The Influence of Phenotyping Method on Neuroimaging Associations with Depression in UK Biobank

BackgroundDepression is assessed in many different ways, with large population studies often relying on minimal phenotyping approaches. Genetic results suggest that more formal clinical diagnoses and simpler self-report measures of depression show some core similarities, but also important differences. It is not yet clear whether this is also the case for neuroimaging measures. MethodsWe studied 39,300 UK Biobank imaging participants (20,701 female; aged 44.6 to 82.3 years, M = 64.1, SD = 7.5) with structural neuroimaging (T1 and DTI) and depression data. Depression phenotypes included a minmal single-item self-report measure, an intermediate symptom-based measure of probable depression, and a more clinically robust measure based on DSM-IV criteria. We tested i) associations between brain structural measures and each depression phenotype, and ii) the effects of depression phenotype on these associations. ResultsSmall depression-brain structure associations ({beta} < 0.1) were significant after FDR correction for many global and regional metrics for all three phenotypes. The most consistent imaging associations across depression phenotypes were for measures of white matter integrity. There were small but significant effects of phenotype definition primarily for cortical thickness, which showed stronger negative associations with Self-reported Depression than the symptom-based measures. ConclusionSimilar to previous genetic studies, we found some consistent associations indicating a core component of depression across phenotypes, and some additional associations that were phenotype-specific. Although these specific results did not relate to depth of phenotyping as expected, effects of phenotype definition are still an important consideration for future depression research.