PuSH - Publikationsserver des Helmholtz Zentrums München

Export: TXT Text RIS Endnote (RIS) BIB BibTeX
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)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
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.
Impact Factor
Scopus SNIP
Altmetric
15.700
0.000
Tags
Anmerkungen
Besondere Publikation
Auf Hompepage verbergern

Zusatzinfos bearbeiten
Eigene Tags bearbeiten
Privat
Eigene Anmerkung bearbeiten
Privat
Auf Publikationslisten für
Homepage nicht anzeigen
Als besondere Publikation
markieren
Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Association
Sprache englisch
Veröffentlichungsjahr 2025
HGF-Berichtsjahr 2025
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Zeitschrift Nature Communications
Quellenangaben Band: 16, Heft: 1, Seiten: , Artikelnummer: 3061 Supplement: ,
Verlag Nature Publishing Group
Verlagsort London
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
Institute of AI for Health (AIH)
Helmholtz Pioneer Campus (HPC)
POF Topic(s) 30205 - Bioengineering and Digital Health
30202 - Environmental Health
Forschungsfeld(er) Enabling and Novel Technologies
Pioneer Campus
PSP-Element(e) G-503800-001
G-540004-001
G-510007-001
Förderungen 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)
DOI 10.1038/s41467-025-58210-w
WOS ID 001456231100009
Scopus ID 105001478471
PubMed ID 40157914
Erfassungsdatum 2025-05-09
[➜Korrektur melden]