Alzheimer Disease is a degenerative disease characterized byprogressive impairment of cognitive function. The main featureof AD the generation of an abnormal peptide, beta amyloid 42(Ab42) from Amyloid Precursor Protein (APP). Ab42 is the mainconstituent of neurotangles and amyloid plaques, microscopic lesionsfound in AD patients brain. Ab42 triggers an inflammatoryresponse that is responsible for most of the observed tissue damage.The diagnosis of AD is a complex task, mostly based on imagingtechniques and clinical evaluation of the patient’s neurologicaland cognitive functions. The search for plasma biomarkers able todetect early mild cognitive impairment is one of the recent attemptthe supply the clinician with new diagnostic tools.In this study we focused on a gas-chromatography mass-spectrometry(GC-MS) analysis coupled to chemometric automatedmetabolomic analysis of AD plasma samples compared with plasmaof healthy subjects of comparable age and gender. Sera fromtwenty AD and twenty controls have been subjects to a procedureoptimized to extract short chain organic acids, sugars and somefatty acids that can be detected by GC coupled to ion trap/MS detection.The method allowed the detection of over five thousandsof individual ions that have been collected and measured by theXCMS software. After automated peak detection and alignment byXCMS, peaks have been normalized by a set of internal standards(C13 Leucine, C13 palmitic acid) and clustered into putative compoundsby a homemade software. About 80 compounds were differentiallyexpressed between AD and controls. After manual verificationof the automated data, most of the compounds have beenexcluded since they represent column leakage or method artifacts,but some compounds represent true plasma constituents that areunder investigation. Current findings will be presented after putativecompound identification by the AMDIS/NIST software.
|Number of pages||1|
|Publication status||Published - 2011|