TY - JOUR
T1 - Distinct genetic liability profiles define clinically relevant patient strata across common diseases
AU - Trastulla, Lucia
AU - Dolgalev, Georgii
AU - Moser, Sylvain
AU - Jiménez-Barrón, Laura T.
AU - Andlauer, Till F.M.
AU - von Scheidt, Moritz
AU - Ruderfer, Douglas M.
AU - Ripke, Stephan
AU - McQuillin, Andrew
AU - Stahl, Eli A.
AU - Domenici, Enrico
AU - Adolfsson, Rolf
AU - Agartz, Ingrid
AU - Agerbo, Esben
AU - Albus, Margot
AU - Alexander, Madeline
AU - Amin, Farooq
AU - Bacanu, Silviu A.
AU - Begemann, Martin
AU - Belliveau, Richard A.
AU - Bene, Judit
AU - Bergen, Sarah E.
AU - Bevilacqua, Elizabeth
AU - Bigdeli, Tim B.
AU - Black, Donald W.
AU - Blackwood, Douglas H.R.
AU - Borglum, Anders D.
AU - Bramon, Elvira
AU - Bruggeman, Richard
AU - Buccola, Nancy G.
AU - Buckner, Randy L.
AU - Bulik-Sullivan, Brendan
AU - Buxbaum, Joseph D.
AU - Byerley, William
AU - Cahn, Wiepke
AU - Cai, Guiqing
AU - Campion, Dominique
AU - Cantor, Rita M.
AU - Carr, Vaughan J.
AU - Carrera, Noa
AU - Catts, Stanley V.
AU - Chambert, Kimberley D.
AU - Chan, Raymond C.K.
AU - Chen, Eric Y.H.
AU - Chen, Ronald Y.L.
AU - Cheng, Wei
AU - Cheung, Eric F.C.
AU - Chong, Siow Ann
AU - Cichon, Sven
AU - Cloninger, C. Robert
AU - Schizophrenia Working Group of the Psychiatric Genomics Consortium
AU - van Os, Jim
AU - Germeys, Inez
N1 - Funding Information:
We thank all members of the Ziller, Gagneur and Schunkert labs for their support and critical feedback. We also thank Bernhard Baune and Monika Stoll for providing critical feedback on the manuscript. This research has been conducted using the UK Biobank Resource under application numbers 34217 and 25214. We thank all participants, researchers, and support staff who make the study possible. Bona fide researchers can apply to use the UK Biobank data set by registering and applying at http://ukbiobank.ac.uk/register-apply/ . The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health, and by NCI, NHGRI, NHLBI, NIDA, NIMH, and NINDS. This study used data from the CommonMind consortium provided through NIMH. Data for this publication were obtained from NIMH Repository & Genomics Resource, a centralized national biorepository for genetic studies of psychiatric disorders. Data were generated as part of the CommonMind Consortium supported by funding from Takeda Pharmaceuticals Company Limited, F. Hoffman-La Roche Ltd and NIH grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881, AG02219, AG05138, MH06692, R01MH110921, R01MH109677, R01MH109897, U01MH103392, and contract HHSN271201300031C through IRP NIMH. Brain tissue for the study was obtained from the following brain bank collections: the Mount Sinai NIH Brain and Tissue Repository, the University of Pennsylvania Alzheimer\u2019s Disease Core Center, the University of Pittsburgh NeuroBioBank and Brain and Tissue Repositories, and the NIMH Human Brain Collection Core. CMC Leadership: Panos Roussos, Joseph Buxbaum, Andrew Chess, Schahram Akbarian, Vahram Haroutunian (Icahn School of Medicine at Mount Sinai), Bernie Devlin, David Lewis (University of Pittsburgh), Raquel Gur, Chang-Gyu Hahn (University of Pennsylvania), Enrico Domenici (University of Trento), Mette A. Peters, Solveig Sieberts (Sage Bionetworks), Thomas Lehner, Stefano Marenco, Barbara K. Lipska (NIMH). This work was supported by grants from the BMBF eMed program grant 01ZX1504, NIH grant DP3DK111898, the European Union\u2019s Horizon Europe research and innovation programme under grant agreement No 101057454 PSYCHSTRATA to MZ, the Max-Planck-Society and BMBF eMed program grant 01ZX1706 to MZ, HS. and JG. As well as the BMBF Regulatory Genomics project MERGE 031L0174A/B to JG and MZ. to J.G.TGS and PF are supported by the Deutsche Forschungsgemeinschaft (German Research Foundation; DFG) within the framework of the projects http://www.kfo241.de and http://www.PsyCourse.de (SCHU 1603/4-1, 5-1, 7-1; FA241/16-1). TGS received additional support from the German Federal Ministry of Education and Research (BMBF) within the framework of the BipoLife network (01EE1404H), IntegraMent (01ZX1614K), e:Med Program (01ZX1614K) and the Dr. Lisa Oehler Foundation (Kassel, Germany). TGS was further supported by the grants GWPI-BIOPSY (01EW 2005) and MulioBio (01EW 2009) from ERA-NET Neuron (BMBF). UH was supported by European Union\u2019s Horizon 2020 Research and Innovation Programme (PSY-PGx, grant agreement No 945151). SP received support from the NARSAD Young Investigator Grant. HS received additional support from DigiMed Bayern ( www.digimed-bayern.de ; DMB-1805\u20130001) funded by the Bavarian State Ministry of Health, Care and Prevention and the Bavarian State Ministry of Science and the Arts through the DHM-MSRM Joint Research Center (1530/891 02), the German Research Foundation (DFG) as part of the Sonderforschungsbereich SFB 1123 (B02) and the Sonderforschungsbereich SFB TRR 267 (B05). The work has been also supported by the German Federal Ministry of Economics and Energy in its scheme of ModulMax (Grant No: ZF4590201BA8). The work was also funded by the German Federal Ministry of Education and Research (BMBF) within the framework of COMMITMENT (01ZX1904A). As a Co-applicant of the British Heart Foundation (BHF)/German Centre of Cardiovascular Research (DZHK)-collaboration (DZHK-BHF: 81X2600522) and the Leducq Foundation for Cardiovascular Research (PlaqOmics: 18CVD02).
Publisher Copyright:
© The Author(s) 2024.
PY - 2024/12/1
Y1 - 2024/12/1
N2 - 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.
AB - 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.
U2 - 10.1038/s41467-024-49338-2
DO - 10.1038/s41467-024-49338-2
M3 - Article
SN - 2041-1723
VL - 15
JO - Nature Communications
JF - Nature Communications
IS - 1
M1 - 5534
ER -