A polygenic risk score of atrial fibrillation improves prediction of lifetime risk for heart failure.

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.

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.

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.

Whole-Genome Sequencing Analysis of Human Metabolome in Multi-Ethnic Populations.

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.

Cross-Sectional Blood Metabolite Markers of Hypertension: A Multicohort Analysis of 44,306 Individuals from the COnsortium of METabolomics Studies.

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.

Molecular Signature of Multisystem Cardiometabolic Stress and Its Association With Prognosis.

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.