1
|
Ramírez J, van Duijvenboden S, Young WJ, Chen Y, Usman T, Orini M, Lambiase PD, Tinker A, Bell CG, Morris AP, Munroe PB. Fine mapping of candidate effector genes for heart rate. Hum Genet 2024:10.1007/s00439-024-02684-z. [PMID: 38969939 DOI: 10.1007/s00439-024-02684-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2024] [Accepted: 06/19/2024] [Indexed: 07/07/2024]
Abstract
An elevated resting heart rate (RHR) is associated with increased cardiovascular mortality. Genome-wide association studies (GWAS) have identified > 350 loci. Uniquely, in this study we applied genetic fine-mapping leveraging tissue specific chromatin segmentation and colocalization analyses to identify causal variants and candidate effector genes for RHR. We used RHR GWAS summary statistics from 388,237 individuals of European ancestry from UK Biobank and performed fine mapping using publicly available genomic annotation datasets. High-confidence causal variants (accounting for > 75% posterior probability) were identified, and we collated candidate effector genes using a multi-omics approach that combined evidence from colocalisation with molecular quantitative trait loci (QTLs), and long-range chromatin interaction analyses. Finally, we performed druggability analyses to investigate drug repurposing opportunities. The fine mapping pipeline indicated 442 distinct RHR signals. For 90 signals, a single variant was identified as a high-confidence causal variant, of which 22 were annotated as missense. In trait-relevant tissues, 39 signals colocalised with cis-expression QTLs (eQTLs), 3 with cis-protein QTLs (pQTLs), and 75 had promoter interactions via Hi-C. In total, 262 candidate genes were highlighted (79% had promoter interactions, 15% had a colocalised eQTL, 8% had a missense variant and 1% had a colocalised pQTL), and, for the first time, enrichment in nervous system pathways. Druggability analyses highlighted ACHE, CALCRL, MYT1 and TDP1 as potential targets. Our genetic fine-mapping pipeline prioritised 262 candidate genes for RHR that warrant further investigation in functional studies, and we provide potential therapeutic targets to reduce RHR and cardiovascular mortality.
Collapse
Affiliation(s)
- Julia Ramírez
- Aragon Institute of Engineering Research, University of Zaragoza, Zaragoza, Spain.
- Centro de Investigación Biomédica en Red - Bioingeniería, Biomateriales y Nanomedicina, Zaragoza, Spain.
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
| | - Stefan van Duijvenboden
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
- Nuffield Department of Population Health, University of Oxford, Old Road Campus, Headington, Oxford, OX3 7LF, UK.
- Institute of Cardiovascular Science, University College London, London, UK.
| | - William J Young
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Barts Heart Centre, St Bartholomew's Hospital, London, EC1A 7BE, UK
| | - Yutang Chen
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Environmental Systems Science, ETH Zurich, Zurich, Switzerland
| | | | - Michele Orini
- Institute of Cardiovascular Science, University College London, London, UK
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London, UK
- Barts Heart Centre, St Bartholomew's Hospital, London, EC1A 7BE, UK
| | - Andrew Tinker
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Barts Cardiovascular Biomedical Research Centre, National Institute of Health and Care Research, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Christopher G Bell
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Andrew P Morris
- Centre for Musculoskeletal Research, The University of Manchester, Manchester, UK
- National Institute of Health and Care Research, Manchester Biomedical Research Centre, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Patricia B Munroe
- William Harvey Research Institute, Barts and the London Faculty of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.
- Khalifa University, Abu Dhabi, United Arab Emirates.
- Barts Cardiovascular Biomedical Research Centre, National Institute of Health and Care Research, Queen Mary University of London, London, EC1M 6BQ, UK.
| |
Collapse
|
2
|
Lo Faro V, Bhattacharya A, Zhou W, Zhou D, Wang Y, Läll K, Kanai M, Lopera-Maya E, Straub P, Pawar P, Tao R, Zhong X, Namba S, Sanna S, Nolte IM, Okada Y, Ingold N, MacGregor S, Snieder H, Surakka I, Shortt J, Gignoux C, Rafaels N, Crooks K, Verma A, Verma SS, Guare L, Rader DJ, Willer C, Martin AR, Brantley MA, Gamazon ER, Jansonius NM, Joos K, Cox NJ, Hirbo J. Novel ancestry-specific primary open-angle glaucoma loci and shared biology with vascular mechanisms and cell proliferation. Cell Rep Med 2024; 5:101430. [PMID: 38382466 PMCID: PMC10897632 DOI: 10.1016/j.xcrm.2024.101430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 03/28/2023] [Accepted: 01/25/2024] [Indexed: 02/23/2024]
Abstract
Primary open-angle glaucoma (POAG), a leading cause of irreversible blindness globally, shows disparity in prevalence and manifestations across ancestries. We perform meta-analysis across 15 biobanks (of the Global Biobank Meta-analysis Initiative) (n = 1,487,441: cases = 26,848) and merge with previous multi-ancestry studies, with the combined dataset representing the largest and most diverse POAG study to date (n = 1,478,037: cases = 46,325) and identify 17 novel significant loci, 5 of which were ancestry specific. Gene-enrichment and transcriptome-wide association analyses implicate vascular and cancer genes, a fifth of which are primary ciliary related. We perform an extensive statistical analysis of SIX6 and CDKN2B-AS1 loci in human GTEx data and across large electronic health records showing interaction between SIX6 gene and causal variants in the chr9p21.3 locus, with expression effect on CDKN2A/B. Our results suggest that some POAG risk variants may be ancestry specific, sex specific, or both, and support the contribution of genes involved in programmed cell death in POAG pathogenesis.
Collapse
Affiliation(s)
- Valeria Lo Faro
- Department of Ophthalmology, Amsterdam University Medical Center (AMC), Amsterdam, the Netherlands; Department of Clinical Genetics, Amsterdam University Medical Center (AMC), Amsterdam, the Netherlands; Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Institute for Quantitative and Computational Biosciences, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Dan Zhou
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ying Wang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Kristi Läll
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Esteban Lopera-Maya
- University of Groningen, UMCG, Department of Genetics, Groningen, the Netherlands
| | - Peter Straub
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Priyanka Pawar
- Vanderbilt Eye Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ran Tao
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA; Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Xue Zhong
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Serena Sanna
- University of Groningen, UMCG, Department of Genetics, Groningen, the Netherlands; Institute for Genetics and Biomedical Research (IRGB), National Research Council (CNR), Cagliari, Italy
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Osaka, Japan; Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan; Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka, Japan; Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka, Japan; Center for Infectious Disease Education and Research (CiDER), Osaka University, Osaka, Japan
| | - Nathan Ingold
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Queensland University of Technology, Brisbane, QLD, Australia; School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD, Australia
| | - Stuart MacGregor
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Queensland University of Technology, Brisbane, QLD, Australia
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Ida Surakka
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Jonathan Shortt
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Chris Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Nicholas Rafaels
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Kristy Crooks
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Anurag Verma
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA, USA; Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA
| | - Shefali S Verma
- Department of Pathology, University of Pennsylvania, Philadelphia, PA, USA
| | - Lindsay Guare
- Department of Pathology, University of Pennsylvania, Philadelphia, PA, USA; Institute for Biomedical Informatics, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel J Rader
- Department of Medicine, Division of Translational Medicine and Human Genetics, University of Pennsylvania, Philadelphia, PA, USA; Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, USA; Department of Genetics, University of Pennsylvania, Philadelphia, PA, USA
| | - Cristen Willer
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway; Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA; Department of Human Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA; Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Milam A Brantley
- Vanderbilt Eye Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Eric R Gamazon
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nomdo M Jansonius
- Department of Ophthalmology, Amsterdam University Medical Center (AMC), Amsterdam, the Netherlands
| | - Karen Joos
- Vanderbilt Eye Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Nancy J Cox
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jibril Hirbo
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA.
| |
Collapse
|
3
|
Long X, Wei J, Fang Q, Yuan X, Du J. Single-cell RNA sequencing reveals the transcriptional heterogeneity of Tbx18-positive cardiac cells during heart development. Funct Integr Genomics 2024; 24:18. [PMID: 38265516 DOI: 10.1007/s10142-024-01290-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Revised: 12/29/2023] [Accepted: 01/02/2024] [Indexed: 01/25/2024]
Abstract
The T-box family transcription factor 18 (Tbx18) has been found to play a critical role in regulating the development of the mammalian heart during the primary stages of embryonic development while the cellular heterogeneity and landscape of Tbx18-positive (Tbx18+) cardiac cells remain incompletely characterized. Here, we analyzed prior published single-cell RNA sequencing (scRNA-seq) mouse heart data to explore the heterogeneity of Tbx18+ cardiac cell subpopulations and provide a comprehensive transcriptional landscape of Tbx18+ cardiac cells during their development. Bioinformatic analysis methods were utilized to identify the heterogeneity between cell groups. Based on the gene expression characteristics, Tbx18+ cardiac cells can be classified into a minimum of two distinct cell populations, namely fibroblast-like cells and cardiomyocytes. In terms of temporal heterogeneity, these cells exhibit three developmental stages, namely the MEM stage, ML_P0 stage, and P stage Tbx18+ cardiac cells. Furthermore, Tbx18+ cardiac cells encompass several cell types, including cardiac progenitor-like cells, cardiomyocytes, and epicardial/stromal cells, as determined by specific transcriptional regulatory networks. The scRNA-seq results revealed the involvement of extracellular matrix (ECM) signals and epicardial epithelial-to-mesenchymal transition (EMT) in the development of Tbx18+ cardiac cells. The utilization of a lineage-tracing model served to validate the crucial function of Tbx18 in the differentiation of cardiac cells. Consequently, these findings offer a comprehensive depiction of the cellular heterogeneity within Tbx18+ cardiac cells.
Collapse
Affiliation(s)
- Xianglin Long
- Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Jiangjun Wei
- Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Qinghua Fang
- Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China
| | - Xin Yuan
- Department of Nephrology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.
| | - Jianlin Du
- Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, 400010, China.
| |
Collapse
|
4
|
Texis T, Rivera-Mancía S, Colín-Ramírez E, Cartas-Rosado R, Koepsell D, Rubio-Carrasco K, Rodríguez-Dorantes M, Gonzalez-Covarrubias V. Genetic Determinants of Atherogenic Indexes. Genes (Basel) 2023; 14:1214. [PMID: 37372394 DOI: 10.3390/genes14061214] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 05/24/2023] [Accepted: 05/25/2023] [Indexed: 06/29/2023] Open
Abstract
Atherogenesis and dyslipidemia increase the risk of cardiovascular disease, which is the leading cause of death in developed countries. While blood lipid levels have been studied as disease predictors, their accuracy in predicting cardiovascular risk is limited due to their high interindividual and interpopulation variability. The lipid ratios, atherogenic index of plasma (AIP = log TG/HDL-C) and the Castelli risk index 2 (CI2 = LDL-C/HDL-C), have been proposed as better predictors of cardiovascular risk, but the genetic variability associated with these ratios has not been investigated. This study aimed to identify genetic associations with these indexes. The study population (n = 426) included males (40%) and females (60%) aged 18-52 years (mean 39 years); the Infinium GSA array was used for genotyping. Regression models were developed using R and PLINK. AIP was associated with variation on APOC3, KCND3, CYBA, CCDC141/TTN, and ARRB1 (p-value < 2.1 × 10-6). The three former were previously associated with blood lipids, while CI2 was associated with variants on DIPK2B, LIPC, and 10q21.3 rs11251177 (p-value 1.1 × 10-7). The latter was previously linked to coronary atherosclerosis and hypertension. KCND3 rs6703437 was associated with both indexes. This study is the first to characterize the potential link between genetic variation and atherogenic indexes, AIP, and CI2, highlighting the relationship between genetic variation and dyslipidemia predictors. These results also contribute to consolidating the genetics of blood lipid and lipid indexes.
Collapse
Affiliation(s)
- Tomas Texis
- National Institute of Genomic Medicine (INMEGEN), Mexico City 14610, Mexico
| | | | - Eloisa Colín-Ramírez
- School of Sports Sciences, Anahuac University of North Mexico, Huixquilucan 52786, Mexico
| | - Raul Cartas-Rosado
- National Institute of Cardiology Ignacio Chavez, Mexico City 14080, Mexico
| | - David Koepsell
- Conduct Research Committee, Texas A&M University, College Station, TX 77843, USA
| | - Kenneth Rubio-Carrasco
- National Institute of Genomic Medicine (INMEGEN), Mexico City 14610, Mexico
- School of Sports Sciences, Anahuac University of North Mexico, Huixquilucan 52786, Mexico
- Faculty of Chemistry UNAM, Mexico City 04510, Mexico
| | | | | |
Collapse
|
5
|
Buckner T, Johnson RK, Vanderlinden LA, Carry PM, Romero A, Onengut-Gumuscu S, Chen WM, Kim S, Fiehn O, Frohnert BI, Crume T, Perng W, Kechris K, Rewers M, Norris JM. Genome-wide analysis of oxylipins and oxylipin profiles in a pediatric population. Front Nutr 2023; 10:1040993. [PMID: 37057071 PMCID: PMC10086335 DOI: 10.3389/fnut.2023.1040993] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 03/14/2023] [Indexed: 03/30/2023] Open
Abstract
Background Oxylipins are inflammatory biomarkers derived from omega-3 and-6 fatty acids implicated in inflammatory diseases but have not been studied in a genome-wide association study (GWAS). The aim of this study was to identify genetic loci associated with oxylipins and oxylipin profiles to identify biologic pathways and therapeutic targets for oxylipins. Methods We conducted a GWAS of plasma oxylipins in 316 participants in the Diabetes Autoimmunity Study in the Young (DAISY). DNA samples were genotyped using the TEDDY-T1D Exome array, and additional variants were imputed using the Trans-Omics for Precision Medicine (TOPMed) multi-ancestry reference panel. Principal components analysis of 36 plasma oxylipins was used to capture oxylipin profiles. PC1 represented linoleic acid (LA)- and alpha-linolenic acid (ALA)-related oxylipins, and PC2 represented arachidonic acid (ARA)-related oxylipins. Oxylipin PC1, PC2, and the top five loading oxylipins from each PC were used as outcomes in the GWAS (genome-wide significance: p < 5×10-8). Results The SNP rs143070873 was associated with (p < 5×10-8) the LA-related oxylipin 9-HODE, and rs6444933 (downstream of CLDN11) was associated with the LA-related oxylipin 13 S-HODE. A locus between MIR1302-7 and LOC100131146, rs10118380 and an intronic variant in TRPM3 were associated with the ARA-related oxylipin 11-HETE. These loci are involved in inflammatory signaling cascades and interact with PLA2, an initial step to oxylipin biosynthesis. Conclusion Genetic loci involved in inflammation and oxylipin metabolism are associated with oxylipin levels.
Collapse
Affiliation(s)
- Teresa Buckner
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
- Department of Kinesiology, Nutrition, and Dietetics, University of Northern Colorado, Greeley, CO, United States
| | - Randi K. Johnson
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
- Department of Biomedical Informatics, CU School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Lauren A. Vanderlinden
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
| | - Patrick M. Carry
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
- Colorado Program for Musculoskeletal Research, Department of Orthopedics, CU School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Alex Romero
- Department of Biomedical Informatics, CU School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Suna Onengut-Gumuscu
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, United States
| | - Wei-Min Chen
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, United States
| | - Soojeong Kim
- Department of Health Administration, Dongseo University, Busan, Republic of Korea
| | - Oliver Fiehn
- NIH-West Coast Metabolomics Center, University of California-Davis, Davis, CA, United States
| | - Brigitte I. Frohnert
- The Barbara Davis Center for Diabetes, CU School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Tessa Crume
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
| | - Wei Perng
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
| | - Katerina Kechris
- Department of Biostatistics and Informatics, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
| | - Marian Rewers
- The Barbara Davis Center for Diabetes, CU School of Medicine, Anschutz Medical Campus, Aurora, CO, United States
| | - Jill M. Norris
- Department of Epidemiology, Colorado School of Public Health, Anschutz Medical Campus, Aurora, CO, United States
| |
Collapse
|
6
|
Wu Y, Bayrak CS, Dong B, He S, Stenson PD, Cooper DN, Itan Y, Chen L. Identifying shared genetic factors underlying epilepsy and congenital heart disease in Europeans. Hum Genet 2023; 142:275-288. [PMID: 36352240 DOI: 10.1007/s00439-022-02502-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 10/24/2022] [Indexed: 11/11/2022]
Abstract
Epilepsy (EP) and congenital heart disease (CHD) are two apparently unrelated diseases that nevertheless display substantial mutual comorbidity. Thus, while congenital heart defects are associated with an elevated risk of developing epilepsy, the incidence of epilepsy in CHD patients correlates with CHD severity. Although genetic determinants have been postulated to underlie the comorbidity of EP and CHD, the precise genetic etiology is unknown. We performed variant and gene association analyses on EP and CHD patients separately, using whole exomes of genetically identified Europeans from the UK Biobank and Mount Sinai BioMe Biobank. We prioritized biologically plausible candidate genes and investigated the enriched pathways and other identified comorbidities by biological proximity calculation, pathway analyses, and gene-level phenome-wide association studies. Our variant- and gene-level results point to the Voltage-Gated Calcium Channels (VGCC) pathway as being a unifying framework for EP and CHD comorbidity. Additionally, pathway-level analyses indicated that the functions of disease-associated genes partially overlap between the two disease entities. Finally, phenome-wide association analyses of prioritized candidate genes revealed that cerebral blood flow and ulcerative colitis constitute the two main traits associated with both EP and CHD.
Collapse
Affiliation(s)
- Yiming Wu
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Cigdem Sevim Bayrak
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bosi Dong
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Shixu He
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China
| | - Peter D Stenson
- Institute of Medical Genetics, Cardiff University, Cardiff, UK
| | - David N Cooper
- Institute of Medical Genetics, Cardiff University, Cardiff, UK
| | - Yuval Itan
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA. .,Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA.
| | - Lei Chen
- Department of Neurology, West China Hospital of Sichuan University, Chengdu, Sichuan, People's Republic of China.
| |
Collapse
|
7
|
Sebastian S, Weinstein LS, Ludwig A, Munroe P, Tinker A. Slowing Heart Rate Protects Against Pathological Cardiac Hypertrophy. FUNCTION 2022; 4:zqac055. [PMID: 36540889 PMCID: PMC9761894 DOI: 10.1093/function/zqac055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 10/27/2022] [Indexed: 12/23/2022] Open
Abstract
We aimed to determine the pathophysiological impact of heart rate (HR) slowing on cardiac function. We have recently developed a murine model in which it is possible to conditionally delete the stimulatory heterotrimeric G-protein (Gαs) in the sinoatrial (SA) node after the addition of tamoxifen using cre-loxP technology. The addition of tamoxifen leads to bradycardia. We used this approach to examine the physiological and pathophysiological effects of HR slowing. We first looked at the impact on exercise performance by running the mice on a treadmill. After the addition of tamoxifen, mice with conditional deletion of Gαs in the SA node ran a shorter distance at a slower speed. Littermate controls preserved their exercise capacity after tamoxifen. Results consistent with impaired cardiac capacity in the mutants were also obtained with a dobutamine echocardiographic stress test. We then examined if HR reduction influenced pathological cardiac hypertrophy using two models: ligation of the left anterior descending coronary artery for myocardial infarction and abdominal aortic banding for hypertensive heart disease. In littermate controls, both procedures resulted in cardiac hypertrophy. However, induction of HR reduction prior to surgical intervention significantly ameliorated the hypertrophy. In order to assess potential protein kinase pathways that may be activated in the left ventricle by relative bradycardia, we used a phospho-antibody array and this revealed selective activation of phosphoinositide-3 kinase. In conclusion, HR reduction protects against pathological cardiac hypertrophy but limits physiological exercise capacity.
Collapse
Affiliation(s)
- Sonia Sebastian
- William Harvey Heart Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | - Lee S Weinstein
- Metabolic Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases/National Institutes of Health, Building 10, Room 8C101, Bethesda, MD 20892-1752, USA
| | - Andreas Ludwig
- Institut fuer Experimentelle und Klinische Pharmakologie und Toxikologie, Universitaet Erlangen-Nuernberg, Fahrstr. 17, 91054 Erlangen, Germany
| | - Patricia Munroe
- William Harvey Heart Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | | |
Collapse
|
8
|
Cárcel-Márquez J, Muiño E, Gallego-Fabrega C, Cullell N, Lledós M, Llucià-Carol L, Sobrino T, Campos F, Castillo J, Freijo M, Arenillas JF, Obach V, Álvarez-Sabín J, Molina CA, Ribó M, Jiménez-Conde J, Roquer J, Muñoz-Narbona L, Lopez-Cancio E, Millán M, Diaz-Navarro R, Vives-Bauza C, Serrano-Heras G, Segura T, Ibañez L, Heitsch L, Delgado P, Dhar R, Krupinski J, Delgado-Mederos R, Prats-Sánchez L, Camps-Renom P, Blay N, Sumoy L, de Cid R, Montaner J, Cruchaga C, Lee JM, Martí-Fàbregas J, Férnandez-Cadenas I. A Polygenic Risk Score Based on a Cardioembolic Stroke Multitrait Analysis Improves a Clinical Prediction Model for This Stroke Subtype. Front Cardiovasc Med 2022; 9:940696. [PMID: 35872910 PMCID: PMC9304625 DOI: 10.3389/fcvm.2022.940696] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Accepted: 06/06/2022] [Indexed: 11/13/2022] Open
Abstract
Background Occult atrial fibrillation (AF) is one of the major causes of embolic stroke of undetermined source (ESUS). Knowing the underlying etiology of an ESUS will reduce stroke recurrence and/or unnecessary use of anticoagulants. Understanding cardioembolic strokes (CES), whose main cause is AF, will provide tools to select patients who would benefit from anticoagulants among those with ESUS or AF. We aimed to discover novel loci associated with CES and create a polygenetic risk score (PRS) for a more efficient CES risk stratification. Methods Multitrait analysis of GWAS (MTAG) was performed with MEGASTROKE-CES cohort (n = 362,661) and AF cohort (n = 1,030,836). We considered significant variants and replicated those variants with MTAG p-value < 5 × 10−8 influencing both traits (GWAS-pairwise) with a p-value < 0.05 in the original GWAS and in an independent cohort (n = 9,105). The PRS was created with PRSice-2 and evaluated in the independent cohort. Results We found and replicated eleven loci associated with CES. Eight were novel loci. Seven of them had been previously associated with AF, namely, CAV1, ESR2, GORAB, IGF1R, NEURL1, WIPF1, and ZEB2. KIAA1755 locus had never been associated with CES/AF, leading its index variant to a missense change (R1045W). The PRS generated has been significantly associated with CES improving discrimination and patient reclassification of a model with age, sex, and hypertension. Conclusion The loci found significantly associated with CES in the MTAG, together with the creation of a PRS that improves the predictive clinical models of CES, might help guide future clinical trials of anticoagulant therapy in patients with ESUS or AF.
Collapse
Affiliation(s)
- Jara Cárcel-Márquez
- Stroke Pharmacogenomics and Genetics Group, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- Departament de Medicina, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Elena Muiño
- Stroke Pharmacogenomics and Genetics Group, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
| | - Cristina Gallego-Fabrega
- Stroke Pharmacogenomics and Genetics Group, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- Stroke Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Natalia Cullell
- Stroke Pharmacogenomics and Genetics Group, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- Stroke Pharmacogenomics and Genetics Laboratory, Fundación Docència i Recerca Mútua Terrassa, Hospital Mútua Terrassa, Terrassa, Spain
| | - Miquel Lledós
- Stroke Pharmacogenomics and Genetics Group, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
| | - Laia Llucià-Carol
- Stroke Pharmacogenomics and Genetics Group, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- Department de Genética i de Microbiologia, Universitat Autónoma de Barcelona, Barcelona, Spain
| | - Tomás Sobrino
- Clinical Neurosciences Research Laboratory, Hospital Clínico Universitario de Santiago de Compostela, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Francisco Campos
- Clinical Neurosciences Research Laboratory, Hospital Clínico Universitario de Santiago de Compostela, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - José Castillo
- Clinical Neurosciences Research Laboratory, Hospital Clínico Universitario de Santiago de Compostela, Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Spain
| | - Marimar Freijo
- Department of Neurology, Biocruces-Bizkaia Health Research Institute, Bilbao, Spain
| | | | - Victor Obach
- Department of Neurology, Hospital Clínic de Barcelona, IDIBAPS, Barcelona, Spain
| | - José Álvarez-Sabín
- Stroke Unit, Department of Neurology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Carlos A. Molina
- Stroke Unit, Department of Neurology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Marc Ribó
- Stroke Unit, Department of Neurology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Jordi Jiménez-Conde
- Department of Neurology, IMIM-Hospital del Mar; Neurovascular Research Group, IMIM (Institut Hospital del Mar d'Investigacions Mèdiques), Universitat Autònoma de Barcelona/DCEXS-Universitat Pompeu Fabra, Barcelona, Spain
| | - Jaume Roquer
- Department of Neurology, IMIM-Hospital del Mar; Neurovascular Research Group, IMIM (Institut Hospital del Mar d'Investigacions Mèdiques), Universitat Autònoma de Barcelona/DCEXS-Universitat Pompeu Fabra, Barcelona, Spain
| | - Lucia Muñoz-Narbona
- Department of Neurosciences, Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Elena Lopez-Cancio
- Department of Neurology, University Hospital Central de Asturias (HUCA).Oviedo, Spain
| | - Mònica Millán
- Department of Neurosciences, Hospital Germans Trias i Pujol, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Rosa Diaz-Navarro
- Department of Neurology, Son Espases University Hospital, Illes Balears Health Research Institute (IdISBa), Palma, Spain
| | - Cristòfol Vives-Bauza
- Department of Neurology, Son Espases University Hospital, Illes Balears Health Research Institute (IdISBa), Palma, Spain
| | | | - Tomás Segura
- Department of Neurology, University Hospital of Albacete, Albacete, Spain
| | - Laura Ibañez
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, United States
| | - Laura Heitsch
- Department of Emergency Medicine, Washington University School of Medicine, Saint Louis, MO, United States
- Department of Neurology, Washington University School of Medicine, Saint Louis, MO, United States
| | - Pilar Delgado
- Neurovascular Research Laboratory, Vall d'Hebron Institute of Research, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Rajat Dhar
- Department of Neurology, Washington University School of Medicine, Saint Louis, MO, United States
| | - Jerzy Krupinski
- Neurology Service, Hospital Universitari Mútua Terrassa, Terrassa, Spain
| | - Raquel Delgado-Mederos
- Stroke Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Luis Prats-Sánchez
- Stroke Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Pol Camps-Renom
- Stroke Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Natalia Blay
- GenomesForLife-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Lauro Sumoy
- High Content Genomics and Bioinformatics Unit, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Rafael de Cid
- GenomesForLife-GCAT Lab, Germans Trias i Pujol Research Institute (IGTP), Badalona, Spain
| | - Joan Montaner
- Institute de Biomedicine of Seville, IBiS/Hospital Universitario Virgen del Rocío/CSIC/University of Seville and Department of Neurology, Hospital Universitario Virgen Macarena, Seville, Spain
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, United States
- Neurogenomics and Informatics Center at Washington University in St. Louis, Saint Louis, MO, United States
| | - Jin-Moo Lee
- Department of Neurology, Washington University School of Medicine, Saint Louis, MO, United States
| | - Joan Martí-Fàbregas
- Stroke Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Israel Férnandez-Cadenas
- Stroke Pharmacogenomics and Genetics Group, Institut d'Investigació Biomèdica Sant Pau (IIB SANT PAU), Barcelona, Spain
- *Correspondence: Israel Férnandez-Cadenas
| |
Collapse
|
9
|
Gonzalez DM, Schrode N, Ebrahim TAM, Broguiere N, Rossi G, Drakhlis L, Zweigerdt R, Lutolf MP, Beaumont KG, Sebra R, Dubois NC. Dissecting mechanisms of chamber-specific cardiac differentiation and its perturbation following retinoic acid exposure. Development 2022; 149:275658. [DOI: 10.1242/dev.200557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/26/2022] [Indexed: 11/20/2022]
Abstract
ABSTRACT
The specification of distinct cardiac lineages occurs before chamber formation and acquisition of bona fide atrial or ventricular identity. However, the mechanisms underlying these early specification events remain poorly understood. Here, we performed single cell analysis at the murine cardiac crescent, primitive heart tube and heart tube stages to uncover the transcriptional mechanisms underlying formation of atrial and ventricular cells. We find that progression towards differentiated cardiomyocytes occurs primarily based on heart field progenitor identity, and that progenitors contribute to ventricular or atrial identity through distinct differentiation mechanisms. We identify new candidate markers that define such differentiation processes and examine their expression dynamics using computational lineage trajectory methods. We further show that exposure to exogenous retinoic acid causes defects in ventricular chamber size, dysregulation in FGF signaling and a shunt in differentiation towards orthogonal lineages. Retinoic acid also causes defects in cell-cycle exit resulting in formation of hypomorphic ventricles. Collectively, our data identify, at a single cell level, distinct lineage trajectories during cardiac specification and differentiation, and the precise effects of manipulating cardiac progenitor patterning via retinoic acid signaling.
Collapse
Affiliation(s)
- David M. Gonzalez
- Icahn School of Medicine at Mount Sinai 1 Department of Cell, Developmental, and Regenerative Biology , , New York, NY 10029 , USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai 2 , New York, NY 10029 , USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai 3 , New York, NY 10029 , USA
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai 4 , New York, NY 10029 , USA
| | - Nadine Schrode
- Icahn School of Medicine at Mount Sinai 5 Department of Genetics and Genomic Sciences , , New York, NY 10029 , USA
| | - Tasneem A. M. Ebrahim
- Icahn School of Medicine at Mount Sinai 1 Department of Cell, Developmental, and Regenerative Biology , , New York, NY 10029 , USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai 2 , New York, NY 10029 , USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai 3 , New York, NY 10029 , USA
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai 4 , New York, NY 10029 , USA
| | - Nicolas Broguiere
- School of Life Sciences, EPFL 6 Laboratory of Stem Cell Bioengineering , , Lausanne CH-1015 , Switzerland
| | - Giuliana Rossi
- School of Life Sciences, EPFL 6 Laboratory of Stem Cell Bioengineering , , Lausanne CH-1015 , Switzerland
| | - Lika Drakhlis
- Roche Institute for Translational Bioengineering 7 , Roche Pharma Research and Early Development , Basel 4052 , Switzerland
| | - Robert Zweigerdt
- Roche Institute for Translational Bioengineering 7 , Roche Pharma Research and Early Development , Basel 4052 , Switzerland
| | - Matthias P. Lutolf
- School of Life Sciences, EPFL 6 Laboratory of Stem Cell Bioengineering , , Lausanne CH-1015 , Switzerland
- Roche Institute for Translational Bioengineering 7 , Roche Pharma Research and Early Development , Basel 4052 , Switzerland
| | - Kristin G. Beaumont
- Icahn School of Medicine at Mount Sinai 5 Department of Genetics and Genomic Sciences , , New York, NY 10029 , USA
- Leibniz Research Laboratories for Biotechnology and Artificial Organs (LEBAO) 8 , Department of Cardiothoracic, Transplantation and Vascular Surgery (HTTG) , , Hannover , Germany
- REBIRTH–Research Center for Translational Regenerative Medicine, Hannover Medical School 8 , Department of Cardiothoracic, Transplantation and Vascular Surgery (HTTG) , , Hannover , Germany
| | - Robert Sebra
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai 3 , New York, NY 10029 , USA
- Icahn School of Medicine at Mount Sinai 5 Department of Genetics and Genomic Sciences , , New York, NY 10029 , USA
- Sema4, a Mount Sinai venture 9 , Stamford, CT 06902 , USA
| | - Nicole C. Dubois
- Icahn School of Medicine at Mount Sinai 1 Department of Cell, Developmental, and Regenerative Biology , , New York, NY 10029 , USA
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai 2 , New York, NY 10029 , USA
- Black Family Stem Cell Institute, Icahn School of Medicine at Mount Sinai 3 , New York, NY 10029 , USA
- Cardiovascular Research Institute, Icahn School of Medicine at Mount Sinai 4 , New York, NY 10029 , USA
| |
Collapse
|
10
|
Pharmacological Mechanisms of Tinglizi against Chronic Heart Failure Determined by Network Pharmacology and Molecular Docking. EVIDENCE-BASED COMPLEMENTARY AND ALTERNATIVE MEDICINE 2022; 2022:2152399. [PMID: 35035498 PMCID: PMC8758258 DOI: 10.1155/2022/2152399] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 11/30/2021] [Indexed: 11/18/2022]
Abstract
Objective. Tinglizi has been extensively used to treat chronic heart failure (CHF) in modern times, but the material basis and pharmacological mechanisms are still unclear. To explore the material basis and corresponding potential targets and to elucidate the mechanism of Tinglizi, network pharmacology and molecular docking methods were utilized. Methods. The main chemical compounds and potential targets of Tinglizi were collected from the pharmacological database analysis platform (TCMSP). The corresponding genes of related action targets were queried through gene cards and UniProt database. The corresponding genes of CHF-related targets were searched through Disgenet database, and the intersection targets were obtained by drawing Venn map with the target genes related to pharmacodynamic components. Then, drug targets and disease targets were intersected and put into STRING database to establish a protein interaction network. The “active ingredient-CHF target” network was constructed with Cytoscape 3.8.2. Finally, Gene Ontology (GO) Enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of intersection targets were analyzed using metascape. With the aid of SYBYL software, the key active ingredients and core targets were docked at molecular level, and the results were visualized by PyMOL software. Molecular docking was carried out to investigate interactions between active compounds and potential targets. Results. A total of 12 active components in Tinglizi were chosen from the TCMSP database, and 193 corresponding targets were predicted. Twenty-nine potential targets of Tinglizi on CHF were obtained, of which nine were the core targets of this study. Twenty GO items were obtained by GO function enrichment analysis (
), and 10 signal pathways were screened by KEGG pathway enrichment analysis (
), which is closely related to the treatment of CHF by Tinglizi. The constructed drug compound composition action target disease network shows that quercetin, kaempferol, and other active compounds play a key role in the whole network. The results of molecular docking showed that all the key active ingredients, such as quercetin and isorhamnetin, were able to successfully dock with ADRB2 and HMOX1 with a total score above 5.0, suggesting that these key components have a strong binding force with the targets. Conclusion. Through network pharmacology and molecular docking technology, we found that the main components of Tinglizi in the treatment of CHF are quercetin, kaempferol, β-sitosterol, isorhamnetin, and so on. The action targets are beta 2-adrenergic receptor (ADRB2), heme oxygenase 1 (HMOX1), and so on. The main pathways are advanced glycation end products/receptor for advanced glycation end products (AGE-RAGE) signaling pathway in diabetic complications, hypoxia-inducible factor (HIF-1) signaling pathway, estrogen signaling pathway, and so on. They play an integrated role in the treatment of CHF.
Collapse
|
11
|
Xhaard C, Dandine-Roulland C, Villemereuil PD, Floch EL, Bacq-Daian D, Machu JL, Ferreira JP, Deleuze JF, Zannad F, Rossignol P, Girerd N. Heritability of a resting heart rate in a 20-year follow-up family cohort with GWAS data: Insights from the STANISLAS cohort. Eur J Prev Cardiol 2021; 28:1334-1341. [PMID: 34647585 DOI: 10.1177/2047487319890763] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Accepted: 11/05/2019] [Indexed: 11/17/2022]
Abstract
BACKGROUND The association between resting heart rate (HR) and cardiovascular outcomes, especially heart failure, is now well established. However, whether HR is mainly an integrated marker of risk associated with other features, or rather a genetic origin risk marker, is still a matter for debate. Previous studies reported a heritability ranging from 14% to 65%. DESIGN We assessed HR heritability in the STANISLAS family-study, based on the data of four visits performed over a 20-year period, and adjusted for most known confounding effects. METHODS These analyses were conducted using a linear mixed model, adjusted on age, sex, tea or coffee consumption, beta-blocker use, physical activity, tobacco use, and alcohol consumption to estimate the variance captured by additive genetic effects, via average information restricted maximum likelihood analysis, with both self-reported pedigree and genetic relatedness matrix (GRM) calculated from genome-wide association study data. RESULTS Based on the data of all visits, the HR heritability (h2) estimate was 23.2% with GRM and 24.5% with pedigree. However, we found a large heterogeneity of HR heritability estimations when restricting the analysis to each of the four visits (h2 from 19% to 39% using pedigree, and from 14% to 32% using GRM). Moreover, only a little part of variance was explained by the common household effect (<5%), and half of the variance remained unexplained. CONCLUSION Using a comprehensive analysis based on a family cohort, including the data of multiple visits and GRM, we found that HR variability is about 25% from genetic origin, 25% from repeated measures and 50% remains unexplained.
Collapse
Affiliation(s)
- Constance Xhaard
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| | - Claire Dandine-Roulland
- Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Pierre de Villemereuil
- CEFE, CNRS, Université de Montpellier, Université Paul Valéry Montpellier 3, EPHE, IRD, Montpellier, France
| | - Edith Le Floch
- Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Delphine Bacq-Daian
- Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Jean-Loup Machu
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| | - Joao Pedro Ferreira
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| | - Jean-François Deleuze
- Centre National de Recherche en Génomique Humaine (CNRGH), Institut de Biologie François Jacob, CEA, Université Paris-Saclay, Evry, France
| | - Faiez Zannad
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| | - Patrick Rossignol
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| | - Nicolas Girerd
- INSERM Centre d'Investigation Clinique CIC-P 1433, CHRU Nancy, INSERM U1116, FCRIN INI-CRCT, Lorraine Université, Nancy, France
| |
Collapse
|
12
|
Mkaouar R, Abdallah LCB, Naouali C, Lahbib S, Turki Z, Elouej S, Bouyacoub Y, Somai M, Mcelreavey K, Bashamboo A, Abdelhak S, Messaoud O. Oligogenic Inheritance Underlying Incomplete Penetrance of PROKR2 Mutations in Hypogonadotropic Hypogonadism. Front Genet 2021; 12:665174. [PMID: 34539727 PMCID: PMC8446458 DOI: 10.3389/fgene.2021.665174] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2021] [Accepted: 07/05/2021] [Indexed: 11/17/2022] Open
Abstract
The role of the prokineticin 2 pathway in human reproduction, olfactory bulb morphogenesis, and gonadotropin-releasing hormone secretion is well established. Recent studies have highlighted the implication of di/oligogenic inheritance in this disorder. In the present study, we aimed to identify the genetic mechanisms that could explain incomplete penetrance in hypogonadotropic hypogonadism (HH). This study involved two unrelated Tunisian patients with HH, which was triggered by identifying a homozygous p.(Pro290Ser) mutation in the PROKR2 gene in a girl (HH1) with Kallmann syndrome (KS). The functional effect of this variant has previously been well demonstrated. Unexpectedly, her unaffected father (HH1P) and brother (HH1F) also carried this genetic variation at a homozygous state. In the second family, we identified a heterozygous p.(Lys205del) mutation in PROKR2, both in a male patient with normosmic idiopathic IHH (HH12) and his asymptomatic mother. Whole-exome sequencing in the three HH1 family members allowed the identification of additional variants in the prioritized genes. We then carried out digenic combination predictions using the oligogenic resource for variant analysis (ORVAL) software. For HH1, we found the highest number of disease-causing variant pairs. Notably, a CCDC141 variant (c.2803C > T) was involved in 18 pathogenic digenic combinations. The CCDC141 variant acts in an autosomal recessive inheritance mode, based on the digenic effect prediction data. For the second patient (HH12), prediction by ORVAL allowed the identification of an interesting pathogenic digenic combination between DUSP6 and SEMA7A genes, predicted as “dual molecular diagnosis.” The SEMA7A variant p.(Glu436Lys) is novel and predicted as a VUS by Varsome. Sanger validation revealed the absence of this variant in the healthy mother. We hypothesize that disease expression in HH12 could be induced by the digenic transmission of the SEMA7A and DUSP6 variants or a monogenic inheritance involving only the SEMA7A VUS if further functional assays allow its reclassification into pathogenic. Our findings confirm that homozygous loss-of-function genetic variations are insufficient to cause KS, and that oligogenism is most likely the main transmission mode involved in Congenital Hypogonadotropic Hypogonadism.
Collapse
Affiliation(s)
- Rahma Mkaouar
- Laboratoire de Génomique Biomédicale et Oncogénétique, Institut Pasteur de Tunis, Tunis, Tunisia.,Faculté des Sciences Mathématiques, Physiques et Naturelles de Tunis, Université de Tunis El Manar, Tunis, Tunisia
| | | | - Chokri Naouali
- Laboratoire de Génomique Biomédicale et Oncogénétique, Institut Pasteur de Tunis, Tunis, Tunisia
| | - Saida Lahbib
- Laboratoire de Génomique Biomédicale et Oncogénétique, Institut Pasteur de Tunis, Tunis, Tunisia
| | - Zinet Turki
- Département d'Endocrinologie et de Technologie Alimentaire, Institut de Nutrition, Tunis, Tunisia
| | - Sahar Elouej
- Laboratoire de Génomique Biomédicale et Oncogénétique, Institut Pasteur de Tunis, Tunis, Tunisia
| | - Yosra Bouyacoub
- Laboratoire de Génomique Biomédicale et Oncogénétique, Institut Pasteur de Tunis, Tunis, Tunisia
| | - Maali Somai
- Département d'Endocrinologie et de Technologie Alimentaire, Institut de Nutrition, Tunis, Tunisia
| | | | - Anu Bashamboo
- Génétique du Développement Humain, Institut Pasteur, Paris, France
| | - Sonia Abdelhak
- Laboratoire de Génomique Biomédicale et Oncogénétique, Institut Pasteur de Tunis, Tunis, Tunisia
| | - Olfa Messaoud
- Laboratoire de Génomique Biomédicale et Oncogénétique, Institut Pasteur de Tunis, Tunis, Tunisia
| |
Collapse
|
13
|
Zhou J, Chen C, Liu S, Zhou W, Du J, Jiang Y, Dai J, Jin G, Ma H, Hu Z, Chen J, Shen H. Potential functional variants of KIAA genes are associated with breast cancer risk in a case control study. ANNALS OF TRANSLATIONAL MEDICINE 2021; 9:549. [PMID: 33987247 DOI: 10.21037/atm-20-6108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Background KIAA genes identified in the Kazusa cDNA-sequencing project may play important roles in biological processes and are involved in carcinogenesis of many cancers. Genetic variants of KIAA genes are implicated in the abnormal expression of these genes and are linked to susceptibility of several human complex diseases. Methods The differentially expressed KIAA genes were screened and identified in The Cancer Genome Atlas (TCGA) database of breast cancer. A total of 48 variants located in the 28 KIAA genes were selected to investigate the associations between polymorphism and breast cancer in 1,032 cases and 1,063 cancer-free controls in a Chinese population. Results Two coding variants, which included a SNP rs2306369 in KIAA1109 and a SNP rs1205434 in KIAA1755, were identified to be associated with the incidences of breast cancer. Logistic regression analysis showed that the SNP rs2306369 G allele was associated with a decreased risk of breast cancer (additive model: OR =0.81, 95% CI: 0.66-0.99, P=0.038), whereas the SNP rs1205434 A allele was involved with a higher risk of breast cancer (additive model: OR =1.19, 95% CI: 1.02-1.38, P= 0.025). Further stratified analysis revealed that the SNP rs1205434 showed a significant difference for age at menarche strata (heterogeneity test P=0.009). Multiplicative interaction analysis indicated that there was positive multiplicative interaction between the SNP rs1205434 and menarche age (OR =1.09, 95% CI: 1.01-1.17, P=0.036). Additionally, expression quantitative trait loci analysis revealed that the SNP rs1205434 A allele could decrease the KIAA1755 expression in the Genotype-Tissue Expression (GTEx) database (P=0.002). The Kaplan-Meier plotter showed that breast cancer patients with high KIAA1755 expression have significantly better outcomes than those with low levels of expression (HR =0.84, 95% CI: 0.72-0.99, P=0.033). Conclusions The results indicate that the genetic variants (rs2306369 and rs1205434) in the coding region of KIAA1109 and KIAA1755 respectively may affect Chinese females' breast cancer susceptibility and act as potential predictive biomarkers for breast cancer.
Collapse
Affiliation(s)
- Jing Zhou
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Statistical Center, Information Department, Northern Jiangsu People's Hospital and Clinical Medical College of Yangzhou University, Yangzhou, China
| | - Congcong Chen
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Sijun Liu
- Department of Social Medicine and Health Education, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Wen Zhou
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Jiangbo Du
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Yue Jiang
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Juncheng Dai
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Guangfu Jin
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Hongxia Ma
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Zhibin Hu
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| | - Jiaping Chen
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Hongbing Shen
- Department of Epidemiology, International Joint Research Center on Environment and Human Health, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Medicine, Nanjing Medical University, Nanjing, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing, China
| |
Collapse
|
14
|
Sebastian S, Nobles M, Tsisanova E, Ludwig A, Munroe PB, Tinker A. The role of resistance to inhibitors of cholinesterase 8b in the control of heart rate. Physiol Genomics 2021; 53:150-159. [PMID: 33719582 DOI: 10.1152/physiolgenomics.00157.2020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
We have assessed the role of ric-b8 in the control of heart rate after the gene was implicated in a recent genome-wide association study of resting heart rate. We developed a novel murine model in which it was possible to conditionally delete ric-8b in the sinoatrial (SA) node after the addition of tamoxifen. Despite this, we were unable to obtain homozygotes and thus studied heterozygotes. Haploinsufficiency of ric-8b in the sinoatrial node induced by the addition of tamoxifen in adult animals leads to mice with a reduced heart rate. However, other electrocardiographic intervals (e.g., PR and QRS) were normal, and there was no apparent arrhythmia such as heart block. The positive chronotropic response to isoprenaline was abrogated, whereas the response to carbachol was unchanged. The pacemaker current If (funny current) has an important role in regulating heart rate, and its function is modulated by both isoprenaline and carbachol. Using a heterologous system expressing HCN4, we show that ric-8b can modulate the HCN4 current. Overexpression of ric-8b led to larger HCN4 currents, whereas silencing ric-8b led to smaller currents. Ric-8b modulates heart rate responses in vivo likely via its actions on the stimulatory G-protein.
Collapse
Affiliation(s)
- Sonia Sebastian
- Centre for Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Muriel Nobles
- Centre for Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Elena Tsisanova
- Centre for Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Andreas Ludwig
- Institut für Experimentelle und Klinische Pharmakologie und Toxikologie, Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Patricia B Munroe
- Centre for Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| | - Andrew Tinker
- Centre for Clinical Pharmacology, William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom
| |
Collapse
|
15
|
Erzurumluoglu AM, Liu M, Jackson VE, Barnes DR, Datta G, Melbourne CA, Young R, Batini C, Surendran P, Jiang T, Adnan SD, Afaq S, Agrawal A, Altmaier E, Antoniou AC, Asselbergs FW, Baumbach C, Bierut L, Bertelsen S, Boehnke M, Bots ML, Brazel DM, Chambers JC, Chang-Claude J, Chen C, Corley J, Chou YL, David SP, de Boer RA, de Leeuw CA, Dennis JG, Dominiczak AF, Dunning AM, Easton DF, Eaton C, Elliott P, Evangelou E, Faul JD, Foroud T, Goate A, Gong J, Grabe HJ, Haessler J, Haiman C, Hallmans G, Hammerschlag AR, Harris SE, Hattersley A, Heath A, Hsu C, Iacono WG, Kanoni S, Kapoor M, Kaprio J, Kardia SL, Karpe F, Kontto J, Kooner JS, Kooperberg C, Kuulasmaa K, Laakso M, Lai D, Langenberg C, Le N, Lettre G, Loukola A, Luan J, Madden PAF, Mangino M, Marioni RE, Marouli E, Marten J, Martin NG, McGue M, Michailidou K, Mihailov E, Moayyeri A, Moitry M, Müller-Nurasyid M, Naheed A, Nauck M, Neville MJ, Nielsen SF, North K, Perola M, Pharoah PDP, Pistis G, Polderman TJ, Posthuma D, Poulter N, Qaiser B, Rasheed A, Reiner A, Renström F, Rice J, Rohde R, Rolandsson O, Samani NJ, Samuel M, Schlessinger D, Scholte SH, Scott RA, Sever P, Shao Y, Shrine N, Smith JA, Starr JM, Stirrups K, Stram D, Stringham HM, Tachmazidou I, Tardif JC, Thompson DJ, Tindle HA, Tragante V, Trompet S, Turcot V, Tyrrell J, Vaartjes I, van der Leij AR, van der Meer P, Varga TV, Verweij N, Völzke H, Wareham NJ, Warren HR, Weir DR, Weiss S, Wetherill L, Yaghootkar H, Yavas E, Jiang Y, Chen F, Zhan X, Zhang W, Zhao W, Zhao W, Zhou K, Amouyel P, Blankenberg S, Caulfield MJ, Chowdhury R, Cucca F, Deary IJ, Deloukas P, Di Angelantonio E, Ferrario M, Ferrières J, Franks PW, Frayling TM, Frossard P, Hall IP, Hayward C, Jansson JH, Jukema JW, Kee F, Männistö S, Metspalu A, Munroe PB, Nordestgaard BG, Palmer CNA, Salomaa V, Sattar N, Spector T, Strachan DP, van der Harst P, Zeggini E, Saleheen D, Butterworth AS, Wain LV, Abecasis GR, Danesh J, Tobin MD, Vrieze S, Liu DJ, Howson JMM. Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci. Mol Psychiatry 2020; 25:2392-2409. [PMID: 30617275 PMCID: PMC7515840 DOI: 10.1038/s41380-018-0313-0] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Revised: 09/30/2018] [Accepted: 11/14/2018] [Indexed: 02/02/2023]
Abstract
Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations with P < 5 × 10-8 in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P < 5 × 10-8) in the discovery samples. Ten novel SNVs, including rs12616219 near TMEM182, were followed-up and five of them (rs462779 in REV3L, rs12780116 in CNNM2, rs1190736 in GPR101, rs11539157 in PJA1, and rs12616219 near TMEM182) replicated at a Bonferroni significance threshold (P < 4.5 × 10-3) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, in CCDC141 and two low-frequency SNVs in CEP350 and HDGFRP2. Functional follow-up implied that decreased expression of REV3L may lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.
Collapse
Affiliation(s)
| | - Mengzhen Liu
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Victoria E Jackson
- Department of Health Sciences, University of Leicester, Leicester, UK
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, 1G Royal Pde, 3052, Parkville, Australia
- Department of Medical Biology, University of Melbourne, Melbourne, 3010, Parkville, Australia
| | - Daniel R Barnes
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Gargi Datta
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
| | - Carl A Melbourne
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Robin Young
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Chiara Batini
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Praveen Surendran
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Tao Jiang
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Sheikh Daud Adnan
- National Institute of Cardiovascular Diseases, Sher-e-Bangla Nagar, Dhaka, Bangladesh
| | - Saima Afaq
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
| | - Arpana Agrawal
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Elisabeth Altmaier
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, University of Utrecht, Utrecht, The Netherlands
- Durrer Center for Cardiovascular Research, Netherlands Heart Institute, Utrecht, The Netherlands
- Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, UK
- Farr Institute of Health Informatics Research and Institute of Health Informatics, University College London, London, UK
| | - Clemens Baumbach
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany
| | - Laura Bierut
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Sarah Bertelsen
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Michiel L Bots
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508GA, Utrecht, The Netherlands
- Center for Circulatory Health, University Medical Center Utrecht, 3508GA, Utrecht, The Netherlands
| | - David M Brazel
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Department of Molecular, Cellular, and Developmental Biology, University of Colorado Boulder, Boulder, CO, USA
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, 308232, Singapore
- Department of Cardiology, Ealing Hospital, Middlesex, UB1 3HW, UK
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Centre (DKFZ), Heidelberg, Germany
- Cancer Epidemiology Group, University Medical Centre Hamburg-Eppendorf, University Cancer Centre Hamburg (UCCH), Hamburg, Germany
| | - Chu Chen
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Janie Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Yi-Ling Chou
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Sean P David
- Department of Medicine, Stanford University, Stanford, CA, USA
| | - Rudolf A de Boer
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Christiaan A de Leeuw
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Joe G Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Anna F Dominiczak
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, Cambridge Centre, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, Cambridge Centre, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Charles Eaton
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
- National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare NHS Trust and Imperial College London, London, UK
- UK Dementia Research Institute (UK DRI) at Imperial College London, London, UK
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, 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
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Alison Goate
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jian Gong
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Jeff Haessler
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Christopher Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
| | - Göran Hallmans
- Department of Public Health and Clinical Medicine, Nutritional research, Umeå University, Umeå, Sweden
| | - Anke R Hammerschlag
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Andrew Hattersley
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Andrew Heath
- Department of Psychiatry, Washington University, St. Louis, MO, USA
| | - Chris Hsu
- University of Southern California, California, CA, USA
| | - William G Iacono
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Stavroula Kanoni
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Centre for Genomic Health, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Manav Kapoor
- Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Sharon L Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Fredrik Karpe
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Oxford National Institute for Health Research, Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Jukka Kontto
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271, Helsinki, Finland
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, Middlesex, UB1 3HW, UK
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
| | - Charles Kooperberg
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Department of Biostatistics, University of Washington School of Medicine, Seattle, WA, USA
| | - Kari Kuulasmaa
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271, Helsinki, Finland
| | | | - Dongbing Lai
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Nhung Le
- Department of Medical Microbiology, Immunology and Cell Biology, Southern Illinois University School of Medicine, Springfield, IL, USA
| | - Guillaume Lettre
- Montreal Heart Institute, Montreal, Quebec, H1T 1C8, Canada
- Department of Medicine, Faculty of Medicine, Universite de Montreal, Montreal, Quebec, H3T 1J4, Canada
| | - Anu Loukola
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | | | - Massimo Mangino
- NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London, SE1 9RT, UK
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH, UK
| | - Riccardo E Marioni
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Centre for Genomic Health, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Jonathan Marten
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | | | - Matt McGue
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, 1683, Nicosia, Cyprus
| | | | - Alireza Moayyeri
- Institute of Health Informatics, University College London, London, UK
| | - Marie Moitry
- Department of Epidemiology and Public health, University Hospital of Strasbourg, Strasbourg, France
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Department of Medicine I, Ludwig-Maximilians-University Munich, Munich, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
| | - Aliya Naheed
- Initiative for Noncommunicable Diseases, Health Systems and Population Studies Division, International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b) International Centre for Diarrhoeal Disease Research, Dhaka, Bangladesh
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
| | - Matthew J Neville
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Oxford National Institute for Health Research, Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Sune Fallgaard Nielsen
- Department of Clinical Biochemistry Herlev Hospital, Copenhagen University Hospital, Herlev Ringvej 74, DK-2730, Herlev, Denmark
| | - Kari North
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Markus Perola
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271, Helsinki, Finland
| | - Paul D P Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- Centre for Cancer Genetic Epidemiology, Department of Oncology, Cambridge Centre, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Giorgio Pistis
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Cagliari, Italy
| | - Tinca J Polderman
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, Netherlands
- Department of Clinical Genetics, VU University Medical Centre Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Neil Poulter
- International Centre for Circulatory Health, Imperial College London, London, UK
| | - Beenish Qaiser
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
| | - Asif Rasheed
- Centre for Non-Communicable Diseases, Karachi, Pakistan
| | - Alex Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Frida Renström
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Skåne University Hospital, Lund University, SE-214 28, Malmö, Sweden
- Department of Biobank Research, Umeå University, SE-901 87, Umeå, Sweden
| | - John Rice
- Departments of Psychiatry and Mathematics, Washington University St. Louis, St. Louis, MO, USA
| | | | - Olov Rolandsson
- Department of Public Health & Clinical Medicine, Section for Family Medicine, Umeå universitet, SE, 90185, Umeå, Sweden
| | - Nilesh J Samani
- Department of Cardiovascular Sciences, University of Leicester, Cardiovascular Research Centre, Glenfield Hospital, Leicester, LE3 9QP, UK
| | - Maria Samuel
- Centre for Non-Communicable Diseases, Karachi, Pakistan
| | - David Schlessinger
- National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Steven H Scholte
- Department of Psychology, University of Amsterdam & Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Robert A Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Peter Sever
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
- International Centre for Circulatory Health, Imperial College London, London, UK
| | - Yaming Shao
- University of North Carolina, Chapel Hill, NC, USA
| | - Nick Shrine
- Department of Health Sciences, University of Leicester, Leicester, UK
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Alzheimer Scotland Research Centre, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Kathleen Stirrups
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Department of Haematology, University of Cambridge, Cambridge, CB2 0PT, UK
| | - Danielle Stram
- Department of Preventative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | | | - Jean-Claude Tardif
- Montreal Heart Institute, Montreal, Quebec, H1T 1C8, Canada
- Department of Medicine, Faculty of Medicine, Universite de Montreal, Montreal, Quebec, H3T 1J4, Canada
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Hilary A Tindle
- Department of Medicine, Vanderbilt University, Nashville, TN, USA
| | - Vinicius Tragante
- Department of Cardiology, Division Heart and Lungs, University Medical Center Utrecht, Utrecht University, 3508GA, Utrecht, The Netherlands
| | - Stella Trompet
- Department of gerontology and geriatrics, Leiden University Medical Center, Leiden, The Netherlands
- Department of cardiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Valerie Turcot
- Montreal Heart Institute, Montreal, Quebec, H1T 1C8, Canada
| | - Jessica Tyrrell
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Ilonca Vaartjes
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, 3508GA, Utrecht, The Netherlands
- Center for Circulatory Health, University Medical Center Utrecht, 3508GA, Utrecht, The Netherlands
| | - Andries R van der Leij
- Department of Psychology, University of Amsterdam & Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, Netherlands
| | - Peter van der Meer
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Tibor V Varga
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Skåne University Hospital, Lund University, SE-214 28, Malmö, Sweden
| | - Niek Verweij
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, 301 Binney Street, Cambridge, MA, 02142, USA
| | - Henry Völzke
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
| | - Helen R Warren
- Clinical Pharmacology, William Harvey Research Institute, 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
| | - David R Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Stefan Weiss
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, University Medicine, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine and Ernst-Moritz-Arndt-University Greifswald, 17475, Greifswald, Germany
| | - Leah Wetherill
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Ersin Yavas
- Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
- Department of Biomedical Engineering, The Pennsylvania State University, University Park, Pennsylvania, PA, 16802, USA
| | - Yu Jiang
- Institute of Personalized Medicine, Penn State College of Medicine, Hershey, PA, USA
| | - Fang Chen
- Institute of Personalized Medicine, Penn State College of Medicine, Hershey, PA, USA
| | - Xiaowei Zhan
- Department of Clinical Science, Center for Genetics of Host Defense, University of Texas Southwestern, Dallas, TX, USA
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UB1 3HW, UK
| | - Wei Zhao
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Pennsylvania, PA, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Kaixin Zhou
- School of Medicine, University of Dundee, Dundee, UK
| | - Philippe Amouyel
- Department of Epidemiology and Public Health, Institut Pasteur de Lille, Lille, France
| | - Stefan Blankenberg
- Department of General and Interventional Cardiology, University Heart Center Hamburg, Hamburg, Germany
- University Medical Center Hamburg Eppendorf, Hamburg, Germany
| | - Mark J Caulfield
- Clinical Pharmacology, William Harvey Research Institute, 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
| | - Rajiv Chowdhury
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Francesco Cucca
- Istituto di Ricerca Genetica e Biomedica, Consiglio Nazionale delle Ricerche (CNR), Monserrato, Cagliari, Italy
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah, 21589, Saudi Arabia
| | - Emanuele Di Angelantonio
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Marco Ferrario
- EPIMED Research Centre, Department of Medicine and Surgery, University of Insubria at Varese, Varese, Italy
| | - Jean Ferrières
- Department of Epidemiology, UMR 1027- INSERM, Toulouse University-CHU Toulouse, Toulouse, France
| | - Paul W Franks
- Genetic and Molecular Epidemiology Unit, Lund University Diabetes Centre, Department of Clinical Sciences, Skåne University Hospital, Lund University, SE-214 28, Malmö, Sweden
- Department of Nutrition, Harvard T. H. Chan School of Public Health, Boston, MA, 02115, USA
| | - Tim M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | | | - Ian P Hall
- Division of Respiratory Medicine and NIHR Nottingham Biomedical Research Centre, University of Nottingham, Nottingham, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jan-Håkan Jansson
- Department of Public Health and Clinical Medicine, Skellefteå Research Unit, Umeå University, Umeå, Sweden
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- The Interuniversity Cardiology Institute of the Netherlands, Utrecht, The Netherlands
| | - Frank Kee
- UKCRC Centre of Excellence for Public Health, Queens, University, Belfast, Belfast, UK
| | - Satu Männistö
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271, Helsinki, Finland
| | | | - Patricia B Munroe
- Clinical Pharmacology, William Harvey Research Institute, 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
| | - Børge Grønne Nordestgaard
- Department of Clinical Biochemistry Herlev Hospital, Copenhagen University Hospital, Herlev Ringvej 74, DK-2730, Herlev, Denmark
| | - Colin N A Palmer
- Medical Research Institute, University of Dundee, Ninewells Hospital and Medical School, Dundee, UK
| | - Veikko Salomaa
- Department of Public Health Solutions, National Institute for Health and Welfare, FI-00271, Helsinki, Finland
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Timothy Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH, UK
| | - David Peter Strachan
- Population Health Research Institute, St George!s, University of London, London, SW17 0RE, UK
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | | | - Danish Saleheen
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, USA
- Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Adam S Butterworth
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Louise V Wain
- Department of Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Goncalo R Abecasis
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - John Danesh
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
- Wellcome Trust Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK
- National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, Leicester, UK
- National Institute for Health Research Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Scott Vrieze
- Department of Psychology, University of Minnesota, Minneapolis, MN, USA
| | - Dajiang J Liu
- Institute of Personalized Medicine, Penn State College of Medicine, Hershey, PA, USA.
| | - Joanna M M Howson
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, CB1 8RN, UK.
| |
Collapse
|
16
|
Verweij N, Benjamins JW, Morley MP, van de Vegte YJ, Teumer A, Trenkwalder T, Reinhard W, Cappola TP, van der Harst P. The Genetic Makeup of the Electrocardiogram. Cell Syst 2020; 11:229-238.e5. [PMID: 32916098 DOI: 10.1016/j.cels.2020.08.005] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 05/27/2020] [Accepted: 08/06/2020] [Indexed: 12/11/2022]
Abstract
The electrocardiogram (ECG) is one of the most useful non-invasive diagnostic tests for a wide array of cardiac disorders. Traditional approaches to analyzing ECGs focus on individual segments. Here, we performed comprehensive deep phenotyping of 77,190 ECGs in the UK Biobank across the complete cycle of cardiac conduction, resulting in 500 spatial-temporal datapoints, across 10 million genetic variants. In addition to characterizing polygenic risk scores for the traditional ECG segments, we identified over 300 genetic loci that are statistically associated with the high-dimensional representation of the ECG. We established the genetic ECG signature for dilated cardiomyopathy, associated the BAG3, HSPB7/CLCNKA, PRKCA, TMEM43, and OBSCN loci with disease risk and confirmed this association in an independent cohort. In total, our work demonstrates that a high-dimensional analysis of the entire ECG provides unique opportunities for studying cardiac biology and disease and furthering drug development. A record of this paper's transparent peer review process is included in the Supplemental Information.
Collapse
Affiliation(s)
- Niek Verweij
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands; Genomics plc, Oxford, UK.
| | - Jan-Walter Benjamins
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands
| | - Michael P Morley
- Cardiovascular Institute, Perelman School of Medicine , University of Pennsylvania, Philadelphia, USA
| | - Yordi J van de Vegte
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; DZHK (German Center for Cardiovascular Research), partner site Greifswald, Greifswald, Germany
| | - Teresa Trenkwalder
- Klinik für Herz- und Kreislauferkrankungen, Deutsches Herzzentrum München, Technical University Munich, Munich, Germany; DZHK (German Center for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Wibke Reinhard
- Klinik für Herz- und Kreislauferkrankungen, Deutsches Herzzentrum München, Technical University Munich, Munich, Germany
| | - Thomas P Cappola
- Division of Cardiovascular Medicine at the Perelman School of Medicine at the University of Pennsylvania, Philadelphia, USA
| | - Pim van der Harst
- University of Groningen, University Medical Center Groningen, Department of Cardiology, Groningen, the Netherlands; Department of Cardiology, Heart and Lung Division, University Medical Center Utrecht, Utrecht, the Netherlands
| |
Collapse
|
17
|
Villar D, Frost S, Deloukas P, Tinker A. The contribution of non-coding regulatory elements to cardiovascular disease. Open Biol 2020; 10:200088. [PMID: 32603637 PMCID: PMC7574544 DOI: 10.1098/rsob.200088] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 06/08/2020] [Indexed: 12/17/2022] Open
Abstract
Cardiovascular disease collectively accounts for a quarter of deaths worldwide. Genome-wide association studies across a range of cardiovascular traits and pathologies have highlighted the prevalence of common non-coding genetic variants within candidate loci. Here, we review genetic, epigenomic and molecular approaches to investigate the contribution of non-coding regulatory elements in cardiovascular biology. We then discuss recent insights on the emerging role of non-coding variation in predisposition to cardiovascular disease, with a focus on novel mechanistic examples from functional genomics studies. Lastly, we consider the clinical significance of these findings at present, and some of the current challenges facing the field.
Collapse
Affiliation(s)
- Diego Villar
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, 4 Newark Street, London E1 2AT, UK
| | - Stephanie Frost
- Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, 4 Newark Street, London E1 2AT, UK
| | - Panos Deloukas
- William Harvey Research Institute, Heart Centre, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| | - Andrew Tinker
- William Harvey Research Institute, Heart Centre, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, Charterhouse Square, London EC1M 6BQ, UK
| |
Collapse
|
18
|
Xie T, Wang B, Nolte IM, van der Most PJ, Oldehinkel AJ, Hartman CA, Snieder H. Genetic Risk Scores for Complex Disease Traits in Youth. CIRCULATION-GENOMIC AND PRECISION MEDICINE 2020; 13:e002775. [PMID: 32527150 PMCID: PMC7439939 DOI: 10.1161/circgen.119.002775] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND For most disease-related traits the magnitude of the contribution of genetic factors in adolescents remains unclear. METHODS Twenty continuous traits related to anthropometry, cardiovascular and renal function, metabolism, and inflammation were selected from the ongoing prospective Tracking Adolescents' Individual Lives Survey cohort in the Netherlands with measurements of up to 5 waves from age 11 to 22 years (n=1354, 47.6% males) and all traits available at the third wave (mean age [SD]=16.22 [0.66]). For each trait, unweighted and weighted genetic risk scores (GRSs) were generated based on significantly associated single nucleotide polymorphisms identified from literature. The variance explained by the GRSs in adolescents were estimated by linear regression after adjustment for covariates. RESULTS Except for ALT (alanine transaminase), all GRSs were significantly associated with their traits. The trait variance explained by the GRSs was highest for lipoprotein[a] (39.59%) and varied between 0.09% (ALT) and 18.49% (LDL [low-density lipoprotein]) for the other traits. For most traits, the variances explained in adolescents were comparable with or slightly smaller than those in adults. Significant increases of trait levels (except ALT) and increased risks for overweight/obesity (odds ratio, 6.41 [95% CI, 2.95-15.56]) and hypertension (odds ratio, 2.86 [95% CI, 1.39-6.17]) were found in individuals in the top GRS decile compared with those at the bottom decile. CONCLUSIONS Variances explained by adult-based GRSs for disease-related traits in adolescents, although still relatively modest, were comparable with or slightly smaller than in adults offering promise for improved risk prediction at early ages.
Collapse
Affiliation(s)
- Tian Xie
- Department of Epidemiology (T.X., B.W., I.M.N., P.J.v.d.M., H.S.), University of Groningen, University Medical Center Groningen, the Netherlands
| | - Bin Wang
- Department of Epidemiology (T.X., B.W., I.M.N., P.J.v.d.M., H.S.), University of Groningen, University Medical Center Groningen, the Netherlands
| | - Ilja M Nolte
- Department of Epidemiology (T.X., B.W., I.M.N., P.J.v.d.M., H.S.), University of Groningen, University Medical Center Groningen, the Netherlands
| | - Peter J van der Most
- Department of Epidemiology (T.X., B.W., I.M.N., P.J.v.d.M., H.S.), University of Groningen, University Medical Center Groningen, the Netherlands
| | - Albertine J Oldehinkel
- Department of Psychiatry (A.J.O., C.A.H.), University of Groningen, University Medical Center Groningen, the Netherlands
| | - Catharina A Hartman
- Department of Psychiatry (A.J.O., C.A.H.), University of Groningen, University Medical Center Groningen, the Netherlands
| | - Harold Snieder
- Department of Epidemiology (T.X., B.W., I.M.N., P.J.v.d.M., H.S.), University of Groningen, University Medical Center Groningen, the Netherlands
| |
Collapse
|
19
|
Guo Y, Chung W, Zhu Z, Shan Z, Li J, Liu S, Liang L. Genome-Wide Assessment for Resting Heart Rate and Shared Genetics With Cardiometabolic Traits and Type 2 Diabetes. J Am Coll Cardiol 2020; 74:2162-2174. [PMID: 31648709 DOI: 10.1016/j.jacc.2019.08.1055] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/02/2018] [Revised: 06/24/2019] [Accepted: 08/05/2019] [Indexed: 01/24/2023]
Abstract
BACKGROUND High resting heart rate (RHR) occurs in parallel with type 2 diabetes (T2D) and metabolic disorders, implying shared etiology between them. However, it is unknown if they are causally related, and no study has been conducted to investigate the shared mechanisms underlying these associations. OBJECTIVES The objective of this study was to understand the genetic basis of the association between resting heart rate and cardiometabolic disorders/T2D. METHODS This study examined the genetic correlation, causality, and shared genetics between RHR and T2D using LD Score regression, generalized summary data-based Mendelian randomization, and transcriptome wide association scan (TWAS) in UK Biobank data (n = 428,250) and summary-level data for T2D (74,124 cases and 824,006 control subjects) and 8 cardiometabolic traits (sample size ranges from 51,750 to 236,231). RESULTS Significant genetic correlation between RHR and T2D (rg = 0.22; 95% confidence interval: 0.18 to 0.26; p = 1.99 × 10-22), and 6 cardiometabolic traits (fasting insulin, fasting glucose, waist-hip ratio, triglycerides, high-density lipoprotein, and body mass index; rg range -0.12 to 0.24; all p < 0.05) were observed. RHR has significant estimated causal effect on T2D (odds ratio: 1.12 per 10-beats/min increment; p = 7.79 × 10-11) and weaker causal estimates from T2D to RHR (0.32 beats/min per doubling increment in T2D prevalence; p = 6.14 × 10-54). Sensitivity analysis by controlling for the included cardiometabolic traits did not modify the relationship between RHR and T2D. TWAS found locus chr2q23.3 (rs1260326) was highly pleiotropic among RHR, cardiometabolic traits, and T2D, and identified 7 genes (SMARCAD1, RP11-53O19.3, CTC-498M16.4, PDE8B, AKTIP, KDM4B, and TSHZ3) that were statistically independent and shared between RHR and T2D in tissues from the nervous and cardiovascular systems. These shared genes suggested the involvement of epigenetic regulation of energy and glucose metabolism, and AKT activation-related telomere dysfunction and vascular endothelial aging in the shared etiologies between RHR and T2D. Finally, FADS1 was found to be shared among RHR, fasting glucose, high-density lipoprotein, and triglycerides. CONCLUSIONS These findings provide evidence of significant genetic correlations and causation between RHR and T2D/cardiometabolic traits, advance our understanding of RHR, and provide insight into shared etiology for high RHR and T2D.
Collapse
Affiliation(s)
- Yanjun Guo
- Department of Occupational and Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Wonil Chung
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Statistics and Actuarial Science, Soongsil University, Seoul, Korea
| | - Zhaozhong Zhu
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Zhilei Shan
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Nutrition and Food Hygiene, Hubei Key Laboratory of Food Nutrition and Safety, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jun Li
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Simin Liu
- Departments of Epidemiology, Medicine, and Center for Global Cardiometabolic Health (CGCH), Brown University, Providence, Rhode Island
| | - Liming Liang
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
| |
Collapse
|
20
|
van der Ende MY, Said MA, van Veldhuisen DJ, Verweij N, van der Harst P. Genome-wide studies of heart failure and endophenotypes: lessons learned and future directions. Cardiovasc Res 2019; 114:1209-1225. [PMID: 29912321 DOI: 10.1093/cvr/cvy083] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/25/2017] [Accepted: 04/16/2018] [Indexed: 12/28/2022] Open
Abstract
Heart failure (HF) is a complex clinical syndrome resulting from structural or functional impairments of ventricular filling or ejection of blood. HF has a poor prognosis and the burden to society remains tremendous. The unfulfilled expectation is that expanding our knowledge of the genetic architecture of HF will help to quickly advance the quality of risk assessment, diagnoses, and treatment. To date, genome-wide association studies (GWAS) of HF have led to disappointing results with only limited progress in our understanding and tempering the earlier expectations. However, the analyses of traits closely related to HF (also called 'endophenotypes') have led to promising and novel findings. For example, GWAS of NT-proBNP levels not only identified variants in the NNPA-NPPB locus but also substantiated data suggesting that natriuretic peptides in itself are associated with a lower risk of hypertension and HF. Many other genetic associates currently await experimental follow-up in which genes are prioritized based on bioinformatic analyses and various model organisms are employed to obtain functional insights. Promising genes with identified function could later be used in personalized medicine. Also, targeting specific pathogenic gene mutations is promising to protect future generations from HF, such as recently done in human embryos carrying the cardiomyopathy-associated MYBPC3 mutation. This review discusses the current status of GWAS of HF and its endophenotypes. In addition, future directions such as functional follow-up and application of GWAS results are discussed.
Collapse
Affiliation(s)
- Maaike Yldau van der Ende
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, RB Groningen, The Netherlands
| | - Mir Abdullah Said
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, RB Groningen, The Netherlands
| | - Dirk Jan van Veldhuisen
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, RB Groningen, The Netherlands
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, RB Groningen, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, RB Groningen, The Netherlands
| |
Collapse
|
21
|
Evans KL, Wirtz HS, Li J, She R, Maya J, Gui H, Hamer A, Depre C, Lanfear DE. Genetics of heart rate in heart failure patients (GenHRate). Hum Genomics 2019; 13:22. [PMID: 31113495 PMCID: PMC6528282 DOI: 10.1186/s40246-019-0206-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2018] [Accepted: 04/22/2019] [Indexed: 11/20/2022] Open
Abstract
BACKGROUND Elevated resting heart rate (HR) is a risk factor and therapeutic target in patients with heart failure (HF) and reduced ejection fraction (HFrEF). Previous studies indicate a genetic contribution to HR in population samples but there is little data in patients with HFrEF. METHODS Patients who met Framingham criteria for HF and had an ejection fraction < 50% were prospectively enrolled in a genetic HF registry (2007-2015, n = 1060). All participants donated blood for DNA and underwent genome-wide genotyping with additional variants called via imputation. We performed testing of previously identified variant "hits" (43 loci) as well as a genome-wide association (GWAS) of HR, adjusted for race, using Efficient Mixed-Model Association Expedited (EMMAX). RESULTS The cohort was 35% female, 51% African American, and averaged 68 years of age. There was a 2 beats per minute (bpm) difference in HR by race, AA being slightly higher. Among 43 candidate variants, 4 single nucleotide polymorphisms (SNPs) in one gene (GJA1) were significantly associated with HR. In genome-wide testing, one statistically significant association peak was identified on chromosome 22q13, with strongest SNP rs535263906 (p = 3.3 × 10-8). The peak is located within the gene Cadherin EGF LAG Seven-Pass G-Type Receptor 1 (CELSR1), encoding a cadherin super-family cell surface protein identified in GWAS of other phenotypes (e.g., stroke). The highest associated SNP was specific to the African American population. CONCLUSIONS These data confirm GJA1 association with HR in the setting of HFrEF and identify novel candidate genes for HR in HFrEF patients, particularly CELSR1. These associations should be tested in additional cohorts.
Collapse
Affiliation(s)
- Kaleigh L. Evans
- 0000 0001 2160 8953grid.413103.4Department of Internal Medicine, Henry Ford Hospital, 2799 West Grand Blvd. K-14, Detroit, MI 48202 USA
| | - Heidi S. Wirtz
- 0000 0001 0657 5612grid.417886.4Amgen Inc, Thousand Oaks, CA USA
| | - Jia Li
- 0000 0000 8523 7701grid.239864.2Department of Public Health Sciences, Henry Ford Health System, Detroit, MI USA
| | - Ruicong She
- 0000 0000 8523 7701grid.239864.2Department of Public Health Sciences, Henry Ford Health System, Detroit, MI USA
| | - Juan Maya
- 0000 0001 0657 5612grid.417886.4Amgen Inc, Thousand Oaks, CA USA
| | - Hongsheng Gui
- 0000 0001 2160 8953grid.413103.4Center for Individualized and Genomic Medicine Research, Henry Ford Hospital, Detroit, MI USA
| | - Andrew Hamer
- 0000 0001 0657 5612grid.417886.4Amgen Inc, Thousand Oaks, CA USA
| | - Christophe Depre
- 0000 0001 0657 5612grid.417886.4Amgen Inc, Thousand Oaks, CA USA
| | - David E. Lanfear
- 0000 0001 2160 8953grid.413103.4Department of Internal Medicine, Henry Ford Hospital, 2799 West Grand Blvd. K-14, Detroit, MI 48202 USA
- 0000 0001 2160 8953grid.413103.4Center for Individualized and Genomic Medicine Research, Henry Ford Hospital, Detroit, MI USA
- 0000 0001 2160 8953grid.413103.4Heart and Vascular Institute, Henry Ford Hospital, Detroit, MI USA
| |
Collapse
|
22
|
Yazdani A, Yazdani A, Elsea SH, Schaid DJ, Kosorok MR, Dangol G, Samiei A. Genome analysis and pleiotropy assessment using causal networks with loss of function mutation and metabolomics. BMC Genomics 2019; 20:395. [PMID: 31113383 PMCID: PMC6528192 DOI: 10.1186/s12864-019-5772-4] [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: 07/23/2018] [Accepted: 05/03/2019] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Many genome-wide association studies have detected genomic regions associated with traits, yet understanding the functional causes of association often remains elusive. Utilizing systems approaches and focusing on intermediate molecular phenotypes might facilitate biologic understanding. RESULTS The availability of exome sequencing of two populations of African-Americans and European-Americans from the Atherosclerosis Risk in Communities study allowed us to investigate the effects of annotated loss-of-function (LoF) mutations on 122 serum metabolites. To assess the findings, we built metabolomic causal networks for each population separately and utilized structural equation modeling. We then validated our findings with a set of independent samples. By use of methods based on concepts of Mendelian randomization of genetic variants, we showed that some of the affected metabolites are risk predictors in the causal pathway of disease. For example, LoF mutations in the gene KIAA1755 were identified to elevate the levels of eicosapentaenoate (p-value = 5E-14), an essential fatty acid clinically identified to increase essential hypertension. We showed that this gene is in the pathway to triglycerides, where both triglycerides and essential hypertension are risk factors of metabolomic disorder and heart attack. We also identified that the gene CLDN17, harboring loss-of-function mutations, had pleiotropic actions on metabolites from amino acid and lipid pathways. CONCLUSION Using systems biology approaches for the analysis of metabolomics and genetic data, we integrated several biological processes, which lead to findings that may functionally connect genetic variants with complex diseases.
Collapse
Affiliation(s)
| | - Akram Yazdani
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, 10029 USA
| | - Sarah H. Elsea
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030 USA
| | - Daniel J. Schaid
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905 USA
| | - Michael R. Kosorok
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 USA
| | - Gita Dangol
- Health Science Center, The University of Texas MD Anderson Cancer Center, Austin, TX 77030 USA
| | - Ahmad Samiei
- Hasso Plattner Institute, 14482 Potsdam, Germany
- Climax Data Pattern, Boston, MA USA
| |
Collapse
|
23
|
Ramírez J, Duijvenboden SV, Ntalla I, Mifsud B, Warren HR, Tzanis E, Orini M, Tinker A, Lambiase PD, Munroe PB. Thirty loci identified for heart rate response to exercise and recovery implicate autonomic nervous system. Nat Commun 2018; 9:1947. [PMID: 29769521 PMCID: PMC5955978 DOI: 10.1038/s41467-018-04148-1] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Accepted: 04/06/2018] [Indexed: 12/25/2022] Open
Abstract
Impaired capacity to increase heart rate (HR) during exercise (ΔHRex), and a reduced rate of recovery post-exercise (ΔHRrec) are associated with higher cardiovascular mortality rates. Currently, the genetic basis of both phenotypes remains to be elucidated. We conduct genome-wide association studies (GWASs) for ΔHRex and ΔHRrec in ~40,000 individuals, followed by replication in ~27,000 independent samples, all from UK Biobank. Six and seven single-nucleotide polymorphisms for ΔHRex and ΔHRrec, respectively, formally replicate. In a full data set GWAS, eight further loci for ΔHRex and nine for ΔHRrec are genome-wide significant (P ≤ 5 × 10−8). In total, 30 loci are discovered, 8 being common across traits. Processes of neural development and modulation of adrenergic activity by the autonomic nervous system are enriched in these results. Our findings reinforce current understanding of HR response to exercise and recovery and could guide future studies evaluating its contribution to cardiovascular risk prediction. Genome-wide association studies have identified multiple loci for resting heart rate (HR) but the genetic factors associated with HR increase during and HR recovery after exercise are less well studied. Here, the authors examine both traits in a two-stage GWAS design in up to 67,257 individuals from UK Biobank.
Collapse
Affiliation(s)
- Julia Ramírez
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.,Institute of Cardiovascular Science, University College London, London, WC1E 6BT, UK
| | - Stefan van Duijvenboden
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK.,Institute of Cardiovascular Science, University College London, London, WC1E 6BT, UK
| | - Ioanna Ntalla
- Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Borbala Mifsud
- 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
| | - Helen R Warren
- 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
| | - Evan Tzanis
- 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
| | - Michele Orini
- Barts Heart Centre, St Bartholomews Hospital, London, EC1A 7BE, UK.,Mechanical Engineering Department, University College London, London, WC1E 6BT, UK
| | - Andrew Tinker
- 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
| | - Pier D Lambiase
- Institute of Cardiovascular Science, University College London, London, WC1E 6BT, UK. .,Barts Heart Centre, St Bartholomews Hospital, London, EC1A 7BE, 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.
| |
Collapse
|
24
|
Shahin MH, Conrado DJ, Gonzalez D, Gong Y, Lobmeyer MT, Beitelshees AL, Boerwinkle E, Gums JG, Chapman A, Turner ST, Cooper-DeHoff RM, Johnson JA. Genome-Wide Association Approach Identified Novel Genetic Predictors of Heart Rate Response to β-Blockers. J Am Heart Assoc 2018; 7:JAHA.117.006463. [PMID: 29478026 PMCID: PMC5866313 DOI: 10.1161/jaha.117.006463] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Background For many indications, the negative chronotropic effect of β‐blockers is important to their efficacy, yet the heart rate (HR) response to β‐blockers varies. Herein, we sought to use a genome‐wide association approach to identify novel single nucleotide polymorphisms (SNPs) associated with HR response to β‐blockers. Methods and Results We first performed 4 genome‐wide association analyses for HR response to atenolol (a β1‐adrenergic receptor blocker) as: (1) monotherapy or (2) add‐on therapy, in 426 whites and 273 blacks separately from the PEAR (Pharmacogenomic Evaluation of Antihypertensive Responses) study. A meta‐analysis was then performed between the genome‐wide association analysis performed in PEAR atenolol monotherapy and add‐on therapy, in each race separately, using the inverse variance method assuming fixed effects. From this analysis, SNPs associated with HR response to atenolol at a P<1E‐05 were tested for replication in whites (n=200) and blacks (n=168) treated with metoprolol (a β1‐adrenergic receptor blocker). From the genome‐wide association meta‐analyses, SNP rs17117817 near olfactory receptor family10 subfamily‐p‐member1 (OR10P1), and SNP rs2364349 in sorting nexin‐9 (SNX9) replicated in blacks. The combined studies meta‐analysis P values for the rs17117817 and rs2364349 reached genome‐wide significance (rs17117817G‐allele; Meta‐β=5.53 beats per minute, Meta‐P=2E‐09 and rs2364349 A‐allele; Meta‐β=3.5 beats per minute, Meta‐P=1E‐08). Additionally, SNPs in the OR10P1 and SNX9 gene regions were also associated with HR response in whites. Conclusions This study highlights OR10P1 and SNX9 as novel genes associated with changes in HR in response to β‐blockers. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT00246519.
Collapse
Affiliation(s)
- Mohamed H Shahin
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL
| | - Daniela J Conrado
- Department of Pharmaceutics, College of Pharmacy, University of Florida, Gainesville, FL
| | - Daniel Gonzalez
- Division of Pharmacotherapy and Experimental Therapeutics, UNC Eshelman School of Pharmacy University of North Carolina, Chapel Hill, NC
| | - Yan Gong
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL
| | - Maximilian T Lobmeyer
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL
| | | | - Eric Boerwinkle
- Human Genetics Center and Institute of Molecular Medicine, University of Texas Health Science Center, Houston, TX
| | - John G Gums
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL
| | | | - Stephen T Turner
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, MN
| | - Rhonda M Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL
| | - Julie A Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics, College of Pharmacy, University of Florida, Gainesville, FL
| |
Collapse
|