Cited by 129Functional Brain Connectivity StudiesTreatment of Major DepressionMental Health Research Topics

The DOI matches its Crossref record; 89 of the 89 references it cites were found in a registry or an index; none of the 46 sources its claims cite is checked for support yet.

Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome

Open access
Sun, Xiaoyi, Sun, Jinrong, Lu, Xiaowen, Dong, Qiangli, Zhang, Liang, Wang, Wenxu, Liu, Jin, Ma, Qing, Wang, Xiaoqin, Wei, Dongtao, Chen, Yuan, Liu, Bangshan, Huang, Chu-Chung, Zheng, Yanting, Wu, Yankun, Chen, Taolin, Cheng, Yuqi, Xu, Xiufeng, Gong, Qiyong, Si, Tianmei, Qiu, Shijun, Lin, Ching-Po, Cheng, Jingliang, Tang, Yanqing, Wang, Fei, Qiu, Jiang, Xie, Peng, Li, Lingjiang, He, Yong, He, Yong, Li, Lingjiang, Cheng, Jingliang, Gong, Qiyong, Lin, Ching-Po, Qiu, Jiang, Qiu, Shijun, Si, Tianmei, Tang, Yanqing, Wang, Fei, Xie, Peng, Xu, Xiufeng, Xia, Mingrui, Xia, Mingrui·2023·Biological Psychiatry

Published version of a preprint

Abstract

Background Major depressive disorder (MDD) is a highly heterogeneous disorder that typically emerges in adolescence and can occur throughout adulthood. Studies aimed at quantitatively uncovering the heterogeneity of individual functional connectome abnormalities in MDD and identifying reproducibly distinct neurophysiological MDD subtypes across the lifespan, which could provide promising insights for precise diagnosis and treatment prediction, are still lacking.Methods Leveraging resting-state functional magnetic resonance imaging data from 1148 patients with MDD and 1079 healthy control participants (ages 11-93), we conducted the largest multisite analysis to date for neurophysiological MDD subtyping. First, we characterized typical lifespan trajectories of functional connectivity strength based on the normative model and quantitatively mapped the heterogeneous individual deviations among patients with MDD. Then, we identified neurobiological MDD subtypes using an unsupervised clustering algorithm and evaluated intersite reproducibility. Finally, we validated the subtype differences in baseline clinical variables and longitudinal treatment predictive capacity.Results Our findings indicated great intersubject heterogeneity in the spatial distribution and severity of functional connectome deviations among patients with MDD, which inspired the identification of 2 reproducible neurophysiological subtypes. Subtype 1 showed severe deviations, with positive deviations in the default mode, limbic, and subcortical areas and negative deviations in the sensorimotor and attention areas. Subtype 2 showed a moderate but converse deviation pattern. More importantly, subtype differences were observed in depressive item scores and the predictive ability of baseline deviations for antidepressant treatment outcomes.Conclusions These findings shed light on our understanding of different neurobiological mechanisms underlying the clinical heterogeneity of MDD and are essential for developing personalized treatments for this disorder.

Overview

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TL;DR

Using multisite resting-state fMRI from 1,148 MDD patients and 1,079 healthy controls, this study built normative models of functional connectivity strength and mapped individual deviations to identify neurophysiological MDD subtypes. Two subtypes emerged: a severe-deviation subtype with positive deviations in default mode, limbic, and subcortical areas and a moderate, largely converse subtype, with clinical differences and treatment-response prediction in the severe subtype.

Key findings

  • MDD patients showed larger individual FCS deviation indexes than HCs: number of extremely deviated regions (t=4.22), sum of positive extreme deviations (t=4.11), and sum of negative extreme deviations (t=-2.77; p<0.05, FDR corrected). 72.82% (N=836) of patients had an extreme FCS deviation in at least one region; extreme positive deviations in 25.78% (N=296) and extreme negative deviations in 66.38% (N=762). For any single brain region, extreme deviations were low: ≤2.35% positive (N=27) and ≤3.14% negative (N=36).
  • Two MDD subtypes were identified. Subtype 1 (37%, N=425) showed severe deviations with positive deviations in DMN, LIM, and SUB areas and negative deviations in SMN, DAN, and VAN areas. Subtype 2 (63%, N=723) showed moderate but converse deviations: negative in DMN, LIM, and SUB and positive in SMN, DAN, and VAN. Subtype 1 had significantly higher deviation indexes than HCs and subtype 2; subtype 2 had lower number of extremely deviated regions and sum of negative extreme deviations than HCs.
  • The severe-deviation subtype was older (t=2.64, p=0.008), had higher medicated proportion (χ²=6.11, p=0.013), and higher Suicide item score (t=2.02, p=0.044). The moderate-deviation subtype had higher Work and Activities (t=3.11, p=0.002) and Depressed Mood (t=2.42, p=0.016) item scores. HDRS-17 score correlated negatively with onset age in the severe subtype (r=-0.24, p=0.004) but not the moderate subtype (r=-0.00, p=0.966; subtype difference F=4.41, p=0.037).
  • In a 43-patient treatment subsample (16 severe, 27 moderate), baseline deviation maps predicted 6-month HDRS changes in the severe subtype (r=0.47, p=0.019, one-tailed permutation test) but not the moderate subtype (r=-0.14, p=0.785). Most positively contributive features were in DMN (24.1%), FPN (16.1%), and VAN (15.6%); most negatively contributive were in VIS (40.5%).

Methods

  • Multisite resting-state fMRI data from the DIDA-MDD working group: initially 2,414 participants (1,276 MDD, 1,138 HCs); final sample after quality control was 1,148 MDD patients (aged 11–93) and 1,079 HCs (aged 13–81). A subsample of 43 patients received 6-month paroxetine treatment.
  • Functional connectivity strength (FCS) was computed for 220 cerebral regions using a predefined parcellation; Pearson correlations were thresholded at r=0.2, Fisher r-to-z transformed, summed per region, z-normalized, and ComBat-harmonized for site effects. Normative models of FCS as a function of age and gender were estimated in HCs using Gaussian process regression with 10-fold cross-validation; individual deviations were expressed as Z values, with extreme deviations thresholded at Z=±2.6 (p<0.005).
  • K-means clustering was applied to individual deviation maps, with cluster number 2–10 assessed by 22 effective indexes via NbClust. Subtype differences in deviation patterns and demographic/clinical variables were tested; support vector regression with embedded 5-fold cross-validation and permutation tests examined prediction of treatment response. Validation included leave-one-site-out and alternative thresholds.

Limitations

  • Stated by the authors: the analysis is cross-sectional, so age-related trajectories are population-level rather than individual trajectories; longitudinal samples are needed. Clinical characterization used HDRS-17 item scores, and cognitive impairments were not collected. Treatment prediction included only paroxetine responders, so nonresponders are needed to model treatment-resistant depression. Subtypes were based on FCS alteration patterns, and future work should incorporate genetic and environmental information.
  • Evident from the text: the treatment-response prediction subsample was very small (43 patients; 16 severe, 27 moderate), limiting generalizability. The normative models and subtype solutions depend on analytic choices such as correlation threshold and extreme-deviation threshold, although the authors report validation across several alternatives.

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Crossref · 10.1016/j.biopsych.2023.05.021

Cites

89 of 89 references verified0 citation errors · 0 not checkable

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Show all 36 claims

  • It may state two separate claims as one. 34
  • Probably not a substantial claim. 14
44 of 44
  • The paper relies on this without support.

    The normative model of FCS built from healthy controls provides a valid reference for estimating disease-related deviations in MDD patients.

    “For each patient with MDD, the FCS of the brain regions were positioned on the normative percentile charts from HCs to estimate individual deviation (Fig. 1b).”
  • The paper relies on this without support.

    The DIDA-MDD sample of 1,148 MDD patients and 1,079 HCs is representative of the broader MDD and healthy populations, so findings generalize.

    “we conducted a comprehensive investigation into the neurobiological heterogeneity and subtypes of MDD using a large multisite r-fMRI dataset of 1,148 patients with MDD and 1,079 matched healthy controls (HCs).”
  • The paper relies on this without support.

    The 43-patient subsample receiving 6-month paroxetine treatment is representative of MDD patients' antidepressant treatment response.

    “Additionally, a subsample of 43 patients (Supplementary Table 1) received a 6-month treatment with paroxetine (an antidepressant of selective serotonin reuptake inhibitor, SSRI), and the treatment outcomes were recorded (Supplement).”
  • The paper relies on this without support.

    The areas of the DMN are related to self-referential processing.

    “The areas of the DMN are related to self-referential processing.”
  • The paper relies on this without support.

    Previous studies have found different alteration patterns between patients in different age stages.

    “Previous studies have found different alteration patterns between patients in different age stages.”
  • The paper relies on this without support.

    Patients with MDD have varied cognitive impairments.

    “The patients with MDD also had varied cognitive impairments, which were not collected in the current retrospective study.”
6 of 6

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Metadata

Authors
Sun, X., Sun, J., Lu, X., Dong, Q., Zhang, L., Wang, W., Liu, J., Ma, Q., Wang, X., Wei, D., Chen, Y., Liu, B., Huang, C.-C., Zheng, Y., Wu, Y., Chen, T., Cheng, Y., Xu, X., Gong, Q., Si, T., Qiu, S., Lin, C.-P., Cheng, J., Tang, Y., Wang, F., Qiu, J., Xie, P., Li, L., He, Y., He, Y., Li, L., Cheng, J., Gong, Q., Lin, C.-P., Qiu, J., Qiu, S., Si, T., Tang, Y., Wang, F., Xie, P., Xu, X., Xia, M., & Xia, M.
Affiliations
  • Beijing Normal University (CN)
  • Central South University (CN)
  • Shanghai Medical College of Fudan University (CN)
  • Southwest University (CN)
  • First Affiliated Hospital of Zhengzhou University (CN)
  • East China Normal University (CN)
  • First Affiliated Hospital of Guangzhou University of Chinese Medicine (CN)
  • Peking University (CN)
  • Sichuan University (CN)
  • First Affiliated Hospital of Kunming Medical University (CN)
Venue
Biological Psychiatry
Publisher
Elsevier BV
Published
2023-12
Volume
94
Issue
12
Pages
936-947
ISSN
0006-3223 (ISSN-L)
OpenAlex
W4379741254
Cited by
129
References
88
Citations by year
2026: 54 · 2025: 53 · 2024: 20 · 2023: 2
FWCI
19.27
Type
journal article
Language
en
Open access
Locations
  • Biological Psychiatry (publishedVersion)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
  • PubMed (publishedVersion)
Funders
  • Science and Technology Planning Project of Fuzhou (2018-1002-SF-0442)
  • National Natural Science Foundation of China (81471251, 81771344, 81920108019, 82021004, 82071998, 91649117)
  • Beijing Nova Program (Z191100001119023)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
  • Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
  • Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
Keywords
major depressive disorder, functional connectome, resting-state functional connectivity, normative model, lifespan trajectories, default mode network, limbic system, antidepressant response, treatment prediction, personalized treatment, clinical heterogeneity
MeSH terms
Adolescent, Adult, Brain, Brain Mapping, Major Depressive Disorder, Humans, Magnetic Resonance Imaging, Reproducibility of Results, Connectome

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