孟德尔随机化
疾病
蛋白质组
计算生物学
共域化
生物信息学
医学
全基因组关联研究
可药性
生物
数量性状位点
遗传学
内科学
单核苷酸多态性
遗传变异
基因
基因型
神经科学
作者
Wei Zhang,Leilei Ma,Qianyi Zhou,Tianjiao Gu,Xiaotian Zhang,Haitao Xing
出处
期刊:Diabetes
[American Diabetes Association]
日期:2024-01-11
卷期号:73 (4): 618-627
被引量:28
摘要
At present, safe and effective treatment drugs are urgently needed for diabetic kidney disease (DKD). Circulating protein biomarkers with causal genetic evidence represent promising drug targets, which provides an opportunity to identify new therapeutic targets. Summary data from two protein quantitative trait loci studies are presented, one involving 4,907 plasma proteins data from 35,559 individuals and the other encompassing 4,657 plasma proteins among 7,213 European Americans. Summary statistics for DKD were obtained from a large genome-wide association study (3,345 cases and 2,372 controls) and the FinnGen study (3,676 cases and 283,456 controls). Mendelian randomization (MR) analysis was conducted to examine the potential targets for DKD. The colocalization analysis was used to detect whether the potential proteins exist in the shared causal variants. To enhance the credibility of the results, external validation was conducted. Additionally, enrichment analysis, assessment of protein druggability, and the protein-protein interaction networks were used to further enrich the research findings. The proteome-wide MR analyses identified 21 blood proteins that may causally be associated with DKD. Colocalization analysis further supported a causal relationship between 12 proteins and DKD, with external validation confirming 4 of these proteins, and TGFBI was affirmed through two separate group data sets. These results indicate that targeting these four proteins could be a promising approach for treating DKD, and warrant further clinical investigations. Article Highlights
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