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Alkis T, Luo X, Wall K, Brody J, Bartz T, Chang PP, Norby FL, Hoogeveen RC, Morrison AC, Ballantyne CM, Coresh J, Boerwinkle E, Psaty BM, Shah AM, Yu B. A polygenic risk score of atrial fibrillation improves prediction of lifetime risk for heart failure. ESC Heart Fail 2024; 11:1086-1096. [PMID: 38258344 DOI: 10.1002/ehf2.14665] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Revised: 11/01/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
AIMS Heart failure (HF) has shared genetic architecture with its risk factors: atrial fibrillation (AF), body mass index (BMI), coronary heart disease (CHD), systolic blood pressure (SBP), and type 2 diabetes (T2D). We aim to assess the association and risk prediction performance of risk-factor polygenic risk scores (PRSs) for incident HF and its subtypes in bi-racial populations. METHODS AND RESULTS Five PRSs were constructed for AF, BMI, CHD, SBP, and T2D in White participants of the Atherosclerosis Risk in Communities (ARIC) study. The associations between PRSs and incident HF and its subtypes were assessed using Cox models, and the risk prediction performance of PRSs was assessed using C statistics. Replication was performed in the ARIC study Black and Cardiovascular Health Study (CHS) White participants. In 8624 ARIC study Whites, 1922 (31% cumulative incidence) HF cases developed over 30 years of follow-up. PRSs of AF, BMI, and CHD were associated with incident HF (P < 0.001), where PRSAF showed the strongest association [hazard ratio (HR): 1.47, 95% confidence interval (CI): 1.41-1.53]. Only the addition of PRSAF to the ARIC study HF risk equation improved C statistics for 10 year risk prediction from 0.812 to 0.829 (∆C: 0.017, 95% CI: 0.009-0.026). The PRSAF was associated with both incident HF with reduced ejection fraction (HR: 1.43, 95% CI: 1.27-1.60) and incident HF with preserved ejection fraction (HR: 1.46, 95% CI: 1.33-1.62). The associations between PRSAF and incident HF and its subtypes, as well as the improved risk prediction, were replicated in the ARIC study Blacks and the CHS Whites (P < 0.050). Protein analyses revealed that N-terminal pro-brain natriuretic peptide and other 98 proteins were associated with PRSAF. CONCLUSIONS The PRSAF was associated with incident HF and its subtypes and had significant incremental value over an established HF risk prediction equation.
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Affiliation(s)
- Taryn Alkis
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xi Luo
- Department of Biostatistics and Data Science, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Katherine Wall
- Department of Biostatistics and Data Science, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jennifer Brody
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Traci Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA
| | - Patricia P Chang
- Division of Cardiology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Faye L Norby
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Ron C Hoogeveen
- Department of Medicine, Baylor College of Medicine, Houston, TX, USA
| | - Alanna C Morrison
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Amil M Shah
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX, USA
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2
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Nogal A, Alkis T, Lee Y, Kifer D, Hu J, Murphy RA, Huang Z, Wang-Sattler R, Kastenmüler G, Linkohr B, Barrios C, Crespo M, Gieger C, Peters A, Price J, Rexrode KM, Yu B, Menni C. Predictive metabolites for incident myocardial infarction: a two-step meta-analysis of individual patient data from six cohorts comprising 7897 individuals from the COnsortium of METabolomics Studies. Cardiovasc Res 2023; 119:2743-2754. [PMID: 37706562 PMCID: PMC10757581 DOI: 10.1093/cvr/cvad147] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 06/28/2023] [Accepted: 07/18/2023] [Indexed: 09/15/2023] Open
Abstract
AIMS Myocardial infarction (MI) is a major cause of death and disability worldwide. Most metabolomics studies investigating metabolites predicting MI are limited by the participant number and/or the demographic diversity. We sought to identify biomarkers of incident MI in the COnsortium of METabolomics Studies. METHODS AND RESULTS We included 7897 individuals aged on average 66 years from six intercontinental cohorts with blood metabolomic profiling (n = 1428 metabolites, of which 168 were present in at least three cohorts with over 80% prevalence) and MI information (1373 cases). We performed a two-stage individual patient data meta-analysis. We first assessed the associations between circulating metabolites and incident MI for each cohort adjusting for traditional risk factors and then performed a fixed effect inverse variance meta-analysis to pull the results together. Finally, we conducted a pathway enrichment analysis to identify potential pathways linked to MI. On meta-analysis, 56 metabolites including 21 lipids and 17 amino acids were associated with incident MI after adjusting for multiple testing (false discovery rate < 0.05), and 10 were novel. The largest increased risk was observed for the carbohydrate mannitol/sorbitol {hazard ratio [HR] [95% confidence interval (CI)] = 1.40 [1.26-1.56], P < 0.001}, whereas the largest decrease in risk was found for glutamine [HR (95% CI) = 0.74 (0.67-0.82), P < 0.001]. Moreover, the identified metabolites were significantly enriched (corrected P < 0.05) in pathways previously linked with cardiovascular diseases, including aminoacyl-tRNA biosynthesis. CONCLUSIONS In the most comprehensive metabolomic study of incident MI to date, 10 novel metabolites were associated with MI. Metabolite profiles might help to identify high-risk individuals before disease onset. Further research is needed to fully understand the mechanisms of action and elaborate pathway findings.
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Affiliation(s)
- Ana Nogal
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, Westminster Bridge Road, SE1 7EH London, UK
| | - Taryn Alkis
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St, Suite E407, Houston, 77030 TX, USA
| | - Yura Lee
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St, Suite E407, Houston, 77030 TX, USA
| | - Domagoj Kifer
- Faculty of Pharmacy and Biochemistry, University of Zagreb, Zagreb, Croatia
| | - Jie Hu
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Rachel A Murphy
- Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | - Zhe Huang
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Rui Wang-Sattler
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Gabi Kastenmüler
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Birgit Linkohr
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Clara Barrios
- Department of Nephrology, Hospital del Mar, Institut Hospital del Mar d´Investigacions Mediques, Barcelona, Spain
| | - Marta Crespo
- Department of Nephrology, Hospital del Mar, Institut Hospital del Mar d´Investigacions Mediques, Barcelona, Spain
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Jackie Price
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - Kathryn M Rexrode
- Division of Women’s Health, Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, 1200 Pressler St, Suite E407, Houston, 77030 TX, USA
| | - Cristina Menni
- Department of Twin Research, King’s College London, St Thomas’ Hospital Campus, Westminster Bridge Road, SE1 7EH London, UK
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3
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Feofanova EV, Brown MR, Alkis T, Manuel AM, Li X, Tahir UA, Li Z, Mendez KM, Kelly RS, Qi Q, Chen H, Larson MG, Lemaitre RN, Morrison AC, Grieser C, Wong KE, Gerszten RE, Zhao Z, Lasky-Su J, Yu B. Author Correction: Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations. Nat Commun 2023; 14:6611. [PMID: 37857625 PMCID: PMC10587143 DOI: 10.1038/s41467-023-42472-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023] Open
Affiliation(s)
- Elena V Feofanova
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
| | - Michael R Brown
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
| | - Taryn Alkis
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
| | - Astrid M Manuel
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xihao Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Usman A Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Zilin Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kevin M Mendez
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, USA
| | - Rachel S Kelly
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Han Chen
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Martin G Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Alanna C Morrison
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
| | | | | | - Robert E Gerszten
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Zhongming Zhao
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jessica Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Bing Yu
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA.
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4
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Feofanova EV, Brown MR, Alkis T, Manuel AM, Li X, Tahir UA, Li Z, Mendez KM, Kelly RS, Qi Q, Chen H, Larson MG, Lemaitre RN, Morrison AC, Grieser C, Wong KE, Gerszten RE, Zhao Z, Lasky-Su J, Yu B. Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations. Nat Commun 2023; 14:3111. [PMID: 37253714 PMCID: PMC10229598 DOI: 10.1038/s41467-023-38800-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 05/16/2023] [Indexed: 06/01/2023] Open
Abstract
Circulating metabolite levels may reflect the state of the human organism in health and disease, however, the genetic architecture of metabolites is not fully understood. We have performed a whole-genome sequencing association analysis of both common and rare variants in up to 11,840 multi-ethnic participants from five studies with up to 1666 circulating metabolites. We have discovered 1985 novel variant-metabolite associations, and validated 761 locus-metabolite associations reported previously. Seventy-nine novel variant-metabolite associations have been replicated, including three genetic loci located on the X chromosome that have demonstrated its involvement in metabolic regulation. Gene-based analysis have provided further support for seven metabolite-replicated loci pairs and their biologically plausible genes. Among those novel replicated variant-metabolite pairs, follow-up analyses have revealed that 26 metabolites have colocalized with 21 tissues, seven metabolite-disease outcome associations have been putatively causal, and 7 metabolites might be regulated by plasma protein levels. Our results have depicted the genetic contribution to circulating metabolite levels, providing additional insights into understanding human disease.
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Affiliation(s)
- Elena V Feofanova
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
| | - Michael R Brown
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
| | - Taryn Alkis
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
| | - Astrid M Manuel
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Xihao Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Usman A Tahir
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Zilin Li
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kevin M Mendez
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, USA
| | - Rachel S Kelly
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Qibin Qi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Han Chen
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Martin G Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Rozenn N Lemaitre
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, USA
| | - Alanna C Morrison
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
| | | | | | - Robert E Gerszten
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Zhongming Zhao
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Jessica Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Bing Yu
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center, Houston, TX, USA.
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5
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Moon EH, Alkis T, Liu G, Matsushita K, Hoogeveen RC, Ballantyne CM, Claggett B, Qi Q, Kaplan RC, Rodriguez CJ, Shah AM, Yu B. Abstract P196: Metabolomic Associations With Cardiac Function and Incident Heart Failure in Multi-Ethnic Populations. Circulation 2023. [DOI: 10.1161/circ.147.suppl_1.p196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
Introduction:
Measures of cardiac structure and function provide important diagnostic and prognostic information for heart failure (HF). Few studies have assessed the associations of circulating metabolites with cardiac structure and function.
Hypothesis:
We hypothesize that circulating metabolites that reflect aging process are associated with cardiac structure and function measures and incident HF.
Methods:
Participants from the Atherosclerosis Risk in Communities (ARIC) study visit 5 and the Hispanic Community Health Study / Study of Latinos (HCHS/SOL) study visit 1 who had serum metabolite measures but not prevalent HF were included. Linear regressions were used to examine the associations of metabolites with ten cardiac structure and function variables adjusting for clinical risk factors in each race and study strata, followed by random-effect meta-analyses. The Cox regression was applied to examine the relationship between those identified metabolites and incident HF post visit 5 in ARIC.
Results:
Among 589 analyzed metabolites, 179 were associated with cardiac structure or function measures in 706 Blacks, 3,358 Whites, and 1,380 Hispanics (FDR < 0.05). Forty-one metabolites were related to two or more measures, where 22 were associated with incident HF (308 HF cases, p<0.05, Figure). Metabolites were more associated with cardiac size or diastolic function compared to systolic function measures, i.e., C-glycosyltryptophan, an amino acid that is strongly correlated with age, was positively associated with left ventricular mass index (LVMI) and left atrial volume index(LVAI), as well as an increased risk of HF (HR=1.48); and dodecadienoate (12:2), a dicarboxylate that may have anti-aging property, was negatively associated with LVMI and LVAI, as well as a decreased risk of HF (HR=0.84).
Conclusions:
We identified multiple metabolites associated with cardiac structure and function measures in multi-ethnic populations, highlighting metabolic pathways in aging and their impact on HF.
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Affiliation(s)
- Eun Hye Moon
- Dept of Epidemiology, Human Genetics, and Environmental Sciences, Sch of Public Health, The Univ of Texas Health Science Cntr at Houston, Houston, TX
| | - Taryn Alkis
- Dept of Epidemiology, Human Genetics, and Environmental Sciences, Sch of Public Health, The Univ of Texas Health Science Cntr at Houston, Houston, TX
| | - Guning Liu
- Dept of Epidemiology, Human Genetics, and Environmental Sciences, Sch of Public Health, The Univ of Texas Health Science Cntr at Houston, Houston, TX
| | - Kunihiro Matsushita
- Dept of Epidemiology, Johns Hopkins Bloomberg Sch of Public Health, Baltimore, MD
| | | | | | - Brian Claggett
- Cardiovascular Div, Brigham and Women’s Hosp, Boston, MA
| | - Qibin Qi
- Dept of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Robert C Kaplan
- Dept of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Carlos J Rodriguez
- Depts of Medicine, Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Amil M Shah
- Cardiovascular Div, Brigham and Women’s Hosp, Boston, MA
| | - Bing Yu
- Dept of Epidemiology, Human Genetics, and Environmental Sciences, Sch of Public Health, The Univ of Texas Health Science Cntr at Houston, Houston, TX
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6
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Louca P, Nogal A, Moskal A, Goulding NJ, Shipley MJ, Alkis T, Lindbohm JV, Hu J, Kifer D, Wang N, Chawes B, Rexrode KM, Ben-Shlomo Y, Kivimaki M, Murphy RA, Yu B, Gunter MJ, Suhre K, Lawlor DA, Mangino M, Menni C. Cross-Sectional Blood Metabolite Markers of Hypertension: A Multicohort Analysis of 44,306 Individuals from the COnsortium of METabolomics Studies. Metabolites 2022; 12:601. [PMID: 35888725 PMCID: PMC9324896 DOI: 10.3390/metabo12070601] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 05/27/2022] [Accepted: 06/09/2022] [Indexed: 12/30/2022] Open
Abstract
Hypertension is the main modifiable risk factor for cardiovascular morbidity and mortality but discovering molecular mechanisms for targeted treatment has been challenging. Here we investigate associations of blood metabolite markers with hypertension by integrating data from nine intercontinental cohorts from the COnsortium of METabolomics Studies. We included 44,306 individuals with circulating metabolites (up to 813). Metabolites were aligned and inverse normalised to allow intra-platform comparison. Logistic models adjusting for covariates were performed in each cohort and results were combined using random-effect inverse-variance meta-analyses adjusting for multiple testing. We further conducted canonical pathway analysis to investigate the pathways underlying the hypertension-associated metabolites. In 12,479 hypertensive cases and 31,827 controls without renal impairment, we identified 38 metabolites, associated with hypertension after adjusting for age, sex, body mass index, ethnicity, and multiple testing. Of these, 32 metabolite associations, predominantly lipid (steroids and fatty acyls) and organic acids (amino-, hydroxy-, and keto-acids) remained after further adjusting for comorbidities and dietary intake. Among the identified metabolites, 5 were novel, including 2 bile acids, 2 glycerophospholipids, and ketoleucine. Pathway analysis further implicates the role of the amino-acids, serine/glycine, and bile acids in hypertension regulation. In the largest cross-sectional hypertension-metabolomics study to date, we identify 32 circulating metabolites (of which 5 novel and 27 confirmed) that are potentially actionable targets for intervention. Further in-vivo studies are needed to identify their specific role in the aetiology or progression of hypertension.
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Affiliation(s)
- Panayiotis Louca
- Department of Twin Research, King’s College London, London SE1 7EH, UK; (P.L.); (A.N.); (M.M.)
| | - Ana Nogal
- Department of Twin Research, King’s College London, London SE1 7EH, UK; (P.L.); (A.N.); (M.M.)
| | - Aurélie Moskal
- Nutrition and Metabolism Section, International Agency for Research on Cancer, 69372 Lyon, France; (A.M.); (M.J.G.)
| | - Neil J. Goulding
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK; (N.J.G.); (Y.B.-S.); (D.A.L.)
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
| | - Martin J. Shipley
- Department Epidemiology and Public Health, University College London, London WC1E 7HB, UK; (M.J.S.); (J.V.L.); (M.K.)
| | - Taryn Alkis
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center, Houston, TX 77030, USA; (T.A.); (B.Y.)
| | - Joni V. Lindbohm
- Department Epidemiology and Public Health, University College London, London WC1E 7HB, UK; (M.J.S.); (J.V.L.); (M.K.)
- Clinicum, Department of Public Health, University of Helsinki, P.O. Box 20 Helsinki, Finland
| | - Jie Hu
- Division of Women’s Health, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA; (J.H.); (K.M.R.)
| | - Domagoj Kifer
- Faculty of Pharmacy and Biochemistry, University of Zagreb, 10000 Zagreb, Croatia;
| | - Ni Wang
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, 2820 Gentofte, Denmark; (N.W.); (B.C.)
- Department of Biotechnology and Biomedicine, Technical University of Denmark, 2800 Kongens Lyngby, Denmark
| | - Bo Chawes
- Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, 2820 Gentofte, Denmark; (N.W.); (B.C.)
| | - Kathryn M. Rexrode
- Division of Women’s Health, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA; (J.H.); (K.M.R.)
| | - Yoav Ben-Shlomo
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK; (N.J.G.); (Y.B.-S.); (D.A.L.)
- NIHR Applied Research Collaboration West, University Hospitals Bristol and Weston National Health Service Foundation Trust, Bristol BS1 2NT, UK
| | - Mika Kivimaki
- Department Epidemiology and Public Health, University College London, London WC1E 7HB, UK; (M.J.S.); (J.V.L.); (M.K.)
| | - Rachel A. Murphy
- School of Population and Public Health, University of British Columbia, Vancouver, BC V6T 1Z3, Canada;
- Cancer Control Research, BC Cancer, Vancouver, BC V5Z 1G1, Canada
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center, Houston, TX 77030, USA; (T.A.); (B.Y.)
| | - Marc J. Gunter
- Nutrition and Metabolism Section, International Agency for Research on Cancer, 69372 Lyon, France; (A.M.); (M.J.G.)
| | - Karsten Suhre
- Department of Biophysics and Physiology, Weill Cornell Medicine-Qatar, Doha 24144, Qatar;
| | - Deborah A. Lawlor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK; (N.J.G.); (Y.B.-S.); (D.A.L.)
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK
- Bristol NIHR Biomedical Research Centre, University of Bristol, Bristol BS1 2NT, UK
| | - Massimo Mangino
- Department of Twin Research, King’s College London, London SE1 7EH, UK; (P.L.); (A.N.); (M.M.)
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London SE1 9RT, UK
| | - Cristina Menni
- Department of Twin Research, King’s College London, London SE1 7EH, UK; (P.L.); (A.N.); (M.M.)
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7
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Murthy VL, Yu B, Wang W, Zhang X, Alkis T, Pico AR, Yeri A, Bhupathiraju SN, Bressler J, Ballantyne CM, Freedman JE, Ordovas J, Boerwinkle E, Tucker KL, Shah R. Molecular Signature of Multisystem Cardiometabolic Stress and Its Association With Prognosis. JAMA Cardiol 2020; 5:1144-1153. [PMID: 32717046 DOI: 10.1001/jamacardio.2020.2686] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Importance Cardiometabolic disease is responsible for decreased longevity and poorer cardiovascular outcomes in the modern era. Metabolite profiling provides a specific measure of global metabolic function to examine specific metabolic mechanisms and pathways of cardiometabolic disease beyond its clinical definitions. Objectives To define a molecular basis for cardiometabolic stress and assess its association with cardiovascular prognosis. Design, Setting, and Participants A prospective observational cohort study was conducted in a population-based setting across 2 geographically distinct centers (Boston Puerto Rican Health Study [BPRHS], an ongoing study of individuals enrolled between June 1, 2004, and October 31, 2009; and Atherosclerosis Risk in Communities [ARIC] study, whose participants were originally sampled between November 24, 1986, and February 10, 1990, and followed up through December 31, 2017). Participants in the BPRHS were 668 Puerto Rican individuals with metabolite profiling living in Massachusetts, and participants in the ARIC study were 2152 individuals with metabolite profiling and long-term follow-up for mortality and cardiovascular outcomes. Statistical analysis was performed from October 1, 2018, to March 13, 2020. Exposure The primary exposure was metabolite profiles across both cohorts. Main Outcomes and Measures Outcomes included associations with multisystem cardiometabolic stress and all-cause mortality and incident coronary heart disease (in the ARIC study). Results Participants in the BPRHS (N = 668; 491 women; mean [SD] age, 57.0 [7.4] years; mean [SD] body mass index [calculated as weight in kilograms divided by height in meters squared], 32.0 [6.5]) had higher prevalent cardiometabolic risk relative to those in the ARIC study (N = 2152; 599 African American individuals; 1213 women; mean [SD] age, 54.3 [5.7] years; mean [SD] body mass index, 28.0 [5.5]). Multisystem cardiometabolic stress was defined for 668 Puerto Rican individuals in the BPRHS as a multidimensional composite of hypothalamic-adrenal axis activity, sympathetic activation, blood pressure, proatherogenic dyslipidemia, insulin resistance, visceral adiposity, and inflammation. A total of 260 metabolites associated with cardiometabolic stress were identified in the BPRHS, involving known and novel pathways of cardiometabolic disease (eg, amino acid metabolism, oxidative stress, and inflammation). A parsimonious metabolite-based score associated with cardiometabolic stress in the BPRHS was subsequently created; this score was applied to shared metabolites in the ARIC study, demonstrating significant associations with coronary heart disease and all-cause mortality after multivariable adjustment at a 30-year horizon (per SD increase in metabolomic score: hazard ratio, 1.14; 95% CI, 1.00-1.31; P = .045 for coronary heart disease; and hazard ratio, 1.15; 95% CI, 1.07-1.24; P < .001 for all-cause mortality). Conclusions and Relevance Metabolites associated with cardiometabolic stress identified known and novel pathways of cardiometabolic disease in high-risk, community-based cohorts and were associated with coronary heart disease and survival at a 30-year time horizon. These results underscore the shared molecular pathophysiology of metabolic dysfunction, cardiovascular disease, and longevity and suggest pathways for modification to improve prognosis across all linked conditions.
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Affiliation(s)
- Venkatesh L Murthy
- Frankel Cardiovascular Center, Division of Cardiovascular Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor
| | - Bing Yu
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston
| | - Wenshuang Wang
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston
| | - Xiuyan Zhang
- Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, Lowell
| | - Taryn Alkis
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston
| | - Alexander R Pico
- Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, California
| | - Ashish Yeri
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston
| | - Shilpa N Bhupathiraju
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts.,Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts
| | - Jan Bressler
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston
| | | | - Jane E Freedman
- UMass Memorial Heart and Vascular Center, University of Massachusetts Medical School, Worcester
| | - Jose Ordovas
- Friedman School of Nutrition Science and Policy, School of Graduate Biomedical Sciences, Tufts University, Boston, Massachusetts
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston
| | - Katherine L Tucker
- Department of Biomedical and Nutritional Sciences, University of Massachusetts, Lowell, Lowell
| | - Ravi Shah
- Cardiology Division, Department of Medicine, Massachusetts General Hospital, Boston
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