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BackgroundThe dysregulated immune response to sepsis still remains unclear. Stratification of sepsis patients into endotypes based on immune indicators is important for the future development of personalized therapies. We aimed to evaluate the immune landscape of sepsis and the use of immune clusters for identifying sepsis endotypes.MethodsThe indicators involved in innate, cellular, and humoral immune cells, inhibitory immune cells, and cytokines were simultaneously assessed in 90 sepsis patients and 40 healthy controls. Unsupervised k-means cluster analysis of immune indicator data were used to identify patient clusters, and a random forest approach was used to build a prediction model for classifying sepsis endotypes.ResultsWe depicted that the impairment of innate and adaptive immunity accompanying increased inflammation was the most prominent feature in patients with sepsis. However, using immune indicators for distinguishing sepsis from bacteremia was difficult, most likely due to the considerable heterogeneity in sepsis patients. Cluster analysis of sepsis patients identified three immune clusters with different survival rates. Cluster 1 (36.7%) could be distinguished from the other clusters as being an “effector-type” cluster, whereas cluster 2 (34.4%) was a “potential-type” cluster, and cluster 3 (28.9%) was a “dysregulation-type” cluster, which showed the lowest survival rate. In addition, we established a prediction model based on immune indicator data, which accurately classified sepsis patients into three immune endotypes.ConclusionWe depicted the immune landscape of patients with sepsis and identified three distinct immune endotypes with different survival rates. Cluster membership could be predicted with a model based on immune data.

BackgroundNovel approaches for tuberculosis (TB) diagnosis, especially for distinguishing active TB (ATB) from latent TB infection (LTBI), are urgently warranted. The present study aims to determine whether the combination of HLA-DR on Mycobacterium tuberculosis (MTB)-specific cells and TB antigen/phytohemagglutinin (TBAg/PHA) ratio could facilitate MTB infection status discrimination.MethodsBetween June 2020 and June 2021, participants with ATB and LTBI were recruited from Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort), respectively. The detection of HLA-DR on MTB-specific cells upon TB antigen stimulation and T-SPOT assay were simultaneously performed on all subjects.ResultsA total of 116 (54 ATB and 62 LTBI) and another 84 (43 ATB and 41 LTBI) cases were respectively enrolled from Qiaokou cohort and Caidian cohort. Both HLA-DR on IFN-γ+TNF-α+ cells and TBAg/PHA ratio showed discriminatory value in distinguishing between ATB and LTBI. Receiver operator characteristic (ROC) curve analysis showed that HLA-DR on IFN-γ+TNF-α+ cells produced an area under the ROC curve (AUC) of 0.886. Besides, TBAg/PHA ratio yield an AUC of 0.736. Furthermore, the combination of these two indicators resulted in the accurate discrimination with an AUC of 0.937. When the threshold was set as 0.36, the diagnostic model could differentiate ATB from LTBI with a sensitivity of 92.00% and a specificity of 81.82%. The performance obtained in Qiaokou cohort was further validated in Caidian cohort.ConclusionsThe combination of HLA-DR on MTB-specific cells and TBAg/PHA ratio could serve as a robust tool to determine TB disease states.

BackgroundThe differential diagnosis between tuberculous meningitis (TBM) and bacterial meningitis (BM) remains challenging in clinical practice. This study aimed to establish a diagnostic model that could accurately distinguish TBM from BM.MethodsPatients with TBM or BM were recruited between January 2017 and January 2021 at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort). The detection for indicators involved in cerebrospinal fluid (CSF) and T-SPOT assay were performed simultaneously. Multivariate logistic regression was used to create a diagnostic model.ResultsA total of 174 patients (76 TBM and 98 BM) and another 105 cases (39 TBM and 66 BM) were enrolled from Qiaokou cohort and Caidian cohort, respectively. Significantly higher level of CSF lymphocyte proportion while significantly lower levels of CSF chlorine, nucleated cell count, and neutrophil proportion were observed in TBM group when comparing with those in BM group. However, receiver operating characteristic (ROC) curve analysis showed that the areas under the ROC curve (AUCs) produced by these indicators were all under 0.8. Meanwhile, tuberculosis-specific antigen/phytohemagglutinin (TBAg/PHA) ratio yielded an AUC of 0.889 (95% CI, 0.840–0.938) in distinguishing TBM from BM, with a sensitivity of 68.42% (95% CI, 57.30%–77.77%) and a specificity of 92.86% (95% CI, 85.98%–96.50%) when a cutoff value of 0.163 was used. Consequently, we successfully established a diagnostic model based on the combination of TBAg/PHA ratio, CSF chlorine, CSF nucleated cell count, and CSF lymphocyte proportion for discrimination between TBM and BM. The established model showed good performance in differentiating TBM from BM (AUC: 0.949; 95% CI, 0.921–0.978), with 81.58% (95% CI, 71.42%–88.70%) sensitivity and 91.84% (95% CI, 84.71%–95.81%) specificity. The performance of the diagnostic model obtained in Qiaokou cohort was further validated in Caidian cohort. The diagnostic model in Caidian cohort produced an AUC of 0.923 (95% CI, 0.867–0.980) with 79.49% (95% CI, 64.47%–89.22%) sensitivity and 90.91% (95% CI, 81.55%–95.77%) specificity.ConclusionsThe diagnostic model established based on the combination of four indicators had excellent utility in the discrimination between TBM and BM.

ObjectivesThe longitudinal and systematic evaluation of immunity in coronavirus disease 2019 (COVID-19) patients is rarely reported.MethodsParameters involved in innate, adaptive, and humoral immunity were continuously monitored in COVID-19 patients from onset of illness until 45 days after symptom onset.ResultsThis study enrolled 27 mild, 47 severe, and 46 deceased COVID-19 patients. Generally, deceased patients demonstrated a gradual increase of neutrophils and IL-6 but a decrease of lymphocytes and platelets after the onset of illness. Specifically, sustained low numbers of CD8+ T cells, NK cells, and dendritic cells were noted in deceased patients, while these cells gradually restored in mild and severe patients. Furthermore, deceased patients displayed a rapid increase of HLA-DR expression on CD4+ T cells in the early phase, but with a low level of overall CD45RO and HLA-DR expressions on CD4+ and CD8+ T cells, respectively. Notably, in the early phase, deceased patients showed a lower level of plasma cells and antigen-specific IgG, but higher expansion of CD16+CD14+ proinflammatory monocytes and HLA-DR−CD14+ monocytic-myeloid-derived suppressor cells (M-MDSCs) than mild or severe patients. Among these immunological parameters, M-MDSCs showed the best performance in predicting COVID-19 mortality, when using a cutoff value of ≥10%. Cluster analysis found a typical immunological pattern in deceased patients on day 9 after onset, which was characterized as the increase of inflammatory markers (M-MDSCs, neutrophils, CD16+CD14+ monocytes, and IL-6) but a decrease of host immunity markers.ConclusionsThis study systemically characterizes the kinetics of immunity of COVID-19, highlighting the importance of immunity in patient prognosis.

BackgroundRapid and effective discrimination between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains a challenge. There is an urgent need for developing practical and affordable approaches targeting this issue.MethodsParticipants with ATB and LTBI were recruited at Tongji Hospital (Qiaokou cohort) and Sino-French New City Hospital (Caidian cohort) based on positive T-SPOT results from June 2020 to January 2021. The expression of activation markers including HLA-DR, CD38, CD69, and CD25 was examined on Mycobacterium tuberculosis (MTB)-specific CD4+ T cells defined by IFN-γ, TNF-α, and IL-2 expression upon MTB antigen stimulation.ResultsA total of 90 (40 ATB and 50 LTBI) and another 64 (29 ATB and 35 LTBI) subjects were recruited from the Qiaokou cohort and Caidian cohort, respectively. The expression patterns of Th1 cytokines including IFN-γ, TNF-α, and IL-2 upon MTB antigen stimulation could not differentiate ATB patients from LTBI individuals well. However, both HLA-DR and CD38 on MTB-specific cells showed discriminatory value in distinguishing between ATB patients and LTBI individuals. As for developing a single candidate biomarker, HLA-DR had the advantage over CD38. Moreover, HLA-DR on TNF-α+ or IL-2+ cells had superiority over that on IFN-γ+ cells in differentiating ATB patients from LTBI individuals. Besides, HLA-DR on MTB-specific cells defined by multiple cytokine co-expression had a higher ability to discriminate patients with ATB from LTBI individuals than that of MTB-specific cells defined by one kind of cytokine expression. Specially, HLA-DR on TNF-α+IL-2+ cells produced an AUC of 0.901 (95% CI, 0.833–0.969), with a sensitivity of 93.75% (95% CI, 79.85–98.27%) and specificity of 72.97% (95% CI, 57.02–84.60%) as a threshold of 44% was used. Furthermore, the performance of HLA-DR on TNF-α+IL-2+ cells for differential diagnosis was obtained with validation cohort data: 90.91% (95% CI, 72.19–97.47%) sensitivity and 68.97% (95% CI, 50.77–82.73%) specificity.ConclusionsWe demonstrated that HLA-DR on MTB-specific cells was a potentially useful biomarker for accurate discrimination between ATB and LTBI.

BackgroundEasily accessible tools that reliably stratify Mycobacterium tuberculosis (MTB) infection are needed to facilitate the improvement of clinical management. The current study attempts to reveal lymphocyte-related immune characteristics of active tuberculosis (ATB) patients and establish immunodiagnostic model for discriminating ATB from latent tuberculosis infection (LTBI) and healthy controls (HC).MethodsA total of 171 subjects consisted of 54 ATB, 57 LTBI, and 60 HC were consecutively recruited at Tongji hospital from January 2019 to January 2021. All participants were tested for lymphocyte subsets, phenotype, and function. Other examination including T-SPOT and microbiological detection for MTB were performed simultaneously.ResultsCompared with LTBI and HC, ATB patients exhibited significantly lower number and function of lymphocytes including CD4+ T cells, CD8+ T cells and NK cells, and significantly higher T cell activation represented by HLA-DR and proportion of immunosuppressive cells represented by Treg. An immunodiagnostic model based on the combination of NK cell number, HLA-DR+CD3+ T cells, Treg, CD4+ T cell function, and NK cell function was built using logistic regression. Based on receiver operating characteristic curve analysis, the area under the curve (AUC) of the diagnostic model was 0.920 (95% CI, 0.867-0.973) in distinguishing ATB from LTBI, while the cut-off value of 0.676 produced a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and specificity of 91.23% (95% CI, 81.06%-96.20%). Meanwhile, AUC analysis between ATB and HC according to the diagnostic model was 0.911 (95% CI, 0.855-0.967), with a sensitivity of 81.48% (95% CI, 69.16%-89.62%) and a specificity of 90.00% (95% CI, 79.85%-95.34%).ConclusionsOur study demonstrated that the immunodiagnostic model established by the combination of lymphocyte-related indicators could facilitate the status differentiation of MTB infection.

BackgroundPneumocystis jiroveci pneumonia (PJP) is the most common opportunistic infection in immunocompromised patients. The accurate prediction of PJP development in patients undergoing immunosuppressive therapy remains challenge.MethodsPatients undergoing immunosuppressive treatment and with confirmed pneumocystis jiroveci infection were enrolled. Another group of matched patients with immunosuppressant treatment but without signs of infectious diseases were enrolled to control group.ResultsA total of 80 (40 PJP, 40 non-PJP) participants were enrolled from Tongji Hospital. None of the patients were HIV positive. The routine laboratory indicators, such as LYM, MON, RBC, TP, and ALB, were significantly lower in PJP patients than in non-PJP patients. Conversely, LDH in PJP patients was significantly higher than in non-PJP controls. For immunological indicators, the numbers of T, B, and NK cells were all remarkably lower in PJP patients than in non-PJP controls, whereas the functional markers such as HLA-DR, CD45RO and CD28 expressed on CD4+ or CD8+ T cells had no statistical difference between these two groups. Cluster analysis showing that decrease of host immunity markers including CD3+, CD4+ and CD8+ T cells, and increase of tissue damage marker LDH were the most typical characteristics of PJP patients. A further established model based on combination of CD8+ T cells and LDH showed prominent value in distinguishing PJP from non-PJP, with AUC of 0.941 (95% CI, 0.892-0.990).ConclusionsA model based on combination of routine laboratory and immunological indicators shows prominent value for predicting the development of PJP in HIV-negative patients undergoing immunosuppressive therapy.

BackgroundInadequate tuberculosis (TB) diagnostics, especially for discrimination between active TB (ATB) and latent TB infection (LTBI), are major hurdle in the reduction of the disease burden. The present study aims to investigate the role of lymphocyte non-specific function detection for TB diagnosis in clinical practice.MethodsA total of 208 participants including 49 ATB patients, 64 LTBI individuals, and 95 healthy controls were recruited at Tongji hospital from January 2019 to October 2020. All subjects were tested with lymphocyte non-specific function detection and T-SPOT assay.ResultsSignificantly positive correlation existed between lymphocyte non-specific function and phytohemagglutinin (PHA) spot number. CD4+ T cell non-specific function showed the potential for differentiating patients with negative T-SPOT results from those with positive T-SPOT results with an area under the curve (AUC) of 0.732 (95% CI, 0.572-0.893). The non-specific function of CD4+ T cells, CD8+ T cells, and NK cells was found significantly lower in ATB patients than in LTBI individuals. The AUCs presented by CD4+ T cell non-specific function, CD8+ T cell non-specific function, and NK cell non-specific function for discriminating ATB patients from LTBI individuals were 0.845 (95% CI, 0.767-0.925), 0.770 (95% CI, 0.683-0.857), and 0.691 (95% CI, 0.593-0.789), respectively. Application of multivariable logistic regression resulted in the combination of CD4+ T cell non-specific function, NK cell non-specific function, and culture filtrate protein-10 (CFP-10) spot number as the optimally diagnostic model for differentiating ATB from LTBI. The AUC of the model in distinguishing between ATB and LTBI was 0.939 (95% CI, 0.898-0.981). The sensitivity and specificity were 83.67% (95% CI, 70.96%-91.49%) and 90.63% (95% CI, 81.02%-95.63%) with the threshold as 0.57. Our established model showed superior performance to TB-specific antigen (TBAg)/PHA ratio in stratifying TB infection status.ConclusionsLymphocyte non-specific function detection offers an attractive alternative to facilitate TB diagnosis. The three-index diagnostic model was proved to be a potent tool for the identification of different events involved in TB infection, which is helpful for the treatment and management of patients.

Bacterial DNAs are constantly detected in atherosclerotic plaques (APs), suggesting that a combination of chronic infection and inflammation may have roles in AP formation. A series of studies suggested that certain Gram-negative bacteria were able to interact with dendritic cell-specific intercellular adhesion molecule-3-grabbing non-integrin [DC-SIGN; cluster of differentiation (CD) 209] or langerin (CD207), thereby resulting in deposition of CD209s at infection sites. We wondered if Proteus mirabilis (a member of Proteobacteria family) could interact with APs through CD209/CD207. In this study, we first demonstrated that CD209/CD207 were also receptors for P. mirabilis that mediated adherence and phagocytosis by macrophages. P. mirabilis interacted with fresh and CD209s/CD207-expressing APs cut from human coronary arteries, rather than in healthy and smooth arteries. These interactions were inhibited by addition of a ligand-mimic oligosaccharide and the coverage of the ligand, as well as by anti-CD209 antibody. Finally, the hearts from an atherosclerotic mouse model contained higher numbers of P. mirabilis than that of control mice during infection-challenging. We therefore concluded that the P. mirabilis interacts with APs in human coronary arteries via CD209s/CD207. It may be possible to slow down the progress of atherosclerosis by blocking the interactions between CD209s/CD207 and certain atherosclerosis-involved bacteria with ligand-mimic oligosaccharides.

Extrapulmonary tuberculosis (EPTB) has become more common in recent years; however, the diagnosis of EPTB remains a challenge. In this study, we analyzed the performance of the ratio of TB-specific antigen (TBAg) to phytohemagglutinin (PHA) (TBAg/PHA ratio) in T-SPOT.TB (T-SPOT) assay for diagnosis and treatment monitoring of EPTB. Between 2012 and 2017, 734 EPTB patients were diagnosed and recruited from Tongji hospital, and 1,137 suspected EPTB patients who had other diagnoses were recruited as non-EPTB controls. To validate the study, another small group of EPTB patients and non-EPTB controls were recruited from Sino-French New City Branch of Tongji Hospital. The positive rate of peripheral blood T-SPOT in EPTB and non-EPTB were 88.15 and 32.28%. In T-SPOT positive patients, the direct T-SPOT results had limited value in distinguishing these two conditions. A further calculation of the TBAg/PHA ratio of T-SPOT showed improved performance in each form of EPTB. If using 0.20 as the threshold value of the TBAg/PHA ratio, the pooled sensitivity and specificity were 70.79 and 91.55% in distinguishing EPTB from non-EPTB. The validation results showed a better performance of the TBAg/PHA ratio in distinguishing these two conditions, with a sensitivity and specificity of 81.82 and 97.56%, respectively. Comparing with directly using T-SPOT results, the TBAg/PHA ratio was less affected by immunosuppression. Furthermore, PHA value reflected immunosuppression and could help to judge the credibility of T-SPOT results in EPTB patients with different immune status. The TBAg/PHA ratio was significantly decreased during anti-tuberculosis (TB) treatment, which suggests that it can also be used to monitor therapeutic efficacy. These data provide new insights into the role of T-SPOT assay in TB disease, and the TBAg/PHA ratio might be a useful tool for diagnosis and treatment monitoring of EPTB.

The function of lymphocytes is the key to reflect the immune status of hosts. Evaluation of lymphocyte function is a useful tool to monitor the effect of immunosuppressive treatment and predict the prognosis of immune-mediated diseases (e.g., cancer, autoimmune diseases, and infectious diseases). As the lymphocytes have various activities, such as activation, cytotoxicity, and cytokine secretion, it is a challenge to evaluate the function of lymphocytes in clinical practice and the reference intervals (RIs) of lymphocyte function are rarely reported. The present study showed that the secretion of IFN-γ was well correlated with the activation, chemotaxis, and cytotoxicity of CD4+, CD8+ T cells, and NK cells, which suggests that IFN-γ production can be used as a symbol of lymphocyte function. We therefore created a simple method to detect the function of CD4+, CD8+ T cells, and NK cells simultaneously according to IFN-γ secretion by using whole blood instead of peripheral blood mononuclear cells. We further established the RIs of lymphocyte function (CD4+ T cells: 15.31–34.98%; CD8+ T cells: 26.11–66.59%; NK cells: 39.43–70.79%) in healthy adults. This method showed good reproducibility for the evaluation of lymphocyte function. The established RIs were suitable for use in other centers based on the validation data. We also validated the RIs in individuals with different immune status, and the results showed that kidney transplant recipients and infants (0–1 year) had a decreased lymphocyte function, whereas T cells in systemic lupus erythematosus patients exhibited an opposite trend. Overall, we have successfully established the RIs of lymphocyte function in healthy adults in a simple way, which might be of important clinical value in the diagnosis, monitoring, and prognosis of immune-related diseases.