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

Authors :
Trastulla, Lucia
Dolgalev, Georgii
Moser, Sylvain
Jiménez-Barrón, Laura T.
Andlauer, Till F. M.
von Scheidt, Moritz
Ruderfer, Douglas M.
Ripke, Stephan
McQuillin, Andrew
Stahl, Eli A.
Domenici, Enrico
Adolfsson, Rolf
Agartz, Ingrid
Agerbo, Esben
Albus, Margot
Alexander, Madeline
Amin, Farooq
Bacanu, Silviu A.
Begemann, Martin
Belliveau Jr, Richard A.
Source :
Nature Communications; 6/29/2024, Vol. 15 Issue 1, p1-28, 28p
Publication Year :
2024

Abstract

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. Stratified medicine promises to tailor treatment for individual patients, however it remains a major challenge to leverage genetic risk data to aid patient stratification. Here the authors introduce an approach to stratify individuals based on the aggregated impact of their genetic risk factor profiles on tissue-specific gene expression levels, and highlight its ability to identify biologically meaningful and clinically actionable patient subgroups, supporting the notion of different patient 'biotypes' characterized by partially distinct disease mechanisms. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20411723
Volume :
15
Issue :
1
Database :
Complementary Index
Journal :
Nature Communications
Publication Type :
Academic Journal
Accession number :
178209195
Full Text :
https://doi.org/10.1038/s41467-024-49338-2