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Association between SIRT1 gene polymorphisms and susceptibility to coronary artery disease: a systematic review and
1The Key Laboratory of Myocardial Remodeling Research, The Affiliated Hospital of Guizhou Medical University, Guiyang, Guizhou, China.
Background:
This systematic review and meta-analysis aimed to evaluate and quantitatively synthesize the available evidence on the association between SIRT1 gene polymorphisms and susceptibility to coronary artery disease (CAD).
Methods:
PubMed, Embase, Web of Science, and the Cochrane Library were systematically searched from inception to February 12, 2026, to identify relevant observational studies. Literature screening, data extraction, and quality assessment were independently performed by two reviewers. Meta-analyses were conducted using Stata 16.0, with odds ratios (ORs) and 95% confidence intervals (CIs) as effect measures. Subgroup and sensitivity analyses were further performed where appropriate.
Results:
A total of nine studies were included, with overall methodological quality ranging from moderate to high. Three SIRT1 polymorphisms, rs7069102, rs7895833, and rs4746720, were included in the quantitative synthesis. In the overall analysis, rs7069102 was not significantly associated with CAD susceptibility under any of the five genetic models; however, in the CAD subgroup, it showed a consistent risk effect across all genetic models. Rs7895833 was associated with increased CAD susceptibility only under the recessive model (OR = 1.49, 95% CI: 1.03-2.15). Rs4746720 showed significant associations under the dominant model (OR = 1.26, 95% CI: 1.02-1.55) and the heterozygote model (OR = 1.27, 95% CI: 1.01-1.58).
Conclusion:
Current evidence suggests that certain SIRT1 polymorphisms may be associated with CAD susceptibility, but the observed associations appear to vary by SNP locus, genetic model, and population or disease subgroup. Because the pooled estimates were derived mainly from unadjusted genotype frequencies and could not account for major cardiovascular risk factors, these findings should be interpreted cautiously. Further large, well-designed studies with appropriate adjustment for clinical confounders are needed to confirm these associations.
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