Multi-tissue neocortical transcriptome-wide association study implicates 8 genes across 6 genomic loci in Alzheimer’s disease

• Type of Material: Article
• Authors: Jake Gockley, Sage Bionetworks; Kelsey S. Montgomery, Sage Bionetworks; William L. Poehlman, Sage Bionetworks; Jesse C. Wiley, Sage Bionetworks; Yue Liu, Emory University; Ekaterina Gerasimov, Emory University; Anna K. Greenwood, Sage Bionetworks; Solveig K. Sieberts, Sage Bionetworks; Aliza Wingo, Emory University; Thomas Wingo, Emory University; Lara M. Mangravite, Sage Bionetworks; Benjamin A. Logsdon, Cajal Neuroscience
• Language: English
• Date: 2021-05-04
• Publisher: BMC
• Publication Version: Final Published Version
• Copyright Statement: © The Author(s) 2021
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1186/s13073-021-00890-2
• Title of Journal or Parent Work: Genome Medicine
• Volume: 13
• Grant/Funding Information: Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, provided all ROSMAP data collected, which was funded by NIA grants P30AG10161, R01AG15819, R01AG17917, R01AG30146, R01AG36836, U01AG32984, U01AG46152, the Illinois Department of Public Health, and the Translational Genomics Research Institute. Mayo Study data were provided by the following sources: The Mayo Clinic Alzheimer’s Disease Genetic Studies, led by Dr. Nilufer Ertekin Taner and Dr. Steven G. Younkin, Mayo Clinic, Jacksonville, FL, using samples from the Mayo Clinic Study of Aging, the Mayo Clinic Alzheimer’s Disease Research Center, and the Mayo Clinic Brain Bank. Mayo Data collection was funded through NIA grants P50 AG016574, R01 AG032990, U01 58AG046139, R01 AG018023, U01 AG006576, U01 AG006786, R01 AG025711, R01 AG017216, R01AG003949, NINDS grant R01 NS080820, CurePSP Foundation, and support from Mayo Foundation.; This research was supported by the National Institute on Aging under the AMP-AD Data Coordination Center. Grant number: 5U24AG061340.
• Keywords: Dementia; TWAS; AMP-AD; FUSION; GWAS; Alzheimer’s disease; Neurodegeneration
• Research Categories: Biology, Neuroscience; Biology, Genetics; Psychology, Cognitive

Abstract

Background Alzheimer’s disease (AD) is an incurable neurodegenerative disease currently affecting 1.75% of the US population, with projected growth to 3.46% by 2050. Identifying common genetic variants driving differences in transcript expression that confer AD risk is necessary to elucidate AD mechanism and develop therapeutic interventions. We modify the FUSION transcriptome-wide association study (TWAS) pipeline to ingest gene expression values from multiple neocortical regions. Methods A combined dataset of 2003 genotypes clustered to 1000 Genomes individuals from Utah with Northern and Western European ancestry (CEU) was used to construct a training set of 790 genotypes paired to 888 RNASeq profiles from temporal cortex (TCX = 248), prefrontal cortex (FP = 50), inferior frontal gyrus (IFG = 41), superior temporal gyrus (STG = 34), parahippocampal cortex (PHG = 34), and dorsolateral prefrontal cortex (DLPFC = 461). Following within-tissue normalization and covariate adjustment, predictive weights to impute expression components based on a gene’s surrounding cis-variants were trained. The FUSION pipeline was modified to support input of pre-scaled expression values and support cross validation with a repeated measure design arising from the presence of multiple transcriptome samples from the same individual across different tissues. Results Cis-variant architecture alone was informative to train weights and impute expression for 6780 (49.67%) autosomal genes, the majority of which significantly correlated with gene expression; FDR < 5%: N = 6775 (99.92%), Bonferroni: N = 6716 (99.06%). Validation of weights in 515 matched genotype to RNASeq profiles from the CommonMind Consortium (CMC) was (72.14%) in DLPFC profiles. Association of imputed expression components from all 2003 genotype profiles yielded 8 genes significantly associated with AD (FDR < 0.05): APOC1, EED, CD2AP, CEACAM19, CLPTM1, MTCH2, TREM2, and KNOP1. Conclusions We provide evidence of cis-genetic variation conferring AD risk through 8 genes across six distinct genomic loci. Moreover, we provide expression weights for 6780 genes as a valuable resource to the community, which can be abstracted across the neocortex and a wide range of neuronal phenotypes.