Three single nucleotide polymorphisms associated with type 2 diabetes mellitus in a Chinese population

Chen,Meijun; Zhang,Xuelong; Fang,Qingxiao; Wang,Tongtong; Li,Tingting; Qiao,Hong

doi:10.3892/etm.2016.3920

Three single nucleotide polymorphisms associated with type 2 diabetes mellitus in a Chinese population

Authors:
- Meijun Chen
- Xuelong Zhang
- Qingxiao Fang
- Tongtong Wang
- Tingting Li
- Hong Qiao
View Affiliations

Affiliations: Department of Endocrinology, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China, Laboratory of Medical Genetics, Harbin Medical University, Harbin, Heilongjiang 150001, P.R. China
Published online on: November 18, 2016 https://doi.org/10.3892/etm.2016.3920
Pages: 121-126
Copyright: © Chen et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

Metrics: Total Views: 0 (Spandidos Publications: | PMC Statistics: )

Metrics: Total PDF Downloads: 0 (Spandidos Publications: | PMC Statistics: )

Cited By (CrossRef): 0 citations Loading Articles...

Abstract

An Indian study recently observed three new loci: rs9552911 in the SGCG, rs1593304 near PLXNA4 and rs4858889 in SCAP associated with type 2 diabetes mellitus (T2DM) in a south Asian population. The present study aimed to validate these findings in a Chinese population. We genotyped the above three single-nucleotide polymorphisms (SNPs), rs9552911, rs1593304, and rs4858889, in a group of 1,972 Chinese individuals, comprising of 966 type 2 diabetic patients and 976 controls. Anthropometric variables and biochemical traits were measured in all the participants. The association analyses of genotype-disease and genotype‑traits were estimated. The genotype frequency of rs9552911 differed statistically between the cases and controls (P=0.017). The difference was also evident between the cases and controls in non-obese participants (P=0.033). In addition, the SNP rs9552911 was associated with weight (P=0.033), total cholesterol (P=0.006) and low-density lipoprotein-cholesterol (P=0.007). The SNP rs1593304 was associated with β-cell function estimated by the homeostatic model assessment of β-cell function (P=0.041). However, there was no significant association between rs4858889 and T2DM. In conclusion, the results show that the SNP rs9552911 was associated with T2DM, possibly by affecting body mass index and lipid metabolism. The SNP rs1593304 may impair β-cell function.

View Figures

View References

1	Yang W, Lu J, Weng J, Jia W, Ji L, Xiao J, Shan Z, Liu J, Tian H, Ji Q, et al: China National Diabetes and Metabolic Disorders Study Group: Prevalence of diabetes among men and women in China. N Engl J Med. 362:1090–1101. 2010. View Article : Google Scholar : PubMed/NCBI
2	Yoon KH, Lee JH, Kim JW, Cho JH, Choi YH, Ko SH, Zimmet P and Son HY: Epidemic obesity and type 2 diabetes in Asia. Lancet. 368:1681–1688. 2006. View Article : Google Scholar : PubMed/NCBI
3	Bailes BK: Diabetes mellitus and its chronic complications. AORN J. 76:266–286. 2002. View Article : Google Scholar : PubMed/NCBI
4	Choquet H, Cavalcanti-Proença C, Lecoeur C, Dina C, Cauchi S, Vaxillaire M, Hadjadj S, Horber F, Potoczna N, Charpentier G, et al: The T-381C SNP in BNP gene may be modestly associated with type 2 diabetes: an updated meta-analysis in 49 279 subjects. Hum Mol Genet. 18:2495–2501. 2009. View Article : Google Scholar : PubMed/NCBI
5	Frayling TM: Genome-wide association studies provide new insights into type 2 diabetes aetiology. Nat Rev Genet. 8:657–662. 2007. View Article : Google Scholar : PubMed/NCBI
6	Saxena R, Saleheen D, Been LF, Garavito ML, Braun T, Bjonnes A, Young R, Ho WK, Rasheed A, Frossard P, et al: DIAGRAM; MuTHER; AGEN: Genome-wide association study identifies a novel locus contributing to type 2 diabetes susceptibility in Sikhs of Punjabi origin from India. Diabetes. 62:1746–1755. 2013. View Article : Google Scholar : PubMed/NCBI
7	Alberti KG and Zimmet PZ: Definition, diagnosis and classification of diabetes mellitus and its complications. Part 1: diagnosis and classification of diabetes mellitus provisional report of a WHO consultation. Diabet Med. 15:539–553. 1998. View Article : Google Scholar : PubMed/NCBI
8	Matthews DR, Hosker JP, Rudenski AS, Naylor BA, Treacher DF and Turner RC: Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 28:412–419. 1985. View Article : Google Scholar : PubMed/NCBI
9	Borén J, Taskinen MR, Olofsson SO and Levin M: Ectopic lipid storage and insulin resistance: a harmful relationship. J Intern Med. 274:25–40. 2013. View Article : Google Scholar : PubMed/NCBI
10	Alberti KG, Zimmet P and Shaw J: Metabolic syndrome - a new world-wide definition. A Consensus Statement from the International Diabetes Federation. Diabet Med. 23:469–480. 2006. View Article : Google Scholar : PubMed/NCBI
11	Saltiel AR and Kahn CR: Insulin signalling and the regulation of glucose and lipid metabolism. Nature. 414:799–806. 2001. View Article : Google Scholar : PubMed/NCBI
12	Adiels M, Westerbacka J, Soro-Paavonen A, Häkkinen AM, Vehkavaara S, Caslake MJ, Packard C, Olofsson SO, Yki-Järvinen H, Taskinen MR, et al: Acute suppression of VLDL1 secretion rate by insulin is associated with hepatic fat content and insulin resistance. Diabetologia. 50:2356–2365. 2007. View Article : Google Scholar : PubMed/NCBI
13	Criqui MH, Heiss G, Cohn R, Cowan LD, Suchindran CM, Bangdiwala S, Kritchevsky S, Jacobs DR Jr, O'Grady HK and Davis CE: Plasma triglyceride level and mortality from coronary heart disease. N Engl J Med. 328:1220–1225. 1993. View Article : Google Scholar : PubMed/NCBI
14	Fessler MB, Rudel LL and Brown JM: Toll-like receptor signaling links dietary fatty acids to the metabolic syndrome. Curr Opin Lipidol. 20:379–385. 2009. View Article : Google Scholar : PubMed/NCBI
15	Salem I Hadj, Kamoun F, Louhichi N, Trigui M, Triki C and Fakhfakh F: Impact of single-nucleotide polymorphisms at the TP53-binding and responsive promoter region of BCL2 gene in modulating the phenotypic variability of LGMD2C patients. Mol Biol Rep. 39:7479–7486. 2012. View Article : Google Scholar : PubMed/NCBI
16	Groh S, Zong H, Goddeeris MM, Lebakken CS, Venzke D, Pessin JE and Campbell KP: Sarcoglycan complex: implications for metabolic defects in muscular dystrophies. J Biol Chem. 284:19178–19182. 2009. View Article : Google Scholar : PubMed/NCBI
17	Wallace TM, Levy JC and Matthews DR: Use and abuse of HOMA modeling. Diabetes Care. 27:1487–1495. 2004. View Article : Google Scholar : PubMed/NCBI
18	Kido Y: Progress in diabetes. Rinsho Byori. 61:941–947. 2013.(In Japanese). PubMed/NCBI
19	Qiao H, Zhang X, Zhao X, Zhao Y, Xu L, Sun H and Fu S: Genetic variants of TCF7L2 are associated with type 2 diabetes in a northeastern Chinese population. Gene. 495:115–119. 2012. View Article : Google Scholar : PubMed/NCBI
20	Diamond J: Medicine: diabetes in India. Nature. 469:478–479. 2011. View Article : Google Scholar : PubMed/NCBI