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. 2025 Jun 24:55:e174.
doi: 10.1017/S0033291725100664.

Resolving heterogeneity in first-episode and drug-naive major depressive disorder based on individualized structural covariance network: evidence from the REST-meta-MDD consortium

Songhao Hu  1   2 , Li Zhu  1   2 , Xiangyang Zhang  1
Affiliations

Resolving heterogeneity in first-episode and drug-naive major depressive disorder based on individualized structural covariance network: evidence from the REST-meta-MDD consortium

Songhao Hu et al. Psychol Med. .

Abstract

Background: Major depressive disorder (MDD) is a complex and heterogeneous disorder, and this heterogeneity poses a significant challenge for advancing precision medicine in patients with MDD. MRI-based subtyping analysis has been widely employed to address the heterogeneity of MDD patients. In this study, we investigated the subtypes of first-episode and drug-naive (FEDN) MDD patients based on the individualized structural covariance network (IDSCN).

Methods: In this study, we used T1-weighted anatomical images of 164 FEDN MDD patients and 164 healthy controls from the REST-meta-MDD consortium. The IDSCN of participants was obtained using the network template perturbation method. Subtypes of FEDN MDD were identified using k-means clustering analysis, and differences in neuroimaging findings and clinical symptoms between the identified subtypes were compared using two-sample t-tests.

Results: This study identified two subtypes of FEDN MDD: subtype 1 (n = 117) and subtype 2 (n = 47) by characterizing 10 edges that were significantly altered in at least 5% of patients (i.e., 8 patients) in the IDSCN. Compared with subtype 2, subtype 1 had significantly higher anxiety symptom scores, stronger structural covariance edges in 9 edges within the thalamus, and a significantly reduced gray matter volume (GMV) in the frontal and parietal regions, and in the thalamus.

Conclusions: Our results suggest that patients with FEDN MDD can be classified into two different subtypes based on their IDSCN, providing an important reference for personalized treatment and precision medicine for patients with FEDN MDD.

Keywords: heterogeneity; major depressive disorder; structural covariance network.

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Conflict of interest statement

The authors all declare no conflict of interest.

Figures

Figure 1.
Figure 1.
Flowchart of IDSCN construction. IDSCN, individualized structural covariance network; rSCN, reference SCN; pSCN, perturbed SCN.
Figure 2.
Figure 2.
(A) Structural covariance edges significantly stronger in subtype 1 than in subtype 2; (B) Differences in symptom scale scores between the two subtypes; (C) Differences in Z-scores of structural covariate edges between the two subtypes. Thal_AV_L = Thalamus, Anteroventral, Left;Thal_VPL_R = Thalamus, Ventral posterolateral, Right; Thal_MDm_L = Thalamus, Mediodorsal medial magnocellular, Left;Thal_IL_R = Thalamus, Intralaminar, Right; Thal_MDl_L = Thalamus, Mediodorsal lateral parvocellular, Left;Thal_LGN_L = Thalamus, Lateral geniculate, Left;Thal_MGN_R = Thalamus, Medial Geniculate, Right;Thal_MGN_L = Thalamus, Medial Geniculate, Left;Thal_PuA_L = Thalamus, Pulvinar anterior, Left;Thal_PuA_R = Thalamus, Pulvinar anterior,Right;Thal_PuL_L = Thalamus, Pulvinar lateral, Left;Thal_PuL_R = Thalamus,Pulvinar lateral, Right;Thal_PuI_L = Thalamus, Pulvinar inferior, Left.
Figure 3.
Figure 3.
Scatterplot of the correlation between Z-scores of structural covariance edges and HAMA scores. Thal_AV_L = Thalamus, Anteroventral, Left; Thal_VPL_R = Thalamus, Ventral posterolateral, Right;Thal_MGN_R = Thalamus, Medial Geniculate, Right;Thal_MGN_L = Thalamus, Medial Geniculate, Left;Thal_PuI_L = Thalamus, Pulvinar inferior, Left.
Figure 4.
Figure 4.
Brain regions with significantly higher GMV in subtype 2 than GMV in subtype 1. The color bars indicate the t-value (FWE correction, cluster-p < 0.05, voxel-p < 0.001).
Figure 5.
Figure 5.
Summary of FEDN MDD subtypes.
See this image and copyright information in PMC

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