| Title: | Unravelling depression heterogeneity: Exploring the role of external risk factors in symptom network dynamics |
| Journal: | Journal of Affective Disorders |
| Published: | 23 Aug 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/40850553/ |
| DOI: | https://doi.org/10.1016/j.jad.2025.120112 |
Publication 16064
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Abstract
BACKGROUND: Network studies have provided insights into the onset and course of major depressive disorder (MDD) by investigating the role of specific symptoms and the interactions between them. However, the heterogeneity of MDD is influenced by external risk factors beyond the direct interactions between symptoms that are modelled in depressive symptom networks.</p>
METHODS: This study examined how variability in key risk factors influences the interactions between depressive symptoms, using a large sample from the UK Biobank (N = 115,609, all of White British ancestry). Specifically, we investigated how risk factors (including comorbid anxiety, childhood trauma exposure, genetic liability for depression, and sex) are conditionally associated with specific symptoms and their influence on the structure and connectivity of symptom networks.</p>
RESULTS: The findings revealed that the external risk factors influenced the structure of the symptom network and increased network connectivity. The pattern of relationships with depressive symptoms was heterogeneous across risk factors. Notably, comorbid anxiety emerged as the key risk factor, directly associating with all depressive symptoms and significantly shaping the network structure. Across all networks constructed in this study, anhedonia and depressed mood consistently emerged as the most central symptoms.</p>
CONCLUSIONS: This study suggests that the differential association and influence of external risk factors contribute to the considerable clinical heterogeneity of MDD. Comorbid anxiety poses the strongest influence on depressive symptoms and their network characteristics. Anhedonia and depressed mood play critical roles in activating depressive symptomatology and serve as potential effective intervention targets.</p>
3 Authors
- Tingyan Yang
- Eske M Derks
- Jackson G Thorp
1 Application
| Application ID | Title |
|---|---|
| 25331 | Gene mapping and genetic correlation across complex traits |
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