The reduction of low peripheral CD4 in patients with HIV-1 is associated with the presence of Mycobacterium tuberculosis bacilli, the production of interleukin 10 (IL-10) and phenotypic changes within granulomas, according to a study published in the Journal of Infectious Diseases.
Collin R Diedrich, PhD, of the Clinical Infectious Diseases Research Initiative at the Institute of Infectious Disease and Molecular Medicine at the University of Cape Town in the Republic of South Africa and colleagues looked at 71 excised cervical lymph nodes from patients who had both HIV-1 and TB, and patients with either HIV-1 or TB. The patients had a range of low peripheral CD4 (pCD4) counts and their adherence to ART was variable.
M tuberculosis numbers increased while CD4 T cells decreased in granulomas in patients with HIV-1. “pCD4 depletion correlated with granulomas that contained fewer CD4 and CD8 T cells, less interferon (IFN)-gamma, more neutrophils, more IL-10 and increased M tuberculosis bacilli. M tuberculosis numbers correlated positively with IL-10 and IFN-alpha, and fewer CD4 and CD8 T cells. ART reduced IL-10 production,” researchers reported in the study.
In an interview with Infectious Disease Advisor, Dr Diedrich said, “The primary takeaway for clinicians is that our understanding of the HIV/M tuberculosis co-infection is coming along, but there is a lot we do not understand. For example, we know that a depletion of peripheral CD4 T cells in HIV-infected persons correlates to an increase in susceptibility to tuberculosis, but we don’t entirely understand how HIV is effecting granulomas within these persons.”
During the interview, Dr Diedrich said there were many studies on the subject, but noted “variations in study methodology and a lack of information on granulomas make it difficult to compare multiple studies to each other and [there are] inherent biases within the work … For example, some studies use vague terminology such as ‘poorly formed granuloma’ or uses 4 stars to indicate bacterial load, which works well when comparing granulomas within that specific study but make it difficult for other researchers to compare their own data too.”
He said that this study “quantitatively examines the total counts of cells or total coverage of cytokines within entire lymph node sections so other researchers could more easily compare my study to their own.” Dr Diedrich emphasized the need to reduce bias, and suggested “better ways to automate cellular and cytokine quantification. That’s why I used Cell Profiler software in my current study. Another way to reduce bias was that I was blinded by patient groups. I required blinding because I didn’t want my own bias to mess with my results.”