IgG glycosylation associates with risk of progression from latent to active tuberculosis
Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved..
OBJECTIVES: Glycosylation motifs shape antibody structure, stability and antigen affinity and play an important role in antibody localization and function. Serum IgG glycosylation profiles are significantly altered in infectious diseases, including tuberculosis (TB), but have not been studied in the context of progression from latent to active TB.
METHODS: We performed a longitudinal study of paired bulk IgG glycosylation and transcriptomic profiling in blood from individuals with active TB (ATB) or latent TB infection (LTBI) before and after treatment.
RESULTS: We identified that a combination of two IgG1 glycosylation traits were sufficient to distinguish ATB from LTBI with high specificity and sensitivity, prior to, and after treatment. Importantly, these two features positively correlated with previously defined cellular and RNA signatures of ATB risk in LTBI, namely monocyte to lymphocyte ratio and the expression of interferon (IFN)-associated gene signature of progression (IFN-risk signature) in blood prior to treatment. Additional glycosylation features at higher prevalence in LTBI individuals with high expression of the IFN-risk signature prior to treatment included fucosylation on IgG1, IgG2 and IgG3.
CONCLUSIONS: Together, our results demonstrate that bulk IgG glycosylation features could be useful in stratifying the risk of LTBI reactivation and progression to ATB.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:88 |
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| Enthalten in: |
The Journal of infection - 88(2024), 3 vom: 15. März, Seite 106115 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Burel, Julie G [VerfasserIn] |
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| Links: |
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| Themen: |
Biomarkers |
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| Anmerkungen: |
Date Completed 19.03.2024 Date Revised 19.03.2024 published: Print-Electronic Citation Status MEDLINE |
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| doi: |
10.1016/j.jinf.2024.01.014 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM367987864 |
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| 245 | 1 | 0 | |a IgG glycosylation associates with risk of progression from latent to active tuberculosis |
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| 500 | |a Date Completed 19.03.2024 | ||
| 500 | |a Date Revised 19.03.2024 | ||
| 500 | |a published: Print-Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved. | ||
| 520 | |a OBJECTIVES: Glycosylation motifs shape antibody structure, stability and antigen affinity and play an important role in antibody localization and function. Serum IgG glycosylation profiles are significantly altered in infectious diseases, including tuberculosis (TB), but have not been studied in the context of progression from latent to active TB | ||
| 520 | |a METHODS: We performed a longitudinal study of paired bulk IgG glycosylation and transcriptomic profiling in blood from individuals with active TB (ATB) or latent TB infection (LTBI) before and after treatment | ||
| 520 | |a RESULTS: We identified that a combination of two IgG1 glycosylation traits were sufficient to distinguish ATB from LTBI with high specificity and sensitivity, prior to, and after treatment. Importantly, these two features positively correlated with previously defined cellular and RNA signatures of ATB risk in LTBI, namely monocyte to lymphocyte ratio and the expression of interferon (IFN)-associated gene signature of progression (IFN-risk signature) in blood prior to treatment. Additional glycosylation features at higher prevalence in LTBI individuals with high expression of the IFN-risk signature prior to treatment included fucosylation on IgG1, IgG2 and IgG3 | ||
| 520 | |a CONCLUSIONS: Together, our results demonstrate that bulk IgG glycosylation features could be useful in stratifying the risk of LTBI reactivation and progression to ATB | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Blood biomarkers | |
| 650 | 4 | |a IgG glycosylation | |
| 650 | 4 | |a Transcriptomics | |
| 650 | 4 | |a Tuberculosis | |
| 650 | 7 | |a Immunoglobulin G |2 NLM | |
| 650 | 7 | |a Biomarkers |2 NLM | |
| 700 | 1 | |a Wang, Wenjun |e verfasserin |4 aut | |
| 700 | 1 | |a Wuhrer, Manfred |e verfasserin |4 aut | |
| 700 | 1 | |a Dedicoat, Martin |e verfasserin |4 aut | |
| 700 | 1 | |a Fletcher, Thomas E |e verfasserin |4 aut | |
| 700 | 1 | |a Cunningham, Adam F |e verfasserin |4 aut | |
| 700 | 1 | |a O'Shea, Matthew K |e verfasserin |4 aut | |
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