R Zhang1, F Jiang, C Hu, W Yu, J Wang, C Wang, X Ma, S Tang, Y Bao, K Xiang, W Jia. 1. Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
Abstract
AIMS: Metabolic disorders are independent risk factors for the development of Type 2 diabetes. The aim of the study is to test the association of LPIN1 variants with Type 2 diabetes and clinical characteristics in large samples of the Chinese population. METHODS: In the first stage, 15 single nucleotide polymorphisms within the LPIN1 region were selected and genotyped in 3700 Chinese Han participants. In the second stage, the single nucleotide polymorphisms showing significant association or trends towards association were genotyped in an additional 3122 samples for replication. Meta-analyses and genotype-phenotype association studies were performed after combining the data from the two stages. RESULTS: In the first stage, we detected that rs16857876 was significantly associated with Type 2 diabetes with an odds ratio of 0.806 (95% CI 0.677-0.958, P = 0.015), while rs11695610 showed a trend with Type 2 diabetes (odds ratio 0.846, 95% CI 0.709-1.009, P = 0.062). In the second stage, a similar effect of rs11695610 on Type 2 diabetes was observed (odds ratio 0.849, 95% CI 0.700-1.030, P = 0.096). The meta-analyses combining the information from the two stages showed a significant effect of rs11695610 on Type 2 diabetes with an odds ratio of 0.847 (95% CI 0.744-0.965, P = 0.012). Finally, the phenotype-genotype association analyses showed that rs11695610 was associated with 2-h plasma glucose (P = 0.040) and triglyceride levels (P = 0.034). CONCLUSIONS: Our data implied that common single nucleotide polymorphisms within the LPIN1 region were associated with Type 2 diabetes and metabolic traits in the Chinese population.
AIMS: Metabolic disorders are independent risk factors for the development of Type 2 diabetes. The aim of the study is to test the association of LPIN1 variants with Type 2 diabetes and clinical characteristics in large samples of the Chinese population. METHODS: In the first stage, 15 single nucleotide polymorphisms within the LPIN1 region were selected and genotyped in 3700 Chinese Han participants. In the second stage, the single nucleotide polymorphisms showing significant association or trends towards association were genotyped in an additional 3122 samples for replication. Meta-analyses and genotype-phenotype association studies were performed after combining the data from the two stages. RESULTS: In the first stage, we detected that rs16857876 was significantly associated with Type 2 diabetes with an odds ratio of 0.806 (95% CI 0.677-0.958, P = 0.015), while rs11695610 showed a trend with Type 2 diabetes (odds ratio 0.846, 95% CI 0.709-1.009, P = 0.062). In the second stage, a similar effect of rs11695610 on Type 2 diabetes was observed (odds ratio 0.849, 95% CI 0.700-1.030, P = 0.096). The meta-analyses combining the information from the two stages showed a significant effect of rs11695610 on Type 2 diabetes with an odds ratio of 0.847 (95% CI 0.744-0.965, P = 0.012). Finally, the phenotype-genotype association analyses showed that rs11695610 was associated with 2-h plasma glucose (P = 0.040) and triglyceride levels (P = 0.034). CONCLUSIONS: Our data implied that common single nucleotide polymorphisms within the LPIN1 region were associated with Type 2 diabetes and metabolic traits in the Chinese population.
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