MOESM1 of Predictors of switch to and early outcomes on third-line antiretroviral therapy at a large public-sector clinic in Johannesburg, South Africa

Additional file 1: Table S1. Summary of third-line patients transferred in from clinical trials (n=10)

Characteristics of ACTG 5221 (A5221) Study Population.

<p>Characteristics of ACTG 5221 (A5221) Study Population.</p

HBV Genotypes and Baseline Characteristics.

1<p>38 of 48 isolates were successfully sequenced, samples identified as occult HBV infection were excluded from this analysis.</p>2<p>Elevated AST and ALT are defined as AST and ALT>40 IU/ml.</p>3<p>FIB-4 score: Fibrosis 4 score.</p

Phylogenetic Analysis of the 37 study entry samples (six digit number, two letters) with HBV pol sequence results and Genbank reference sequences (accession number genotype) at baseline.

<p>From this tree 32 sequences cluster with the reference genotype A sequences, four cluster with the genotype D reference sequences and one with the genotype E reference sequences. Bootstrap values on the tree referred to how rooted the phylogenetic tree is at the branch i.e. level of confidence. Note that samples identified as occult HBV infection are excluded from this analysis. 37 isolates were sequenced at baseline, one isolate was sequenced after baseline and was thus not included in the tree.</p

PD-1 and CTLA-4 expression on PPD-specific CD4 T-cells in response to TB treatment.

<p><b>A.</b> Representative plot showing the gating scheme used to identify PD-1, CTLA-4, and 2B4 expression on PPD-specific CD4 T-cells. Single, live, CD3⁺, CD4⁺ cells were gated for CD27 and CD45RO. The naïve CD4 T cell population was identified (CD27⁺CD45RO^-) and selected to set gates for PD-1, CTLA-4 and 2B4 as this population typically does not express inhibitory molecules. These gates were then applied to PPD-specific and total CD4 T-cell populations. <b>B.</b> Expression of PD-1, CTLA-4, and 2B4 on PPD-specific CD4 T-cells in untreated and treated TB disease. <b>C.</b> Correlation between baseline CD4 T-cell count and frequency of PD-1 and CTLA-4 expression on PPD-specific CD4 T-cells in untreated and treated TB disease. Lines of best fit, along with Spearman’s rank correlation coefficient and corresponding p-values are shown <b>D.</b> Expression of PD-1, CTLA-4, and 2B4 on CMV-specific CD4 T-cells in untreated and treated TB disease in our HIV-TB and TB cohorts. <b>E</b>. Expression of PD-1, CTLA-4, and 2B4 on total CD4 T-cells in untreated and treated TB disease in our HIV-TB and TB cohorts. <b>F</b>. Bar graph depicts the co-expression patterns of PD-1, CTLA-4, and 2B4 on PPD-specific CD4 T-cells in untreated and treated TB disease in our HIV-TB and TB cohorts. To assess expression of inhibitory molecules on PPD and CMV-specific CD4 T-cells, only samples with at least 50 cytokine positive cells and 2-fold higher responses than negative control samples were included to allow for a statistically valid analysis. * denotes p<0.05, ** p<0.01, *** p<0.001 by Wilcoxon matched-pairs signed rank test. $denotes p<0.05,$ $p<0.01,$ $$ p<0.001 by Mann-Whitney test.</p

TB therapy alters maturation phenotype of PPD-specific CD4 T-cells.

<p><b>A.</b> Representative example of differentiation marker expression on PPD-specific CD4 T-cells. PPD-specific CD4 T-cells (red dots) are overlaid onto density plots of CD27 and CD45RO and CD27 and CD57, gated on total CD4 T-cells. <b>B.</b> Frequency of PPD-specific CD4 T-cells expressing CD27⁺CD45RO⁺ (CM), CD27^-CD45RO⁺ (EM), and CD57⁺ (TD) phenotypes. <b>C.</b> Correlation between baseline CD4 T-cell count and frequency of PPD-specific CD4 T-cells expressing CM and TD phenotypes in untreated and treated TB disease. Lines of best fit, along with Spearman’s rank correlation coefficient and corresponding p-values are shown <b>D.</b> Frequency of CMV-specific CD4 T-cells expressing CM, EM, and TD phenotypes in our HIV-TB and TB cohorts. <b>E.</b> Frequency of naïve, CM, EM, and TD subsets on total CD4 T-cells in untreated and treated TB disease in our HIV-TB and TB cohorts. To assess maturation phenotype on PPD and CMV-specific CD4 T-cells, only samples with at least 50 cytokine positive cells and 2-fold higher responses than negative control samples were included to allow for a statistically valid analysis. The Wilcoxon matched-pairs signed rank test was used for paired comparisons (HIV-TB cohort) while the Mann-Whitney test was used to analyze unpaired data (TB cohort and comparisons between cohorts). * denotes p<0.05, ** p<0.01, *** p<0.001 by Wilcoxon matched-pairs signed rank test. $denotes p<0.05,$ $p<0.01,$ $$ p<0.001 by Mann-Whitney test.</p

TB therapy alters the functional profile of PPD-specific CD4 T-cells.

<p><b>A.</b> Representative plot showing the gating scheme used to identify cytokine/chemokine positive cells. Single, live, CD3⁺, CD4⁺ T cells were gated for CD27 and CD45RO to identify the total CD4 memory population. Cytokine/chemokine gates were then applied to the total CD4 memory population to identify cytokine/chemokine positive cells. <b>B.</b> Total frequency of IFN-γ, TNF-α, IL-2, and MIP-1β produced by memory CD4 T-cells in untreated and treated TB disease within our HIV-TB and TB cohorts. Background cytokine/chemokine production from the negative control sample was subtracted. <b>C.</b> Pie graph displaying the proportion of cytokine/chemokine⁺ CD4 T-cells producing all 4 cytokines/chemokines (light grey wedge) or any combination of 3 cytokines/chemokines (medium gray), 2 cytokines/chemokines (dark grey), or a single cytokine/chemokine (black wedge) in untreated and treated TB disease. The bar graph depicts the relative contribution of each cytokine/chemokine producing subset to the overall PPD-specific CD4 T-cell response. “G” denotes IFN-γ, “2” denotes IL-2, “T” denotes TNF-α, and “M” denotes MIP-1β. For all bar graphs bars represent the interquartile range (IQR), horizontal lines denote the median, and whiskers the 10^th and 90^th percentiles. Solid bars represent our HIV-TB cohort, patterned bars represent our TB cohort. Light gray represents untreated TB disease while dark gray represents treated TB disease. Statistical analysis was performed using the Wilcoxon matched-pairs signed rank test for paired data (HIV-TB cohort) and the Mann-Whitney test for unpaired data (TB cohort or comparisons between cohorts).* denotes p<0.05, ** p<0.01, *** p<0.001 by Wilcoxon matched-pairs signed rank test. $denotes p<0.05,$ $p<0.01,$ $$ p<0.001 by Mann-Whitney test.</p

Baseline Demographic and Clinical Characteristics.

1<p>Comparing HBsAg-positive to HBsAg-negative subjects.</p>2<p>Elevated AST and ALT are defined as AST and ALT>40 IU/ml. ALT values are available for 47/48 HBsAg-positive, 19/20 HBeAg-positive, and 10/12 occult HBV subjects.</p>3<p>HBV viral loads available for 11/12 occult HBV subjects.</p>4<p>ALT and HBV viral loads available for 46/48 HBsAg-positive subjects, 18/20 HBeAg-negative, and 9/12 occult HBV subjects.</p>5<p>FIB-4 score: Fibrosis 4 score, available for 687 HIV-positive but HBsAg-negative, 47/48 HBsAg-positive subjects, and 19/20 HBeAg-negative subjects.</p

Identification of a 251 Gene Expression Signature That Can Accurately Detect <i>M. tuberculosis</i> in Patients with and without HIV Co-Infection

<div><p>Background</p><p>Co-infection with tuberculosis (TB) is the leading cause of death in HIV-infected individuals. However, diagnosis of TB, especially in the presence of an HIV co-infection, can be limiting due to the high inaccuracy associated with the use of conventional diagnostic methods. Here we report a gene signature that can identify a tuberculosis infection in patients co-infected with HIV as well as in the absence of HIV.</p><p>Methods</p><p>We analyzed global gene expression data from peripheral blood mononuclear cell (PBMC) samples of patients that were either mono-infected with HIV or co-infected with HIV/TB and used support vector machines to identify a gene signature that can distinguish between the two classes. We then validated our results using publically available gene expression data from patients mono-infected with TB.</p><p>Results</p><p>Our analysis successfully identified a 251-gene signature that accurately distinguishes patients co-infected with HIV/TB from those infected with HIV only, with an overall accuracy of 81.4% (sensitivity = 76.2%, specificity = 86.4%). Furthermore, we show that our 251-gene signature can also accurately distinguish patients with active TB in the absence of an HIV infection from both patients with a latent TB infection and healthy controls (88.9–94.7% accuracy; 69.2–90% sensitivity and 90.3–100% specificity). We also demonstrate that the expression levels of the 251-gene signature diminish as a correlate of the length of TB treatment.</p><p>Conclusions</p><p>A 251-gene signature is described to (a) detect TB in the presence or absence of an HIV co-infection, and (b) assess response to treatment following anti-TB therapy.</p></div

Summary of TB Diagnostic Tests.

<p>Sensitivities of currently used TB diagnostic tests.</p