| Title: |
Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm |
| Authors: |
Jiang, Y; Luo, C; Wang, J; Palaniyappan, L; Chang, X; Xiang, S; Zhang, J; Duan, M; Huang, H; Gaser, C; Nemoto, K; Miura, K; Hashimoto, R; Westlye, LT; Richard, G; Fernandez-Cabello, S; Parker, N; Andreassen, OA; Kircher, T; Nenadić, I; Stein, F; Thomas-Odenthal, F; Teutenberg, L; Usemann, P; Dannlowski, U; Hahn, T; Grotegerd, D; Meinert, S; Lencer, R; Tang, Y; Zhang, T; Li, C; Yue, W; Zhang, Y; Yu, X; Zhou, E; Lin, CP; Tsai, SJ; Rodrigue, AL; Glahn, D; Pearlson, G; Blangero, J; Karuk, A; Pomarol-Clotet, E; Salvador, R; Fuentes-Claramonte, P; Garcia-León, MÁ; Spalletta, G; Piras, F; Vecchio, D; Banaj, N; Cheng, J; Liu, Z; Yang, J; Gonul, AS; Uslu, O; Burhanoglu, BB; Uyar Demir, A; Rootes-Murdy, K; Calhoun, VD; Sim, K; Green, M; Quidé, Y; Chung, YC; Kim, WS; Sponheim, SR; Demro, C; Ramsay, IS; Iasevoli, F; de Bartolomeis, A; Barone, A; Ciccarelli, M; Brunetti, A; Cocozza, S; Pontillo, G; Tranfa, M; Park, MTM; Kirschner, M; Georgiadis, F; Kaiser, S; Van Rheenen, TE; Rossell, SL; Hughes, M; Woods, W; Carruthers, SP; Sumner, P; Ringin, E; Spaniel, F; Skoch, A; Tomecek, D; Homan, P; Homan, S; Omlor, W; Cecere, G; Nguyen, DD; Preda, A; Thomopoulos, SI; Jahanshad, N; Cui, LB; Yao, D; Quide, Yann |
| Source: |
urn:ISSN:2041-1723 ; Nature Communications, 15, 1, 5996 |
| Publisher Information: |
Springer Nature |
| Publication Year: |
2024 |
| Collection: |
UNSW Sydney (The University of New South Wales): UNSWorks |
| Subject Terms: |
5202 Biological Psychology; 52 Psychology; Mental Illness; Brain Disorders; Schizophrenia; Machine Learning and Artificial Intelligence; Serious Mental Illness; Mental Health; Neurosciences; 3 Good Health and Well Being; Humans; Male; Female; Adult; Algorithms; Magnetic Resonance Imaging; Gray Matter; Machine Learning; Middle Aged; Brain; Cross-Sectional Studies; Europe; Neuroimaging; Reproducibility of Results; North America; Hippocampus; ENIGMA Schizophrenia Consortium; ZIB Consortium; anzsrc-for: 5202 Biological Psychology; anzsrc-for: 52 Psychology |
| Description: |
Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
unknown |
| Relation: |
https://hdl.handle.net/1959.4/102997 |
| DOI: |
10.1038/s41467-024-50267-3 |
| Availability: |
https://hdl.handle.net/1959.4/102997; https://unsworks.unsw.edu.au/bitstreams/7079bbfa-b01b-4c66-b1d4-a1992a9d51ee/download; https://doi.org/10.1038/s41467-024-50267-3 |
| Rights: |
open access ; https://purl.org/coar/access_right/c_abf2 ; CC BY ; https://creativecommons.org/licenses/by/4.0/ ; free_to_read |
| Accession Number: |
edsbas.684D9D4D |
| Database: |
BASE |