Atrial fibrillation (AF) affects over 33 million individuals worldwide1 and has a complex heritability.2 We conducted the largest meta-analysis of genome-wide association studies for AF to date, consisting of over half a million individuals including 65,446 with AF. In total, we identified 97 loci significantly associated with AF including 67 of which were novel in a combined-ancestry analysis, and 3 in a European specific analysis. We sought to identify AF-associated genes at the GWAS loci by performing RNA-sequencing and expression quantitative trait loci (eQTL) analyses in 101 left atrial samples, the most relevant tissue for AF. We also performed transcriptome-wide analyses that identified 57 AF-associated genes, 42 of which overlap with GWAS loci. The identified loci implicate genes enriched within cardiac developmental, electrophysiological, contractile and structural pathways. These results extend our understanding of the biological pathways underlying AF and may facilitate the development of therapeutics for AF.

ObjectiveTo examine the association between risk factor burdens—categorized as optimal, borderline, or elevated—and the lifetime risk of atrial fibrillation.DesignCommunity based cohort study.SettingLongitudinal data from the Framingham Heart Study.ParticipantsIndividuals free of atrial fibrillation at index ages 55, 65, and 75 years were assessed. Smoking, alcohol consumption, body mass index, blood pressure, diabetes, and history of heart failure or myocardial infarction were assessed as being optimal (that is, all risk factors were optimal), borderline (presence of borderline risk factors and absence of any elevated risk factor), or elevated (presence of at least one elevated risk factor) at index age.Main outcome measureLifetime risk of atrial fibrillation at index age up to 95 years, accounting for the competing risk of death.ResultsAt index age 55 years, the study sample comprised 5338 participants (2531 (47.4%) men). In this group, 247 (4.6%) had an optimal risk profile, 1415 (26.5%) had a borderline risk profile, and 3676 (68.9%) an elevated risk profile. The prevalence of elevated risk factors increased gradually when the index ages rose. For index age of 55 years, the lifetime risk of atrial fibrillation was 37.0% (95% confidence interval 34.3% to 39.6%). The lifetime risk of atrial fibrillation was 23.4% (12.8% to 34.5%) with an optimal risk profile, 33.4% (27.9% to 38.9%) with a borderline risk profile, and 38.4% (35.5% to 41.4%) with an elevated risk profile. Overall, participants with at least one elevated risk factor were associated with at least 37.8% lifetime risk of atrial fibrillation. The gradient in lifetime risk across risk factor burden was similar at index ages 65 and 75 years.ConclusionsRegardless of index ages at 55, 65, or 75 years, an optimal risk factor profile was associated with a lifetime risk of atrial fibrillation of about one in five; this risk rose to more than one in three in individuals with at least one elevated risk factor.

No abstract

Background:Aging is related to an increased risk of morbidity and mortality and is affected by environmental factors. Exposure to polycyclic aromatic hydrocarbons (PAHs) is associated with adverse health outcomes; but the association of such exposure with DNA methylation aging, a novel aging marker, is unclear.Objectives:Our aim was to investigate the association of PAH exposure with methylation aging.Methods:We trained and validated a methylation age predictor suitable for Chinese populations using whole blood methylation data in 989 Chinese and 160 Caucasians. We defined two aging indicators: Δage, as methylation age minus chronological age; and aging rate, the ratio of methylation to chronological age. The association of PAH exposure with aging indicators was evaluated using linear regressions in three panels of healthy Chinese participants (N=539, among the aforementioned 989 Chinese participants) whose exposure levels were assessed by 10 urinary monohydroxy-PAH metabolites.Results:We developed a methylation age predictor providing accurate predictions in both Chinese individuals and Caucasian persons (R=0.94–0.96, RMSE=3.8–4.3). Among the 10 urinary metabolites that we measured, 1-hydroxypyrene and 9-hydroxyphenanthrene were associated with methylation aging independently of other OH-PAHs and risk factors; 1-unit increase in 1-hydroxypyrene was associated with a 0.53-y increase in Δage [95% confidence interval (CI): 0.18, 0.88; false discovery rate (FDR) FDR=0.004] and 1.17% increase in aging rate (95% CI: 0.36, 1.98; FDR=0.02), whereas for 9-hydroxyphenanthrene, the increase was 0.54-y for Δage (95% CI: 0.17, 0.91; FDR=0.004), and 1.15% for aging rate (95% CI: 0.31, 1.99; FDR=0.02). The association direction was consistent across the three Chinese panels with the association magnitude correlating with the panels’ exposure levels; the association was validated by methylation data of purified leukocytes. Several cytosine-phosphoguanines, including those located on FHL2 and ELOVL2, were found associated with both aging indicators and monohydroxy-PAH levels.Conclusions:We developed a methylation age predictor specific for Chinese populations but also accurate for Caucasian populations. Our findings suggest that exposure to PAHs may be associated with an adverse impact on human aging and epigenetic alterations in Chinese populations. https://doi.org/10.1289/EHP2773

Human genetics and studies in experimental models support a key role of monocyte-chemoattractant protein-1 (MCP-1) in atherosclerosis. Yet, the associations of circulating MCP-1 levels with risk of coronary heart disease and cardiovascular death in the general population remain largely unexplored. OBJECTIVE To explore whether circulating levels of MCP-1 are associated with risk of incident coronary heart disease, myocardial infarction, and cardiovascular mortality in the general population.DATA SOURCES AND SELECTION Population-based cohort studies, identified through a systematic review, that have examined associations of circulating MCP-1 levels with cardiovascular end points.DATA EXTRACTION AND SYNTHESIS Using a prespecified harmonized analysis plan, study-specific summary data were obtained from Cox regression models after excluding individuals with overt cardiovascular disease at baseline. Derived hazard ratios (HRs) were synthesized using random-effects meta-analyses. MAIN OUTCOMES AND MEASURESIncident coronary heart disease (myocardial infarction, coronary revascularization, and unstable angina), nonfatal myocardial infarction, and cardiovascular death (from cardiac or cerebrovascular causes). RESULTSThe meta-analysis included 7 cohort studies involving 21 401 individuals (mean [SD] age, 53.7 [10.2] years; 10 012 men [46.8%]). Mean (SD) follow-up was 15.3 (4.5) years (326 392 person-years at risk). In models adjusting for age, sex, and race/ethnicity, higher MCP-1 levels at baseline were associated with increased risk of coronary heart disease (HR per 1-SD increment in MCP-1 levels: 1.06 [95% CI, 1.01-1.11]; P = .01), nonfatal myocardial infarction (HR, 1.07 [95% CI, 1.01-1.13]; P = .02), and cardiovascular death (HR, 1.12 [95% CI, 1.05-1.20]; P < .001). In analyses comparing MCP-1 quartiles, these associations followed dose-response patterns. After additionally adjusting for vascular risk factors, the risk estimates were attenuated, but the associations of MCP-1 levels with cardiovascular death remained statistically significant, as did the association of MCP-1 levels in the upper quartile with coronary heart disease. There was no significant heterogeneity; the results did not change in sensitivity analyses excluding events occurring in the first 5 years after MCP-1 measurement, and the risk estimates were stable after additional adjustments for circulating levels of interleukin-6 and high-sensitivity C-reactive protein.CONCLUSIONS AND RELEVANCE Higher circulating MCP-1 levels are associated with higher long-term cardiovascular mortality in community-dwelling individuals free of overt cardiovascular disease. These findings provide further support for a key role of MCP-1-signaling in cardiovascular disease.

Previous studies have shown that both single nucleotide polymorphisms (SNPs) and questionnaires-based method can be used for twin zygosity determination, but few validation studies have been conducted using Chinese populations. In the current study, we recruited 192 same sex Chinese adult twin pairs to evaluate the validity of using genetic markers-based method and questionnaire-based method in zygosity determination. We considered the relatedness analysis based on more than 0.6 million SNPs genotyping as the golden standards for zygosity determination. After quality control, qualified twins were left for relatedness analysis based on identical by descent calculation. Then those same sex twin pairs were included in the zygosity questionnaire validation analysis. Logistic regression model was applied to assess the discriminant ability of age, sex and the three questions in zygosity determination. Leave one out cross-validation was used as a measurement of internal validation. The results of zygosity determination based on 65 SNPs in 450k methylation array were all consistent with genotyping. Age, gender, questions of appearance confused by strangers and previously perceived zygosity consisted of the most predictable model with a consistency rate of 0.8698, cross validation predictive error of 0.1347. For twin studies with genotyping and\or 450k methylation array, there would be no need to conduct other zygosity testing for the sake of costs consideration.

Rationale: GWAS (Genome-Wide Association Studies) have identified hundreds of genetic loci associated with atrial fibrillation (AF). However, these loci explain only a small proportion of AF heritability. Objective: To develop an approach to identify additional AF-related genes by integrating multiple omics data. Methods and Results: Three types of omics data were integrated: (1) summary statistics from the AFGen 2017 GWAS; (2) a whole blood EWAS (Epigenome-Wide Association Study) of AF; and (3) a whole blood TWAS (Transcriptome-Wide Association Study) of AF. The variant-level GWAS results were collapsed into gene-level associations using fast set-based association analysis. The CpG-level EWAS results were also collapsed into gene-level associations by an adapted SNP-set Kernel Association Test approach. Both GWAS and EWAS gene-based associations were then meta-analyzed with TWAS using a fixed-effects model weighted by the sample size of each data set. A tissue-specific network was subsequently constructed using the NetWAS (Network-Wide Association Study). The identified genes were then compared with the AFGen 2018 GWAS that contained more than triple the number of AF cases compared with AFGen 2017 GWAS. We observed that the multiomics approach identified many more relevant AF-related genes than using AFGen 2018 GWAS alone (1931 versus 206 genes). Many of these genes are involved in the development and regulation of heart- and muscle-related biological processes. Moreover, the gene set identified by multiomics approach explained much more AF variance than those identified by GWAS alone (10.4% versus 3.5%). Conclusions: We developed a strategy to integrate multiple omics data to identify AF-related genes. Our integrative approach may be useful to improve the power of traditional GWAS, which might be particularly useful for rare traits and diseases with limited sample size.

The genetic contribution of blood pressure and heart rate (HR) varied widely between studies. Demographic factors such as ethnicity, age and/or sex might explain some of the heterogeneity. We performed a systematic review focusing on four phenotypes: systolic blood pressure (SBP), diastolic blood pressure (DBP), HR and pulse pressure (PP). Meta-regression was conducted to analyze potential factors in relation to SBP and DBP heritability. A total of 10,613 independent twins that came from 17 studies were included in the analysis. The weighted mean value of heritability for SBP and DBP was 0.54 (95% CIs: 0.48-0.60) and 0.49 (95% CIs: 0.42-0.56). Comparatively, three studies of HR and four studies of PP heritability were limited for the heterogeneity test. Meta-regression showed that, on average, SBP heritability with additive genes/unique environment (AE) model tend to have a higher heritability than additive genes/shared environment/unique environment (ACE) model (coefficient = 0.0947, p = .0142). A similar result was found for DBP as well. No other factors such as sex, age, ethnicity, publication year were significantly associated with heritability variance. Our study shows heritability estimates based on twin studies of both SBP and DBP are around 50%, using an AE rather than an ACE model; the variance due to C ended up in A, suggesting that the AE model may overestimate heritability if a small contribution of shared environment exists.