Depression contributes to Alzheimer's disease through shared genetic risk. (1st February 2022)

• Record Type: Journal Article
• Authors: Harerimana, Nadia V.; Liu, Yue; Gerasimov, Ekaterina S; Duong, Duc M; Beach, Thomas G; Reiman, Eric M.; Schneider, Julie A.; Boyle, Patricia A; De Jager, Philip L; Bennett, David A.; Lah, James J; Levey, Allan I; Seyfried, Nicholas T; Wingo, Thomas S.; Wingo, Aliza P.
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 3
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-02-01
• 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.053251
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Depression increases the risk for Alzheimer's disease (AD) in many prospective studies and recent evidence has shown a genetic correlation between these two disorders. Yet, the biological mechanisms underlying this association are unclear. To elucidate molecular mechanisms underlying the association between depression and elevated AD risk. Method: This study used results of the largest published genome‐wide association study (GWAS) of depression (N=807, 553) and AD (N=455, 248), respectively, and human brain transcriptomes (N=580) and proteomes (N=469) profiled from postmortem brains from participants of three prospective cohorts of aging and dementia. First, linkage disequilibrium score regression was performed to assess for genetic correlation between depression and AD. Next, Mendelian randomization was used to test for causality. Subsequently, to resolve the genetic signals to specific genes, quantitative trait locus (QTL) analysis was performed on the significant depression GWAS signals using brain transcriptomic and proteomic profiles. Finally, brain transcripts and proteins identified by the QTL analysis were tested for association with AD endophenotypes and diagnosis.Participants underwent annual clinical examinations, cognitive testing, and post‐mortem brain pathological evaluation and RNA‐sequencing and proteomic analyses using tandem mass tag mass spectrometry. Approximately 15, 800 mRNAs and 8, 400 high abundance proteins were included in the analyses after quality control. AD endophenotypes, including longitudinal change of cognitive performance, beta‐amyloid, neurofibrillary tangles, and AD clinical diagnosis were assessed. Results: This study confirmed the genetic correlation between depression and AD. Mendelian randomization suggested a significant causal role for depression on AD but no evidence for causal role of AD on depression was found. The QTL analysis found that the depression GWAS variants regulated 62 brain transcripts and 45 brain proteins. Among those, 34 transcripts and 8 proteins were associated with rate of cognitive decline over time, AD pathologies, and AD diagnosis in two separate datasets implicating them in the development of AD. Conclusions: Depression appears to have a causal role in AD. The causal relationship between depression and AD is likely driven, at least in part, by the 42 brain transcripts and proteins identified in this study.