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Human brain functional genomics and the mechanisms underlying genetic risk for schizophrenia

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  • UserDr Michael Gandal
  • ClockThursday 20 May 2021, 15:00-16:00
  • HouseOnline.

If you have a question about this talk, please contact Sarah Morgan.

Our understanding of the pathophysiology of neuropsychiatric disorders, including schizophrenia (SCZ), lags greatly behind other fields of medicine. Defining genetic contributions to disease risk can provide a rigorous foothold for mechanistic understanding, and over the past decade, large-scale genetic studies have successfully identified hundreds of genetic variants robustly associated with SCZ . However, mechanistic insight and clinical translation continue to lag the pace of risk variant identification, hindered by the sheer number of targets and their predominant noncoding localization, as well as pervasive pleiotropy and incomplete penetrance. Successful next steps require identification of “causal” genetic variants and their proximal biological consequences; placing variants within biologically defined functional contexts, reflecting specific molecular pathways, cell types, circuits, and developmental windows; and characterizing the downstream, convergent neurobiological impact of polygenicity within an individual. Comprehensive transcriptomic profiling in human brain can provide a quantitative biological context for interpreting the molecular effects of disease-associated genetic variants and for identifying shared and distinct molecular pathways disrupted across major neuropsychiatric disorders. Here, I will discuss our recent work as part of the PsychENCODE Consortium to generate a large-scale functional genomic resource of the human cortex, integrating genotype and RNA seq data from more than 2000 samples, including over 500 derived from individuals with SCZ . We find pervasive differential splicing and expression, with changes at the transcript isoform-level—as opposed to the gene level—showing the largest effect sizes, genetic enrichments, and disease specificity. Coexpression networks identify a glial-immune signal demonstrating shared disruption of the blood-brain-barrier and up-regulation of NFkB-associated genes, as well as disease-specific alterations in microglial-, astrocyte-, and interferon-response modules. Finally, we leverage the transcriptome-wide association (TWAS) approach to identify 64 high confidence candidate risk genes. This large-scale integration of genomic data in human brain enables a comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness and provides a resource for mechanistic insight and therapeutic development.

This talk is part of the Making connections- brains and other complex systems series.

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