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Multiple biological pathways associate with cerebral amyloid load in the early Alzheimer's continuum
Author(s) -
Salvadó Gemma,
Molinuevo Jose Luis,
MilàAlomà Marta,
Falcon Carles,
Operto Greg,
Cacciaglia Raffaele,
ArenazaUrquijo Eider M,
VilorTejedor Natalia,
Shekari Mahnaz,
Minguillón Carolina,
Fauria Karine,
Battle Mark R,
Buckley Chris J,
Farrar Gill,
Simon Maryline,
Kollmorgen Gwendlyn,
Blennow Kaj,
Zetterberg Henrik,
SuárezCalvet Marc,
Gispert Juan Domingo
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.044733
Subject(s) - neurogranin , cerebrospinal fluid , neurodegeneration , neuroinflammation , biomarker , pathology , amyloid (mycology) , medicine , neuroscience , pathophysiology , alzheimer's disease , psychology , disease , chemistry , biochemistry , protein kinase c , enzyme
Background The pathophysiological events associated with the earliest cerebral amyloid deposition are not fully understood. Here, we describe, in cognitively unimpaired individuals, the association between amyloid load and cerebrospinal fluid (CSF) biomarkers of the pathogenic events described in Alzheimer’s disease (AD): core AD biomarkers (Aβ 42/40 and pTau), synaptic dysfunction (neurogranin), neurodegeneration (neurofilament light [NfL]), microglial and astroglial‐related response (sTREM2, YKL‐40, GFAP, S100b), neuroinflammation (IL‐6) and α‐synuclein. Method The first consecutive 293 participants of the ALFA+ study with both valid CSF biomarker determination and [ 18 F]flutemetamol amyloid PET scans acquired within one year time were included. We measured the CSF biomarkers using the Roche NeuroToolkit robust prototype assays and the commercially available Elecsys® Phospho‐Tau CSF assay. Centiloid (CL) values and SUVr images were derived from [ 18 F]flutemetamol scans using the whole cerebellum as reference region. We sought for correlations between CSF biomarkers and cerebral amyloid deposition both globally, using the Centiloids as outcome variable, and regionally, using a voxel‐wise approach. The final model used for both analyses included: main effects of all CSF biomarkers and also interaction effects between CSF biomarkers with age, sex and APOE‐ε4 status. Interactions were only included if they showed a trend effect (p<0.10) in the global analysis. Neurogranin and pTau were included in the model as a unique vector due to their high collinearity (r>0.9). Result In the global analysis, pTau‐neurogranin, NfL, GFAP and YKL‐40 showed a positive correlation with global amyloid burden (Table 1). Significant interaction effects were found between: age*pTau‐neurogranin (older participants show higher amyloid deposition with higher pTau‐neurogranin); sex*sTREM2 (women with higher sTREM2 had higher amyloid deposition); APOE‐ε4* NfL (carriers with higher NfL had higher amyloid deposition) and APOE‐ε4* α‐synuclein (carriers with higher α‐synuclein had lower amyloid deposition), which are shown in Table 1 and Figure 1. Regional main effects are shown in Figure 2 while interactions are shown in Figure 3. Conclusion Neurodegeneration and inflammation pathways are associated to early amyloid deposition. The fact that biomarkers of these pathways show interactive effects with the main AD risk factors (age, sex and APOE‐ε4 ) also suggests that they play different roles in the early stage of the Alzheimer’s continuum.