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.

Atrial fibrillation affects more than 33 million people worldwide and increases the risk of stroke, heart failure, and death.1,2 Fourteen genetic loci have been associated with atrial fibrillation in European and Asian ancestry groups.3–7 To further define the genetic basis of atrial fibrillation, we performed large-scale, multi-racial meta-analyses of common and rare variant association studies. The genome-wide association studies (GWAS) included 18,398 individuals with atrial fibrillation and 91,536 referents; the exome-wide association studies (ExWAS) and rare variant association studies (RVAS) involved 22,806 cases and 132,612 referents. We identified 12 novel genetic loci that exceeded genome-wide significance, implicating genes involved in cardiac electrical and structural remodeling. Our results nearly double the number of known genetic loci for atrial fibrillation, provide insights into the molecular basis of atrial fibrillation, and may facilitate new potential targets for drug discovery.8

RV dysfunction and PH are highly prevalent and are both associated with poor outcome in patients with HFpEF.

The incidence of AF in the present cohort was comparable to that shown in data of older studies. Obesity has become a major risk factor for incident AF. Although overall cardiovascular event rates were lower in the present study, the present study confirms the association of incident AF with such events.

Clinicaltrials.gov NCT00877643.

Background Atrial fibrillation (AF) is common and has a substantial genetic basis. Identification of individuals at greatest AF risk could minimize the incidence of cardioembolic stroke. Methods To determine whether genetic data can stratify risk for development of AF, we examined associations between AF genetic risk scores and incident AF in five prospective studies comprising 18,919 individuals of European ancestry. We examined associations between AF genetic risk scores and ischemic stroke in a separate study of 509 ischemic stroke cases (202 cardioembolic [40%]) and 3,028 controls. Scores were based on 11 to 719 common variants (≥5%) associated with AF at P-values ranging from <1×10−3 to <1×10−8 in a prior independent genetic association study. Results Incident AF occurred in 1,032 (5.5%) individuals. AF genetic risk scores were associated with new-onset AF after adjusting for clinical risk factors. The pooled hazard ratio for incident AF for the highest versus lowest quartile of genetic risk scores ranged from 1.28 (719 variants; 95%CI, 1.13–1.46; P=1.5×10−4) to 1.67 (25 variants; 95%CI, 1.47–1.90; P=9.3×10−15). Discrimination of combined clinical and genetic risk scores varied across studies and scores (maximum C statistic, 0.629–0.811; maximum ΔC statistic from clinical score alone, 0.009–0.017). AF genetic risk was associated with stroke in age- and sex-adjusted models. For example, individuals in the highest quartile of a 127-variant score had a 2.49-fold increased odds of cardioembolic stroke, versus those in the lowest quartile (95%CI, 1.39–4.58; P=2.7×10−3). The effect persisted after excluding individuals (n=70) with known AF (odds ratio, 2.25; 95%CI, 1.20–4.40; P=0.01). Conclusions Comprehensive AF genetic risk scores were associated with incident AF beyond clinical AF risk factors, with magnitudes of risk comparable to other clinical risk factors, though offered small improvements in discrimination. AF genetic risk was also associated with cardioembolic stroke in age- and sex-adjusted analyses. Efforts to determine whether AF genetic risk may improve identification of subclinical AF or distinguish stroke mechanisms are warranted.

IMPORTANCE Increased free thyroxine (FT 4 ) and decreased thyrotropin are associated with increased risk of atrial fibrillation (AF) in observational studies, but direct involvement is unclear.OBJECTIVE To evaluate the potential direct involvement of thyroid traits on AF. DESIGN, SETTING, AND PARTICIPANTS Study-level mendelian randomization (MR) included 11 studies, and summary-level MR included 55 114 AF cases and 482 295 referents, all of European ancestry.EXPOSURES Genomewide significant variants were used as instruments for standardized FT 4 and thyrotropin levels within the reference range, standardized triiodothyronine (FT 3 ):FT 4 ratio, hypothyroidism, standardized thyroid peroxidase antibody levels, and hyperthyroidism. Mendelian randomization used genetic risk scores in study-level analysis or individual single-nucleotide polymorphisms in 2-sample MR for the summary-level data. MAIN OUTCOMES AND MEASURES Prevalent and incident AF. RESULTSThe study-level analysis included 7679 individuals with AF and 49 233 referents (mean age [standard error], 62 [3] years; 15 859 men [29.7%]). In study-level random-effects meta-analysis, the pooled hazard ratio of FT 4 levels (nanograms per deciliter) for incident AF was 1.55 (95% CI, 1.09-2.20; P = .02; I 2 = 76%) and the pooled odds ratio (OR) for prevalent AF was 2.80 (95% CI, 1.41-5.54; P = .003; I 2 = 64%) in multivariable-adjusted analyses. The FT 4 genetic risk score was associated with an increase in FT 4 by 0.082 SD (standard error, 0.007; P < .001) but not with incident AF (risk ratio, 0.84; 95% CI, 0.62-1.14; P = .27) or prevalent AF (OR, 1.32; 95% CI, 0.64-2.73; P = .46). Similarly, in summary-level inverse-variance weighted random-effects MR, gene-based FT 4 within the reference range was not associated with AF (OR, 1.01; 95% CI, 0.89-1.14; P = .88). However, gene-based increased FT 3 :FT 4 ratio, increased thyrotropin within the reference range, and hypothyroidism were associated with AF with inverse-variance weighted random-effects OR of 1.33 (95% CI, 1.08-1.63; P = .006), 0.88 (95% CI, 0.84-0.92; P < .001), and 0.94 (95% CI, 0.90-0.99; P = .009), respectively, and robust to tests of horizontal pleiotropy. However, the subset of hypothyroidism single-nucleotide polymorphisms involved in autoimmunity and thyroid peroxidase antibodies levels were not associated with AF. Gene-based hyperthyroidism was associated with AF with MR-Egger OR of 1.31 (95% CI, 1.05-1.63; P = .02) with evidence of horizontal pleiotropy (P = .045). CONCLUSIONS AND RELEVANCEGenetically increased FT 3 :FT 4 ratio and hyperthyroidism, but not FT 4 within the reference range, were associated with increased AF, and increased thyrotropin within the reference range and hypothyroidism were associated with decreased AF, supporting a pathway involving the pituitary-thyroid-cardiac axis.

Parameters using myocardial strain analysis may predict response to cardiac resynchronization therapy (CRT). As the agreement between currently available strain imaging modalities is unknown, three different modalities were compared. Twenty-seven CRT-candidates, prospectively included in the MARC study, underwent cardiac magnetic resonance (CMR) imaging and echocardiographic examination. Left ventricular (LV) circumferential strain was analysed with CMR tagging (CMR-TAG), CMR feature tracking (CMR-FT), and speckle tracking echocardiography (STE). Basic strain values and parameters of dyssynchrony and discoordination obtained with CMR-FT and STE were compared to CMR-TAG. Agreement of CMR-FT and CMR-TAG was overall fair, while agreement between STE and CMR-TAG was often poor. For both comparisons, agreement on discoordination parameters was highest, followed by dyssynchrony and basic strain parameters. For discoordination parameters, agreement on systolic stretch index was highest, with fair intra-class correlation coefficients (ICC) (CMR-FT: 0.58, STE: 0.55). ICC of septal systolic rebound stretch (SRSsept) was poor (CMR-FT: 0.41, STE: 0.30). Internal stretch factor of septal and lateral wall (ISFsep–lat) showed fair ICC values (CMR-FT: 0.53, STE: 0.46), while the ICC of the total LV (ISFLV) was fair for CMR-FT (0.55) and poor for STE (ICC: 0.32). The CURE index had a fair ICC for both comparisons (CMR-FT: 0.49, STE 0.41). Although comparison of STE to CMR-TAG was limited by methodological differences, agreement between CMR-FT and CMR-TAG was overall higher compared to STE and CMR-TAG. CMR-FT is a potential clinical alternative for CMR-TAG and STE, especially in the detection of discoordination in CRT-candidates.Electronic supplementary materialThe online version of this article (doi:10.1007/s10554-017-1253-5) contains supplementary material, which is available to authorized users.