The diagnostic performance of CD27−CD38+IFN-γ+CD4+/CD4+ and other MTB-specific phenotypic markers for ATB diagnosis was evaluated in this study. The AUC of CD4+IFN-γ+CD38+CD27−/CD4+ for the diagnosis of ATB was the highest (0.890), and the sensitivity and specificity was 0.869 and 0.849 with the optimal cutoff value of CD4+IFN-γ+CD38+CD27−/CD4+ as 1.34 × 10–4. Therefore, CD27−CD38+IFN-γ+CD4+/CD4+ might be an effective biomarker for ATB diagnosis and differential diagnosis in future clinical application.
In recent years, the research on T cell-related molecular markers has been a hot topic. Xu et al.  evaluated CD27 in CD27−IFN-γ+CD4+ T cells for differential diagnosis in TB-unexposed healthy people, TB contacts, and smear-negative TB and concluded that the percentage of CD27−IFN-γ+CD4+ cells can distinguish smear-negative TB patients from the other two groups (AUC = 0.88, sensitivity 82.1%, specificity 80.0%). The study focused on the differential diagnosis of sputum smear-negative ATB and LTB, but many of the smear-negative patients were culture-positive. There are still some ATB patients with both negative smear and culture, and it is challenging to distinguish ATB from LTBI in these patients. Therefore, it is more meaningful to compare ATB with LTBI in sputum culture-negative, which is also one of the key contents of the present study. Latorre et al.  found that the rates of CD27− and CCR4+ in IFN-γ+ TNF-α+CD4+ T cells stimulated by ESAT−6/CFP−10 or PPD had a high diagnostic value and a high diagnostic accuracy between ATB and LTBI, but the ATB and LTBI participants in the study were enrolled within the first 4 weeks of initiation of anti-TB therapy or prophylactic anti-TB therapy, and it is questionable whether anti-TB therapy interfered with the results. Silveira-Mattos et al.  focused on CD38, HLADR, and Ki67. The results showed that the rates of CD38+, HLADR+, or Ki67+ in IFN-γ+CD4+ T cells could differentiate LTBI from ATB. HLADR+ and Ki67+ could identify EPTB and PTB accurately. HIV infection did not affect the ability of these markers to distinguish between ATB and LTBI, EPTB, and PTB. Still, a large proportion of EPTB tends to be combined with PTB, so the comparison is worth considering.
This study focused on the rates of CD27− and CD38+ and their co-occurrence. The results showed that after peripheral blood was stimulated by ESAT 6/CFP10, the rates of CD4+IFN-γ+CD27− and CD4+IFN-γ+CD27− on CD4+ IFN-γ+ cells of ATB were higher than in the other groups. The rate of CD4+IFN-γ+CD38+ in ATB was higher than in LTBI and OD, but there were no differences with NTM and HC groups. The rates of CD4+IFN-γ+CD38+, CD4+IFN-γ+CD27−, and CD4+IFN-γ+CD27−CD38+ subsets in CD4+ cells were higher in ATB than in the other groups. Similar results were observed for the rates of CD4+IFN-γ+CD38+ and CD4+IFN−γ+CD27−, consistent with the previous study mentioned above. Nevertheless, there are few studies on CD4+IFN-γ+CD27−CD38+, and additional studies are necessary to strengthen the results. ROC curves were performed for the proportions of CD4+IFN-γ+CD38+, CD4+IFN-γ+CD27−, and CD4+IFN-γ+CD27−CD38+ in CD4+ and CD4+ IFN-γ+ as diagnostic indexes. According to their AUC, CD4+IFN-γ+CD27−/CD4+IFN-γ+ and CD4+IFN-γ+CD27−CD38+/CD4+IFN-γ+ have diagnostic value for ATB. The AUC of CD4+IFN-γ+CD27−CD38+/CD4+ was 0.890, indicating the highest diagnosis value. The reason that the diagnostic value of each biomarker on CD4+ cells is higher than CD4+IFN-γ+ may be related to the both effect of CD27−CD38+ and IFN-γ, but the exact mechanisms remain to be explored in future research .
As it is difficult to diagnose culture-negative TB clinically, acid-fast sputum staining tests cannot distinguish TB from NTM. In countries and regions with relatively poor public health resources, the Xpert MTB/RIF test is not easily accessible. On the other hand, EPTB is more difficult to diagnose than PTB. The diagnosis is usually made by pathology, excluding other diseases and diagnostic treatment, which is expensive in time and resources. In this study, the results showed no difference of CD4+IFN-γ+CD27−CD38+ on CD4+ neither between TB culture+ and TB culture− nor between PTB and EPTB. Still, the rates were higher in TB culture− and EPTB than in the LTBI, NTM, OD, and HC groups. Therefore, CD4+IFN-γ+CD27−CD38+ cell subsets could be helpful for culture− TB and EPTB diagnosis.
There are several kinds of MTB antigens used in the stimulation, including MTB-PPD (MTB purified protein derivative). The sensitivity of PPD is usually higher than ESAT6/CFP10 etc. for the in vitro stimulation, but MTB-PPD can also stimulate the T cell response for the individuals who have taken BCG Vaccine, which greatly reduce the specificity of the test, especially in China. ESAT6/CFP10 does not exist in BCG Vaccine, so we used ESAT6/CFP10 as stimulator, and in this study we collected at least 100,000 CD4+ cells for each blood sample to ensure the sensitivity of ESAT6/CFP10 alone.
This study has certain limitations. The study aimed to explore the indicators for ATB diagnosis, and the phenotypic markers in the ATB group were compared with the LTBI, NTM, OD, and HC groups because the differential diagnosis of these groups is also of great clinical value. Unfortunately, the sample size for the NTM group was relatively small, mainly because it was a single-center study with a limited sample size. Therefore, multicenter studies with larger samples should be carried out. In addition, this study did not examine the effects of treatments on CD4+IFN-γ+CD27−CD38+ cell subsets. The study by Ahmed  showed Phenotypic changes of MTB-specific T cells are potential surrogate markers for tuberculosis treatment efficacy and can help to discriminate between aTB [profile: CD38(pos), CD27(low)) and latent MTB infection (CD38(neg), CD27(high)], which is consistent with our results. The study also examined changes in markers after anti-TB treatment, which unfortunately was not studied in our study and will be further analyzed in a follow-up study.
In conclusion, CD27−CD38+IFN-γ+CD4+/CD4+ might be a potential biomarker for TB diagnosis and differential diagnosis.