Variant rs2237892 of KCNQ1 Is Potentially Associated with Hypertension and Macrovascular Complications in Type 2 Diabetes Mellitus in A Chinese Han Population

Shared Genetics between Age at Menarche and Type 2 Diabetes Mellitus: Genome-Wide Genetic Correlation Study

Background: Age at menarche (AAM) has been associated with type 2 diabetes mellitus (T2DM). However, little is known about their shared heritability. Methods: Our data comes from the Taiwan Biobank. Genome-wide association studies (GWASs) were conducted to identify single-nucleotide polymorphisms (SNPs) related to AAM-, T2DM-, and T2DM-related phenotypes, such as body fat percentage (BFP), fasting blood glucose (FBG), and hemoglobin A1C (HbA1C). Further, the conditional false discovery rate (cFDR) method was applied to examine the shared genetic signals. Results: Conditioning on AAM, Quantile-quantile plots showed an earlier departure from the diagonal line among SNPs associated with BFP and FBG, indicating pleiotropic enrichments among AAM and these traits. Further, the cFDR analysis found 39 independent pleiotropic loci that may underlie the AAM-T2DM association. Among them, FN3KRP rs1046896 (cFDR = 6.84 × 10-49), CDKAL1 rs2206734 (cFDR = 6.48 × 10-10), B3GNTL1 rs58431774 (cFDR = 2.95 × 10-10), G6PC2 rs1402837 (cFDR = 1.82 × 10-8), and KCNQ1 rs60808706 (cFDR = 9.49 × 10-8) were highlighted for their significant genetic enrichment. The protein-protein interaction analysis revealed a significantly enriched network among novel discovered genes that were mostly found to be involved in the insulin and glucagon signaling pathways. Conclusions: Our study highlights potential pleiotropic effects across AAM and T2DM. This may shed light on identifying the genetic causes of T2DM.

Saudi Community-Based Screening Study on Genetic Variants in β-Cell Dysfunction and Its Role in Women with Gestational Diabetes Mellitus

BACKGROUND

Diabetes (hyperglycemia) is defined as a multifactorial metabolic disorder in which insulin resistance and defects in pancreatic β-cell dysfunction are two major pathophysiologic abnormalities that underpin towards gestational diabetes mellitus (GDM). TCF7L2, KCNQ1, and KCNJ11 genes are connected to the mechanism of β-cell dysfunction. The purpose of this study was to investigate the genes associated with β-cell dysfunction and their genetic roles in the rs7903146, rs2237892, and rs5219 variants in Saudi women diagnosed with type 2 diabetes mellitus and GDM.

MATERIALS AND METHODS

In this case-control study, 100 women with GDM and 100 healthy volunteers (non-GDM) were recruited. Genotyping was performed using polymerase chain reaction (PCR), followed by restriction fragment length analysis. Validation was performed using Sanger sequencing. Statistical analyses were performed using multiple software packages.

RESULTS

Clinical studies showed a β-cell dysfunction positive association in women with GDM when compared to non-GDM women (p < 0.05). Both rs7903146 (CT vs. CC: OR-2.12 [95%CI: 1.13-3.96]; p = 0.01 & T vs. C: (OR-2.03 [95%CI: 1.32-3.11]; p = 0.001) and rs5219 SNPs (AG vs. AA: OR-3.37 [95%CI: 1.63-6.95]; p = 0.0006 & G vs. A: OR-3.03 [95%CI: 1.66-5.52]; p = 0.0001) showed a positive association with genotype and allele frequencies in women with GDM. ANOVA analysis confirmed that weight (p = 0.02), BMI (p = 0.01), and PPBG (p = 0.003) were associated with rs7903146 and BMI (p = 0.03) was associated with rs2237892 SNPs.

CONCLUSIONS

This study confirms that the SNPs rs7903146 (TCF7L2) and rs5219 (KCNJ11) are strongly associated with GDM in the Saudi population. Future studies should address the limitations of this study.

Associations between KCNQ1 and ITIH4 gene polymorphisms and infant weight gain in early life

BACKGROUND

An earlier meta-analysis of genome-wide association studies in Asian populations detected five novel body mass index-associated single-nucleotide polymorphisms (SNPs), including potassium voltage-gated channel subfamily Q member 1 (KCNQ1) (rs2237892), ALDH2/MYL2 (rs671, rs12229654), ITIH4 (rs2535633), and NT5C2 (rs11191580). Whether these SNPs take effect in early life, for example, affect infant rapid weight gain (RWG), is unclear.

METHODS

We obtained genomic DNA from 460 term infants with normal birth weight. RWG was defined as the change of weight-for-age standardized Z-score, calculated according to the Children Growth Standard released by the World Health Organization, from birth to 3 months of age >0.67. Using genetic models, associations between the candidate SNPs and infant RWG were examined, along with the interaction between the SNPs and the potential risk factors.

RESULTS

RWG was presented in 225 of 460 infants. SNP rs2535633 and rs2237892 were associated with the risk of RWG. Both additive and multiplicative interaction effects were found between infant delivery mode and rs2237892. The negative association between the rs2237892 T allele and infant RWG was only observed in vaginally delivered infants.

CONCLUSIONS

Obesity-related loci rs2535633 and rs2237892 are associated with infant RWG in the first 3 months of infancy. The relationship between rs2237892 and infant RGW might be moderated by cesarean delivery.

IMPACT

Genetic predisposition is an essential aspect to understand infant weight gain. Obesity-related SNPs, rs2535633 and rs2237892, are associated with RWG in very early years of life. The negative association between rs2237892 T allele and RWG is only observed in infants delivered vaginally instead of cesarean section.

Integrated analysis of probability of type 2 diabetes mellitus with polymorphisms and methylation of KCNQ1 gene: A nested case-control study

BACKGROUND

To estimate the associations between single-nucleotide polymorphisms (SNPs) and methylation of KCNQ1 gene and type 2 diabetes mellitus (T2DM) risk and the interactions among SNPs, methylation, and environmental factors on T2DM risk.

METHODS

We genotyped five SNPs and tested methylation at 39 CpG loci of KCNQ1 in 290 T2DM cases and 290 matched controls nested in the Rural Chinese Cohort Study. Conditional logistic regression model was used to estimate the associations between SNPs and KCNQ1 methylation and T2DM risk. Multifactor dimensionality reduction (MDR) analysis was used to estimate the effect of the interactions SNPs-SNPs, SNPs-methylation, methylation-methylation and SNPs, and methylation-environment on T2DM risk.

RESULTS

Probability of T2DM was decreased with rs2283228 of KCNQ1 (CA vs AA, odds ratio [OR] = 0.65, 95% confidence interval [CI] 0.42-0.99). T2DM probability was significantly increased with rs2237895 combined with hypertriglyceridemia (OR_eg  = 2.76, 95% CI 1.35-5.62), with hypertension (OR_eg  = 2.23, 95% CI 1.25-3.98), and with body mass index (BMI; OR_eg  = 1.93, 95% CI 1.12-3.34). T2DM probability was associated with methylation of CG11 and CG41 (OR = 1.89, 95% CI 1.23-2.89, P = .003). It was significantly associated with the interaction between BMI, hypertriglyceridemia, and CG5 methylation (P = .028 and .028), and the combined effects of CG11 with hypertriglyceridemia and hypertension. On MDR analysis, no significant interaction was observed.

CONCLUSION

T2DM probability was reduced 35% with rs2283228 polymorphism. It was associated with rs2237895 combined with hypertension, with BMI and with hypertriglyceridemia. The methylation at two CpG loci of KCNQ1 significantly increased T2DM risk by 89%.

TCF7L2 rs7903146 Is Associated With Increased Risk of New-Onset Diabetes After Transplant: A Meta-analysis of Literature

BACKGROUND

Single nucleotide polymorphisms may influence the risk of development of new-onset diabetes after transplant (NODAT), a post-transplant clinical complication that is often implicated in allograft rejection and mortality. We performed a meta-analysis of association between transcription factor 7-like-2 (TCF7L2) rs7903146 and risk of NODAT.

METHODS

A systematic search was conducted using PubMed and ScienceDirect electronic databases for studies published between January 2001 and January 2021. Case-control or cohort studies reporting association between NODAT (diagnosis based on American Diabetes Association criteria) and TCF7L2 rs7903146 were included. MetaGenyo was used for meta-analysis (random-effects model). Pooled odds ratios with 95% confidence intervals were reported to evaluate the strength of association.

RESULTS

Two reviewers independently screened for articles. A total of 6 case-control studies were included for full-text review and quantitative analysis after screening for eligibility. Genotypic distributions were in Hardy-Weinberg equilibrium for included studies. All articles reported statistically significant association of TCF7L2 rs7903146 for risk of NODAT except for 1 study. There was moderate heterogeneity among studies (I² = 60.6%). Pooled analysis revealed 51% odds of developing NODAT with TCF7L2 rs7903146 T allele (allele contrast model: odds ratio, 1.51; 95% confidence interval, 1.13-2.02; P = .005).

CONCLUSIONS

The present meta-analysis demonstrated association between TCF7L2 variant rs7903146 and risk of developing NODAT. This finding suggest clinical implications for individuals undergoing kidney transplant.

Multiple Single Nucleotide Polymorphism Testing Improves the Prediction of Diabetic Retinopathy Risk with Type 2 Diabetes Mellitus

Diabetic retinopathy (DR) is one of the most frequent causes of irreversible blindness, thus prevention and early detection of DR is crucial. The purpose of this study is to identify genetic determinants of DR in individuals with type 2 diabetic mellitus (T2DM). A total of 551 T2DM patients (254 with DR, 297 without DR) were included in this cross-sectional research. Thirteen T2DM-related single nucleotide polymorphisms (SNPs) were utilized for constructing genetic risk prediction model. With logistic regression analysis, genetic variations of the FTO (rs8050136) and PSMD6 (rs831571) polymorphisms were independently associated with a higher risk of DR. The area under the curve (AUC) calculated on known nongenetic risk variables was 0.704. Based on the five SNPs with the highest odds ratio (OR), the combined nongenetic and genetic prediction model improved the AUC to 0.722. The discriminative accuracy of our 5-SNP combined risk prediction model increased in patients who had more severe microalbuminuria (AUC = 0.731) or poor glycemic control (AUC = 0.746). In conclusion, we found a novel association for increased risk of DR at two T2DM-associated genetic loci, FTO (rs8050136) and PSMD6 (rs831571). Our predictive risk model presents new insights in DR development, which may assist in enabling timely intervention in reducing blindness in diabetic patients.

Effect of KCNQ1 rs2237892 polymorphism on the predisposition to type 2 diabetes mellitus: An updated meta-analysis

OBJECTIVES

Previous studies have analyzed the potential effect of KCNQ1 rs2237892 polymorphism on the predisposition to type 2 diabetes mellitus, but the findings are inconclusive and the subject of debate. The purpose of our study was to provide further insight into the potential association between KCNQ1 rs2237892 polymorphism and the risk of type 2 diabetes mellitus.

METHODS

In total, 50 articles (60 studies) with 77,276 cases and 76,054 controls were utilized in our analysis. The pooled odds ratio (OR), 95% confidence interval (95% CI), and p value were used to evaluate the significance of our findings. Funnel plots and Beggar's regression tests were utilized to determine the presence of publication bias.

RESULTS

Our meta-analysis results indicated that KCNQ1 rs2237892 polymorphism could be correlated with the risk of type 2 diabetes mellitus under the C allelic, recessive, and dominant genetic models (OR = 1.25, 95% 1.19-1.32, p < 0.001; OR = 1.50, 95% CI 1.34-1.68, p < 0.001; OR = 1.26, 95% CI 1.14-1.40, p < 0.001, respectively). Additionally, ethnicity analysis revealed that the source of control, case size, and Hardy-Weinberg Equilibrium status were correlated to the polymorphism in the three genetic models.

CONCLUSIONS

Our meta-analysis demonstrated significant evidence to support the association between KCNQ1 rs2237892 polymorphism and predisposition to type 2 diabetes mellitus.

Association of Combined TCF7L2 and KCNQ1 Gene Polymorphisms with Diabetic Micro- and Macrovascular Complications in Type 2 Diabetes Mellitus

BACKGROUND

Vascular complications are the major morbid consequences of type 2 diabetes mellitus (T2DM). The transcription factor 7-like 2 (TCF7L2), potassium voltage-gated channel subfamily Q member 1 (KCNQ1), and inwardly-rectifying potassium channel, subfamily J, member 11 gene (KCNJ11) are common T2DM susceptibility genes in various populations. However, the associations between polymorphisms in these genes and diabetic complications are controversial. This study aimed to investigate the effects of combined gene-polymorphisms within TCF7L2, KCNQ1, and KCNJ11 on vascular complications in Thai subjects with T2DM.

METHODS

We conducted a case-control study comprising 960 T2DM patients and 740 non-diabetes controls. Single nucleotide polymorphisms in TCF7L2, KCNQ1, and KCNJ11 were genotyped and evaluated for their association with diabetic vascular complications.

RESULTS

The gene variants TCF7L2 rs290487-T, KCNQ1 rs2237892-C, and KCNQ1 rs2237897-C were associated with increased risk of T2DM. TCF7L2 rs7903146-C, TCF7L2 rs290487-C, KCNQ1 rs2237892-T, and KCNQ1 rs2237897-T revealed an association with hypertension. The specific combination of risk-alleles that have effects on T2DM and hypertension, TCF7L2 rs7903146-C, KCNQ1 rs2237892-C, and KCNQ1 rs2237897-T, as genetic risk score (GRS), pronounced significant association with coronary artery disease (CAD), cumulative nephropathy and CAD, and cumulative microvascular and macrovascular complications (respective odds ratios [ORs] with 95% confidence interval [95% CI], comparing between GRS 2-3 and GRS 5-6, were 7.31 [2.03 to 26.35], 3.92 [1.75 to 8.76], and 2.33 [1.13 to 4.79]).

CONCLUSION

This study demonstrated, for the first time, the effect conferred by specific combined genetic variants in TCF7L2 and KCNQ1 on diabetic vascular complications, predominantly with nephropathy and CAD. Such a specific pattern of gene variant combination may implicate in the progression of T2DM and life-threatening vascular complications.

Advances in Current Diabetes Proteomics: From the Perspectives of Label- free Quantification and Biomarker Selection

BACKGROUND

Due to its prevalence and negative impacts on both the economy and society, the diabetes mellitus (DM) has emerged as a worldwide concern. In light of this, the label-free quantification (LFQ) proteomics and diabetic marker selection methods have been applied to elucidate the underlying mechanisms associated with insulin resistance, explore novel protein biomarkers, and discover innovative therapeutic protein targets.

OBJECTIVE

The purpose of this manuscript is to review and analyze the recent computational advances and development of label-free quantification and diabetic marker selection in diabetes proteomics.

METHODS

Web of Science database, PubMed database and Google Scholar were utilized for searching label-free quantification, computational advances, feature selection and diabetes proteomics.

RESULTS

In this study, we systematically review the computational advances of label-free quantification and diabetic marker selection methods which were applied to get the understanding of DM pathological mechanisms. Firstly, different popular quantification measurements and proteomic quantification software tools which have been applied to the diabetes studies are comprehensively discussed. Secondly, a number of popular manipulation methods including transformation, pretreatment (centering, scaling, and normalization), missing value imputation methods and a variety of popular feature selection techniques applied to diabetes proteomic data are overviewed with objective evaluation on their advantages and disadvantages. Finally, the guidelines for the efficient use of the computationbased LFQ technology and feature selection methods in diabetes proteomics are proposed.

CONCLUSION

In summary, this review provides guidelines for researchers who will engage in proteomics biomarker discovery and by properly applying these proteomic computational advances, more reliable therapeutic targets will be found in the field of diabetes mellitus.

Association of KCNQ1rs2237892C⟶T Gene with Type 2 Diabetes Mellitus: A Meta-Analysis

BACKGROUND

Type 2 diabetes mellitus (T2DM) is one of the most common chronic diseases in adults, causing high morbidity and mortality worldwide. In recent years, the prevalence of T2DM has been increasing significantly, and genome-wide association studies (GWAS) have shown that KCNQ1 significantly increases the risk of T2DM.

OBJECTIVE

To find large-scale evidence on whether the KCNQ1rs2237892C⟶T gene polymorphism is associated with T2DM susceptibility.

METHODS

A comprehensive review of the Chinese and English literature on the association of T2DM with KCNQ1rs2237892 is published by PubMed and Baidu Academic. The included literature was part or all of the studied loci which were evaluated for association with T2DM. Forest plots were made of the included literature to analyze the association of KCNQ1 with polymorphisms of the studied loci, and funnel plots and Egger's test were used to evaluate the publication bias of the selected included literature.

RESULTS

Ten case-control studies including a total of 7027 cases and 8208 controls met our inclusion criteria. Allele (C allele frequency distribution) (OR: 1.19; 95% CI: 0.87,1.62; P < 0.00001), recessive (OR: 0.73; 95% CI: 0.45,1.18; P < 0.00001) genetic model under the full population was observed between KCNQ1rs2237892C⟶T gene polymorphism and T2DM without a significant relationship. In a stratified analysis by race, a meaningful association was found in non-Asian populations under the allelic genetic model, but no association was found in Asian populations.

CONCLUSION

This meta-analysis showed no significant association between the rs2237892 polymorphism of the KCNQ1 gene and the risk of T2DM.

KCNQ1 common genetic variant and type 2 diabetes mellitus risk

Background

Type 2 diabetes mellitus (T2DM) is a multifactorial trait that both environmental and genetic factors contribute to its pathogenesis. The most common single nucleotide polymorphism (SNP) of the potassium voltage-gated channel subfamily Q member 1 (KCNQ1) gene, rs2237892, is highly associated with the risk of T2DM. The aim of the present study was to examine any association between KCNQ1 gene rs2237892 variant and risk of T2DM in a group of Iranian patients.

Methods

Genotyping was carried out in 100 type 2 diabetic patients and 100 non-diabetic subjects using the Sanger sequencing method.

Results

The CC genotype caused more than 30% reduction in the risk of T2DM in compared with CT. Nonetheless, this association was not statistically significant and this variant had no protective effect for T2DM. A significant difference was not found in genotypes (CC, CT, and TT) and alleles (C and T) frequency of KCNQ1 rs2237892 SNP between T2DM and control groups (P = 0.475 and P = 0.470, respectively).

Conclusions

Our investigations did not show enough evidence for the presence of an association between KCNQ1 gene rs2237892 polymorphism and risk of T2DM among a group of Iranian patients.

Computational determination of human PPARG gene: SNPs and prediction of their effect on protein functions of diabetic patients

Background

The Peroxisome proliferator-activated receptor gamma gene (PPARG), encodes a member of the peroxisome-activated receptor subfamily of nuclear receptors. PPARs form heterodimers with retinoid X receptors (RXRs) which regulate transcription of various genes. Three subtypes of PPARs are known: PPAR-alpha, PPAR-delta and PPAR-gamma. The protein encoded by this gene is PPAR-gamma which is a regulator of adipocyte differentiation. PPARG-gamma has been implicated in the pathology of numerous diseases including obesity, diabetes, atherosclerosis and cancer.

Aim

This study aimed to perform insilico analysis to predict the effects that can be imposed by SNPs reported in PPARG gene.

Methodology

This gene was investigated in NCBI database (http://www.ncbi.nlm.nih.gov/) during the year 2016 and the SNPs in coding region (exonal SNPs) that are non-synonymous (ns SNPs) were analyzed by computational softwares. SIFT, Polyphen, I-Mutant and PHD-SNP softwares). SIFT was used to filter the deleterious SNPs, Polyphen was used to determine the degree of pathogenicity, I-Mutant was used to determine the effect of mutation on protein stability while PHD-SNP software was used to investigate the effect of mutation on protein function. Furthermore, Structural and functional analysis of ns SNPs was also studied using Project HOPE software and modeling was conducted by Chimera.

Results

A total of 34,035 SNPs from NCBI, were found, 21,235 of them were found in Homo sapiens, 134 in coding non synonymous (missense) and 89 were synonymous. Only SNPs present in coding regions were selected for analysis. Out of 12 deleterious SNPs sorted by SIFT, 10 were predicted by Polyphen to be probably damaging with PISC score = 1 and only two were benign. All these 10 double positive SNPs were disease related as predicted by PHD-SNPs and revealed decreased stability indicated by I-Mutant.

Conclusion

Based on the findings of this study, it can be concluded that the deleterious ns SNPs (rs72551364 and rs121909244SNPs) of PPARG are important candidates for the cause of different types of human diseases including diabetes mellitus.

Associations of KCNQ1 Polymorphisms with the Risk of Type 2 Diabetes Mellitus: An Updated Meta-Analysis with Trial Sequential Analysis

BACKGROUND

Previous studies have examined the role of the KQT-like subfamily Q member1 (KCNQ1) gene polymorphisms on the risk of type 2 diabetes mellitus (T2DM), but the findings are inconclusive.

OBJECTIVE

To examine the association between the KCNQ1 gene polymorphisms and the risk of T2DM using an updated meta-analysis with an almost tripled number of studies.

METHODS

Five electronic databases, such as PubMed and Embase, were searched thoroughly for relevant studies on the associations between seven most studied KCNQ1 gene polymorphisms, including rs2237892, rs2237897, rs2237895, rs2283228, rs231362, rs151290, and rs2074196, and T2DM risk up to September 14, 2019. The summary odds ratios (ORs) with their 95% confidence intervals (CIs) were applied to assess the strength of associations in the random-effects models. We used the trial sequential analysis (TSA) to measure the robustness of the evidence.

RESULTS

49 publications including 55 case-control studies (68,378 cases and 66,673 controls) were finally enrolled. In overall analyses, generally, increased T2DM risk was detected for rs2237892, rs2237895, rs2283228, rs151290, and rs2074196, but not for rs231362 under all genetic models. The ORs and 95% CIs for allelic comparison were 1.23 (1.14-1.33) for rs2237892, 1.21 (1.16-1.27) for rs2237895, 1.27 (1.11-1.46) for rs2237897, 1.25 (1.09-1.42) for rs2283228, 1.14 (1.03-1.27) for rs151290, 1.31 (1.23-1.39) for rs2074196, and 1.16 (0.83, 1.61) for rs231362. Stratified analyses showed that associations for rs2237892, rs2237895, rs2283228, and rs151290 were more evident among Asians than Caucasians. TSA demonstrated that the evidence was sufficient for all polymorphisms in this study. The genotypes of the three SNPs (rs2237892, rs2283228, and rs231362) were significantly correlated with altered KCNQ1 gene expression.

CONCLUSION

This meta-analysis suggested that KCNQ1 gene polymorphisms (rs2237892, rs2283228, rs2237895, rs151290, and rs2074196) might be the susceptible factors for T2DM, especially among Asian population.

A Systematically Assembled Signature of Genes to be Deep-Sequenced for Their Associations with the Blood Pressure Response to Exercise

: Background: Exercise is one of the best nonpharmacologic therapies to treat hypertension. The blood pressure (BP) response to exercise is heritable. Yet, the genetic basis for the antihypertensive effects of exercise remains elusive. Methods: To assemble a prioritized gene signature, we performed a systematic review with a series of Boolean searches in PubMed (including Medline) from earliest coverage. The inclusion criteria were human genes in major BP regulatory pathways reported to be associated with: (1) the BP response to exercise; (2) hypertension in genome-wide association studies (GWAS); (3) the BP response to pharmacotherapy; (4a) physical activity and/or obesity in GWAS; and (4b) BP, physical activity, and/or obesity in non-GWAS. Included GWAS reports disclosed the statistically significant thresholds used for multiple testing. Results: The search yielded 1422 reports. Of these, 57 trials qualified from which we extracted 11 genes under criteria 1, 18 genes under criteria 2, 28 genes under criteria 3, 27 genes under criteria 4a, and 29 genes under criteria 4b. We also included 41 genes identified from our previous work. Conclusions: Deep-sequencing the exons of this systematically assembled signature of genes represents a cost and time efficient approach to investigate the genomic basis for the antihypertensive effects of exercise.

The Kv7 Channel and Cardiovascular Risk Factors

Potassium channels play a pivotal role in the regulation of excitability in cells such as neurons, cardiac myocytes, and vascular smooth muscle cells. The KCNQ (Kv7) family of voltage-activated K⁺ channels hyperpolarizes the cell and stabilizes the membrane potential. Here, we outline how Kv7 channel activity may contribute to the development of the cardiovascular risk factors such as hypertension, diabetes, and obesity. Questions and hypotheses regarding previous and future research have been raised. Alterations in the Kv7 channel may contribute to the development of cardiovascular disease (CVD). Pharmacological modification of Kv7 channels may represent a possible treatment for CVD in the future.

A variation in KCNQ1 gene is associated with repaglinide efficacy on insulin resistance in Chinese Type 2 Diabetes Mellitus Patients

Repaglinide is an insulin secretagogue that often exhibits considerable interindividual variability in therapeutic efficacy. The current study was designed to investigate the impact of KCNQ1 genetic polymorphism on the efficacy of repaglinide and furthermore to identify the potential mechanism of action in patients with type 2 diabetes. A total of 305 patients and 200 healthy subjects were genotyped for the KCNQ1 rs2237892 polymorphism, and 82 patients with T2DM were randomized for the oral administration of repaglinide for 8 weeks. HepG2 cells were incubated with repaglinide in the absence or presence of a KCNQ1 inhibitor or the pcDNA3.1-hKCNQ1 plasmid, after which the levels of Akt, IRS-2 and PI(3)K were determined. Our data showed that repaglinide significantly decreased HOMA-IR in patients with T2DM. Furthermore, the level of HOMA-IR was significantly reduced in those patients with CT or TT genotypes than CC homozygotes. The KCNQ1 inhibitor enhanced repaglinide efficacy on insulin resistance, with IRS-2/PI(3)K/Akt signaling being up-regulated markedly. As in our clinical experiment, these data strongly suggest that KCNQ1 genetic polymorphism influences repaglinide response due to the pivotal role of KCNQ1 in regulating insulin resistance through the IRS-2/PI(3)K/Akt signaling pathway. This study was registered in the Chinese Clinical Trial Register on May 14, 2013. (No. ChiCTR-CCC13003536).