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CATEGORIES:Making connections- brains and other complex syste
 ms
SUMMARY:Human brain functional genomics and the mechanisms
  underlying genetic risk for schizophrenia - Dr Mi
 chael Gandal
DTSTART;TZID=Europe/London:20210520T150000
DTEND;TZID=Europe/London:20210520T160000
UID:TALK160324AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/160324
DESCRIPTION:Our understanding of the pathophysiology of neurop
 sychiatric disorders\, including schizophrenia (SC
 Z)\, lags greatly behind other fields of medicine.
  Defining genetic contributions to disease risk ca
 n provide a rigorous foothold for mechanistic unde
 rstanding\, and over the past decade\, large-scale
  genetic studies have successfully identified hund
 reds of genetic variants robustly associated with 
 SCZ. However\, mechanistic insight and clinical tr
 anslation continue to lag the pace of risk variant
  identification\, hindered by the sheer number of 
 targets and their predominant noncoding localizati
 on\, as well as pervasive pleiotropy and incomplet
 e penetrance. Successful next steps require identi
 fication of "causal" genetic variants and their pr
 oximal biological consequences\; placing variants 
 within biologically defined functional contexts\, 
 reflecting specific molecular pathways\, cell type
 s\, circuits\, and developmental windows\; and cha
 racterizing the downstream\, convergent neurobiolo
 gical impact of polygenicity within an individual.
  Comprehensive transcriptomic profiling in human b
 rain can provide a quantitative biological context
  for interpreting the molecular effects of disease
 -associated genetic variants and for identifying s
 hared and distinct molecular pathways disrupted ac
 ross major neuropsychiatric disorders. Here\, I wi
 ll discuss our recent work as part of the PsychENC
 ODE Consortium to generate a large-scale functiona
 l genomic resource of the human cortex\, integrati
 ng genotype and RNA seq data from more than 2000 s
 amples\, including over 500 derived from individua
 ls with SCZ. We find pervasive differential splici
 ng and expression\, with changes at the transcript
  isoform-level -- as opposed to the gene level -- 
 showing the largest effect sizes\, genetic enrichm
 ents\, and disease specificity. Coexpression netwo
 rks identify a glial-immune signal demonstrating s
 hared disruption of the blood-brain-barrier and up
 -regulation of NFkB-associated genes\, as well as 
 disease-specific alterations in microglial-\, astr
 ocyte-\, and interferon-response modules. Finally\
 , we leverage the transcriptome-wide association (
 TWAS) approach to identify 64 high confidence cand
 idate risk genes.  This large-scale integration of
  genomic data in human brain enables a comprehensi
 ve systems-level view of the neurobiological archi
 tecture of major neuropsychiatric illness and prov
 ides a resource for mechanistic insight and therap
 eutic development.
LOCATION:Online
CONTACT:Sarah Morgan
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