TY - JOUR
T1 - White matter integrity and late-life depression in community-dwelling individuals
T2 - Diffusion tensor imaging study using tract-based spatial statistics
AU - Reppermund, Simone
AU - Zhuang, Lin
AU - Wen, Wei
AU - Slavin, Melissa J.
AU - Trollor, Julian N.
AU - Brodaty, Henry
AU - Sachdev, Perminder S.
PY - 2014/10/1
Y1 - 2014/10/1
N2 - Background: Late-life depression has been associated with white matter changes in studies using the regions of interest approach. Aims: 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. Method: 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. Results: 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. Conclusions: 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.
AB - Background: Late-life depression has been associated with white matter changes in studies using the regions of interest approach. Aims: 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. Method: 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. Results: 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. Conclusions: 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.
UR - http://www.scopus.com/inward/record.url?scp=84908123334&partnerID=8YFLogxK
U2 - 10.1192/bjp.bp.113.142109
DO - 10.1192/bjp.bp.113.142109
M3 - Article
C2 - 25147370
AN - SCOPUS:84908123334
VL - 205
SP - 315
EP - 320
JO - British Journal of Psychiatry
JF - British Journal of Psychiatry
SN - 0007-1250
IS - 4
ER -