| Literature DB >> 34387340 |
Yanfa Sun1,2,3,4, Dan Zhou5, Md Rezanur Rahman6, Jingjing Zhu2, Dalia Ghoneim2, Nancy J Cox5, Thomas G Beach7, Chong Wu8, Eric R Gamazon5,9,10, Lang Wu2.
Abstract
Alzheimer's disease (ad) adversely affects the health, quality of life and independence of patients. There is a critical need to identify novel blood gene biomarkers for ad risk assessment. We performed a transcriptome-wide association study to identify biomarker candidates for ad risk. We leveraged two sets of gene expression prediction models of blood developed using different reference panels and modeling strategies. By applying the prediction models to a meta-GWAS including 71 880 (proxy) cases and 383 378 (proxy) controls, we identified significant associations of genetically determined expression of 108 genes in blood with ad risk. Of these, 15 genes were differentially expressed between ad patients and controls with concordant directions in measured expression data. With evidence from the analyses based on both genetic instruments and directly measured expression levels, this study identifies 15 genes with strong support as biomarkers in blood for ad risk, which may enhance ad risk assessment and mechanism-focused studies.Entities:
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Year: 2021 PMID： 34387340 PMCID： PMC8831284 DOI： 10.1093/hmg/ddab229
Source DB: PubMed Journal: Hum Mol Genet ISSN： 0964-6906 Impact factor: 5.121