White matter microstructure and its relation to longitudinal measures of depressive symptoms in mid-late life

Abstract

BackgroundStudies of white matter microstructure in depression typically show alterations in depressed individuals, but they are frequently limited by small sample sizes and the absence of longitudinal measures of depressive symptoms. Depressive symptoms are however dynamic, and understanding the neurobiology of different trajectories could have important clinical implications.\n\nMethodsWe examined associations between current and longitudinal measures of depressive symptoms and white matter microstructure (Fractional Anisotropy, FA; Mean Diffusivity; MD) in the UK Biobank Imaging study. Depressive symptoms were assessed on 2-4 occasions over 5.9 to 10.7 years (on N=18,959 individuals on at least two occasions, N=4,444 on four occasions) from which we derived four measures of depressive symptomatology; (i) cross-sectional measure at the time of scan (imaging was conducted at a single time point), and three longitudinal measures, (ii) trajectory (iii) mean and (iv) intra-subject variance over time.\n\nResultsDecreased white matter microstructure in the anterior thalamic radiation demonstrated significant associations across all four measures of depressive symptoms (for MD: {beta}=0.020 to 0.029, pcorr<0.030). The greatest effect sizes were however seen between decreasing white matter integrity and increasing longitudinal progression of symptoms (for MD: {beta}=0.030 to 0.040, pcorr<0.049). Cross-sectional symptom severity was particularly associated with decreased white matter integrity in association fibres and thalamic radiations (MD: {beta}=0.015 to 0.039, pcorr<0.041). While greater mean and within subject variance of depressive symptoms were mainly associated with decreased white matter microstructure within projection fibres (MD: {beta}=0.019 to 0.029, pcorr<0.044).\n\nConclusionsThese findings indicate shared and differential neurobiological associations with severity, course and intra-subject variability of depressive symptoms. This enriches our understanding of the neurobiology underlying dynamic features of the disorder.