TY - JOUR
T1 - Psychosis brain subtypes validated in first-episode cohorts and related to illness remission
T2 - results from the PHENOM consortium
AU - Dwyer, Dominic B.
AU - Chand, Ganesh B.
AU - Pigoni, Alessandro
AU - Khuntia, Adyasha
AU - Wen, Junhao
AU - Antoniades, Mathilde
AU - Hwang, Gyujoon
AU - Erus, Guray
AU - Doshi, Jimit
AU - Srinivasan, Dhivya
AU - Varol, Erdem
AU - Kahn, Rene S.
AU - Schnack, Hugo G.
AU - Meisenzahl, Eva
AU - Wood, Stephen J.
AU - Zhuo, Chuanjun
AU - Sotiras, Aristeidis
AU - Shinohara, Russell T.
AU - Shou, Haochang
AU - Fan, Yong
AU - Schaulfelberger, Maristela
AU - Rosa, Pedro
AU - Lalousis, Paris A.
AU - Upthegrove, Rachel
AU - Kaczkurkin, Antonia N.
AU - Moore, Tyler M.
AU - Nelson, Barnaby
AU - Gur, Raquel E.
AU - Gur, Ruben C.
AU - Ritchie, Marylyn D.
AU - Satterthwaite, Theodore D.
AU - Murray, Robin M.
AU - Di Forti, Marta
AU - Ciufolini, Simone
AU - Zanetti, Marcus V.
AU - Wolf, Daniel H.
AU - Pantelis, Christos
AU - Crespo-Facorro, Benedicto
AU - Busatto, Geraldo F.
AU - Davatzikos, Christos
AU - Koutsouleris, Nikolaos
AU - Dazzan, Paola
N1 - Publisher Copyright:
© 2023, The Author(s).
PY - 2023/5
Y1 - 2023/5
N2 - Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups—a ‘lower brain volume’ subgroup (SG1) and an ‘higher striatal volume’ subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership (‘None’), and mixed SG1 + SG2 subgroups (‘Mixed’). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of ‘lower brain volume’ in SG1 and ‘higher striatal volume’ (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature.
AB - Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups—a ‘lower brain volume’ subgroup (SG1) and an ‘higher striatal volume’ subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership (‘None’), and mixed SG1 + SG2 subgroups (‘Mixed’). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of ‘lower brain volume’ in SG1 and ‘higher striatal volume’ (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature.
UR - http://www.scopus.com/inward/record.url?scp=85158129069&partnerID=8YFLogxK
U2 - 10.1038/s41380-023-02069-0
DO - 10.1038/s41380-023-02069-0
M3 - Article
C2 - 37147389
AN - SCOPUS:85158129069
SN - 1359-4184
VL - 28
SP - 2008
EP - 2017
JO - Molecular Psychiatry
JF - Molecular Psychiatry
IS - 5
ER -