Circulating TIGIT(±)PD1(+)TPH, TIGIT (±) PD1(+)TFH cells are elevated and their predicting role in systemic lupus erythematosus

循环中TIGIT(±)PD1(+)TPH和TIGIT(±)PD1(+)TFH细胞水平升高,它们在系统性红斑狼疮中具有预测作用。

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Abstract

It is well established that increased peripheral helper T cells (TPH) and follicular helper T cells (TFH) was found in systemic lupus erythematosus (SLE) patients. However, the expression patterns and immunomodulatory roles of TIGIT and PD1 on TPH/TFH in SLE are poorly understood. The expression patterns of TIGIT and PD1 on TPH and TFH cells were examined using flow cytometry and their expression patterns in SLE patients were then further evaluated for their correlation with auto-antibodies, disease activity and severity, B cell differentiation. Logistic regression was used to analyze the risk factors. And the receiver operating characteristic curves and logistic regression model were created to evaluate the predicting role in SLE. TIGIT(±)PD1(+)TPH, TIGIT(±)PD1(+)TFH cells in the peripheral blood of SLE patients were upregulated, whereas TIGIT(+)PD1(-)TFH was downregulated. TIGIT (±) PD1(+)TPH, TIGIT (±) PD1(+)TFH cells positively correlated with auto-antibodies production, disease activity and severity, whereas TIGIT(+)PD1(-)TFH cells negatively correlated. TIGIT (±) PD1(+)TPH, TIGIT(-)PD1(+)TFH were positively correlated with the frequency of plasmablasts. Furthermore, higher TIGIT(+)PD1(+)TPH and TIGIT(+)PD1(+)TFH were shown to be risk factors for SLE, whereas TIGIT(+)PD1(-)TFH was found to be a protective factor, according to logistic regression analysis. A further logistic regression model showed that combination of TPH/TFH and routine blood indicators may has potential predicting value for SLE, with AUC of 0.957. The increased TIGIT (±) PD1(+)TPH, increased TIGIT (±) PD1(+)TFH, decreased TIGIT(+)PD1(-)TFH correlates with disease severity and activity, may boost our comprehending of the role of TIGIT and PD1 on TPH/TFH in SLE, and a logistic regression model based on combination of TPH/TFH and routine blood indicators shows prominent value for predicting SLE.

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