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Microglial activation indexed by [ 11 C]PBR28 is associated with synaptic depletion in the Alzheimer’s disease spectrum
Author(s) -
Benedet Andréa Lessa,
Ashton Nicholas J,
Pascoal Tharick A.,
Brinkmalm Ann,
Nilsson Johanna,
Kvartsberg Hlin,
Mathotaarachchi Sulantha,
Savard Melissa,
Therriault Joseph,
Tissot Cécile,
Chamoun Mira,
Blennow Kaj,
Zetterberg Henrik,
RosaNeto Pedro
Publication year - 2020
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1002/alz.046191
Subject(s) - neurogranin , neuroinflammation , biomarker , dementia , neuroscience , microglia , psychology , cerebrospinal fluid , context (archaeology) , medicine , disease , biology , inflammation , biochemistry , signal transduction , paleontology , protein kinase c
Background A large body of evidence supports the link between neuroinflammation and neurodegenerative conditions, including Alzheimer’s disease (AD). In AD, high expression of immune mediators have been associated with increased microglial reactivity. Several mechanisms were proposed to explain the relationship between microglial activation and synaptic plasticity/dysfunction. However, it remains unresolved whether neuroinflammation has a primary rather than a reactive contribution to synaptic deficits. Thus, in vivo human studies are extremely important to help deciphering the immediate causes of synaptic degeneration and the role of neuroinflammation in this context. Here we investigated, in the AD spectrum, the association between cerebrospinal fluid (CSF) biomarkers of synaptic depletion and microglial activation, indexed by [ 11 C]PBR28 PET, using data from the Translational Biomarkers of Aging and Dementia (TRIAD) cohort. Method 70 participants (15 young controls, 27 normal controls (CN), 20 mild cognitive impairment (MCI) and 8 AD) were evaluated with cross‐sectional CSF biomarkers and [ 11 C]PBR28 PET. The CSF biomarkers were quantified by in‐house immunoassays for neurogranin and neuromodulin (GAP‐43), whereas SNAP‐25 and synaptotagmin‐1 (SYT1) were quantified using an immunoprecipitation mass spectrometry method. Linear models were applied to evaluate group differences in CSF biomarker concentrations, adjusting for age and sex. Voxel‐wise linear regressions examined the association between CSF‐ and PET‐based measures. ROI‐based average SUVR was used to test the correlation between CSF biomarkers and [ 11 C]PBR28SUVR. Result AD participants had higher concentrations of CSF synaptic biomarkers compared with CN. Findings at the voxel level showed a good agreement between CSF biomarkers (Figure 1), with increased CSF biomarker levels being associated with greater [ 11 C]PBR28uptake in the frontal, posterior cingulate, temporal and inferior‐parietal cortices. Amongst the biomarkers tested, CSF SNAP‐25 biomarkers showed the strongest correlations with [ 11 C]PBR28 (R SNAP25_total =0.69; R SNAP25_long =0.67; Figure 2). Further results will indicate the relationship between sTREM2 and [ 11 C]PBR28. Conclusion Results support a link between neuroinflammation and synaptic degeneration. Although causality could not be inferred, the findings corroborate a detrimental effect of neuroinflammation on synapses at later disease stages. Finally, the results also support CSF SNAP‐25as a biomarker to track synaptic dysfunction and degeneration in AD pathophysiology.