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To the Editor:
Tuberculosis (TB) remains a major threat to health in developing countries and in HIV-1-infected persons (1). In sub-Saharan Africa, the most common etiology of pericardial effusions in HIV-1-infected persons is TB (2). Mortality in patients with tuberculous pericarditis coinfected with HIV-1 can reach 40% in the absence of antiretroviral treatment, and neither antimicrobial therapy of TB alone nor the addition of corticosteroids to chemotherapy resulted in a clinically satisfactory mortality reduction, although corticosteroids significantly reduced hospitalization and incidence of constrictive pericarditis, regardless of HIV status (3). Improved understanding of immunological mechanisms at the disease site is required for the development of more effective host-directed therapies. Because HIV-1 coinfection alters the memory phenotype of CD41 T cells in the pericardium (4), we hypothesized that HIV infection would also affect transcript abundance of key immune mediators in pericardial TB at the disease site. Based on known transcriptional perturbation in extrapulmonary TB (5-9), we selected 42 analytes and performed differential transcriptomic analysis by quantitative reverse transcription polymerase chain reaction in paired blood and pericardial fluid from 27 patients (15 definite and 12 probable patients with tuberculous pericarditis, and 17 patients coinfected with HIV-1). We report a detailed immunopathological characterization of pericardial TB, with 21 analytes also confirmed at the protein level. Methods, patient characteristics (see Tables E1 and E2 in the online supplement), and raw data for all genes in blood and pericardial fluid (Tables E3 and E4) are detailed in the online supplement. Preliminary data have been reported in the form of an abstract (10).
A rigorous data analysis was conducted (Figure 1A). Brie fl y, pairwise fluid versus blood comparisons of individual genes yielded 21 differentially expressed genes in pericardial fluid compared with blood after application of Benjamini-Hochberg multiple testing correction (Tables E4). Next, cluster analysis was employed, with the resulting heat map (Figure E1) showing that strikingly, most blood and pericardial fluid samples from individual patients clustered together. This appeared to be driven by highly correlated gene expression patterns between the two compartments, as further shown in the correlation matrices of blood and pericardial fluid samples (Figure E2). Gene coexpression patterns in blood differed from pericardial fluid, in which pronounced coexpression of fibrosis-associated and neutrophil-associated genes were evident, as well as coexpression...