medRxivGenetic & Genomic MedicinePreprint
Shared genetic etiology between chronic diseases and heart failure risk: the dual role of leukocyte telomere length
Jason Y. Y. WongiD, Batel BlechteriD, Zhonghua LiuiD, Jianxin ShiiD, Veronique Lee RogeriD
Abstract
IntroductionGenetic susceptibility to various chronic diseases has been shown to influence heart failure (HF) risk. However, the pathogenic mechanisms underlying these associations, particularly the role of phenotypic leukocyte telomere length (LTL), is unknown. We investigated the shared genetic etiology between chronic diseases, various traits, and HF risk, and whether LTL mediates or modifies these relationships. MethodsWe conducted prospective cohort analyses on 404,883 European participants from the UK Biobank, including 9,989 incident HF cases. Multivariable Cox regression was used to estimate associations between HF risk and 24 polygenic risk scores (PRSs) for various diseases or traits previously generated in the UK Biobank using a Bayesian approach. We assessed multiplicative interactions between the PRSs and LTL previously measured in the UK Biobank using quantitative PCR. Mediation analyses were conducted to estimate the proportion of the total effect of PRSs acting indirectly through LTL, an integrative marker of biological aging. ResultsWe identified 9 PRSs associated with HF risk, including those for various cardiovascular diseases or traits, rheumatoid arthritis (P=1.3E-04), and asthma (P=1.8E-08). Additionally, longer LTL was strongly associated with decreased HF risk (P-trend=1.7E-08). Notably, the asthma PRS had a super-multiplicative interaction with LTL (P-interaction=2.8E-03). However, LTL mediated only 1.13% (P<0.001) of the total effect of the asthma PRS on HF risk. ConclusionsOur findings shed light onto the shared genetic etiology between HF risk, asthma, rheumatoid arthritis, and other traits. Longer LTL strengthened the genetic effect of asthma on HF, supporting their utility in risk stratification analyses.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 1
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