Cognitive profiles across the psychosis continuum.
Psychosis continuum
antipsychotic-naïve
cognition
first-episode
machine learning
self-organizing maps
ultra-high risk
Journal
Psychiatry research
ISSN: 1872-7123
Titre abrégé: Psychiatry Res
Pays: Ireland
ID NLM: 7911385
Informations de publication
Date de publication:
11 Sep 2024
11 Sep 2024
Historique:
received:
12
04
2024
revised:
24
07
2024
accepted:
29
08
2024
medline:
13
9
2024
pubmed:
13
9
2024
entrez:
12
9
2024
Statut:
aheadofprint
Résumé
Cognitive impairments are core features in individuals across the psychosis continuum and predict functional outcomes. Nevertheless, substantial variability in cognitive functioning within diagnostic groups, along with considerable overlap with healthy controls, hampers the translation of research findings into personalized treatment planning. Aligned with precision medicine, we employed a data driven machine learning method, self-organizing maps, to conduct transdiagnostic clustering based on cognitive functions in a sample comprising 228 healthy controls, 200 individuals at ultra-high risk for psychosis, and 98 antipsychotic-naïve patients with first-episode psychosis. The self-organizing maps revealed six clinically distinct cognitive profiles that significantly predicted baseline functional level and changes in functional level after one year. Cognitive flexibility in particular, as well as specific executive functions emerged as cardinal in differentiating the profiles. The application of self-organizing maps appears to be a promising approach to inform clinical decision-making based on individualized cognitive profiles, including patient allocation to different interventions. Moreover, this method has the potential to enable cross-diagnostic stratification in research trials, utilizing data-driven subgrouping informed by categories from underlying dimensions of cognition rather than from clinical diagnoses. Finally, the method enables cross-diagnostic profiling across other data modalities, such as brain networks or metabolic subtypes.
Identifiants
pubmed: 39265468
pii: S0165-1781(24)00453-0
doi: 10.1016/j.psychres.2024.116168
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
116168Informations de copyright
Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.
Déclaration de conflit d'intérêts
Declaration of competing interest Dr. Ebdrup is part of the Advisory Board of Eli Lilly Denmark A/S, Janssen-Cilag, Lundbeck Pharma A/S, and Takeda Pharmaceutical Company Ltd; and has received lecture fees from Bristol-Myers Squibb, Otsuka Pharma Scandinavia AB, Eli Lilly Company, and Lundbeck Pharma A/S. Dr. Bojesen received lecture fees from Lundbeck Pharma A/S. The rest of the authors have no conflicts to disclose.