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Published on: October 13, 2016
A potential multimodal biomarker - cognitive signature associated with the conversion from subjective cognitive
Mohamed Haddad1, Mohamed Raâfet Ben Khedher1,2,3, Chadi Ouechtati1
1Centre Armand-Frappier Santé Biotechnologie Institut National de la Recherche Scientifique Laval QC Canada.
Introduction:
The disruption of key mechanisms involved in amyloid beta (Aβ) clearance during the early stages of dementia may contribute to the progression of cognitive decline toward irreversible brain damage. In this study, we investigated multiple immune-related pathways implicated in the management and clearance of Aβ within circulating extracellular vesicles (cEVs) and serum from individuals with subjective cognitive decline (SCD) who later progressed to mild cognitive impairment (MCI).
Methods:
A cytokine panel and the levels of Aβ1-42 were quantified in both cEVs and serum from a longitudinally followed cohort of elderly with SCD, using mesoscale and Luminex technologies. We investigated associations with Aβ burden, cognitive performance, APOE ε4 allele status, and the likelihood of conversion to MCI.
Results:
In SCD patients, the concentrations of Aβ1-42 and macrophage-colony stimulating factor (M-CSF) were higher, respectively, in cEVs and serum. No difference was observed for fraktaline, interleukin (IL)-4, IL-13, interferon gamma (IFN-γ), and sCD40L in either cEVs or serum between SCD and control patients. Based on receiver operating characteristic curve analysis, regression modeling, and correlations with cognitive performance, M-CSF levels in serum effectively distinguished individuals with SCD who converted to MCI from those who remained stable. Interestingly, combining M-CSF and cEVs Aβ1-42 with the Rey Auditory Verbal Learning Test (RAVLT) cognitive scores provided an excellent classification for SCD converted to MCI up to 2 years prior to clinical diagnosis.
Discussion:
Our findings support the potential value of integrating serum M-CSF levels with RAVLT performance and cEVs Aβ1-42 concentrations into a multimodal biomarker panel for longitudinal monitoring of progressive neurocognitive impairment.
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