Disease risk varies significantly between ethnic groups, however, the clinical significance and implications of these observations are poorly understood. Investigating ethnic differences within the human proteome may shed light on the impact of ancestry on disease risk. We used admixture mapping to explore the impact of genetic ancestry on 237 cardiometabolic biomarkers in 2,216 Latin Americans within the Outcomes Reduction with an Initial Glargine Intervention (ORIGIN) study. We developed a variance component model in order to determine the proportion of variance explained by inter-ancestry differences, and we applied it to the biomarker panel. Multivariable linear regression was used to identify and localize genetic loci affecting biomarker variability between ethnicities. Variance component analysis revealed that 5% of biomarkers were significantly impacted by genetic admixture (p < 0.05/237), including C-peptide, apolipoprotein-E, and intercellular adhesion molecule 1. We also identified 46 regional associations across 40 different biomarkers (p < 1.13 × 10-6). An independent analysis revealed that 34 of these 46 regions were associated at genome-wide significance (p < 5 × 10-8) with their respective biomarker in either Europeans or Latin populations. Additional analyses revealed that an admixture mapping signal associated with increased C-peptide levels was also associated with an increase in diabetes risk (odds ratio [OR] = 6.07 per SD, 95% confidence interval [CI] 1.44 to 25.56, p = 0.01) and surrogate measures of insulin resistance. Our results demonstrate the impact of ancestry on biomarker levels, suggesting that some of the observed differences in disease prevalence have a biological basis, and that reference intervals for those biomarkers should be tailored to ancestry. Specifically, our results point to a strong role of ancestry in insulin resistance and diabetes risk.

中文翻译：

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基因祖先对人血清蛋白质组的影响。

种族之间的疾病风险差异很大，但是，对这些观察结果的临床意义和含义了解甚少。研究人类蛋白质组中的种族差异可能会揭示祖先对疾病风险的影响。我们通过初步的甘精胰岛素干预（ORIGIN）研究，使用混合作图来探索遗传谱系对2 216名拉丁美洲人中237种心脏代谢生物标志物的影响。我们开发了方差成分模型，以确定由族际差异解释的方差比例，并将其应用于生物标记物面板。多变量线性回归用于鉴定和定位影响种族之间生物标记变异性的遗传基因座。方差成分分析显示，有5％的生物标志物受到遗传掺混物的显着影响（p <0.05 / 237），包括C肽，载脂蛋白E和细胞间粘附分子1。我们还鉴定了40个不同生物标志物之间的46个区域关联（p <1.13×10-6）。一项独立分析显示，这46个区域中的34个在欧洲人或拉丁人口中具有全基因组意义（p <5×10-8）与它们各自的生物标志物相关。其他分析表明，与C肽水平升高相关的混合映射信号也与糖尿病风险增加相关（比值比[OR] = 6.07 / SD，95％置信区间[CI] 1.44至25.56，p = 0.01）并替代胰岛素抵抗措施。我们的结果证明了祖先对生物标志物水平的影响，这表明观察到的某些疾病发生率差异具有生物学基础，并且应针对祖先量身定制这些生物标志物的参考间隔。具体而言，我们的结果表明血统在胰岛素抵抗和糖尿病风险中具有重要作用。