ArticleInternational journal of environmental research and public health2020
A Replication Study Identified Seven SNPs Associated with Quantitative Traits of Type 2 Diabetes among Chinese Population in A Cross-Sectional Study.
Article in International journal of environmental research and public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 5 citations in OpenAlex.
- Identification of SEC16B as a novel regulator of glucose homeostasis.Diabetologia · 2025Article
- Identification of Regulatory Factors and Prognostic Markers in Amyotrophic Lateral Sclerosis.Antioxidants (Basel, Switzerland) · 2022Article
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8 authors at 1 institution in 1 country.
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Abstract
Genome-wide association studies (GWAS) have identified common variants for quantitative traits (insulin resistance and impaired insulin release) of type 2 diabetes (T2D) across different ethnics including China, but results were inconsistent. The study included 1654 subjects who were selected from the 2010-2012 China National Nutrition and Health Surveillance (CNNHS). Insulin resistance and impaired insulin release were assessed by homeostasis model assessment (HOMA). The study included 64 diabetes-related single nucleotide polymorphisms (SNPs), which were done using Mass ARRAY. A logistic regression model was employed to explore the associations of SNPs with insulin resistance and impaired insulin release by correcting for the confounders. The 5q11.2-rs4432842, RASGRP1-rs7403531, and SEC16B-rs574367 increased the risk of insulin resistance with OR = 1.23 (95% CI: 1.04-1.45, OR = 1.35 (95% CI: 1.13-1.62), OR = 1.34 (95% CI: 1.07-1.67), respectively, while MAEA-rs6815464 decreased the risk of insulin resistance (OR = 0.84, 95% CI: 0.71-1.00). CENTD2-rs1552224, TSPAN8-rs7961581 and ANK1-rs516946 was associated with increased risk of impaired insulin release with OR = 1.47 (95% CI: 1.09-1.99), OR = 1.25 (95% CI: 1.03-1.51), OR = 1.39 (95% CI: 1.07-1.81), respectively. Our findings would provide insight into the pathogenesis of individual SNPs and T2D.
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