Identification of blood eQTLs for AD risk loci: Genetics/genetic factors of Alzheimer's disease. (7th December 2020)

• Record Type: Journal Article
• Authors: Bradley, Joseph; Deming, Yuetiva; Li, Zeran; Harari, Oscar; Saef, Benjamin; Budde, John P.; Wang, Fengxian; Farias, Fabiana H.G.; Davenport, Richard; Cruchaga, Carlos
• Is Part Of: Alzheimer's & dementia. Volume 16(2020)Supplement 3
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-12-07
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.043801
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Alzheimer's disease (AD) is the sixth leading cause of death in the US and most common form of dementia, affecting an estimated 5 million individuals. Currently there are no publicly available treatments for clinical or pre‐clinical symptoms of AD as well as there is high number of genetic variants involved in the onset and progression of the disease. The Alzheimer's disease Neuroimaging Initiative (ADNI) aims to determine imaging, clinical and genetic biomarkers for early detection and treatment of AD. The goal of this study was to identify blood eQTLs for the genes located under the GWAS loci for AD risk. Method: The expression data, collected and RMA normalized by ADNI, was captured by the Affymetrix Human Genome U219 Microarray. The data were normalized, trimmed to 500 genes within known AD risk gene regions, and used with GWAS data in multivariate linear regression of European individuals. These analyses can help to identify the functional variant and gene driving the original association. Result: Our analysis found genome‐wide eQTLs for over 200 genes (∼600 including all isoforms) across the genome. Conclusion: These results suggests that these variants may play a role in the onset and progression of AD; however, further analysis associating these variants with case/control status, age at onset, and differential expression would be necessary to further verify this. We may also speculate from these data that AD risk loci where we could not find eQTLs play a much stronger functional role in AD onset.