Detection Of Developing Joint Infection in prosthetic Hips (DODJI-Hips)

Prosthetic joint infection (PJI) is one of the most common reasons for failure among hip and knee arthroplasty, with an incidence of around 0.39-3.9% [1]. Infection can occur early (within days of surgery) or late (over a year after surgery), and no specific early markers for infection onset exist. Given the significant costs to the NHS for corrective revision surgery, the added suffering and risk to patients from surgery, and the risk of enhancing antimicrobial resistance through the use of broad-spectrum antibiotics, a more specific predictive test for early onset of infection is required.

The use of medical implants in modern medicine has become an increasingly common occurrence, with hip and knee arthroplasty accounting for a large number of medical implant surgeries. Unfortunately, infections frequently result in failure of the implanted device (around 1-2% for knee and hip arthroplasty), requiring extensive revision surgery [REF]. Currently, no predictive biomarkers for PJI exist, and diagnostic tests require infection to have already taken hold and may often be highly invasive. Research conducted by the NIH suggests that accumulation of bacteria (known as biofilms) may account for over 80% of microbial infections in the human body and have been shown to develop on medical implants, such as those used in hip and knee arthroplasty. Biofilms are an accumulation of microorganisms (predominantly bacteria) on a surface, resulting in a functional community which provides antibiotic resistance and a beneficial environment for the growth of pathogenic species that would otherwise be removed by the body’s defences. Bacterial biofilms on medical implants are poorly understood, making treatment very complex.

Clinical criteria have been developed for the determination of PJI, with the most recent being the European Bone and Joint Infection Society (EBJIS) 2021 diagnostic criteria. These were approved and endorsed by the Musculoskeletal Infection Society (MSIS), EBJIS and the European Society of Clinical Microbiology and Infectious Disease (ESCMID) study group for Implant-Associated Infections (ESGIAI) [2,3]. Diagnostic approaches often focus on pathogen detection through culture-based approaches, often prepared from synovial fluid, periprosthetic tissue, or sonication fluid from the surface biofilm. However, culture-based approaches can demonstrate low sensitivity (50-70%) due to fastidious or slow-growing bacteria and use of antibiotics before sample collection [4,5]. In contrast, approaches based on next generation sequencing (NGS) demonstrate higher sensitivities (91.7-94%) in both preoperative and intraoperative sample collection [4,5].

In addition, inflammatory biomarkers such as C-Reactive Protein (CRP), Alpha-defensin, and leukocyte count are commonly targeted for PJI diagnosis. However, given the broad role of these markers across the immune response system, these cannot be solely relied upon as a diagnostic criterion [2,6]. Novel, more specific PJI biomarkers, combined with the power of NGS for less biased characterisation of pathogens, could therefore provide more accurate diagnostic tools for clinicians to more effectively detect and treat PJI.

We aim to identify novel predictive biomarkers for PJI based on assessment of biofilms forming on implants removed in revision surgery, and identification of gene expression changes in the host in response to the presence of infection. We will compare these measures in multiple sample types in patients with culture-positive results indicative of the presence of pathogenic infection (PJI) against those where culture-positive results do not indicate the presence of any known pathogen, or where no infection is suspected (e.g., aseptic loosening) to address four main questions:

1) Can we accurately describe the characteristic microbiome of hip joint prosthetic biofilms?
2) Is there a distinct characteristic microbiome or biofilm structure associated with PJI?
3) Does PJI result in a characteristic gene expression signature in the host?
4) Can we detect such characteristic biofilm members and gene expression signatures as biomarkers from less invasive synovial fluid and blood samples?

References:
[1] https://doi.org/10.3390/jcm12185908
[2] https://doi.org/10.1302/0301-620X.103B1.BJJ-2020-1381.R1
[3] https://doi.org/10.1530/EOR-23-0044
[4] https://doi.org/10.1016/j.ijid.2020.07.039
[5] https://doi.org/10.1007/s00167-022-07196-9
[6] https://doi.org/10.1016/j.arth.2018.02.078

Prosthetic joint infection (PJI) represents one of the most common reasons for failure among hip and knee arthroplasty, with an incidence of around 1-2%. Diagnosing infection can be challenging, as loosening of cement and metal reactions can be impossible to differentiate without invasive procedures. Given the significant costs to the NHS for corrective revision surgery, the added suffering and risks to patients from surgery, and the risk of enhancing antimicrobial resistance through the use of broad-spectrum antibiotics, a predictive test for early diagnosis of infection is required. In this study, we will use nanopore sequencing platforms from Oxford Nanopore Technologies (ONT) to identify potential novel biomarkers for PJI in samples collected from patients undergoing revision surgery. We will explore the microbes present, along with the host’s immunological response, to identify potential novel biomarkers in infected samples compared to those revised for other reasons. We will test for detection of these biomarkers in tissue surrounding the implant, as well as in less invasive sample types (synovial fluid and blood). These will provide novel biomarkers for diagnosis and early treatment of PJI for the future.