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.

Automated summary

Arthroplasty failure, a major complication of joint replacement surgery, can be caused by periprosthetic joint infection (PJI) or non-infectious etiologies. Differentiating between PJI and non-infectious arthroplasty failure (NIAF) is crucial for proper medical and surgical treatment. Various methods, such as culture, nucleic acid amplification tests, and metagenomic techniques, have been successful in distinguishing between the two. Host-based approaches, including biomarkers and immune response profiling, hold promise in overcoming limitations of microbial-based detection methods and shedding light on the causes of arthroplasty failure.