Haplotype-based interaction of the PPARGC1A and UCP1 genes is associated with impaired fasting glucose or type 2 diabetes mellitus

Abstract

The aim of this study is to evaluate the effect of single-nucleotide polymorphisms (SNPs) of the PPARGC1A and UCP1 genes on impaired fasting glucose (IFG) or type 2 diabetes mellitus (T2DM) and the haplotype-based interaction between these genes.A cross-sectional study was conducted by cluster sampling in Henan province, China. Based on the level of fasting plasma glucose (FPG) and the history of T2DM, the participants were divided into 2 groups; 83 individuals were in the IFG+DM group (those with IFG or T2DM) and 445 individuals were in the NFPG group (those with normal FPG). Kernel canonical correlation analysis (KCCA), a haplotype-based gene-gene interaction method, which can increase the biological interpretability and extract nonlinear characteristics of SNPs, was used to analyze the correlation and interaction between PPARGC1A and UCP1 genes.The age, BMI, total cholesterol and triglycerides were statistically different between 2 groups (P ≤ .001). Haplotype analysis showed no significant difference in frequency distribution between the 2 groups when the PPARGC1A or UCP1 gene was tested (P > .05). KCCA analysis showed that the maximum kernel canonical correlation coefficient of the PPARGC1A and UCP1 genes was 0.9977 and 0.9995 in the IFG+DM and NPFG groups, respectively. A haplotype-based gene–gene interaction was observed significantly (U = −6.28, P < .001), indicating the possibility of an interaction between haplotype AAG of the PPARGC1A gene and haplotypes CTCG (odds ratio [OR] = 1.745, 95% confidence interval [95% CI] 1.069–2.847) and CTCA (OR = 0.239, 95% CI 0.060–0.958) of the UCP1 gene.Haplotype-based interaction between the PPARGC1A and UCP1 genes is associated with IFG or T2DM among residents in Henan, China.

Exploring effective approaches for haplotype block phasing

“…Phasing, also known as haplotype estimation, reconstructs the haplotype sequences from genotype data and has been essential for understanding sequence-specific variation such as allele-specific expression [4, 5], methylation effects [6], and compound heterozygosity [2, 7]. Moreover, numerous studies have shown that haplotype-based association analysis can identify variants that would be missed by a standard single nucleotide polymorphism (SNP)-based analysis [8–10].…”

Prevalence of uncoupling protein one genetic polymorphisms and their relationship with cardiovascular and metabolic health

“…For instance, the frequency of AG genotype of A-3826G in persons with CMP ranges from 24% in Italy [ 25 ], to around 50% in Colombia [ 20 ], Japan [ 21 ], and Korea [ 17 ], and to 85% in China [ 19 ]. Similarly, wide frequency ranges have been reported also for the other three SNPs across different populations [ 10 , 20 , 26 , 27 ]. At the same time, some studies report that UCP1 SNPs are strongly associated with disease risk [ 7 , 19 , 28 ], while others report no such findings [ 29 – 31 ].…”

Prevalence of uncoupling protein one genetic polymorphisms and their relationship with cardiovascular and metabolic health

“…For instance, the frequency of AG of A-3826G in persons with CMP ranges from 24% in Italy (22), to around 50% in Colombia (10), Japan (19), and Korea (16), and to 85% in China (18). Similarly wide frequency ranges have been reported also for the other three SNPs across different populations (11,(23)(24)(25). At the same time, some studies report that UCP1 SNPs are strongly associated with disease risk (9,18,26), while others report no such findings (27)(28)(29).…”