Evaluation of Lipocalin-2 as a Biomarker of Periprosthetic Joint Infection.

BACKGROUND: Periprosthetic joint infection (PJI) remains a major clinical challenge. In this study, we evaluated the diagnostic performance of lipocalin-2 (LCN2), a well-characterized neutrophil protein, in synovial fluid to discriminate PJI and aseptic implant failure. METHODS: Synovial fluid from patients with acute or chronic PJI, aseptic failure, or controls was obtained during surgery. LCN2 was quantified using a modified enzyme immunoassay coupled with chemiluminescence (Architect Urine NGAL; Abbott Laboratories). RESULTS: Synovial fluid was collected from 72 patients: 22 (30.6%) proven infections, 22 (30.6%) aseptic implant failures, and 28 (38.8%) controls. Synovial fluid was obtained from the hip in 18 (25%) and knee in 54 (75%) cases. Among infections, there were 16 (22.2%) acute and 6 (8.3%) chronic PJIs. The median (interquartile range) LCN2 concentration in synovial fluid was 1536.5 ng/mL (261.8-12,923) in the infection group, 87.0 (54.8-135) in the aseptic group, and 55 (45-67.8) in the control group (P < .001). LCN2 discriminated nearly perfectly between controls and confirmed infection (area under the receiver operating characteristic 0.98, 95% confidence interval 0.95-1.00). The optimal cut-off value for maximal sensitivity (86.3%) and specificity (77.2%) to discriminate aseptic failure versus proven infection was 152 ng/mL, with an area under the receiver operating characteristic of 0.92 (95% confidence interval 0.84-0.99). CONCLUSION: LCN2 is a potential novel biomarker that may be helpful to inform surgical teams on the potential risk of PJI and optimize specific surgical interventions as it distinguishes between septic and aseptic failure of prosthesis with high sensitivity and specificity.

Extracellular Vesicle Isolation and Characterization from Periprosthetic Joint Synovial Fluid in Revision Total Joint Arthroplasty.

Extracellular vesicles (EVs) comprise an as yet insufficiently investigated intercellular communication pathway in the field of revision total joint arthroplasty (RTJA). This study examined whether periprosthetic joint synovial fluid contains EVs, developed a protocol for their isolation and characterized them with respect to quantity, size, surface markers as well as documented their differences between aseptic implant failure (AIF) and periprosthetic joint infection (PJI). EV isolation was accomplished using ultracentrifugation, electron microscopy (EM) and nanoparticle tracking analysis evaluated EV presence as well as particle size and quantity. EV surface markers were studied by a bead-based multiplex analysis. Using our protocol, EM confirmed the presence of EVs in periprosthetic joint synovial fluid. Higher EV particle concentrations and decreased particle sizes were apparent for PJI. Multiplex analysis confirmed EV-typical surface epitopes and revealed upregulated CD44 and HLA-DR/DP/DQ for AIF, as well as increased CD40 and CD105. Our protocol achieved isolation of EVs from periprosthetic joint synovial fluid, confirmed by EM and multiplex analysis. Characterization was documented with respect to size, concentration and epitope surface signature. Our results indicate various differences between PJI and AIF EVs. This pilot study enables new research approaches and rising diagnostic opportunities in the field of RTJA.

High-Dimensional Analysis of Immune Cell Composition Predicts Periprosthetic Joint Infections and Dissects Its Pathophysiology.

Accurate diagnosis of periprosthetic joint infections (PJI) is one of the most widely researched areas in modern orthopedic endoprosthesis. However, our understanding of the immunological basis of this severe complication is still limited. In this study, we developed a flow cytometric approach to precisely characterize the immune cell composition in periprosthetic joints. Using high-dimensional multi-parametric data, we defined, for the first time, the local immune cell populations of artificial joints. We identified significant differences in the cellular distribution between infected and non-infected samples, and revealed that myeloid-derived suppressor cells (MDSCs) act as potential regulators of infiltrating immune cells in PJI. Further, we developed an algorithm to predict septic and aseptic samples with high sensitivity and specificity, that may serve as an indispensable addition to the current criteria of the Musculoskeletal Infection Society. This study describes a novel approach to flow cytometrically analyze the immune cell infiltrate of joint fluid that not only improves our understanding of the pathophysiology of PJI, but also enables the development of a novel screening tool to predict infection status. Our data further suggest that pharmacological targeting of MDSCs represents a novel strategy for addressing PJI.