蛋白质组
生物
转录组
孟德尔随机化
全基因组关联研究
基因
疾病
计算生物学
遗传学
遗传关联
蛋白质组学
破译
医学
阿尔茨海默病
生物信息学
基因表达
单核苷酸多态性
遗传变异
基因型
病理
作者
Ya‐Nan Ou,Yuxiang Yang,Yue‐Ting Deng,Can Zhang,Hao Hu,Bang‐Sheng Wu,Yi Liu,Yan‐Jiang Wang,Ying Zhu,John Suckling,Lan Tan,Jin‐Tai Yu
标识
DOI:10.1038/s41380-021-01251-6
摘要
Genome-wide association studies (GWASs) have discovered numerous risk genes for Alzheimer's disease (AD), but how these genes confer AD risk is challenging to decipher. To efficiently transform genetic associations into drug targets for AD, we employed an integrative analytical pipeline using proteomes in the brain and blood by systematically applying proteome-wide association study (PWAS), Mendelian randomization (MR) and Bayesian colocalization. Collectively, we identified the brain protein abundance of 7 genes (ACE, ICA1L, TOM1L2, SNX32, EPHX2, CTSH, and RTFDC1) are causal in AD (P < 0.05/proteins identified for PWAS and MR; PPH4 >80% for Bayesian colocalization). The proteins encoded by these genes were mainly expressed on the surface of glutamatergic neurons and astrocytes. Of them, ACE with its protein abundance was also identified in significant association with AD on the blood-based studies and showed significance at the transcriptomic level. SNX32 was also found to be associated with AD at the blood transcriptomic level. Collectively, our current study results on genetic, proteomic, and transcriptomic approaches has identified compelling genes, which may provide important leads to design future functional studies and potential drug targets for AD.
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