Details

Autor(en) / Beteiligte

• Luo, Jie
• Li, Ling
• Niu, Mingming
• Kong, Dehui
• Jiang, Yi
• Poudel, Suresh
• Shieh, Annie W.
• Cheng, Lijun
• Giase, Gina
• Grennan, Kay
• White, Kevin P.
• Chen, Chao
• Wang, Sidney H.
• Pinto, Dalila
• Wang, Yue
• Liu, Chunyu
• Peng, Junmin
• Wang, Xusheng

Titel

Genetic regulation of human brain proteome reveals proteins implicated in psychiatric disorders

Ist Teil von

• Molecular psychiatry, 2024-05, Vol.29 (11), p.3330-3343

Ort / Verlag

London: Nature Publishing Group UK

Erscheinungsjahr

2024

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Psychiatric disorders are highly heritable yet polygenic, potentially involving hundreds of risk genes. Genome-wide association studies have identified hundreds of genomic susceptibility loci with susceptibility to psychiatric disorders; however, the contribution of these loci to the underlying psychopathology and etiology remains elusive. Here we generated deep human brain proteomics data by quantifying 11,608 proteins across 268 subjects using 11-plex tandem mass tag coupled with two-dimensional liquid chromatography-tandem mass spectrometry. Our analysis revealed 788 cis -acting protein quantitative trait loci associated with the expression of 883 proteins at a genome-wide false discovery rate <5%. In contrast to expression at the transcript level and complex diseases that are found to be mainly influenced by noncoding variants, we found protein expression level tends to be regulated by non-synonymous variants. We also provided evidence of 76 shared regulatory signals between gene expression and protein abundance. Mediation analysis revealed that for most (88%) of the colocalized genes, the expression levels of their corresponding proteins are regulated by cis -pQTLs via gene transcription. Using summary data-based Mendelian randomization analysis, we identified 4 proteins and 19 genes that are causally associated with schizophrenia. We further integrated multiple omics data with network analysis to prioritize candidate genes for schizophrenia risk loci. Collectively, our findings underscore the potential of proteome-wide linkage analysis in gaining mechanistic insights into the pathogenesis of psychiatric disorders.