Characterization of multiple soluble immune checkpoints in individuals with different Mycobacterium tuberculosis infection status and dynamic changes during anti-tuberculosis treatment

Abstract

Background Immune checkpoints are crucial for the maintenance of subtle balance between self-tolerance and effector immune responses, but the role of soluble immune checkpoints (sICs) in Mycobacterium tuberculosis (M. tb) infection remains unknown. We assessed the levels of multiple sICs in individuals with distinct M. tb infection status, and their dynamic changes during anti-tuberculosis treatment. Methods We enrolled 24 patients with pulmonary tuberculosis, among which 10 patients were diagnosed with tuberculous pleurisy (TBP), 10 individuals with latent tuberculosis infection (LTBI), and 10 healthy volunteers from Wuxi Fifth People’s Hospital and Huashan Hospital between February 2019 and May 2021. Plasma concentrations of thirteen sICs were measured at enrollment and during anti-tuberculosis treatment using luminex-based multiplex assay. sICs levels in tuberculous pleural effusion (TPE) and their relations to laboratory test markers of TPE were also assessed in TBP patients. Results The circulating levels of sPD-1, sPD-L1, sCTLA-4, sBTLA, sGITR, sIDO, sCD28, sCD27 and s4-1BB were upregulated in tuberculosis patients than in healthy controls. A lower sPD-L1 level was found in LTBI individuals than in tuberculosis patients. In TBP patients, the levels of sPD-1, sPD-L2, sCD28, sCD80, sCD27, sTIM-3, sLAG-3, sBTLA, s4-1BB and sIDO increased significantly in TPE than in plasma. In TPE, sBTLA and sLAG-3 correlated positively with the adenosine deaminase level. sIDO and sCD80 correlated positively with the lactate dehydrogenase level and the percentage of lymphocytes in TPE, respectively. Meanwhile, sCD27 correlated negatively with the specific gravity and protein level in TPE. In tuberculosis patients, the circulating levels of sBTLA and sPD-L1 gradually declined during anti-tuberculosis treatment. Conclusions We characterized the changing balance of sICs in M. tb infection. And our results revealed the relations of sICs to laboratory test markers and treatment responses in tuberculosis patients, indicating that certain sICs may serve as potential biomarkers for disease surveillance and prognosis of tuberculosis.

The rs11684747 and rs55790676 SNPs of ADAM17 influence tuberculosis susceptibility and plasma levels of TNF, TNFR1, and TNFR2

“…Recent research indicates that TIM-3 acts as an exhaustion marker in CD4+ and CD8+ T cells during Mtb infection (Jayaraman et al, 2016). Interestingly, we found higher levels of TIM-3 in ATB patients and those homozygous to the rs12692386 SNP of ADAM17, suggesting its involvement in chronic infection, which is in line with previous reports (Chen et al, 2022).…”

Soluble immune checkpoint molecules in patients with antineutrophil cytoplasmic antibody-associated vasculitis

“…However, we speculated that chronic immune activation status may influence dysregulation of checkpoint molecules. Dysregulation of soluble immune checkpoint molecules has also been reported in infectious disease other than autoimmune diseases such as hepatitis B virus (HBV), human immunodeficiency virus (HIV), and tuberculosis infection 28 – 30 . Although detailed function, regulation and mechanism of soluble immune checkpoint molecules in each disease are largely unknown, these findings suggest the possibility that chronic immune activation status may influence dysregulation of checkpoint molecules.…”

From simple to complex: Protein‐based biomarker discovery in tuberculosis

“…We further discuss different sample types, experimental platforms, and briefly the signaling pathways associated with the identified host-derived proteins. [12,13], [17], [29], [63] # , [66], [103][104][105][106][107][108][109][110][111][112][113][114] Mass spectrometry [22][23][24], [25] # , [115][116][117][118][119][120][121][122][123][124][125][126][127]] SOMAscan [19,20] Other [21], [70], [78], [128,129] Sputum/Saliva ELISA [7] Multiplex bead assay [14], [29] Mass spectrometry [26], [30], [31] # , [32]<...…”