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CSF proteomic profiling of mild cognitive impairment individuals with suspected non‐Alzheimer’s disease pathophysiology
Author(s) -
Delvenne Aurore,
Gobom Johan,
Tijms Betty M,
Bos Isabelle,
Verhey Frans RJ,
Ramakers Inez HGB,
Scheltens Philip,
Teunissen Charlotte E,
Vandenberghe Rik,
Gabel Silvy,
Popp Julius,
Peyratout Gwendoline,
MartinezLage Pablo,
Tainta Mikel,
Tsolaki Magda,
FreundLevi Yvonne,
Lovestone Simon,
Streffer Johannes,
Blennow Kaj,
Zetterberg Henrik,
Visser Pieter Jelle,
Vos Stephanie JB
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.047247
Subject(s) - snap , pathophysiology , biomarker , cerebrospinal fluid , dementia , cognitive impairment , proteomics , alzheimer's disease , medicine , disease , oncology , psychology , pathology , biology , gene , computer science , biochemistry , computer graphics (images)
Abstract Background Suspected non‐Alzheimer’s disease pathophysiology (SNAP) is a biomarker‐defined concept that encompasses individuals with Alzheimer’s disease (AD) neuronal injury but without amyloidosis. We have previously shown that 24% of mild cognitive impairment (MCI) individuals with SNAP will progress within 3 years to the AD dementia stage. Nonetheless, it remains unclear what explains the MCI‐SNAP biomarker profile and whether it reflects an early stage of AD, atypical AD or non‐AD pathology. We aimed to investigate the underlying pathophysiology of MCI‐SNAP using proteomics in cerebrospinal fluid (CSF). Method We included 206 individuals from the European EMIF‐AD MBD study and Maastricht BB‐ACL study. Based on CSF Aβ1‐42 (A) and p‐tau (T), individuals were classified as cognitively normal with normal A and T (CN, n=100), MCI with normal A and abnormal T (MCI‐SNAP, n=32), and MCI with abnormal A and T (MCI‐AD, n=74). We centrally generated CSF proteomic data for 1761 proteins using tandem tag mass spectrometry. We compared protein concentrations between groups using ANOVA adjusted for age and sex (1/3 observations per group minimum). We performed Gene Ontology enrichment analyses with false discovery rate to uncover the biological pathways of MCI‐SNAP. We investigated the expression profile of proteins in fetal/mature astrocytes, neurons, oligodendrocytes, microglia and endothelial cells. Result Sample characteristics are presented in Table 1. In MCI‐SNAP, we found 83 decreased and 28 increased proteins compared to CN and 177 decreased and 21 increased proteins compared to MCI‐AD. In MCI‐AD, we found 13 decreased and 193 increased proteins compared to CN. Proteins with decreased levels in MCI‐SNAP compared to both CN and MCI‐AD (n=55) were enriched for extracellular matrix, hemostasis, immune system, proteolysis and lysosome (Figure 1). A high percentage of these decreased proteins in MCI‐SNAP are expressed by mature astrocytes (51%) and endothelial cells (49%). Proteins increased in MCI‐SNAP and MCI‐AD compared to CN (n=17) were related to cytoskeleton organization and mainly expressed by neurons (88%). Conclusion Our results show that the pathophysiology of SNAP is distinct from that of AD. Further studies are needed to clarify the role of extracellular matrix, hemostasis, immune system, proteolysis and lysosome processes in SNAP.