PDF(Pubmed)
Abstract：
OBJECTIVE: Metformin is widely used to treat type 2 diabetes mellitus (T2DM) individuals. Clinically, inter-individual variability of metformin response is of significant concern and is under interrogation. In this study, a targeted exome and whole transcriptome analysis were performed to identify predictive biomarkers of metformin response in drug-naïve T2DM individuals.
METHODS: The study followed a prospective study design. Drug-naïve T2DM individuals (n = 192) and controls (n = 223) were enrolled. T2DM individuals were administered with metformin monotherapy and defined as responders and non-responders based on their glycated haemoglobin change over three months. 146 T2DM individuals were used for the final analysis and remaining samples were lost during the follow-up. Target exome sequencing and RNA-seq was performed to analyze genetic and transcriptome profile. The selected SNPs were validated by genotyping and allele specific gene expression using the TaqMan assay. The gene prioritization, enrichment analysis, drug-gene interactions, disease-gene association, and correlation analysis were performed using various tools and databases.
RESULTS: rs1050152 and rs272893 in SLC22A4 were associated with improved response to metformin. The copy number loss was observed in PPARGC1A in the non-responders. The expression analysis highlighted potential differentially expressed targets for predicting metformin response (n = 35) and T2DM (n = 14). The expression of GDF15, TWISTNB, and RPL36A genes showed a maximum correlation with the change in HbA1c levels. The disease-gene association analysis highlighted MAGI2 rs113805659 to be linked with T2DM.
CONCLUSIONS: The results provide evidence for the genetic variations, perturbed transcriptome, allele-specific gene expression, and pathways associated with metformin drug response in T2DM.
METHODS: The study followed a prospective study design. Drug-naïve T2DM individuals (n = 192) and controls (n = 223) were enrolled. T2DM individuals were administered with metformin monotherapy and defined as responders and non-responders based on their glycated haemoglobin change over three months. 146 T2DM individuals were used for the final analysis and remaining samples were lost during the follow-up. Target exome sequencing and RNA-seq was performed to analyze genetic and transcriptome profile. The selected SNPs were validated by genotyping and allele specific gene expression using the TaqMan assay. The gene prioritization, enrichment analysis, drug-gene interactions, disease-gene association, and correlation analysis were performed using various tools and databases.
RESULTS: rs1050152 and rs272893 in SLC22A4 were associated with improved response to metformin. The copy number loss was observed in PPARGC1A in the non-responders. The expression analysis highlighted potential differentially expressed targets for predicting metformin response (n = 35) and T2DM (n = 14). The expression of GDF15, TWISTNB, and RPL36A genes showed a maximum correlation with the change in HbA1c levels. The disease-gene association analysis highlighted MAGI2 rs113805659 to be linked with T2DM.
CONCLUSIONS: The results provide evidence for the genetic variations, perturbed transcriptome, allele-specific gene expression, and pathways associated with metformin drug response in T2DM.
摘要：
目的：二甲双胍广泛用于治疗2型糖尿病（T2DM）个体。临床上,二甲双胍反应的个体间差异是非常值得关注的,目前正在接受调查.在这项研究中,我们进行了靶向外显子组和全转录组分析,以确定药物初发T2DM个体中二甲双胍反应的预测性生物标志物.
方法：本研究遵循前瞻性研究设计。纳入药物初始T2DM个体(n=192)和对照(n=223)。对T2DM个体施用二甲双胍单一疗法,并基于其在三个月内的糖化血红蛋白变化将其定义为应答者和非应答者。146个T2DM个体用于最终分析,并且剩余的样品在随访期间丢失。进行靶外显子组测序和RNA-seq以分析遗传和转录组谱。使用TaqMan测定通过基因分型和等位基因特异性基因表达来验证所选择的SNP。基因优先排序，富集分析,药物-基因相互作用，疾病-基因关联，使用各种工具和数据库进行相关性分析.
结果：SLC22A4中的rs1050152和rs272893与二甲双胍反应改善相关。在非应答者的PPARGC1A中观察到拷贝数损失。表达分析强调了预测二甲双胍反应(n=35)和T2DM(n=14)的潜在差异表达靶标。GDF15、TWISTNB、和RPL36A基因显示与HbA1c水平变化的最大相关性。疾病基因关联分析强调MAGI2rs113805659与T2DM相关。
结论：结果为遗传变异提供了证据，扰动的转录组，等位基因特异性基因表达，2型糖尿病中与二甲双胍药物反应相关的通路。
方法：本研究遵循前瞻性研究设计。纳入药物初始T2DM个体(n=192)和对照(n=223)。对T2DM个体施用二甲双胍单一疗法,并基于其在三个月内的糖化血红蛋白变化将其定义为应答者和非应答者。146个T2DM个体用于最终分析,并且剩余的样品在随访期间丢失。进行靶外显子组测序和RNA-seq以分析遗传和转录组谱。使用TaqMan测定通过基因分型和等位基因特异性基因表达来验证所选择的SNP。基因优先排序，富集分析,药物-基因相互作用，疾病-基因关联，使用各种工具和数据库进行相关性分析.
结果：SLC22A4中的rs1050152和rs272893与二甲双胍反应改善相关。在非应答者的PPARGC1A中观察到拷贝数损失。表达分析强调了预测二甲双胍反应(n=35)和T2DM(n=14)的潜在差异表达靶标。GDF15、TWISTNB、和RPL36A基因显示与HbA1c水平变化的最大相关性。疾病基因关联分析强调MAGI2rs113805659与T2DM相关。
结论：结果为遗传变异提供了证据，扰动的转录组，等位基因特异性基因表达，2型糖尿病中与二甲双胍药物反应相关的通路。
