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.

Highlights d Integrated proteogenomic characterization in 103 ccRCC cases d Delineation of chromosomal translocation events leading to chromosome 3p loss d Tumor-specific proteomic/phosphoproteomic alterations unrevealed by mRNA analysis d Immune-based subtypes of ccRCC defined by mRNA, proteome, and phosphoproteome

In the originally published version of this article, Daniel Geiszler's last name was misspelled. This error has now been corrected in the article online.

Highlights d Proteogenomics characterization of 218 pediatric brain tumor samples of 7 histologies d Proteomic clusters reveal actionable biological features spanning histological boundaries d Proteomics reveal downstream effects of DNA alterations not evident in transcriptomics d Kinase activity analyses provide insights into pathway activities and druggable targets

Highlights d CD14 + monocytes play a central role during ZIKV infection and express CD169 d CD169 is a biomarker of acute ZIKV infection and correlates with CXCL10 levels d ZIKV infection leads to distinct temporal patterns of gene and protein expression d Pre-existing dengue immunity has minimal impact on the innate immune response to Zika