2019
DOI: 10.1038/s41380-019-0385-5
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Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping

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… Show more

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Cited by 172 publications
(124 citation statements)
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“…It is still not clear which factors associated with ELS are the most detrimental for later life outcomes or exactly how these events can have such long-lasting effects on brain functions. Furthermore, it has been proposed that depression, subsequent to ELS, comprises a subset of patients with unique etiopathology who would benefit from different treatment or preventative medicine as compared with other patients [28,29]. Further understanding of the molecular neurobiology associated with ELS will bring us closer to identifying vulnerable populations and developing effective treatments.…”
Section: Introductionmentioning
confidence: 99%
“…It is still not clear which factors associated with ELS are the most detrimental for later life outcomes or exactly how these events can have such long-lasting effects on brain functions. Furthermore, it has been proposed that depression, subsequent to ELS, comprises a subset of patients with unique etiopathology who would benefit from different treatment or preventative medicine as compared with other patients [28,29]. Further understanding of the molecular neurobiology associated with ELS will bring us closer to identifying vulnerable populations and developing effective treatments.…”
Section: Introductionmentioning
confidence: 99%
“…Clinical heterogeneity may also reflect different underlying biological and causal pathways. Increasing evidence suggests that depressive symptoms and subtypes are differentially associated with genetic risk factors that overlap with other disorders (Beijers, Wardenaar, van Loo, & Schoevers, 2019;Thorp et al, 2019;Milaneschi et al, 2016;Milaneschi et al, 2017a). Investigating the clinical and genetic correlates of more homogenous subtypes may improve the understanding of specific aetiological mechanisms and the development of potential treatment targets.…”
Section: Introductionmentioning
confidence: 99%
“…40 Few studies have also investigated the identification of depression subphenotypes using multimodal data. 41,42 For example, Dry- our study cohort of more than 20 000 subjects (cases and controls) to detect depression subphenotypes is one of the largest to date. And finally, we demonstrate the applicability of off-the-shelf machine learning algorithms for subphenotyping which provides a more interpretable and generalizable framework for implementing our approach in external datasets for future replication studies.…”
Section: Association Of Medications With the Depression Subphenotypesmentioning
confidence: 99%