Serum soluble PD-1 plays a role in predicting infection complications in patients with acute pancreatitis

Abstract

Background: Most of acute pancreatitis (AP) are mild and self-limiting, however, 15%–20% of patients develop severe acute pancreatitis (SAP) or moderately acute pancreatitis (MSAP) with local or systemic complications. Infection complications (ICs) result in 40%–70% morbidity and high mortality rates among SAP and MSAP patients. It is more important to early recognize of ICs of MSAP or SAP. Several studies have indicated that serum soluble programmed cell death protein (sPD-1) or programmed cell death 1 ligand (sPD-L1) levels were higher in patients with severe sepsis than in healthy volunteers and have a predictive capacity for mortality. However, the role of serum sPD-1/sPD-L1 in AP remains unclear. This study aimed to investigate whether the ICs of AP patients is associated with their sPD-1 and sPD-L1 levels, which were determined via enzyme-linked immunosorbent assay of peripheral blood samples from 63 MSAP and SAP patients and 30 healthy volunteers. Results: The serum sPD-1 levels in AP patients on Days 1, 3, and 10 after onset were significantly increased in a time-dependent manner compared with that in healthy volunteers. Moreover, the AP patients with ICs had significantly higher serum sPD-1 levels than the AP without ICs. While serum sPD-L1 levels in AP were similar to that in healthy volunteers. Besides, serum levels of sPD-1/sPD-L1 were negatively correlated with circulating lymphocytes. Univariate and multivariate regression analyses showed that the upregulated serum sPD-1 level was an independent risk factor for ICs in AP. The area under the receiver operating characteristics curve indicated that combination with Acute Physiology and Chronic Health Evaluation II score and serum sPD-1 level had a high accuracy in predicting ICs in AP. Conclusion: Serum sPD-1/sPD-L1 may be involved in the immunosuppressive process in AP. Moreover, the serum sPD-1 level may be an independent risk factor for predicting ICs in AP patients.