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Background <p>Accurate detection of tuberculosis (TB) treatment failure and recurrence can improve disease control, but current sputum-based monitoring tools pose significant limitations. This study aimed to identify sputum-independent biomarkers for detecting and predicting TB treatment failure and recurrence.</p> Methods <p>Within the Pan-African TB Sequel study, we conducted a matched case-control study with 40 participants who had recurrent TB or treatment failure and 37 successfully treated controls matched by sex, age, and HIV status. Cases were classified as (a) non-converters with persistently positive sputum <i>Mycobacterium tuberculosis</i> (MTB) results during treatment, (b) reverters at the end of treatment (EOT), or (c) recurrence after EOT. Peripheral blood was collected at baseline, months 2, 4, 6, 9, and 12, and at suspected recurrence. MTB-specific T-cell activation markers (CD38, CD27, HLA-DR, Ki67) and transcriptomic signatures (Sweeney3, Risk6, MAMS6) were assessed and compared to the reference standard MTB culture and smear results.</p> Results <p>Here, we show that both MTB-specific T-cell activation and transcriptomic signatures detected non-conversion and TB recurrence at month 9 or 12 after treatment initiation. CD38 expression demonstrates 100% sensitive (95% CI: 56.6–100%) and 78% specific (95% CI: 56.5–99.4%) for detecting TB recurrence, with an AUC of 0.98 (95% CI: 91–100%). Among transcriptomic signatures, MAMS6, RISK6, and Sweeney3 achieve 75% sensitivity (95% CI: 50–100%) and 87–93% specificity (95% CI: MAMS6 0–100%, RISK6 0–93%, Sweeney3 0–100%), with comparable AUCs (0.78–0.83). Neither marker detected TB reversion at EOT.</p> Conclusion <p>These sputum-independent biomarkers effectively identify TB disease, non-conversion and recurrence TB after EOT, whereas their utility in detecting TB reversion during treatment remains limited.</p>

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Host response biomarkers of tuberculosis recurrence and treatment failure

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月14日

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  • Bernadette Bauer,
  • Mohamed I. M. Ahmed,
  • Olga Baranov,
  • Abhishek Bakuli,
  • Luming Lin,
  • Abisai Kisinda,
  • Mkunde Chachage,
  • Nyanda E. Ntinginya,
  • Celso Khosa,
  • Michael Hoelscher,
  • Mohammed Rassool,
  • Salome Charalambous,
  • Jayne S. Sutherland,
  • Kathrin Held,
  • Andrea Rachow,
  • Christof Geldmacher,
  • Beate Kampmann,
  • Basil Sambou,
  • Abi-Janet Riley,
  • Binta Sarr,
  • Caleb Muefong,
  • Georgetta Daffeh,
  • Olumuyiwa Owolabi,
  • Ben Dowsing,
  • Azeezat Sallahdeen,
  • Shamanthi Jayasooriya,
  • Abdou Sillah,
  • Monica Davies,
  • Alhaji Jobe,
  • Momodou Jallow,
  • Salieu Barry,
  • Lamin Bah,
  • Simon Badjie,
  • Kairaba Kanyi,
  • Gambia Sowe,
  • Isatou Loum,
  • Awa Touray,
  • Mustapha Bah,
  • Rohey Jallow,
  • Simon Donkor,
  • Issa Sabi,
  • Tina Minja,
  • Daniel Mapamba,
  • Emmanuel Sichone,
  • Lwitiho Sudi,
  • Elimina Siyame,
  • Julieth M. Lalashowi,
  • Ian Sanne,
  • Lyndel Singh,
  • Jaclyn Bennet Denise Evans,
  • Kamban Hirasen,
  • Nelly Jinga,
  • Ilesh Jani,
  • Nilesh Bhatt,
  • Sofia Viegas,
  • Carla Madeira,
  • Khalide Azam,
  • Cláudio Abujate,
  • Narciso Macie,
  • Nádia Sitoe,
  • Salomão Manjate,
  • Vânia Maphossa,
  • Alberto Machaze,
  • Cristovão Matusse,
  • Antonio Machiana,
  • Candido Azize,
  • Arlindo Machava,
  • Celina Nhamuave,
  • Elvira Monteiro,
  • Olena Ivanova,
  • Anna-Maria Mekota,
  • Elmar Saathoff,
  • Friedrich Riess,
  • Fidelina Zekoll,
  • Gavin Churchyard,
  • Robert Wallis,
  • Kavindhran Velen,
  • Farzana Sathar,
  • Fadzai Munedzimwe,
  • Stefan Niemann,
  • Matthias Merker,
  • Viola Dreyer,
  • Ulrich Schaible,
  • Christoph Leschczyk,
  • Lindsay Zurba,
  • Knut Lönnroth

摘要

Background

Accurate detection of tuberculosis (TB) treatment failure and recurrence can improve disease control, but current sputum-based monitoring tools pose significant limitations. This study aimed to identify sputum-independent biomarkers for detecting and predicting TB treatment failure and recurrence.

Methods

Within the Pan-African TB Sequel study, we conducted a matched case-control study with 40 participants who had recurrent TB or treatment failure and 37 successfully treated controls matched by sex, age, and HIV status. Cases were classified as (a) non-converters with persistently positive sputum Mycobacterium tuberculosis (MTB) results during treatment, (b) reverters at the end of treatment (EOT), or (c) recurrence after EOT. Peripheral blood was collected at baseline, months 2, 4, 6, 9, and 12, and at suspected recurrence. MTB-specific T-cell activation markers (CD38, CD27, HLA-DR, Ki67) and transcriptomic signatures (Sweeney3, Risk6, MAMS6) were assessed and compared to the reference standard MTB culture and smear results.

Results

Here, we show that both MTB-specific T-cell activation and transcriptomic signatures detected non-conversion and TB recurrence at month 9 or 12 after treatment initiation. CD38 expression demonstrates 100% sensitive (95% CI: 56.6–100%) and 78% specific (95% CI: 56.5–99.4%) for detecting TB recurrence, with an AUC of 0.98 (95% CI: 91–100%). Among transcriptomic signatures, MAMS6, RISK6, and Sweeney3 achieve 75% sensitivity (95% CI: 50–100%) and 87–93% specificity (95% CI: MAMS6 0–100%, RISK6 0–93%, Sweeney3 0–100%), with comparable AUCs (0.78–0.83). Neither marker detected TB reversion at EOT.

Conclusion

These sputum-independent biomarkers effectively identify TB disease, non-conversion and recurrence TB after EOT, whereas their utility in detecting TB reversion during treatment remains limited.