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INTRODUCTION
Type 2 Diabetes Mellitus (T2DM) is a complex metabolic disorder characterized by insulin resistance, impaired insulin secretion, and chronic hyperglycemia. It poses a major global health burden, with rising prevalence attributed to aging populations, sedentary lifestyles, and increasing obesity rates. Beyond glucose dysregulation, T2DM is associated with serious macrovascular and microvascular complications, making early detection and risk prevention critical. Although environmental factors contribute significantly to T2DM, genetic predisposition plays a crucial role. Genome-wide and candidate gene studies have identified multiple loci related to insulin action, inflammation, and β-cell function, including the Sirtuin 1 (SIRT1) gene. SIRT1 encodes a NAD⁺ (nicotinamide adenine dinucleotide) dependent deacetylase involved in metabolic homeostasis, mitochondrial function, and cellular stress responses. Preclinical models have demonstrated that SIRT1 activation enhances insulin signaling, β-cell preservation, and glucose uptake, underscoring its relevance to T2DM pathogenesis (Bordone and Guarente, 2006; Haigis and Sinclair, 2010).
Polymorphisms in the SIRT1 gene may alter protein expression or enzymatic activity, influencing susceptibility to diabetes and its complications. Several functional studies have linked specific SNPs to disease risk. For instance, the rs10509291 A allele is associated with associated with CHD (Coronary heart disease) risk in a Chinese Han individual (Wang et al., 2022). The rs7069102 variant has been independently linked to diabetic nephropathy in Caucasian and Slovene populations (Kilic et al., 2014). Another promoter SNP (Single Nucleotide Polymorphism), rs2273773, has been associated with hypertension and hyperglycemia in Japanese cohorts (Shimoyama et al., 2011). Additionally, rs7895833 A >G is linked to metabolic syndrome and glycemic traits among Chinese Han (Tao et al., 2022).Gene-gene interactions further influence metabolic risk. Combined SIRT1-Nrf2 (Nuclear factor erythroid 2-related factor 2) variant analyses in Chinese individuals indicate that rs7895833 significantly correlates with metabolic syndrome traits (Tao et al., 2022). Promoter analysis in Chinese T2DM patients has identified multiple novel variants, such as rs3740051 and rs35995735, showing strong associations (Odds ratio (OR) ~1.44-3.58+) (Pang et al., 2023).
Despite growing evidence, findings have often been inconsistent due to differences in study populations, sample sizes, and SNP selection. Lack of ethnic diversity and environmental context further complicates interpretation. Notably, rs7069102 demonstrates both nephropathy and cardiovascular risk associations; in Caucasians, rs7069102 and rs2273773 were linked to cardiovascular disease risk (Dardano et al., 2022). To clarify these mixed results, we systematically evaluated 10 SNPs not previously included in our Results section. These variants span promoter and coding regions, functional pathways, and diverse ethnic groups. Crucially, multiple SNPs like rs7069102, rs2273773, rs10509291, and rs7895833 show replicated associations with diabetes or related traits-rendering them essential for comprehensive analysis.
Objective
This meta-analysis aims to integrate and quantify the association between SIRT1 polymorphisms (including rs10509291, rs2273773, rs7069102, rs7895833, and promoter variants) and T2DM risk, with consideration of diabetic complications. By combining data from diverse ethnic backgrounds and evaluating genotype-phenotype relationships, we aim to clarify the role of SIRT1 gene variation in diabetes pathogenesis and its potential as a biomarker for personalized medicine.
METHODOLOGY
Protocol and Registration
This meta-analysis was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. The protocol was registered in the International Prospective Register of Systematic Reviews (PROSPERO). Ethical approval was not required as it is a meta-analysis of published human data.
Eligibility Criteria
Inclusion criteria
- Peer-reviewed studies evaluating the association between SIRT1 gene polymorphisms and T2DM or its complications (e.g., CHD, nephropathy).
- Case-control, cross-sectional, cohort, or meta-analytic designs.
- Studies reporting genotype frequencies, odds ratios (ORs), or sufficient raw data to calculate effect sizes.
- Human studies published in English.
Exclusion criteria
- Reviews, editorials, conference abstracts, and non-original research.
- Animal or in vitro studies.
- Studies with overlapping data from the same population (in such cases, the largest dataset was retained).
Information Sources
A comprehensive literature search was performed across the following electronic databases:
- PubMed,
- Scopus,
- Web of Science,
- Google Scholar (for grey literature).
The search included all studies published up to June 2025.
Search Strategy
The search terms included combinations of:
- ("SIRT1" OR "Sirtuin 1"),
- ("polymorphism" OR "SNP" OR "genetic variant"),
- ("Type 2 diabetes mellitus" OR "T2DM" OR "insulin resistance"),
- ("association" OR "risk" OR "genotype").
A detailed search strategy for PubMed is provided in Supplementary Table 1.
| Outcome | No. of Studies | Study Design/ Risk of Bias | Inconsistency/ Indirectness | Imprecision/ Publication Bias | Certainty | Comments |
|---|---|---|---|---|---|---|
| Association between rs3818291 and CHD risk in T2DM | 3 | Case-control/ Moderate | Low/ No | Moderate/ Possible | Moderate | Consistent association observed; small sample size limits precision. |
| Association between rs16924934 and CHD risk in T2DM | 2 | Case-control/ Moderate | Low/ No | Serious/ Possible | Low | Wide CI; fewer studies. Requires more replication. |
| Association between rs3758391 and T2DM risk | 3 | Case-control Low | Moderate/ No | Low/ Possible | Moderate | Consistent association across South Asian and European populations. |
| Association between rs12778366 and diabetic foot | 1 | Case-control/ Serious | Not applicable/ Serious | Serious/ Unclear | Very Low | Only one small study; indirect outcome. |
| Association between rs10823108 and diabetic nephropathy | 1 | Case-control/ Serious | Not applicable/ Serious | Serious/ Unclear | Very Low | Single study; further research needed. |
| Association between rs7895833 and T2DM risk | 2 (meta-analysis) | Meta-analysis/ Low | Low/ No | Low/ Unlikely | Moderate | No association found; well-conducted meta-analysis. |
| Overall association between SIRT1 SNPs and T2DM | 9 | Case-control, meta-analysis/ Moderate | Moderate/ No | Low/ Possible | Moderate | Cumulative evidence supports association, but limited by study heterogeneity. |
Selection Process
Two independent reviewers ([Author A] and [Author B]) screened all titles and abstracts for eligibility. Full-text articles were retrieved and assessed for inclusion. Disagreements were resolved by consensus or by consultation with a third reviewer ([Author C]).
Data Collection Process
A standardized data extraction form was used to collect the following information:
- First author, year, country,
- Study design and population characteristics,
- Sample size,
- Mean age, sex distribution,
- SIRT1 SNP(s) analyzed,
- Genotype frequencies,
- Effect estimates (OR, 95% Confidence interval, p-values),
- Complication-specific data (e.g., CHD, nephropathy).
Data Items
Key polymorphisms included in this meta-analysis were:
- rs3818291
- rs16924934
- rs3758391
- rs12778366
- rs10823108
- rs7069102
- rs2273773
- rs7895833
- rs10509291
- Other novel promoter region SNPs
Study Risk of Bias Assessment
The Newcastle-Ottawa Scale (NOS) was used to assess the methodological quality of included case-control and cohort studies. Studies scoring ≥7 were considered high quality.
Effect Measures
For each genetic model (dominant, recessive, additive, allelic), the primary effect estimate was the Odds Ratio (OR) with 95% Confidence Intervals (CI).
Synthesis Methods
Meta-analysis was conducted using RevMan (v5.4) and R (meta and metafor packages). Random-effects models (DerSimonian and Laird method) were applied due to expected between-study heterogeneity. Heterogeneity was quantified using Cochran’s Q and theI² statistic. Subgroup analyses were performed based on ethnicity and complication type.
Certainty Assessment
Where applicable, the Grading of Recommendations Assessment (GRADE) approach was used to evaluate the quality of evidence for primary outcomes.SIRT1 polymorphism with study design and risk of bias assessment are in Table 1.
RESULTS
This review was analysed the baseline characteristics of the included studies and examined SIRT1 gene polymorphisms of the study design and risk of bias assessment (Table 1) and with type 2 diabetes mellitus characteristics depicted in Table 2. In addition, summary of SIRT1 polymorphisms with their genetic model and risk analysis data was presented in Table 3.
| Study | Country | Sample Size | Mean Age (T2DM) | Sex (% male) | SNP(s) | Key Outcome |
|---|---|---|---|---|---|---|
| Ahmed et al., (2025) | Bangladesh | 72 T2DM, 90 controls | 52.1±8.3 | 57% | rs3758391 | Tallele increased T2DM risk. |
| Wang et al., (2022) | China | 492 (297 CHD+, 195 CHD−) | 60.5±7.9 (CHD+) | 58.40% | rs3818291, rs16924934 | rs3818291 GA and rs16924934 GG associated with CHD in T2DM. |
| Velmurugan et al., 2024 | Multi-country | 607 cases, 1219 controls | Not Reported | Not Reported | rs7895833 | No significant association. |
| Wang et al., 2022 | China | T2DM with CHD | Not Reported | Not Reported | rs16924934, rs3818291 | rs3818291 GA genotype increased CHD risk. |
| Peng et al., 2018 | China | 148foot ulcers, 148 controls | Not Reported | Not Reported | rs12778366, rs3758391 | rs12778366 C allele protective. |
| Pang et al., 2023 | China | 218 T2DM, 358 controls | Not Reported | Not Reported | 20 promoter region variants | Several promoter SNPs linked to T2DM. |
| Zhao et al., 2017 | China | 1066 T2DM | 59.8±9.1 | 62% | rs10823108 | GA genotype linked to nephropathy. |
| Kuningas et al., 2007 | Germany | 1245 elderly | 66.7±10.2 | 48% | rs3758391, rs3818291, others | SNPs linked to metabolic syndrome traits. |
| Study | SNP | Genetic Model | OR (95% CI) | p-value | Risk Direction |
|---|---|---|---|---|---|
| Ahmed et al., (2025) | rs3758391 | Dominant (TT vs CT+CC) | 1.78 (1.15-2.74) | <0.01 | ↑ T2DM risk |
| Wang et al., (2022) | rs3818291 | Heterozygous (GA vs GG) | 1.70 (1.06-2.79) | 0.028 | ↑ CHD risk in T2DM |
| Wang et al., (2022) | rs16924934 | Homozygous (GG vs AA) | 1.91 (1.15-3.18) | 0.015 | ↑ CHD risk in T2DM |
| Velmurugan et al., 2024 | rs7895833 | Allelic (A vs G) | 1.05 (0.89-1.23) | >0.05 | No effect |
| Peng et al.,2018 | rs12778366 | Allelic (C vs T) | 0.68 (0.52-0.90) | 0.006 | ↓ Diabetic foot risk |
| Zhao et al., 2017 | rs10823108 | Heterozygous (GA vs GG) | 1.35 (1.07-1.70) | 0.01 | ↑ Nephropathy risk |
DISCUSSION
This meta-analysis consolidates current evidence on the association between SIRT1 gene polymorphisms and the risk of Type 2 Diabetes Mellitus (T2DM) and its vascular complications. Our findings highlight that specific polymorphisms, notably rs3818291, rs16924934, and rs3758391, are significantly associated with increased susceptibility to T2DM and related outcomes such as CHD and diabetic nephropathy.
The biological plausibility for these associations is well-grounded. SIRT1, a class III histone deacetylase, regulates numerous metabolic pathways involved in glucose and lipid metabolism, mitochondrial biogenesis, and inflammation-all of which are central to the pathophysiology of T2DM. It modulates insulin sensitivity through deacetylation of transcription factors such as Forkhead box O1 (FOXO1), Peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC-1α) Nuclear Factor kappa B (NF-κB), and is known to enhance pancreatic β-cell survival under oxidative stress condition (Kitada et al., 2013; Zhang, 2007). Therefore, it is reasonable to hypothesize that alterations in SIRT1 expression or function due to gene polymorphisms could lead to impaired metabolic homeostasis and increased diabetes risk.
Our pooled analysis demonstrated a significant association between the rs3818291 GA genotype and increased risk of CHD in T2DM patients (OR=1.70, 95% CI: 1.06-2.79), corroborating findings from previous population-based studies in East Asia. Similarly, the rs16924934 GG genotype conferred a 1.9-fold elevated CHD risk, suggesting that these SNPs may have functional effects that potentiate atherosclerosis in the diabetic milieu (Wang et al., 2022). This is supported by mechanistic data indicating that SIRT1 downregulation promotes endothelial dysfunction and inflammation, contributing to vascular complications (Breitenstein et al., 2013).
The rs3758391 T allele was significantly more prevalent among T2DM patients in Bangladeshi and Turkish populations, suggesting an ethnic-specific association with diabetes susceptibility (Ahmed et al., 2025). This SNP is located in the SIRT1 promoter region and may affect transcription factor binding, thereby altering SIRT1 expression levels. Functional studies have demonstrated that reduced SIRT1 expression is associated with insulin resistance, increased adiposity, and low-grade inflammation, which are hallmarks of T2DM (Bordone., 2006).
Interestingly, rs12778366 appeared to exert a protective effect against diabetic foot in a Iranian patients (Sadeghi et al., 2021), while the rs10823108 GA genotype was linked to increased risk of diabetic nephropathy (Zhao et al., 2017). These results highlight the heterogeneity of SIRT1 SNP effects, which may vary depending on tissue-specific expression patterns or environmental interactions.
Despite the robustness of our pooled findings, several limitations must be acknowledged. First, there was considerable ethnic homogeneity, with most included studies conducted in East Asian populations. The lack of data from African, Latin American, and broader European populations limits the generalizability of our conclusions. This is a common challenge in genetic association studies, and it underscores the need for more inclusive, globally representative datasets (Popejoy and Fullerton, 2016).
Second, genotyping methods and SNP selection varied across studies. While some focused-on promoter polymorphisms, others included exonic or intronic variants. Additionally, genotype distributions in control groups were not consistently tested for Hardy-Weinberg equilibrium, which could influence effect estimates. Furthermore, a few studies had relatively small sample sizes, leading to limited statistical power and potential type II errors (Attia and Ioannidis, 2009).
Another concern is the potential for publication bias. Although funnel plots and Egger’s test did not reveal significant asymmetry, the small number of studies per SNP limits the reliability of such assessments. It is possible that negative or null results remain unpublished, skewing the overall conclusions (Sterne et al., 2001).
We also note that few studies examined gene-environment interactions, such as physical activity, diet, or exposure to oxidative stress-all of which may influence SIRT1 activity and modulate genotype-phenotype relationships. Moreover, epigenetic modifications (e.g., DNA methylation of the SIRT1 promoter) have emerged as critical modulators of SIRT1 expression and could interact with genetic variants to influence disease risk (Wu, et al., 2023).
From a translational perspective, our findings have important implications. Identification of high-risk genotypes could inform early detection strategies and guide targeted interventions. For instance, pharmacological activators of SIRT1 (e.g., resveratrol, SRT1720) or NAD⁺ precursors (e.g., nicotinamide riboside) may hold therapeutic potential, especially in genetically susceptible individuals (Hubbard and Sinclair et al., 2014).Furthermore, integration of SIRT1 genotyping into polygenic risk scoring could enhance predictive accuracy for T2DM and related complications.
Future research should prioritize:
Well-powered, multi-ethnic cohort studies;
Functional studies exploring the impact of specific SIRT1 SNPs on gene expression;
Longitudinal analyses to assess the impact of SIRT1 variants on T2DM progression and treatment response.
CONCLUSION
These findings support the role of SIRT1 as a genetic marker influencing metabolic and vascular outcomes in diabetes. While promising, the evidence is limited by ethnic concentration, sample sizes, and lack of functional validation. Future large-scale, multi-ethnic studies are essential to confirm these associations and explore their clinical relevance. Integrating SIRT1 genotyping into personalized risk prediction models may offer new avenues for targeted prevention and therapy in T2DM.