Sep 2026· Psychiatry and Clinical Neurosciences· 0 citations· 86 references
Medicine
TL;DR
This study provides a data-driven characterization of cognitive heterogeneity in MDD, identifying two cognitive dimensions spanning from relative preservation to widespread impairment, and provides preliminary biological context for interpreting cognitive heterogeneity in MDD.
Abstract
Background
Major depressive disorder (MDD) is often accompanied by cognitive impairment; however, the cognitive heterogeneity of MDD and its neurobiological context remain poorly understood.
Methods
A total of 198 participants with MDD and 275 HCs underwent multi-domain cognitive assessments and multi-modal MRI acquisition. A semi-supervised approach was applied to identify cognitive dimensions of MDD, and individual-level structural-enriched functional networks (SFNs) were constructed. Network-based statistics were applied to characterize network-level associations between structural-functional coupling deviation and cognitive dimensions. Furthermore, the correlations between the spatial pattern of SFN deviation and meta-analytic neurocognitive terms, cortical transcriptome, and neurotransmitter density distribution maps were detected.
Results
In the MDD group, 103 individuals were assigned to Cluster 1, presenting widespread cognitive impairments, whereas 95 were assigned to Cluster 2, presenting cognitive preservations. An abnormally enhanced SFN subnetwork (PPerm = 0.042) was identified, which showed significant spatial correlation with meta-analytic neurocognitive maps (r = 0.181, P < 0.001). The SFN deviation pattern was spatially associated with 2458 genes enriched primarily in neuronal and synaptic function, and these genes also showed enrichment for pathways annotated to neurodegenerative diseases (PFDR < 0.05). In addition, SFN deviation was spatially associated with three neurotransmitter maps, including N-methyl-D-aspartate receptor, cannabinoid type-1 receptor, and norepinephrine transporter (PFDR = 0.028).
Conclusions
The study provides a data-driven characterization of cognitive heterogeneity in MDD, identifying two cognitive dimensions spanning from relative preservation to widespread impairment. By integrating structural-functional coupling deviations with transcriptomic and neurotransmitter maps, these findings provide preliminary biological context for interpreting cognitive heterogeneity in MDD.
These findings identify distinct cortical morphometric organization in BDD and MDD, and these differences are linked to transcriptomic, cellular, and neurotransmitter-related annotations, providing multiscale insights into the neurobiological divergence between the two disorders.
Guang-Wei Sun, Tai-Peng Sun, Yu-Cheng Yuan et al.· Psychiatry and Clinical Neur...· 0 citations
Major depressive disorder (MDD) exhibits substantial clinical and neurobiological heterogeneity, along with marked variability in treatment response, underscoring the need for objective neuroimaging markers to inform personalized interventions.
Twenty-two patients with MDD and twenty-one age- and sex-mat...
Results indicate that multi-omics integration, in addition to explaining the molecular architecture of MDD, also characterizes patient subgroups with pathophysiological mechanisms, dimensions of symptoms, and disease treatment, which demonstrates that there is a shift in psychiatry toward a more mechanistic approach.
Elham Amjad, B. Sokouti· OBM Neurobiology· 0 citations
Abstract Background Major Depressive Disorder (MDD) is characterized by substantial heterogeneity in both symptomatic presentation and underlying neurobiology, posing significant challenges for accurate diagnosis and effective intervention. While prior research has attempted to delineate MDD subtypes using only neuroim...
Z. Chen, Q. Bo, C. Wang· International Journal of Neu...· 0 citations
Background/Objective Major depressive disorder (MDD) exhibits significant heterogeneity, and identifying these distinct biological subtypes aids clinical intervention. In this study, we employed functional gradient and Hydra clustering methods to distinguish subtypes of depression. Method Imaging data were derived from...
Xiao-Zheng Liu, Zhong-Wei Guo· Depression and Anxiety· 0 citations
Introduction Major depressive disorder (MDD) is a highly prevalent and disabling psychiatric disorder. Human neuroimaging studies increasingly frame its neurobiological substrate in terms of alterations of large-scale brain network organization. Resting-state fMRI findings broadly align with this view, yet remaining hi...
Javier F. Castilla-Jiménez, Juan Carlos Díaz-Patiño, S. Enriquez-Geppert et al.· bioRxiv· 0 citations
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