4.8 Article

Plasma biosignature and brain pathology related to persistent cognitive impairment in late-life depression

Journal

MOLECULAR PSYCHIATRY
Volume 20, Issue 5, Pages 594-601

Publisher

NATURE PUBLISHING GROUP
DOI: 10.1038/mp.2014.76

Keywords

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Funding

  1. ACISR for Late Life Depression Prevention and Treatment [MH080240, MH080240-S1, P30 MH90333]
  2. Alzheimer's Disease Research Center [P50 AG05133]
  3. John A Hartford Foundation Center of Excellence in Geriatric Psychiatry
  4. UFMG Intramural Research Grant [01/2013]
  5. CNPq [472138/2013-8]
  6. [R01 CA181450]

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Cognitive impairment is highly prevalent among individuals with late-life depression (LLD) and tends to persist even after successful treatment. The biological mechanisms underlying cognitive impairment in LLD are complex and likely involve abnormalities in multiple pathways, or 'cascades,' reflected in specific biomarkers. Our aim was to evaluate peripheral (blood-based) evidence for biological pathways associated with cognitive impairment in older adults with LLD. To this end, we used a data-driven comprehensive proteomic analysis (multiplex immunoassay including 242 proteins), along with measures of structural brain abnormalities (gray matter atrophy and white matter hyperintensity volume via magnetic resonance imaging), and brain amyloid-beta (A beta) deposition (PiB-positron emission tomography). We analyzed data from 80 older adults with remitted major depression (36 with mild cognitive impairment (LLD+MCI) and 44 with normal cognitive (LLD+NC)) function. LLD+MCI was associated with differential expression of 24 proteins (P < 0.05 and q-value <0.30) related mainly to the regulation of immune-inflammatory activity, intracellular signaling, cell survival and protein and lipid homeostasis. Individuals with LLD+MCI also showed greater white matter hyperintensity burden compared with LLD+NC (P = 0.015). We observed no differences in gray matter volume or brain A beta deposition between groups. Machine learning analysis showed that a group of three proteins (Apo AI, IL-12 and stem cell factor) yielded accuracy of 81.3%, sensitivity of 75% and specificity of 86.4% in discriminating participants with MCI from those with NC function (with an averaged cross-validation accuracy of 76.3%, sensitivity of 69.4% and specificity of 81.8% with nested cross-validation considering the model selection bias). Cognitive impairment in LLD seems to be related to greater cerebrovascular disease along with abnormalities in immune-inflammatory control, cell survival, intracellular signaling, protein and lipid homeostasis, and clotting processes. These results suggest that individuals with LLD and cognitive impairment may be more vulnerable to accelerated brain aging and shed light on possible mediators of their elevated risk for progression to dementia.

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