NEW YORK (GenomeWeb) – By tapping into brain gene expression and genome-wide association data, researchers from Mount Sinai's Icahn School of Medicine and elsewhere have identified hundreds of new associations and tracked the expression of schizophrenia-related genes in distinct human brain regions over the human lifespan.
"Our new predictor models gave us unprecedented power to study predicted gene expression in schizophrenia, and to identify new risk genes associated with the disease," first and corresponding author Laura Huckins, a genetics, genomic sciences, and psychiatry researcher at the Icahn School of Medicine, said in a statement, adding that "it was fascinating to see schizophrenia risk genes expressed throughout development, including in early pregnancy."
Huckins and her colleagues started with data generated for the CommonMind Consortium project — a collection of genotyping, gene expression, and expression quantitative trait locus data for the dorsolateral prefrontal brain cortex region. With these data, the researchers did transcriptomic imputation, developing a machine learning-based genetically regulated gene expression model that was validated against known RNA sequence data in independent datasets and subsequently used to predict schizophrenia-related gene expression patterns in 40,299 schizophrenia cases and 62,264 unaffected controls.
"Transcriptomic imputation approaches codify the relationships between genotype and gene expression in matched panels of individuals, then impute the genetic component of the transcriptome into large-scale genotype-only datasets, such as case-control GWAS cohorts, enabling investigation of disease-associated gene expression changes," the authors wrote in their Nature Genetics study, out online today. "This will allow us to study genes with modest effect sizes, likely representing a large proportion of genomic risk for psychiatric disorders."
In particular, the team's analysis pointed to 413 gene-schizophrenia associations in 13 human brain regions, involving 256 genes — and some three-dozen pathways — in 13 brain regions. In subsequent gene set enrichment analyses, in silico analyses, and mouse model gene experiments, meanwhile, the authors shored up these schizophrenia associations and got a look at the expression of these genes in distinct brain regions over different points in development.
In the dorsolateral prefrontal cortex, for example, the researchers detected 69 schizophrenia-related genes, including 49 genes falling outside of the major histocompatibility complex immune region — associations they subsequently assessed in another 4,133 cases and 24,788 controls.
Across the schizophrenia-associated gene set, the team's hypothesis-based pathway analysis highlighted three pathways, including a synaptic function pathway involving the fragile X mental retardation protein, while a hypothesis-free search for enrichment led to 33 other pathways with apparent ties to schizophrenia. The authors went on to retrace the expression of schizophrenia-related genes across the human lifespan using brain gene expression clusters identified at eight stages of prenatal or postnatal development with data from the BrainSpan database.
"By laying the groundwork for combining transcriptomic imputation and genome-wide association study findings, our hope is to not only elucidate gene development as it relates to schizophrenia, but also shape the future of research methods and design," Huckins explained.