iScienceGenetic & Genomic MedicinePeer-reviewed journal article
Using brain cell-type-specific protein interactomes to interpret genetic data in schizophrenia
Yu-Han H. HsuiD, Greta PintacudaiD, Ruize Liu, Eugeniu Nacu, April KimiD, Kalliopi Tsafou, Natalie Petrossian, William J. CrottyiD, Jung Min SuhiD, Jackson Riseman, Jacqueline M. MartíniD, Julia C. BiaginiiD, Daya MenaiD, Joshua K.T. Ching, Edyta Małolepsza, Taibo LiiD, Tarjinder SinghiD, Tian GeiD, Shawn B. EgriiD, Benjamin TanenbaumiD, Caroline R. StancliftiD, Annie M. ApffeliD, Stephan RipkeiD, Benjamin M. NealeiD, Aiden Peter CorviniD, , Ina GieglingiD
Abstract
Genetics have nominated many schizophrenia risk genes that lack functional interpretation. To empower such interpretation, we executed interaction proteomics for six risk genes in human induced neurons and found the resulting protein network to be enriched for common variant risk of schizophrenia in Europeans and East Asians. The network is down-regulated in layer 5/6 cortical neurons of patients and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and also contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in patients with schizophrenia and bipolar disease. Our findings establish brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and psychiatric diseases. One Sentence SummaryNeuronal protein interactomes is an organizing framework for integrating genetic and transcriptomic data in schizophrenia.
- organism: human
- assay: proteomics
- research focus: GWAS / association mapping
- research focus: fine-mapping
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 10
- FWCI
- 1.82
- Field percentile
- top 17%
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