Integrating human brain proteomes and genome‐wide association results implicates new genes in Alzheimer's disease: Functionalizing genetic variants in Alzheimer's disease. (7th December 2020)

• Record Type: Journal Article
• Authors: Wingo, Aliza P.; Liu, Yue; Gockley, Jake; Logsdon, Benjamin A.; Duong, Duc; Dammer, Eric B.; Robins, Chloe; Cutler, David J.; De Jager, Philip L.; Lah, James J.; Bennett, David A.; Levey, Allan I.; Seyfried, Nicholas T.; Wingo, Thomas S.
• 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.043865
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Alzheimer's disease (AD) is the most common type of dementia, and it has a substantial genetic basis. Recent AD genome‐wide association studies (GWAS) continue to expand the number of loci that are significantly associated with AD; however, how those loci confer risk for AD remains unclear. Here, we addressed this problem by integrating 376 deep human brain proteomes and 888 human brain transcriptomes with recent AD GWAS results to identify genes, transcripts, and proteins that likely contribute to AD pathogenesis. Methods: We inferred the genetically controlled portion of protein abundance using 376 deep human brain proteomes, and these results were integrated with two recent large AD GWAS results that included 455, 258 participants (Jansen et al 2019), and 82, 771 participants (Kunkle et al 2019), respectively, using the FUSION pipeline (Gusev et al 2016). We performed an analogous analysis using 888 human brain transcriptomes to infer the genetically controlled portion of the transcript abundance and integrated those results with the aforementioned AD GWAS results. Results: We identified a total of 15 genes whose genetically regulated brain protein abundances were associated with AD. They are ACE, CARHSP1, CTSH, DOC2A, EPHX2, ICA1L, LACTB, MADD, PITPNC1, PLEKHA1, PVR, RTFDC1, SNX32, STX4, and STX6. At the transcript level, we identified a total of 49 genes whose cis ‐regulated mRNA expression levels were associated with AD. Of the 15 genes identified at the protein level, 33% (5 of 15) were also identified at the transcript level. Furthermore, 73% of these 15 genes identified at the protein level were highly expressed in excitatory neurons based on a reference single‐cell RNA‐sequencing dataset from human brain. In an independent replication dataset using single‐shot label‐free proteomes (n = 205), only one of the 15 proteins were measured and imputed (EPHX2). We replicated EPHX2's association with AD in that dataset. Conclusion: Together, our findings implicate 15 human brain proteins in the pathogenesis of AD and suggest that these proteins are controlled by both transcriptional and post‐transcriptional mechanisms. Our results lay a foundation for future mechanistic studies to develop novel treatments and biomarkers for AD.