A set of plasmatic microRNA related to innate immune response highly predicts the onset of immune reconstitution inflammatory syndrome in tuberculosis co-infected HIV individuals (ANRS-12358 study)

Abstract

Background: After initiation of combination antiretroviral treatment (cART), HIV-1/tuberculosis coinfected patients are at high risk of developing tuberculosis-associated immune reconstitution inflammatory syndrome (TB-IRIS). MicroRNAs, small molecules of approximately 22 nucleotides, which regulate post-transcriptional gene expression and their profile has been proposed as a biomarker for many diseases. We tested whether the microRNA profile could be a predictive biomarker for TB-IRIS.

Methods: Twenty-six selected microRNAs involved in the regulation of the innate immune response were investigated. Free plasmatic and microRNA-derived exosomes were measured by flow cytometry. The plasma from 74 HIV-1+TB+ individuals (35 IRIS and 39 non-IRIS) at the time of the diagnosis and before any treatment (baseline) of CAMELIA trial (ANRS1295-CIPRA KH001-DAIDS-ES ID10425); 15 HIV+TB- and 23 HIV-TB+, both naïve of any treatment; and 20 HIV-TB- individuals as controls were analysed.

Results: At baseline, both IRIS and non-IRIS HIV+/TB+ individuals had similar demographic and clinical characteristics, including sex, age, body mass index, very low CD4+ cell counts (27 cells/mm³), and plasma HIV RNA load levels (5.76 log copies/ml). Twenty out of 26 plasmatic-microRNAs tested were no different between IRIS and controls. Twelve of the 26 tested microRNAs showed statistically significant differences between IRIS and non-IRIS patients (p-values ranging from p <0.05 to p <0.0001). Among these, five could discriminate between IRIS and non-IRIS individuals using ROC curve analysis (AUC scores ranging from 0.74 to 0.92). The combination of two (hsa-mir-29c-3p and hsa-mir-146a-5p) or three microRNAs (hsa-mir-29c-3p, hsa-mir-29a-3p, and hsa-mir-146a-5p) identified IRIS with 100% sensitivity and high specificity (95% and 97%, respectively).

Conclusion: The combination of at least two or three plasmatic microRNAs known to regulate inflammation and/or cytokine responses could be used as biomarkers to discriminate IRIS from non-IRIS in HIV-TB co-infected individuals at the time of diagnosis and prior to any treatment.

Keywords: HIV; IRIS; biomarkers; exosomes; microRNA; tuberculosis.

Figure 1

Differential expression of twelve plasma microRNAs in IRIS and non-IRIS patients at baseline and controls. The expression level of the tested plasma microRNAs is indicated on the Y-axis. The X-axis represents the study groups. Lower plasma levels were found in IRIS individuals compared to non-IRIS individuals. Non-IRIS individuals have higher plasma levels for the twelve microRNAs : (A) hsa-mir-29a-3p; (B) hsa-mir-29b-3p; (C) hsa-mir-29c-3p; (D) hsa-mir-33a-5p; (E) has-mir-146a-5p; (F) hsa-mir-223-3p; (G) hsa-mir-16-1-3p; (H) hsa-mir-25-3p; (I) hsa-mir-532-5p; (J) has-mir-590-5p; (K) hsa-mir-30e-5p; and (L) has-mir-148a-3p. In contrast, IRIS patients have similar levels compared to TB and HIV controls. Kruskal-Wallis test was used for analysis. Results are presented as median (25%-75% IQR) log₁₀MFI. Statistically significant difference is indicated: * p<0.05; ** p=0.01; *** p=0.001; and **** p<0.0001.

Figure 2

Volcano plot of the differential expression of the tested plasma microRNAs between IRIS and non-IRIS patients at baseline. The circular dots represent the differences in the median value of each plasma microRNA level and its p-value in transformed -log₁₀ between the IRIS and non-IRIS groups. The name of each microRNA is shown on the graph. The x-axis shows the log₁₀ MFI difference in plasma microRNA levels between the IRIS and non-IRIS groups, while the y-axis shows the distribution of p-values (transformed to -log₁₀) obtained from the statistical comparison between the IRIS and non-IRIS groups for each plasma microRNA. A control false discovery rate (FDR) of 1%, represented by a horizontal dotted line, was established to determine the small p-values of the corresponding comparison using the Benjamini method for stacked p-value analysis (GraphPad Prism v10). Significantly different levels are represented by red dots. Among these, six plasma microRNAs with p-values less than 0.0001, shown in the square box, were selected for further analysis.

Figure 3

Plasma levels of microRNAs at IRIS onset and fold change from baseline to IRIS onset in IRIS versus non-IRIS patients. (A) Plasma levels of six of the 26 microRNAs tested are shown. These microRNAs were significantly different between IRIS and non-IRIS subjects. (B) The fold change of ten microRNAs that were significantly different between IRIS and non-IRIS individuals are shown. The Wilcoxon matched-pair test was used for analysis and results are presented as median (25%-75% IQR). Statistically significant differences between study groups are indicated as follows: *p<0.05; **p=0.01; ***p=0.001.

Figure 4

Receiver Operating characteristic (ROC) curve analysis of five microRNAs in IRIS versus non-IRIS patients at baseline. (A) Five plasma microRNAs that were highly significantly different between IRIS (n=35) and non-IRIS (n=39) were selected for ROC curve analysis using GraphPad Prism software version 10. The results of area under the curve (AUC), p-value, sensitivity (SE), specificity (SP) and cut-off (in log₁₀MFI) for each microRNA marker are shown. The arrow on the curve indicates the point of a specific threshold with corresponding sensitivity and specificity. (B) The combinatorial ROC curve analysis of the five microRNAs was performed using the web-based application CombiROC (http://combiroc.eu/). Both combinatorial ROC curves have a sensitivity of 100% and a specificity of more than 94%. The proportions of false positive (FP), false negative (FN), true positive (TP) and true negative (TN) are shown in the pie chart.