Diagnostic accuracy of interleukin 32γ for tuberculous pleural effusion

Introduction

Tuberculosis is an infectious disease caused by Mycobacterium tuberculosis (Mtb). In 2022, approximately 7.5 million new cases of tuberculosis (TB) were reported globally, resulting in an estimated 1.3 million deaths (1). Tuberculous pleural effusion (TPE) is one of the most common forms of extrapulmonary tuberculosis (2). It is definitively diagnosed through mycobacterial culture of pleural fluid or pleural specimens, although their positive rates are as low as 40% and 65%, respectively (3,4). Another reliable diagnostic method for TPE is the identification of granulomas on pleural biopsy samples (2,5). However, the pleural biopsy is an invasive test with certain surgical risks and complications. Besides, such sophisticated technology may not be available in low resource settings. Therefore, several biochemical assays have been developed to investigate the intrapleural immune response in TPE patients (6). Measuring the concentrations of adenosine deaminase (ADA) and interferon-gamma (IFN-γ) has proven useful for establishing a presumptive diagnosis of TPE compared with non-TPE. However, these biomarkers have limitations in diagnosing TPE; ADA levels may be falsely low in elderly patients and falsely elevated in bacterial pleural co-infections (7). There is considerable variability in the measurement of IFN-γ, including differences in the thresholds for detecting TPE (ranging from 0.3–10 IU/mL and 1.5–300 pg/mL) and in the units used to express its levels in pleural fluid (IU/mL versus pg/mL) (6). Furthermore, the diagnostic accuracy of a single biomarker often decreases in areas of extremely high or low disease prevalence. Therefore, combining different detection methods for pleural effusion can improve the diagnosis of TPE (6,8). Consequently, there is a need for novel and efficient biomarkers for better diagnosis of TPE.

Interleukin 32 (IL-32) is a proinflammatory cytokine that plays a crucial role in the immune response to Mtb. Its expression can be induced by Mtb in peripheral blood mononuclear cells (PBMCs) and purified monocyte populations (9,10). Studies have shown that IL-32 expression is significantly increased in the pulmonary tissue of patients with active tuberculosis, and it enhances the host’s immunity to Mtb (11-13). These findings establish IL-32 as a functional marker for the disease and a potential indicator of the body’s ability to protect itself against active tuberculosis (14). Among its isoforms, IL-32γ is the most active and the only one that can be secreted by cells due to the signal peptide in its exon (13,15), making it the predominant subtype in the pleural fluid. Our previous study demonstrated that IL-32γ facilitates macrophage proliferation and apoptosis, serving as a potential diagnostic marker for TPE (16). However, the limitations of that study included a small sample size and inadequate investigation of disease variability and patient’s age. Given that age may influence immune regulation (17,18), this study, aims to investigate the effect of age as an independent covariate on the diagnostic accuracy of IL-32γ, ADA, and IFN-γ in TPE compared with non-TPE. We present this article in accordance with the STARD reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1676/rc).

Methods

Study populations

The prospective study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the ethics committee of Beijing Chaoyang Hospital, Capital Medical University (No. 2024-ke-15) and informed consent was obtained from all individual participants. Patients with a confirmed diagnosis of pleural effusion were systematically recruited from Beijing Chao-Yang Hospital between June 2019 and May 2022. Only patients who met the predetermined inclusion criteria were included in the study, while those who did not were excluded.

Diagnostic criteria and sample collection

TPE was diagnosed if any of the following criteria were met: positive Mtb culture from pleural effusion or pleural biopsy specimen; the presence of epithelioid cell granuloma and/or caseating granulomas in the pleural biopsy specimen, with no evidence of other granulomatous diseases; exudative effusion accompanied by elevated ADA levels and either moderately or strongly positive skin tests for pure protein derivatives of tuberculin (PPD); positive IFN-γ release test; or a positive Mtb antibody. Malignant pleural effusion (MPE) was diagnosed by the presence of malignant cells in pleural effusion or pleural biopsy specimens. Parapneumonic pleural effusion (PPE) was diagnosed as pleural effusion associated with bacterial pneumonia, bronchiectasis, or lung abscess. Transudative pleural effusion was classified based on Light’s criteria and attributed to other underlying conditions. The exclusion criteria included patients who had received antituberculosis or antitumor therapy prior to admission, those with immunosuppressed conditions (such as diabetes, hepatitis B/C infection, chronic glomerulonephritis, or immunosuppressive therapy), and patients who had undergone any invasive intrathoracic procedures or experienced chest trauma within three months.

Pleural effusion samples were collected through diagnostic thoracentesis or medical thoracoscopy. The samples were centrifuged at 400 g for 6 min, and the supernatant was separated and stored at –80 ℃ for further analysis.

Measurement of IL-32γ, ADA, and IFN-γ

The concentrations of IL-32γ and IFN-γ in the pleural effusion samples were measured using ELISA kits (IL-32γ, DY3040-05, R&D systems, USA; IFN-γ, KHC402, Invitrogen, USA) following the manufacturer’s instructions. ADA levels were determined using an automatic biochemical analyzer (TBA40FR, Toshiba, Japan) with a peroxidase method kit (B1036, XinChuangYuan Biotech, China) following the manufacturer’s instructions.

Statistical analysis

Categorical variables were presented as frequencies, while continuous variables were presented as medians with 25th to 75th percentiles. Significant differences in categorical variables were determined using the Chi-squared (χ²) test. The Mann-Whitney U test and Kruskal-Wallis test were used to evaluate differences between two or multiple groups of continuous variables, respectively. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic value of variables, with the areas under the curves (AUC) calculated and compared using the z-test. All of the statistical analyses were performed using MedCalc 22.0 (MedCalc Software, Belgium) and GraphPad Prism 8.3 (GraphPad Software, USA), with P<0.05 considered to be statistically significant.

Results

Clinical and demographic parameters of patients with pleural effusions

A total of 188 patients with pleural effusions were enrolled in this study. The clinicopathological characteristics of patients with TPE and non-TPE are summarized in Table 1. Non-TPE cases were further classified as MPE, PPE, and transudative pleural effusion. The results showed that patients with TPE were significantly younger than those with non-TPE (P<0.001) across all of the etiological subgroups (P<0.01). However, there was no significant difference in gender distribution between the two groups (Table 1). The concentrations of total protein, glucose, and lactate dehydrogenase, as well as white blood cell (WBC) counts, were significantly higher in TPE than those in non-TPE (Table 1). There was no significant difference in chlorine concentration or the percentages of pleural fluid mononuclear cells (PFMCs) and polymorphonuclear leukocytes (PMNs) in WBC between the two groups (Table 1).

Concentrations of IL-32γ, ADA, and IFN-γ in pleural effusions

Regardless of age, the concentrations of IL-32γ, ADA, and IFN-γ were significantly higher in TPE groups than those in non-TPE groups (P<0.001) (Figure 1A-1C, Table 2). In the different etiological subgroups, these biomarkers were also significantly higher in TPE groups than those in MPE, PPE, or transudative pleural effusion subgroups (P<0.01, Table 2). Based on previous research and our preliminary studies (19,20), 65 years was set as the benchmark for two subgroups: the young group (≤65 years of age) and the elderly group (>65 years of age). In the young group, IL-32γ, ADA, and IFN-γ levels were significantly higher in TPE groups than those in non-TPE groups (P<0.001) (Table 2). Among the different etiological subgroups, these biomarkers were significantly higher in TPE groups than those in MPE subgroup (Table 2). However, no significant differences were observed between TPE and transudative pleural effusion for IL-32γ or ADA. In the elderly group, IL-32γ and ADA levels were significantly higher in TPE groups than those in non-TPE groups (IL-32γ, P<0.001; ADA, P=0.001), but no significant difference was found in IFN-γ levels between the two groups (Table 2). In the different etiological subgroups, IL-32γ levels were significantly higher in TPE than those in MPE, PPE, or transudative pleural effusion subgroups, ADA levels were significantly higher in TPE than those in MPE or transudative pleural effusion subgroups, but no significant difference was found in IFN-γ levels between TPE and the other etiological subgroups (Table 2).

Figure 1 Concentrations and diagnostic capacity of IL-32γ, ADA, and IFN-γ for TPE overall or by age. (A-C) Concentrations of IL-32γ, ADA, and IFN-γ in PE from TPE and non-TPE patients, respectively. (D-F) ROC curves show the diagnostic capacity of the IL-32γ, ADA, and IFN-γ in pleural effusion. (G-I) ROC curves show the diagnostic capacity of the IL-32γ, ADA, and IFN-γ in TPE of patients aged >65 years. ***, P<0.001. ADA, adenosine deaminase; AUC, area under the curve; CI, confidence interval; IL-32γ, interleukin 32γ; IFN-γ, interferon-γ; PE, pleural effusion; ROC, receiver operating characteristic; TPE, tuberculous pleural effusion.

Diagnostic values of IL-32γ, ADA, and IFN-γ in pleural effusions

The diagnostic capacity of IL-32γ, ADA, and IFN-γ for TPE was determined using ROC curve analysis (Table 3). Generally, IL-32γ demonstrated an AUC of 0.812 [95% confidence interval (CI): 0.748–0.865, P<0.001] with a threshold level of 181.56 ng/L (Figure 1D, Table 3). As shown in Table 3, the sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive value (PPV), and negative predictive value (NPV) of IL-32γ were 70.2%, 86.0%, 5.0, 0.4, 92.0%, and 55.7%, respectively. The diagnostic accuracy parameters of ADA and IFN-γ are presented in Figure 1E,1F and Table 3. ADA and IFN-γ demonstrated AUCs of 0.946 (95% CI: 0.904–0.974, P<0.001) and 0.964 (95% CI: 0.926–0.985, P<0.001), respectively.

In the young group, IL-32γ demonstrated an AUC of 0.789 (95% CI: 0.713–0.853, P<0.001) at a threshold of 175.95 ng/L. The AUCs of ADA (0.991; 95% CI: 0.959–1.000) and IFN-γ (0.992; 95% CI: 0.961–1.000) were significantly higher than that of IL-32γ.

Notably, in the elderly group, IL-32γ demonstrated an AUC of 0.984 (95% CI: 0.891–1.000), which was significantly higher than ADA (0.817; 95% CI: 0.672–0.918, P=0.03) and IFN-γ (0.578; 95% CI: 0.420–0.725, P=0.02), at a threshold of 257.44 ng/L (Figure 1G-1I, Table 3). In this group, the sensitivity, specificity, PLR, NLR, PPV, and NPV of IL-32γ were 88.9%, 100.0%, –, 0.1, 100.0%, and 97.2%, respectively (Table 3).

Diagnostic values of combinations of IL-32γ and ADA, IL-32γ and IFN-γ, and ADA and IFN-γ in pleural effusions

In all of the age groups, the AUCs for IL-32γ combined with ADA (0.970, 95% CI: 0.934–0.989) and IL-32γ combined with IFN-γ (0.999, 95% CI: 0.979–1.000) were significantly higher than those of IL-32γ (P<0.001), ADA (P=0.02), or IFN-γ (P=0.02) alone (Figure 2A,2B, Tables 4,5). Similarly, in the elderly group, the AUCs for IL-32γ combined with ADA (0.981, 95% CI: 0.886–1.000) and IL-32γ combined with IFN-γ (1.000, 95% CI: 0.920–1.000) were significantly higher than those of ADA (P=0.04) or IFN-γ (P=0.01) alone (Figure 2C,2D, Tables 4,5). However, in the young group, no significant differences were observed in the AUCs for IL-32γ combined with ADA or IL-32γ combined with IFN-γ compared with ADA or IFN-γ alone (Table 5).

Figure 2 Diagnostic capacity of IL-32γ combined with ADA or IFN-γ for TPE overall or by age. (A,B) ROC curves show the diagnostic capacity of IL-32γ combined with ADA or IFN-γ for TPE in all of the age groups, respectively. (C,D) ROC curves show the diagnostic capacity of IL-32γ combined with ADA or IFN-γ for TPE in the elderly group, respectively. ADA, adenosine deaminase; AUC, area under the curve; CI, confidence interval; IL-32γ, interleukin 32γ; IFN-γ, interferon-γ; ROC, receiver operating characteristic; TPE, tuberculous pleural effusion.

Discussion

IL-32γ is a recently discovered proinflammatory cytokine that plays a crucial role in the immune response to intracellular pathogens such as Mtb (11,12). In this study, the concentration and diagnostic accuracy of IL-32γ were investigated. The results of this study showed that IL-32γ levels were significantly increased in TPE compared with non-TPE; establishing IL-32γ as a useful diagnostic biomarker for TPE, with an AUC of 0.812. Further age-based subgroup analysis revealed that IL-32γ had better diagnostic efficacy in distinguishing TPE from non-TPE in the elderly group (aged >65 years), with an AUC of 0.984, exceeding the diagnostic efficacy of both ADA and IFN-γ. Moreover, combining multiple factors for diagnosis enhanced the diagnostic efficacy between TPE and non-TPE. In all ages, especially in the elderly group (aged >65 years), the diagnostic efficacy of IL-32γ combined with ADA or with IFN-γ was significantly higher than that of ADA or IFN-γ alone. These findings revealed that IL-32γ serve as a potential diagnostic biomarker for distinguishing TPE from non-TPE, especially in elderly patients.

Some studies have shown that IL-32γ levels are significantly higher in TPE than that in non-TPE (16,21). Our previous study suggested that IL-32γ in pleural effusion serves as a potential diagnostic marker for distinguishing TPE from non-TPE (16). However, the limitations of that study included a small sample size and inadequate investigation of disease variability or patient’s age. Therefore, in this study, we collected additional samples to expand the sample size and analyzed the diagnostic efficacy of IL-32γ based on disease etiology and age. Our results showed that the AUC of IL-32γ was lower than that of our previous study (16). These differences may be attributed to variations in the number and characteristics of the patients, as well as the etiology of the pleural effusions analyzed in both studies. Furthermore, we investigated the diagnostic efficacy of IL-32γ in different age subgroups, as well as the efficacy of IL-32γ combined with ADA or IL-32γ combined with IFN-γ in these age groups. Thus, this study provides novel insight into the diagnostic performance of IL-32γ in TPE.

ADA has consistently shown high diagnostic accuracy for TPE since it was first reported in 1978 (22). However, some studies have established a negative correlation between ADA levels in pleural fluid and age. This suggests that ADA serves as a more accurate diagnostic marker in young patients than in older patients (18,23-26). Also, ADA levels in TPE decreased with increasing age, resulting in reduced diagnostic accuracy in older patients. This age-related decline in immune function likely impacts ADA expression (18,25,26). Similarly, the diagnostic accuracy of IFN-γ was influenced by age (18,26). Our results were consistent with prior studies, demonstrating a decline in the diagnostic efficacy of ADA and IFN-γ in the elderly group (aged >65 years). Conversely, IL-32γ exhibited higher diagnostic efficacy in elderly patients compared with younger patients. Additionally, the diagnostic efficacy of IL-32γ was significantly higher than that of ADA and IFN-γ in the elderly group (aged >65 years).

Research has shown that age-related changes in immunity can alter the fundamental mechanisms of the immune system (17,27). This change can be attributed to the decline in immune function with aging in elderly individuals. This decline in immune response results from a reduction in lymphocyte function, including disruption of cell activation, senescence of immunocytes, and disorder in the maturation processes of these cells (28). These findings suggest that the expression and secretion of IL-32γ, ADA, and IFN-γ might be influenced by age. Notably, in elderly patients (age >65 years), diagnostic performance was greatly enhanced using IL-32γ alone or in combination with ADA or IFN-γ, making these markers especially useful for identifying patients with TPE. However, further research is required to investigate the specific mechanism by which age modulates the expression of IL-32γ, ADA, and IFN-γ.

It should be mentioned that the current guideline recommends ADA as the preferred test for the diagnosis of TPE, because it is less expensive and simpler (29). In contrast, despite the superiority of IFN-γ in diagnosing TPE, the high cost and the lack of an accepted cut-off value for the discrimination of TPE limit its daily clinical use (6). Our data demonstrate that the measurement of IL-32γ obtained from pleural fluid may provide high levels of sensitivity and specificity for TPE, which may be applicable for the development of a rapid and non-invasive diagnostic test in low resource settings.

This study has some limitations. First, the number of older patients with TPE and younger patients with non-TPE we included were small, which might have biased the estimation of test accuracy. Second, the number of non-TPE subjects was limited, especially in the PPE or Transudative group, which might also lead to biased results. Therefore, we will consider increasing the sample size to verify the diagnostic accuracy of IL-32γ in pleural effusions. In addition, further studies are required to confirm the mechanism associated with the IL-32γ in pleural effusions.

Conclusions

In conclusion, this study highlights the importance of IL-32γ as a biomarker for diagnosing patients with TPE. The concentration of IL-32γ was significantly elevated in patients with TPE compared with non-TPE. Furthermore, IL-32γ, either alone or in combination with ADA or IFN-γ, exhibited high diagnostic efficacy in distinguishing TPE and non-TPE, especially in patients over the age of 65 years.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1676/rc

Data Sharing Statement: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1676/dss

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1676/prf

Funding: This work was supported by the National Natural Science Foundation of China (82200111), Beijing Scholars Program (048), and Reform and Development Program of Beijing Institute of Respiratory Medicine (Ggyfz202406).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-24-1676/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The prospective study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by the ethics committee of Beijing Chaoyang Hospital, Capital Medical University (No: 2024-ke-15) and informed consent was obtained from all individual participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

1. World Health Organization. Global tuberculosis report 2023. 2023, Geneva: World Health Organization.
2. Light RW. Update on tuberculous pleural effusion. Respirology 2010;15:451-8. [Crossref] [PubMed]
3. Antonangelo L, Faria CS, Sales RK. Tuberculous pleural effusion: diagnosis & management. Expert Rev Respir Med 2019;13:747-59. [Crossref] [PubMed]
4. Wong PC. Management of tuberculous pleuritis: can we do better? Respirology 2005;10:144-8. [Crossref] [PubMed]
5. Porcel JM. Tuberculous pleural effusion. Lung 2009;187:263-70. [Crossref] [PubMed]
6. Skouras VS, Kalomenidis I. Pleural fluid tests to diagnose tuberculous pleuritis. Curr Opin Pulm Med 2016;22:367-77. [Crossref] [PubMed]
7. Porcel JM, Esquerda A, Bielsa S. Diagnostic performance of adenosine deaminase activity in pleural fluid: a single-center experience with over 2100 consecutive patients. Eur J Intern Med 2010;21:419-23. [Crossref] [PubMed]
8. Fei G, Yijun M, Weijiang J, et al. Biomarkers for distinguishing tuberculous pleural effusion from non-tuberculosis effusion: a retrospective study. BMC Infect Dis 2023;23:771. [Crossref] [PubMed]
9. Kundu M, Basu J. IL-32: an emerging player in the immune response network against tuberculosis? PLoS Med 2006;3:e274. [Crossref] [PubMed]
10. Kim SH, Han SY, Azam T, et al. Interleukin-32: a cytokine and inducer of TNFalpha. Immunity 2005;22:131-42. [PubMed]
11. Bai X, Shang S, Henao-Tamayo M, et al. Human IL-32 expression protects mice against a hypervirulent strain of Mycobacterium tuberculosis. Proc Natl Acad Sci U S A 2015;112:5111-6. [Crossref] [PubMed]
12. Bai X, Dinarello CA, Chan ED. The role of interleukin-32 against tuberculosis. Cytokine 2015;76:585-7. [Crossref] [PubMed]
13. Li W, Deng W, Xie J. The Biology and Role of Interleukin-32 in Tuberculosis. J Immunol Res 2018;2018:1535194. [Crossref] [PubMed]
14. Montoya D, Inkeles MS, Liu PT, et al. IL-32 is a molecular marker of a host defense network in human tuberculosis. Sci Transl Med 2014;6:250ra114. [Crossref] [PubMed]
15. Heinhuis B, Koenders MI, van de Loo FA, et al. Inflammation-dependent secretion and splicing of IL-32{gamma} in rheumatoid arthritis. Proc Natl Acad Sci U S A 2011;108:4962-7. [Crossref] [PubMed]
16. Du J, Shao MM, Yi FS, et al. Interleukin 32 as a Potential Marker for Diagnosis of Tuberculous Pleural Effusion. Microbiol Spectr 2022;10:e0255321. [Crossref] [PubMed]
17. Giefing-Kröll C, Berger P, Lepperdinger G, et al. How sex and age affect immune responses, susceptibility to infections, and response to vaccination. Aging Cell 2015;14:309-21. [Crossref] [PubMed]
18. Jiang CG, Wang W, Zhou Q, et al. Influence of age on the diagnostic accuracy of soluble biomarkers for tuberculous pleural effusion: a post hoc analysis. BMC Pulm Med 2020;20:178. [Crossref] [PubMed]
19. Singh S, Bajorek B. Defining 'elderly' in clinical practice guidelines for pharmacotherapy. Pharm Pract (Granada) 2014;12:489. [Crossref] [PubMed]
20. Zheng SC, Huang ZY, Zhai K, et al. Hepatocyte growth factor combined with adenosine deaminase as biomarker for diagnosis of tuberculous pleural effusion. Front Microbiol 2023;14:1181912. [Crossref] [PubMed]
21. Wang X, Yang C, Quan C, et al. The regulation and potential role of interleukin-32 in tuberculous pleural effusion. Front Immunol 2024;15:1342641. [Crossref] [PubMed]
22. Piras MA, Gakis C, Budroni M, et al. Adenosine deaminase activity in pleural effusions: an aid to differential diagnosis. Br Med J 1978;2:1751-2. [Crossref] [PubMed]
23. Zarić B, Kuruc V, Milovančev A, et al. Differential diagnosis of tuberculous and malignant pleural effusions: what is the role of adenosine deaminase? Lung 2008;186:233-40. [Crossref] [PubMed]
24. Tay TR, Tee A. Factors affecting pleural fluid adenosine deaminase level and the implication on the diagnosis of tuberculous pleural effusion: a retrospective cohort study. BMC Infect Dis 2013;13:546. [Crossref] [PubMed]
25. Abrao FC, de Abreu IR, Miyake DH, et al. Role of adenosine deaminase and the influence of age on the diagnosis of pleural tuberculosis. Int J Tuberc Lung Dis 2014;18:1363-9. [Crossref] [PubMed]
26. Korczynski P, Klimiuk J, Safianowska A, et al. Impact of age on the diagnostic yield of four different biomarkers of tuberculous pleural effusion. Tuberculosis (Edinb) 2019;114:24-9. [Crossref] [PubMed]
27. Nikolich-Žugich J. The twilight of immunity: emerging concepts in aging of the immune system. Nat Immunol 2018;19:10-9. [Crossref] [PubMed]
28. Lee SJ, Kim HS, Lee SH, et al. Factors influencing pleural adenosine deaminase level in patients with tuberculous pleurisy. Am J Med Sci 2014;348:362-5. [Crossref] [PubMed]
29. Roberts ME, Rahman NM, Maskell NA, et al. British Thoracic Society Guideline for pleural disease. Thorax 2023;78:s1-s42. [Crossref] [PubMed]