Genetic Determinants of Coronary Artery Disease in Type 2 Diabetes Mellitus Among Asian Populations: A Meta-Analysis

<b>Background/Objectives</b>: Type 2 diabetes mellitus (T2DM) significantly elevates the risk of coronary artery disease (CAD), particularly in Asian populations where both conditions are epidemic. While shared genetic factors contribute to this comorbidity, evidence from Asian cohorts remains fragmented, with limited focus on population-specific variants. This meta-analysis synthesizes evidence on genetic variants associated with CAD risk in Asian patients with T2DM. <b>Methods</b>: We systematically searched several databases according to the PRISMA statement and checklist. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated using random-effects models, with heterogeneity assessed via I<sup>2</sup> and Cochran's Q, and publication bias via funnel plots and Egger's test. <b>Results</b>: In total, data on 11,268 subjects were reviewed, including 4668 cases and 6600 controls. Among 950 identified studies, 18 met eligibility criteria, and 14 studies provided sufficient data for the meta-analysis. The random-effects pooled estimate across all studied variants was not statistically significant (OR = 1.16 [95% CI: 0.68-2.00]; z = 0.56, <i>p</i> = 0.58). However, analysis of individual loci revealed gene-specific associations with CAD among this population: PCSK1 gene (OR = 2.12 [95% CI: 1.26-3.52]; <i>p</i> < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27-3.97]; <i>p</i> < 0.01; weight = 8.62%). ADIPOQ gene (OR = 8.00 [95% CI: 2.34-27.14]; <i>p</i> < 0.01; weight = 6.35%). Several genes were associated with an elevated risk of CAD: PCSK1 gene (OR = 2.12 [95% CI: 1.26-3.52]; <i>p</i> < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27-3.97]; <i>p</i> < 0.01; weight = 8.62%) and ADIPOQ gene (OR = 8.00 [95% CI: 2.34-27.14]; <i>p</i> < 0.01; weight = 6.35%). Several genes were associated with possible protective effects: ACE gene (OR = 0.41 [95% CI: 0.23-0.73]; <i>p</i> < 0.01; weight = 8.57%), Q192R gene (OR = 0.20 [95% CI: 0.08-0.52]; <i>p</i> < 0.001; weight = 7.41%). Heterogeneity was substantial (τ<sup>2</sup> = 0.78; I<sup>2</sup> = 81.95%; Q (13) = 64.67, <i>p</i> < 0.001). <b>Conclusions</b>: This first meta-analysis of genetic variants associated with CAD in Asian populations with T2DM identified specific locus-level associations implicating lipid metabolism, incretin signaling, and oxidative stress pathways. The lack of a significant pooled effect, alongside high heterogeneity, underscores the complexity and population-specific nature of this genetic architecture. These findings suggest that effective precision risk stratification may depend more on specific variants than on a broad polygenic signal, highlighting the need for further research in a larger, distinct sample size.

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Medical Sciences
Published
2026-01-21
DOI
https://doi.org/10.3390/medsci14010052
Primary Topic
Genetic Associations and Epidemiology
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article

Genetic Determinants of Coronary Artery Disease in Type 2 Diabetes Mellitus Among Asian Populations: A Meta-Analysis

Kuralay Atageldiyeva, Alessandro Salustri, Kamilla Mussina, Joseph U. Almazan et al.
Medical Sciences
Genetic Associations and Epidemiology
article

Genetic Determinants of Coronary Artery Disease in Type 2 Diabetes Mellitus Among Asian Populations: A Meta-Analysis

Kuralay Atageldiyeva, Alessandro Salustri, Kamilla Mussina, Joseph U. Almazan, Aida Kabibulatova
article en

Abstract

<b>Background/Objectives</b>: Type 2 diabetes mellitus (T2DM) significantly elevates the risk of coronary artery disease (CAD), particularly in Asian populations where both conditions are epidemic. While shared genetic factors contribute to this comorbidity, evidence from Asian cohorts remains fragmented, with limited focus on population-specific variants. This meta-analysis synthesizes evidence on genetic variants associated with CAD risk in Asian patients with T2DM. <b>Methods</b>: We systematically searched several databases according to the PRISMA statement and checklist. Pooled odds ratios (ORs) with corresponding 95% confidence intervals (CIs) were calculated using random-effects models, with heterogeneity assessed via I<sup>2</sup> and Cochran's Q, and publication bias via funnel plots and Egger's test. <b>Results</b>: In total, data on 11,268 subjects were reviewed, including 4668 cases and 6600 controls. Among 950 identified studies, 18 met eligibility criteria, and 14 studies provided sufficient data for the meta-analysis. The random-effects pooled estimate across all studied variants was not statistically significant (OR = 1.16 [95% CI: 0.68-2.00]; z = 0.56, <i>p</i> = 0.58). However, analysis of individual loci revealed gene-specific associations with CAD among this population: PCSK1 gene (OR = 2.12 [95% CI: 1.26-3.52]; <i>p</i> < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27-3.97]; <i>p</i> < 0.01; weight = 8.62%). ADIPOQ gene (OR = 8.00 [95% CI: 2.34-27.14]; <i>p</i> < 0.01; weight = 6.35%). Several genes were associated with an elevated risk of CAD: PCSK1 gene (OR = 2.12 [95% CI: 1.26-3.52]; <i>p</i> < 0.05; weight = 8.77%), GLP1R gene (OR = 2.25 [95% CI: 1.27-3.97]; <i>p</i> < 0.01; weight = 8.62%) and ADIPOQ gene (OR = 8.00 [95% CI: 2.34-27.14]; <i>p</i> < 0.01; weight = 6.35%). Several genes were associated with possible protective effects: ACE gene (OR = 0.41 [95% CI: 0.23-0.73]; <i>p</i> < 0.01; weight = 8.57%), Q192R gene (OR = 0.20 [95% CI: 0.08-0.52]; <i>p</i> < 0.001; weight = 7.41%). Heterogeneity was substantial (τ<sup>2</sup> = 0.78; I<sup>2</sup> = 81.95%; Q (13) = 64.67, <i>p</i> < 0.001). <b>Conclusions</b>: This first meta-analysis of genetic variants associated with CAD in Asian populations with T2DM identified specific locus-level associations implicating lipid metabolism, incretin signaling, and oxidative stress pathways. The lack of a significant pooled effect, alongside high heterogeneity, underscores the complexity and population-specific nature of this genetic architecture. These findings suggest that effective precision risk stratification may depend more on specific variants than on a broad polygenic signal, highlighting the need for further research in a larger, distinct sample size.

Medical SciencesVol. 14(1)
Astana Medical University (KZ), Nazarbayev University (KZ)
Good health and well-being
Openalex Percentile: Top 82%
Genetic Associations and Epidemiology
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