- Title
- BrainGENIE: The Brain Gene Expression and Network Imputation Engine
- Creator
- Hess, Jonathan L.; Quinn, Thomas P.; Kumarasinghe, Nishantha; Ophoff, Roel; Schall, Ulrich; Scott, Rodney; Stamova, Boryana; Tooney, Paul; Kong, Sek Won; Cairns, Murray; Tsuang, Ming T.; Faraone, Stephen V.; Zhang, Chunling; Glatt, Stephen J.; Hearn, Gentry C.; Chen, Samuel; Beveridge, Natalie Jane; Carr, Vaughan; de Jong, Simone; Gardiner, Erin; Kelly, Brian
- Relation
- NHMRC.1121474 http://purl.org/au-research/grants/nhmrc/1121474 & 1147644 http://purl.org/au-research/grants/nhmrc/1147644 & 1188493
- Relation
- Translational Psychiatry Vol. 13, Issue 1, no. 98
- Publisher Link
- http://dx.doi.org/10.1038/s41398-023-02390-w
- Publisher
- Nature Publishing Group
- Resource Type
- journal article
- Date
- 2023
- Description
- In vivo experimental analysis of human brain tissue poses substantial challenges and ethical concerns. To address this problem, we developed a computational method called the Brain Gene Expression and Network-Imputation Engine (BrainGENIE) that leverages peripheral-blood transcriptomes to predict brain tissue-specific gene-expression levels. Paired blood–brain transcriptomic data collected by the Genotype-Tissue Expression (GTEx) Project was used to train BrainGENIE models to predict gene-expression levels in ten distinct brain regions using whole-blood gene-expression profiles. The performance of BrainGENIE was compared to PrediXcan, a popular method for imputing gene expression levels from genotypes. BrainGENIE significantly predicted brain tissue-specific expression levels for 2947–11,816 genes (false-discovery rate-adjusted p < 0.05), including many transcripts that cannot be predicted significantly by a transcriptome-imputation method such as PrediXcan. BrainGENIE recapitulated measured diagnosis-related gene-expression changes in the brain for autism, bipolar disorder, and schizophrenia better than direct correlations from blood and predictions from PrediXcan. We developed a convenient software toolset for deploying BrainGENIE, and provide recommendations for how best to implement models. BrainGENIE complements and, in some ways, outperforms existing transcriptome-imputation tools, providing biologically meaningful predictions and opening new research avenues.
- Subject
- human brain tissue; gene-expression prediction; transcriptome prediction; Genotype-Tissue Expression (GTEx)
- Identifier
- http://hdl.handle.net/1959.13/1484470
- Identifier
- uon:51344
- Identifier
- ISSN:2158-3188
- Language
- eng
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