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. 2020 Jan 17;126(2):200-209.
doi: 10.1161/CIRCRESAHA.119.315686. Epub 2019 Nov 6.

Monogenic and Polygenic Contributions to Atrial Fibrillation Risk: Results From a National Biobank

Affiliations

Monogenic and Polygenic Contributions to Atrial Fibrillation Risk: Results From a National Biobank

Seung Hoan Choi et al. Circ Res. .

Abstract

Rationale: Genome-wide association studies have identified over 100 genetic loci for atrial fibrillation (AF); recent work described an association between loss-of-function (LOF) variants in TTN and early-onset AF.

Objective: We sought to determine the contribution of rare and common genetic variation to AF risk in the general population.

Methods: The UK Biobank is a population-based study of 500 000 individuals including a subset with genome-wide genotyping and exome sequencing. In this case-control study, we included AF cases and controls of genetically determined white-European ancestry; analyses were performed using a logistic mixed-effects model adjusting for age, sex, the first 4 principal components of ancestry, empirical relationships, and case-control imbalance. An exome-wide, gene-based burden analysis was performed to examine the relationship between AF and rare, high-confidence LOF variants in genes with ≥10 LOF carriers. A polygenic risk score for AF was estimated using the LDpred algorithm. We then compared the contribution of AF polygenic risk score and LOF variants to AF risk.

Results: The study included 1546 AF cases and 41 593 controls. In an analysis of 9099 genes with sufficient LOF variant carriers, a significant association between AF and rare LOF variants was observed in a single gene, TTN (odds ratio, 2.71, P=2.50×10-8). The association with AF was more significant (odds ratio, 6.15, P=3.26×10-14) when restricting to LOF variants located in exons highly expressed in cardiac tissue (TTNLOF). Overall, 0.44% of individuals carried TTNLOF variants, of whom 14% had AF. Among individuals in the highest 0.44% of the AF polygenic risk score only 9.3% had AF. In contrast, the AF polygenic risk score explained 4.7% of the variance in AF susceptibility, while TTNLOF variants only accounted for 0.2%.

Conclusions: Both monogenic and polygenic factors contribute to AF risk in the general population. While rare TTNLOF variants confer a substantial AF penetrance, the additive effect of many common variants explains a larger proportion of genetic susceptibility to AF.

Keywords: atrial fibrillation; exome; genetics; population; risk.

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Figures

Figure 1.
Figure 1.. High-confidence loss-of-function variants in TTN among atrial fibrillation cases and controls in UK Biobank.
Figure 1A is a Manhattan plot of the gene-based burden analysis for predicted high-confidence loss-of-function (LOF) variants and atrial fibrillation. Grey dotted line represents the exome-wide significance level. Results are based on LOF variants in canonical transcripts only, and are adjusted for sex, age, polygenic risk score and the first four principal components of ancestry. LOF variants in TTN are associated with AF. Figure 1(B) shows the locations of LOF variants in titin (protein encoded by TTN) found in heart failure, non-ischemic cardiomyopathy and atrial fibrillation patients, as well as in controls. Shown variants are restricted to those found in exons highly expressed in cardiac tissue. Red bars (N = 27) in atrial fibrillation cases are LOF variants found among patients who did not have heart failure prior to atrial fibrillation. Blue bars from the second and third rows represent LOF variants identified from patients who had atrial fibrillation prior to heart failure or non-ischemic cardiomyopathy. The bottom of the Figure 1B illustrates different bands of TTN. The TTN exons highly expressed in heart tissue are shown on the inside of the band in grey.
Figure 2.
Figure 2.. Prevalence and penetrance of TTNLOF variants with respect to atrial fibrillation and heart failure.
Figure 2A exhibits the proportion of carriers with high confidence loss-of-function variants in cardiac TTN (TTNLOF) and 95% confidence intervals among unrelated atrial fibrillation (AF), heart failure (HF), and nonischemic cardiomyopathy (CMP) cases. Figure 2B shows the penetrance of TTNLOF variants for AF, HF, and CMP. Of the three diseases, TTNLOF variants are most frequent among individuals with non-ischemic cardiomyopathy. All values are calculated from an unrelated subset of the exome sequencing cohort (N = 41,212). AF cases with HF prior to AF are excluded.
Figure 3.
Figure 3.. Prevalence of atrial fibrillation conferred by loss-of-function variants in cardiac TTN compared to polygenic risk in the UK Biobank.
The first figure illustrates the distribution of AF polygenic risk score in the UK Biobank. Each human icon represents 1% of the population and a dotted vertical line exhibits highest 0.44% of AF polygenic risk group. Among this 0.44% group, 9.3% individual had atrial fibrillation. The bottom figure illustrates the carriers with high confidence loss-of-function variants in cardiac TTN (TTNLOF). As shown in the last human icon, 0.44% participants of the UK Biobank carried TTNLOF variants and among those, 14.3% had atrial fibrillation.
Figure 4.
Figure 4.. Prevalence of atrial fibrillation conferred by loss-of-function variants in cardiac TTN compared to polygenic risk in the UK Biobank.
Figure 4 shows the prevalence of atrial fibrillation (AF) conferred by loss-of-function variants in cardiac TTN (TTNLOF) and the prevalence conferred by high AF polygenic risk scores (PRS) in an unrelated subset of the exome sequencing cohort where cases of AF with heart failure prior to AF are excluded (N = 41,212). Increasingly extreme tails of the PRS distribution are shown in blue. TTNLOF variant carriers are shown in red. Approximately 0.44% of the population carried TTNLOF variants, of which 14% had AF. Meanwhile, only 9.3% of individuals in the top 0.44% of AF PRS had AF.
Figure 5.
Figure 5.. Prevalence of atrial fibrillation stratified by monogenic and polygenic risk in the UK Biobank.
Figure 5 shows the prevalence of atrial fibrillation (AF), stratified by polygenic and monogenic risk in the unrelated subset of the exome sequencing cohort (N = 41,212). In the population, AF prevalence increased with increasing AF polygenic risk score (PRS) and was considerably higher in carriers of loss-of-function variants in cardiac TTN (TTNLOF) which are shown in red. Among TTNLOF carriers, AF PRS associated with AF penetrance: Carriers in the lowest tertile of PRS had an AF prevalence of 6.7% compared to 21.5% in the highest tertile.

Comment in

  • The Open Science of Atrial Fibrillation.
    Keavney BD, McGurk KA. Keavney BD, et al. Circ Res. 2020 Jan 17;126(2):210-211. doi: 10.1161/CIRCRESAHA.119.316357. Epub 2020 Jan 16. Circ Res. 2020. PMID: 31944917 No abstract available.

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References

    1. Zoni-Berisso M, Lercari F, Carazza T, Domenicucci S. Epidemiology of atrial fibrillation: European perspective. Clinical Epidemiology. 2014;6:213. - PMC - PubMed
    1. Wilke T, Groth A, Mueller S, Pfannkuche M, Verheyen F, Linder R, Maywald U, Bauersachs R, Breithardt G. Incidence and prevalence of atrial fibrillation: An analysis based on 8.3 million patients. Europace. 2013;15:486–493 - PubMed
    1. Chugh SS, Havmoeller R, Narayanan K, et al. Worldwide epidemiology of atrial fibrillation: A global burden of disease 2010 study. Circulation. 2014;129:837–847 - PMC - PubMed
    1. Go AS, Hylek EM, Phillips KA, Chang Y, Henault LE, Selby JV, Singer DE. Prevalence of diagnosed atrial fibrillation in adults. JAMA : the journal of the American Medical Association. 2001;285:2370. - PubMed
    1. Kumar P, Gehi AK. Atrial fibrillation and metabolic syndrome: Understanding the connection. J Atr Fibrillation. 2012;5:647. - PMC - PubMed

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