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Blood RNA signature RISK4LEP predicts leprosy years before clinical onset
BACKGROUND: Leprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late- or misdiagnosed leading to irreversible disabilities. Blood transcriptomic biomarkers that prospectively predict those who progress to leprosy (progressors) would allow early diagnosis, better treatment...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8182229/ https://www.ncbi.nlm.nih.gov/pubmed/34090257 http://dx.doi.org/10.1016/j.ebiom.2021.103379 |
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author | Tió-Coma, Maria Kiełbasa, Szymon M. van den Eeden, Susan J.F. Mei, Hailiang Roy, Johan Chandra Wallinga, Jacco Khatun, Marufa Soren, Sontosh Chowdhury, Abu Sufian Alam, Khorshed van Hooij, Anouk Richardus, Jan Hendrik Geluk, Annemieke |
author_facet | Tió-Coma, Maria Kiełbasa, Szymon M. van den Eeden, Susan J.F. Mei, Hailiang Roy, Johan Chandra Wallinga, Jacco Khatun, Marufa Soren, Sontosh Chowdhury, Abu Sufian Alam, Khorshed van Hooij, Anouk Richardus, Jan Hendrik Geluk, Annemieke |
author_sort | Tió-Coma, Maria |
collection | PubMed |
description | BACKGROUND: Leprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late- or misdiagnosed leading to irreversible disabilities. Blood transcriptomic biomarkers that prospectively predict those who progress to leprosy (progressors) would allow early diagnosis, better treatment outcomes and facilitate interventions aimed at stopping bacterial transmission. To identify potential risk signatures of leprosy, we collected whole blood of household contacts (HC, n=5,352) of leprosy patients, including individuals who were diagnosed with leprosy 4-61 months after sample collection. METHODS: We investigated differential gene expression (DGE) by RNA-Seq between progressors before presence of symptoms (n=40) and HC (n=40), as well as longitudinal DGE within each progressor. A prospective leprosy signature was identified using a machine learning approach (Random Forest) and validated using reverse transcription quantitative PCR (RT-qPCR). FINDINGS: Although no significant intra-individual longitudinal variation within leprosy progressors was identified, 1,613 genes were differentially expressed in progressors before diagnosis compared to HC. We identified a 13-gene prospective risk signature with an Area Under the Curve (AUC) of 95.2%. Validation of this RNA-Seq signature in an additional set of progressors (n=43) and HC (n=43) by RT-qPCR, resulted in a final 4-gene signature, designated RISK4LEP (MT-ND2, REX1BD, TPGS1, UBC) (AUC=86.4%). INTERPRETATION: This study identifies for the first time a prospective transcriptional risk signature in blood predicting development of leprosy 4 to 61 months before clinical diagnosis. Assessment of this signature in contacts of leprosy patients can function as an adjunct diagnostic tool to target implementation of interventions to restrain leprosy development. FUNDING: This study was supported by R2STOP Research grant, the Order of Malta-Grants-for-Leprosy-Research, the Q.M. Gastmann-Wichers Foundation and the Leprosy Research Initiative (LRI) together with the Turing Foundation (ILEP# 702.02.73 and # 703.15.07). |
format | Online Article Text |
id | pubmed-8182229 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-81822292021-06-15 Blood RNA signature RISK4LEP predicts leprosy years before clinical onset Tió-Coma, Maria Kiełbasa, Szymon M. van den Eeden, Susan J.F. Mei, Hailiang Roy, Johan Chandra Wallinga, Jacco Khatun, Marufa Soren, Sontosh Chowdhury, Abu Sufian Alam, Khorshed van Hooij, Anouk Richardus, Jan Hendrik Geluk, Annemieke EBioMedicine Research paper BACKGROUND: Leprosy, a chronic infectious disease caused by Mycobacterium leprae, is often late- or misdiagnosed leading to irreversible disabilities. Blood transcriptomic biomarkers that prospectively predict those who progress to leprosy (progressors) would allow early diagnosis, better treatment outcomes and facilitate interventions aimed at stopping bacterial transmission. To identify potential risk signatures of leprosy, we collected whole blood of household contacts (HC, n=5,352) of leprosy patients, including individuals who were diagnosed with leprosy 4-61 months after sample collection. METHODS: We investigated differential gene expression (DGE) by RNA-Seq between progressors before presence of symptoms (n=40) and HC (n=40), as well as longitudinal DGE within each progressor. A prospective leprosy signature was identified using a machine learning approach (Random Forest) and validated using reverse transcription quantitative PCR (RT-qPCR). FINDINGS: Although no significant intra-individual longitudinal variation within leprosy progressors was identified, 1,613 genes were differentially expressed in progressors before diagnosis compared to HC. We identified a 13-gene prospective risk signature with an Area Under the Curve (AUC) of 95.2%. Validation of this RNA-Seq signature in an additional set of progressors (n=43) and HC (n=43) by RT-qPCR, resulted in a final 4-gene signature, designated RISK4LEP (MT-ND2, REX1BD, TPGS1, UBC) (AUC=86.4%). INTERPRETATION: This study identifies for the first time a prospective transcriptional risk signature in blood predicting development of leprosy 4 to 61 months before clinical diagnosis. Assessment of this signature in contacts of leprosy patients can function as an adjunct diagnostic tool to target implementation of interventions to restrain leprosy development. FUNDING: This study was supported by R2STOP Research grant, the Order of Malta-Grants-for-Leprosy-Research, the Q.M. Gastmann-Wichers Foundation and the Leprosy Research Initiative (LRI) together with the Turing Foundation (ILEP# 702.02.73 and # 703.15.07). Elsevier 2021-06-03 /pmc/articles/PMC8182229/ /pubmed/34090257 http://dx.doi.org/10.1016/j.ebiom.2021.103379 Text en © 2021 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Research paper Tió-Coma, Maria Kiełbasa, Szymon M. van den Eeden, Susan J.F. Mei, Hailiang Roy, Johan Chandra Wallinga, Jacco Khatun, Marufa Soren, Sontosh Chowdhury, Abu Sufian Alam, Khorshed van Hooij, Anouk Richardus, Jan Hendrik Geluk, Annemieke Blood RNA signature RISK4LEP predicts leprosy years before clinical onset |
title | Blood RNA signature RISK4LEP predicts leprosy years before clinical onset |
title_full | Blood RNA signature RISK4LEP predicts leprosy years before clinical onset |
title_fullStr | Blood RNA signature RISK4LEP predicts leprosy years before clinical onset |
title_full_unstemmed | Blood RNA signature RISK4LEP predicts leprosy years before clinical onset |
title_short | Blood RNA signature RISK4LEP predicts leprosy years before clinical onset |
title_sort | blood rna signature risk4lep predicts leprosy years before clinical onset |
topic | Research paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8182229/ https://www.ncbi.nlm.nih.gov/pubmed/34090257 http://dx.doi.org/10.1016/j.ebiom.2021.103379 |
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