ERBB2和ERBB3多态性与中国人群血脂异常和血脂水平的关系

IF 1.6 4区 生物学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Lijun Zhu, Zhengmei Fang, Mengyun Huang, Lianping He, Miao Xu, Yue Yu, Yuelong Jin, Yan Chen, Yingshui Yao
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引用次数: 0

摘要

以血液中脂质水平异常为特征的血脂异常是心血管疾病的重要危险因素。在这项病例对照研究中,评估了中国安徽北部人群中ERBB2和ERBB3基因单核苷酸多态性与血脂异常风险之间的关系。特别是,我们使用TaqMan分析了543例血脂异常患者和648例健康对照者的5种潜在功能多态性。多因素logistic回归用于评估基因型和血脂异常之间的关系,调整混杂变量。ERBB2 rs2517955和rs1058808单核苷酸多态性与血脂异常显著相关。rs2517955变异在男性、55岁或以下的个体以及没有糖尿病的人群中显示出对血脂异常的保护作用。同样,rs1058808变异降低了这些分层组中血脂异常的风险。相反,ERBB3 rs2292238与糖尿病患者血脂异常风险增加相关。与相应的野生型等位基因相比,rs2517955和rs1058808的变异等位基因与高密度脂蛋白胆固醇水平降低的风险降低相关。此外,ERBB2 rs2517955变异与总胆固醇水平显著相关,而ERBB3 rs3741499和rs877636变异与低密度脂蛋白胆固醇水平显著相关。我们的研究结果表明,ERBB2和ERBB3多态性与中国人群血脂异常的风险密切相关。这些结果为进一步研究血脂异常和确定潜在的治疗靶点提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Association Between ERBB2 and ERBB3 Polymorphisms and Dyslipidaemia and Serum Lipid Levels in a Chinese Population.

Dyslipidaemia, characterised by abnormal lipid levels in the blood, is an important risk factor for cardiovascular disease. In this case-control study, the association between single-nucleotide polymorphisms in ERBB2 and ERBB3 genes and the risk of dyslipidaemia in a population from Northern Anhui, China was evaluated. Particularly, we analysed samples from 543 patients with dyslipidaemia and 648 healthy controls for five potentially functional polymorphisms using TaqMan assays. Multivariate logistic regression was used to assess the relationship between genotype and dyslipidaemia, adjusting for confounding variables. The ERBB2 rs2517955 and rs1058808 single-nucleotide polymorphisms were significantly associated with dyslipidaemia. The rs2517955 variant showed a protective effect against dyslipidaemia in males, individuals aged 55 years or younger, and those without diabetes. Similarly, the rs1058808 variant decreased the risk of dyslipidaemia in these stratified groups. Conversely, ERBB3 rs2292238 was associated with an increased risk of dyslipidaemia in patients with diabetes. Compared with the corresponding wild-type alleles, variant alleles of rs2517955 and rs1058808 were associated with a reduced risk of decreased high-density lipoprotein cholesterol levels. Additionally, ERBB2 rs2517955 variants were significantly linked to total cholesterol levels, whereas ERBB3 rs3741499 and rs877636 variants were significantly associated with low-density lipoprotein cholesterol levels. Our findings suggest that ERBB2 and ERBB3 polymorphisms are closely associated with the risk of dyslipidaemia in the Chinese population. These results provide valuable insights for further genetic studies of dyslipidaemia and the identification of potential therapeutic targets.

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来源期刊
Biochemical Genetics
Biochemical Genetics 生物-生化与分子生物学
CiteScore
3.90
自引率
0.00%
发文量
133
审稿时长
4.8 months
期刊介绍: Biochemical Genetics welcomes original manuscripts that address and test clear scientific hypotheses, are directed to a broad scientific audience, and clearly contribute to the advancement of the field through the use of sound sampling or experimental design, reliable analytical methodologies and robust statistical analyses. Although studies focusing on particular regions and target organisms are welcome, it is not the journal’s goal to publish essentially descriptive studies that provide results with narrow applicability, or are based on very small samples or pseudoreplication. Rather, Biochemical Genetics welcomes review articles that go beyond summarizing previous publications and create added value through the systematic analysis and critique of the current state of knowledge or by conducting meta-analyses. Methodological articles are also within the scope of Biological Genetics, particularly when new laboratory techniques or computational approaches are fully described and thoroughly compared with the existing benchmark methods. Biochemical Genetics welcomes articles on the following topics: Genomics; Proteomics; Population genetics; Phylogenetics; Metagenomics; Microbial genetics; Genetics and evolution of wild and cultivated plants; Animal genetics and evolution; Human genetics and evolution; Genetic disorders; Genetic markers of diseases; Gene technology and therapy; Experimental and analytical methods; Statistical and computational methods.
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