Nephrology Division and Endocrine Unit, Massachusetts General Hospital, Boston, Massachussetts, USA.
Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, Maryland, USA.
Kidney Int. 2022 Apr;101(4):814-823. doi: 10.1016/j.kint.2022.01.014. Epub 2022 Feb 1.
Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations was unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.
代谢组学全基因组关联研究 (GWAS) 有助于阐明人类代谢的遗传贡献。然而，迄今为止的研究主要集中在相对健康的、基于人群的白种人样本上。在这里，我们对慢性肾功能不全队列 (CRIC) 研究中的 537 种血液代谢物进行了 GWAS，分别在 822 名白人和 687 名黑人研究参与者中进行了分析。然后应用跨种族荟萃分析来改善潜在因果变异的精细映射。白人和黑人参与者的平均估计肾小球滤过率分别为 44.4 和 41.5 mL/min/1.73m。在 19 个基因座上发现了 45 个显著的代谢物关联，包括在 PYROXD2、PHYHD1、FADS1-3、ACOT2、MYRF、FAAH 和 LIPC 上的新关联。在进一步调整估计肾小球滤过率和蛋白尿的模型中，关联的强度保持不变，这与基因产物对相关代谢物的直接生化效应一致。在几个基因座上，跨种族荟萃分析利用了不同人群之间连锁不平衡的差异，与仅在白人群体中进行精细映射相比，减少了潜在因果单核苷酸多态性的数量和/或基因组间隔。在所有验证的关联中，我们发现白人和黑人研究参与者之间潜在因果单核苷酸多态性的效应大小具有很强的一致性。因此，我们的研究确定了慢性肾脏病血液代谢物的新遗传决定因素，证明了不同队列在代谢组学 GWAS 中提高因果推断的价值，并强调了不同种族之间代谢的共同遗传基础。
