Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis.
Major depressive disorder (MDD) is defined by an array of symptoms that make it challenging to understand the condition at a population level. Subtyping offers a way to unpick this phenotypic diversity for improved disorder characterisation. We aimed to identify depression subtypes longitudinally us...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0314604 |
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| author | Carolin Oetzmann Nicholas Cummins Femke Lamers Faith Matcham Sara Siddi Katie M White Josep Maria Haro Srinivasan Vairavan Brenda W J H Penninx Vaibhav A Narayan Matthew Hotopf Ewan Carr |
| author_facet | Carolin Oetzmann Nicholas Cummins Femke Lamers Faith Matcham Sara Siddi Katie M White Josep Maria Haro Srinivasan Vairavan Brenda W J H Penninx Vaibhav A Narayan Matthew Hotopf Ewan Carr |
| author_sort | Carolin Oetzmann |
| collection | DOAJ |
| description | Major depressive disorder (MDD) is defined by an array of symptoms that make it challenging to understand the condition at a population level. Subtyping offers a way to unpick this phenotypic diversity for improved disorder characterisation. We aimed to identify depression subtypes longitudinally using the Inventory of Depressive Symptomatology: Self-Report (IDS-SR). A secondary analysis of a two-year cohort study called Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD), which collected data every three months from patients with a history of recurrent MDD in the United Kingdom, the Netherlands, and Spain (N = 619). We used latent class and latent transition analysis to identify subtypes at baseline, determined their consistency at 6- and 12-month follow-ups, and examined transitions over time. We identified a 4-class solution: (1) severe with appetite decrease, (2) severe with appetite increase, (3) moderate severity and (4) low severity. These same classes were identified at 6- and 12-month follow-ups, and participants tended to remain in the same class over time. We found no statistically significant differences between the two severe subtypes regarding baseline clinical and sociodemographic characteristics. Our findings emphasize severity differences over symptom types, suggesting that current subtyping methods provide insights akin to existing severity measures. When examining transitions, participants were most likely to remain in their respective classes over 1-year, indicating chronicity rather than oscillations in depression severity. Future work recommendations are made. |
| format | Article |
| id | doaj-art-e11f0e4f771d4561af0acccdd4541d99 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-e11f0e4f771d4561af0acccdd4541d992025-02-05T05:31:27ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01201e031460410.1371/journal.pone.0314604Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis.Carolin OetzmannNicholas CumminsFemke LamersFaith MatchamSara SiddiKatie M WhiteJosep Maria HaroSrinivasan VairavanBrenda W J H PenninxVaibhav A NarayanMatthew HotopfEwan CarrMajor depressive disorder (MDD) is defined by an array of symptoms that make it challenging to understand the condition at a population level. Subtyping offers a way to unpick this phenotypic diversity for improved disorder characterisation. We aimed to identify depression subtypes longitudinally using the Inventory of Depressive Symptomatology: Self-Report (IDS-SR). A secondary analysis of a two-year cohort study called Remote Assessment of Disease and Relapse in Major Depressive Disorder (RADAR-MDD), which collected data every three months from patients with a history of recurrent MDD in the United Kingdom, the Netherlands, and Spain (N = 619). We used latent class and latent transition analysis to identify subtypes at baseline, determined their consistency at 6- and 12-month follow-ups, and examined transitions over time. We identified a 4-class solution: (1) severe with appetite decrease, (2) severe with appetite increase, (3) moderate severity and (4) low severity. These same classes were identified at 6- and 12-month follow-ups, and participants tended to remain in the same class over time. We found no statistically significant differences between the two severe subtypes regarding baseline clinical and sociodemographic characteristics. Our findings emphasize severity differences over symptom types, suggesting that current subtyping methods provide insights akin to existing severity measures. When examining transitions, participants were most likely to remain in their respective classes over 1-year, indicating chronicity rather than oscillations in depression severity. Future work recommendations are made.https://doi.org/10.1371/journal.pone.0314604 |
| spellingShingle | Carolin Oetzmann Nicholas Cummins Femke Lamers Faith Matcham Sara Siddi Katie M White Josep Maria Haro Srinivasan Vairavan Brenda W J H Penninx Vaibhav A Narayan Matthew Hotopf Ewan Carr Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis. PLoS ONE |
| title | Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis. |
| title_full | Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis. |
| title_fullStr | Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis. |
| title_full_unstemmed | Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis. |
| title_short | Identifying depression subtypes and investigating their consistency and transitions in a 1-year cohort analysis. |
| title_sort | identifying depression subtypes and investigating their consistency and transitions in a 1 year cohort analysis |
| url | https://doi.org/10.1371/journal.pone.0314604 |
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