Sonicate Fluid Cellularity Predicted by Transcriptomic Deconvolution Differentiates Infectious from Non-Infectious Arthroplasty Failure

Identification of immune infiltration and immune-related biomarkers of periprosthetic joint infection

Background

The immune response associated with periprosthetic joint infection (PJI) is an emerging but relatively unexplored topic. The aim of this study was to investigate immune cell infiltration in periprosthetic tissues and identify potential immune-related biomarkers.

Methods

The GSE7103 dataset from the GEO database was selected as the data source. Differentially expressed genes (DEGs) and significant modular genes in weighted correlation network analysis (WGCNA) were identified. Functional enrichment analysis and transcription factor prediction were performed on the overlapping genes. Next, immune-related genes from the ImmPort database were matched. The protein-protein interaction (PPI) analysis was performed to identify hub genes. CIBERSORTx was used to evaluate the immune cell infiltration pattern. Spearman correlation analysis was used to evaluate the relationship between hub genes and immune cells.

Results

A total of 667 DEGs were identified between PJI and control samples, and 1847 PJI-related module genes were obtained in WGCNA. Enrichment analysis revealed that the common genes were mainly enriched in immune and host defense-related terms. TFEC, SPI1, and TWIST2 were the top three transcription factors. Three hub genes, SDC1, MMP9, and IGF1, were identified in the immune-related PPI network. Higher levels of plasma cells, CD4+ memory resting T cells, follicular helper T cells, resting mast cells, and neutrophils were found in the PJI group, while levels of M0 macrophages were lower. Notably, the expression of all three hub genes correlated with the infiltration levels of seven types of immune cells.

Conclusion

The present study revealed immune infiltration signatures in the periprosthetic tissues of PJI patients. SDC1, MMP9, and IGF1 were potential immune-related biomarkers for PJI.

Periprosthetic joint infection and immunity: Current understanding of host-microbe interplay

Periprosthetic joint infection (PJI) is a major complication of total joint arthroplasty. Even with current treatments, failure rates are unacceptably high with a 5-year mortality rate of 26%. Majority of the literature in the field has focused on development of better biomarkers for diagnostics and treatment strategies including innovate antibiotic delivery systems, antibiofilm agents, and bacteriophages. Nevertheless, the role of the immune system, our first line of defense during PJI, is not well understood. Evidence of infection in PJI patients is found within circulation, synovial fluid, and tissue and include numerous cytokines, metabolites, antimicrobial peptides, and soluble receptors that are part of the PJI diagnosis workup. Macrophages, neutrophils, and myeloid-derived suppressor cells (MDSCs) are initially recruited into the joint by chemokines and cytokines produced by immune cells and bacteria and are activated by pathogen-associated molecular patterns. While these cells are efficient killers of planktonic bacteria by phagocytosis, opsonization, degranulation, and recruitment of adaptive immune cells, biofilm-associated bacteria are troublesome. Biofilm is not only a physical barrier for the immune system but also elicits effector functions. Additionally, bacteria have developed mechanisms to evade the immune system by inactivating effector molecules, promoting killing or anti-inflammatory effector cell phenotypes, and intracellular persistence and dissemination. Understanding these shortcomings and the mechanisms by which bacteria can subvert the immune system may open new approaches to better prepare our own immune system to combat PJI. Furthermore, preoperative immune system assessment and screening for dysregulation may aid in developing preventative interventions to decrease PJI incidence.

Activated mast cells in periprosthetic joint infection-associated tissue

Background

Periprosthetic joint infection (PJI) is a devastating complication of total joint arthroplasty surgery. Increased densities of activated mast cells have been predicted to be present in PJI compared to non-infectious arthroplasty failure based on analysis of transcriptomic data, but their presence in PJI-associated periprosthetic tissues has not been visually confirmed.

Objective

This preliminary study investigated the presence and activation status of mast cells in periprosthetic tissues associated with PJI.

Methods

Periprosthetic tissues from five PJI cases and three arthroplasty failures due to instability and one due to stiffness were immunohistochemically stained using tryptase and microscopically evaluated to enumerate mast cells and evaluate overall activation status within tissue samples. Mast cell activation was evidenced by the release of tryptase into the extracellular space surrounding mast cells.

Results

Mast cells were found in all samples, with average cellular densities of 22 and 26 cells/mm2 tissue in PJI and uninfected samples, respectively (p, 0.6610). Apparent mast cell activation and degranulation was readily observed throughout each of the five PJI samples studied, but not in any of the uninfected samples studied.

Conclusion

While preliminary, these findings provide evidence for a role of mast cells in the immune response in PJI. Additional investigation of the role of mast cells during arthroplasty failure is warranted, providing a better understanding of underlying biology and informing potential diagnostic and treatment targets.

Profiling the Immune Response to Periprosthetic Joint Infection and Non-Infectious Arthroplasty Failure

Arthroplasty failure is a major complication of joint replacement surgery. It can be caused by periprosthetic joint infection (PJI) or non-infectious etiologies, and often requires surgical intervention and (in select scenarios) resection and reimplantation of implanted devices. Fast and accurate diagnosis of PJI and non-infectious arthroplasty failure (NIAF) is critical to direct medical and surgical treatment; differentiation of PJI from NIAF may, however, be unclear in some cases. Traditional culture, nucleic acid amplification tests, metagenomic, and metatranscriptomic techniques for microbial detection have had success in differentiating the two entities, although microbiologically negative apparent PJI remains a challenge. Single host biomarkers or, alternatively, more advanced immune response profiling-based approaches may be applied to differentiate PJI from NIAF, overcoming limitations of microbial-based detection methods and possibly, especially with newer approaches, augmenting them. In this review, current approaches to arthroplasty failure diagnosis are briefly overviewed, followed by a review of host-based approaches for differentiation of PJI from NIAF, including exciting futuristic combinational multi-omics methodologies that may both detect pathogens and assess biological responses, illuminating causes of arthroplasty failure.