Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University, Nanning, 530021, Guangxi, People's Republic of China.
Department of Pathophysiology, School of Premedical Science, Guangxi Medical University, Nanning, 530021, Guangxi, People's Republic of China.
Sci Rep. 2018 Apr 18;8(1):6189. doi: 10.1038/s41598-018-24432-w.
Little is known about the association of the BCL3-PVRL2-TOMM40 SNPs and dyslipidemia. This study was to detect 12 BCL3-PVRL2-TOMM40 SNPs, gene-gene and gene-environment interactions on dyslipidemia in the Chinese Maonan population. Genotyping was performed in 1130 normal and 832 dyslipidemia participants. Generalized multifactor dimensionality reduction was used to screen the best interaction combination among SNPs and environmental exposures. Allele and genotype frequencies of the detected SNPs were different between the two groups (P < 0.05-0.001). Association of the 12 SNPs and serum lipid levels was observed (P < 0.004-0.001). Multiple-locus linkage disequilibrium was not statistically independent in the population (D' = 0.01-0.98). The dominant model of rs8100239 and rs157580 SNPs, several haplotypes and G × G interaction haplotypes contributed to a protection, whereas the dominant model of rs10402271, rs3810143, rs519113, rs6859 SNPs, another haplotypes and G × G interaction haplotypes revealed an increased morbidity function (P < 0.05-0.001). There were significant three-locus model involving SNP-SNP, SNP-environment, haplotype-haplotype interactions (P < 0.05-0.001). The subjects carrying several genotypes and haplotypes decreased dyslipidemia risk, whereas the subjects carrying other genotypes and haplotypes increased dyslipidemia risk. The BCL3-PVRL2-TOMM40 SNPs, gene-gene and gene-environment interactions on dyslipidemia were observed in the Chinese Maonan population.
关于 BCL3-PVRL2-TOMM40 SNPs 与血脂异常的关联知之甚少。本研究旨在检测中国毛南族人群中 12 个 BCL3-PVRL2-TOMM40 SNPs、基因-基因和基因-环境相互作用与血脂异常的关系。在 1130 名正常人和 832 名血脂异常患者中进行基因分型。广义多因子降维法用于筛选 SNP 和环境暴露之间的最佳相互作用组合。两组间检测到的 SNPs 的等位基因和基因型频率不同(P<0.05-0.001)。观察到 12 个 SNPs 与血清脂质水平的相关性(P<0.004-0.001)。该人群中多个位点的连锁不平衡在统计学上不独立(D'=0.01-0.98)。rs8100239 和 rs157580 多态性的显性模型、几种单倍型和 G×G 相互作用单倍型具有保护作用,而 rs10402271、rs3810143、rs519113、rs6859 多态性的显性模型、另一种单倍型和 G×G 相互作用单倍型显示出增加的发病功能(P<0.05-0.001)。存在显著的三核苷酸模型,涉及 SNP-SNP、SNP-环境、单倍型-单倍型相互作用(P<0.05-0.001)。携带几种基因型和单倍型的个体降低了血脂异常的风险,而携带其他基因型和单倍型的个体增加了血脂异常的风险。在中国毛南族人群中观察到 BCL3-PVRL2-TOMM40 SNPs、基因-基因和基因-环境相互作用与血脂异常有关。