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Whole genome profiling refines a panel of correlates to predict vaccine efficacy against Mycobacterium tuberculosis
Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
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2020 (English)In: Tuberculosis, ISSN 1472-9792, E-ISSN 1873-281X, Vol. 120, article id 101895Article in journal (Refereed) Published
Abstract [en]

New vaccines are needed to combat the public health threat posed by M. tuberculosis (M. tb), but no correlates have been defined to aid vaccine development. Using mouse models, we previously developed an in vitro system that measures the ability of M. tb-immune lymphocytes to control bacterial replication during co-culture with M. tb-infected macrophages. We demonstrated that the degree of in vitro growth control by lymphocytes from mice given vaccines of varying efficacy reflected the relative degree of in vivo protection against lethal challenge. Further, using targeted analyses of gene expression in lymphocytes recovered from co-cultures, we found mediators whose relative expression also correlated with in vitro and in vivo outcomes. Here we advanced those findings by employing genome-wide expression analyses. We first screened splenocytes recovered from co-cultures by microarray, revealing additional genes whose expression correlated with protection. After applying pathway analyses to down-select gene candidates, we used both splenocytes and peripheral blood lymphocytes to validate microarray findings by qRT-PCR. We then subjected data from top candidates to rigorous statistical analyses. Resulting correlate candidates, including CXCL9, IFN-γ, and CCL5, significantly predicted protection with high specificity. These findings therefore refine and extend a panel of relevant immune correlates to advance vaccine development.

Place, publisher, year, edition, pages
Elsevier, 2020. Vol. 120, article id 101895
Keywords [en]
Vaccine, Correlates, Biomarkers, T lymphocytes, Gene expression
National Category
Health Sciences Pharmaceutical and Medical Biotechnology
Identifiers
URN: urn:nbn:se:umu:diva-167929DOI: 10.1016/j.tube.2019.101895ISI: 000515103700006Scopus ID: 2-s2.0-85078761598OAI: oai:DiVA.org:umu-167929DiVA, id: diva2:1392216
Available from: 2020-02-06 Created: 2020-02-06 Last updated: 2025-02-17Bibliographically approved

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Rydén, Patrik

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CiteExportLink to record
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