Brain expression quantitative trait locus and network analyses reveal downstream effects and putative drivers for brain-related diseases

Abstract

Identification of therapeutic targets from genome-wide association studies (GWAS) requires insights into downstream functional consequences. We harmonized 8,613 RNA-sequencing samples from 14 brain datasets to create the MetaBrain resource and performed cis- and trans-expression quantitative trait locus (eQTL) meta-analyses in multiple brain region- and ancestry-specific datasets (n ≤ 2,759). Many of the 16,169 cortex cis-eQTLs were tissue-dependent when compared with blood cis-eQTLs. We inferred brain cell types for 3,549 cis-eQTLs by interaction analysis. We prioritized 186 cis-eQTLs for 31 brain-related traits using Mendelian randomization and co-localization including 40 cis-eQTLs with an inferred cell type, such as a neuron-specific cis-eQTL (CYP24A1) for multiple sclerosis. We further describe 737 trans-eQTLs for 526 unique variants and 108 unique genes. We used brain-specific gene-co-regulation networks to link GWAS loci and prioritize additional genes for five central nervous system diseases. This study represents a valuable resource for post-GWAS research on central nervous system diseases.

Heart-brain connections: Phenotypic and genetic insights from magnetic resonance images

“…Evidence of pairwise colocalization was defined as having a posterior probability of the shared causal variant hypothesis (PPH4) > 0.8 ( 72 , 73 ). Many shared genetic variants were found to be expression quantitative trait loci (eQTLs) in a recent large-scale eQTL meta-analysis of brain ( 74 ) and blood tissues ( 75 ). The traits with shared genetic effects are presented in table S10, with selected pairs shown in Fig.…”

“…S50). The index variants of 7p21.1 (rs2107595) and 12q24.12 (rs597808) were eQTLs of TWIST1 and ALDH2 in human brain tissues ( 74 ), suggesting that these CMR-associated variants were known to affect gene expression in human brain. TWIST1 was associated with cerebral vasculature defects ( 85 ), and there was a higher level of ALDH2 activity in the putamen and temporal cortex of patients with Alzheimer’s disease ( 86 ).…”

Neuroimaging genomics as a window into the evolution of human sulcal organization

“…We further scrutinised the regulatory and evolutionary relevance of the SNP rs884370 by leveraging the MetaBrain expression quantitative trait loci (eQTL) dataset (de Klein et al 2023), a publicly available ancient DNA genotype dataset, and non-human primate genome assemblies. Our analyses revealed that rs884370 is annotated as a cis-eQTL of ZIC4 (P=5.81×10 -14 , Beta(SE)=0.23(0.03)) and ZIC1 (P=1.55×10 -14 , Beta(SE)=0.23(0.03)) in adult brain tissue (Fig.…”

omicSynth: an Open Multi-omic Community Resource for Identifying Druggable Targets across Neurodegenerative Diseases

“…It is not subject to copyright under 17 USC 105 and is also made available volume of publicly available data sources. All eQTL and mQTL data obtained, except from the sources eQTLgen, metaBrain and Zeng, et al (multi ancestry), were already in SMR format and obtained from the Yang Lab's Data Resource page [13][14][15]. The eQTL sources from the Yang Lab include Genotype-Tissue Expression (GTEx) project v8 release, PsychENCODE, and BrainMeta v1 (formerly brain-eMeta) [16][17][18].…”