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Structural brain changes as biomarkers and outcome predictors in patients with late-life depression: a cross-sectional and prospective study.

Publication ,  Journal Article
Ribeiz, SRI; Duran, F; Oliveira, MC; Bezerra, D; Castro, CC; Steffens, DC; Busatto Filho, G; Bottino, CMC
Published in: PLoS One
2013

The relationship between structural changes in grey matter and treatment response in patients with late-life depression remains an intriguing area of research. This magnetic resonance imaging (MRI) study compares the baseline grey matter volume of elderly people with and without major depression (according to the DSM-IV-TR criteria) and assesses its association with antidepressant treatment response. Brain MRI scans were processed using statistical parametric mapping and voxel-based morphometry. The sample consisted of 30 patients with depression and 22 healthy controls. We found a significant volumetric reduction in the orbitofrontal cortex bilaterally in patients in comparison with controls. According to their remission status after antidepressant treatment, patients were classified as remitted or not remitted. Compared with controls, remitted patients showed a volumetric reduction in the orbitofrontal cortex bilaterally and in another cluster in the right middle temporal pole. Non-remitted patients showed an even greater volumetric reduction in the orbitofrontal cortex bilaterally compared with controls. To investigate predictive factors of remission after antidepressant treatment, we used a logistic regression. Both baseline Mini Mental State Examination score and baseline left superior lateral orbitofrontal cortex volume (standardized to the total grey matter volume) were associated with remission status. Our findings support the use of regional brain atrophy as a potential biomarker for depression. In addition, baseline cognitive impairment and regional grey matter abnormalities predict antidepressant response in patients with late-life depression.

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Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2013

Volume

8

Issue

11

Start / End Page

e80049

Location

United States

Related Subject Headings

  • Prospective Studies
  • Middle Aged
  • Male
  • Magnetic Resonance Imaging
  • Logistic Models
  • Humans
  • General Science & Technology
  • Female
  • Depressive Disorder, Major
  • Cross-Sectional Studies
 

Citation

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Ribeiz, S. R. I., Duran, F., Oliveira, M. C., Bezerra, D., Castro, C. C., Steffens, D. C., … Bottino, C. M. C. (2013). Structural brain changes as biomarkers and outcome predictors in patients with late-life depression: a cross-sectional and prospective study. PLoS One, 8(11), e80049. https://doi.org/10.1371/journal.pone.0080049
Ribeiz, Salma R. I., Fabio Duran, Melaine C. Oliveira, Diana Bezerra, Claudio Campi Castro, David C. Steffens, Geraldo Busatto Filho, and Cássio M. C. Bottino. “Structural brain changes as biomarkers and outcome predictors in patients with late-life depression: a cross-sectional and prospective study.PLoS One 8, no. 11 (2013): e80049. https://doi.org/10.1371/journal.pone.0080049.
Ribeiz SRI, Duran F, Oliveira MC, Bezerra D, Castro CC, Steffens DC, et al. Structural brain changes as biomarkers and outcome predictors in patients with late-life depression: a cross-sectional and prospective study. PLoS One. 2013;8(11):e80049.
Ribeiz, Salma R. I., et al. “Structural brain changes as biomarkers and outcome predictors in patients with late-life depression: a cross-sectional and prospective study.PLoS One, vol. 8, no. 11, 2013, p. e80049. Pubmed, doi:10.1371/journal.pone.0080049.
Ribeiz SRI, Duran F, Oliveira MC, Bezerra D, Castro CC, Steffens DC, Busatto Filho G, Bottino CMC. Structural brain changes as biomarkers and outcome predictors in patients with late-life depression: a cross-sectional and prospective study. PLoS One. 2013;8(11):e80049.

Published In

PLoS One

DOI

EISSN

1932-6203

Publication Date

2013

Volume

8

Issue

11

Start / End Page

e80049

Location

United States

Related Subject Headings

  • Prospective Studies
  • Middle Aged
  • Male
  • Magnetic Resonance Imaging
  • Logistic Models
  • Humans
  • General Science & Technology
  • Female
  • Depressive Disorder, Major
  • Cross-Sectional Studies