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dc.contributor.authorde Araujo, Leonardo S
dc.contributor.authorRibeiro-Alves, Marcelo
dc.contributor.authorWipperman, Matthew F
dc.contributor.authorVorkas, Charles Kyriakos
dc.contributor.authorPessler, Frank
dc.contributor.authorSaad, Maria Helena Féres
dc.date.accessioned2021-12-01T14:09:08Z
dc.date.available2021-12-01T14:09:08Z
dc.date.issued2021-10-09
dc.identifier.citationCells. 2021 Oct 9;10(10):2704. doi: 10.3390/cells10102704.en_US
dc.identifier.pmid34685683
dc.identifier.doi10.3390/cells10102704
dc.identifier.urihttp://hdl.handle.net/10033/623108
dc.description.abstractExternal validation in different cohorts is a key step in the translational development of new biomarkers. We previously described three host mRNA whose expression in peripheral blood is significantly higher (NPC2) or lower (DOCK9 and EPHA4) in individuals with TB compared to latent TB infection (LTBI) and controls. We have now conducted an independent validation of these genes by re-analyzing publicly available transcriptomic datasets from Brazil, China, Haiti, India, South Africa, and the United Kingdom. Comparisons between TB and control/LTBI showed significant differential expression of all three genes (NPC2high&nbsp;p < 0.01, DOCK9low&nbsp;p < 0.01, and EPHA4low&nbsp;p < 0.05). NPC2high had the highest mean area under the ROC curve (AUROC) for the differentiation of TB vs. controls (0.95) and LTBI (0.94). In addition, NPC2 accurately distinguished TB from the clinically similar conditions pneumonia (AUROC, 0.88), non-active sarcoidosis (0.87), and lung cancer (0.86), but not from active sarcoidosis (0.66). Interestingly, individuals progressing from LTBI to TB showed a constant increase in NPC2 expression with time when compared to non-progressors (p < 0.05), with a significant change closer to manifestation of active disease (≤3 months, p = 0.003). Moreover, NPC2 expression normalized with completion of anti-TB treatment. Taken together, these results validate NPC2 mRNA as a diagnostic host biomarker for active TB independent of host genetic background. Moreover, they reveal its potential to predict progression from latent to active infection and to indicate a response to anti-TB treatment.en_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectMycobacterium tuberculosisen_US
dc.subjectNPC2en_US
dc.subjectNiemann–Pick disease type C2en_US
dc.subjectRNAen_US
dc.subjectbiomarkersen_US
dc.subjectdiagnosisen_US
dc.subjectmRNAen_US
dc.subjecttranscriptionen_US
dc.subjecttreatmenten_US
dc.subjecttuberculosisen_US
dc.titleTranscriptomic Biomarkers for Tuberculosis: Validation of as a Single mRNA Biomarker to Diagnose TB, Predict Disease Progression, and Monitor Treatment Response.en_US
dc.typeArticleen_US
dc.identifier.eissn2073-4409
dc.contributor.departmentTWINCORE, Zentrum für experimentelle und klinische Infektionsforschung GmbH,Feodor-Lynen Str. 7, 30625 Hannover, Germany.en_US
dc.identifier.journalCellsen_US
dc.source.volume10
dc.source.issue10
refterms.dateFOA2021-12-01T14:09:09Z
dc.source.journaltitleCells
dc.source.countrySwitzerland


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