肾脏疾病
全基因组关联研究
代谢物
肾功能
内科学
生物
人口
疾病
代谢组学
医学
单核苷酸多态性
遗传关联
遗传学
生物信息学
基因型
基因
环境卫生
作者
Shengyuan Luo,Elena V. Feofanova,Adrienne Tin,Sarah Tung,Eugene P. Rhee,Josef Coresh,Dan E. Arking,Aditya Surapaneni,Pascal Schlosser,Yong Li,Anna Köttgen,Bing Yu,Morgan E. Grams
标识
DOI:10.1016/j.kint.2021.03.026
摘要
The genome-wide association study (GWAS) is a powerful means to study genetic determinants of disease traits and generate insights into disease pathophysiology. To date, few GWAS of circulating metabolite levels have been performed in African Americans with chronic kidney disease. Hypothesizing that novel genetic-metabolite associations may be identified in a unique population of African Americans with a lower glomerular filtration rate (GFR), we conducted a GWAS of 652 serum metabolites in 619 participants (mean measured glomerular filtration rate 45 mL/min/1.73m2) in the African American Study of Kidney Disease and Hypertension, a clinical trial of blood pressure lowering and antihypertensive medication in African Americans with chronic kidney disease. We identified 42 significant variant metabolite associations. Twenty associations had been previously identified in published GWAS, and eleven novel associations were replicated in a separate cohort of 818 African Americans with genetic and metabolomic data from the Atherosclerosis Risk in Communities Study. The replicated novel variant-metabolite associations comprised eight metabolites and eleven distinct genomic loci. Nine of the replicated associations represented clear enzyme-metabolite interactions, with high expression in the kidneys as well as the liver. Three loci (ACY1, ACY3, and NAT8) were associated with a common pool of metabolites, acetylated amino acids, but with different individual affinities. Thus, extensive metabolite profiling in an African American population with chronic kidney disease aided identification of novel genome-wide metabolite associations, providing clues about substrate specificity and the key roles of enzymes in modulating systemic levels of metabolites.
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