LDL) cholesterol, total cholesterol (TC), triglyceride (TG), glycated hemoglobin (HbA1c), fasting glucose, systolic blood pressure (SBP) and diastolic blood pressure (DBP). A Bonferroni corrected threshold of P = 0.006 was considered as significant, and 0.006 < P < 0.05 was considered suggestive of evidence for a potential association. Genetically predicted DBP was significantly associated with CKD [odds ratio (OR) was 1.35 (95% confidence interval (CI) (1.10, 1.65); P = 0.004)]. There was suggestive evidence for potential associations between genetically predicted higher HDL cholesterol [OR: 0.88, 95%CI (0.80, 0.98), P = 0.025] and lower adds of CKD, and between higher SBP [OR: 1.36, 95%CI (1.07, 1.73), P = 0.013] and higher adds of CKD. However, genetically predicted LDL cholesterol, TC, TG, HbA1c, and fasting glucose did not show any causal association with CKD.
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Affiliation(s)
- Hui-Min Liu
- Center of System Biology and Data Information, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - Qin Hu
- Kangda College of Nanjing Medical University, Nanjing, China
| | - Qiang Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Guan-Yue Su
- Institute of Biomedical Engineering, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, China
| | - Hong-Mei Xiao
- Center of System Biology and Data Information, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - Bo-Yang Li
- Center of System Biology and Data Information, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - Wen-Di Shen
- Center of System Biology and Data Information, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - Xiang Qiu
- Center of System Biology and Data Information, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - Wan-Qiang Lv
- Center of System Biology and Data Information, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China
| | - Hong-Wen Deng
- Center of System Biology and Data Information, School of Basic Medical Science, Central South University, Changsha, China.,Center of Reproductive Health, School of Basic Medical Science, Central South University, Changsha, China.,Tulane Center of Bioinformatics and Genomics, Department of Biostatistics and Data Science, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, United States
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188
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Simonyte S, Kuciene R, Dulskiene V, Lesauskaite V. Associations of the adrenomedullin gene polymorphism with prehypertension and hypertension in Lithuanian children and adolescents: a cross-sectional study. Sci Rep 2019; 9:6807. [PMID: 31048758 PMCID: PMC6497928 DOI: 10.1038/s41598-019-43287-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2018] [Accepted: 04/04/2019] [Indexed: 11/09/2022] Open
Abstract
The aim of this study was to evaluate the association of ADM genetic variant and HBP among Lithuanian adolescents aged 12-15 years. This is a cross-sectional study of a randomly selected sample of 675 12-15-years-old schoolchildren who were surveyed during November 2010 to April 2012 in the baseline survey. Single-nucleotide polymorphism (SNP) of ADM gene (rs7129220) was evaluated using real-time PCR. Logistic regression analyses were used to test the associations of ADM (rs7129220) polymorphism with HBP under four inheritance models based on the Akaike Information Criterion (AIC) and to calculate the odds ratios. In the multivariate analysis, boys carrying ADM AG genotype (vs. carriers of ADM GG genotype), ADM AG + AA genotype (vs. carriers of ADM GG genotype) and ADM AG genotype (vs. carriers of ADM GG + AA genotype) had higher odds of having hypertension in codominant, dominant, and overdominant inheritance models. Girls with ADM AG + AA had increased odds of prehypertension compared to girls with the ADM GG genotype carriers in dominant inheritance model. Significant associations were observed in additive models separately for boys (hypertension) and girls (prehypertension). Our results indicate that ADM gene polymorphism was significantly associated with higher odds of HBP in Lithuanian adolescents aged 12-15 years.
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Affiliation(s)
- Sandrita Simonyte
- Institute of Cardiology of the Medical Academy, Lithuanian University of Health Sciences, Sukileliu 15, LT-50161, Kaunas, Lithuania.
| | - Renata Kuciene
- Institute of Cardiology of the Medical Academy, Lithuanian University of Health Sciences, Sukileliu 15, LT-50161, Kaunas, Lithuania
| | - Virginija Dulskiene
- Institute of Cardiology of the Medical Academy, Lithuanian University of Health Sciences, Sukileliu 15, LT-50161, Kaunas, Lithuania
| | - Vaiva Lesauskaite
- Institute of Cardiology of the Medical Academy, Lithuanian University of Health Sciences, Sukileliu 15, LT-50161, Kaunas, Lithuania
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189
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Prevalence of endothelial nitric oxide synthase (ENOS) gene G894T polymorphism and its association with hypertension: a population-based study with Brazilian women. ACTA ACUST UNITED AC 2019; 4:e63-e73. [PMID: 31211272 PMCID: PMC6549039 DOI: 10.5114/amsad.2019.84539] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2018] [Accepted: 03/18/2019] [Indexed: 11/29/2022]
Abstract
Introduction Hypertension is one of the most prevalent diseases in the world, accounting for millions of deaths each year. The reduction in the concentration of nitric oxide (NO) produced by the catalysis of endothelial nitric oxide synthase (eNOS) is associated with higher blood pressure (BP) levels. This reduction might be because of genetic polymorphisms. This study investigated the prevalence of the eNOS gene G894T polymorphism in women from northeast Brazil and its association with hypertension. Material and methods This cross-sectional study included 810 women (aged 19–49 years). Sociodemographic, health, anthropometric, and BP data were collected. Hypertension was defined according to the following criteria: systolic BP ≥ 140 mm Hg, diastolic BP ≥ 90 mm Hg, the regular use of antihypertensive medication, or some combination thereof. Epithelial cells from the cheek mucosa were obtained for DNA extraction. Genotyping was performed via real-time PCR. The measure of association was the prevalence ratio (PR) and its 95% CI as calculated via Poisson regression. Results The frequencies of the GG, GT, and TT genotypes were 57.1%, 35.7%, and 7.2%, respectively. For each of these genotypes, the prevalence of hypertension in women was 17.9%, 23.6%, and 34.4%, respectively. Relative to the GG genotype, the PRs after adjusting for cofounding factors were 1.24 (95% CI: 0.95–1.61, p = 0.11) for GT and 1.76 (95% CI: 1.16–2.67, p < 0.01) for TT. Conclusions The T allele of the G894T polymorphisms is associated with hypertension in women. This may have implications for prevention and treatment.
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190
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Pescatello LS, Parducci P, Livingston J, Taylor BA. A Systematically Assembled Signature of Genes to be Deep-Sequenced for Their Associations with the Blood Pressure Response to Exercise. Genes (Basel) 2019; 10:genes10040295. [PMID: 30979034 PMCID: PMC6523684 DOI: 10.3390/genes10040295] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2019] [Revised: 04/04/2019] [Accepted: 04/04/2019] [Indexed: 02/08/2023] Open
Abstract
: Background: Exercise is one of the best nonpharmacologic therapies to treat hypertension. The blood pressure (BP) response to exercise is heritable. Yet, the genetic basis for the antihypertensive effects of exercise remains elusive. Methods: To assemble a prioritized gene signature, we performed a systematic review with a series of Boolean searches in PubMed (including Medline) from earliest coverage. The inclusion criteria were human genes in major BP regulatory pathways reported to be associated with: (1) the BP response to exercise; (2) hypertension in genome-wide association studies (GWAS); (3) the BP response to pharmacotherapy; (4a) physical activity and/or obesity in GWAS; and (4b) BP, physical activity, and/or obesity in non-GWAS. Included GWAS reports disclosed the statistically significant thresholds used for multiple testing. Results: The search yielded 1422 reports. Of these, 57 trials qualified from which we extracted 11 genes under criteria 1, 18 genes under criteria 2, 28 genes under criteria 3, 27 genes under criteria 4a, and 29 genes under criteria 4b. We also included 41 genes identified from our previous work. Conclusions: Deep-sequencing the exons of this systematically assembled signature of genes represents a cost and time efficient approach to investigate the genomic basis for the antihypertensive effects of exercise.
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Affiliation(s)
- Linda S Pescatello
- Department of Kinesiology, University of Connecticut, Storrs, CT 06269, USA.
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269, USA.
| | - Paul Parducci
- Department of Kinesiology, University of Connecticut, Storrs, CT 06269, USA.
| | - Jill Livingston
- Homer Babbidge Library, Health Sciences, University of Connecticut, Storrs, CT 06269, USA.
| | - Beth A Taylor
- Department of Kinesiology, University of Connecticut, Storrs, CT 06269, USA.
- Institute for Systems Genomics, University of Connecticut, Storrs, CT 06269, USA.
- Preventive Cardiology, Hartford Hospital, Hartford, CT 06269, USA.
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191
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Kolifarhood G, Daneshpour MS, Khayat BS, Saadati HM, Guity K, Khosravi N, Akbarzadeh M, Sabour S. Generality of genomic findings on blood pressure traits and its usefulness in precision medicine in diverse populations: A systematic review. Clin Genet 2019; 96:17-27. [PMID: 30820929 DOI: 10.1111/cge.13527] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 02/14/2019] [Accepted: 02/21/2019] [Indexed: 01/01/2023]
Abstract
Remarkable findings from genome-wide association studies (GWAS) on blood pressure (BP) traits have made new insights for developing precision medicine toward more effective screening measures. However, generality of GWAS findings in diverse populations is hampered by some technical limitations. There is no comprehensive study to evaluate source(s) of the non-generality of GWAS results on BP traits, so to fill the gap, this systematic review study was carried out. Using MeSH terms, 1545 records were detected through searching in five databases and 49 relevant full-text articles were included in our review. Overall, 749 unique variants were reported, of those, majority of variants have been detected in Europeans and were associated to systolic and diastolic BP traits. Frequency of genetic variants with same position was low in European and non-European populations (n = 38). However, more than 200 (>25%) single nucleotide polymorphisms were found on same loci or linkage disequilibrium blocks (r2 ≥ 80%). Investigating for locus position and linkage disequilibrium of infrequent unique variants showed modest to high reproducibility of findings in Europeans that in some extent was generalizable in other populations. Beyond theoretical limitations, our study addressed other possible sources of non-generality of GWAS findings for BP traits in the same and different origins.
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Affiliation(s)
- Goodarz Kolifarhood
- Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam S Daneshpour
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Bahareh S Khayat
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hossein M Saadati
- Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Kamran Guity
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Nasim Khosravi
- Department of Community Health Nursing, School of Nursing and Midwifery, Iran University of Medical Sciences, Tehran, Iran
| | - Mahdi Akbarzadeh
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Siamak Sabour
- Department of Epidemiology, School of Public Health, Shahid Beheshti University of Medical Sciences, Tehran, Iran.,Safety Promotion and Injury Prevention Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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192
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Cowley AW. Chrm3 Gene and M3 Muscarinic Receptors Contribute to Salt-Sensitive Hypertension. Hypertension 2019; 72:588-591. [PMID: 30354773 DOI: 10.1161/hypertensionaha.118.11494] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Allen W Cowley
- From the Department of Physiology, Medical College of Wisconsin, Milwaukee
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193
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Schulz A, Müller NV, van de Lest NA, Eisenreich A, Schmidbauer M, Barysenka A, Purfürst B, Sporbert A, Lorenzen T, Meyer AM, Herlan L, Witten A, Rühle F, Zhou W, de Heer E, Scharpfenecker M, Panáková D, Stoll M, Kreutz R. Analysis of the genomic architecture of a complex trait locus in hypertensive rat models links Tmem63c to kidney damage. eLife 2019; 8:42068. [PMID: 30900988 PMCID: PMC6478434 DOI: 10.7554/elife.42068] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2018] [Accepted: 03/20/2019] [Indexed: 12/23/2022] Open
Abstract
Unraveling the genetic susceptibility of complex diseases such as chronic kidney disease remains challenging. Here, we used inbred rat models of kidney damage associated with elevated blood pressure for the comprehensive analysis of a major albuminuria susceptibility locus detected in these models. We characterized its genomic architecture by congenic substitution mapping, targeted next-generation sequencing, and compartment-specific RNA sequencing analysis in isolated glomeruli. This led to prioritization of transmembrane protein Tmem63c as a novel potential target. Tmem63c is differentially expressed in glomeruli of allele-specific rat models during onset of albuminuria. Patients with focal segmental glomerulosclerosis exhibited specific TMEM63C loss in podocytes. Functional analysis in zebrafish revealed a role for tmem63c in mediating the glomerular filtration barrier function. Our data demonstrate that integrative analysis of the genomic architecture of a complex trait locus is a powerful tool for identification of new targets such as Tmem63c for further translational investigation. The human kidneys filter the entire volume of the blood about 300 times each day. This ability depends on specialized cells, known as podocytes, which wrap around some of the blood vessels in the kidney. These cells control which molecules leave the blood based on their size. Normally large molecules like proteins are blocked, while smaller molecules including waste products, toxins, excess water and salts pass through into the urine. If this filtration system is damaged, by high blood pressure, for example, it can lead to chronic kidney disease. A hallmark of this disease, often called CKD for short, is high levels of the protein albumin in the urine. Previous studies involving rats with high blood pressure have found several regions of the genome that contribute to high levels of albumin in the urine, including one on chromosome 6. However, this region contains several genes and it was unclear which genes affected the condition. Schulz et al. set out to narrow down the list and find specific genes that might contribute to elevated albumin in the urine of rats with high blood pressure. This search identified the gene for a protein called TMEM63c as a likely candidate. This protein spans the outer membrane of podocyte cells. Analysis of kidney biopsies showed that patients with chronic kidney disease also had low levels of this protein in their podocytes. Further experiments, this time in zebrafish, showed that reducing the activity of the gene for tmem63c led to damaged podocytes and a leakier filter in the kidneys. The results suggest that this gene plays an important role in the integrity of the kidneys filtration barrier. It is possible that faulty versions of this gene are behind some cases of chronic kidney disease. If this proves to be the case, a better understanding of the role of this gene may lead to new treatments for the condition.
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Affiliation(s)
- Angela Schulz
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,Institute of Clinical Pharmacology and Toxicology, Berlin Institute of Health, Berlin, Germany
| | - Nicola Victoria Müller
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,Institute of Clinical Pharmacology and Toxicology, Berlin Institute of Health, Berlin, Germany.,Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Electrochemical Signaling in Development and Disease, Berlin, Germany
| | - Nina Anne van de Lest
- Department of Pathology, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Andreas Eisenreich
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,Institute of Clinical Pharmacology and Toxicology, Berlin Institute of Health, Berlin, Germany
| | - Martina Schmidbauer
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.,Institute of Clinical Pharmacology and Toxicology, Berlin Institute of Health, Berlin, Germany
| | - Andrei Barysenka
- Westfälische Wilhelms University, Genetic Epidemiology, Institute for Human Genetics, Münster, Germany
| | - Bettina Purfürst
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Core Facility Electron Microscopy, Berlin, Germany
| | - Anje Sporbert
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Advanced Light Microscopy, Berlin, Germany
| | - Theodor Lorenzen
- Institute of Clinical Pharmacology and Toxicology, Berlin Institute of Health, Berlin, Germany
| | | | - Laura Herlan
- Institute of Clinical Pharmacology and Toxicology, Berlin Institute of Health, Berlin, Germany
| | - Anika Witten
- Westfälische Wilhelms University, Genetic Epidemiology, Institute for Human Genetics, Münster, Germany
| | - Frank Rühle
- Westfälische Wilhelms University, Genetic Epidemiology, Institute for Human Genetics, Münster, Germany
| | - Weibin Zhou
- Division of Nephrology, Department of Medicine, Center for Human Disease Modeling, Duke University School of Medicine, Durham, United States
| | - Emile de Heer
- Department of Pathology, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Marion Scharpfenecker
- Department of Pathology, Leiden University Medical Center (LUMC), Leiden, The Netherlands
| | - Daniela Panáková
- DZHK (German Centre for Cardiovascular Research), Partner site Berlin, Berlin, Germany
| | - Monika Stoll
- Westfälische Wilhelms University, Genetic Epidemiology, Institute for Human Genetics, Münster, Germany.,Department of Biochemistry, Maastricht University, Genetic Epidemiology and Statistical Genetics, Maastricht, The Netherlands
| | - Reinhold Kreutz
- Institute of Clinical Pharmacology and Toxicology, Berlin Institute of Health, Berlin, Germany.,DZHK (German Centre for Cardiovascular Research), Partner site Berlin, Berlin, Germany
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194
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Abstract
The autonomic nervous system exerts broad control over the involuntary functions of the human body through complex equilibrium between sympathetic and parasympathetic tone. Imbalance in this equilibrium is associated with a multitude of cardiovascular outcomes, including mortality. The cardiovascular static state of this equilibrium can be quantified using physiological parameters such as heart rate (HR), blood pressure, and by spectral analysis of HR variability. Here, we review the current state of knowledge of the genetic background of cardiovascular measurements of autonomic tone. For most parameters of autonomic tone, a large portion of variability is explained by genetic heritability. Many of the static parameters of autonomic tone have also been studied through candidate-gene approach, yielding some insight into how genotypes of adrenergic receptors affect variables such as HR. Genome-wide approaches in large cohorts similarly exist for static variables such as HR and blood pressure but less is known about the genetic background of the dynamic and more specific measurements, such as HR variability. Furthermore, because most autonomic measures are likely polygenic, pathway analyses and modeling of polygenic effects are critical. Future work will hopefully explain the control of autonomic tone and guide individualized therapeutic interventions.
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195
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Kokubo Y, Padmanabhan S, Iwashima Y, Yamagishi K, Goto A. Gene and environmental interactions according to the components of lifestyle modifications in hypertension guidelines. Environ Health Prev Med 2019; 24:19. [PMID: 30857519 PMCID: PMC6410507 DOI: 10.1186/s12199-019-0771-2] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2018] [Accepted: 02/24/2019] [Indexed: 12/24/2022] Open
Abstract
Risk factors for hypertension consist of lifestyle and genetic factors. Family history and twin studies have yielded heritability estimates of BP in the range of 34–67%. The most recent paper of BP GWAS has explained about 20% of the population variation of BP. An overestimation of heritability may have occurred in twin studies due to violations of shared environment assumptions, poor phenotyping practices in control cohorts, failure to account for epistasis, gene-gene and gene-environment interactions, and other non-genetic sources of phenotype modulation that are suspected to lead to underestimations of heritability in GWAS. The recommendations of hypertension guidelines in major countries consist of the following elements: weight reduction, a healthy diet, dietary sodium reduction, increasing physical activity, quitting smoking, and moderate alcohol consumption. The hypertension guidelines are mostly the same for each country or region, beyond race and culture. In this review, we summarize gene-environmental interactions associated with hypertension by describing lifestyle modifications according to the hypertension guidelines. In the era of precision medicine, clinicians who are responsible for hypertension management should consider the gene-environment interactions along with the appropriate lifestyle components toward the prevention and treatment of hypertension. We briefly reviewed the interaction of genetic and environmental factors along the constituent elements of hypertension guidelines, but a sufficient amount of evidence has not yet accumulated, and the results of genetic factors often differed in each study.
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Affiliation(s)
- Yoshihiro Kokubo
- Department of Preventive Cardiology, National Cerebral and Cardiovascular Center, 5-7-1, Fujishiro-dai, Suita, Osaka, 565-8565, Japan. .,Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK.
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Yoshio Iwashima
- Division of Hypertension and Nephrology, Department of Medicine, National Cerebral and Cardiovascular Center, Suita, Japan
| | - Kazumasa Yamagishi
- Department of Public Health Medicine, Faculty of Medicine, and Health Services Research and Development Center, University of Tsukuba, Tsukuba, Japan
| | - Atsushi Goto
- Epidemiology and Prevention Group, Center for Public Health Sciences, National Cancer Center, Tokyo, Japan
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196
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Zhou A, Hyppönen E. Long-term coffee consumption, caffeine metabolism genetics, and risk of cardiovascular disease: a prospective analysis of up to 347,077 individuals and 8368 cases. Am J Clin Nutr 2019; 109:509-516. [PMID: 30838377 DOI: 10.1093/ajcn/nqy297] [Citation(s) in RCA: 52] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2018] [Accepted: 10/02/2018] [Indexed: 02/04/2023] Open
Abstract
BACKGROUND Coffee is one of the most widely consumed stimulants worldwide and is generally considered to be safe or even beneficial for health. However, increased risk of myocardial infarction and hypertension has been suggested for individuals who carry a functional variant at cytochrome P450 1A2 (CYP1A2), which makes them less effective at metabolizing caffeine. OBJECTIVES The aim of this study was to examine if the CYP1A2 genotype or a genetic score for caffeine metabolism (caffeine-GS) modifies the association between habitual coffee consumption and the risk of cardiovascular disease (CVD). METHODS Genetic data and information on habitual coffee intake and relevant covariates were available for 347,077 individuals in the UK Biobank, including 8368 incident CVD cases. We used logistic regression to test for the association between coffee intake and CVD risk, and whether the association varies with CYP1A2 genotype or caffeine-GS. RESULTS The association between habitual coffee intake and CVD risk was nonlinear, and, compared with participants drinking 1-2 cups/day, the risk of CVD was elevated for nondrinkers, drinkers of decaffeinated coffee, and those who reported drinking >6 cups/day (increase in odds by 11%, 7%, and 22%, respectively, P-curvature = 0.013). CYP1A2 genotype and caffeine-GS were not associated with CVD (P ≥ 0.22 for all comparisons). There was no evidence for an interaction between the CYP1A2 genotype or caffeine-GS and coffee intake with respect to risk of CVD (P ≥ 0.53). CONCLUSIONS Heavy coffee consumption was associated with a modest increase in CVD risk, but this association was unaffected by genetic variants influencing caffeine metabolism.
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Affiliation(s)
- Ang Zhou
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, Adelaide, Australia
| | - Elina Hyppönen
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, Adelaide, Australia.,Population, Policy and Practice, UCL Institute of Child Health, London, United Kingdom.,South Australian Health and Medical Research Institute, Adelaide, Australia
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197
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Affiliation(s)
- Timon Seeger
- From the Stanford Cardiovascular Institute, CA (T.S., J.C.W.); Department of Medicine, Division of Cardiology (T.S., J.S.W.); Department of Pediatrics, Division of Stem Cell Transplantation and Regenerative Medicine (M.P.); and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, CA (M.P., J.C.W.)
| | - Matthew Porteus
- From the Stanford Cardiovascular Institute, CA (T.S., J.C.W.); Department of Medicine, Division of Cardiology (T.S., J.S.W.); Department of Pediatrics, Division of Stem Cell Transplantation and Regenerative Medicine (M.P.); and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, CA (M.P., J.C.W.)
| | - Joseph C Wu
- From the Stanford Cardiovascular Institute, CA (T.S., J.C.W.); Department of Medicine, Division of Cardiology (T.S., J.S.W.); Department of Pediatrics, Division of Stem Cell Transplantation and Regenerative Medicine (M.P.); and Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, CA (M.P., J.C.W.).
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198
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Ali AT, Boehme L, Carbajosa G, Seitan VC, Small KS, Hodgkinson A. Nuclear genetic regulation of the human mitochondrial transcriptome. eLife 2019; 8:e41927. [PMID: 30775970 PMCID: PMC6420317 DOI: 10.7554/elife.41927] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 02/14/2019] [Indexed: 12/21/2022] Open
Abstract
Mitochondria play important roles in cellular processes and disease, yet little is known about how the transcriptional regime of the mitochondrial genome varies across individuals and tissues. By analyzing >11,000 RNA-sequencing libraries across 36 tissue/cell types, we find considerable variation in mitochondrial-encoded gene expression along the mitochondrial transcriptome, across tissues and between individuals, highlighting the importance of cell-type specific and post-transcriptional processes in shaping mitochondrial-encoded RNA levels. Using whole-genome genetic data we identify 64 nuclear loci associated with expression levels of 14 genes encoded in the mitochondrial genome, including missense variants within genes involved in mitochondrial function (TBRG4, MTPAP and LONP1), implicating genetic mechanisms that act in trans across the two genomes. We replicate ~21% of associations with independent tissue-matched datasets and find genetic variants linked to these nuclear loci that are associated with cardio-metabolic phenotypes and Vitiligo, supporting a potential role for variable mitochondrial-encoded gene expression in complex disease.
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Affiliation(s)
- Aminah T Ali
- Department of Medical and Molecular Genetics, School of Basic and Medical BiosciencesKing’s College LondonLondonUnited Kingdom
| | - Lena Boehme
- Department of Medical and Molecular Genetics, School of Basic and Medical BiosciencesKing’s College LondonLondonUnited Kingdom
| | - Guillermo Carbajosa
- Department of Medical and Molecular Genetics, School of Basic and Medical BiosciencesKing’s College LondonLondonUnited Kingdom
| | - Vlad C Seitan
- Department of Medical and Molecular Genetics, School of Basic and Medical BiosciencesKing’s College LondonLondonUnited Kingdom
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, School of Life Course SciencesKing’s College LondonLondonUnited Kingdom
| | - Alan Hodgkinson
- Department of Medical and Molecular Genetics, School of Basic and Medical BiosciencesKing’s College LondonLondonUnited Kingdom
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199
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Lim JE, Kim HO, Rhee SY, Kim MK, Kim YJ, Oh B. Gene-environment interactions related to blood pressure traits in two community-based Korean cohorts. Genet Epidemiol 2019; 43:402-413. [PMID: 30770579 DOI: 10.1002/gepi.22195] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2018] [Revised: 11/08/2018] [Accepted: 11/26/2018] [Indexed: 01/11/2023]
Abstract
Hypertension is a complex disorder caused by genetic and environmental risk factors. Recently, genome-wide association studies (GWASs) identified more than 100 genetic variants for blood pressure traits and hypertension. However, the interactions between these genetic variants and environmental factors have not been systematically investigated. Therefore, we examined the interaction between genetic and environmental risk factors in blood pressure traits using the genetic risk score (GRS). Two Korean community-based cohorts, Cohort I (KARE; N = 8,840) and Cohort II (CAVAS; N = 9,599), were used for this study, and GRSs were calculated from 42 GWAS single-nucleotide polymorphisms (SNPs) that were validated for their association in these cohorts. We calculated GRSs in both ways by considering the effect sizes of each SNP (weighted GRS) and not considering the effect sizes (unweighted GRS). The unweighted GRS was strongly associated with systolic blood pressure, diastolic blood pressure, and hypertension (p = 9.03 × 10 -47 , p = 9.41 × 10 -48 , and p = 3.22 × 10 -55 by meta-analysis, respectively) and the weighted GRS showed the similar results. The environmental factors of body mass index, waist circumference, and drinking status were significantly associated with blood pressure traits, and the interaction between these factors and GRSs were examined. However, no interactions were found with either the GRS or the individual SNPs considered for the GRS. Our findings show that it is challenging to find GRS-environment interactions regarding blood pressure traits.
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Affiliation(s)
- Ji Eun Lim
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Hye Ok Kim
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Sang Youl Rhee
- Department of Endocrinology and Metabolism, Kyung Hee University School of Medicine, Seoul, Republic of Korea
| | - Mi Kyung Kim
- Institute for Health and Society, Hanyang University, Seoul, Republic of Korea.,Department of Preventive Medicine, College of Medicine, Hanyang University, Seoul, Republic of Korea
| | - Yeon-Jung Kim
- Division of Biobank for Health Science, Center for Genome Science, Korea National Institute of Health, Chungcheongbuk-do, Republic of Korea
| | - Bermseok Oh
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul, Republic of Korea
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200
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Moon S, Kim YJ, Han S, Hwang MY, Shin DM, Park MY, Lu Y, Yoon K, Jang HM, Kim YK, Park TJ, Song DS, Park JK, Lee JE, Kim BJ. The Korea Biobank Array: Design and Identification of Coding Variants Associated with Blood Biochemical Traits. Sci Rep 2019; 9:1382. [PMID: 30718733 PMCID: PMC6361960 DOI: 10.1038/s41598-018-37832-9] [Citation(s) in RCA: 166] [Impact Index Per Article: 33.2] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2018] [Accepted: 12/11/2018] [Indexed: 02/05/2023] Open
Abstract
We introduce the design and implementation of a new array, the Korea Biobank Array (referred to as KoreanChip), optimized for the Korean population and demonstrate findings from GWAS of blood biochemical traits. KoreanChip comprised >833,000 markers including >247,000 rare-frequency or functional variants estimated from >2,500 sequencing data in Koreans. Of the 833 K markers, 208 K functional markers were directly genotyped. Particularly, >89 K markers were presented in East Asians. KoreanChip achieved higher imputation performance owing to the excellent genomic coverage of 95.38% for common and 73.65% for low-frequency variants. From GWAS (Genome-wide association study) using 6,949 individuals, 28 associations were successfully recapitulated. Moreover, 9 missense variants were newly identified, of which we identified new associations between a common population-specific missense variant, rs671 (p.Glu457Lys) of ALDH2, and two traits including aspartate aminotransferase (P = 5.20 × 10−13) and alanine aminotransferase (P = 4.98 × 10−8). Furthermore, two novel missense variants of GPT with rare frequency in East Asians but extreme rarity in other populations were associated with alanine aminotransferase (rs200088103; p.Arg133Trp, P = 2.02 × 10−9 and rs748547625; p.Arg143Cys, P = 1.41 × 10−6). These variants were successfully replicated in 6,000 individuals (P = 5.30 × 10−8 and P = 1.24 × 10−6). GWAS results suggest the promising utility of KoreanChip with a substantial number of damaging variants to identify new population-specific disease-associated rare/functional variants.
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Affiliation(s)
- Sanghoon Moon
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | - Young Jin Kim
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | - Sohee Han
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | - Mi Yeong Hwang
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | - Dong Mun Shin
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | | | | | - Kyungheon Yoon
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | - Hye-Mi Jang
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | - Yun Kyoung Kim
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | - Tae-Joon Park
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | - Dae Sub Song
- Division of Epidemiology and Health Index, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | - Jae Kyung Park
- Division of Epidemiology and Health Index, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea
| | - Jong-Eun Lee
- DNA link, Incorporated, Seoul, 03759, Republic of Korea
| | - Bong-Jo Kim
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, 28159, Republic of Korea.
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