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
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,Tao Gu,Xiaotian Zhang,Xing Huang
出处
期刊:Diabetes
[American Diabetes Association]
日期:2024-01-11
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 (pQTL) studies: 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 (3345 cases and 2372 controls) and the FinnGen study (3676 cases and 283,456 controls). Mendelian randomization (MR) analysis was conducted to examine the potential targets for DKD. The colocalization analysis was utilized to detect whether the potential proteins exist 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 (PPI) networks were employed 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 four of these proteins, and TGFBI was affirmed through two separate group datasets. These results indicate that targeting these four proteins could be a promising approach for treating DKD, and warrant further clinical investigations
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