Cited by 240Treatment of Major DepressionAnxiety, Depression, Psychometrics, Treatment, Cognitive ProcessesFunctional Brain Connectivity Studies

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Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping

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Beijers, Lian, Wardenaar, Klaas J., van Loo, Hanna M., Schoevers, Robert A.·2019·Molecular Psychiatry

DOI 10.1038/s41380-019-0385-5

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Abstract

Research into major depressive disorder (MDD) is complicated by population heterogeneity, which has motivated the search for more homogeneous subtypes through data-driven computational methods to identify patterns in data. In addition, data on biological differences could play an important role in identifying clinically useful subtypes. This systematic review aimed to summarize evidence for biological subtypes of MDD from data-driven studies. We undertook a systematic literature search of PubMed, PsycINFO, and Embase (December 2018). We included studies that identified (1) data-driven subtypes of MDD based on biological variables, or (2) data-driven subtypes based on clinical features (e.g., symptom patterns) and validated these with biological variables post-hoc. Twenty-nine publications including 24 separate analyses in 20 unique samples were identified, including a total of ~ 4000 subjects. Five out of six biochemical studies indicated that there might be depression subtypes with and without disturbed neurotransmitter levels, and one indicated there might be an inflammatory subtype. Seven symptom-based studies identified subtypes, which were mainly determined by severity and by weight gain vs. loss. Two studies compared subtypes based on medication response. These symptom-based subtypes were associated with differences in biomarker profiles and functional connectivity, but results have not sufficiently been replicated. Four out of five neuroimaging studies found evidence for groups with structural and connectivity differences, but results were inconsistent. The single genetic study found a subtype with a distinct pattern of SNPs, but this subtype has not been replicated in an independent test sample. One study combining all aforementioned types of data discovered a subtypes with different levels of functional connectivity, childhood abuse, and treatment response, but the sample size was small. Although the reviewed work provides many leads for future research, the methodological differences across studies and lack of replication preclude definitive conclusions about the existence of clinically useful and generalizable biological subtypes.

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Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & for the PRISMA Group (2009) · BMJ · doi:10.1136/bmj.b2535 · Cited by 83,823
Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement
Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000097 · Cited by 64,042
Preferred reporting items for systematic reviews and meta-analyses: the PRISMA Statement.
(2009) · PubMed Central · Cited by 44,859
Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement
PRISMA-P Group, Moher, D., Shamseer, L., Clarke, M., Ghersi, D., Liberati, A., Petticrew, M., Shekelle, P., & Stewart, L. A. (2015) · Systematic Reviews · doi:10.1186/2046-4053-4-1 · Cited by 26,223
Research domain criteria (RDoC): toward a new classification framework for research on mental disorders
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., Sanislow, C., & Wang, P. (2010) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2010.09091379 · Cited by 7,067
Estimating the Number of Clusters in a Data Set Via the Gap Statistic
Tibshirani, R., Walther, G., & Hastie, T. (2001) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00293 · Cited by 6,205
Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010
Whiteford, H. A., Degenhardt, L., Rehm, J., Baxter, A. J., Ferrari, A. J., Erskine, H. E., Charlson, F. J., Norman, R. E., Flaxman, A. D., Johns, N., et al. (2013) · The Lancet · doi:10.1016/s0140-6736(13)61611-6 · Cited by 6,006
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Frayling, T. M., Timpson, N. J., Weedon, M. N., Zeggini, E., Freathy, R. M., Lindgren, C. M., Perry, J. R. B., Elliott, K. S., Lango, H., Rayner, N. W., et al. (2007) · Science · doi:10.1126/science.1141634 · Cited by 4,531
The molecular neurobiology of depression
Krishnan, V., & Nestler, E. J. (2008) · Nature · doi:10.1038/nature07455 · Cited by 2,889
The Preventable Causes of Death in the United States: Comparative Risk Assessment of Dietary, Lifestyle, and Metabolic Risk Factors
Danaei, G., Ding, E. L., Mozaffarian, D., Taylor, B., Rehm, J., Murray, C. J. L., & Ezzati, M. (2009) · PLoS Medicine · doi:10.1371/journal.pmed.1000058 · Cited by 2,860

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Authors: Beijers, L., Wardenaar, K. J., van Loo, H. M., & Schoevers, R. A.
Affiliations: University Medical Center Groningen (NL)
Corresponding author: Beijers, Lian
ORCID: Beijers, Lian
Wardenaar, Klaas J.
Schoevers, Robert A.
Venue: Molecular Psychiatry
Publisher: Springer Science and Business Media LLC
Published: 2019-03-01
Volume: 24
Issue: 6
Pages: 888-900
ISSN: 1359-4184 (ISSN-L)
1476-5578
DOI: 10.1038/s41380-019-0385-5
OpenAlex: W2919937325
Cited by: 240
References: 99
Citations by year: 2026: 29 · 2025: 48 · 2024: 34 · 2023: 36 · 2022: 32 · 2021: 22 · 2020: 31 · 2019: 7
FWCI: 2.95
Type: journal article
Language: en
Open access: green
hdl.handle.net
Licence: other-oa
www.springer.com/tdm (tdm)
Locations: Molecular Psychiatry (publishedVersion)
PubMed (publishedVersion)
University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
Topics: Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
Social Sciences › Psychology › Experimental and Cognitive Psychology › Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Keywords: major depressive disorder, depression subtypes, biological heterogeneity, neurotransmitter levels, inflammatory depression, biomarker profiles, functional connectivity, neuroimaging, genetic subtypes, childhood abuse, treatment response, weight gain and loss
MeSH terms: Adult, Depression, Major Depressive Disorder, Female, Humans, Male, Middle Aged, Psychometrics, Genetic Association Studies, Neuroimaging

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Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping

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