Identification of SPARC-like 1 protein as part of a biomarker panel for Alzheimer's disease in cerebrospinal fluid.

We have used proteomic fingerprinting to investigate diagnosis of Alzheimer's disease (AD). Samples of lumbar cerebrospinal fluid (CSF) from clinically-diagnosed AD cases (n = 33), age-matched controls (n = 20), and mild cognitive impairment (MCI) patients (n = 10) were used to obtain proteomic...

Бүрэн тодорхойлолт

Номзүйн дэлгэрэнгүй
Үндсэн зохиолчид: Vafadar-Isfahani, B, Ball, G, Coveney, C, Lemetre, C, Boocock, D, Minthon, L, Hansson, O, Miles, A, Janciauskiene, S, Warden, D, Smith, A, Wilcock, G, Kalsheker, N, Rees, R, Matharoo-Ball, B, Morgan, K
Формат: Journal article
Хэл сонгох:English
Хэвлэсэн: 2012
_version_ 1826264307056246784
author Vafadar-Isfahani, B
Ball, G
Coveney, C
Lemetre, C
Boocock, D
Minthon, L
Hansson, O
Miles, A
Janciauskiene, S
Warden, D
Smith, A
Wilcock, G
Kalsheker, N
Rees, R
Matharoo-Ball, B
Morgan, K
author_facet Vafadar-Isfahani, B
Ball, G
Coveney, C
Lemetre, C
Boocock, D
Minthon, L
Hansson, O
Miles, A
Janciauskiene, S
Warden, D
Smith, A
Wilcock, G
Kalsheker, N
Rees, R
Matharoo-Ball, B
Morgan, K
author_sort Vafadar-Isfahani, B
collection OXFORD
description We have used proteomic fingerprinting to investigate diagnosis of Alzheimer's disease (AD). Samples of lumbar cerebrospinal fluid (CSF) from clinically-diagnosed AD cases (n = 33), age-matched controls (n = 20), and mild cognitive impairment (MCI) patients (n = 10) were used to obtain proteomic profiles, followed by bioinformatic analysis that generated a set of potential biomarkers in CSF samples that could discriminate AD cases from controls. The identity of the biomarker ions was determined using mass spectroscopy. The panel of seven peptide biomarker ions was able to discriminate AD patients from controls with a median accuracy of 95% (sensitivity 85%, specificity 97%). When this model was applied to an independent blind dataset from MCI patients, the intensity of signals was intermediate between the control and AD patients implying that these markers could potentially predict patients with early neurodegenerative disease. The panel were identified, in order of predictive ability, as SPARC-like 1 protein, fibrinogen alpha chain precursor, amyloid-β, apolipoprotein E precursor, serum albumin precursor, keratin type I cytoskeletal 9, and tetranectin. The 7 ion ANN model was further validated using an independent cohort of samples, where the model was able to classify AD cases from controls with median accuracy of 84.5% (sensitivity 93.3%, specificity 75.7%). Validation by immunoassay was performed on the top three identified markers using the discovery samples and an independent sample cohort which was from postmortem confirmed AD patients (n = 17).
first_indexed 2024-03-06T20:05:40Z
format Journal article
id oxford-uuid:28d40780-f937-42de-8c5b-43b5a057cfe7
institution University of Oxford
language English
last_indexed 2024-03-06T20:05:40Z
publishDate 2012
record_format dspace
spelling oxford-uuid:28d40780-f937-42de-8c5b-43b5a057cfe72022-03-26T12:15:18ZIdentification of SPARC-like 1 protein as part of a biomarker panel for Alzheimer's disease in cerebrospinal fluid.Journal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:28d40780-f937-42de-8c5b-43b5a057cfe7EnglishSymplectic Elements at Oxford2012Vafadar-Isfahani, BBall, GCoveney, CLemetre, CBoocock, DMinthon, LHansson, OMiles, AJanciauskiene, SWarden, DSmith, AWilcock, GKalsheker, NRees, RMatharoo-Ball, BMorgan, KWe have used proteomic fingerprinting to investigate diagnosis of Alzheimer's disease (AD). Samples of lumbar cerebrospinal fluid (CSF) from clinically-diagnosed AD cases (n = 33), age-matched controls (n = 20), and mild cognitive impairment (MCI) patients (n = 10) were used to obtain proteomic profiles, followed by bioinformatic analysis that generated a set of potential biomarkers in CSF samples that could discriminate AD cases from controls. The identity of the biomarker ions was determined using mass spectroscopy. The panel of seven peptide biomarker ions was able to discriminate AD patients from controls with a median accuracy of 95% (sensitivity 85%, specificity 97%). When this model was applied to an independent blind dataset from MCI patients, the intensity of signals was intermediate between the control and AD patients implying that these markers could potentially predict patients with early neurodegenerative disease. The panel were identified, in order of predictive ability, as SPARC-like 1 protein, fibrinogen alpha chain precursor, amyloid-β, apolipoprotein E precursor, serum albumin precursor, keratin type I cytoskeletal 9, and tetranectin. The 7 ion ANN model was further validated using an independent cohort of samples, where the model was able to classify AD cases from controls with median accuracy of 84.5% (sensitivity 93.3%, specificity 75.7%). Validation by immunoassay was performed on the top three identified markers using the discovery samples and an independent sample cohort which was from postmortem confirmed AD patients (n = 17).
spellingShingle Vafadar-Isfahani, B
Ball, G
Coveney, C
Lemetre, C
Boocock, D
Minthon, L
Hansson, O
Miles, A
Janciauskiene, S
Warden, D
Smith, A
Wilcock, G
Kalsheker, N
Rees, R
Matharoo-Ball, B
Morgan, K
Identification of SPARC-like 1 protein as part of a biomarker panel for Alzheimer's disease in cerebrospinal fluid.
title Identification of SPARC-like 1 protein as part of a biomarker panel for Alzheimer's disease in cerebrospinal fluid.
title_full Identification of SPARC-like 1 protein as part of a biomarker panel for Alzheimer's disease in cerebrospinal fluid.
title_fullStr Identification of SPARC-like 1 protein as part of a biomarker panel for Alzheimer's disease in cerebrospinal fluid.
title_full_unstemmed Identification of SPARC-like 1 protein as part of a biomarker panel for Alzheimer's disease in cerebrospinal fluid.
title_short Identification of SPARC-like 1 protein as part of a biomarker panel for Alzheimer's disease in cerebrospinal fluid.
title_sort identification of sparc like 1 protein as part of a biomarker panel for alzheimer s disease in cerebrospinal fluid
work_keys_str_mv AT vafadarisfahanib identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT ballg identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT coveneyc identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT lemetrec identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT boocockd identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT minthonl identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT hanssono identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT milesa identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT janciauskienes identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT wardend identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT smitha identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT wilcockg identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT kalshekern identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT reesr identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT matharooballb identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid
AT morgank identificationofsparclike1proteinaspartofabiomarkerpanelforalzheimersdiseaseincerebrospinalfluid