Last updated:
Author(s):
Aniket Sawant, Irina Griķe, Baiba Vilne
Publish date:
19 July 2025
Journal:
Mitochondrion
PubMed ID:
40691914

Abstract

Coronary Artery Diseases (CAD) contribute significantly to the global morbidity and mortality. While genome-wide association studies have identified numerous nuclear genomic variants linked to CAD, these account for less than 20 % of the disease’s estimated heritability (variation in disease risk attributed to genetic factors), suggesting the potential contribution of non-nuclear genetic elements, such as mitochondrial single-nucleotide variants (MT-SNVs). MT-SNVs may also influence lifestyle-related traits, which often interact with genetic predisposition to modulate CAD risk.

HYPOTHESIS: MT-SNVs contribute to the unexplained heritability of CAD and may also be associated with lifestyle behaviours.

METHODS: We analysed 203 high-quality common and low-frequency MT-SNVs (minor allele frequency > 0.01) in 20,400 CAD cases (myocardial infarction and/or revascularisation) from the UK Biobank after rigorous quality control and imputation. Associations between MT-SNVs and 85 quantitative food intake traits (FIQTs) and 23 established CAD risk factors (e.g., smoking status, lipid levels, physical activity) using both Frequentist and Bayesian methods. Correlation analyses were performed across these 108 lifestyle behaviours.

RESULTS: Several MT-SNVs were nominally associated with the CAD status and lifestyle habits, including m.10873T > C (MT-ND4 gene), m.15301G > A (MT-CYB gene), m.8701A > G (MT-ATP6 gene), and m.9540T > C (MT-CO3). After adjusting for covariates, these associations did not remain statistically significant. CAD status was significantly but weakly correlated (|r| < 0.2) with 64 dietary preferences of the 108 lifestyle traits (Bonferroni-adjusted P < 0.05), indicating modest but widespread dietary pattern differences.

CONCLUSIONS: Our findings suggest that MT-SNVs may explain some of the CAD heritability. However, larger cohorts with more comprehensive mitochondrial data are needed to clarify their potential role.

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