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SWATH-MS analysis of cerebrospinal fluid to generate a robust battery of biomarkers for Alzheimer's disease

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dc.contributor.authorPark, SA-
dc.contributor.authorJung, JM-
dc.contributor.authorPark, JS-
dc.contributor.authorLee, JH-
dc.contributor.authorPark, B-
dc.contributor.authorKim, HJ-
dc.contributor.authorPark, JH-
dc.contributor.authorChae, WS-
dc.contributor.authorJeong, JH-
dc.contributor.authorChoi, SH-
dc.contributor.authorBaek, JH-
dc.date.accessioned2022-11-23T07:32:48Z-
dc.date.available2022-11-23T07:32:48Z-
dc.date.issued2020-
dc.identifier.urihttp://repository.ajou.ac.kr/handle/201003/22829-
dc.description.abstractCerebrospinal fluid (CSF) Abeta42 and tau protein levels are established diagnostic biomarkers of Alzheimer's disease (AD). However, their inadequacy to represent clinical efficacy in drug trials indicates the need for new biomarkers. Sequential window acquisition of all theoretical fragment ion spectra (SWATH)-based mass spectrometry (MS) is an advanced proteomic tool for large-scale, high-quality quantification. In this study, SWATH-MS showed that VGF, chromogranin-A, secretogranin-1, and opioid-binding protein/cell adhesion molecule were significantly decreased in 42 AD patients compared to 39 controls, whereas 14-3-3zeta was increased (FDR < 0.05). In addition, 16 other proteins showed substantial changes (FDR < 0.2). The expressions of the top 21 analytes were closely interconnected, but were poorly correlated with CSF Abeta42, tTau, and pTau181 levels. Logistic regression analysis and data mining were used to establish the best algorithm for AD, which created novel biomarker panels with high diagnostic value (AUC = 0.889 and 0.924) and a strong correlation with clinical severity (all p < 0.001). Targeted proteomics was used to validate their usefulness in a different cohort (n = 36) that included patients with other brain disorders (all p < 0.05). This study provides a list of proteins (and combinations thereof) that could serve as new AD biomarkers.-
dc.language.isoen-
dc.subject.MESHAged-
dc.subject.MESHAlgorithms-
dc.subject.MESHAlzheimer Disease-
dc.subject.MESHArea Under Curve-
dc.subject.MESHBiomarkers-
dc.subject.MESHCohort Studies-
dc.subject.MESHData Mining-
dc.subject.MESHDementia-
dc.subject.MESHFemale-
dc.subject.MESHGene Expression Profiling-
dc.subject.MESHGene Expression Regulation-
dc.subject.MESHGenetic Variation-
dc.subject.MESHHumans-
dc.subject.MESHMale-
dc.subject.MESHMass Spectrometry-
dc.subject.MESHMiddle Aged-
dc.subject.MESHPeptide Fragments-
dc.subject.MESHProteomics-
dc.subject.MESHReference Values-
dc.subject.MESHtau Proteins-
dc.titleSWATH-MS analysis of cerebrospinal fluid to generate a robust battery of biomarkers for Alzheimer's disease-
dc.typeArticle-
dc.identifier.pmid32366888-
dc.identifier.urlhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7198522-
dc.subject.keywordAlzheimer's disease-
dc.subject.keywordDementia-
dc.contributor.affiliatedAuthorPark, SA-
dc.contributor.affiliatedAuthorPark, B-
dc.type.localJournal Papers-
dc.identifier.doi10.1038/s41598-020-64461-y-
dc.citation.titleScientific reports-
dc.citation.volume10-
dc.citation.number1-
dc.citation.date2020-
dc.citation.startPage7423-
dc.citation.endPage7423-
dc.identifier.bibliographicCitationScientific reports, 10(1). : 7423-7423, 2020-
dc.identifier.eissn2045-2322-
dc.relation.journalidJ020452322-
Appears in Collections:
Journal Papers > School of Medicine / Graduate School of Medicine > Anatomy
Journal Papers > School of Medicine / Graduate School of Medicine > Biomedical Informatics
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