Depressive symptoms in Parkinson's disease correlate with cortical atrophy over time.
Brain Cogn
; 111: 127-133, 2017 02.
Article
en En
| MEDLINE
| ID: mdl-27918935
INTRODUCTION: Depressive symptoms are very common in patients with Parkinson's disease (PD) and have a significant impact on the quality of life. METHODS: The present study analyzed the correlations between over-time changes in depressive symptoms and gray matter parameters of cortical thickness and subcortical volumes in non-demented PD patients. RESULTS: A significant correlation was observed, between increased scores for depression over time and lower cortical thickness over time in the right temporo-parietal junction, right occipital medial region, right dorsolateral prefrontal cortex, right posterior cingulate region, left middle temporal as well as left supplementary motor area. Furthermore, the presence of depressive symptoms at baseline predicted increased cortical thinning over time in the left middle temporal, left anterior cingulate, right posterior cingulate and right parahippocampal cortices. Finally, a statistically significant negative correlation has been revealed between the thalamus' volume changes over time and the change in depressive symptoms scores. All other analyzed subcortical structures didn't reveal any significant correlations. CONCLUSION: These results suggest that depressive symptoms in PD patients are associated with gray matter cortical thinning and thalamus volume shrinkage over time and higher scores of depressive symptoms at baseline correlate with a higher rate of cortical thinning longitudinally. The present study highlights the importance of addressing depressive symptoms in PD patients early in the disease.
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Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Enfermedad de Parkinson
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Tálamo
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Corteza Cerebral
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Progresión de la Enfermedad
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Depresión
Tipo de estudio:
Diagnostic_studies
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Observational_studies
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Prognostic_studies
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Risk_factors_studies
Límite:
Aged
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Female
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Humans
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Male
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Middle aged
Idioma:
En
Revista:
Brain Cogn
Año:
2017
Tipo del documento:
Article