Genetically regulated expression in late-onset Alzheimer's disease implicates risk genes within known and novel loci.

TitleGenetically regulated expression in late-onset Alzheimer's disease implicates risk genes within known and novel loci.
Publication TypeJournal Article
Year of Publication2021
AuthorsChen H-H, Petty LE, Sha J, Zhao Y, Kuzma A, Valladares O, Bush W, Naj AC, Gamazon ER, Below JE
Corporate AuthorsAlzheimer’s Disease Genetics Consortium, International Genomics of Alzheimer’s Project
JournalTransl Psychiatry
Volume11
Issue1
Pagination618
Date Published12/2021
ISSN2158-3188
KeywordsAlzheimer Disease, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Multifactorial Inheritance, Polymorphism, Single Nucleotide
Abstract

Late-onset Alzheimer disease (LOAD) is highly polygenic, with a heritability estimated between 40 and 80%, yet risk variants identified in genome-wide studies explain only ~8% of phenotypic variance. Due to its increased power and interpretability, genetically regulated expression (GReX) analysis is an emerging approach to investigate the genetic mechanisms of complex diseases. Here, we conducted GReX analysis within and across 51 tissues on 39 LOAD GWAS data sets comprising 58,713 cases and controls from the Alzheimer's Disease Genetics Consortium (ADGC) and the International Genomics of Alzheimer's Project (IGAP). Meta-analysis across studies identified 216 unique significant genes, including 72 with no previously reported LOAD GWAS associations. Cross-brain-tissue and cross-GTEx models revealed eight additional genes significantly associated with LOAD. Conditional analysis of previously reported loci using established LOAD-risk variants identified eight genes reaching genome-wide significance independent of known signals. Moreover, the proportion of SNP-based heritability is highly enriched in genes identified by GReX analysis. In summary, GReX-based meta-analysis in LOAD identifies 216 genes (including 72 novel genes), illuminating the role of gene regulatory models in LOAD.

DOI10.1038/s41398-021-01677-0
Alternate JournalTransl Psychiatry
PubMed ID34873149
PubMed Central IDPMC8648734
Grant ListR01 GM140287 / GM / NIGMS NIH HHS / United States
R01 HG011138 / HG / NHGRI NIH HHS / United States
U01 AG032984 / AG / NIA NIH HHS / United States
RF1 AG061351 / AG / NIA NIH HHS / United States
R56 AG068026 / AG / NIA NIH HHS / United States
R35 HG010718 / HG / NHGRI NIH HHS / United States