White matter integrity and late-life depression in community-dwelling individuals: diffusion tensor imaging study using tract-based spatial statistics.
cross_sectional · Level IV
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- Record sourced from PubMed, PMID 25147370.
- Also identified by DOI 10.1192/bjp.bp.113.142109.
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Abstract
Late-life depression has been associated with white matter changes in studies using the regions of interest approach. To investigate the cross-sectional and longitudinal relationship between white matter integrity and depression in community-dwelling individuals using diffusion tensor imaging with tract-based spatial statistics. The sample comprised 381 participants aged between 72 and 92 years who were assessed twice within 2 years. Depressive symptoms were measured with the Geriatric Depression Scale. Tract-based spatial statistics were applied to investigate white matter integrity in currently depressed v. non-depressed elderly people and in those with a history of depression v. no history of depression. The relationship between white matter integrity and development of depressive symptoms after 2 years were analysed with logistic regression. Individuals with current depression had widespread white matter integrity reduction compared with non-depressed elderly people. Significant fractional anisotropy reductions were found in 45 brain areas with the most notable findings in the frontal lobe, association and projection fibres. A history of depression was not associated with reduced fractional anisotropy. White matter changes in the superior frontal gyrus, posterior thalamic radiation, superior longitudinal fasciculus and in the body of corpus callosum predicted depression at follow-up. Reduced white matter integrity is associated with late-life depression and predicts future depressive symptoms whereas a history of depression is not related to white matter changes. Disruption to white matter integrity may be a biomarker to predict late-life depression.
Medical subject headings
- Aging
- Brain
- Depressive Disorder
- Diffusion Tensor Imaging