Many large whole-genome sequenncing (WGS) consortia are searching for genetic pathways in clinical disorders such as autism spectrum disorder (ASD), schizophrenia (SCZ), and bipolar disorder (BD) — hoping to develop novel drugs to treat these three common psychiatric disorders that usually result in lifelong disability. Genome-wide association studies (GWAS) have identified hundreds of causal genetic variants that are (statistically robustly) associated with these disorders, plus thousands more that likely contribute to their pathogenesis. However, neurobiological mechanisms (through which genetic variation imparts risk to ASD, SCZ and/or BD) remain still largely unknown.
The majority of disease-associated genetic variation lies in noncoding regions (segments of DNA having no genes that result in protein products) enriched for noncoding RNAs (ncRNAs) and cis-regulatory [cis = near to a gene(s)] elements that regulate gene expression and splicing of their related coding gene targets. Such regulatory relationships show substantial heterogeneity across human cell types, tissues, and developmental stages and sometimes are even species-specific. Recognizing the importance of understanding transcriptional regulation and noncoding genome function, several consortia have undertaken large-scale efforts to provide maps of the transcriptome (portions of protein-coding DNA that are transcribed and result in an RNA or protein product) and its genetic and epigenetic regulation across human tissues.
Although some studies have included central nervous system (CNS) tissues, a more comprehensive analysis focusing on the brain in both healthy and disease states is necessary to accelerate our understanding of the molecular mechanisms of these disorders. Authors [see attaced article] present results of the analysis of RNA-sequencing (RNA-seq) data from the PsychENCODE Consortium, integrating genetic and genomic data from more than 2000 well-curated, high-quality postmortem brain samples from individuals with SCZ, BD, and ASD (as well as controls).
Coexpression networks are able to isolate disease-specific neuronal alterations, as well as microglial, astrocyte, and interferon-response modules — defining previously unidentified neural-immune mechanisms. Authors integrated genetic and genomic data to perform a transcriptome-wide association study, prioritizing disease loci that are likely mediated by cis effects on brain expression.This thorough transcriptome-wide characterization of molecular pathology across three major psychiatric disorders is an excellent start, in providing a baseline resource for future studies with regard to mechanistic insight and therapeutic development.
Science 14 Dec 2o18; 362: 1265