Major depressive disorder on a neuromorphic continuum

Jiao Li, Zhiliang Long, Gong-Jun Ji, Shaoqiang Han, Yuan Chen, Guanqun Yao, Yong Xu, Kerang Zhang, Yong Zhang, Jingliang Cheng, Kai Wang, Huafu Chen and Wei Liao ()
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Jiao Li: University of Electronic Science and Technology of China
Zhiliang Long: Southwest University
Gong-Jun Ji: Anhui Medical University
Shaoqiang Han: Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University
Yuan Chen: Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University
Guanqun Yao: Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University
Yong Xu: Department of Clinical Psychology, The Eighth Affiliated Hospital, Sun Yat-Sen University
Kerang Zhang: Department of Psychiatry, First Hospital/First Clinical Medical College of Shanxi Medical University
Yong Zhang: Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University
Jingliang Cheng: Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University
Kai Wang: Anhui Medical University
Huafu Chen: University of Electronic Science and Technology of China
Wei Liao: University of Electronic Science and Technology of China

Nature Communications, 2025, vol. 16, issue 1, 1-13

Abstract: Abstract The heterogeneity of major depressive disorder (MDD) has hindered clinical translation and neuromarker identification. Biotyping facilitates solving the problems of heterogeneity, by dissecting MDD patients into discrete subgroups. However, interindividual variations suggest that depression may be conceptualized as a “continuum,” rather than as a “category.” We use a Bayesian model to decompose structural MRI features of MDD patients from a multisite cross-sectional cohort into three latent disease factors (spatial pattern) and continuum factor compositions (individual expression). The disease factors are associated with distinct neurotransmitter receptors/transporters obtained from open PET sources. Increases cortical thickness in sensory and decreases in orbitofrontal cortices (Factor 1) associate with norepinephrine and 5-HT2A density, decreases in the cingulo-opercular network and subcortex (Factor 2) associate with norepinephrine and 5-HTT density, and increases in social and affective brain systems (Factor 3) relate to 5-HTT density. Disease factor patterns can also be used to predict depressive symptom improvement in patients from the longitudinal cohort. Moreover, individual factor expressions in MDD are stable over time in a longitudinal cohort, with differentially expressed disease controls from a transdiagnostic cohort. Collectively, our data-driven disease factors reveal that patients with MDD organize along continuous dimensions that affect distinct sets of regions.

Date: 2025
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DOI: 10.1038/s41467-025-57682-0

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