Abstract
BackgroundMajor depression (MD) is determined by a multitude of factors including genetic risk variants that regulate gene expression. We examined the genetic component of gene expression in MD by performing a transcriptome-wide association study (TWAS), inferring gene expression–trait relationships from genetic, transcriptomic, and phenotypic information. MethodsGenes differentially expressed in depression were identified with the TWAS FUSION method, based on summary statistics from the largest genome-wide association analysis of MD (n = 135,458 cases, n = 344,901 controls) and gene expression levels from 21 tissue datasets (brain; blood; thyroid, adrenal, and pituitary glands). Follow-up analyses were performed to extensively characterize the identified associations: colocalization, conditional, and fine-mapping analyses together with TWAS-based pathway investigations. ResultsTranscriptome-wide significant differences between cases and controls were found at 94 genes, approximately half of which were novel. Of the 94 significant genes, 6 represented strong, colocalized, and potentially causal associations with depression. Such high-confidence associations include NEGR1, CTC-467M3.3, TMEM106B, LRFN5, ESR2, and PROX2. Lastly, TWAS-based enrichment analysis highlighted dysregulation of gene sets for, among others, neuronal and synaptic processes. ConclusionsThis study sheds further light on the genetic component of gene expression in depression by characterizing the identified associations, unraveling novel risk genes, and determining which associations are congruent with a causal model. These findings can be used as a resource for prioritizing and designing subsequent functional studies of MD.
Highlights
Major depression (MD) is determined by a multitude of factors including genetic risk variants that regulate gene expression
We identified 176 significant features, from 94 unique genes, which were differentially expressed (p, 1.37 3 1026) across multiple single nucleotide polymorphisms (SNPs) weight sets in MD (Figure 1; Figure S1A, B in Supplement 1; Table S2 in Supplement 2)
The largest number of associations were from the PsychENCODE dorsolateral prefrontal cortex (DLPFC) set (22 associated features), but inferences on tissue enrichment are difficult, as SNP weight sets differ in their characteristics
Summary
Major depression (MD) is determined by a multitude of factors including genetic risk variants that regulate gene expression. Of the 94 significant genes, 6 represented strong, colocalized, and potentially causal associations with depression. Such high-confidence associations include NEGR1, CTC-467M3.3, TMEM106B, LRFN5, ESR2, and PROX2. CONCLUSIONS: This study sheds further light on the genetic component of gene expression in depression by characterizing the identified associations, unraveling novel risk genes, and determining which associations are congruent with a causal model.
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