Identification of highly reliable risk genes for Alzheimer's disease through joint-tissue integrative analysis

作者全名："Wang, Yong Heng; Luo, Pan Pan; Geng, Ao Yi; Li, Xinwei; Liu, Tai-Hang; He, Yi Jie; Huang, Lin; Tang, Ya Qin"

作者地址："[Wang, Yong Heng; Luo, Pan Pan; Geng, Ao Yi; Liu, Tai-Hang; He, Yi Jie; Huang, Lin; Tang, Ya Qin] Chongqing Med Univ, Sch Basic Med Sci, Dept Bioinformat, Chongqing, Peoples R China; [Wang, Yong Heng; Liu, Tai-Hang] Chongqing Med Univ, Joint Int Res Lab Reprod & Dev, Chongqing, Peoples R China; [Li, Xinwei] Chongqing Univ, Sch Microelect & Commun Engn, Chongqing, Peoples R China"

通信作者："Tang, YQ (通讯作者)，Chongqing Med Univ, Sch Basic Med Sci, Dept Bioinformat, Chongqing, Peoples R China."

来源：FRONTIERS IN AGING NEUROSCIENCE

ESI学科分类：NEUROSCIENCE & BEHAVIOR

WOS号：WOS:001022922900001

JCR分区：Q2

影响因子：4.1

年份：2023

卷号：15

期号：　

开始页：　

结束页：　

文献类型：Article

关键词：GWAS; TWAS; Mendelian Randomization; eQTL; Alzheimer's disease

摘要："Numerous genetic variants associated with Alzheimer's disease (AD) have been identified through genome-wide association studies (GWAS), but their interpretation is hindered by the strong linkage disequilibrium (LD) among the variants, making it difficult to identify the causal variants directly. To address this issue, the transcriptome-wide association study (TWAS) was employed to infer the association between gene expression and a trait at the genetic level using expression quantitative trait locus (eQTL) cohorts. In this study, we applied the TWAS theory and utilized the improved Joint-Tissue Imputation (JTI) approach and Mendelian Randomization (MR) framework (MR-JTI) to identify potential AD-associated genes. By integrating LD score, GTEx eQTL data, and GWAS summary statistic data from a large cohort using MR-JTI, a total of 415 AD-associated genes were identified. Then, 2873 differentially expressed genes from 11 AD-related datasets were used for the Fisher test of these AD-associated genes. We finally obtained 36 highly reliable AD-associated genes, including APOC1, CR1, ERBB2, and RIN3. Moreover, the GO and KEGG enrichment analysis revealed that these genes are primarily involved in antigen processing and presentation, amyloid-beta formation, tau protein binding, and response to oxidative stress. The identification of these potential AD-associated genes not only provides insights into the pathogenesis of AD but also offers biomarkers for early diagnosis of the disease."

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