Mendelian randomization facilitates identification of schizophrenia risk enhancer RNAs
Linyan Ye, Chaoying Ni, Renhao Chen, Siyao Che, Fu Xiong, Cunyou Zhao, Zhongju Wang

TL;DR
This study uses genetic data to identify enhancer RNAs linked to schizophrenia risk and shows how they influence disease risk through gene regulation.
Contribution
The study introduces a novel approach using SMR analysis to identify schizophrenia-risk enhancer RNAs and validates their regulatory role experimentally.
Findings
61 schizophrenia-risk TNEs were identified using SMR analysis, with 19 overlapping with differential expression results.
Reduced levels of ZNF135 in schizophrenia were linked to derepression of motif-matched TNEs.
The enhancer RNA RGS6e was experimentally validated to regulate nervous system genes and reduce schizophrenia risk.
Abstract
The transcription of enhancer RNA (eRNA) marks enhancer activity and may confer context-dependent regulatory functions, yet its underlying mechanism remains elusive. Leveraging BrainSeq data, we constructed ancestry-stratified expression quantitative trait locus (eQTL) maps for 71,022 transcriptional non-coding enhancer (TNE) RNAs. By integrating the latest Psychiatric Genomics Consortium (PGC3) schizophrenia GWAS with European-ancestry population-based eQTLs via Summary-data-based Mendelian Randomization (SMR), we identified 61 schizophrenia-risk TNEs, 19 of which overlapped with those from differential expression (DE) analysis. Intriguingly, for 19 overlapping TNEs, effects from DE analysis were inversely correlated with SMR effects (r = −0.57, P = 0.01), attributable to the opposing contributions of phenotype and genotype to TNE expression (r = −0.78, P = 2.96E−3). We further linked…
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Taxonomy
TopicsGenomics and Chromatin Dynamics · Genetic Associations and Epidemiology · Epigenetics and DNA Methylation
