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

Genome Medicine

Benjamin A. Logsdon¹  Yue Liu²  Ekaterina Gerasimov²  Thomas S. Wingo³  Aliza P. Wingo⁴  Jake Gockley⁵  William L. Poehlman⁵  Anna K. Greenwood⁵  Solveig K. Sieberts⁵  Jesse C. Wiley⁵  Lara M. Mangravite⁵  Kelsey S. Montgomery⁵ 

[1] Cajal Neuroscience, 1616 Eastlake Avenue East, Suite 208, 98102, Seattle, WA, USA;Department of Neurology, Emory University School of Medicine, 30322, Atlanta, GA, USA;Department of Neurology, Emory University School of Medicine, 30322, Atlanta, GA, USA;Department of Human Genetics, Emory University School of Medicine, 30322, Atlanta, GA, USA;Division of Mental Health, Atlanta VA Medical Center, Decatur, GA, USA;Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA;Sage Bionetworks, Seattle, WA, USA;

关键词: Alzheimer’s disease;    TWAS;    FUSION;    GWAS;    Dementia;    Neurodegeneration;    AMP-AD;   

DOI  :  10.1186/s13073-021-00890-2

来源: Springer

【 摘 要 】

BackgroundAlzheimer’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.MethodsA 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.ResultsCis-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.ConclusionsWe 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.

【 授权许可】

CC BY