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There is increasing interest in using data-driven unsupervised methods to identify structural underpinnings of common mental illnesses, including major depressive disorder (MDD) and associated traits such as cognition. However, studies are often limited to severe clinical cases with small sample sizes and most do not include replication. Here, we examine two relatively large samples with structural magnetic resonance imaging (MRI), measures of lifetime MDD and cognitive variables: Generation Scotland (GS subsample, N = 980) and UK Biobank (UKB, N = 8,900), for discovery and replication, using an exploratory approach. Regional measures of FreeSurfer derived cortical thickness (CT), cortical surface area (CSA), cortical volume (CV) and subcortical volume (subCV) were input into a clustering process, controlling for common covariates. The main analysis steps involved constructing participant K-nearest neighbour graphs and graph partitioning with Markov stability to determine optimal clustering of participants. Resultant clusters were (1) checked whether they were replicated in an independent cohort and (2) tested for associations with depression status and cognitive measures. Participants separated into two clusters based on structural brain measurements in GS subsample, with large Cohen's d effect sizes between clusters in higher order cortical regions, commonly associated with executive function and decision making. Clustering was replicated in the UKB sample, with high correlations of cluster effect sizes for CT, CSA, CV and subCV between cohorts across regions. The identified clusters were not significantly different with respect to MDD case–control status in either cohort (GS subsample: p FDR =.2239–.6585; UKB: p FDR =.2003–.7690). Significant differences in general cognitive ability were, however, found between the clusters for both datasets, for CSA, CV and subCV (GS subsample: d = 0.2529–.3490, p FDR <.005; UKB: d = 0.0868–0.1070, p FDR <.005). Our results suggest that there are replicable natural groupings of participants based on cortical and subcortical brain measures, which may be related to differences in cognitive performance, but not to the MDD case–control status.
- Major Depressive Disorder
- Machine Learning
- Markov Stability
- Structural Neuroimaging
- structural neuroimaging
- major depressive disorder
- machine learning
- Markov stability
FingerprintDive into the research topics of 'Spectral Clustering Based on Structural Magnetic Resonance Imaging and its Relationship with Major Depressive Disorder and Cognitive Ability'. Together they form a unique fingerprint.
- 6 Article
Cohort profile for the STratifying Resilience and Depression Longitudinally (STRADL) study: A depression-focused investigation of Generation Scotland, using detailed clinical, cognitive, and neuroimaging assessmentsHabota, T., Sandu, A-L., Waiter, G. D., McNeil, C. J., Steele, D., MacFarlane, J. A., Whalley, H. C., Valentine, R., Younie, D., Crouch, N., Hawkins, E. L., Hirose, Y., Romaniuk, L., Milburn, K., Buchan, G., Coupar, T., Stirling, M., Jagpal, B., McLennan, B., Priba, L. & 20 others, , 16 Jul 2021, In: Wellcome Open Research. 4, 14 p., 185.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile39 Downloads (Pure)
Backhouse, E. V., Shenkin, S. D. ., McIntosh, A. M., Bastin, M. E., Whalley, H. C., Valdes Hernandez, M., Muñoz Maniega, S., Harris, M., Stolicyn, A., Campbell, A., Steele, D., Waiter, G. D., Sandu, A-L., Waymont, J. M. J., Murray, A. D., Cox, S. R., de Rooij, S. R., Roseboom, T. J. & Wardlaw, J. M., 28 Sep 2021, (E-pub ahead of print) In: Brain.
Research output: Contribution to journal › Article › peer-reviewOpen Access
Structural brain correlates of serum and epigenetic markers of inflammation in major depressive disorderGreen, C., Shen, X., Stevenson, A., Conole, E. L. S., Harris, M. A., Barbu, M. C., Hawkins, E. L., Adams, M. J., Hillary, R. F., Lawrie, S. M., Evans, K. L., Walker, R. M., Morris, S. W., Porteous, D. J., Wardlaw, J. M., Steele, J. D., Waiter, G. D., Sandu, A-L., Campbell, A., Marioni, R. E. & 4 others, , Feb 2021, In: Brain, Behavior, and Immunity. 92, p. 39-48 10 p.
Research output: Contribution to journal › Article › peer-reviewOpen AccessFile