Identifying and validating subtypes within major psychiatric disorders based on frontal-posterior functional imbalance via deep learning
Open accessAbstract
Converging evidence increasingly implicates shared etiologic and pathophysiological characteristics among major psychiatric disorders (MPDs), such as schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD). Examining the neurobiology of the psychotic-affective spectrum may greatly advance biological determination of psychiatric diagnosis, which is critical for the development of more effective treatments. In this study, ensemble clustering was developed to identify subtypes within a trans-diagnostic sample of MPDs. Whole brain amplitude of low-frequency fluctuations (ALFF) was used to extract the low-dimensional features for clustering in a total of 944 participants: 581 psychiatric patients (193 with SZ, 171 with BD, and 217 with MDD) and 363 healthy controls (HC). We identified two subtypes with differentiating patterns of functional imbalance between frontal and posterior brain regions, as compared to HC: (1) Archetypal MPDs (60% of MPDs) had increased frontal and decreased posterior ALFF, and decreased cortical thickness and white matter integrity in multiple brain regions that were associated with increased polygenic risk scores and enriched risk gene expression in brain tissues; (2) Atypical MPDs (40% of MPDs) had decreased frontal and increased posterior ALFF with no associated alterations in validity measures. Medicated Archetypal MPDs had lower symptom severity than their unmedicated counterparts; whereas medicated and unmedicated Atypical MPDs had no differences in symptom scores. Our findings suggest that frontal versus posterior functional imbalance as measured by ALFF is a novel putative trans-diagnostic biomarker differentiating subtypes of MPDs that could have implications for precision medicine.
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Medial prefrontal cortex showing heterogeneous FCS alterations in our study was found to have both increased and decreased FCS in previous case-control studies.
“For example, the medial prefrontal cortex showing heterogenous FCS alterations in our study was found to have both increased and decreased FCS in previous case-control studies [47, 51-53].”
From Mapping neurophysiological subtypes of major depressive disorder using normative models of the functional connectome (2023) · cites this paper as [47]
FCS alterations in these regions have been proven to be related to regulation of widespread cognitive, emotional, and executive control functions in MDD.
“The FCS alterations in these regions have been proven to be related to the regulation of widespread cognitive, emotional, and executive control functions in patients with MDD [6, 42-50].”
From Mapping neurophysiological subtypes of major depressive disorder using normative models of the functional connectome (2023) · cites this paper as [47]
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- Authors
- Chang, M., Womer, F. Y., Gong, X., Chen, X., Tang, L., Feng, R., Dong, S., Duan, J., Chen, Y., Zhang, R., Wang, Y., Ren, S., Wang, Y., Kang, J., Yin, Z., Wei, Y., Wei, S., Jiang, X., Xu, K., Cao, B., Zhang, Y., Zhang, W., Tang, Y., Zhang, X., & Wang, F.
- Affiliations
- First Hospital of China Medical University (CN)
- Washington University in St. Louis (US)
- Fudan University (CN)
- Northeastern University (CN)
- University of Alberta (CA)
- Royal University Hospital (CA)
- Nanjing Brain Hospital (CN)
- Corresponding author
- Tang, Yanqing
- Zhang, Xizhe
- Wang, Fei
- ORCID
- Venue
- Molecular Psychiatry
- Published
- 2020-10-01
- Volume
- 26
- Issue
- 7
- Pages
- 2991-3002
- ISSN
- 1359-4184 (ISSN-L)
- 1476-5578
- PMC
- PMC8505253
- OpenAlex
- W4210273173
- Cited by
- 92
- References
- 47
- Citations by year
- 2026: 16 · 2025: 17 · 2024: 19 · 2023: 22 · 2022: 15 · 2021: 3
- FWCI
- 5.37
- Type
- journal article
- Language
- en
- Update notices
- correction (2020-11-17)
- Open access
- hybrid
- doi.org
- Locations
- Molecular Psychiatry (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Digital Commons@Becker (Washington University School of Medicine) (submittedVersion, cc-by)
- Funders
- National Natural Science Foundation of China (81571311,, 2016YFC0906400, 81271499, 81571331, 81071099, 2015AA020513, 81725005, 2016YFC1306900)
- Natural Science Foundation of Liaoning Province (2016YFC1306900, 81725005)
- China Medical University (81725005, 2016YFC1306900)
- National Key Research and Development Program of China (2016YFC0904300, 81571331, 2015AA020513, 81571311, 81725005, 81071099, 2016YFC0906400, 2016YFC1306900, 81271499)
- National Science Fund for Distinguished Young Scholars (81725005)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Keywords
- severe mental illness, amplitude of low-frequency fluctuation, schizophrenia, bipolar disorder, major depressive disorder, consensus clustering, cortical thickness, white matter integrity, polygenic risk score, medication effects, symptom severity, precision medicine
- MeSH terms
- Deep Learning, Bipolar Disorder, Brain, Major Depressive Disorder, Humans, Magnetic Resonance Imaging
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