| Title: | Comparing data-driven subtypes of depression informed by clinical and neuroimaging data: A Registered Report |
| Journal: | Biological Psychiatry Global Open Science |
| Published: | 1 Feb 2025 |
| DOI: | https://doi.org/10.1016/j.bpsgos.2025.100473 |
Publication 14452
WARNING: the interactive features of this website use CSS3, which your browser does not support. To use the full features of this website, please update your browser.
Abstract
Background Efforts to elucidate subtypes within depression have yet to establish a consensus. This study aims to rigorously compare different subtyping approaches in the same subject space, to quantitatively test agreement across subtyping approaches and determine if the different approaches are sensitive to different sources of heterogeneity in depression. Methods We implemented six different data-driven subtyping methods developed in prior work using the same UK Biobank participants (N=2,276 depressed, N=1,595 healthy controls). The six approaches include two symptom-based, two structural neuroimaging-based, and two functional neuroimaging-based techniques. The resulting subtypes were compared based on subject assignment, stability, and sensitivity to subtype differences in demographics, general health, clinical characteristics, neuroimaging, trauma, cognition, genetics, and inflammation markers. Results We found almost no agreement between the resulting subtypes of the six approaches (mean ARI=0.006), even within data domains. This finding was largely driven by differences in input feature set (mean ARI=0.005) rather than clustering algorithm (mean ARI=0.23). However, each approach had relatively high internal stability across bootstraps (ARI=0.36-0.89), most approaches performed above null, and most approaches were sensitive to relevant phenotypes within their data domain. Conclusions Despite marginal overlap between approaches, we found the subtyping approaches to be internally consistent. These results explain why previous studies found strong evidence for subtypes within their analysis but with very little convergence between studies. We recommend future work incorporates systematic comparisons between their approach and alternative/previous approaches to facilitate consensus on depression subtypes.</p>
7 Authors
- Kayla Hannon
- Setthanan Jarukasemkit
- Leda Balogh
- Fyzeen Ahmad
- Petra Lenzini
- Aristeidis Sotiras
- Janine D. Bijsterbosch
1 Application
| Application ID | Title |
|---|---|
| 47267 | Cross-diagnostic and cross-platform multimodal analysis of UK Biobank imaging data |
Enabling scientific discoveries that improve human health