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Trastulla, L.* ; Dolgalev, G.* ; Moser, S.* ; Jiménez-Barrón, L.T.* ; Andlauer, T.F.M.* ; von Scheidt, M.* ; Budde, M.* ; Heilbronner, U.* ; Papiol, S.* ; Teumer, A.* ; Homuth, G.* ; Völzke, H.* ; Dörr, M.* ; Falkai, P.* ; Schulze, T.G.* ; Gagneur, J. ; Iorio, F.* ; Müller-Myhsok, B.* ; Schunkert, H.* ; Ziller, M.J.*

Distinct genetic liability profiles define clinically relevant patient strata across common diseases.

Nat. Commun. 15:5534 (2024)
Verlagsversion DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Stratified medicine holds great promise to tailor treatment to the needs of individual patients. While genetics holds great potential to aid patient stratification, it remains a major challenge to operationalize complex genetic risk factor profiles to deconstruct clinical heterogeneity. Contemporary approaches to this problem rely on polygenic risk scores (PRS), which provide only limited clinical utility and lack a clear biological foundation. To overcome these limitations, we develop the CASTom-iGEx approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue specific gene expression levels. The paradigmatic application of this approach to coronary artery disease or schizophrenia patient cohorts identified diverse strata or biotypes. These biotypes are characterized by distinct endophenotype profiles as well as clinical parameters and are fundamentally distinct from PRS based groupings. In stark contrast to the latter, the CASTom-iGEx strategy discovers biologically meaningful and clinically actionable patient subgroups, where complex genetic liabilities are not randomly distributed across individuals but rather converge onto distinct disease relevant biological processes. These results support the notion of different patient biotypes characterized by partially distinct pathomechanisms. Thus, the universally applicable approach presented here has the potential to constitute an important component of future personalized medicine paradigms.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Genome-wide Association; Polygenic Risk; Schizophrenia; Heterogeneity; Wikipathways; Metaanalysis; Prediction; Traits; Models; Driven
Sprache englisch
Veröffentlichungsjahr 2024
HGF-Berichtsjahr 2024
ISSN (print) / ISBN 2041-1723
e-ISSN 2041-1723
Zeitschrift Nature Communications
Quellenangaben Band: 15, Heft: 1, Seiten: , Artikelnummer: 5534 Supplement: ,
Verlag Nature Publishing Group
Verlagsort London
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Computational Biology (ICB)
POF Topic(s) 30205 - Bioengineering and Digital Health
Forschungsfeld(er) Enabling and Novel Technologies
PSP-Element(e) G-503800-001
Förderungen
BMBF
European Union's Horizon Europe research and innovation programme
BMBF eMed program
NIMH Human Brain Collection Core
IRP NIMH
NIH
F. Hoffman-La Roche Ltd
Takeda Pharmaceuticals Company Limited
CommonMind Consortium
NINDS
NIMH
NIDA
NHLBI
NHGRI
NCI
BMBF Regulatory Genomics
Deutsche Forschungsgemeinschaft (German Research Foundation)
(DFG)
Leducq Foundation for Cardiovascular Research
British Heart Foundation (BHF)/German Centre of Cardiovascular Research (DZHK)
German Federal Ministry of Education and Research (BMBF)
German Federal Ministry of Economics and Energy
German Research Foundation (DFG)
Bavarian State Ministry of Science and the Arts
Bavarian State Ministry of Health
NARSAD Young Investigator Grant
European Union'sHorizon 2020 Research and Innovation Programme (PSY-PGx)
ERA-NET Neuron (BMBF)
Dr. Lisa Oehler Foundation (Kassel, Germany)
German Federal Ministry of Education and Research (BMBF) within the framework of the BipoLife network
Common Fund of the Office of the Director of the National Institutes of Health
DOI 10.1038/s41467-024-49338-2
WOS ID 001287263000001
Scopus ID 85197716640
PubMed ID 38951512
Erfassungsdatum 2024-07-15
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