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Hölzlwimmer, F.R.* ; Lindner, J.* ; Tsitsiridis, G.* ; Wagner, N.* ; Casale, F.P. ; Yépez, V.A.* ; Gagneur, J.

Aberrant gene expression prediction across human tissues.

Nat. Commun. 16:3061 (2025)
DOI PMC
Despite the frequent implication of aberrant gene expression in diseases, algorithms predicting aberrantly expressed genes of an individual are lacking. To address this need, we compile an aberrant expression prediction benchmark covering 8.2 million rare variants from 633 individuals across 49 tissues. While not geared toward aberrant expression, the deleteriousness score CADD and the loss-of-function predictor LOFTEE show mild predictive ability (1-1.6% average precision). Leveraging these and further variant annotations, we next train AbExp, a model that yields 12% average precision by combining in a tissue-specific fashion expression variability with variant effects on isoforms and on aberrant splicing. Integrating expression measurements from clinically accessible tissues leads to another two-fold improvement. Furthermore, we show on UK Biobank blood traits that performing rare variant association testing using the continuous and tissue-specific AbExp variant scores instead of LOFTEE variant burden increases gene discovery sensitivity and enables improved phenotype predictions.
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Publication type Article: Journal article
Document type Scientific Article
Corresponding Author
Keywords Association
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Quellenangaben Volume: 16, Issue: 1, Pages: , Article Number: 3061 Supplement: ,
Publisher Nature Publishing Group
Publishing Place London
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)
Institute of AI for Health (AIH)
Helmholtz Pioneer Campus (HPC)
Grants National Health Service (NHS)
NCI
Common Fund of the Office of the Director of the National Institutes of Health
Helmholtz Association - Free State of Bavaria's Hightech Agenda through the Institute of AI for Health
European Union's Horizon Europe research and innovation program
Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)
VALE
German Bundesministerium fr Bildung und Forschung (BMBF) through the Model Exchange for Regulatory Genomics project
NHGRI
NHLBI
NIDA
Diabetes UK
Cancer Research UK
British Heart Foundation
Welsh Government
Northwest Regional Development Agency
Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government
Answer ALS Consortium
NINDS
NIMH
Bundesministerium fr Bildung und Forschung (Federal Ministry of Education and Research)