Abstract

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.
Lingua originaleEnglish
Pagine61-61
Numero di pagine1
Stato di pubblicazionePublished - 2011

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Plasmas
Ions
Sugar Acids
Palmitic Acid
Amyloid beta-Protein Precursor
Organic acids
Biomarkers
Amyloid
Leucine
Gas chromatography
Mass spectrometry
Brain
Tissue
Acids
Metabolomics
amyloid beta-protein (1-42)

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title = "Metabolomic analysis of plasma from Alzheimer disease patients",
abstract = "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.",
author = "Altieri, {Grazia Ida} and Vincenza Valenti and Roberto Monastero and Massimiliano Greco and Maurizio Averna and Pietro Tralongo and Cefalu', {Angelo Baldassare} and Rossella Spina and Ornella Palesano and Alessandra Cannizzaro and Davide Noto and Francesca Fayer",
year = "2011",
language = "English",
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TY - CONF

T1 - Metabolomic analysis of plasma from Alzheimer disease patients

AU - Altieri, Grazia Ida

AU - Valenti, Vincenza

AU - Monastero, Roberto

AU - Greco, Massimiliano

AU - Averna, Maurizio

AU - Tralongo, Pietro

AU - Cefalu', Angelo Baldassare

AU - Spina, Rossella

AU - Palesano, Ornella

AU - Cannizzaro, Alessandra

AU - Noto, Davide

AU - Fayer, Francesca

PY - 2011

Y1 - 2011

N2 - 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.

AB - 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.

UR - http://hdl.handle.net/10447/104740

M3 - Other

SP - 61

EP - 61

ER -