501
|
Yu CY, Gu Y, Jiang YC, Zhang XW. Identification of intrinsic genes across general hypertension, hypertension with left ventricular remodeling, and uncontrolled hypertension. Front Cardiovasc Med 2022; 9:992284. [PMID: 36277786 PMCID: PMC9582241 DOI: 10.3389/fcvm.2022.992284] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 08/18/2022] [Indexed: 01/11/2023] Open
Abstract
The purpose of the present article is to identify intrinsic genes across general hypertension (HT), hypertension with left ventricular remodeling (HT-LVR), and uncontrolled hypertension (UN-HT). In total, four microarray datasets (GSE24752, GSE75360, GSE74144, and GSE71994) were downloaded from the GEO database and were used to identify differentially expressed genes (DEGs), respectively. Furthermore, gene set enrichment analysis (GSEA) was utilized to screen for significantly enriched biological pathways across the four datasets above, respectively. Furthermore, weighted gene co-expression network analysis (WGCNA) and functional enrichment analysis were applied to screen out gene modules of interest and potential biological functions, respectively. Finally, a Metascape-based multiple gene list meta-analysis was used to investigate intrinsic genes at different stages of the progression of hypertension. A total of 75 DEGs (63 upregulated genes and 12 downregulated genes, GSE24752) and 23 DEGs (2 upregulated genes and 21 downregulated genes, GSE74144) were identified. However, there were few DEGs identified in GSE75360, GSE71994, and part of the GSE74144 datasets. GSEA and functional enrichment of gene module of interest have indicated that "Heme metabolism," "TNF alpha/NFkB," and "interferon alpha response signaling," and MYC target v1/v2 were enriched significantly in different stages of hypertension progression. Significantly, findings from the multiple gene list meta-analysis suggested that FBXW4 and other 13 genes were unique to the hypertension group, and TRIM11 and other 40 genes were mainly involved in hypertension with the left ventricular remodeling group, while the other 18 genes including F13A1 significantly enriched in uncontrolled hypertension. Collectively, the precise switch of the "immune-metabolic-inflammatory" loop pathway was the most significant hallmark across different stages of hypertension, thereby providing a potential therapeutic target for uncontrolled hypertension treatment.
Collapse
|
502
|
Louca P, Tran TQB, Toit CD, Christofidou P, Spector TD, Mangino M, Suhre K, Padmanabhan S, Menni C. Machine learning integration of multimodal data identifies key features of blood pressure regulation. EBioMedicine 2022; 84:104243. [PMID: 36084617 PMCID: PMC9463529 DOI: 10.1016/j.ebiom.2022.104243] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2022] [Revised: 08/02/2022] [Accepted: 08/11/2022] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Association studies have identified several biomarkers for blood pressure and hypertension, but a thorough understanding of their mutual dependencies is lacking. By integrating two different high-throughput datasets, biochemical and dietary data, we aim to understand the multifactorial contributors of blood pressure (BP). METHODS We included 4,863 participants from TwinsUK with concurrent BP, metabolomics, genomics, biochemical measures, and dietary data. We used 5-fold cross-validation with the machine learning XGBoost algorithm to identify features of importance in context of one another in TwinsUK (80% training, 20% test). The features tested in TwinsUK were then probed using the same algorithm in an independent dataset of 2,807 individuals from the Qatari Biobank (QBB). FINDINGS Our model explained 39·2% [4·5%, MAE:11·32 mmHg (95%CI, +/- 0·65)] of the variance in systolic BP (SBP) in TwinsUK. Of the top 50 features, the most influential non-demographic variables were dihomo-linolenate, cis-4-decenoyl carnitine, lactate, chloride, urate, and creatinine along with dietary intakes of total, trans and saturated fat. We also highlight the incremental value of each included dimension. Furthermore, we replicated our model in the QBB [SBP variance explained = 45·2% (13·39%)] cohort and 30 of the top 50 features overlapped between cohorts. INTERPRETATION We show that an integrated analysis of omics, biochemical and dietary data improves our understanding of their in-between relationships and expands the range of potential biomarkers for blood pressure. Our results point to potentially key biological pathways to be prioritised for mechanistic studies. FUNDING Chronic Disease Research Foundation, Medical Research Council, Wellcome Trust, Qatar Foundation.
Collapse
Affiliation(s)
- Panayiotis Louca
- Department of Twin Research and Genetic Epidemiology, King's College London, London, England, SE1 7EH, United Kingdom
| | - Tran Quoc Bao Tran
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom
| | - Clea du Toit
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom
| | - Paraskevi Christofidou
- Department of Twin Research and Genetic Epidemiology, King's College London, London, England, SE1 7EH, United Kingdom
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, England, SE1 7EH, United Kingdom
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, England, SE1 7EH, United Kingdom; NIHR Biomedical Research Centre at Guy's and St Thomas' Foundation Trust, London, SE1 9RT, United Kingdom
| | - Karsten Suhre
- Bioinformatics Core, Weill Cornell Medicine-Qatar, Doha, Qatar; Department of Physiology and Biophysics, Weill Cornell Medicine, New York, NY, USA
| | - Sandosh Padmanabhan
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, Glasgow G12 8QQ, United Kingdom.
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, King's College London, London, England, SE1 7EH, United Kingdom.
| |
Collapse
|
503
|
Polimanti R, Wendt FR, Pathak GA, Tylee DS, Tcheandjieu C, Hilliard AT, Levey DF, Adhikari K, Gaziano JM, O'Donnell CJ, Assimes TL, Stein MB, Gelernter J. Understanding the comorbidity between posttraumatic stress severity and coronary artery disease using genome-wide information and electronic health records. Mol Psychiatry 2022; 27:3961-3969. [PMID: 35986173 PMCID: PMC10986859 DOI: 10.1038/s41380-022-01735-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 07/29/2022] [Accepted: 08/05/2022] [Indexed: 02/07/2023]
Abstract
The association between coronary artery disease (CAD) and posttraumatic stress disorder (PTSD) contributes to the high morbidity and mortality observed for these conditions. To understand the dynamics underlying PTSD-CAD comorbidity, we investigated large-scale genome-wide association (GWA) statistics from the Million Veteran Program (MVP), the UK Biobank (UKB), the Psychiatric Genomics Consortium, and the CARDIoGRAMplusC4D Consortium. We observed a genetic correlation of CAD with PTSD case-control and quantitative outcomes, ranging from 0.18 to 0.32. To investigate possible cause-effect relationships underlying these genetic correlations, we performed a two-sample Mendelian randomization (MR) analysis, observing a significant bidirectional relationship between CAD and PTSD symptom severity. Genetically-determined PCL-17 (PTSD 17-item Checklist) total score was associated with increased CAD risk (odds ratio = 1.04; 95% confidence interval, 95% CI = 1.01-1.06). Conversely, CAD genetic liability was associated with reduced PCL-17 total score (beta = -0.42; 95% CI = -0.04 to -0.81). Because of these opposite-direction associations, we conducted a pleiotropic meta-analysis to investigate loci with concordant vs. discordant effects on PCL-17 and CAD, observing that concordant-effect loci were enriched for molecular pathways related to platelet amyloid precursor protein (beta = 1.53, p = 2.97 × 10-7) and astrocyte activation regulation (beta = 1.51, p = 2.48 × 10-6) while discordant-effect loci were enriched for biological processes related to lipid metabolism (e.g., triglyceride-rich lipoprotein particle clearance, beta = 2.32, p = 1.61 × 10-10). To follow up these results, we leveraged MVP and UKB electronic health records (EHR) to assess longitudinal changes in the association between CAD and posttraumatic stress severity. This EHR-based analysis highlighted that earlier CAD diagnosis is associated with increased PCL-total score later in life, while lower PCL total score was associated with increased risk of a later CAD diagnosis (Mann-Kendall trend test: MVP tau = 0.932, p < 2 × 10-16; UKB tau = 0.376, p = 0.005). In conclusion, both our genetically-informed analyses and our EHR-based follow-up investigation highlighted a bidirectional relationship between PTSD and CAD where multiple pleiotropic mechanisms are likely to be involved.
Collapse
Affiliation(s)
- Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA.
- VA CT Healthcare Center, West Haven, CT, USA.
| | - Frank R Wendt
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - Gita A Pathak
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - Daniel S Tylee
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | | | - Austin T Hilliard
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - Keyrun Adhikari
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
| | - J Michael Gaziano
- Department of Medicine, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Christopher J O'Donnell
- Department of Medicine, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Themistocles L Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
| | - Murray B Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- VA San Diego Healthcare System, Psychiatry Service, San Diego, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, West Haven, CT, USA
- VA CT Healthcare Center, West Haven, CT, USA
- Departments of Genetics and of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| |
Collapse
|
504
|
Ditmars HL, Logue MW, Toomey R, McKenzie RE, Franz CE, Panizzon MS, Reynolds CA, Cuthbert KN, Vandiver R, Gustavson DE, Eglit GML, Elman JA, Sanderson-Cimino M, Williams ME, Andreassen OA, Dale AM, Eyler LT, Fennema-Notestine C, Gillespie NA, Hauger RL, Jak AJ, Neale MC, Tu XM, Whitsel N, Xian H, Kremen WS, Lyons MJ. Associations between depression and cardiometabolic health: A 27-year longitudinal study. Psychol Med 2022; 52:3007-3017. [PMID: 33431106 PMCID: PMC8547283 DOI: 10.1017/s003329172000505x] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
BACKGROUND Clarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems. METHODS The study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse ('baseline') and the longitudinal Vietnam Era Twin Study of Aging ('follow-up'). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)]. RESULTS Total depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07-1.57), erectile dysfunction (OR 1.32, 95% CI 1.10-1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04-1.53), and sleep apnea (OR 1.40, 95% CI 1.13-1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09-1.60). CONCLUSIONS A history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.
Collapse
Affiliation(s)
- Hillary L. Ditmars
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Mark W. Logue
- Research Service, VA Boston Healthcare System, Boston, MA
- Biomedical Genetics Program, Boston University School of Medicine, Boston, MA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Rosemary Toomey
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Ruth E. McKenzie
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
- School of Education and Social Policy, Merrimack College, North Andover, MA, USA
| | - Carol E. Franz
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Matthew S. Panizzon
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Chandra A. Reynolds
- Department of Psychology, University of California, Riverside, Riverside, CA
| | - Kristy N. Cuthbert
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | - Richard Vandiver
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| | | | - Graham M. L. Eglit
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- VA San Diego Healthcare System, San Diego, CA
| | - Jeremy A. Elman
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
| | - Mark Sanderson-Cimino
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology
| | - McKenna E. Williams
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology
| | - Ole A. Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine University of Oslo Oslo, Norway
- Division of Mental Health and Addiction, Oslo University Hospital Oslo, Oslo, Norway
| | - Anders M. Dale
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA
- Department of Neurosciences, University of California, San Diego, La Jolla, CA
| | - Lisa T. Eyler
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Christine Fennema-Notestine
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Nathan A. Gillespie
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
| | - Richard L. Hauger
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Amy J. Jak
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Michael C. Neale
- Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
- Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA
| | - Xin M. Tu
- Department of Family Medicine and Public Health, VA San Diego Healthcare System, San Diego, CA
| | - Nathan Whitsel
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
| | - Hong Xian
- Department of Epidemiology & Biostatistics, Saint Louis University College for Public Health & Social Justice
| | - William S. Kremen
- Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA
- Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA
- Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA
| | - Michael J. Lyons
- Department of Psychological and Brain Sciences, Boston University, Boston, MA
| |
Collapse
|
505
|
Ramírez J, van Duijvenboden S, Young WJ, Tinker A, Lambiase PD, Orini M, Munroe PB. Prediction of Coronary Artery Disease and Major Adverse Cardiovascular Events Using Clinical and Genetic Risk Scores for Cardiovascular Risk Factors. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2022; 15:e003441. [PMID: 35861959 PMCID: PMC9584057 DOI: 10.1161/circgen.121.003441] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Accepted: 04/21/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND Coronary artery disease (CAD) and major adverse cardiovascular events (MACE) are the leading causes of death in the general population, but risk stratification remains suboptimal. CAD genetic risk scores (GRSs) predict risk independently from clinical tools, like QRISK3. We assessed the added value of GRSs for a variety of cardiovascular traits (CV GRSs) for predicting CAD and MACE and tested their early-life screening potential by comparing against the CAD GRS only. METHODS We used data from 379 581 participants in the UK Biobank without known cardiovascular conditions (follow-up, 11.3 years; 3.3% CAD cases and 5.2% MACE cases). In a training subset (50%) we built 3 scores: QRISK3; QRISK3 and an established CAD GRS; and QRISK3, the CAD GRS and the CV GRSs. In an independent subset (50%), we evaluated each score's performance using the concordance index, odds ratio and net reclassification index. We then repeated the analyses without considering QRISK3. RESULTS For CAD, the combination of QRISK3 and the CAD GRS had a better performance than QRISK3 alone (concordance index, 0.766 versus 0.753; odds ratio, 5.47 versus 4.82; net reclassification index, 7.7%). Adding the CV GRSs did not significantly improve risk stratification. When only looking at genetic information, the combination of CV GRSs and the CAD GRS had a better performance than the CAD GRS alone (concordance index, 0.637 versus 0.625; odds ratio, 2.17 versus 2.07; net reclassification index, 3.3%). Similar results were obtained for MACE. CONCLUSIONS In individuals without known cardiovascular disease, the inclusion of CV GRSs to a clinical tool and an established CAD GRS does not improve CAD or MACE risk stratification. However, their combination only with the CAD GRS increases prediction performance indicating potential use in early-life screening before the advanced development of conventional cardiovascular risk factors.
Collapse
Affiliation(s)
- Julia Ramírez
- Clinical Pharmacology and Precision Medicine Deparment, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (J.R., S.v.D., W.J.Y., A.T., P.B.M.)
- Electronic Engineering and Communications Department, Aragon Institute of Engineering Research, University of Zaragoza, Spain and CIBER's Bioengineering, Biomaterials and Nanomedicine, Spain. (J.R.)
| | - Stefan van Duijvenboden
- Clinical Pharmacology and Precision Medicine Deparment, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (J.R., S.v.D., W.J.Y., A.T., P.B.M.)
- Institute of Cardiovascular Science, University College London, London, United Kingdom (S.v.D., P.D.L., M.O.)
| | - William J. Young
- Clinical Pharmacology and Precision Medicine Deparment, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (J.R., S.v.D., W.J.Y., A.T., P.B.M.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (W.J.Y., P.D.L., M.O.)
| | - Andrew Tinker
- Clinical Pharmacology and Precision Medicine Deparment, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (J.R., S.v.D., W.J.Y., A.T., P.B.M.)
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (A.T., P.B.M.)
| | - Pier D. Lambiase
- Institute of Cardiovascular Science, University College London, London, United Kingdom (S.v.D., P.D.L., M.O.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (W.J.Y., P.D.L., M.O.)
| | - Michele Orini
- Institute of Cardiovascular Science, University College London, London, United Kingdom (S.v.D., P.D.L., M.O.)
- Barts Heart Centre, St Bartholomew’s Hospital, London, United Kingdom (W.J.Y., P.D.L., M.O.)
| | - Patricia B. Munroe
- Clinical Pharmacology and Precision Medicine Deparment, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom (J.R., S.v.D., W.J.Y., A.T., P.B.M.)
- NIHR Barts Cardiovascular Biomedical Research Centre, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (A.T., P.B.M.)
| |
Collapse
|
506
|
Villapalos-García G, Zubiaur P, Rivas-Durán R, Campos-Norte P, Arévalo-Román C, Fernández-Rico M, García-Fraile Fraile L, Fernández-Campos P, Soria-Chacartegui P, Fernández de Córdoba-Oñate S, Delgado-Wicke P, Fernández-Ruiz E, González-Álvaro I, Sanz J, Abad-Santos F, de Los Santos I. Transmembrane protease serine 2 ( TMPRSS2) rs75603675, comorbidity, and sex are the primary predictors of COVID-19 severity. Life Sci Alliance 2022; 5:e202201396. [PMID: 35636966 PMCID: PMC9152129 DOI: 10.26508/lsa.202201396] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 05/12/2022] [Accepted: 05/13/2022] [Indexed: 01/08/2023] Open
Abstract
By the end of December 2021, coronavirus disease 2019 (COVID-19) produced more than 271 million cases and 5.3 million deaths. Although vaccination is an effective strategy for pandemic control, it is not yet equally available in all countries. Therefore, identification of prognostic biomarkers remains crucial to manage COVID-19 patients. The aim of this study was to evaluate predictors of COVID-19 severity previously proposed. Clinical and demographic characteristics and 120 single-nucleotide polymorphisms were analyzed from 817 patients with COVID-19, who attended the emergency department of the Hospital Universitario de La Princesa during March and April 2020. The main outcome was a modified version of the 7-point World Health Organization (WHO) COVID-19 severity scale (WHOCS); both in the moment of the first hospital examination (WHOCS-1) and of the severest WHOCS score (WHOCS-2). The TMPRSS2 rs75603675 genotype (OR = 0.586), dyslipidemia (OR = 2.289), sex (OR = 0.586), and the Charlson Comorbidity Index (OR = 1.126) were identified as the main predictors of disease severity. Consequently, these variables might influence COVID-19 severity and could be used as predictors of disease development.
Collapse
Affiliation(s)
- Gonzalo Villapalos-García
- Clinical Pharmacology Department, Hospital Universitario La Princesa, Instituto Teófilo Hernando, Universidad Autónoma de Madrid (UAM), Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Pablo Zubiaur
- Clinical Pharmacology Department, Hospital Universitario La Princesa, Instituto Teófilo Hernando, Universidad Autónoma de Madrid (UAM), Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain
| | - Rebeca Rivas-Durán
- Infectious Diseases Unit, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Pilar Campos-Norte
- Infectious Diseases Unit, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Cristina Arévalo-Román
- Infectious Diseases Unit, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Marta Fernández-Rico
- Infectious Diseases Unit, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Lucio García-Fraile Fraile
- Infectious Diseases Unit, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Paula Fernández-Campos
- Clinical Pharmacology Department, Hospital Universitario La Princesa, Instituto Teófilo Hernando, Universidad Autónoma de Madrid (UAM), Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Paula Soria-Chacartegui
- Clinical Pharmacology Department, Hospital Universitario La Princesa, Instituto Teófilo Hernando, Universidad Autónoma de Madrid (UAM), Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Sara Fernández de Córdoba-Oñate
- Molecular Biology Unit, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Pablo Delgado-Wicke
- Molecular Biology Unit, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Elena Fernández-Ruiz
- Molecular Biology Unit, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Isidoro González-Álvaro
- Rheumatology Service, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Jesús Sanz
- Infectious Diseases Unit, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| | - Francisco Abad-Santos
- Clinical Pharmacology Department, Hospital Universitario La Princesa, Instituto Teófilo Hernando, Universidad Autónoma de Madrid (UAM), Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain
| | - Ignacio de Los Santos
- Infectious Diseases Unit, Hospital Universitario La Princesa, Instituto de Investigación Sanitaria La Princesa (IIS-IP), Madrid, Spain
| |
Collapse
|
507
|
Yuan S, Carter P, Mason AM, Yang F, Burgess S, Larsson SC. Genetic Liability to Rheumatoid Arthritis in Relation to Coronary Artery Disease and Stroke Risk. Arthritis Rheumatol 2022; 74:1638-1647. [PMID: 35583917 PMCID: PMC9804931 DOI: 10.1002/art.42239] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 04/30/2022] [Accepted: 05/12/2022] [Indexed: 01/09/2023]
Abstract
OBJECTIVE To assess the causality of the associations of rheumatoid arthritis (RA) with coronary artery disease (CAD) and stroke using the Mendelian randomization approach. METHODS Independent single-nucleotide polymorphisms strongly associated with RA (n = 70) were selected as instrumental variables from a genome-wide association meta-analysis including 14,361 RA patients and 43,923 controls of European ancestry. Summary-level data for CAD, all stroke, any ischemic stroke and its subtypes, intracerebral hemorrhage (ICH), and subarachnoid hemorrhage were obtained from meta-analyses of genetic studies, international genetic consortia, the UK Biobank, and the FinnGen consortium. We obtained summary-level data for common cardiovascular risk factors and related inflammatory biomarkers to assess possible mechanisms. RESULTS Genetic liability to RA was associated with an increased risk of CAD and ICH. For a 1-unit increase in log odds of RA, the combined odds ratios were 1.02 (95% confidence interval [1.01, 1.03]; P = 0.003) for CAD and 1.05 (95% confidence interval [1.02, 1.08]; P = 0.001) for ICH. Genetic liability to RA was associated with increased levels of tumor necrosis factor and C-reactive protein (CRP). The association with CAD was attenuated after adjustment for genetically predicted CRP levels. There were no associations of genetic liability to RA with the other studied outcomes. CONCLUSION This study found that genetic liability to RA was associated with an increased risk of CAD and ICH and that the association with CAD might be mediated by CRP. The heightened cardiovascular risk should be actively monitored and managed in RA patients, and this may include dampening systemic inflammation.
Collapse
Affiliation(s)
| | | | | | - Fangkun Yang
- Ningbo First Hospital and Zhejiang UniversityNingboChina
| | | | - Susanna C. Larsson
- Karolinska Institutet, Stockholm, Sweden, and Uppsala UniversityUppsalaSweden
| |
Collapse
|
508
|
Zhao SS, Rajasundaram S, Karhunen V, Alam U, Gill D. Sodium-glucose cotransporter 1 inhibition and gout: Mendelian randomisation study. Semin Arthritis Rheum 2022; 56:152058. [PMID: 35839537 DOI: 10.1016/j.semarthrit.2022.152058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/03/2022] [Accepted: 06/27/2022] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Sodium-glucose cotransporter 2 inhibitors (SGLT2i) reduce serum urate, but their efficacy depends on renal function which is often impaired in people with gout. SGLT1 is primarily expressed in the small intestine and its inhibition may be a more suitable therapeutic target. We aimed to investigate the association of genetically proxied SGLT1i with gout risk, serum urate levels and cardiovascular safety using Mendelian randomisation (MR). METHODS Leveraging data from a genome-wide association study of 344,182 individuals in the UK Biobank, we identified a missense variant in the SLC5A1 gene that associated with glycated haemoglobin (HbA1c) to proxy SGLT1i. Outcome genetic data comprised 13,179 gout cases and 750,634 controls, 457,690 individuals for serum urate levels, and up to 977,323 individuals for cardiovascular safety outcomes. We applied the Wald ratio method and investigated potential genetic confounding using colocalization. RESULTS The rs17683430 missense variant was selected to instrument SGLT1i. Genetically proxied SGLT1i was associated with 75% reduction in gout risk (OR 0.25; 95%CI 0.06, 0.99; p = 0.048) and 32.0 μmol/L reduction in serum urate (95%CI -56.7, -7.3; p = 0.01), per 6.7 mmol/mol reduction in HbA1c. SGLT1i was associated with increased levels of low-density lipoprotein cholesterol (0.37 mmol/L; 95%CI 0.17, 0.56; p = 0.0002) but not risk of coronary heart disease, stroke, or chronic kidney disease. Colocalization did not suggest that results are attributable to genetic confounding. CONCLUSION SGLT1 inhibition may represent a novel therapeutic option for preventing gout in people with or without comorbid diabetes. Randomised trials are needed to formally investigate efficacy and safety.
Collapse
Affiliation(s)
- Sizheng Steven Zhao
- Centre for Epidemiology Versus Arthritis, Division of Musculoskeletal and Dermatological Science, School of Biological Sciences, Faculty of Biological Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Stopford Building, Oxford Road, Manchester M13 9PT, UK.
| | - Skanda Rajasundaram
- Centre for Evidence-Based Medicine, University of Oxford, Oxford, UK; Faculty of Medicine, Imperial College London, London, UK
| | - Ville Karhunen
- Research Unit of Mathematical Sciences, University of Oulu, Oulu, Finland; Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Uazman Alam
- Institute of Life Course and Medical Sciences and the Pain Research Institute, University of Liverpool, Liverpool, UK; Department of Diabetes & Endocrinology, Liverpool University Hospital NHS Foundation Trust, Liverpool, UK; Division of Diabetes, Endocrinology and Gastroenterology, Institute of Human Development, University of Manchester, Manchester, UK
| | - Dipender Gill
- Centre of Excellence in Genetics, Novo Nordisk Research Centre Oxford, Oxford, UK; Department of Epidemiology and Biostatistics, Imperial College London, London, UK; Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
| |
Collapse
|
509
|
Zu T, Lian H, Green B, Yu Y. Ultra-high Dimensional Quantile Regression for Longitudinal Data: an Application to Blood Pressure Analysis. J Am Stat Assoc 2022. [DOI: 10.1080/01621459.2022.2128806] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/14/2022]
Affiliation(s)
- Tianhai Zu
- Department of Operations, Business Analytics, & Information Systems, University of Cincinnati, Cincinnati, Ohio, USA
| | - Heng Lian
- Department of Mathematics, City University of Hong Kong, Tat Chee Avenue, Kowloon Tong Hong Kong, China
| | - Brittany Green
- Department of Information Systems, Analytics, and Operations, University of Louisville, Louisville, Kentucky, USA
| | - Yan Yu
- Department of Operations, Business Analytics, & Information Systems, University of Cincinnati, Cincinnati, Ohio, USA
| |
Collapse
|
510
|
Zhang Y, Elgart M, Kurniansyah N, Spitzer BW, Wang H, Kim D, Shah N, Daviglus M, Zee PC, Cai J, Gottlieb DJ, Cade BE, Redline S, Sofer T. Genetic determinants of cardiometabolic and pulmonary phenotypes and obstructive sleep apnoea in HCHS/SOL. EBioMedicine 2022; 84:104288. [PMID: 36174398 PMCID: PMC9515437 DOI: 10.1016/j.ebiom.2022.104288] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 08/24/2022] [Accepted: 09/08/2022] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Obstructive Sleep Apnoea (OSA) often co-occurs with cardiometabolic and pulmonary diseases. This study is to apply genetic analysis methods to explain the associations between OSA and related phenotypes. METHODS In the Hispanic Community Healthy Study/Study of Latinos, we estimated genetic correlations ρg between the respiratory event index (REI) and 54 anthropometric, glycemic, cardiometabolic, and pulmonary phenotypes. We used summary statistics from published genome-wide association studies to construct Polygenic Risk Scores (PRSs) representing the genetic basis of each correlated phenotype (ρg>0.2 and p-value<0.05), and of OSA. We studied the association of the PRSs of the correlated phenotypes with both REI and OSA (REI≥5), and the association of OSA PRS with the correlated phenotypes. Causal relationships were tested using Mendelian Randomization (MR) analysis. FINDINGS The dataset included 11,155 participants, 31.03% with OSA. 22 phenotypes were genetically correlated with REI. 10 PRSs covering obesity and fat distribution (BMI, WHR, WHRadjBMI), blood pressure (DBP, PP, MAP), glycaemic control (fasting insulin, HbA1c, HOMA-B) and insomnia were associated with REI and/or OSA. OSA PRS was associated with BMI, WHR, DBP and glycaemic traits (fasting insulin, HbA1c, HOMA-B and HOMA-IR). MR analysis identified robust causal effects of BMI and WHR on OSA, and probable causal effects of DBP, PP, and HbA1c on OSA/REI. INTERPRETATION There are shared genetic underpinnings of anthropometric, blood pressure, and glycaemic phenotypes with OSA, with evidence for causal relationships between some phenotypes. FUNDING Described in Acknowledgments.
Collapse
Affiliation(s)
- Yuan Zhang
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA,Department of Respiratory Medicine, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Michael Elgart
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Nuzulul Kurniansyah
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Brian W. Spitzer
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Doyoon Kim
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Neomi Shah
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Phyllis C. Zee
- Center for Circadian and Sleep Medicine, Department of Neurology, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Daniel J. Gottlieb
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Brian E. Cade
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA,Corresponding author at: Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, 221 Longwood Avenue, Boston, MA 02115, USA.
| |
Collapse
|
511
|
Association between arterial hypertension and liver outcomes using polygenic risk scores: a population-based study. Sci Rep 2022; 12:15581. [PMID: 36114231 PMCID: PMC9481629 DOI: 10.1038/s41598-022-20084-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 09/08/2022] [Indexed: 12/03/2022] Open
Abstract
Arterial hypertension (HTA) is associated with liver disease, but causality remains unclear. We investigated whether genetic predisposition to HTA is associated with liver disease in the population, and if antihypertensive medication modifies this association. Participants of the Finnish health-examination surveys, FINRISK 1992–2012 and Health 2000 (n = 33,770), were linked with national electronic healthcare registers for liver-related outcomes (K70-K77, C22.0) and with the drug reimbursement registry for new initiation of antihypertensive medication during follow-up. Genetic predisposition to HTA was defined by polygenic risk scores (PRSs). During a median 12.9-year follow-up (409,268.9 person-years), 441 liver-related outcomes occurred. In the fully-adjusted Cox-regression models, both measured systolic blood pressure and clinically defined HTA were associated with liver-related outcomes. PRSs for systolic and diastolic blood pressure were significantly associated with liver-related outcomes (HR/SD 1.19, 95% CI 1.01–1.24, and 1.12, 95% CI 1.01–1.25, respectively). In the highest quintile of the systolic blood pressure PRS, new initiation of antihypertensive medication was associated with reduced rates of liver-related outcomes (HR 0.55, 95% CI 0.31–0.97). HTA and a genetic predisposition for HTA are associated with liver-related outcomes in the population. New initiation of antihypertensive medication attenuates this association in persons with high genetic risk for HTA.
Collapse
|
512
|
Lopez-Pineda A, Vernekar M, Moreno-Grau S, Rojas-Muñoz A, Moatamed B, Lee MTM, Nava-Aguilar MA, Gonzalez-Arroyo G, Numakura K, Matsuda Y, Ioannidis A, Katsanis N, Takano T, Bustamante CD. Validating and automating learning of cardiometabolic polygenic risk scores from direct-to-consumer genetic and phenotypic data: implications for scaling precision health research. Hum Genomics 2022; 16:37. [PMID: 36076307 PMCID: PMC9452874 DOI: 10.1186/s40246-022-00406-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Accepted: 08/06/2022] [Indexed: 11/29/2022] Open
Abstract
INTRODUCTION A major challenge to enabling precision health at a global scale is the bias between those who enroll in state sponsored genomic research and those suffering from chronic disease. More than 30 million people have been genotyped by direct-to-consumer (DTC) companies such as 23andMe, Ancestry DNA, and MyHeritage, providing a potential mechanism for democratizing access to medical interventions and thus catalyzing improvements in patient outcomes as the cost of data acquisition drops. However, much of these data are sequestered in the initial provider network, without the ability for the scientific community to either access or validate. Here, we present a novel geno-pheno platform that integrates heterogeneous data sources and applies learnings to common chronic disease conditions including Type 2 diabetes (T2D) and hypertension. METHODS We collected genotyped data from a novel DTC platform where participants upload their genotype data files and were invited to answer general health questionnaires regarding cardiometabolic traits over a period of 6 months. Quality control, imputation, and genome-wide association studies were performed on this dataset, and polygenic risk scores were built in a case-control setting using the BASIL algorithm. RESULTS We collected data on N = 4,550 (389 cases / 4,161 controls) who reported being affected or previously affected for T2D and N = 4,528 (1,027 cases / 3,501 controls) for hypertension. We identified 164 out of 272 variants showing identical effect direction to previously reported genome-significant findings in Europeans. Performance metric of the PRS models was AUC = 0.68, which is comparable to previously published PRS models obtained with larger datasets including clinical biomarkers. DISCUSSION DTC platforms have the potential of inverting research models of genome sequencing and phenotypic data acquisition. Quality control (QC) mechanisms proved to successfully enable traditional GWAS and PRS analyses. The direct participation of individuals has shown the potential to generate rich datasets enabling the creation of PRS cardiometabolic models. More importantly, federated learning of PRS from reuse of DTC data provides a mechanism for scaling precision health care delivery beyond the small number of countries who can afford to finance these efforts directly. CONCLUSIONS The genetics of T2D and hypertension have been studied extensively in controlled datasets, and various polygenic risk scores (PRS) have been developed. We developed predictive tools for both phenotypes trained with heterogeneous genotypic and phenotypic data generated outside of the clinical environment and show that our methods can recapitulate prior findings with fidelity. From these observations, we conclude that it is possible to leverage DTC genetic repositories to identify individuals at risk of debilitating diseases based on their unique genetic landscape so that informed, timely clinical interventions can be incorporated.
Collapse
Affiliation(s)
- Arturo Lopez-Pineda
- Galatea Bio, Inc., 975 W 22nd Street, Hialeah, Florida, 33010, USA
- Amphora Health, Batallon Independencia 80, Morelia, Michoacan, 58260, Mexico
| | - Manvi Vernekar
- Genomelink, Inc., 2150 Shattuck Avenue, Berkeley, California, 94704, USA
- Awakens Japan K.K., 2-11-3 Meguro, Meguro-ku, Tokyo, 1530063, Japan
| | | | | | - Babak Moatamed
- Galatea Bio, Inc., 975 W 22nd Street, Hialeah, Florida, 33010, USA
| | | | - Marco A Nava-Aguilar
- Galatea Bio, Inc., 975 W 22nd Street, Hialeah, Florida, 33010, USA
- Amphora Health, Batallon Independencia 80, Morelia, Michoacan, 58260, Mexico
| | - Gilberto Gonzalez-Arroyo
- Galatea Bio, Inc., 975 W 22nd Street, Hialeah, Florida, 33010, USA
- Amphora Health, Batallon Independencia 80, Morelia, Michoacan, 58260, Mexico
| | - Kensuke Numakura
- Genomelink, Inc., 2150 Shattuck Avenue, Berkeley, California, 94704, USA
- Awakens Japan K.K., 2-11-3 Meguro, Meguro-ku, Tokyo, 1530063, Japan
| | - Yuta Matsuda
- Genomelink, Inc., 2150 Shattuck Avenue, Berkeley, California, 94704, USA
- Awakens Japan K.K., 2-11-3 Meguro, Meguro-ku, Tokyo, 1530063, Japan
| | - Alexander Ioannidis
- Galatea Bio, Inc., 975 W 22nd Street, Hialeah, Florida, 33010, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, 1265 Welch Road, Stanford, California, 94305, USA
| | | | - Tomohiro Takano
- Genomelink, Inc., 2150 Shattuck Avenue, Berkeley, California, 94704, USA.
- Awakens Japan K.K., 2-11-3 Meguro, Meguro-ku, Tokyo, 1530063, Japan.
| | - Carlos D Bustamante
- Galatea Bio, Inc., 975 W 22nd Street, Hialeah, Florida, 33010, USA.
- Department of Biomedical Data Science, Stanford University School of Medicine, 1265 Welch Road, Stanford, California, 94305, USA.
- Chan Zuckerberg Biohub, 499 Illinois Street, San Francisco, California, 94158, USA.
| |
Collapse
|
513
|
Ardissino M, Slob EAW, Rajasundaram S, Reddy RK, Woolf B, Girling J, Johnson MR, Ng FS, Gill D. Safety of beta-blocker and calcium channel blocker antihypertensive drugs in pregnancy: a Mendelian randomization study. BMC Med 2022; 20:288. [PMID: 36064525 PMCID: PMC9446737 DOI: 10.1186/s12916-022-02483-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 07/14/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Beta-blocker (BB) and calcium channel blocker (CCB) antihypertensive drugs are commonly used in pregnancy. However, data on their relative impact on maternal and foetal outcomes are limited. We leveraged genetic variants mimicking BB and CCB antihypertensive drugs to investigate their effects on risk of pre-eclampsia, gestational diabetes and birthweight using the Mendelian randomization paradigm. METHODS Genetic association estimates for systolic blood pressure (SBP) were extracted from summary data of a genome-wide association study (GWAS) on 757,601 participants. Uncorrelated single-nucleotide polymorphisms (SNPs) associated with SBP (p < 5 × 10-8) in BB and CCB drug target gene regions were selected as proxies for drug target perturbation. Genetic association estimates for the outcomes were extracted from GWASs on 4743 cases and 136,325 controls (women without a hypertensive disorder in pregnancy) for pre-eclampsia or eclampsia, 7676 cases and 130,424 controls (women without any pregnancy-related morbidity) for gestational diabetes, and 155,202 women (who have given birth at least once) for birthweight of the first child. All studies were in European ancestry populations. Mendelian randomization estimates were generated using the two-sample inverse-variance weighted model. RESULTS Although not reaching the conventional threshold for statistical significance, genetically-proxied BB was associated with reduced risk of pre-eclampsia (OR per 10 mmHg SBP reduction 0.27, 95%CI 0.06-1.19, p = 0.08) and increased risk of gestational diabetes (OR per 10 mmHg SBP reduction 2.01, 95%CI 0.91-4.42, p = 0.08), and significantly associated with lower birthweight of first child (beta per 10 mmHg SBP reduction - 0.27, 95%CI - 0.39 to - 0.15, p = 1.90 × 10-5). Genetically-proxied CCB was associated with reduced risk of pre-eclampsia and eclampsia (OR 0.62, 95%CI 0.43-0.89, p = 9.33 × 10-3), and was not associated with gestational diabetes (OR 1.05, 95% CI 0.76-1.45, p = 0.76) or changes in birthweight of first child (beta per 10 mmHg SBP reduction 0.02, 95%CI - 0.04-0.07, p = 0.54). CONCLUSIONS While BB and CCB antihypertensive drugs may both be efficacious for lowering blood pressure in pregnancy, this genetic evidence suggests that BB use may lower birthweight. Conversely, CCB use may reduce risk of pre-eclampsia and eclampsia without impacting gestational diabetes risk or birthweight. These data support further study on the effects of BBs on birthweight.
Collapse
Affiliation(s)
- Maddalena Ardissino
- National Heart and Lung Institute, Imperial College London, London, UK
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Eric A W Slob
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus University Rotterdam, Rotterdam, the Netherlands
| | - Skanda Rajasundaram
- Centre for Evidence-Based Medicine, University of Oxford, Oxford, UK
- Faculty of Medicine, Imperial College London, London, UK
| | - Rohin K Reddy
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Benjamin Woolf
- School of Psychological Science, University of Bristol, Bristol, UK
- Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
| | - Joanna Girling
- Chelsea and Westminster Hospital NHS Foundation Trust, West Middlesex Hospital, London, UK
| | - Mark R Johnson
- Division of Reproductive and Developmental Biology, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Fu Siong Ng
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Dipender Gill
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, UK.
- Department of Epidemiology and Biostatistics, School of Public Health, Medical School Building, St Mary's Hospital, Imperial College London, W2 1PG, London, UK.
- Chief Scientific Office, Research and Early Development, Novo Nordisk, Copenhagen, Denmark.
| |
Collapse
|
514
|
Cohen JB, Mitchell GF, Gill D, Burgess S, Rahman M, Hanff T, Ramachandran VS, Mutalik K, Townsend RR, Chirinos JA. Arterial Stiffness and Diabetes Risk in Framingham Heart Study and UK Biobank. Circ Res 2022; 131:545-554. [PMID: 35946401 PMCID: PMC7613487 DOI: 10.1161/circresaha.122.320796] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Accepted: 07/26/2022] [Indexed: 01/26/2023]
Abstract
BACKGROUND Microvascular damage from large artery stiffness (LAS) in pancreatic, hepatic, and skeletal muscles may affect glucose homeostasis. Our goal was to evaluate the association between LAS and the risk of type 2 diabetes using prospectively collected, carefully phenotyped measurements of LAS as well as Mendelian randomization analyses. METHODS Carotid-femoral pulse wave velocity (CF-PWV) and brachial and central pulse pressure were measured in 5676 participants of the FHS (Framingham Heart Study) without diabetes. We used Cox proportional hazards regression to evaluate the association of CF-PWV and pulse pressure with incident diabetes. We subsequently performed 2-sample Mendelian randomization analyses evaluating the associations of genetically predicted brachial pulse pressure with type 2 diabetes in the UKBB (United Kingdom Biobank). RESULTS In FHS, individuals with higher CF-PWV were older, more often male, and had higher body mass index and mean arterial pressure compared to those with lower CF-PWV. After a median follow-up of 7 years, CF-PWV and central pulse pressure were associated with an increased risk of new-onset diabetes (per SD increase, multivariable-adjusted CF-PWV hazard ratio, 1.36 [95% CI, 1.03-1.76]; P=0.030; central pulse pressure multivariable-adjusted CF-PWV hazard ratio, 1.26 [95% CI, 1.08-1.48]; P=0.004). In United Kingdom Biobank, genetically predicted brachial pulse pressure was associated with type 2 diabetes, independent of mean arterial pressure (adjusted odds ratio, 1.16 [95% CI, 1.00-1.35]; P=0.049). CONCLUSIONS Using prospective cohort data coupled with Mendelian randomization analyses, we found evidence supporting that greater LAS is associated with increased risk of developing diabetes. LAS may play an important role in glucose homeostasis and may serve as a useful marker of future diabetes risk.
Collapse
Affiliation(s)
- Jordana B. Cohen
- Renal-Electrolyte and Hypertension Division, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Stephen Burgess
- Medical Research Council Biostatistics Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Mahboob Rahman
- Department of Medicine, Case Western University, University Hospitals Case Medical Center, Cleveland, OH, USA
| | - Thomas Hanff
- Division of Cardiovascular Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Vasan S. Ramachandran
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | | | - Raymond R. Townsend
- Renal-Electrolyte and Hypertension Division, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Julio A. Chirinos
- Division of Cardiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| |
Collapse
|
515
|
Tomaszewski M, Morris AP, Howson JMM, Franceschini N, Eales JM, Xu X, Dikalov S, Guzik TJ, Humphreys BD, Harrap S, Charchar FJ. Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications. Kidney Int 2022; 102:492-505. [PMID: 35690124 PMCID: PMC9886011 DOI: 10.1016/j.kint.2022.04.045] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2021] [Revised: 03/10/2022] [Accepted: 04/22/2022] [Indexed: 02/06/2023]
Abstract
Hypertension is a major cardiovascular disease risk factor and contributor to premature death globally. Family-based investigations confirmed a significant heritable component of blood pressure (BP), whereas genome-wide association studies revealed >1000 common and rare genetic variants associated with BP and/or hypertension. The kidney is not only an organ of key relevance to BP regulation and the development of hypertension, but it also acts as the tissue mediator of genetic predisposition to hypertension. The identity of kidney genes, pathways, and related mechanisms underlying the genetic associations with BP has started to emerge through integration of genomics with kidney transcriptomics, epigenomics, and other omics as well as through applications of causal inference, such as Mendelian randomization. Single-cell methods further enabled mapping of BP-associated kidney genes to cell types, and in conjunction with other omics, started to illuminate the biological mechanisms underpinning associations of BP-associated genetic variants and kidney genes. Polygenic risk scores derived from genome-wide association studies and refined on kidney omics hold the promise of enhanced diagnostic prediction, whereas kidney omics-informed drug discovery is likely to contribute new therapeutic opportunities for hypertension and hypertension-mediated kidney damage.
Collapse
Affiliation(s)
- Maciej Tomaszewski
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK; Manchester Heart Centre and Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK.
| | - Andrew P Morris
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK
| | - Joanna M M Howson
- Department of Genetics, Novo Nordisk Research Centre Oxford, Novo Nordisk Ltd, Oxford, UK
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA
| | - James M Eales
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Xiaoguang Xu
- Division of Cardiovascular Sciences, Faculty of Medicine, Biology and Health, University of Manchester, Manchester, UK
| | - Sergey Dikalov
- Division of Clinical Pharmacology, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Tomasz J Guzik
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK; Department of Internal and Agricultural Medicine, Jagiellonian University College of Medicine, Kraków, Poland
| | - Benjamin D Humphreys
- Division of Nephrology, Department of Medicine, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Stephen Harrap
- Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Fadi J Charchar
- Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia; Health Innovation and Transformation Centre, School of Science, Psychology and Sport, Federation University Australia, Ballarat, Victoria, Australia; Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| |
Collapse
|
516
|
Ferolito B, do Valle IF, Gerlovin H, Costa L, Casas JP, Gaziano JM, Gagnon DR, Begoli E, Barabási AL, Cho K. Visualizing novel connections and genetic similarities across diseases using a network-medicine based approach. Sci Rep 2022; 12:14914. [PMID: 36050444 PMCID: PMC9436158 DOI: 10.1038/s41598-022-19244-y] [Citation(s) in RCA: 4] [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: 04/21/2022] [Accepted: 08/26/2022] [Indexed: 11/08/2022] Open
Abstract
Understanding the genetic relationships between human disorders could lead to better treatment and prevention strategies, especially for individuals with multiple comorbidities. A common resource for studying genetic-disease relationships is the GWAS Catalog, a large and well curated repository of SNP-trait associations from various studies and populations. Some of these populations are contained within mega-biobanks such as the Million Veteran Program (MVP), which has enabled the genetic classification of several diseases in a large well-characterized and heterogeneous population. Here we aim to provide a network of the genetic relationships among diseases and to demonstrate the utility of quantifying the extent to which a given resource such as MVP has contributed to the discovery of such relations. We use a network-based approach to evaluate shared variants among thousands of traits in the GWAS Catalog repository. Our results indicate many more novel disease relationships that did not exist in early studies and demonstrate that the network can reveal clusters of diseases mechanistically related. Finally, we show novel disease connections that emerge when MVP data is included, highlighting methodology that can be used to indicate the contributions of a given biobank.
Collapse
Affiliation(s)
- Brian Ferolito
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA.
| | - Italo Faria do Valle
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
- Center for Complex Network Research, Department of Physics, Northeastern University, Boston, 02115, USA
| | - Hanna Gerlovin
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
| | - Lauren Costa
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
| | - Juan P Casas
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
- Brigham and Women's Hospital, Division of Aging, Department of Medicine, Harvard Medical School, Boston, 02115, USA
| | - J Michael Gaziano
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
- Brigham and Women's Hospital, Division of Aging, Department of Medicine, Harvard Medical School, Boston, 02115, USA
| | - David R Gagnon
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
- School of Public Health, Department of Biostatistics, Boston University, Boston, 02215, USA
| | - Edmon Begoli
- Oak Ridge National Laboratory, Oak Ridge, 37830, USA
| | - Albert-László Barabási
- Center for Complex Network Research, Department of Physics, Northeastern University, Boston, 02115, USA
| | - Kelly Cho
- VA Boston Healthcare System, Massachusetts Veterans Epidemiology and Research Information Center, (MAVERIC), 150 S. Huntington Avenue, Boston, 02130, USA
- Brigham and Women's Hospital, Division of Aging, Department of Medicine, Harvard Medical School, Boston, 02115, USA
| |
Collapse
|
517
|
Timmers PRHJ, Wilson JF. Limited Effect of Y Chromosome Variation on Coronary Artery Disease and Mortality in UK Biobank-Brief Report. Arterioscler Thromb Vasc Biol 2022; 42:1198-1206. [PMID: 35861954 PMCID: PMC9394501 DOI: 10.1161/atvbaha.122.317664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND The effect of genetic variation in the male-specific region of the Y chromosome (MSY) on coronary artery disease and cardiovascular risk factors has been disputed. In this study, we systematically assessed the association of MSY genetic variation on these traits using a kin-cohort analysis of family disease history in the largest sample to date. METHODS We tested 90 MSY haplogroups against coronary artery disease, hypertension, blood pressure, classical lipid levels, and all-cause mortality in up to 152 186 unrelated, genomically British individuals from UK Biobank. Unlike previous studies, we did not adjust for heritable lifestyle factors (to avoid collider bias) and instead adjusted for geographic variables and socioeconomic deprivation, given the link between MSY haplogroups and geography. For family history traits, subject MSY haplogroups were tested against father and mother disease as validation and negative control, respectively. RESULTS Our models find little evidence for an effect of any MSY haplogroup on cardiovascular risk in participants. Parental models confirm these findings. CONCLUSIONS Kin-cohort analysis of the Y chromosome uniquely allows for discoveries in subjects to be validated using family history data. Despite our large sample size, improved models, and parental validation, there is little evidence to suggest cardiovascular risk in UK Biobank is influenced by genetic variation in MSY.
Collapse
Affiliation(s)
- Paul R H J Timmers
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer (P.R.H.J.T., J.F.W.), University of Edinburgh, United Kingdom.,Centre for Global Health Research, Usher Institute (P.R.H.J.T., J.F.W.), University of Edinburgh, United Kingdom
| | - James F Wilson
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer (P.R.H.J.T., J.F.W.), University of Edinburgh, United Kingdom.,Centre for Global Health Research, Usher Institute (P.R.H.J.T., J.F.W.), University of Edinburgh, United Kingdom
| |
Collapse
|
518
|
Yang MJ, Zhang Z, Wang YJ, Li JC, Guo QL, Chen X, Wang E. Association of Nap Frequency With Hypertension or Ischemic Stroke Supported by Prospective Cohort Data and Mendelian Randomization in Predominantly Middle-Aged European Subjects. Hypertension 2022; 79:1962-1970. [PMID: 35876003 DOI: 10.1161/hypertensionaha.122.19120] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND AND PURPOSE The aim of this study was to investigate the association between daytime napping frequency and the incidence of essential hypertension or stroke as well as to validate causality in this relationship via Mendelian randomization (MR). METHODS We conducted Cox regression analysis on 358 451 participants free of hypertension or stroke from UK Biobank. To validate the results of the observational analysis, we conducted a 2-sample MR for daytime napping frequency (123 single-nucleotide polymorphisms) with essential hypertension in FinnGen Biobank, stroke, and ischemic stroke in MEGASTROKE consortium and performed a corresponding 1-sample MR on the UK Biobank data. RESULTS Compared with never napping, usually napping was associated with a higher risk of essential hypertension (hazard ratio, 1.12 [95% CI, 1.08-1.17]), stroke (hazard ratio, 1.24 [95% CI, 1.10-1.39], and ischemic stroke (hazard ratio, 1.20 [95% CI, 1.05-1.36]) in our prospective observational analysis. Both the 1-sample and 2-sample MR results indicated that increased daytime napping frequency was likely to be a potential causal risk factor for essential hypertension in FinnGEN (odds ratio, 1.43 [95% CI, 1.06-1.92]) and UK Biobank (odds ratio, 1.40 [95% CI, 1.28-1.58]). The 2-sample MR results supported the potential causal effect of nap frequency on ischemic stroke in MEGASTROKE (odds ratio, 1.29 [95% CI, 1.04-1.62]). CONCLUSIONS Prospective observational and MR analyses provided evidence that increased daytime nap frequency may represent a potential causal risk factor for essential hypertension. The potential causal association of increased nap frequency with ischemic stroke was supported by 2-sample MR and prospective observational results.
Collapse
Affiliation(s)
- Min-Jing Yang
- Department of Anesthesiology (M.-j.Y., Z.Z., Q.-l.G.) Central South University, Changsha, Hunan, China
| | - Zhong Zhang
- Department of Anesthesiology (M.-j.Y., Z.Z., Q.-l.G.) Central South University, Changsha, Hunan, China
| | - Yi-Jing Wang
- National Clinical Research Center for Geriatric Disorders (Y.-j.W., J.-c.L.) Central South University, Changsha, Hunan, China.,Xiangya Hospital, Centre for Medical Genetics, Hunan Key Laboratory of Medical Genetics, School of Life Sciences (Y.-j.W., J.-c.L.), Central South University, Changsha, Hunan, China
| | - Jin-Chen Li
- National Clinical Research Center for Geriatric Disorders (Y.-j.W., J.-c.L.) Central South University, Changsha, Hunan, China.,Xiangya Hospital, Centre for Medical Genetics, Hunan Key Laboratory of Medical Genetics, School of Life Sciences (Y.-j.W., J.-c.L.), Central South University, Changsha, Hunan, China
| | - Qu-Lian Guo
- Department of Anesthesiology (M.-j.Y., Z.Z., Q.-l.G.) Central South University, Changsha, Hunan, China
| | - Xiang Chen
- Department of Anesthesiology (X.C., E.W.) Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders (X.C., E.W.) Central South University, Changsha, Hunan, China
| | - E Wang
- Department of Anesthesiology (X.C., E.W.) Central South University, Changsha, Hunan, China.,National Clinical Research Center for Geriatric Disorders (X.C., E.W.) Central South University, Changsha, Hunan, China
| |
Collapse
|
519
|
Kivioja A, Toivonen E, Tyrmi J, Ruotsalainen S, Ripatti S, Huhtala H, Jääskeläinen T, Heinonen S, Kajantie E, Kere J, Kivinen K, Pouta A, Saarela T, Laivuori H. Increased Risk of Preeclampsia in Women With a Genetic Predisposition to Elevated Blood Pressure. Hypertension 2022; 79:2008-2015. [PMID: 35862124 PMCID: PMC9370253 DOI: 10.1161/hypertensionaha.122.18996] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Accepted: 06/07/2022] [Indexed: 11/16/2022]
Abstract
BACKGROUND Preeclampsia causes significant maternal and perinatal morbidity. Genetic factors seem to affect the onset of the disease. We aimed to investigate whether the polygenic risk score for blood pressure (BP; BP-PRS) is associated with preeclampsia, its subtypes, and BP values during pregnancy. METHODS The analyses were performed in the FINNPEC study (Finnish Genetics of Pre-Eclampsia Consortium) cohort of 1514 preeclamptic and 983 control women. In a case-control setting, the data were divided into percentiles to compare women with high BP-PRS (HBP-PRS; >95th percentile) or low BP-PRS (≤5th percentile) to others. Furthermore, to evaluate the effect of BP-PRS on BP, we studied 3 cohorts: women with preeclampsia, hypertensive controls, and normotensive controls. RESULTS BP values were higher in women with HBP-PRS throughout the pregnancy. Preeclampsia was more common in women with HBP-PRS compared with others (71.8% and 60.1%, respectively; P=0.009), and women with low BP-PRS presented with preeclampsia less frequently than others (44.8% and 61.5%, respectively; P<0.001). HBP-PRS was associated with an increased risk for preeclampsia (odds ratio, 1.7 [95% CI, 1.1-2.5]). Furthermore, women with HBP-PRS presented with recurrent preeclampsia and preeclampsia with severe features more often. CONCLUSIONS Our results suggest that HBP-PRS is associated with an increased risk of preeclampsia, recurrent preeclampsia, and preeclampsia with severe features. Furthermore, women with HBP-PRS present higher BP values during pregnancy. The results strengthen the evidence pointing toward the role of genetic variants associated with BP regulation in the etiology of preeclampsia, especially its more severe forms.
Collapse
Affiliation(s)
- Anna Kivioja
- Department of Obstetrics and Gynecology, Tampere University Hospital, Finland (A.K., E.T., H.L.)
- Center for Child, Adolescent, and Maternal Health, Faculty of Medicine and Health Technology (A.K., E.T., J.T., H.L.), Tampere University, Finland
| | - Elli Toivonen
- Department of Obstetrics and Gynecology, Tampere University Hospital, Finland (A.K., E.T., H.L.)
- Center for Child, Adolescent, and Maternal Health, Faculty of Medicine and Health Technology (A.K., E.T., J.T., H.L.), Tampere University, Finland
| | - Jaakko Tyrmi
- Center for Child, Adolescent, and Maternal Health, Faculty of Medicine and Health Technology (A.K., E.T., J.T., H.L.), Tampere University, Finland
- Computational Medicine, Faculty of Medicine (J.T.), University of Oulu, Finland
- Center for Life Course Health Research, Faculty of Medicine (J.T.), University of Oulu, Finland
- Biocenter Oulu (J.T.), University of Oulu, Finland
| | - Sanni Ruotsalainen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science (S. Ruotsalainen, S. Ripatti, K.K., H.L.), University of Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science (S. Ruotsalainen, S. Ripatti, K.K., H.L.), University of Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA (S. Ripatti)
| | - Heini Huhtala
- Faculty of Social Sciences (H.H.), Tampere University, Finland
| | - Tiina Jääskeläinen
- Medical and Clinical Genetics (T.J., H.L.), University of Helsinki and Helsinki University Hospital, Finland
| | - Seppo Heinonen
- Obsterics and Gynaecology (S.H.), University of Helsinki and Helsinki University Hospital, Finland
| | - Eero Kajantie
- PEDEGO Research Unit, Medical Research Center Oulu, Oulu University Hospital (E.K., A.P.), University of Oulu, Finland
- Children’s Hospital (E.K.), University of Helsinki and Helsinki University Hospital, Finland
- Public Health Promotion Unit (E.K.), University of Helsinki and Helsinki University Hospital, Finland
- Department of Clinical and Molecular Medicine, Norwegian University of Health and Technology, Trondheim, Norway (E.K.)
| | - Juha Kere
- Department of Biosciences and Nutrition, Karolinska Institutet, Huddinge, Sweden (J.K.)
| | - Katja Kivinen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science (S. Ruotsalainen, S. Ripatti, K.K., H.L.), University of Helsinki, Finland
| | - Anneli Pouta
- PEDEGO Research Unit, Medical Research Center Oulu, Oulu University Hospital (E.K., A.P.), University of Oulu, Finland
- Department of Government Services (A.P.), National Institute for Health and Welfare, Helsinki, Finland
| | - Tanja Saarela
- Department of Clinical Genetics, Kuopio University Hospital, Finland (T.S.)
| | - Hannele Laivuori
- Center for Child, Adolescent, and Maternal Health, Faculty of Medicine and Health Technology (A.K., E.T., J.T., H.L.), Tampere University, Finland
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science (S. Ruotsalainen, S. Ripatti, K.K., H.L.), University of Helsinki, Finland
- Medical and Clinical Genetics (T.J., H.L.), University of Helsinki and Helsinki University Hospital, Finland
| |
Collapse
|
520
|
Chen L, Fan Z, Sun X, Qiu W, Mu W, Chai K, Cao Y, Wang G, Lv G. Examination on the risk factors of cholangiocarcinoma: A Mendelian randomization study. Front Pharmacol 2022; 13:900424. [PMID: 36091764 PMCID: PMC9462706 DOI: 10.3389/fphar.2022.900424] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2022] [Accepted: 07/26/2022] [Indexed: 11/24/2022] Open
Abstract
Background: Several risk factors have been identified for CCA, however, whether such associations were causal remains unknown. Methods: Mendelian randomization (MR) has been applied to examine the causal relationship between 26 putative risk factors and CCA. The genetic variants for each risk factor were extracted from their corresponding genome-wide association study (GWAS) if they reached the genome-wide significance (p-value < 5 × 10−8). The genetic associations with CCA were obtained from the publicly available GWAS with the largest sample size. Mainly, inverse-variance weighted (IVW) has been adopted to estimate the causal effect on CCA. Both multivariable and mediation MR analyses were carried out to detect independent factors. Results: Three putative risk factors can causally elevate the risk of CCA after FDR correction, including liver fat content (LFC), non-alcoholic fatty liver disease (NAFLD), and cholelithiasis. The odds of CCA would increase per 1-SD increase in the liver fat content (LFC) (OR = 2.12 [1.66, 2.71]) and logOR of NAFLD. The genetic liability to cholelithiasis would increase the risk of CCA as well (OR = 2.17 [1.47, 3.20]). They were still significant in other methods. The multivariable MR analysis indicated that genetically-elevated LFC should increase the risk of CCA independently of cholelithiasis (OR = 1.88 [1.39, 2.55]). In the mediation MR analysis, the indirect effect was not significant when treating cholelithiasis as the mediator (indirect OR = 0.95 [0.85, 1.07]). Conclusion: This MR study identified that gallstone and liver fat accumulation are two independent risk factors of CCA, suggesting two modifiable ways of preventing CCA.
Collapse
|
521
|
Mehanna M, McDonough CW, Smith SM, Gong Y, Gums JG, Chapman AB, Johnson JA, Cooper-DeHoff RM. Influence of Genetic West African Ancestry on Metabolomics among Hypertensive Patients. Metabolites 2022; 12:metabo12090783. [PMID: 36144188 PMCID: PMC9506508 DOI: 10.3390/metabo12090783] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Revised: 08/18/2022] [Accepted: 08/20/2022] [Indexed: 12/02/2022] Open
Abstract
Patients with higher genetic West African ancestry (GWAA) have hypertension (HTN) that is more difficult to treat and have higher rates of cardiovascular diseases (CVD) and differential responses to antihypertensive drugs than those with lower GWAA. The mechanisms underlying these disparities are poorly understood. Using data from 84 ancestry-informative markers in US participants from the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) and PEAR-2 trials, the GWAA proportion was estimated. Using multivariable linear regression, the baseline levels of 886 metabolites were compared between PEAR participants with GWAA < 45% and those with GWAA ≥ 45% to identify differential metabolites and metabolic clusters. Metabolites with a false discovery rate (FDR) < 0.2 were used to create metabolic clusters, and a cluster analysis was conducted. Differential clusters were then tested for replication in PEAR-2 participants. We identified 353 differential metabolites (FDR < 0.2) between PEAR participants with GWAA < 45% (n = 383) and those with GWAA ≥ 45% (n = 250), which were used to create 24 metabolic clusters. Of those, 13 were significantly different between groups (Bonferroni p < 0.002). Four clusters, plasmalogen and lysoplasmalogen, sphingolipid metabolism and ceramide, cofactors and vitamins, and the urea cycle, were replicated in PEAR-2 (Bonferroni p < 0.0038) and have been previously linked to HTN and CVD. Our findings may give insights into the mechanisms underlying HTN racial disparities.
Collapse
Affiliation(s)
- Mai Mehanna
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA
| | - Caitrin W. McDonough
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA
| | - Steven M. Smith
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA
- Department of Pharmaceutical Outcomes & Policy, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA
| | - Yan Gong
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA
| | - John G. Gums
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA
| | - Arlene B. Chapman
- Department of Medicine, University of Chicago, Chicago, IL 60637, USA
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA
| | - Rhonda M. Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research and Center for Pharmacogenomics and Precision Medicine, College of Pharmacy, University of Florida, Gainesville, FL 32610, USA
- Correspondence: ; Tel.: +1-(352)-273-6184
| |
Collapse
|
522
|
Moonen JR, Chappell J, Shi M, Shinohara T, Li D, Mumbach MR, Zhang F, Nair RV, Nasser J, Mai DH, Taylor S, Wang L, Metzger RJ, Chang HY, Engreitz JM, Snyder MP, Rabinovitch M. KLF4 recruits SWI/SNF to increase chromatin accessibility and reprogram the endothelial enhancer landscape under laminar shear stress. Nat Commun 2022; 13:4941. [PMID: 35999210 PMCID: PMC9399231 DOI: 10.1038/s41467-022-32566-9] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 08/05/2022] [Indexed: 12/14/2022] Open
Abstract
Physiologic laminar shear stress (LSS) induces an endothelial gene expression profile that is vasculo-protective. In this report, we delineate how LSS mediates changes in the epigenetic landscape to promote this beneficial response. We show that under LSS, KLF4 interacts with the SWI/SNF nucleosome remodeling complex to increase accessibility at enhancer sites that promote the expression of homeostatic endothelial genes. By combining molecular and computational approaches we discover enhancers that loop to promoters of KLF4- and LSS-responsive genes that stabilize endothelial cells and suppress inflammation, such as BMPR2, SMAD5, and DUSP5. By linking enhancers to genes that they regulate under physiologic LSS, our work establishes a foundation for interpreting how non-coding DNA variants in these regions might disrupt protective gene expression to influence vascular disease.
Collapse
Affiliation(s)
- Jan-Renier Moonen
- Vera Moulton Wall Center for Pulmonary Vascular Diseases, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA
- BASE Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - James Chappell
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Minyi Shi
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Tsutomu Shinohara
- Vera Moulton Wall Center for Pulmonary Vascular Diseases, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA
- BASE Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Dan Li
- Vera Moulton Wall Center for Pulmonary Vascular Diseases, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Maxwell R Mumbach
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Fan Zhang
- Vera Moulton Wall Center for Pulmonary Vascular Diseases, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Ramesh V Nair
- Stanford Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Joseph Nasser
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Daniel H Mai
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Shalina Taylor
- Vera Moulton Wall Center for Pulmonary Vascular Diseases, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Lingli Wang
- Vera Moulton Wall Center for Pulmonary Vascular Diseases, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA
- BASE Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Ross J Metzger
- Vera Moulton Wall Center for Pulmonary Vascular Diseases, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Howard Y Chang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Center for Personal Dynamic Regulomes, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Jesse M Engreitz
- BASE Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Michael P Snyder
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Stanford Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Marlene Rabinovitch
- Vera Moulton Wall Center for Pulmonary Vascular Diseases, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- Stanford Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, 94305, USA.
- BASE Initiative, Betty Irene Moore Children's Heart Center, Lucile Packard Children's Hospital, Stanford University School of Medicine, Stanford, CA, 94305, USA.
| |
Collapse
|
523
|
Yang F, Hu T, Cui H. Serum urate and heart failure: a bidirectional Mendelian randomization study. Eur J Prev Cardiol 2022; 29:1570-1578. [PMID: 35578763 DOI: 10.1093/eurjpc/zwac100] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 05/11/2022] [Accepted: 05/12/2022] [Indexed: 11/13/2022]
Abstract
AIMS Observational studies indicate that serum urate level is associated with heart failure (HF). However, whether this association is causal remains controversial, due to confounding factors and reverse causality. We aim to evaluate the causal relationship of genetically predicted serum urate level with HF. METHODS AND RESULTS A bidirectional Mendelian randomization (MR) study was performed. Instrumental variables were obtained from the largest genome-wide association studies of serum urate (457 690 individuals) to date. We obtained summary statistics of HF from HERMES consortium (47 309 cases; 930 014 controls), the FinnGen study (13 087 cases; 195 091 controls), and the UK Biobank study (1088 cases; 360 106 controls). Inverse-variance-weighted method was applied to obtain MR estimates and other statistical methods were conducted in the sensitivity analyses. The reverse MR analysis was performed to evaluate the effect of HF on serum urate levels. Genetically determined serum urate level was associated with HF [odds ratio (OR), 1.07; 95% confidence interval (CI), 1.03-1.10; P = 8.6×10-5]. The main results kept robust in the most sensitivity analyses. The association pattern remained for the HF in FinnGen (OR, 1.10; 95% CI, 1.03-1.19; P = 0.008) and the combined results of three data sources (OR, 1.08; 95% CI, 1.04-1.13; P < 0.001). No consistent evidence was found for the causal effect of HF on serum urate levels. CONCLUSION We provide consistent evidence for the causal effect of genetically predicted serum urate level on HF, but not the reverse effect of HF. Urate-lowering therapy may be of cardiovascular benefit in the prevention of HF.
Collapse
Affiliation(s)
- Fangkun Yang
- Department of Cardiology, Ningbo Hospital of Zhejiang University (Ningbo First Hospital), School of Medicine, Zhejiang University, Ningbo, China
- Department of Cardiology, Second Affiliated Hospital of Zhejiang University, School of Medicine, Zhejiang University, Hangzhou, China
- Cardiology Centre, Ningbo First Hospital, Ningbo University, 59 Liuting Road, Ningbo 315010, China
| | - Teng Hu
- School of Medicine, Ningbo University, Ningbo, China
| | - Hanbin Cui
- Cardiology Centre, Ningbo First Hospital, Ningbo University, 59 Liuting Road, Ningbo 315010, China
| |
Collapse
|
524
|
Allara E, Lee WH, Burgess S, the INVENT consortium, Larsson SC. Genetically predicted cortisol levels and risk of venous thromboembolism. PLoS One 2022; 17:e0272807. [PMID: 35984822 PMCID: PMC9390895 DOI: 10.1371/journal.pone.0272807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Accepted: 07/26/2022] [Indexed: 11/18/2022] Open
Abstract
INTRODUCTION In observational studies, venous thromboembolism (VTE) has been associated with Cushing's syndrome and with persistent mental stress, two conditions associated with higher cortisol levels. However, it remains unknown whether high cortisol levels within the usual range are causally associated with VTE risk. We aimed to assess the association between plasma cortisol levels and VTE risk using Mendelian randomization. METHODS Three genetic variants in the SERPINA1/SERPINA6 locus (rs12589136, rs11621961 and rs2749527) were used to proxy plasma cortisol. The associations of the cortisol-associated genetic variants with VTE were acquired from the INVENT (28 907 cases and 157 243 non-cases) and FinnGen (6913 cases and 169 986 non-cases) consortia. Corresponding data for VTE subtypes were available from the FinnGen consortium and UK Biobank. Two-sample Mendelian randomization analyses (inverse-variance weighted method) were performed. RESULTS Genetic predisposition to higher plasma cortisol levels was associated with a reduced risk of VTE (odds ratio [OR] per one standard deviation increment 0.73, 95% confidence interval [CI] 0.62-0.87, p<0.001). The association was stronger for deep vein thrombosis (OR 0.69, 95% CI 0.55-0.88, p = 0.003) than for pulmonary embolism which did not achieve statistical significance (OR 0.83, 95% CI 0.63-1.09, p = 0.184). Adjusting for genetically predicted systolic blood pressure inverted the direction of the point estimate for VTE, although the resulting CI was wide (OR 1.06, 95% CI 0.70-1.61, p = 0.780). CONCLUSIONS This study provides evidence that genetically predicted plasma cortisol levels in the high end of the normal range are associated with a decreased risk of VTE and that this association may be mediated by blood pressure. This study has implications for the planning of observational studies of cortisol and VTE, suggesting that blood pressure traits should be measured and accounted for.
Collapse
Affiliation(s)
- Elias Allara
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Wei-Hsuan Lee
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Stephen Burgess
- BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- MRC Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
| | | | - Susanna C. Larsson
- Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
- Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| |
Collapse
|
525
|
Life-Course Associations between Blood Pressure-Related Polygenic Risk Scores and Hypertension in the Bogalusa Heart Study. Genes (Basel) 2022; 13:genes13081473. [PMID: 36011384 PMCID: PMC9408577 DOI: 10.3390/genes13081473] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2022] [Revised: 07/30/2022] [Accepted: 08/15/2022] [Indexed: 11/16/2022] Open
Abstract
Genetic information may help to identify individuals at increased risk for hypertension in early life, prior to the manifestation of elevated blood pressure (BP) values. We examined 369 Black and 832 White Bogalusa Heart Study (BHS) participants recruited in childhood and followed for approximately 37 years. The multi-ancestry genome-wide polygenic risk scores (PRSs) for systolic BP (SBP), diastolic BP (DBP), and hypertension were tested for an association with incident hypertension and stage 2 hypertension using Cox proportional hazards models. Race-stratified analyses were adjusted for baseline age, age2, sex, body mass index, genetic principal components, and BP. In Black participants, each standard deviation increase in SBP and DBP PRS conferred a 38% (p = 0.009) and 22% (p = 0.02) increased risk of hypertension and a 74% (p < 0.001) and 50% (p < 0.001) increased risk of stage 2 hypertension, respectively, while no association was observed with the hypertension PRSs. In Whites, each standard deviation increase in SBP, DBP, and hypertension PRS conferred a 24% (p < 0.05), 29% (p = 0.01), and 25% (p < 0.001) increased risk of hypertension, and a 27% (p = 0.08), 29% (0.01), and 42% (p < 0.001) increased risk of stage 2 hypertension, respectively. The addition of BP PRSs to the covariable-only models generally improved the C-statistics (p < 0.05). Multi-ancestry BP PRSs demonstrate the utility of genomic information in the early life prediction of hypertension.
Collapse
|
526
|
Hou T, Li M, Lin H, Zhao Z, Lu J, Wang T, Xu Y, Wang W, Bi Y, Ning G, Xu M. The Causal Effect of Systolic Blood Pressure Lowering on Vascular Outcomes in Diabetes: A Mendelian Randomization Study. J Clin Endocrinol Metab 2022; 107:2616-2625. [PMID: 35703944 DOI: 10.1210/clinem/dgac354] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Indexed: 11/19/2022]
Abstract
CONTEXT The effect of lowering systolic blood pressure (SBP) on clinical outcomes in diabetic patients is controversial. OBJECTIVE We used 2-sample mendelian randomization (MR) to study the causal effect of decreasing SBP on the risk of macrovascular and microvascular outcomes in diabetic patients. METHODS We used 362 SBP-related genetic variants from a large genome-wide association study (n = 299 024) and UK Biobank (n = 375 256) as exposure. We evaluated 5 macrovascular and microvascular complications up to 60 742 cases as outcomes in diabetes, including coronary artery disease (CAD), peripheral artery disease (PAD), nephropathy, retinopathy, and composite complications. All cases were diagnosed together with diabetes. We performed follow-up analyses by conducting 7 sensitivity analyses and comparing the present MR with results in general population, and clinical trials. RESULTS Genetic predisposition of each 10-mm Hg SBP decrease was significantly associated with a 28% decreased risk of CAD (odds ratio [OR]: 0.72; 95% CI, 0.59-0.89; P = .002), a 34% decreased risk of nephropathy (OR: 0.66; 95% CI, 0.54-0.81; P < .001), and a 34% decreased risk of the composite complications (OR: 0.66; 95% CI, 0.58-0.76; P < .001), and was nominally associated with a decreased risk of PAD (OR: 0.69; 95% CI, 0.48-0.99) and retinopathy (OR: 0.90; 95% CI, 0.81-0.99). The MR results in diabetes were similar with that in the general population and clinical trials. CONCLUSION SBP lowering was causally associated with an attenuated risk of diabetic CAD and nephropathy. It provides genetic evidence for the beneficial effect of lifelong SBP control in preventing diabetes-related vascular outcomes.
Collapse
Affiliation(s)
- Tianzhichao Hou
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Hong Lin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| |
Collapse
|
527
|
Ruotsalainen SE, Surakka I, Mars N, Karjalainen J, Kurki M, Kanai M, Krebs K, Graham S, Mishra PP, Mishra BH, Sinisalo J, Palta P, Lehtimäki T, Raitakari O, Milani L, Okada Y, Palotie A, Widen E, Daly MJ, Ripatti S. Inframe insertion and splice site variants in MFGE8 associate with protection against coronary atherosclerosis. Commun Biol 2022; 5:802. [PMID: 35978133 PMCID: PMC9385630 DOI: 10.1038/s42003-022-03552-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2021] [Accepted: 06/06/2022] [Indexed: 11/29/2022] Open
Abstract
Cardiovascular diseases are the leading cause of premature death and disability worldwide, with both genetic and environmental determinants. While genome-wide association studies have identified multiple genetic loci associated with cardiovascular diseases, exact genes driving these associations remain mostly uncovered. Due to Finland's population history, many deleterious and high-impact variants are enriched in the Finnish population giving a possibility to find genetic associations for protein-truncating variants that likely tie the association to a gene and that would not be detected elsewhere. In a large Finnish biobank study FinnGen, we identified an association between an inframe insertion rs534125149 in MFGE8 (encoding lactadherin) and protection against coronary atherosclerosis. This variant is highly enriched in Finland, and the protective association was replicated in meta-analysis of BioBank Japan and Estonian biobank. Additionally, we identified a protective association between splice acceptor variant rs201988637 in MFGE8 and coronary atherosclerosis, independent of the rs534125149, with no significant risk-increasing associations. This variant was also associated with lower pulse pressure, pointing towards a function of MFGE8 in arterial aging also in humans in addition to previous evidence in mice. In conclusion, our results suggest that inhibiting the production of lactadherin could lower the risk for coronary heart disease substantially.
Collapse
Affiliation(s)
- Sanni E Ruotsalainen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Ida Surakka
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Nina Mars
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | | | - Mitja Kurki
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Masahiro Kanai
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Masfsachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Kristi Krebs
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Sarah Graham
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Binisha H Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Juha Sinisalo
- Heart and Lung Center, Helsinki University Hospital and Helsinki University, Helsinki, Finland
| | - Priit Palta
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Olli Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Centre for Population Health Research, University of Turku, Turku University Hospital, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, University of Turku, Turku, Finland
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
| | - Mark J Daly
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic and Translational Genetics Unit, Masfsachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Helsinki, Finland.
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Department of Public Health, Clinicum, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
| |
Collapse
|
528
|
Hoek AG, van Oort S, Elders PJM, Beulens JWJ. Causal Association of Cardiovascular Risk Factors and Lifestyle Behaviors With Peripheral Artery Disease: A Mendelian Randomization Approach. J Am Heart Assoc 2022; 11:e025644. [PMID: 35929454 PMCID: PMC9496309 DOI: 10.1161/jaha.122.025644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Background We investigated the causal associations between the genetic liability to cardiovascular and lifestyle risk factors and peripheral artery disease (PAD), using a Mendelian randomization approach. Methods and Results We performed a 2‐sample inverse‐variance weighted Mendelian randomization analysis, multiple sensitivity analyses to assess pleiotropy and multivariate Mendelian randomization analyses to assess mediating/confounding factors. European‐ancestry genomic summary data (P<5×10−8) for type 2 diabetes, lipid‐fractions, smoking, alcohol and coffee consumption, physical activity, sleep, and education level were selected. Genetic associations with PAD were extracted from the Million‐Veteran‐Program genome‐wide association studies (cases=31 307, controls=211 753, 72% European‐ancestry) and the GoLEAD‐SUMMIT genome‐wide association studies (11 independent genome‐wide association studies, European‐ancestry, cases=12 086, controls=449 548). Associations were categorized as robust (Bonferroni‐significant (P<0.00294), consistent over PAD‐cohorts/sensitivity analyses), suggestive (P value: 0.00294–0.05, associations in 1 PAD‐cohort/inconsistent sensitivity analyses) or not present. Robust evidence for genetic liability to type 2 diabetes, smoking, insomnia, and inverse associations for higher education level with PAD were found. Suggestive evidence for the genetic liability to higher low‐density lipoprotein cholesterol, triglyceride‐levels, alcohol consumption, and inverse associations for high‐density lipoprotein cholesterol, and increased sleep duration were found. No associations were found for physical activity and coffee consumption. However, effects fully attenuated for low‐density lipoprotein cholesterol and triglycerides after correcting for apoB, and for insomnia after correcting for body mass index and lipid‐fractions. Nonsignificant attenuation by potential mediators was observed for education level and type 2 diabetes. Conclusions Detrimental effects of smoking and type 2 diabetes, but not of low‐density lipoprotein cholesterol and triglycerides, on PAD were confirmed. Lower education level and insomnia were identified as novel risk factors for PAD; however, complete mediation for insomnia and incomplete mediation for education level by downstream risk factors was observed.
Collapse
Affiliation(s)
- Anna G Hoek
- Amsterdam UMC location Vrije Universiteit Amsterdam Epidemiology and Data Science Amsterdam The Netherlands.,Amsterdam Cardiovascular Sciences Amsterdam The Netherlands
| | - Sabine van Oort
- Amsterdam UMC location Vrije Universiteit Amsterdam Epidemiology and Data Science Amsterdam The Netherlands.,Amsterdam UMC location Vrije Universiteit Amsterdam General Practice Amsterdam The Netherlands
| | - Petra J M Elders
- Amsterdam UMC location Vrije Universiteit Amsterdam General Practice Amsterdam The Netherlands.,Amsterdam Public Health, Methodology Amsterdam The Netherlands
| | - Joline W J Beulens
- Amsterdam UMC location Vrije Universiteit Amsterdam Epidemiology and Data Science Amsterdam The Netherlands.,Amsterdam Cardiovascular Sciences Amsterdam The Netherlands.,Amsterdam Public Health, Methodology Amsterdam The Netherlands.,University Medical Centre Utrecht Utrecht University, Julius Center for Health Sciences and Primary Care Utrecht The Netherlands
| |
Collapse
|
529
|
Francis CM, Futschik ME, Huang J, Bai W, Sargurupremraj M, Teumer A, Breteler MMB, Petretto E, Ho ASR, Amouyel P, Engelter ST, Bülow R, Völker U, Völzke H, Dörr M, Imtiaz MA, Aziz NA, Lohner V, Ware JS, Debette S, Elliott P, Dehghan A, Matthews PM. Genome-wide associations of aortic distensibility suggest causality for aortic aneurysms and brain white matter hyperintensities. Nat Commun 2022; 13:4505. [PMID: 35922433 PMCID: PMC9349177 DOI: 10.1038/s41467-022-32219-x] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 07/20/2022] [Indexed: 12/13/2022] Open
Abstract
Aortic dimensions and distensibility are key risk factors for aortic aneurysms and dissections, as well as for other cardiovascular and cerebrovascular diseases. We present genome-wide associations of ascending and descending aortic distensibility and area derived from cardiac magnetic resonance imaging (MRI) data of up to 32,590 Caucasian individuals in UK Biobank. We identify 102 loci (including 27 novel associations) tagging genes related to cardiovascular development, extracellular matrix production, smooth muscle cell contraction and heritable aortic diseases. Functional analyses highlight four signalling pathways associated with aortic distensibility (TGF-β, IGF, VEGF and PDGF). We identify distinct sex-specific associations with aortic traits. We develop co-expression networks associated with aortic traits and apply phenome-wide Mendelian randomization (MR-PheWAS), generating evidence for a causal role for aortic distensibility in development of aortic aneurysms. Multivariable MR suggests a causal relationship between aortic distensibility and cerebral white matter hyperintensities, mechanistically linking aortic traits and brain small vessel disease.
Collapse
Affiliation(s)
- Catherine M Francis
- National Heart and Lung Institute, Imperial College London, Programme in Cardiovascular Genetics and Genomics, London, UK
- Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, SW3 6NP, UK
| | - Matthias E Futschik
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC London Institute of Medical Sciences (LMS), Imperial College London, London, W12 0NN, UK
| | - Jian Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Wenjia Bai
- Department of Brain Sciences, Imperial College London, London, UK
- Department of Computing, Imperial College London, London, UK
| | - Muralidharan Sargurupremraj
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Enrico Petretto
- Programme in Cardiovascular & Metabolic Disorders and Centre for Computational Biology, Duke-NUS Medical School, Singapore, 169857, Republic of Singapore
- Institute of Big Data and Artificial Intelligence, China Pharmaceutical University (CPU), 211198, Nanjing, China
- Computational Biology Programme, Faculty of Science, National University of Singapore, Singapore, Singapore
| | - Amanda S R Ho
- Computational Biology Programme, Faculty of Science, National University of Singapore, Singapore, Singapore
| | - Philippe Amouyel
- LabEx DISTALZ-U1167, RID-AGE-Risk Factors and Molecular Determinants of Aging-Related Diseases, University of Lille, Lille, France
- Inserm, U1167, Lille, France
- Centre Hospitalier Universitaire Lille, Lille, France
- Institut Pasteur de Lille, Lille, France
| | - Stefan T Engelter
- Department of Neurology and Stroke Center, University Hospital and University of Basel, Petersgraben 4, CH - 4031, Basel, Switzerland
- Department of Clinical Neurology and Neurorehabilitation, University Department of Geriatric Medicine FELIX PLATTER, University of Basel, Basel, Switzerland
| | - Robin Bülow
- Department of Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Uwe Völker
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Marcus Dörr
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Mohammed-Aslam Imtiaz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - N Ahmad Aziz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Valerie Lohner
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - James S Ware
- National Heart and Lung Institute, Imperial College London, Programme in Cardiovascular Genetics and Genomics, London, UK
- Royal Brompton & Harefield Hospitals, Guy's and St. Thomas' NHS Foundation Trust, London, SW3 6NP, UK
- MRC London Institute of Medical Sciences (LMS), Imperial College London, London, W12 0NN, UK
| | - Stephanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
- Department of Neurology, Institute for Neurodegenerative Diseases, Bordeaux University Hospital - CHU Bordeaux, 33000, Bordeaux, France
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
- Health Data Research (HDR) UK London at Imperial College London, London, UK
- Britsh Heart Foundation Centre of Research Excellence at Imperial College London, London, UK
- National Institute for Health Research Imperial Biomedical Research Centre, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- UK Dementia Research Institute at Imperial College London, London, UK.
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, London, UK.
- UK Dementia Research Institute at Imperial College London, London, UK.
- National Institute for Health Research Imperial Biomedical Research Centre, Imperial College London, London, UK.
| |
Collapse
|
530
|
Tcheandjieu C, Zhu X, Hilliard AT, Clarke SL, Napolioni V, Ma S, Lee KM, Fang H, Chen F, Lu Y, Tsao NL, Raghavan S, Koyama S, Gorman BR, Vujkovic M, Klarin D, Levin MG, Sinnott-Armstrong N, Wojcik GL, Plomondon ME, Maddox TM, Waldo SW, Bick AG, Pyarajan S, Huang J, Song R, Ho YL, Buyske S, Kooperberg C, Haessler J, Loos RJF, Do R, Verbanck M, Chaudhary K, North KE, Avery CL, Graff M, Haiman CA, Le Marchand L, Wilkens LR, Bis JC, Leonard H, Shen B, Lange LA, Giri A, Dikilitas O, Kullo IJ, Stanaway IB, Jarvik GP, Gordon AS, Hebbring S, Namjou B, Kaufman KM, Ito K, Ishigaki K, Kamatani Y, Verma SS, Ritchie MD, Kember RL, Baras A, Lotta LA, Kathiresan S, Hauser ER, Miller DR, Lee JS, Saleheen D, Reaven PD, Cho K, Gaziano JM, Natarajan P, Huffman JE, Voight BF, Rader DJ, Chang KM, Lynch JA, Damrauer SM, Wilson PWF, Tang H, Sun YV, Tsao PS, O'Donnell CJ, Assimes TL. Large-scale genome-wide association study of coronary artery disease in genetically diverse populations. Nat Med 2022; 28:1679-1692. [PMID: 35915156 PMCID: PMC9419655 DOI: 10.1038/s41591-022-01891-3] [Citation(s) in RCA: 189] [Impact Index Per Article: 63.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 06/08/2022] [Indexed: 02/03/2023]
Abstract
We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.
Collapse
Affiliation(s)
- Catherine Tcheandjieu
- VA Palo Alto Health Care System, Palo Alto, CA, USA.
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- Gladstone Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, USA.
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.
| | - Xiang Zhu
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Statistics, Stanford University, Stanford, CA, USA
- Department of Statistics, The Pennsylvania State University, University Park, PA, USA
- Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, USA
| | | | - Shoa L Clarke
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Valerio Napolioni
- School of Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA
| | - Shining Ma
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Kyung Min Lee
- VA Informatics and Computing Infrastructure, VA Salt Lake City Health Care System, Salt Lake City, UT, USA
| | - Huaying Fang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Fei Chen
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Yingchang Lu
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Noah L Tsao
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Sridharan Raghavan
- Medicine Service, VA Eastern Colorado Health Care System, Aurora, CO, USA
- Department of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Satoshi Koyama
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Bryan R Gorman
- VA Boston Healthcare System, Boston, MA, USA
- Booz Allen Hamilton, McLean, VA, USA
| | - Marijana Vujkovic
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Derek Klarin
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- VA Boston Healthcare System, Boston, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Vascular Surgery and Endovascular Therapy, University of Florida School of Medicine, Gainesville, FL, USA
- Stanford University School of Medicine, Stanford, CA, USA
| | - Michael G Levin
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Nasa Sinnott-Armstrong
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Genevieve L Wojcik
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Mary E Plomondon
- Department of Medicine, Rocky Mountain Regional VA Medical Center, Aurora, CO, USA
- CART Program, VHA Office of Quality and Patient Safety, Washington, DC, USA
| | - Thomas M Maddox
- Healthcare Innovation Lab, JC HealthCare/Washington University School of Medicine, St Louis, MO, USA
- Division of Cardiology, Washington University School of Medicine, St Louis, MO, USA
| | - Stephen W Waldo
- Department of Medicine, Rocky Mountain Regional VA Medical Center, Aurora, CO, USA
- CART Program, VHA Office of Quality and Patient Safety, Washington, DC, USA
- Division of Cardiology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Alexander G Bick
- Department of Biomedical Informatics, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Saiju Pyarajan
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jie Huang
- VA Boston Healthcare System, Boston, MA, USA
- Department of Global Health, Peking University School of Public Health, Beijing, China
- School of Public Health and Emergency Management, Southern University of Science and Technology, Shenzhen, China
| | | | - Yuk-Lam Ho
- VA Boston Healthcare System, Boston, MA, USA
| | - Steven Buyske
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Ruth J F Loos
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ron Do
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Marie Verbanck
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- EA 7537 BioSTM, Université de Paris, Paris, France
| | - Kumardeep Chaudhary
- Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Christy L Avery
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Loïc Le Marchand
- Cancer Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Lynne R Wilkens
- Cancer Epidemiology Program, University of Hawaii Cancer Center, University of Hawaii, Honolulu, HI, USA
| | - Joshua C Bis
- Department of Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | - Hampton Leonard
- Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
- Data Tecnica Int'l, LLC, Glen Echo, MD, USA
| | - Botong Shen
- Health Disparities Research Section, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Leslie A Lange
- Department of Medicine, Division of Biomedical Informatics and Personalized Medicine, Aurora, CO, USA
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, Aurora, CO, USA
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Ayush Giri
- Department of Medicine, Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Obstetrics and Gynecology, Division of Quantitative Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ozan Dikilitas
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Iftikhar J Kullo
- Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN, USA
| | - Ian B Stanaway
- Department of Medicine, Division of Nephrology, University of Washington, Seattle, WA, USA
| | - Gail P Jarvik
- Department of Medicine, Medical Genetics, University of Washington School of Medicine, Seattle, WA, USA
- Department of Genome Sciences, University of Washington School of Medicine, Seattle, WA, USA
| | - Adam S Gordon
- Center for Genetic Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Scott Hebbring
- Center for Precision Medicine Research, Marshfield Clinic Research Institute, Marshfield, WI, USA
| | - Bahram Namjou
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Kenneth M Kaufman
- Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Kaoru Ito
- Laboratory for Cardiovascular Genomics and Informatics, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Kazuyoshi Ishigaki
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa, Japan
- Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences - The University of Tokyo, Tokyo, Japan
| | - Shefali S Verma
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute for Biomedical Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rachel L Kember
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Aris Baras
- Regeneron Genetics Center, Tarrytown, NY, USA
| | | | - Sekar Kathiresan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Cardiology Division, Massachusetts General Hospital, Boston, MA, USA
- Verve Therapeutics, Cambridge, MA, USA
| | - Elizabeth R Hauser
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, NC, USA
- Department of Biostatistics and Bioinformatics, Duke University Medical Center, Durham, NC, USA
| | - Donald R Miller
- Center for Healthcare Organization and Implementation Research, Bedford VA Healthcare System, Bedford, MA, USA
- Center for Population Health, Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, MA, USA
| | - Jennifer S Lee
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Danish Saleheen
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, Division of Cardiology, Columbia University, New York, NY, USA
| | - Peter D Reaven
- Phoenix VA Health Care System, Phoenix, AZ, USA
- College of Medicine, University of Arizona, Phoenix, AZ, USA
| | - Kelly Cho
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - J Michael Gaziano
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Pradeep Natarajan
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Cardiology Division, Massachusetts General Hospital, Boston, MA, USA
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA
| | | | - Benjamin F Voight
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Department of Systems Pharmacology and Translational Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Institute of Translational Medicine and Therapeutics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Daniel J Rader
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kyong-Mi Chang
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Julie A Lynch
- VA Salt Lake City Health Care System, Salt Lake City, UT, USA
- College of Nursing and Health Sciences, University of Massachusetts, Boston, MA, USA
| | - Scott M Damrauer
- Department of Surgery, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA, USA
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Peter W F Wilson
- Atlanta VA Medical Center, Atlanta, GA, USA
- Division of Cardiology, Emory University School of Medicine, Atlanta, GA, USA
| | - Hua Tang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA, USA
| | - Yan V Sun
- Atlanta VA Health Care System, Atlanta, GA, USA
- Department of Epidemiology, Emory University Rollins School of Public Health, Atlanta, GA, USA
| | - Philip S Tsao
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Christopher J O'Donnell
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Themistocles L Assimes
- VA Palo Alto Health Care System, Palo Alto, CA, USA.
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- Cardiovascular Institute, Stanford University School of Medicine, Stanford, CA, USA.
- Department of Epidemiology and Population Health, Stanford University School of Medicine, Stanford, CA, USA.
| |
Collapse
|
531
|
Kelly TN, Sun X, He KY, Brown MR, Taliun SAG, Hellwege JN, Irvin MR, Mi X, Brody JA, Franceschini N, Guo X, Hwang SJ, de Vries PS, Gao Y, Moscati A, Nadkarni GN, Yanek LR, Elfassy T, Smith JA, Chung RH, Beitelshees AL, Patki A, Aslibekyan S, Blobner BM, Peralta JM, Assimes TL, Palmas WR, Liu C, Bress AP, Huang Z, Becker LC, Hwa CM, O'Connell JR, Carlson JC, Warren HR, Das S, Giri A, Martin LW, Craig Johnson W, Fox ER, Bottinger EP, Razavi AC, Vaidya D, Chuang LM, Chang YPC, Naseri T, Jain D, Kang HM, Hung AM, Srinivasasainagendra V, Snively BM, Gu D, Montasser ME, Reupena MS, Heavner BD, LeFaive J, Hixson JE, Rice KM, Wang FF, Nielsen JB, Huang J, Khan AT, Zhou W, Nierenberg JL, Laurie CC, Armstrong ND, Shi M, Pan Y, Stilp AM, Emery L, Wong Q, Hawley NL, Minster RL, Curran JE, Munroe PB, Weeks DE, North KE, Tracy RP, Kenny EE, Shimbo D, Chakravarti A, Rich SS, Reiner AP, Blangero J, Redline S, Mitchell BD, Rao DC, Ida Chen YD, Kardia SLR, Kaplan RC, Mathias RA, He J, Psaty BM, Fornage M, Loos RJF, Correa A, Boerwinkle E, Rotter JI, Kooperberg C, Edwards TL, et alKelly TN, Sun X, He KY, Brown MR, Taliun SAG, Hellwege JN, Irvin MR, Mi X, Brody JA, Franceschini N, Guo X, Hwang SJ, de Vries PS, Gao Y, Moscati A, Nadkarni GN, Yanek LR, Elfassy T, Smith JA, Chung RH, Beitelshees AL, Patki A, Aslibekyan S, Blobner BM, Peralta JM, Assimes TL, Palmas WR, Liu C, Bress AP, Huang Z, Becker LC, Hwa CM, O'Connell JR, Carlson JC, Warren HR, Das S, Giri A, Martin LW, Craig Johnson W, Fox ER, Bottinger EP, Razavi AC, Vaidya D, Chuang LM, Chang YPC, Naseri T, Jain D, Kang HM, Hung AM, Srinivasasainagendra V, Snively BM, Gu D, Montasser ME, Reupena MS, Heavner BD, LeFaive J, Hixson JE, Rice KM, Wang FF, Nielsen JB, Huang J, Khan AT, Zhou W, Nierenberg JL, Laurie CC, Armstrong ND, Shi M, Pan Y, Stilp AM, Emery L, Wong Q, Hawley NL, Minster RL, Curran JE, Munroe PB, Weeks DE, North KE, Tracy RP, Kenny EE, Shimbo D, Chakravarti A, Rich SS, Reiner AP, Blangero J, Redline S, Mitchell BD, Rao DC, Ida Chen YD, Kardia SLR, Kaplan RC, Mathias RA, He J, Psaty BM, Fornage M, Loos RJF, Correa A, Boerwinkle E, Rotter JI, Kooperberg C, Edwards TL, Abecasis GR, Zhu X, Levy D, Arnett DK, Morrison AC. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. Hypertension 2022; 79:1656-1667. [PMID: 35652341 PMCID: PMC9593435 DOI: 10.1161/hypertensionaha.122.19324] [Show More Authors] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 05/12/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. METHODS We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. RESULTS Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (P<5×10-8). Among them, a rare intergenic variant at novel locus, LOC100506274, was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; P=4.99×10-8) but not stage-2 analysis (P=0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; P=4.18×10-7) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; P=7.28×10-23). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (P<1×10-6 and P<1×10-4, respectively). DISCUSSION We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.
Collapse
Affiliation(s)
- Tanika N Kelly
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
- Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA
| | - Xiao Sun
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Karen Y He
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.)
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Sarah A Gagliano Taliun
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Jacklyn N Hellwege
- Division of Genetic Medicine, Department of Medicine (J.N.H.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | - Marguerite R Irvin
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Xuenan Mi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle' WA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill (N.F.)
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Shih-Jen Hwang
- National Heart, Lung and Blood Institute, Population Sciences Branch, National Institutes of Health, Framingham, MA (S.-J.H.)
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Yan Gao
- Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson' MS
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Girish N Nadkarni
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
- Department of Medicine (G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Tali Elfassy
- Division of Epidemiology, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami' FL (T.E.)
| | - Jennifer A Smith
- Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor' MI
| | - Ren-Hua Chung
- Institute of Population Sciences, National Health Research Institutes, Taiwan (R.-H.C.)
| | - Amber L Beitelshees
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Amit Patki
- Department of Biostatistics (A.P., V.S.), University of Alabama at Birmingham' AL
| | - Stella Aslibekyan
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Brandon M Blobner
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services (B.M.P.), University of Washington, Seattle' WA
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
| | - Juan M Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Themistocles L Assimes
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford' CA (T.L.A.)
- Division of Cardiology Medicine, Palo Alto VA HealthCare System, Palo Alto' CA (T.L.A.)
| | - Walter R Palmas
- Division of General Medicine, Department of Medicine, Columbia University, New York, NY (W.R.P.)
| | - Chunyu Liu
- Department of Biostatistics, Boston University, Boston' MA (C.L.)
| | - Adam P Bress
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City' UT (A.P.B.)
| | - Zhijie Huang
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Lewis C Becker
- Division of Cardiology, Department of Medicine (L.C.B.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Chii-Min Hwa
- Taichung Veterans General Hospital, Taichung, Taiwan (C.-M.H.)
| | - Jeffrey R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Jenna C Carlson
- Department of Biostatistics, Graduate School of Public Health (J.C.C.), University of Pittsburgh, PA
| | - Helen R Warren
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Centre (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
| | - Sayantan Das
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Ayush Giri
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University, Nashville, TN (A.G.)
| | - Lisa W Martin
- Division of Cardiology, Department of Medicine, George Washington University, Washington, DC (L.W.M.)
| | - W Craig Johnson
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Ervin R Fox
- Division of Cardiology, Department of Medicine (E.R.F.), University of Mississippi Medical Center, Jackson' MS
| | - Erwin P Bottinger
- Hasso Plattner Institute for Digital Health at Mount Sinai (E.P.B.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Alexander C Razavi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Dhananjay Vaidya
- Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei' Taiwan (L.-M.C.)
| | - Yen-Pei C Chang
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia' Samoa (T.N.)
| | - Deepti Jain
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Hyun Min Kang
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Adriana M Hung
- Division of Nephrology and Hypertension, Department of Medicine (A.M.H.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | | | - Beverly M Snively
- Division of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC (B.M.S.)
| | - Dongfeng Gu
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.G., J.H.)
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | | | - Benjamin D Heavner
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Jonathon LeFaive
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - James E Hixson
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Kenneth M Rice
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Fei Fei Wang
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Jonas B Nielsen
- Department of Internal Medicine: Cardiology (J.B.N.), University of Michigan, Ann Arbor' MI
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark (J.B.N.)
| | - Jianfeng Huang
- Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.G., J.H.)
| | - Alyna T Khan
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics (W.Z.), University of Michigan, Ann Arbor' MI
| | - Jovia L Nierenberg
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Cathy C Laurie
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Nicole D Armstrong
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Mengyao Shi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Yang Pan
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Adrienne M Stilp
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Leslie Emery
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Quenna Wong
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Nicola L Hawley
- Department of Chronic Disease Epidemiology, Yale University, New Haven, CT (N.L.H.)
| | - Ryan L Minster
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Patricia B Munroe
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Centre (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
| | - Daniel E Weeks
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
- Department of Biostatistics (D.E.W.), University of Pittsburgh, PA
| | - Kari E North
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle' WA
| | - Russell P Tracy
- Department of Pathology & Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington' VT (R.P.T.)
| | - Eimear E Kenny
- Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson' MS
- Department of Genetics and Genomics (E.E.K.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Daichi Shimbo
- Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY (D.S.)
| | - Aravinda Chakravarti
- Department of Medicine (A.C.), University of Mississippi Medical Center, Jackson' MS
| | - Stephen S Rich
- Center for Public Health, University of Virginia, Charlottesville' VA (S.S.R.)
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (A.P.R., C.K.)
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA (S.R.)
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore' MD (B.D.M.)
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R.)
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Sharon L R Kardia
- Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor' MI
| | - Robert C Kaplan
- Division of Social Medicine, Albert Einstein College of Medicine, Bronx, NY (R.C.K.)
| | - Rasika A Mathias
- Division of Allergy & Clinical Immunology, Department of Medicine (R.A.M.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jiang He
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Bruce M Psaty
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
- Kaiser Permanente Washington Health Research Institute, Seattle' WA (B.M.P.)
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine (M.F.), The University of Texas Health Science Center at Houston' Houston' TX
- Human Genetics Center (M.F.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Ruth J F Loos
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
- The Mindich Child Health and Development Institute (R.J.F.L.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Adolfo Correa
- Center for Human Genetics and Genomics, New York University Grossman School of Medicine, New York, NY (A.C.)
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX (E.B.)
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (A.P.R., C.K.)
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine (T.L.E.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | - Gonçalo R Abecasis
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.)
| | - Daniel Levy
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY (D.K.A.)
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| |
Collapse
|
532
|
Zhang J, Chen Z, Pärna K, van Zon SKR, Snieder H, Thio CHL. Mediators of the association between educational attainment and type 2 diabetes mellitus: a two-step multivariable Mendelian randomisation study. Diabetologia 2022; 65:1364-1374. [PMID: 35482055 PMCID: PMC9283137 DOI: 10.1007/s00125-022-05705-6] [Citation(s) in RCA: 52] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 02/15/2022] [Indexed: 12/25/2022]
Abstract
AIMS/HYPOTHESIS Type 2 diabetes mellitus is a major health burden disproportionately affecting those with lower educational attainment (EA). We aimed to obtain causal estimates of the association between EA and type 2 diabetes and to quantify mediating effects of known modifiable risk factors. METHODS We applied two-step, two-sample multivariable Mendelian randomisation (MR) techniques using SNPs as genetic instruments for exposure and mediators, thereby minimising bias due to confounding and reverse causation. We leveraged summary data on genome-wide association studies for EA, proposed mediators (i.e. BMI, blood pressure, smoking, television watching) and type 2 diabetes. The total effect of EA on type 2 diabetes was decomposed into a direct effect and indirect effects through multiple mediators. Additionally, traditional mediation analysis was performed in a subset of the National Health and Nutrition Examination Survey 2013-2014. RESULTS EA was inversely associated with type 2 diabetes (OR 0.53 for each 4.2 years of schooling; 95% CI 0.49, 0.56). Individually, the largest contributors were BMI (51.18% mediation; 95% CI 46.39%, 55.98%) and television watching (50.79% mediation; 95% CI 19.42%, 82.15%). Combined, the mediators explained 83.93% (95% CI 70.51%, 96.78%) of the EA-type 2 diabetes association. Traditional analysis yielded smaller effects but showed consistent direction and priority ranking of mediators. CONCLUSIONS/INTERPRETATION These results support a potentially causal protective effect of EA against type 2 diabetes, with considerable mediation by a number of modifiable risk factors. Interventions on these factors thus have the potential of substantially reducing the burden of type 2 diabetes attributable to low EA.
Collapse
Affiliation(s)
- Jia Zhang
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Shenzhen Center for Disease Control and Prevention, Shenzhen, Guangdong, China
| | - Zekai Chen
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Katri Pärna
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Sander K R van Zon
- Department of Health Sciences, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Chris H L Thio
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| |
Collapse
|
533
|
Vaura F, Kim H, Udler MS, Salomaa V, Lahti L, Niiranen T, FinnGen*. Multi-Trait Genetic Analysis Reveals Clinically Interpretable Hypertension Subtypes. Circ Genom Precis Med 2022; 15:e003583. [PMID: 35604428 PMCID: PMC9558213 DOI: 10.1161/circgen.121.003583] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background:
Hypertension comprises a heterogeneous range of phenotypes. We asked whether underlying genetic structure could explain a part of this heterogeneity.
Methods:
Our study sample comprised N=198 148 FinnGen participants (56% women, mean age 58 years) and N=21 168 well-phenotyped FINRISK participants (53% women, mean age 50 years). First, we identified genetic hypertension components with an unsupervised Bayesian non-negative matrix factorization algorithm using public genome-wide association data for 144 genetic hypertension variants and 16 clinical traits. For these components, we computed their (1) cross-sectional associations with clinical traits in FINRISK using linear regression and (2) longitudinal associations with incident adverse outcomes in FinnGen using Cox regression.
Results:
We observed 4 genetic hypertension components corresponding to recognizable clinical phenotypes: obesity (high body mass index), dyslipidemia (low high-density lipoprotein cholesterol and high triglycerides), hypolipidemia (low low-density lipoprotein cholesterol and low total cholesterol), and short stature. In FINRISK, all hypertension components had robust associations with their respective clinical characteristics. In FinnGen, the Obesity component was associated with increased diabetes risk (hazard ratio per 1 SD increase 1.08 [Bonferroni corrected CI, 1.05–1.10]) and the Hypolipidemia component with increased autoimmune disease risk (hazard ratio per 1 SD increase 1.05 [Bonferroni corrected CI, 1.03–1.07]). In addition, all hypertension components were related to both hypertension and cardiovascular disease.
Conclusions:
Our unsupervised analysis demonstrates that the genetic basis of hypertension can be understood as a mixture of 4 broad, clinically interpretable components capturing disease heterogeneity. These components could be used to stratify individuals into specific genetic subtypes and, therefore, to benefit personalized health care and pharmaceutical research.
Collapse
Affiliation(s)
- Felix Vaura
- Department of Internal Medicine (F.V., T.N.), University of Turku, Turku, Finland
| | - Hyunkyung Kim
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston (H.K., M.U.)
- Broad Institute of MIT and Harvard, Cambridge, MA (H.K., M.U.)
| | - Miriam S. Udler
- Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston (H.K., M.U.)
| | - Veikko Salomaa
- Department of Public Health & Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland (V.S., T.N.)
| | - Leo Lahti
- Department of Computing (L.L.), University of Turku, Turku, Finland
| | - Teemu Niiranen
- Department of Internal Medicine (F.V., T.N.), University of Turku, Turku, Finland
- Department of Public Health & Welfare, Finnish Institute for Health and Welfare, Helsinki, Finland (V.S., T.N.)
| | | |
Collapse
|
534
|
Fujii R, Hishida A, Nakatochi M, Tsuboi Y, Suzuki K, Kondo T, Ikezaki H, Hara M, Okada R, Tamura T, Shimoshikiryo I, Suzuki S, Koyama T, Kuriki K, Takashima N, Arisawa K, Momozawa Y, Kubo M, Takeuchi K, Wakai K, Matsuo K, Tanaka K, Miura K, Kita Y, Takezaki T, Nagase H, Mikami H, Uehara R, Narimatsu H. Associations of Genome-Wide Polygenic Risk Score and Risk Factors With Hypertension in a Japanese Population. Circ Genom Precis Med 2022; 15:e003612. [DOI: 10.1161/circgen.121.003612] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Background:
Although many polygenic risk scores (PRS) for cardiovascular traits have been developed in European populations, it is an urgent task to construct a PRS and to evaluate its ability in non-European populations. We developed a genome-wide PRS for blood pressure in a Japanese population and examined the associations between this PRS and hypertension prevalence.
Methods:
We performed a cross-sectional study in 11 252 Japanese individuals who participated in the J-MICC (Japan Multi-Institutional Collaborative Cohort) study. Using publicly available GWAS summary statistics from Biobank Japan, we developed the PRS in the target data (n=7876). With >30 000 single nucleotide polymorphisms, we evaluated PRS performance in the test data (n=3376). Hypertension was defined as systolic blood pressure of 130 mm Hg or more, or diastolic blood pressure of 85 mm Hg or more, or taking an antihypertensive drug.
Results:
Compared with the middle PRS quintile, the prevalence of hypertension at the top PRS quintile was higher independently from traditional risk factors (odds ratio, 1.73 [95% CI, 1.32–2.27]). The difference of mean systolic blood pressure and diastolic blood pressure between the middle and the top PRS quintile was 4.55 (95% CI, 2.26–6.85) and 2.32 (95% CI, 0.86–3.78) mm Hg, respectively. Subgroups reflecting combinations of Japanese PRS and modifiable lifestyles and factors (smoking, alcohol intake, sedentary time, and obesity) were associated with the prevalence of hypertension. A European-derived PRS was not associated with hypertension in our participants.
Conclusions:
A PRS for blood pressure was significantly associated with hypertension and BP traits in a general Japanese population. Our findings also highlighted the importance of a combination of PRS and risk factors for identifying high-risk subgroups.
Collapse
Affiliation(s)
- Ryosuke Fujii
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Japan (R.F., Y.T., K.S.), Nagoya University Graduate School of Medicine, Nagoya, Japan
- Division of interactive Medical & Healthcare Systems, Department of Integrated Health Sciences (R.F., T. Kondo), Nagoya University Graduate School of Medicine, Nagoya, Japan
- Institute for Biomedicine, Eurac Research (affiliated to the University of Lübeck), Bolzano/Bozen, Italy (R.F.)
| | - Asahi Hishida
- Department of Preventive Medicine (A.H., R.O., T.T., K.T., K.W.), Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Masahiro Nakatochi
- Public Health Informatics Unit, Department of Integrated Health Sciences (M.N.), Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Yoshiki Tsuboi
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Japan (R.F., Y.T., K.S.), Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Koji Suzuki
- Department of Preventive Medical Sciences, Fujita Health University School of Medical Sciences, Toyoake, Japan (R.F., Y.T., K.S.), Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Takaaki Kondo
- Division of interactive Medical & Healthcare Systems, Department of Integrated Health Sciences (R.F., T. Kondo), Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Hiroaki Ikezaki
- Department of Comprehensive General Internal Medicine, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan (H.I.)
| | - Megumi Hara
- Department of Preventive Medicine, Faculty of Medicine, Saga University, Saga, Japan (M.H.)
| | - Rieko Okada
- Department of Preventive Medicine (A.H., R.O., T.T., K.T., K.W.), Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Takashi Tamura
- Department of Preventive Medicine (A.H., R.O., T.T., K.T., K.W.), Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Ippei Shimoshikiryo
- Department of International Island & Community Medicine, Kagoshima University Graduate School of Medical & Dental Sciences, Kagoshima, Japan (I.S.)
| | - Sadao Suzuki
- Department of Public Health, Nagoya City University Graduate School of Medical Sciences, Nagoya, Japan (S.S.)
| | - Teruhide Koyama
- Department of Epidemiology for Community Health & Medicine, Kyoto Prefectural University of Medicine, Kyoto, Japan (T. Koyama)
| | - Kiyonori Kuriki
- Laboratory of Public Health, Division of Nutritional Sciences, School of Food & Nutritional Sciences, University of Shizuoka, Shizuoka, Shizuoka (K.K.)
| | - Naoyuki Takashima
- Department of Public Health, Shiga University of Medical Science, Otsu, Japan (N.T.)
- Department of Public Health, Kindai University Faculty of Medicine, Osaka, Japan (N.T.)
| | - Kokichi Arisawa
- Department of Preventive Medicine, Tokushima University Graduate School of Biomedical Scinces, Tokushima, Japan (K.A.)
| | - Yukihide Momozawa
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Kanagawa, Japan (Y.M., M.K.)
| | - Michiaki Kubo
- Laboratory for Genotyping Development, Center for Integrative Medical Sciences, RIKEN, Kanagawa, Japan (Y.M., M.K.)
| | - Kenji Takeuchi
- Department of Preventive Medicine (A.H., R.O., T.T., K.T., K.W.), Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Kenji Wakai
- Department of Preventive Medicine (A.H., R.O., T.T., K.T., K.W.), Nagoya University Graduate School of Medicine, Nagoya, Japan
| | | | | | | | | | | | | | | | | | | |
Collapse
|
535
|
Cui J, Chasman DI, Raychaudhuri S, Xu C, Ridker PM, Solomon DH, Karlson EW. Genetics are not likely to offer clinically useful predictions for elevated liver enzyme levels in patients using low dose methotrexate. Semin Arthritis Rheum 2022; 55:152036. [PMID: 35671649 PMCID: PMC10782828 DOI: 10.1016/j.semarthrit.2022.152036] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 05/25/2022] [Accepted: 05/27/2022] [Indexed: 12/12/2022]
Abstract
OBJECTIVE To examine genetic influence on the risk of elevations in liver function tests (AST and ALT) among patients using low-dose methotrexate (LD-MTX). METHODS We examined data from the LD-MTX arm of a randomized double-blind placebo-controlled trial conducted among subjects without rheumatic disease. Genome wide association studies (GWAS) were performed in subjects of European ancestry to test the association between single nucleotide polymorphisms (SNPs) and the log transformed maximum values of AST, ALT, and dichotomized outcome with AST or ALT > 2 times upper limit of normal (ULN). The association between variants in MTX metabolism candidate genes and the outcomes was also tested. Furthermore, associations between a drug induced liver injury (DILI) weighted genetic risk score (wGRS) and the outcomes were tested, combining 10 SNPs and 11 classical HLA alleles associated with DILI. RESULTS In genome-wide genetic analyses among 1,429 subjects of European ancestry who were randomized to receive LD-MTX, two SNPs reached genome wide significance for association with log transformed maximum ALT. We observed associations between established candidate genes in MTX pharmacogenetics and log transformed maximum AST and ALT, as well as in dichotomized outcome with AST or ALT > 2 x ULN. There was no association between DILI wGRS or candidate variants and AST, ALT, or DILI response. CONCLUSIONS Modest evidence was observed that common variants affected AST and ALT levels in subjects of European ancestry on LD-MTX, but this genetic effect is not useful as a clinical predictor of MTX toxicity.
Collapse
Affiliation(s)
- Jing Cui
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital USA.
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital USA; Division of Genetics, Brigham and Women's Hospital, Boston, MA USA
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital USA; Division of Genetics, Brigham and Women's Hospital, Boston, MA USA
| | - Chang Xu
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital USA
| | - Daniel H Solomon
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital USA
| | - Elizabeth W Karlson
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital USA
| |
Collapse
|
536
|
Clifton L, Collister JA, Liu X, Littlejohns TJ, Hunter DJ. Assessing agreement between different polygenic risk scores in the UK Biobank. Sci Rep 2022; 12:12812. [PMID: 35896674 PMCID: PMC9329440 DOI: 10.1038/s41598-022-17012-6] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 07/19/2022] [Indexed: 11/16/2022] Open
Abstract
Polygenic risk scores (PRS) are proposed for use in clinical and research settings for risk stratification. However, there are limited investigations on how different PRS diverge from each other in risk prediction of individuals. We compared two recently published PRS for each of three conditions, breast cancer, hypertension and dementia, to assess the stability of using these algorithms for risk prediction in a single large population. We used imputed genotyping data from the UK Biobank prospective cohort, limited to the White British subset. We found that: (1) 20% or more of SNPs in the first PRS were not represented in the more recent PRS for all three diseases, by the same SNP or a surrogate with R2 > 0.8 by linkage disequilibrium (LD). (2) Although the difference in the area under the receiver operating characteristic curve (AUC) obtained using the two PRS is hardly appreciable for all three diseases, there were large differences in individual risk prediction between the two PRS. For instance, for each disease, of those classified in the top 5% of risk by the first PRS, over 60% were not so classified by the second PRS. We found substantial discordance between different PRS for the same disease, indicating that individuals could receive different medical advice depending on which PRS is used to assess their genetic susceptibility. It is desirable to resolve this uncertainty before using PRS for risk stratification in clinical settings.
Collapse
Affiliation(s)
- Lei Clifton
- Nuffield Department of Population Health, University of Oxford, Oxford, UK.
| | | | - Xiaonan Liu
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | | | - David J Hunter
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| |
Collapse
|
537
|
Armstrong ND, Srinivasasainagendra V, Chekka LMS, Nguyen NHK, Nahid NA, Jones AC, Tanner RM, Hidalgo BA, Limdi NA, Claas SA, Gong Y, McDonough CW, Cooper-DeHoff RM, Johnson JA, Tiwari HK, Arnett DK, Irvin MR. Genetic Contributors of Efficacy and Adverse Metabolic Effects of Chlorthalidone in African Americans from the Genetics of Hypertension Associated Treatments (GenHAT) Study. Genes (Basel) 2022; 13:1260. [PMID: 35886043 PMCID: PMC9319619 DOI: 10.3390/genes13071260] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 07/01/2022] [Accepted: 07/07/2022] [Indexed: 02/05/2023] Open
Abstract
Hypertension is a leading risk factor for cardiovascular disease mortality. African Americans (AAs) have the highest prevalence of hypertension in the United States, and to alleviate the burden of hypertension in this population, better control of blood pressure (BP) is needed. Previous studies have shown considerable interpersonal differences in BP response to antihypertensive treatment, suggesting a genetic component. Utilizing data from 4297 AA participants randomized to chlorthalidone from the Genetics of Hypertension Associated Treatments (GenHAT) study, we aimed to identify variants associated with the efficacy of chlorthalidone. An additional aim was to find variants that contributed to changes in fasting glucose (FG) in these individuals. We performed genome-wide association analyses on the change of systolic and diastolic BP (SBP and DBP) over six months and FG levels over 24 months of treatment. We sought replication in the International Consortia of Pharmacogenomics Studies. We identified eight variants statistically associated with BP response and nine variants associated with FG response. One suggestive LINC02211-CDH9 intergenic variant was marginally replicated with the same direction of effect. Given the impact of hypertension in AAs, this study implies that understanding the genetic background for BP control and glucose changes during chlorthalidone treatment may help prevent adverse cardiovascular events in this population.
Collapse
Affiliation(s)
- Nicole D. Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (N.D.A.); (A.C.J.); (R.M.T.); (B.A.H.)
| | - Vinodh Srinivasasainagendra
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (V.S.); (H.K.T.)
| | - Lakshmi Manasa S. Chekka
- Division of Applied Regulatory Sciences, Center for Drug Evaluation and Research, Silver Spring, MD 20903, USA;
| | - Nam H. K. Nguyen
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32611, USA; (N.H.K.N.); (N.A.N.); (Y.G.); (C.W.M.); (R.M.C.-D.); (J.A.J.)
| | - Noor A. Nahid
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32611, USA; (N.H.K.N.); (N.A.N.); (Y.G.); (C.W.M.); (R.M.C.-D.); (J.A.J.)
| | - Alana C. Jones
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (N.D.A.); (A.C.J.); (R.M.T.); (B.A.H.)
- Medical Scientist Training Program, University of Alabama at Birmingham, Birmingham, AL 35294, USA
| | - Rikki M. Tanner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (N.D.A.); (A.C.J.); (R.M.T.); (B.A.H.)
| | - Bertha A. Hidalgo
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (N.D.A.); (A.C.J.); (R.M.T.); (B.A.H.)
| | - Nita A. Limdi
- Department of Neurology, University of Alabama at Birmingham, Birmingham, AL 35294, USA;
| | - Steven A. Claas
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY 40506, USA; (S.A.C.); (D.K.A.)
| | - Yan Gong
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32611, USA; (N.H.K.N.); (N.A.N.); (Y.G.); (C.W.M.); (R.M.C.-D.); (J.A.J.)
| | - Caitrin W. McDonough
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32611, USA; (N.H.K.N.); (N.A.N.); (Y.G.); (C.W.M.); (R.M.C.-D.); (J.A.J.)
| | - Rhonda M. Cooper-DeHoff
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32611, USA; (N.H.K.N.); (N.A.N.); (Y.G.); (C.W.M.); (R.M.C.-D.); (J.A.J.)
- Division of Cardiovascular Medicine, Department of Medicine, University of Florida, Gainesville, FL 32611, USA
| | - Julie A. Johnson
- Department of Pharmacotherapy and Translational Research, College of Pharmacy, University of Florida, Gainesville, FL 32611, USA; (N.H.K.N.); (N.A.N.); (Y.G.); (C.W.M.); (R.M.C.-D.); (J.A.J.)
- Division of Cardiovascular Medicine, Department of Medicine, University of Florida, Gainesville, FL 32611, USA
| | - Hemant K. Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (V.S.); (H.K.T.)
| | - Donna K. Arnett
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, KY 40506, USA; (S.A.C.); (D.K.A.)
- Deans Office, College of Public Health, University of Kentucky, Lexington, KY 40506, USA
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (N.D.A.); (A.C.J.); (R.M.T.); (B.A.H.)
| |
Collapse
|
538
|
Unravelling the Distinct Effects of Systolic and Diastolic Blood Pressure Using Mendelian Randomisation. Genes (Basel) 2022; 13:genes13071226. [PMID: 35886009 PMCID: PMC9323763 DOI: 10.3390/genes13071226] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/05/2022] [Accepted: 07/06/2022] [Indexed: 12/25/2022] Open
Abstract
A true discrepancy between the effect of systolic blood pressure (SBP) and diastolic blood pressure (DBP) on cardiovascular (CV) outcomes remains unclear. This study performed two-sample Mendelian randomization (MR) using genetic instruments that exclusively predict SBP, DBP or both to dissect the independent effect of SBP and DBP on a range of CV outcomes. Genetic predisposition to higher SBP and DBP was associated with increased risk of coronary artery disease (CAD), myocardial infarction (MI), stroke, heart failure (HF), atrial fibrillation (AF), chronic kidney disease (CKD) and type 2 diabetes mellitus (T2DM). Genetically proxied SBP exclusively was associated with CAD (OR 1.18, 95% CI: 1.03–1.36, per 10 mmHg), stroke (1.44[1.28–1.62]), ischemic stroke (1.49[1.30–1.69]), HF (1.41[1.20–1.65]), AF (1.28[1.15–1.43]), and T2DM (1.2[1.13–1.46]). Genetically proxied DBP exclusively was associated with stroke (1.21[1.06–1.37], per 5 mmHg), ischemic stroke (1.24[1.09–1.41]), stroke small-vessel (1.35[1.10–1.65]) and CAD (1.19[1.00–1.41]). Multivariable MR using exclusive SBP and DBP instruments showed the predominant effect of SBP on CAD (1.23[1.05–1.44], per 10 mmHg), stroke (1.39[1.20–1.60]), ischemic stroke (1.44[1.25–1.67]), HF (1.42[1.18–1.71]), AF (1.26[1.10–1.43]) and T2DM (1.31[1.14–1.52]). The discrepancy between effects of SBP and DBP on outcomes warrants further studies on underpinning mechanisms which may be amenable to therapeutic targeting.
Collapse
|
539
|
Large-Scale Multi-Omics Studies Provide New Insights into Blood Pressure Regulation. Int J Mol Sci 2022; 23:ijms23147557. [PMID: 35886906 PMCID: PMC9323755 DOI: 10.3390/ijms23147557] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 06/27/2022] [Accepted: 06/29/2022] [Indexed: 12/04/2022] Open
Abstract
Recent genome-wide association studies uncovered part of blood pressure’s heritability. However, there is still a vast gap between genetics and biology that needs to be bridged. Here, we followed up blood pressure genome-wide summary statistics of over 750,000 individuals, leveraging comprehensive epigenomic and transcriptomic data from blood with a follow-up in cardiovascular tissues to prioritise likely causal genes and underlying blood pressure mechanisms. We first prioritised genes based on coding consequences, multilayer molecular associations, blood pressure-associated expression levels, and coregulation evidence. Next, we followed up the prioritised genes in multilayer studies of genomics, epigenomics, and transcriptomics, functional enrichment, and their potential suitability as drug targets. Our analyses yielded 1880 likely causal genes for blood pressure, tens of which are targets of the available licensed drugs. We identified 34 novel genes for blood pressure, supported by more than one source of biological evidence. Twenty-eight (82%) of these new genes were successfully replicated by transcriptome-wide association analyses in a large independent cohort (n = ~220,000). We also found a substantial mediating role for epigenetic regulation of the prioritised genes. Our results provide new insights into genetic regulation of blood pressure in terms of likely causal genes and involved biological pathways offering opportunities for future translation into clinical practice.
Collapse
|
540
|
Weng Z, Liu Q, Yan Q, Liang J, Zhang X, Xu J, Li W, Xu C, Gu A. Associations of genetic risk factors and air pollution with incident hypertension among participants in the UK Biobank study. CHEMOSPHERE 2022; 299:134398. [PMID: 35339527 DOI: 10.1016/j.chemosphere.2022.134398] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 03/19/2022] [Accepted: 03/19/2022] [Indexed: 06/14/2023]
Abstract
The purposes of this study were to quantify the association of the combination of air pollution and genetic risk factors with hypertension and explore the interactions between air pollution and genetic risk. This study included 391,366 participants of European ancestry initially free from pre-existing hypertension in the UK Biobank. Exposure to ambient air pollutants, including particulate matter (PM2.5 PM2.5-10, and PM10), nitrogen dioxide (NO2) and nitrogen oxides (NOX), was estimated through land use regression modelling, and the associations between air pollutants and the incidence of hypertension were investigated using a Cox proportional hazards model adjusted for covariates. Furthermore, we established a polygenic risk score for hypertension and assessed the combined effect of genetic susceptibility and air pollution on incident hypertension. The results showed significant associations between the risk of hypertension and exposure to PM2.5 (hazard ratio [HR]: 1.41, 95% confidence interval [CI]: 1.29-1.53; per 10 μg/m3), PM10 (1.05, 1.00-1.09; per 10 μg/m3), and NOX (1.01, 1.01-1.02 per 10 μg/m3). Additive effects of PM2.5 and NOX exposure and genetic risk were observed. Compared to individuals with a low genetic risk and low air pollution exposure, participants with high air pollution exposure and a high genetic risk had a significantly increased risk of hypertension (PM2.5: 71% (66%-76%), PM10: 59% (55%-64%), NOX: 65% (60%-70%)). Our results indicate that long-term exposure to air pollution is associated with an increased risk of hypertension, especially in individuals with a high genetic risk.
Collapse
Affiliation(s)
- Zhenkun Weng
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Qian Liu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Qing Yan
- Department of Neurosurgery, Children's Hospital of Nanjing Medical University, Nanjing, China
| | - Jingjia Liang
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Xin Zhang
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Jin Xu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China; Department of Maternal, Child, and Adolescent Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Wenxiang Li
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China
| | - Cheng Xu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China.
| | - Aihua Gu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Key Laboratory of Modern Toxicology of Ministry of Education, Center for Global Health, Nanjing Medical University, Nanjing, China.
| |
Collapse
|
541
|
Marques-Vidal P, Chekanova V, Vaucher J. Association between genetic risk of high SBP and hypertension control: the CoLaus|PsyColaus study. J Hypertens 2022; 40:1388-1393. [PMID: 35703291 PMCID: PMC10004752 DOI: 10.1097/hjh.0000000000003158] [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: 01/28/2022] [Accepted: 03/14/2022] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To assess whether a genetic risk score (GRS) for high SBP is associated with poor control of hypertension. METHODS Data from the four waves of a population-based, prospective study conducted in Lausanne, Switzerland. Control of hypertension was defined based on SBP less than 140 mmHg and DBP less than 90 mmHg. A weighted GRS was computed from 362 SNPs. RESULTS Overall, 1097 (51% men, mean age 61 years), 1126 (53% men, age 65 years), 1020 (52% men, age 69 years) and 809 (50% men, age 71 years) participants treated for hypertension were selected from the baseline (2003-2006), first (2009-2012), second (2014-2017) and third (2018-2021) surveys. Hypertension control rates were 50, 58, 52 and 59% for the baseline, first, second and third surveys, respectively. No association was found between GRS and hypertension control: multivariate-adjusted mean ± standard error for controlled vs. uncontrolled participants: 9.30 ± 0.09 vs. 9.50 ± 0.09 ( P = 0.12); 9.32 ± 0.08 vs. 9.53 ± 0.10 ( P = 0.10); 9.17 ± 0.08 vs. 9.34 ± 0.11 ( P = 0.22), and 9.18 ± 0.09 vs. 9.46 ± 0.11 ( P = 0.07) for the baseline, first, second and third surveys, respectively. Power analysis showed that a minimum of 3410 people treated for hypertension would be necessary to detect an association between the GRS and hypertension control rates. Notably, positive associations between the GRS and SBP levels were found among participants not treated for hypertension, with Spearman correlations ranging between 0.05 and 0.09 (all P < 0.05). CONCLUSION Using a GRS associated with SBP levels is not predictive of hypertension control. The use of GRS for hypertension management is not warranted in clinical practice. http://links.lww.com/HJH/C26.
Collapse
Affiliation(s)
- Pedro Marques-Vidal
- Lausanne university hospital and university of Lausanne, Lausanne, Switzerland
| | | | - Julien Vaucher
- Lausanne university hospital and university of Lausanne, Lausanne, Switzerland
| |
Collapse
|
542
|
Canoy D, Nazarzadeh M, Copland E, Bidel Z, Rao S, Li Y, Rahimi K. How Much Lowering of Blood Pressure Is Required to Prevent Cardiovascular Disease in Patients With and Without Previous Cardiovascular Disease? Curr Cardiol Rep 2022; 24:851-860. [PMID: 35524880 PMCID: PMC9288358 DOI: 10.1007/s11886-022-01706-4] [Citation(s) in RCA: 48] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/19/2022] [Indexed: 11/12/2022]
Abstract
PURPOSE OF REVIEW To review the recent large-scale randomised evidence on pharmacologic reduction in blood pressure for the primary and secondary prevention of cardiovascular disease. RECENT FINDINGS Based on findings of the meta-analysis of individual participant-level data from 48 randomised clinical trials and involving 344,716 participants with mean age of 65 years, the relative reduction in the risk of developing major cardiovascular events was proportional to the magnitude of achieved reduction in blood pressure. For each 5-mmHg reduction in systolic blood pressure, the risk of developing cardiovascular events fell by 10% (hazard ratio [HR] (95% confidence interval [CI], 0.90 [0.88 to 0.92]). When participants were stratified by their history of cardiovascular disease, the HRs (95% CI) in those with and without previous cardiovascular disease were 0.89 (0.86 to 0.92) and 0.91 (0.89 to 0.94), respectively, with no significant heterogeneity in these effects (adjusted P for interaction = 1.0). When these patient groups were further stratified by their baseline systolic blood pressure in increments of 10 mmHg from < 120 to ≥ 170 mmHg, there was no significant heterogeneity in the relative risk reduction across these categories in people with or without previous cardiovascular disease (adjusted P for interaction were 1.00 and 0.28, respectively). Pharmacologic lowering of blood pressure was effective in preventing major cardiovascular disease events both in people with or without previous cardiovascular disease, which was not modified by their baseline blood pressure level. Treatment effects were shown to be proportional to the intensity of blood pressure reduction, but even modest blood pressure reduction, on average, can lead to meaningful gains in the prevention of incident or recurrent cardiovascular disease.
Collapse
Affiliation(s)
- Dexter Canoy
- Deep Medicine, Nuffield Department of Women’s and Reproductive Health, University of Oxford, Hayes House 1F, 75 George St, Oxford, OX1 2BQ UK
- National Institutes of Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Milad Nazarzadeh
- Deep Medicine, Nuffield Department of Women’s and Reproductive Health, University of Oxford, Hayes House 1F, 75 George St, Oxford, OX1 2BQ UK
| | - Emma Copland
- Deep Medicine, Nuffield Department of Women’s and Reproductive Health, University of Oxford, Hayes House 1F, 75 George St, Oxford, OX1 2BQ UK
- National Institutes of Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Zeinab Bidel
- Deep Medicine, Nuffield Department of Women’s and Reproductive Health, University of Oxford, Hayes House 1F, 75 George St, Oxford, OX1 2BQ UK
- National Institutes of Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Shihir Rao
- Deep Medicine, Nuffield Department of Women’s and Reproductive Health, University of Oxford, Hayes House 1F, 75 George St, Oxford, OX1 2BQ UK
| | - Yikuan Li
- Deep Medicine, Nuffield Department of Women’s and Reproductive Health, University of Oxford, Hayes House 1F, 75 George St, Oxford, OX1 2BQ UK
| | - Kazem Rahimi
- Deep Medicine, Nuffield Department of Women’s and Reproductive Health, University of Oxford, Hayes House 1F, 75 George St, Oxford, OX1 2BQ UK
- National Institutes of Health Research Oxford Biomedical Research Centre, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| |
Collapse
|
543
|
Parcha V, Irvin MR, Lange LA, Armstrong ND, Pampana A, Meyer M, Judd SE, Arora G, Arora P. Corin Missense Variants, Blood Pressure, and Hypertension in 11 322 Black Individuals: Insights From REGARDS and the Jackson Heart Study. J Am Heart Assoc 2022; 11:e025582. [PMID: 35699180 PMCID: PMC9238660 DOI: 10.1161/jaha.121.025582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 04/27/2022] [Indexed: 11/18/2022]
Abstract
Background Corin enzyme contributes to the processing of inactive natriuretic peptides to bioactive hormones. In Black individuals, Corin gene variants (rs111253292 [Q568P] and rs75770792 [T555I]) have been previously reported to have a modest association with blood pressure (BP) and hypertension. Methods and Results We evaluated the association of Corin genotype with BP traits, prevalent hypertension, and incident hypertension among self-identified 11 322 Black Americans in the REGARDS (Reasons for Geographic and Racial Differences in Stroke) study and the JHS (Jackson Heart Study) using multivariable-adjusted regression modeling. Multivariable-adjusted genotype-stratified differences in NT-proBNP (N-terminal pro-B-type natriuretic peptide) and BNP (B-type natriuretic peptide) levels were assessed. Genotype-stratified NPPA and NPPB expression differences in healthy organ donor left atrial and left ventricular heart tissue (N=15) were also examined. The rs111253292 genotype was not associated with systolic BP (β±SE, 0.42±0.58; -1.24±0.82), diastolic BP (0.51±0.33; -0.41±0.46), mean arterial pressure (0.48±0.38; -0.68±0.51), and prevalent hypertension (odds ratio [OR], 0.93 [95% CI, 0.80-1.09]; OR, 0.79 [95% CI, 0.61-1.01]) in both REGARDS and JHS, respectively. The rs75770792 genotype was not associated with systolic BP (0.48±0.58; -1.26±0.81), diastolic BP (0.52±0.33; -0.33±0.45), mean arterial pressure (0.50±0.38; -0.63±0.50), and prevalent hypertension (OR, 1.02 [95% CI, 0.84-1.23]; OR, 0.87 [95% CI, 0.67-1.13]) in both cohorts, respectively. The Corin genotype was also not associated with incident hypertension (OR, 1.35 [95% CI, 0.94-1.93]; OR, 0.95 [95% CI, 0.64-1.39]) in the study cohorts. The NT-proBNP levels in REGARDS and BNP levels in JHS were similar between the Corin genotype groups. In heart tissue, the NPPA and NPPB expression was similar between the genotype groups. Conclusions Corin gene variants observed more commonly in Black individuals are not associated with differences in NP expression, circulating NP levels, and BP or hypertension as previously reported in candidate gene studies. Understanding the genetic determinants of complex cardiovascular traits in underrepresented populations requires further evaluation.
Collapse
Affiliation(s)
- Vibhu Parcha
- Division of Cardiovascular DiseaseUniversity of Alabama at BirminghamBirminghamAL
| | | | - Leslie A. Lange
- Division of Biomedical Informatics and Personalized MedicineDepartment of MedicineUniversity of Colorado School of MedicineAuroraCO
- Department of EpidemiologyUniversity of Colorado School of Public HealthAuroraCO
| | | | - Akhil Pampana
- Division of Cardiovascular DiseaseUniversity of Alabama at BirminghamBirminghamAL
| | - Mariah Meyer
- Division of Biomedical Informatics and Personalized MedicineDepartment of MedicineUniversity of Colorado School of MedicineAuroraCO
| | - Suzanne E. Judd
- Department of BiostatisticsUniversity of Alabama at BirminghamBirminghamAL
| | - Garima Arora
- Division of Cardiovascular DiseaseUniversity of Alabama at BirminghamBirminghamAL
| | - Pankaj Arora
- Division of Cardiovascular DiseaseUniversity of Alabama at BirminghamBirminghamAL
- Section of CardiologyBirmingham Veterans Affairs Medical CenterBirminghamAL
| |
Collapse
|
544
|
Kurniansyah N, Goodman MO, Kelly TN, Elfassy T, Wiggins KL, Bis JC, Guo X, Palmas W, Taylor KD, Lin HJ, Haessler J, Gao Y, Shimbo D, Smith JA, Yu B, Feofanova EV, Smit RAJ, Wang Z, Hwang SJ, Liu S, Wassertheil-Smoller S, Manson JE, Lloyd-Jones DM, Rich SS, Loos RJF, Redline S, Correa A, Kooperberg C, Fornage M, Kaplan RC, Psaty BM, Rotter JI, Arnett DK, Morrison AC, Franceschini N, Levy D, Sofer T. A multi-ethnic polygenic risk score is associated with hypertension prevalence and progression throughout adulthood. Nat Commun 2022; 13:3549. [PMID: 35729114 PMCID: PMC9213527 DOI: 10.1038/s41467-022-31080-2] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 05/31/2022] [Indexed: 12/12/2022] Open
Abstract
In a multi-stage analysis of 52,436 individuals aged 17-90 across diverse cohorts and biobanks, we train, test, and evaluate a polygenic risk score (PRS) for hypertension risk and progression. The PRS is trained using genome-wide association studies (GWAS) for systolic, diastolic blood pressure, and hypertension, respectively. For each trait, PRS is selected by optimizing the coefficient of variation (CV) across estimated effect sizes from multiple potential PRS using the same GWAS, after which the 3 trait-specific PRSs are combined via an unweighted sum called "PRSsum", forming the HTN-PRS. The HTN-PRS is associated with both prevalent and incident hypertension at 4-6 years of follow up. This association is further confirmed in age-stratified analysis. In an independent biobank of 40,201 individuals, the HTN-PRS is confirmed to be predictive of increased risk for coronary artery disease, ischemic stroke, type 2 diabetes, and chronic kidney disease.
Collapse
Affiliation(s)
- Nuzulul Kurniansyah
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Matthew O Goodman
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Tanika N Kelly
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Tali Elfassy
- Department of Medicine, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Walter Palmas
- Department of Medicine, Columbia University Medical Center, New York, NY, USA
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Henry J Lin
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jeffrey Haessler
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Yan Gao
- The Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS, USA
| | - Daichi Shimbo
- Department of Medicine, Columbia University Irving Medical Center, New York, NY, USA
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Bing Yu
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Elena V Feofanova
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Roelof A J Smit
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Zhe Wang
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shih-Jen Hwang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Simin Liu
- Center for Global Cardiometabolic Health and Departments of Epidemiology, Medicine, and Surgery, Brown University, Providence, RI, USA
| | - Sylvia Wassertheil-Smoller
- Department of Epidemiology & Population Health, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - JoAnn E Manson
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Adolfo Correa
- Departments of Medicine and Pediatrics, University of Mississippi Medical Center, Jackson, MS, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Robert C Kaplan
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Daniel Levy
- The Population Sciences Branch of the National Heart, Lung and Blood Institute, Bethesda, MD, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| |
Collapse
|
545
|
Zhang N, Wang Y, Chen Z, Liu D, Tse G, Korantzopoulos P, Letsas KP, Goudis CA, Lip GYH, Li G, Zhang Z, Liu T. Circulating Vitamin D Concentrations and Risk of Atrial Fibrillation: A Mendelian Randomization Study Using Non-deficient Range Summary Statistics. Front Nutr 2022; 9:842392. [PMID: 35782933 PMCID: PMC9248862 DOI: 10.3389/fnut.2022.842392] [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: 12/23/2021] [Accepted: 04/13/2022] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND AND AIMS Vitamin D deficiency is a common disorder and has been linked with atrial fibrillation (AF) in several observational studies, although the causal relationships remain unclear. We conducted a Mendelian randomization (MR) analysis to determine the causal association between serum 25-hydroxyvitamin D [25(OH)D] concentrations and AF. METHODS AND RESULTS The analyses were performed using summary statistics obtained for single-nucleotide polymorphisms (SNPs) identified from large genome-wide association meta-analyses conducted on serum 25(OH)D (N = 79,366) and AF (N = 1,030,836). Six SNPs related to serum 25(OH)D were used as instrumental variables. The association between 25(OH)D and AF was estimated using both the fixed-effect and random-effects inverse variance weighted (IVW) method. The MR analyses found no evidence to support a causal association between circulating 25(OH)D level and risk of AF using random-effects IVW (odds ratio per unit increase in log 25(OH)D = 1.003, 95% CI, 0.841-1.196; P = 0.976) or fixed-effect IVW method (OR = 1.003, 95% CI, 0.876-1.148; P = 0.968). Sensitivity analyses yielded similar results. No heterogeneity and directional pleiotropy were detected. CONCLUSION Using summary statistics, this MR study suggests that genetically predicted circulating vitamin D concentrations, especially for a non-deficient range, were not causally associated with AF in the general population. Future studies using non-linear design and focusing on the vitamin D deficiency population are needed to further evaluate the causal effect of vitamin D concentrations on AF.
Collapse
Affiliation(s)
- Nan Zhang
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China
| | - Yueying Wang
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China
| | - Ziliang Chen
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China
| | - Daiqi Liu
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China
| | - Gary Tse
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China
- Kent and Medway Medical School, Canterbury, United Kingdom
- Epidemiology Research Unit, Cardiovascular Analytics Group, Hong Kong, China
| | | | - Konstantinos P. Letsas
- Arrhythmia Unit, Laboratory of Cardiac Pacing and Electrophysiology, Onassis Cardiac Surgery Center, Athens, Greece
| | | | - Gregory Y. H. Lip
- Liverpool Centre for Cardiovascular Science, University of Liverpool and Liverpool Heart and Chest Hospital, Liverpool, United Kingdom
- Department of Clinical Medicine, Aalborg University, Aalborg, Denmark
| | - Guangping Li
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China
| | - Zhiwei Zhang
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China
| | - Tong Liu
- Tianjin Key Laboratory of Ionic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China
| |
Collapse
|
546
|
Vaitinadin NS, Shi M, Shaffer CM, Farber-Eger E, Lowery BD, Agrawal V, Gupta DK, Roden DM, Wells QS, Mosley JD. Genetic Determinants of Body Mass Index and Fasting Glucose Are Mediators of Grade 1 Diastolic Dysfunction. J Am Heart Assoc 2022; 11:e025578. [PMID: 35656995 PMCID: PMC9238715 DOI: 10.1161/jaha.122.025578] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background Early (grade 1) cardiac left ventricular diastolic dysfunction (G1DD) increases the risk for heart failure with preserved ejection fraction and may improve with aggressive risk factor modification. Type 2 diabetes, obesity, hypertension, and coronary heart disease are associated with increased incidence of diastolic dysfunction. The genetic drivers of G1DD are not defined. Methods and Results We curated genotyped European ancestry G1DD cases (n=668) and controls with normal diastolic function (n=1772) from Vanderbilt's biobank. G1DD status was explored through (1) an additive model genome-wide association study, (2) shared polygenic risk through logistic regression, and (3) instrumental variable analysis using 2-sample Mendelian randomization (the inverse-variance weighted method, Mendelian randomization-Egger, and median) to determine potential modifiable risk factors. There were no common single nucleotide polymorphisms significantly associated with G1DD status. A polygenic risk score for BMI was significantly associated with increased G1DD risk (odds ratio [OR], 1.20 for 1-SD increase in BMI [95% CI, 1.08-1.32]; P=0.0003). The association was confirmed by the inverse-variance weighted method (OR, 1.89 [95% CI, 1.37-2.61]). Among the candidate mediators for BMI, only fasting glucose was significantly associated with G1DD status by the inverse-variance weighted method (OR, 4.14 for 1-SD increase in fasting glucose [95% CI, 1.55-11.02]; P=0.005). Multivariable Mendelian randomization showed a modest attenuation of the BMI association (OR, 1.84 [95% CI, 1.35-2.52]) when adjusting for fasting glucose. Conclusions These data suggest that a genetic predisposition to elevated BMI increases the risk for G1DD. Part of this effect may be mediated through altered glucose homeostasis.
Collapse
Affiliation(s)
| | - Mingjian Shi
- Department of Biomedical Informatics Vanderbilt University Medical Center Nashville TN
| | | | - Eric Farber-Eger
- Department of Medicine Vanderbilt University Medical Center Nashville TN
| | - Brandon D Lowery
- Department of Medicine Vanderbilt University Medical Center Nashville TN
| | - Vineet Agrawal
- Department of Medicine Vanderbilt University Medical Center Nashville TN
| | - Deepak K Gupta
- Department of Medicine Vanderbilt University Medical Center Nashville TN
| | - Dan M Roden
- Department of Medicine Vanderbilt University Medical Center Nashville TN.,Department of Pharmacology Vanderbilt University Nashville TN
| | - Quinn S Wells
- Department of Medicine Vanderbilt University Medical Center Nashville TN.,Department of Biomedical Informatics Vanderbilt University Medical Center Nashville TN
| | - Jonathan D Mosley
- Department of Medicine Vanderbilt University Medical Center Nashville TN.,Department of Biomedical Informatics Vanderbilt University Medical Center Nashville TN
| |
Collapse
|
547
|
Ackland GL, Abbott TEF. Hypotension as a marker or mediator of perioperative organ injury: a narrative review. Br J Anaesth 2022; 128:915-930. [PMID: 35151462 PMCID: PMC9204667 DOI: 10.1016/j.bja.2022.01.012] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 12/16/2021] [Accepted: 01/08/2022] [Indexed: 12/21/2022] Open
Abstract
Perioperative hypotension has been repeatedly associated with organ injury and worse outcome, yet many interventions to reduce morbidity by attempting to avoid or reverse hypotension have floundered. In part, this reflects uncertainty as to what threshold of hypotension is relevant in the perioperative setting. Shifting population-based definitions for hypertension, plus uncertainty regarding individualised norms before surgery, both present major challenges in constructing useful clinical guidelines that may help improve clinical outcomes. Aside from these major pragmatic challenges, a wealth of biological mechanisms that underpin the development of higher blood pressure, particularly with increasing age, suggest that hypotension (however defined) or lower blood pressure per se does not account solely for developing organ injury after major surgery. The mosaic theory of hypertension, first proposed more than 60 yr ago, incorporates multiple, complementary mechanistic pathways through which clinical (macrovascular) attempts to minimise perioperative organ injury may unintentionally subvert protective or adaptive pathways that are fundamental in shaping the integrative host response to injury and inflammation. Consideration of the mosaic framework is critical for a more complete understanding of the perioperative response to acute sterile and infectious inflammation. The largely arbitrary treatment of perioperative blood pressure remains rudimentary in the context of multiple complex adaptive hypertensive endotypes, defined by distinct functional or pathobiological mechanisms, including the regulation of reactive oxygen species, autonomic dysfunction, and inflammation. Developing coherent strategies for the management of perioperative hypotension requires smarter, mechanistically solid interventions delivered by RCTs where observer bias is minimised.
Collapse
Affiliation(s)
- Gareth L Ackland
- Translational Medicine and Therapeutics, William Harvey Research Institute, Queen Mary University of London, London, UK.
| | - Tom E F Abbott
- Translational Medicine and Therapeutics, William Harvey Research Institute, Queen Mary University of London, London, UK
| |
Collapse
|
548
|
Burgess S, Chirinos JA, Damrauer SM, Gill D. Genetically Predicted Pulse Pressure and Risk of Abdominal Aortic Aneurysm: A Mendelian Randomization Analysis. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2022; 15:e003575. [PMID: 35522177 PMCID: PMC9213080 DOI: 10.1161/circgen.121.003575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/02/2022]
Affiliation(s)
- Stephen Burgess
- Medical Research Council Biostatistics Unit, Cambridge Institute of Public Health, United Kingdom (S.B.)
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, United Kingdom (S.B.)
| | - Julio A. Chirinos
- Division of Cardiovascular Medicine, Hospital of the University of Pennsylvania, University of Pennsylvania Perelman School of Medicine, Philadelphia (J.A.C.)
- Departments of Surgery and Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia (J.A.C., S.M.D.)
| | - Scott M. Damrauer
- Corporal Michael J. Crescenz VA Medical Center, Philadelphia, PA (S.M.D.)
| | - Dipender Gill
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London (D.G.)
- Clinical Pharmacology Group, St George’s University Hospitals NHS Foundation Trust (D.G.)
- Clinical Pharmacology and Therapeutics Section, Institute for Infection and Immunity, St George’s, University of London (D.G.)
- Novo Nordisk Research Centre Oxford, United Kingdom (D.G.)
| |
Collapse
|
549
|
Oftedal G. Proportionality of single nucleotide causation. STUDIES IN HISTORY AND PHILOSOPHY OF SCIENCE 2022; 93:215-222. [PMID: 35580376 DOI: 10.1016/j.shpsa.2022.04.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/28/2021] [Revised: 03/07/2022] [Accepted: 04/20/2022] [Indexed: 06/15/2023]
Abstract
Assessing the proportionality of causal relationships help us pick out the most relevant causes of an effect. In this paper, I nuance and apply the concept of proportionality from the philosophy of causation debate to the mapping of associations between variations in single nucleotides in the DNA and complex phenotypic traits, such as cancer, bipolar disorder, and happiness. I discuss under what circumstances single nucleotides, as far as these can be understood as causes, may satisfy the criterion of proportionality in an interventionist understanding of causality. I suggest that the overall relatively low stability and explanatory power of such variants may indicate that, in the causation of complex phenotypic traits, there are alternative causal levels that are more proportional than the level of nucleotides. I suggest network modules as candidates for more proportional organism-internal causes of complex phenotypes. Additionally, I address the broadness of many phenotypic traits investigated in GWAS, as well as the selection between several different proportional causes of an effect.
Collapse
Affiliation(s)
- Gry Oftedal
- Centre for Philosophy and the Sciences (CPS), Department of Philosophy, Classics, History of Art and Ideas, University of Oslo, Postboks 1020 Blindern, 0315, Oslo, Norway.
| |
Collapse
|
550
|
McGurk KA, Farrell L, Kendall AC, Keavney BD, Nicolaou A. Genetic analyses of circulating PUFA-derived mediators identifies heritable dihydroxyeicosatrienoic acid species. Prostaglandins Other Lipid Mediat 2022; 160:106638. [PMID: 35472599 DOI: 10.1016/j.prostaglandins.2022.106638] [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: 12/13/2021] [Revised: 03/30/2022] [Accepted: 04/20/2022] [Indexed: 10/18/2022]
Abstract
Estimates of heritability are the first step in identifying a trait with substantial variation due to genetic factors. Large-scale genetic analyses can identify the DNA variants that influence the levels of circulating lipid species and the statistical technique Mendelian randomisation can use these DNA variants to address potential causality of these lipids in disease. We estimated the heritability of plasma eicosanoids, octadecanoids and docosanoids to identify those lipid species with substantial heritability. We analysed plasma lipid mediators in 31 White British families (196 participants) ascertained for high blood pressure and deeply clinically and biochemically phenotyped over a 25-year period. We found that the dihydroxyeicosatrienoic acid (DHET) species, 11,12-DHET and 14,15-DHET, products of arachidonic acid metabolism by cytochrome P450 (CYP) monooxygenase and soluble epoxide hydrolase (sEH), exhibited substantial heritability (h2 = 33%-37%; Padj<0.05). Identification of these two heritable bioactive lipid species allows for future large-scale, targeted, lipidomics-genomics analyses to address causality in cardiovascular and other diseases.
Collapse
Affiliation(s)
- Kathryn A McGurk
- Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK; Laboratory for Lipidomics and Lipid Research, Division of Pharmacy and Optometry, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Laura Farrell
- Laboratory for Lipidomics and Lipid Research, Division of Pharmacy and Optometry, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Alexandra C Kendall
- Laboratory for Lipidomics and Lipid Research, Division of Pharmacy and Optometry, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Bernard D Keavney
- Manchester Heart Centre, Manchester University NHS Foundation Trust, UK
| | - Anna Nicolaou
- Laboratory for Lipidomics and Lipid Research, Division of Pharmacy and Optometry, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.
| |
Collapse
|