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

Beijers, Lian; Wardenaar, Klaas J.; van Loo, Hanna M.; Schoevers, Robert A.

doi:10.1038/s41380-019-0385-5

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

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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Dissecting diagnostic heterogeneity in depression by integrating neuroimaging and genetics
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Depression and Anxiety in the Epilepsies: from Bench to Bedside
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Scoping Review on the Multimodal Classification of Depression and Experimental Study on Existing Multimodal Models
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A Review and a Framework of Variables for Defining and Characterizing Tinnitus Subphenotypes
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Discrete prefrontal neuronal circuits determine repeated stress-induced behavioral phenotypes in male mice
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A scoping review of electroencephalographic (EEG) markers for tracking neurophysiological changes and predicting outcomes in substance use disorder treatment
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Sex and Age Influence the Associated Risk of Depression in Patients with Psoriasis: A Retrospective Population Study Based on Diagnosis and Drug-Use
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Biomarkers of central and peripheral inflammation mediate the association between HIV and depressive symptoms
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Two distinct subtypes of obsessive compulsive disorder revealed by a framework integrating multimodal neuroimaging information
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Depression is a risk factor for metabolic syndrome: Results from the ELSA-Brasil cohort study
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Individual Deviations from Normative Electroencephalographic Connectivity Predict Antidepressant Response
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Identification of 14-3-3 epsilon as a regulator of the neural apoptotic pathway for chronic-stress-induced depression
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Individualized resting-state functional connectivity abnormalities unveil two major depressive disorder subtypes with contrasting abnormal patterns of abnormality
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Symptom Patterns of the Occurrence of Depression and Anxiety in a Japanese General Adult Population Sample: A Latent Class Analysis
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Treatment-resistant depression: role of genetic factors in the perspective of clinical stratification and treatment personalisation
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Identifying Subgroups of Major Depressive Disorder Using Brain Structural Covariance Networks and Mapping of Associated Clinical and Cognitive Variables
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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 · 2018: 1
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 › 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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