Study on Expression of Gene Encoding Sirtuin-1 and Its Association with Single Nucleotide Polymorphism in Type 2 Diabetes Mellitus

Study on Expression of Gene Encoding Sirtuin-1 and Its Association with Single Nucleotide Polymorphism in Type 2 Diabetes Mellitus | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Study on Expression of Gene Encoding Sirtuin-1 and Its Association with Single Nucleotide Polymorphism in Type 2 Diabetes Mellitus Era karn, Suman Bala Sharma, Manoj Kumar Nandkeoliar, Preeti Yadav, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9490914/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Type 2 diabetes is a complex metabolic disorder, which is influenced by the interplay of genes and environment. From the perspective of energy balance and insulin signaling, some genes are coming forward as potential contributors to susceptibility to the disorder. Sirtuin 1 (SIRT1), a NAD⁺-dependent deacetylase, plays a critical role at the crossroads of glucose metabolism, insulin action, mitochondrial function, and inflammation. This study investigated whether a SIRT1 T/C polymorphism and the relative expression of SIRT1 are associated with susceptibility to T2DM in a North Indian population. Methods We conducted a case-control study involving 45 patients with T2DM and 45 healthy controls, matched for age and sex. The SIRT1 T/C polymorphism was identified by PCR-RFLP. The relative expression of SIRT1 was measured by RT-qPCR. Genotype and allele frequencies were compared between cases and controls, and tested for Hardy-Weinberg equilibrium. Odds ratios with 95% confidence intervals were calculated to estimate disease risk. Relative expression was analyzed using the 2⁻ΔΔCt method. Results There were significant differences in genotype and allelic frequencies between cases and controls. Higher frequency of the C allele was observed in T2DM patients while T allele was more prevalent among healthy controls. Patients with TC or CC genotype had a significantly higher risk of T2DM than TT genotype. Expression analysis revealed a significantly lower mean ΔΔCt value in T2DM patients than controls (p = 0.00213), indicating that SIRT1 expression was upregulated in T2DM patients. Conclusions The SIRT1 T/C polymorphism and high expression of SIRT1 are significantly associated with susceptibility to T2DM. SIRT1 is having potential as a molecular biomarker and therapeutic target for Type 2 Diabetes Mellitus. Molecular Genetics Applied Biochemistry Type 2 Diabetes Mellitus SIRT1 Gene Expression Single Nucleotide Polymorphism Insulin Resistance Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Type 2 Diabetes Mellitus (T2DM) is among the most common non-communicable diseases in the world and is a significant global health problem [ 1 ]. T2DM is responsible for more than 90% of all diabetes cases and is characterized by severe microvascular and macrovascular complications such as cardiovascular disease, nephropathy, neuropathy, and retinopathy [ 2 ]. The increasing incidence of T2DM is found due to increased rate of urbanization, a sedentary lifestyle, obesity, and genetic factors, especially in developing nations like India [ 3 ]. The pathophysiology of T2DM is a result of the intricate interplay between peripheral insulin resistance and progressive pancreatic β-cell dysfunction [ 4 ]. Hyperglycemia leads to oxidative stress, low-grade inflammation, mitochondrial damage, and abnormalities in lipid metabolism, further fueling insulin resistance and β-cell failure [ 5 ]. Although there have been improvements in the treatment modalities, there is still a lack of efficient long-term glycemic control, which emphasizes the importance of understanding the molecular mechanisms of the disease. Recent studies have targeted epigenetic regulators and metabolic sensors that mediate the relationship between cellular energy metabolism and gene expression [ 6 ]. Sirtuin-1 (SIRT1), a sirtuin protein family of NAD⁺-dependent deacetylases, has been identified as a major regulator of metabolic homeostasis [ 7 ]. SIRT1 affects insulin signaling pathways, glucose production in the liver, lipid metabolism, mitochondrial biogenesis, oxidative stress responses, and inflammation by deacetylating transcription factors PGC-1α, FOXO1, and NF-κB [ 8 , 9 ]. Decreased SIRT1 expression and activity have been linked to insulin resistance, obesity, metabolic syndrome, and Type 2 Diabetes Mellitus [ 10 ]. Moreover, single nucleotide polymorphisms (SNPs) in the SIRT1 gene can affect the transcriptional activity and enzymatic activity of SIRT1, thereby affecting the metabolic regulation and disease susceptibility of individuals [ 11 ]. Hence, assessing both gene expression and genetic polymorphism of SIRT1 can offer its possible role as a biomarker and therapeutic target. Materials and methods Study Design This case–control study was conducted for a period of 12 months in collaboration with a tertiary care hospital. A total of 90 subjects were enrolled and divided into two groups: Cases: 45 patients diagnosed with Type 2 Diabetes Mellitus Controls: 45 apparently healthy individuals without a family history of diabetes.Cases and controls were matched on age and sex. Ethical Considerations The Institutional Ethics Committee approved the study protocol. Informed consent in writing was obtained from all participants prior to sample collection. Sample Collection. Peripheral venous blood (5 ml) was collected in EDTA vacutainers. DNA Extraction DNA was extracted from it using a standard salting-out method. Spectrophotometry was used to evaluate DNA purity and concentration. RNA Extraction and cDNA Synthesis RNA isolation was done using the QIAamp RNA Blood Mini Kit. The purity and concentration of RNA were determined spectrophotometrically. Reverse transcription was done to synthesize the complementary DNA (cDNA). PCR Amplification The SIRT1 gene region containing the T/C polymorphism was amplified using gene-specific primers. Amplification was carried out in a thermal cycler under optimised conditions of PCR. Restriction Fragment Length Polymorphism (RFLP) Analysis The PCR products were digested with a specific restriction enzyme recognizing the polymorphic site. Digested fragments were separated on agarose gel electrophoresis and visualized under UV illumination. Genotypes were identified based on fragment sizes. Quantitative real-time PCR SIRT1 expression was measured by real-time PCR using SYBR Green. The housekeeping genes were used as an internal control. The relative gene expression levels were derived using the Livak method (2⁻ΔΔCt) Statistical Analysis Data are presented as mean ± standard deviation.Genotype and allele frequencies were calculated by direct counting. Hardy-Weinberg equilibrium was assessed using the chi-square test. Differences between cases and controls were analyzed by chi-square test. Odds Ratio with 95% CI were calculated to assess the risk association. A p-value < 0.05 was considered as statistically significant.Comparison of ΔΔCt between cases and controls was done using an independent t-test. A p-value of less than 0.05 was considered statistically significant. Results Demographic characteristics The study comprises 45 patients with Type 2 Diabetes-mellitus as cases and 45 healthy controls. The age and gender of the cases and controls were matched and there was no statistical difference among them (p > 0.05). There was a highly significant increase in HbA1c levels in the case group compared to the control group (p < 0.001). This indicates poor glycemic control among cases relative to controls. Both groups have nearly identical average BMI value. Smoking and alcohol consumption did not significantly affect the study among participants (p > 0.05)(Table 1) T2DM patients show significantly higher total cholesterol, triglycerides, LDL, and VLDL, with lower HDL compared to controls (p < 0.0001). This pattern indicates diabetic dyslipidemia (Table 2) Table 1: Demographic profile of T2DM Cases and Healthy Controls. Parameters Healthy Controls (N=45) T2DM Cases (N=45) P-Value Age (years) 48.91 ± 7.12 48.91 ± 7.61 0.70 Sex Female 21(46%) 23(51%) 0.67 Male 24(54%) 22(49%) Socio- Economic status Poor 16(37%) 12(26.1%) 0.416 Middle Class 15(32.6%) 20(45.6%) Upper Middle Class 14(30.4%) 13(28.3%) Duration of disease(months) Nil 11.64 ± 4.08 - Smoking 21 (45.7%) 21 (45.7%) 1.00 Alcohol 12 (26.1%) 19 (41.3%) 0.186 BMI 28.10 ± 4.52 28.20 ± 5.18 0.9208 HbA1c 5.84 ± 0.65 10.02 ± 2.37 < 0.001* Values are Mean ± SD Table 2:Serum Lipid profile of T2DM Cases and Healthy Controls. Lipid Parameter Healthy Controls T2DM Patients P-Value Total Cholesterol (TC) mg/dl 146.22 ± 25.34 166.8 ± 35.15 < 0.0001* Triglycerides (TAG) mg/dl 136.94 ± 38.59 177.14 ± 81.48 < 0.0001* HDL-C mg/dl 45.6 ± 9.72 35.29 ± 7.84 < 0.0001* LDL-C. mg/dl 97.62 ± 15.43 125.44 ± 28.79 < 0.0001* VLDL-C. mg/dl 25.5 ± 7.51 33.68 ± 20.02 < 0.0001* Values are Mean ± SD *HDL-C – High density Lipoprotein Cholesterol, LDL-C – Low density Lipoprotein Cholesterol, VLDL-C – Very Low density Lipoprotein Cholesterol Allelic Distribution The T allele frequency was significantly lower in T2DM cases (51.09%) compared to controls (84.44%) (p < 0.001). The T allele was associated with a protective effect against T2DM (OR = 0.192; 95% CI: 0.095–0.388) (Table 3, Fig 1). Table 3: Showing the Allelic Distribution between Type 2 Diabetes Mellitus and Healthy controls . Alleles Healthy Controls(n=45) T2DM Cases(n=45) P-value OR 95% CI T 76 47 <0.001* 0.192 0.095-0.388 84.44% 51.09% C 14 16 15.56% 48.91% Total 45(100%) 45(100%) *OR- Odds Ratio, 95% CI- 95% confidence interval Figure 1: Showing the Allelic Distribution between cases and controls Genotypic Distribution The distribution of SIRT1 T/C polymorphism genotype in cases and controls shows statistically significant difference (χ² = 6.21, p = 0.045) in genotype distribution between cases and controls, which indicates that SIRT1 polymorphism is associated with T2DM (Table 4, Fig 2). Table 4: Showing Genotypic Distribution between Type 2 Diabetes Mellitus and Healthy controls. Genotype Healthy Controls(n=45) T2DM Cases(n=45) P value TT 14 (31.11%) 17 (37.78%} 0.0334* CT 5 (11.11%) 13 (28.89%) CC 26 (57.58%) 16 (33.33%) Figure 2: Showing Genotypic Distribution between Type 2 Diabetes Mellitus and healthy controls. Genetic risk Association: Odds Ratio Analysis Odds ratio analysis indicated enhanced susceptibility to T2DM in variant genotype carriers. Carriers of at least one C allele, that is, TC + CC, had a significantly higher risk of developing T2DM as compared to carriers of the TT genotype (Table 5, Fig 3) . Table 5: Estimation of risk with a 95% Confidence Interval between Genotypes in Type 2 Diabetes mellitus and healthy controls. Genotype Healthy Controls(n=45) T2DM Cases(n=45) P value OR 95% CI TT VS NON-TT 33/12 17 /29 <0.001* 0.19 0.087-0520 CT VS CC 10/2 13/16 0.03* 0.16 0.03-0.313 TT VS CC 33/2 17/16 <0.001* 0.064 0.013-0.877 Figure 3: Showing the Risk estimation between Genotypes in Type 2 Diabetes mellitus and healthy controls. Hardy-Weinberg Equilibrium (HWE) The genotype distribution of the SIRT1(T/C) polymorphism in the control group was in accordance with Hardy–Weinberg equilibrium (χ² = 0.47, p = 0.49), indicating genetic stability of the study population. The genotype distribution in T2DM cases was not in HWE (χ² = 4.12, p = 0.042), indicating a possible association of the polymorphism with the disease status (Table 6). Table 6: Observed and Expected SNP Genotype Frequencies in Type 2 Diabetes Mellitus Cases and Healthy Controls Group Genotype Observed Frequency n (%) Expected Frequency P-value Healthy Controls TT 71.31% 32.09% 0.3011 CT 26.27% 11.82% CC 2.42% 1.09% T2DM Cases TT 26.10% 12.01% 0.042* CT 49.98% 22.99% CC 23.92% 11.01% Independent t-Test Comparison of ΔΔCt Values Between Case and Control Groups The SIRT1 gene was relatively quantified and there was a significant difference between the healthy controls and the patients with Type 2 Diabetes Mellitus. The mean value of the ΔΔCt of the control group was 3.67 ± 2.85, however, T2DM patients had a lower mean value of ΔΔCt of 1.04 ±3.92. This difference was statistically significant while using the independent samples t-test (t = 3.205, p = 0.00213), which implies that the change of the SIRT1 gene expression in people with T2DM was significant (Table 7, Fig 4). Table 7: Independent t-Test Comparison of Sirtuin 1 Gene Expression (ΔΔCt) among Type 2 Diabetes mellitus and healthy controls. Group Mean ± SD 95% CI t-Statistic p-Value Healthy Control 3.67 ± 2.85 –0.31 to2.69 3.206 0.00213* T2DM Case 1.04 ± 3.92 2.69 to 4.65 Figure 4: Showing the Sirtuin 1 Gene expression level between T2DM cases and healthy controls. Discussion The present study showed a significant association of the SIRT1 gene polymorphism with T2DM (higher frequencies of the TC and CC genotypes and C allele in diabetic patients). Our results suggest that the genetic variation in the SIRT1 gene may contribute to increased susceptibility to T2DM. It plays a central role in metabolic homeostasis by enhancing insulin sensitivity, controlling hepatic gluconeogenesis, and suppressing inflammatory signaling; mutations in SIRT1 genes may alter its activity and decrease those protective mechanisms that promote insulin resistance and hyperglycemia [ 12 , 13 ]. Previous studies have reported associations between SIRT1 polymorphisms and T2DM in Asian populations, supporting the biological possibility of the present findings [ 14 , 15 ]. Dong et al. demonstrated a significant association between SIRT1 genetic variants and T2DM risk in a Chinese population, suggesting ethnicity-specific genetic influences [ 14 ]. Shimoyama et al. also reported association between SIRT1 polymorphism and visceral fat accumulation, a major contributor to insulin resistance [ 15 ]. Genetic variation in SIRT1 has also been associated with modified energy metabolism, glucose homeostasis, and insulin signaling pathways . The present study also shows a significant difference in SIRT1 level of expression between T2DM patients and healthy subjects, accompanied by a remarkable up-regulation of SIRT1 among diabetic patients. This changed regulation could represent a cellular response to prolonged metabolic load resulting from chronic hyperglycemia and insulin resistance, both of which are characteristic for T2DM [ 16 ]. SIRT1 is a metabolic sensor that transduces information on cellular energy status to transcriptional control and its up-regulated expression in T2DM may represent an adaptive response to restore metabolic homeostasis despite prolonged exposure to high levels of nutrient excess [ 17 ]. SIRT1 has been implicated in modulating oxidative stress, inflammation and glucose metabolism and mitochondrial function by deacetylation of several key transcription factors or co -activators such as FOXO,2 NF-κB3 and PGC-1α [ 18 , 19 ]. Experimental models have related SIRT1 activation with improved insulin sensitivity, mitochondrial biogenesis and down-regulation of pro-inflammatory signaling pathways. Hence, in the light of these findings, SIRT1 upregulation in T2DM patients of this study would correspond to a compensatory protective program directed at attenuating oxidative injury, diminution of inflammatory mediators and maintenance of glucose homeostasis [ 20 ]. According to these results, the previous studies showed the up-regulated expression of SIRT1 in peripheral blood mono-nuclear cells from T2DM patients and further suggested the role of SIRT1 in systemic metabolic adjustment [ 21 ]. However, even though SIRT1 is over-expressed in T2DM patients, hyperglycemia and insulin resistance persist. This may indicate that compensation of SIRT1 activity is not sufficient to compensate the metabolic dysfunction. The activity of SIRT1 could be inactivated due to the decline of its endogenous co-factor NAD⁺, or some post-translational modifications [ 22 ], such as the impaired downstream signaling cascades, thus attenuating protection. These variabilities in results and inter-individual variation of SIRT1 expression may be explained by differences in allele frequencies, duration of the disease, glycemic control,life-style factors,sample size, study designs, and environmental exposures. This study further adds to the limited Indian data and underlines the importance of population-specific genetic studies in deciphering the complex etiology of T2DM. CONCLUSION The present study indicates that SIRT1 gene expression and SIRT1 T/C polymorphism are significantly associated with Type 2 Diabetes-mellitus (T2DM). There was a substantial up-regulation of SIRT1 gene expression in diabetic patients compared to healthy controls, which indicated a compensatory or stress response modification in metabolic regulatory pathways, as SIRT1 is known to be a central regulator of energy metabolism and glucose homeostasis. Present study also revealed that the T(wild allele) are protective while the C allele is mutant and susceptible to T2DM. These findings suggest that SIRT1 expression and SNP variations play a significant role in the pathogenesis of T2DM and identify SIRT1 as a promising biomarker and therapeutic target for early diagnosis and metabolic intervention. However, further multi-center and population-based studies are needed to confirm these associations and validate the clinical utility of SIRT1 testing in diabetic patients. This study is aligned with UN Sustainable Development Goal No. 3 (Good Health and Well-being) Implementation of Govt. Of India. Statements & Declarations Acknowledgments: The authors would like to thank the Department of Biochemistry and the Department of Medicine, School of Medical Sciences and Research, Sharda University, for providing the necessary laboratory facilities and infrastructure to carry out this research. We would like to thank all the participants of this study for their cooperation and willingness to contribute to this research. Funding : Nil Competing Interest: The authors declare no conflict of interest. Author Contributions: “All authors contributed to the study. Material preparation, validation, formal analysis,data collection and investigation were performed by Era karn. Study conception,design,resources,supervision and original draft was written by Suman Bala Sharma.Project administration and editing after review was done by Manoj Kumar Nandkeoliar.Visualization and methodology were conducted by Preeti Yadav and Mohit Kumar. All authors read and approved the final manuscript.” Data Availability Statement: The data generated and analyzed in this study can be obtained by contacting the corresponding author with a reasonable request. The data are not publicly available due to ethical concerns and maintaining confidentiality. Ethics approval: The study was conducted in accordance with the Declaration and Approval by the Institutional Ethics Committee (Ref no. SU/SMS&R/76-A/2025/09. Issue date: 4/02/2025) of School of Medical Sciences & Research , Sharda University,Greater Noida,U.P, India. Consent to participate: Informed consent was obtained from all subjects involved in the study. References American Diabetes Association. Classification and diagnosis of diabetes. Diabetes Care. 2023;46(Suppl 1):S19–S40. DeFronzo RA, Ferrannini E, et al. Type 2 diabetes mellitus. Nat Rev Dis Primers. 2015;1:15019. International Diabetes Federation. IDF Diabetes Atlas. 10th ed. Brussels: IDF; 2021. Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444(7121):840–6. Evans JL, Goldfine ID, et al. Oxidative stress and stress-activated signaling pathways. Endocr Rev. 2002;23(5):599–622. Ling C, Rönn T. Epigenetics in human obesity and type 2 diabetes. Cell Metab. 2019;29(5):1028–44. Haigis MC, Sinclair DA,et al. Mammalian sirtuins: biological insights and disease relevance. Annu Rev Pathol. 2010;5:253–95. Rodgers JT, Lerin C, et al. Nutrient control of glucose homeostasis through a complex of PGC-1α and SIRT1. Nature. 2005;434(7029):113–8. Kauppinen A, Suuronen T, et al. Antagonistic crosstalk between NF-κB and SIRT1. Cell Signal. 2013;25(10):1939–48. Pfluger PT, Herranz D, et al. Sirt1 protects against high-fat diet-induced metabolic damage. Proc Natl Acad Sci USA. 2008;105(28):9793–8. Zillikens MC, van Meurs JB, et al. SIRT1 genetic variation is related to BMI and risk of obesity. Diabetes. 2009;58(12):2828–34. Guarente L. Sirtuins as regulators of metabolism and healthspan. Nat Rev Mol Cell Biol. 2011;12(7):443–454. Haigis MC, Sinclair DA,et al. Mammalian sirtuins: biological insights and disease relevance. Annu Rev Pathol. 2010;5:253–295. Dong Y, Guo T, et al. SIRT1 genetic polymorphisms are associated with type 2 diabetes in a Chinese population. Diabetes. 2011;60(3):961–966. Shimoyama Y, Mitsuda Y, et al. SIRT1 polymorphisms are associated with visceral fat accumulation and metabolic syndrome. Diabetes Res Clin Pract. 2012;96(1):e15–e18. Kitada M, Koya D, et al. SIRT1 in type 2 diabetes: mechanisms and therapeutic potential. Diabetes Metab J. 2013;37(5):315–25. Imai S, Guarente L, et al. NAD⁺ and sirtuins in aging and disease. Trends Cell Biol. 2014;24(8):464–71. Rodgers JT, Puigserver P, et al. Fasting-dependent glucose and lipid metabolic response through hepatic sirtuin 1. Proc Natl Acad Sci U S A. 2007;104(31):12861–6. Yeung F, Hoberg JE, et al. Modulation of NF-κB-dependent transcription and cell survival by the SIRT1 deacetylase. EMBO J. 2004;23(12):2369–80. de Kreutzenberg SV, Ceolotto G, et al. Downregulation of the longevity-associated protein SIRT1 in insulin resistance and metabolic syndrome. Diabetes. 2010;59(4):1006–15. Kiran S, Anwar T, et al. SIRT1 gene expression in type 2 diabetes mellitus. J Diabetes Metab Disord. 2015;14:13. Canto C, Auwerx J,et al. NAD⁺ as a signaling molecule modulating metabolism. Cold Spring Harb Symp Quant Biol. 2011;76:291–8. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9490914","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":627454182,"identity":"f95e372d-eeec-49d8-9273-a88fdc5f2070","order_by":0,"name":"Era karn","email":"","orcid":"","institution":"Sharda university","correspondingAuthor":false,"prefix":"","firstName":"Era","middleName":"","lastName":"karn","suffix":""},{"id":627454183,"identity":"46160e93-726d-4dde-8ae8-712ec28f97ad","order_by":1,"name":"Suman Bala 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3","display":"","copyAsset":false,"role":"figure","size":231877,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eShowing the Risk estimation between Genotypes in Type 2 Diabetes mellitus and healthy controls.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9490914/v1/8ee7577c6730c9d723c00993.png"},{"id":107707149,"identity":"a6d09d3e-a1ea-42ba-86ca-09677f59425f","added_by":"auto","created_at":"2026-04-24 09:19:38","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":180700,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eShowing the Sirtuin 1 Gene expression level between T2DM cases and healthy 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is among the most common non-communicable diseases in the world and is a significant global health problem [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. T2DM is responsible for more than 90% of all diabetes cases and is characterized by severe microvascular and macrovascular complications such as cardiovascular disease, nephropathy, neuropathy, and retinopathy [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The increasing incidence of T2DM is found due to increased rate of urbanization, a sedentary lifestyle, obesity, and genetic factors, especially in developing nations like India [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe pathophysiology of T2DM is a result of the intricate interplay between peripheral insulin resistance and progressive pancreatic β-cell dysfunction [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Hyperglycemia leads to oxidative stress, low-grade inflammation, mitochondrial damage, and abnormalities in lipid metabolism, further fueling insulin resistance and β-cell failure [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Although there have been improvements in the treatment modalities, there is still a lack of efficient long-term glycemic control, which emphasizes the importance of understanding the molecular mechanisms of the disease.\u003c/p\u003e \u003cp\u003eRecent studies have targeted epigenetic regulators and metabolic sensors that mediate the relationship between cellular energy metabolism and gene expression [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Sirtuin-1 (SIRT1), a sirtuin protein family of NAD⁺-dependent deacetylases, has been identified as a major regulator of metabolic homeostasis [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. SIRT1 affects insulin signaling pathways, glucose production in the liver, lipid metabolism, mitochondrial biogenesis, oxidative stress responses, and inflammation by deacetylating transcription factors PGC-1α, FOXO1, and NF-κB [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDecreased SIRT1 expression and activity have been linked to insulin resistance, obesity, metabolic syndrome, and Type 2 Diabetes Mellitus [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Moreover, single nucleotide polymorphisms (SNPs) in the SIRT1 gene can affect the transcriptional activity and enzymatic activity of SIRT1, thereby affecting the metabolic regulation and disease susceptibility of individuals [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Hence, assessing both gene expression and genetic polymorphism of SIRT1 can offer its possible role as a biomarker and therapeutic target.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003e\u003cstrong\u003eStudy Design\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis case–control study was conducted for a period of 12 months in collaboration with a tertiary care hospital. A total of 90 subjects were enrolled and divided into two groups:\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003e\u0026nbsp;Cases: 45 patients diagnosed with Type 2 Diabetes Mellitus\u003c/li\u003e\n \u003cli\u003eControls: 45 apparently healthy individuals without a family history of diabetes.Cases and controls were matched on age and sex.\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Institutional Ethics Committee approved the study protocol. Informed consent in writing was obtained from all participants prior to sample collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample Collection.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeripheral venous blood (5 ml) was collected in EDTA vacutainers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA Extraction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDNA was extracted from it using a standard salting-out method. Spectrophotometry was used to evaluate DNA purity and concentration.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRNA Extraction and cDNA Synthesis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRNA isolation was done using the QIAamp RNA Blood Mini Kit. The purity and concentration of RNA were determined spectrophotometrically. Reverse transcription was done to synthesize the complementary DNA (cDNA).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePCR Amplification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe SIRT1 gene region containing the \u0026nbsp;T/C polymorphism was amplified using gene-specific primers. Amplification was carried out in a thermal cycler under optimised conditions of PCR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRestriction Fragment Length Polymorphism (RFLP) Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe PCR products were digested with a specific restriction enzyme recognizing the polymorphic site. Digested fragments were separated on agarose gel electrophoresis and visualized under UV illumination. Genotypes were identified based on fragment sizes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eQuantitative real-time PCR\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSIRT1 expression was measured by real-time PCR using SYBR Green. The housekeeping genes were used as an internal control. The relative gene expression levels were derived using the Livak method (2⁻ΔΔCt)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData are presented as mean \u0026nbsp; ± standard deviation.Genotype and allele frequencies were calculated by direct counting. Hardy-Weinberg equilibrium was assessed using the chi-square test. Differences between cases and controls were analyzed by chi-square test. Odds Ratio with 95% CI were calculated to assess the risk association. A p-value \u0026lt; 0.05 was considered as statistically significant.Comparison of ΔΔCt between cases and controls was done using an independent t-test. A p-value of less than 0.05 was considered statistically significant.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eDemographic characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study comprises 45 patients with Type 2 Diabetes-mellitus as cases and 45 healthy \u0026nbsp; controls. The age and gender of the cases and controls were matched \u0026nbsp;and there was no statistical difference among them (p \u0026gt; 0.05).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThere was a highly significant increase in HbA1c levels in the case group compared to the control group (p \u0026lt; 0.001). This indicates poor glycemic control among cases relative to controls.\u003c/p\u003e\n\u003cp\u003eBoth groups have nearly identical average BMI value.\u003c/p\u003e\n\u003cp\u003eSmoking and alcohol consumption did not significantly affect the study among participants (p \u0026gt; 0.05)(Table 1)\u003c/p\u003e\n\u003cp\u003eT2DM patients show significantly higher total cholesterol, triglycerides, LDL, and VLDL, with lower HDL compared to controls (p \u0026lt; 0.0001). This pattern indicates diabetic dyslipidemia (Table 2)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Demographic profile of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eT2DM Cases and Healthy Controls.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"648\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameters\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy Controls\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=45)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2DM Cases\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(N=45)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e48.91 \u0026plusmn; 7.12\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e48.91 \u0026plusmn; 7.61\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;0.70\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 52px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21(46%)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e23(51%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.67\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24(54%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22(49%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"3\" valign=\"top\" style=\"width: 74px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocio- Economic\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;status\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePoor\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16(37%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12(26.1%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.416\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMiddle Class\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15(32.6%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e20(45.6%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper Middle Class\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14(30.4%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13(28.3%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDuration of disease(months)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNil\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11.64 \u0026plusmn; 4.08\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e-\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21 (45.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21 (45.7%)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;1.00 \u0026nbsp; \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12 (26.1%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e19 (41.3%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.186\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.10 \u0026plusmn; 4.52\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.20\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn; \u0026nbsp;5.18\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;0.9208\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHbA1c\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5.84 \u0026plusmn; \u0026nbsp;0.65\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 124px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10.02 \u0026plusmn; 2.37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 91px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u0026lt; 0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e Values are Mean\u003cstrong\u003e\u0026nbsp;\u0026plusmn;\u003c/strong\u003e SD\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:Serum Lipid profile of T2DM Cases and Healthy Controls.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLipid Parameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy Controls\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2DM Patients\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal Cholesterol (TC) mg/dl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e146.22 \u0026plusmn; 25.34\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e166.8 \u0026plusmn; 35.15\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.0001*\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTriglycerides (TAG) mg/dl\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e136.94 \u0026plusmn; 38.59\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e177.14 \u0026plusmn; 81.48\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.0001*\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHDL-C \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;mg/dl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e45.6 \u0026plusmn; 9.72\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e35.29 \u0026plusmn; 7.84\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.0001*\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLDL-C. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;mg/dl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e97.62 \u0026plusmn; 15.43\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e125.44 \u0026plusmn; 28.79\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.0001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 150px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVLDL-C. \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;mg/dl\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.5 \u0026plusmn; 7.51\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e33.68 \u0026plusmn; 20.02\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 151px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt; 0.0001*\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eValues are Mean\u003cstrong\u003e\u0026nbsp;\u0026plusmn;\u003c/strong\u003e SD\u003c/p\u003e\n\u003cp\u003e*HDL-C \u0026ndash; High density Lipoprotein Cholesterol, LDL-C \u0026ndash; Low density Lipoprotein Cholesterol, VLDL-C \u0026ndash; Very Low density Lipoprotein Cholesterol\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAllelic Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe T allele frequency was significantly lower in T2DM cases (51.09%) compared to controls (84.44%) (p \u0026lt; 0.001). The T allele was associated with a protective effect against T2DM (OR = 0.192; 95% CI: 0.095\u0026ndash;0.388) (Table 3, Fig 1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eShowing the\u0026nbsp; \u0026nbsp;Allelic Distribution \u0026nbsp;between Type 2 Diabetes Mellitus\u0026nbsp;\u0026nbsp; and Healthy controls\u003c/strong\u003e.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlleles\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eControls(n=45)\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2DM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCases(n=45)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e76\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e47\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.192\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"4\" style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.095-0.388\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e84.44%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e51.09%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15.56%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e48.91%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e45(100%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e45(100%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 128px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*OR- Odds Ratio, 95% CI- 95% confidence interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 1:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eShowing the \u0026nbsp; Allelic Distribution \u0026nbsp;between cases and controls\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenotypic Distribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe distribution of SIRT1 T/C polymorphism genotype in cases and controls shows statistically significant difference (\u0026chi;\u0026sup2; = 6.21, p = 0.045) in genotype distribution between cases and controls, which indicates that SIRT1 polymorphism is associated with T2DM (Table 4, Fig 2).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eShowing \u0026nbsp;Genotypic Distribution between Type 2 Diabetes Mellitus\u0026nbsp;\u0026nbsp; and Healthy controls.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 169px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenotype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eControls(n=45)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2DM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCases(n=45)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 169px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14 (31.11%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17 (37.78%}\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" valign=\"bottom\" style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.0334*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 169px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (11.11%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13 (28.89%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\" style=\"width: 169px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 217px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e26 (57.58%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 180px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16 (33.33%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 2:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eShowing Genotypic Distribution between Type 2 Diabetes Mellitus \u0026nbsp;and healthy controls.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenetic risk Association: Odds Ratio Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOdds ratio analysis indicated enhanced susceptibility to T2DM in variant genotype carriers. Carriers of at least one C allele, that is, TC + CC, had a significantly higher risk of developing T2DM as compared to carriers of the TT genotype (Table 5, Fig 3) .\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5: Estimation of risk with a 95% Confidence Interval between Genotypes\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ein Type 2 Diabetes mellitus and healthy controls.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenotype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy Controls(n=45)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2DM\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eCases(n=45)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT VS NON-TT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e33/12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17 /29\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.087-0520\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT VS CC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10/2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13/16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.03-0.313\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 123px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT VS CC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 132px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e33/2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 118px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17/16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 85px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;0.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 80px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.064\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.013-0.877\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eFigure 3:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eShowing the Risk estimation between Genotypes in Type 2 Diabetes mellitus \u0026nbsp; and \u0026nbsp;healthy controls.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHardy-Weinberg Equilibrium (HWE)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe genotype distribution of the SIRT1(T/C) polymorphism in the control group was in accordance with Hardy\u0026ndash;Weinberg equilibrium (\u0026chi;\u0026sup2; = 0.47, p = 0.49), indicating genetic stability of the study population.\u003c/p\u003e\n\u003cp\u003eThe genotype distribution in T2DM cases was not in HWE (\u0026chi;\u0026sup2; = 4.12, p = 0.042), indicating a possible association of the polymorphism with the disease status (Table 6).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 6:\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Observed and Expected SNP Genotype Frequencies in Type 2 Diabetes Mellitus Cases and Healthy Controls\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGenotype\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eObserved Frequency n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eExpected Frequency\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy Controls\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e71.31%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e32.09%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.3011\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.27%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11.82%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.42%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.09%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;T2DM Cases\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e26.10%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e12.01%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"3\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.042*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCT\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e49.98%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22.99%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 117px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 186px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e23.92%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 158px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11.01%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eIndependent t-Test Comparison of \u0026Delta;\u0026Delta;Ct Values Between Case and Control Groups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe SIRT1 gene was relatively quantified and there was a significant difference between the healthy controls and the patients with Type 2 Diabetes Mellitus. The mean value of the \u0026Delta;\u0026Delta;Ct \u0026nbsp;of the control group was 3.67 \u0026plusmn; 2.85, however, T2DM patients had a lower mean value of \u0026nbsp;\u0026Delta;\u0026Delta;Ct of 1.04 \u0026plusmn;3.92. This difference was statistically significant while using the independent samples t-test (t = 3.205, p = 0.00213), which implies that the change of the SIRT1 gene expression in people with T2DM was significant (Table 7, Fig 4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 7: Independent t-Test\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eComparison of Sirtuin 1 Gene Expression (\u0026Delta;\u0026Delta;Ct) among Type 2 Diabetes mellitus \u0026nbsp;and \u0026nbsp;healthy controls.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroup\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003et-Statistic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy Control\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.67 \u0026plusmn; 2.85\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026ndash;0.31 to2.69\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 83px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3.206\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" style=\"width: 84px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.00213*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 157px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT2DM Case\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 170px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.04 \u0026plusmn; 3.92\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 140px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.69 to 4.65\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eFigure 4:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eShowing the Sirtuin 1 Gene expression level between T2DM cases and \u0026nbsp;healthy controls.\u003c/strong\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe present study showed a significant association of the SIRT1 gene polymorphism with T2DM (higher frequencies of the TC and CC genotypes and C allele in diabetic patients). Our results suggest that the genetic variation in the SIRT1 gene may contribute to increased susceptibility to T2DM. It plays a central role in metabolic homeostasis by enhancing insulin sensitivity, controlling hepatic gluconeogenesis, and suppressing inflammatory signaling; mutations in SIRT1 genes may alter its activity and decrease those protective mechanisms that promote insulin resistance and hyperglycemia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Previous studies have reported associations between SIRT1 polymorphisms and T2DM in Asian populations, supporting the biological possibility of the present findings [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Dong et al. demonstrated a significant association between SIRT1 genetic variants and T2DM risk in a Chinese population, suggesting ethnicity-specific genetic influences [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Shimoyama et al. also reported association between SIRT1 polymorphism and visceral fat accumulation, a major contributor to insulin resistance [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGenetic variation in SIRT1 has also been associated with modified energy metabolism, glucose homeostasis, and insulin signaling pathways .\u003c/p\u003e \u003cp\u003eThe present study also shows a significant difference in SIRT1 level of expression between T2DM patients and healthy subjects, accompanied by a remarkable up-regulation of SIRT1 among diabetic patients. This changed regulation could represent a cellular response to prolonged metabolic load resulting from chronic hyperglycemia and insulin resistance, both of which are characteristic for T2DM [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. SIRT1 is a metabolic sensor that transduces information on cellular energy status to transcriptional control and its up-regulated expression in T2DM may represent an adaptive response to restore metabolic homeostasis despite prolonged exposure to high levels of nutrient excess [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSIRT1 has been implicated in modulating oxidative stress, inflammation and glucose metabolism and mitochondrial function by deacetylation of several key transcription factors or co -activators such as FOXO,2 NF-κB3 and PGC-1α [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Experimental models have related SIRT1 activation with improved insulin sensitivity, mitochondrial biogenesis and down-regulation of pro-inflammatory signaling pathways. Hence, in the light of these findings, SIRT1 upregulation in T2DM patients of this study would correspond to a compensatory protective program directed at attenuating oxidative injury, diminution of inflammatory mediators and maintenance of glucose homeostasis [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAccording to these results, the previous studies showed the up-regulated expression of SIRT1 in peripheral blood mono-nuclear cells from T2DM patients and further suggested the role of SIRT1 in systemic metabolic adjustment [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. However, even though SIRT1 is over-expressed in T2DM patients, hyperglycemia and insulin resistance persist. This may indicate that compensation of SIRT1 activity is not sufficient to compensate the metabolic dysfunction. The activity of SIRT1 could be inactivated due to the decline of its endogenous co-factor NAD⁺, or some post-translational modifications [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], such as the impaired downstream signaling cascades, thus attenuating protection.\u003c/p\u003e \u003cp\u003eThese variabilities in results and inter-individual variation of SIRT1 expression may be explained by differences in allele frequencies, duration of the disease, glycemic control,life-style factors,sample size, study designs, and environmental exposures. This study further adds to the\u003c/p\u003e \u003cp\u003elimited Indian data and underlines the importance of population-specific genetic studies in deciphering the complex etiology of T2DM.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThe present study indicates that SIRT1 gene expression and SIRT1 T/C polymorphism are significantly associated with Type 2 Diabetes-mellitus (T2DM). There was a substantial up-regulation of SIRT1 gene expression in diabetic patients compared to healthy controls, which indicated a compensatory or stress response modification in metabolic regulatory pathways, as SIRT1 is known to be a central regulator of energy metabolism and glucose homeostasis. Present study also revealed that the T(wild allele) are protective while the C allele is mutant and susceptible to T2DM. These findings suggest that SIRT1 expression and SNP variations play a significant role in the pathogenesis of T2DM and identify SIRT1 as a promising biomarker and therapeutic target for early diagnosis and metabolic intervention. However, further multi-center and population-based studies are needed to confirm these associations and validate the clinical utility of SIRT1 testing in diabetic patients.\u003c/p\u003e\n\u003cp\u003eThis study is aligned with UN Sustainable Development Goal No. 3 (Good Health and Well-being) Implementation of Govt. Of India.\u0026nbsp;\u003c/p\u003e"},{"header":"Statements \u0026 Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003eThe authors would like to thank the Department of Biochemistry and the Department of Medicine, School of Medical Sciences and Research, Sharda University, for providing the necessary laboratory facilities and infrastructure to carry out this research.\u003c/p\u003e\n\u003cp\u003eWe would like to thank all the participants of this study for their cooperation and willingness to contribute to this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: Nil\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interest:\u003c/strong\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e \u003cem\u003e“All authors contributed to the study. Material preparation, validation, formal analysis,data collection and investigation were performed by Era karn. Study conception,design,resources,supervision and original draft was written by Suman Bala Sharma.Project administration and editing after review was done by Manoj Kumar Nandkeoliar.Visualization and methodology were conducted by Preeti Yadav and Mohit Kumar. All authors read and approved the final manuscript.”\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The data generated and analyzed in this study can be obtained by contacting the corresponding author with a reasonable request. The data are not publicly available due to ethical concerns and maintaining confidentiality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval:\u003c/strong\u003eThe study was conducted in accordance with the Declaration and Approval by the Institutional Ethics Committee (Ref no. SU/SMS\u0026amp;R/76-A/2025/09. Issue date: 4/02/2025) of School of Medical Sciences \u0026amp; Research , Sharda University,Greater Noida,U.P, India.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u003c/strong\u003e Informed consent was obtained from all subjects involved in the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAmerican Diabetes Association. Classification and diagnosis of diabetes. Diabetes Care. 2023;46(Suppl 1):S19\u0026ndash;S40.\u003c/li\u003e\n \u003cli\u003eDeFronzo RA, Ferrannini E, et al. Type 2 diabetes mellitus. Nat Rev Dis Primers. 2015;1:15019.\u003c/li\u003e\n \u003cli\u003eInternational Diabetes Federation. IDF Diabetes Atlas. 10th ed. Brussels: IDF; 2021.\u003c/li\u003e\n \u003cli\u003eKahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444(7121):840\u0026ndash;6.\u003c/li\u003e\n \u003cli\u003eEvans JL, Goldfine ID, et al. Oxidative stress and stress-activated signaling pathways. Endocr Rev. 2002;23(5):599\u0026ndash;622.\u003c/li\u003e\n \u003cli\u003eLing C, R\u0026ouml;nn T. Epigenetics in human obesity and type 2 diabetes. Cell Metab. 2019;29(5):1028\u0026ndash;44.\u003c/li\u003e\n \u003cli\u003eHaigis MC, Sinclair DA,et al. Mammalian sirtuins: biological insights and disease relevance. Annu Rev Pathol. 2010;5:253\u0026ndash;95.\u003c/li\u003e\n \u003cli\u003eRodgers JT, Lerin C, \u0026nbsp;et al. Nutrient control of glucose homeostasis through a complex of PGC-1\u0026alpha; and SIRT1. Nature. 2005;434(7029):113\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eKauppinen A, Suuronen T, \u0026nbsp;et al. Antagonistic crosstalk between NF-\u0026kappa;B and SIRT1. Cell Signal. 2013;25(10):1939\u0026ndash;48.\u003c/li\u003e\n \u003cli\u003ePfluger PT, Herranz D, \u0026nbsp;et al. Sirt1 protects against high-fat diet-induced metabolic damage. Proc Natl Acad Sci USA. 2008;105(28):9793\u0026ndash;8.\u003c/li\u003e\n \u003cli\u003eZillikens MC, van Meurs JB, et al. SIRT1 genetic variation is related to BMI and risk of obesity. Diabetes. 2009;58(12):2828\u0026ndash;34.\u003c/li\u003e\n \u003cli\u003eGuarente L. Sirtuins as regulators of metabolism and healthspan. Nat Rev Mol Cell Biol. 2011;12(7):443\u0026ndash;454.\u003c/li\u003e\n \u003cli\u003eHaigis MC, Sinclair DA,et al. Mammalian sirtuins: biological insights and disease relevance. Annu Rev Pathol. 2010;5:253\u0026ndash;295.\u003c/li\u003e\n \u003cli\u003eDong Y, Guo T, et al. SIRT1 genetic polymorphisms are associated with type 2 diabetes in a Chinese population. Diabetes. 2011;60(3):961\u0026ndash;966.\u003c/li\u003e\n \u003cli\u003eShimoyama Y, Mitsuda Y,\u0026nbsp;et al. SIRT1 polymorphisms are associated with visceral fat accumulation and metabolic syndrome. Diabetes Res Clin Pract. 2012;96(1):e15\u0026ndash;e18.\u003c/li\u003e\n \u003cli\u003eKitada M, Koya D,\u0026nbsp;et al. SIRT1 in type 2 diabetes: mechanisms and therapeutic potential. Diabetes Metab J. 2013;37(5):315\u0026ndash;25.\u003c/li\u003e\n \u003cli\u003eImai S, Guarente L,\u0026nbsp;et al. NAD⁺ and sirtuins in aging and disease. Trends Cell Biol. 2014;24(8):464\u0026ndash;71.\u003c/li\u003e\n \u003cli\u003eRodgers JT, Puigserver P,\u0026nbsp;et al. Fasting-dependent glucose and lipid metabolic response through hepatic sirtuin 1. Proc Natl Acad Sci U S A. 2007;104(31):12861\u0026ndash;6.\u003c/li\u003e\n \u003cli\u003eYeung F, Hoberg JE, \u0026nbsp;et al. Modulation of NF-\u0026kappa;B-dependent transcription and cell survival by the SIRT1 deacetylase. EMBO J. 2004;23(12):2369\u0026ndash;80.\u003c/li\u003e\n \u003cli\u003ede Kreutzenberg SV, Ceolotto G, et al. Downregulation of the longevity-associated protein SIRT1 in insulin resistance and metabolic syndrome. Diabetes. 2010;59(4):1006\u0026ndash;15.\u003c/li\u003e\n \u003cli\u003eKiran S, Anwar T,\u0026nbsp;et al. SIRT1 gene expression in type 2 diabetes mellitus. J Diabetes Metab Disord. 2015;14:13.\u003c/li\u003e\n \u003cli\u003eCanto C, Auwerx J,et al. NAD⁺ as a signaling molecule modulating metabolism. Cold Spring Harb Symp Quant Biol. 2011;76:291\u0026ndash;8.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Type 2 Diabetes Mellitus, SIRT1, Gene Expression, Single Nucleotide Polymorphism, Insulin Resistance","lastPublishedDoi":"10.21203/rs.3.rs-9490914/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9490914/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eType 2 diabetes is a complex metabolic disorder, which is influenced by the interplay of genes and environment. From the perspective of energy balance and insulin signaling, some genes are coming forward as potential contributors to susceptibility to the disorder. Sirtuin 1 (SIRT1), a NAD⁺-dependent deacetylase, plays a critical role at the crossroads of glucose metabolism, insulin action, mitochondrial function, and inflammation. This study investigated whether a SIRT1 T/C polymorphism and the relative expression of SIRT1 are associated with susceptibility to T2DM in a North Indian population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a case-control study involving 45 patients with T2DM and 45 healthy controls, matched for age and sex. The SIRT1 T/C polymorphism was identified by PCR-RFLP. The relative expression of SIRT1 was measured by RT-qPCR. Genotype and allele frequencies were compared between cases and controls, and tested for Hardy-Weinberg equilibrium. Odds ratios with 95% confidence intervals were calculated to estimate disease risk. Relative expression was analyzed using the 2⁻ΔΔCt method.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThere were significant differences in genotype and allelic frequencies between cases and controls. Higher frequency of the C allele was observed in T2DM patients while T allele was more prevalent among healthy controls. Patients with TC or CC genotype had a significantly higher risk of T2DM than TT genotype. Expression analysis revealed a significantly lower mean ΔΔCt value in T2DM patients than controls (p\u0026thinsp;=\u0026thinsp;0.00213), indicating that SIRT1 expression was upregulated in T2DM patients.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe SIRT1 T/C polymorphism and high expression of SIRT1 are significantly associated with susceptibility to T2DM. SIRT1 is having potential as a molecular biomarker and therapeutic target for Type 2 Diabetes Mellitus.\u003c/p\u003e","manuscriptTitle":"Study on Expression of Gene Encoding Sirtuin-1 and Its Association with Single Nucleotide Polymorphism in Type 2 Diabetes Mellitus","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-23 09:35:09","doi":"10.21203/rs.3.rs-9490914/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4fe68530-f95b-4887-a635-5e00b4278410","owner":[],"postedDate":"April 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":66781226,"name":"Molecular Genetics"},{"id":66781227,"name":"Applied Biochemistry"}],"tags":[],"updatedAt":"2026-04-23T09:35:09+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-23 09:35:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9490914","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9490914","identity":"rs-9490914","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}