Abstract
Objective The aim of this study was to investigate the association between adiponectin gene polymorphisms rs10937273, rs1501299, rs182052, rs2241767, and rs266729 and environmental risk factors of type 2 diabetes mellitus (T2DM) in Hohhot. The study explored different models of gene-environment interactions, aimed at providing approaches for the prevention and control of T2DM in combination with the characteristics of the local population. Methods A case-control study was conducted including 406 Chinese participants, comprising 203 cases and 203 controls from various hospitals. Adiponectin (ADIPOQ) gene polymorphisms rs10937273, rs1501299, rs182052, rs2241767, and rs266729 were detected using an improved multiple ligation detection reaction technique. Generalized multifactor dimensionality reduction (GMDR) and logistic regression were conducted to analyze the associations between adiponectin gene polymorphisms and T2DM, as well as the interactions between adiponectin gene polymorphisms and environmental factors. Results ADIPOQ gene polymorphisms rs10937273, rs1501299, rs182052, rs2241767, and rs266729 were associated with type 2 diabetes. Based on the haplotype of the five adiponectin gene single-nucleotide polymorphism (SNP) loci, we found that G-G-A-A-C was a susceptible haplotype of T2DM (P < 0.05). Interaction analyses demonstrated associations between rs1501299 and central obesity (consistency = 80%, P = 0.011) and between rs266729 and rs182052 and central obesity (consistency = 70%, P = 0.011). Conclusions Our findings indicate that there is an interaction between the ADIPOQ gene and central obesity, which provides new insights into the prevention and treatment of T2DM.
Highlights
Type 2 diabetes mellitus (T2DM) is a growing global public health concern; according to the latest statistics of the International Diabetes Federation (IDF) from 2019, there are 463 million people aged 20–79 with confirmed or undiagnosed diabetes globally, with 116 million individuals in China
The generalized multifactor dimensionality reduction (GMDR) method was used to analyze the interaction between genotypes, and T2DM environmental risk factors and the environmental risk factors affecting disease occurrence were examined using Generalized multifactor dimensionality reduction (GMDR) software based on a Java platform
The body mass index (BMI) and WHR index were higher in the T2DM group than in the control group, there was a significant difference between the two groups; BMI has become the leading risk factor for diabetes in China
Summary
Type 2 diabetes mellitus (T2DM) is a growing global public health concern; according to the latest statistics of the International Diabetes Federation (IDF) from 2019, there are 463 million people aged 20–79 with confirmed or undiagnosed diabetes globally, with 116 million individuals in China. The prevalence of diabetes mellitus has been increasing worldwide in recent decades owing to urbanization, changes in nutrition intake, obesity, and low exercise. Diabetes mellitus has become a chronic noncommunicable disease that seriously endangers public health [1]. In 2013, the overall prevalence of diabetes in Chinese adults was 10.9% [2], while the prevalence of impaired glucose tolerance was 35.7%. From 2000 to 2016, the number of diabetes cases in China increased by 62.7% [3]. The diabetes epidemic in China is very severe and diabetes prevention and treatment face many challenges, including poor diagnosis, a lack of data regarding basic health parameters or risk factors, a high misdiagnosis rate, and increased prevalence among younger individuals
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