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Individualized gray matter morphological abnormalities uncover two robust transdiagnostic biotypes.

Authors :
Fang, Keke
Hou, Ying
Niu, Lianjie
Han, Shaoqiang
Zhang, Wenzhou
Source :
Journal of Affective Disorders. Nov2024, Vol. 365, p193-204. 12p.
Publication Year :
2024

Abstract

Psychiatric disorders exhibit a shared neuropathology, yet the diverse presentations among patients necessitate the identification of transdiagnostic subtypes to enhance diagnostic and treatment strategies. This study aims to unveil potential transdiagnostic subtypes based on personalized gray matter morphological abnormalities. A total of 496 patients with psychiatric disorders and 255 healthy controls (HCs) from three distinct datasets (one for discovery and two for validation) were enrolled. Individualized gray matter morphological abnormalities were determined using normative modeling to identify transdiagnostic subtypes. In the discovery dataset, two transdiagnostic subtypes with contrasting patterns of structural abnormalities compared to HCs were identified. Reproducibility and generalizability analyses demonstrated that these subtypes could be generalized to new patients and even to new disorders in the validation datasets. These subtypes were characterized by distinct disease epicenters. The gray matter abnormal pattern in subtype 1 was mainly linked to excitatory receptors, whereas subtype 2 showed a predominant association with inhibitory receptors. Furthermore, we observed that the gray matter abnormal pattern in subtype 2 was correlated with transcriptional profiles of inflammation-related genes, while subtype 1 did not show this association. Our findings reveal two robust transdiagnostic biotypes, offering novel insights into psychiatric nosology. • We identify two robust transdiagnostic subtypes based on individualized gray matter morphological abnormalities. • These subtypes exhibiting contrasting patterns of structural abnormalities relative to healthy controls. • The identified subtypes are validated using independent datasets and can be extended to unseen disorders. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01650327
Volume :
365
Database :
Academic Search Index
Journal :
Journal of Affective Disorders
Publication Type :
Academic Journal
Accession number :
179465926
Full Text :
https://doi.org/10.1016/j.jad.2024.08.102