Publikationsdatum:
2018-12-14
Beschreibung:
Despite progress in defining genetic risk for psychiatric disorders, their molecular mechanisms remain elusive. Addressing this, the PsychENCODE Consortium has generated a comprehensive online resource for the adult brain across 1866 individuals. The PsychENCODE resource contains ~79,000 brain-active enhancers, sets of Hi-C linkages, and topologically associating domains; single-cell expression profiles for many cell types; expression quantitative-trait loci (QTLs); and further QTLs associated with chromatin, splicing, and cell-type proportions. Integration shows that varying cell-type proportions largely account for the cross-population variation in expression (with 〉88% reconstruction accuracy). It also allows building of a gene regulatory network, linking genome-wide association study variants to genes (e.g., 321 for schizophrenia). We embed this network into an interpretable deep-learning model, which improves disease prediction by ~6-fold versus polygenic risk scores and identifies key genes and pathways in psychiatric disorders.
Schlagwort(e):
Genetics, Neuroscience, Online Only
Print ISSN:
0036-8075
Digitale ISSN:
1095-9203
Thema:
Biologie
,
Chemie und Pharmazie
,
Geologie und Paläontologie
,
Informatik
,
Medizin
,
Allgemeine Naturwissenschaft
,
Physik
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