Lucia Trastulla, Max Planck Institute of Psychiatry, Munich, Germany
Georgii Dolgalev, University of Münster, Münster, Germany
Sylvain Moser, Max Planck Institute of Psychiatry, Munich, Germany
Laura T. Jiménez-Barrón, Max Planck Institute of Psychiatry, Munich, Germany
Till F. M. Andlauer, Max Planck Institute of Psychiatry, Munich, Germany
Moritz von Scheidt, Technical University Munich, Munich, Germany
Schizophrenia Working Group of the Psychiatric Genomics Consortium:
Douglas M. Ruderfer, Vanderbilt University Medical Center, Nashville, TN
Stephan Ripke, Massachusetts General Hospital, Boston, MA
Andrew McQuillin, University College London, United Kingdom
Eli A. Stahl, Icahn School of Medicine at Mount Sinai, New York, NY
Enrico Domenici, University of Trento, Italy
Rolf Adolfsson, Umea University, Sweden
Ingrid Agartz, Diakonhjemmet Hospital, Oslo, Norway
Esben Agerbo, Aarhus University, Aarhus, Denmark
Margot Albus, State Mental Hospital, Haar, Germany
Madeline Alexander, Stanford University, Stanford, CA
Farooq Amin, Atlanta Veterans Affairs Medical Center, GA
Silviu A. Bacanu, Virginia Commonwealth University, Richmond, VA
Martin Begemann, Max Planck Institute of Experimental Medicine, Gottingen, Germany
Richard A. Belliveau Jr., Broad Institute of MIT and Harvard, Cambridge, MA
Judit Bene, University of Pecs, Pecs, Hungary
Sarah E. Bergen, Karolinska Institutet, Stockholm, Sweden
Elizabeth Bevilacqua, Broad Institute of MIT and Harvard, Cambridge, MA
Tim B. Bigdeli, Virginia Commonwealth University, Richmond, VA
Donald W. Black, University of Iowa Carver College of Medicine, Iowa City, IA
Douglas H. R. Blackwood, University of Edinburgh, United Kingdom
Anders D. Borglum, Aarhus University, Aarhus, Denmark
Nancy G. Buccola, LSU Health Sciences Center - New Orleans
et al

Document Type

Article

Publication Date

7-1-2024

Publication Title

Nature Communications

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.

PubMed ID

38951512

Volume

15

Issue

1

Comments

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Creative Commons License

Creative Commons Attribution 4.0 International License
This work is licensed under a Creative Commons Attribution 4.0 International License.

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