Background
Alzheimer's disease (AD) is one of the most frequent cause of neurodegenerative disorder in the elderly. Inflammation has been implicated in brain degenerative processes and peripheral markers of brain AD related impairment would be useful. Plasma levels of alpha-1-antichymotrypsin (ACT), an acute phase protein and a secondary component of amyloid plaques, are often increased in AD patients and high blood ACT levels correlate with progressive cognitive deterioration. During inflammatory responses changes in the micro-heterogeneity of ACT sugar chains have been described.
Conclusions
Low content of terminal GlcNac and sialic acid in peripheral ACT in AD patients suggests that a different pattern of glycosylation might be a marker of brain inflammation. Moreover ACT glycosylation analysis could be used to predict AD clinical progression and used in clinical trials as surrogate marker of clinical efficacy.
Methods
N-Glycanase digestion from Flavobacterium meningosepticum (PNGase F) was performed on both native and denatured purified ACT condition and resolved to Western blot with the purpose to revealed the ACT de-glycosylation pattern.Further characterization of the ACT glycan profile was obtained by a glycoarray; each lectin group in the assay specifically recognizes one or two glycans/epitopes. Lectin-bound ACT produced a glyco-fingerprint and mayor differences between AD and controls samples were assessed by a specific algorithms.
Results
Western blot analysis of purified ACT after PNGase F treatment and analysis of sugar composition of ACT showed significantly difference in "glyco-fingerprints" patterns from controls (CTR) and AD; ACT from AD showing significantly reduced levels of sialic acid. A difference in terminal GlcNac residues appeared to be related with progressive cognitive deterioration. Conclusions: Low content of terminal GlcNac and sialic acid in peripheral ACT in AD patients suggests that a different pattern of glycosylation might be a marker of brain inflammation. Moreover ACT glycosylation analysis could be used to predict AD clinical progression and used in clinical trials as surrogate marker of clinical efficacy.