Rathod Lokendra, Khan Sameera, Mishra Sweta, Das Deepanker, Bora Kaustubh, Shubham Swasti, Singh Samradhi, Kumar Manoj, Tiwari Rajnarayan R, Tiwari Archana, Mishra Pradyumna Kumar, Sarma Devojit Kumar
ICMR - National Institute for Research in Environmental Health, Bhopal, Madhya Pradesh, India.
School of Bimolecular Engineering & Biotechnology, Rajiv Gandhi Proudyogiki Vishwavidyalaya, Madhya Pradesh, India.
Lancet Reg Health Southeast Asia. 2024 Dec 10;32:100518. doi: 10.1016/j.lansea.2024.100518. eCollection 2025 Jan.
India, with the largest population and second-highest type 2 diabetes mellitus (T2DM) prevalence, presents a unique genetic landscape. This study explores the genetic profiling of T2DM, aiming to bridge gaps in existing research and provide insights for further explorations.
We conducted a systematic review and meta-analysis of literature published up to September 2024 using databases like PubMed, Web of Science, Scopus, and Google Scholar to identify SNPs associated with T2DM in case-control studies within the Indian population. Data extraction followed a rigorously designed checklist independently verified by two reviewers. The quality of the studies assessed by utilizing Newcastle Ottawa scale, and heterogeneity through Cochran's Q, τ, H and statistics. Fixed effect and random effect model was employed for meta-analysis based on heterogeneity, and publication bias was assessed by funnel plot analysis, Egger's and Begg's statistical test. In SNPs with adequate studies meta-regression was used to assess source of heterogeneity. Statistical analyses were performed using Stata 18.0 software.
Our search identified 1309 articles, with 67 included in the systematic review and 35 in the meta-analysis. These 67 case-control studies, involving 33,407 cases and 30,762 controls, analyzed 167 SNPs across 61 genes. Of these, 89 SNPs mapped to 46 genes showed significant associations with T2DM risk ( < 0.05), including 67 linked to increased risk and 16 with protective effects. Geographical analysis highlighted inter- and intra-regional variations. Meta-analysis of 25 SNPs revealed 12 SNPs with high T2DM risk compatibility. gene exhibited a strong compatibility with an overall OR of 1.44 (95% CI 1.36-1.52) and 112.41, while variants rs7903146 and rs12255372, with OR 1.56 (95% CI 1.43-1.66) and 89.036, OR of 1.36 (95% CI 1.17-1.35) with an - of 15.45 respectively.
Our study highlights the importance of considering the diverse ethnic groups of India for development of targeted and effective T2DM management strategies.
Department of Biotechnology (DBT) and Indian Council of Medical Research (ICMR), Government of India.
印度拥有世界上最多的人口和第二高的2型糖尿病（T2DM）患病率，展现出独特的基因图谱。本研究探索T2DM的基因特征，旨在填补现有研究的空白，并为进一步探索提供见解。
我们使用PubMed、Web of Science、Scopus和谷歌学术等数据库，对截至2024年9月发表的文献进行了系统综述和荟萃分析，以确定印度人群病例对照研究中与T2DM相关的单核苷酸多态性（SNP）。数据提取遵循一份经过严格设计的清单，由两名评审员独立核实。利用纽卡斯尔渥太华量表评估研究质量，并通过Cochran's Q、τ、H和I²统计量评估异质性。基于异质性采用固定效应和随机效应模型进行荟萃分析，并通过漏斗图分析、Egger检验和Begg检验评估发表偏倚。对于有足够研究的SNP，采用荟萃回归评估异质性来源。使用Stata 18.0软件进行统计分析。
我们的检索共识别出1309篇文章，其中67篇纳入系统综述，35篇纳入荟萃分析。这67项病例对照研究涉及33407例病例和30762例对照，分析了61个基因中的167个SNP。其中，89个映射到46个基因的SNP与T2DM风险存在显著关联（P<0.05），包括67个与风险增加相关的SNP和16个具有保护作用的SNP。地理分析突出了区域间和区域内的差异。对25个SNP的荟萃分析显示，有12个SNP具有较高的T2DM风险兼容性。基因显示出很强的兼容性，总体比值比（OR）为1.44（95%置信区间[CI] 1.36 - 1.52），I²为112.41，而rs7903146和rs12255372变异体的OR分别为1.56（95% CI 1.43 - 1.66），I²为89.036，OR为1.36（95% CI 1.17 - 1.35），I²为15.45。
我们的研究强调了在制定针对性强且有效的T2DM管理策略时，考虑印度不同种族群体的重要性。
印度政府生物技术部（DBT）和印度医学研究理事会（ICMR）。
