Multiparameter immunoprofiling for the diagnosis and differentiation of progressive versus nonprogressive nontuberculous mycobacterial lung disease-A pilot study

Abstract

Clinical prediction of nontuberculous mycobacteria lung disease (NTM-LD) progression remains challenging. We aimed to evaluate antigen-specific immunoprofiling utilizing flow cytometry (FC) of activation-induced markers (AIM) and IFN-γ enzyme-linked immune absorbent spot assay (ELISpot) accurately identifies patients with NTM-LD, and differentiate those with progressive from nonprogressive NTM-LD. A Prospective, single-center, and laboratory technician-blinded pilot study was conducted to evaluate the FC and ELISpot based immunoprofiling in patients with NTM-LD (n = 18) and controls (n = 22). Among 18 NTM-LD patients, 10 NTM-LD patients were classified into nonprogressive, and 8 as progressive NTM-LD based on clinical and radiological features. Peripheral blood mononuclear cells were collected from patients with NTM-LD and control subjects with negative QuantiFERON results. After stimulation with purified protein derivative (PPD), mycobacteria-specific peptide pools (MTB300, RD1-peptides), and control antigens, we performed IFN-γ ELISpot and FC AIM assays to access their diagnostic accuracies by receiver operating curve (ROC) analysis across study groups. Patients with NTM-LD had significantly higher percentage of CD4+/CD8+ T-cells co-expressing CD25+CD134+ in response to PPD stimulation, differentiating between NTM-LD and controls. Among patients with NTM-LD, there was a significant difference in CD25+CD134+ co-expression in MTB300-stimulated CD8+ T-cells (p <0.05; AUC-ROC = 0.831; Sensitivity = 75% [95% CI: 34.9-96.8]; Specificity = 90% [95% CI: 55.5-99.7]) between progressors and nonprogressors. Significant differences in the ratios of antigen-specific IFN-γ ELISpot responses were also seen for RD1-nil/PPD-nil and RD1-nil/anti-CD3-nil between patients with nonprogressive vs. progressive NTM-LD. Our results suggest that multiparameter immunoprofiling can accurately identify patients with NTM-LD and may identify patients at risk of disease progression. A larger longitudinal study is needed to further evaluate this novel immunoprofiling approach.

Fig 1. Study flowchart of patient inclusion and exclusion criteria.

Fig 2. Testing results of IFN-γ ELISpot in controls and NTM-LD patients.

IFN-γ ELISpot results of RD1 peptides (A), PPD (B), MTB300 peptide pool (C) and Candida antigen (D), MTB300-RD1 (E), ratios of net RD1/PPD (F), MTB300/PPD (G), MTB300/Candida (H) and PPD/Candida (I). The response by Ag-specific cells was background subtracted for each donor. Differences between the groups were compared using a Mann–Whitney U-test. Statistically significant differences were represented as p value. ns = nonsignificant (P>.05). The boxes show the median and interquartile range, and the whiskers show minimum and maximum values.

Fig 3. Frequency of CD3⁺CD4⁺CD25⁺CD134⁺ T cells in controls, nonprogressive and progressive NTM-LD.

Representative flow cytometry plots showing the expression of CD3⁺CD4⁺CD25⁺CD134⁺ T cells in response to mycobacterial antigens in Controls, nonprogressive and progressive NTM-LD patients respectively. PBMCs of control subjects and NTM-LD patients were stimulated either with Candida antigen, ESAT-6/CFP-10 (RD1) peptides, MTB300 and PPD or left unstimulated for 40 hours and measured CD25 and CD134 response by flow cytometry. The percentage of CD4⁺CD25⁺CD134⁺ T cells was shown in the upper right quadrants in each plot. Upper panel–control subject (ID178); middle panel–nonprogressive NTM-LD (ID225); Lower panel–progressive NTM-LD (ID292).

Fig 4. Testing results of flow cytometric CD4⁺/CD8⁺CD25⁺CD134⁺ T cells in controls and NTM-LD cohorts.

Flow cytometric detection of the percentage of CD3⁺CD4⁺CD25⁺CD134⁺ against RD1 peptides (A), PPD (B), MTB300 peptide pool (C), Candida antigen (D) and anti-CD3 (E). Percentage of CD3⁺CD8⁺CD25⁺134⁺ in RD1 peptides (F), PPD (G), MTB300 peptide pool (H) and anti-CD3 (I). The response by stimulated cells was background subtracted for each donor. Differences between the groups were compared using a Mann–Whitney U-test. ns = nonsignificant (P<0.05). Horizontal line represents median, and upper and lower boundaries of box represent 75th and 25th percentile. The whiskers extend from each quartile to the minimum and maximum.

Fig 5. Diagnostic performance of IFN-γ ELISpot and CD25⁺CD134⁺ T cells in NTM-LD diagnosis.

Receiver operating characteristics curve (ROC) plots show the diagnostic accuracy of IFN-γ ELISpot (5A) and CD25⁺CD134⁺ markers (5B) in discriminating between control subjects and NTM-LD patients.

Fig 6. Testing results of IFN-γ ELISpot and flow cytometric CD4⁺/CD8⁺CD25⁺CD134⁺ T cells in nonprogressive and progressive NTM-LD.

ELISpot results of MTB300-RD1 sfu (A), net ratios of RD1/PPD sfu (B), MTB300/Candida sfu (C) and RD1/antiCD3 sfu (D). Flow cytometric detection of percentage of CD3⁺CD4⁺CD25⁺CD134⁺ against RD1 peptides (E), PPD (F), MTB300 peptide pool (G). Percentage of CD3⁺CD8⁺CD25⁺134⁺ with PPD (H) and MTB300 peptide pool (I) The response by stimulated cells was background subtracted for each donor. Differences between the groups were compared using a Mann–Whitney U-test. ns = nonsignificant (P<0.05). The boxes show the median and interquartile range, and the whiskers show minimum and maximum values.

Fig 7. Diagnostic performance of IFN-γ ELISpot and CD8⁺CD25⁺CD134⁺ for predicting progressive NTM-LD.

Receiver operating characteristics curve (ROC) were performed for ratios of IFN-γ ELISpot RD1/PPD, MTB300/Candida, RD1/anti-CD3 sfu, and MTB300-RD1 sfu; and MTB300 specific FC CD8⁺CD25⁺CD134⁺ markers in distinguishing progressive from nonprogressive NTM-LD patients.