The Journal of Clinical Investigation (Feb 2022)

Antiretroviral therapy timing impacts latent tuberculosis infection reactivation in a Mycobacterium tuberculosis/SIV coinfection model

  • Riti Sharan,
  • Shashank R. Ganatra,
  • Allison N. Bucsan,
  • Journey Cole,
  • Dhiraj K. Singh,
  • Xavier Alvarez,
  • Maya Gough,
  • Cynthia Alvarez,
  • Alyssa Blakley,
  • Justin Ferdin,
  • Rajesh Thippeshappa,
  • Bindu Singh,
  • Ruby Escobedo,
  • Vinay Shivanna,
  • Edward J. Dick Jr.,
  • Shannan Hall-Ursone,
  • Shabaana A. Khader,
  • Smriti Mehra,
  • Jyothi Rengarajan,
  • Deepak Kaushal

Journal volume & issue
Vol. 132, no. 3

Abstract

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Studies using the nonhuman primate model of Mycobacterium tuberculosis/simian immunodeficiency virus coinfection have revealed protective CD4+ T cell–independent immune responses that suppress latent tuberculosis infection (LTBI) reactivation. In particular, chronic immune activation rather than the mere depletion of CD4+ T cells correlates with reactivation due to SIV coinfection. Here, we administered combinatorial antiretroviral therapy (cART) 2 weeks after SIV coinfection to study whether restoration of CD4+ T cell immunity occurred more broadly, and whether this prevented reactivation of LTBI compared to cART initiated 4 weeks after SIV. Earlier initiation of cART enhanced survival, led to better control of viral replication, and reduced immune activation in the periphery and lung vasculature, thereby reducing the rate of SIV-induced reactivation. We observed robust CD8+ T effector memory responses and significantly reduced macrophage turnover in the lung tissue. However, skewed CD4+ T effector memory responses persisted and new TB lesions formed after SIV coinfection. Thus, reactivation of LTBI is governed by very early events of SIV infection. Timing of cART is critical in mitigating chronic immune activation. The potential novelty of these findings mainly relates to the development of a robust animal model of human M. tuberculosis/HIV coinfection that allows the testing of underlying mechanisms.

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