Detection of Biomarkers for Prosthetic Infection Type (DEBIT)

The use of medical implants in modern medicine has become an increasingly common occurrence. Hip and knee arthroplasty account for a large number of medical implant surgeries, with over 200,000 performed annually in the UK and Wales (National Joint Registry Report Annual Report; https://reports.njrcentre.org.uk/).

Prosthetic joint infection (PJI) represents one of the most common reasons for failure among hip and knee arthroplasty, with an incidence of around 0.5-2% (increasing significantly in cases of revision arthroplasty) [1-4], and an estimated cost to the NHS for revision surgery of between ~£1,000 and £165,000 (median ~£20,000) [2]. Infection can occur early (with about a third diagnosed within the first 6 months [2]) 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 risks 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.

Currently, no specific 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 [5]. 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) [6,7].

Whilst the profile of microorganisms can differ significantly between patients, the most commonly detected pathogens in a study comparing Germany and the United States were coagulase-negative Staphylococcus (ConS; 20-39%), Staphylococcus aureus (13-31%), Streptococcus (6-7%), Enterococcus (4-7%), anaerobic (1-9%), fungal (0-2%), mycobacterial (0-1%), polymicrobial (3-7%) and other organisms (1-5%), with ~16% culture negative [8].

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 [9,10]. In addition, previous studies have demonstrated that biofilms are present in the majority (57%) of PJI-negative cases where aseptic loosening (osteolysis) has been identified as the primary reason for revision, with up to 76% of cases showing evidence of biofilm formation in cases of severe osteolysis [11]. In contrast, approaches based on next generation sequencing (NGS) demonstrate higher sensitivities (91.7-94%) in both preoperative and intraoperative sample collection [9,10].

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 [6,12].

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 between the following groups: 1) Patients with positive culture results indicative of the presence of pathogenic infection (PJI Likely Group); 2) Patients with clinical indicators of infection, but culture results not diagnostic of infection (PJI Suspected Group); 3) Patients with no clinical indicators of infection and culture results not diagnostic of infection, but revision is required due to e.g. aseptic loosening (osteolysis), periprosthetic fracture, dislocation, etc. (Control Group). Culture results considered diagnostic for infection are those where two or more samples are positive for the presence of the same organism.
We will 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] Drees P, Eckardt A, Gay RE, Gay S, Huber LC. Mechanisms of disease: Molecular insights into aseptic loosening of orthopedic implants. Nat Clin Pract Rheumatol. 2007 Mar;3(3):165-71. doi: 10.1038/ncprheum0428. PMID: 17334339.
[2] Perni S, Bojan B, Prokopovich P. A retrospective study of risk factors, causative micro-organisms and healthcare resources consumption associated with prosthetic joint infections (PJI) using the Clinical Practice Research Datalink (CPRD) Aurum database. PLoS One. 2023 Mar 21;18(3):e0282709. doi: 10.1371/journal.pone.0282709. PMID: 36943830; PMCID: PMC10030031.
[3]Perni S, Prokopovich P. Risk equations for prosthetic joint infections (PJIs) in UK: a retrospective study using the Clinical Practice Research Datalink (CPRD) AURUM and GOLD databases. BMJ Open. 2024 May 7;14(5):e082501. doi: 10.1136/bmjopen-2023-082501. PMID: 38719289; PMCID: PMC11086542.
[4] Atkin B, Dupley L, Chakravorty P, Zafar K, Boden R. Approach to patients with a potential prosthetic joint infection. BMJ. 2022 Mar 21;376:e069502.
[5] Research on microbial biofilms (PA-03-047). NIH, National Heart, Lung, and Blood Institute. December 20, 2002.
[6] McNally M, Sousa R, Wouthuyzen-Bakker M, Chen AF, Soriano A, Vogely HC, Clauss M, Higuera CA, Trebše R. The EBJIS definition of periprosthetic joint infection. Bone Joint J. 2021 Jan;103-B(1):18-25. doi: 10.1302/0301-620X.103B1.BJJ-2020-1381.R1. PMID: 33380199; PMCID: PMC7954183.
[7] McNally M, Sigmund I, Hotchen A, Sousa R. Making the diagnosis in prosthetic joint infection: a European view. EFORT Open Rev. 2023 May 9;8(5):253-263. doi: 10.1530/EOR-23-0044. PMID: 37158373; PMCID: PMC10233812.
[8] Aggarwal VK, Bakhshi H, Ecker NU, Parvizi J, Gehrke T, Kendoff D. Organism profile in periprosthetic joint infection: pathogens differ at two arthroplasty infection referral centers in Europe and in the United States. J Knee Surg. 2014 Oct;27(5):399-406. doi: 10.1055/s-0033-1364102. Epub 2014 Jan 10. PMID: 24414388.
[9] Fang X, Cai Y, Shi T, Huang Z, Zhang C, Li W, Zhang C, Yang B, Zhang W, Guan Z. Detecting the presence of bacteria in low-volume preoperative aspirated synovial fluid by metagenomic next-generation sequencing. Int J Infect Dis. 2020 Oct;99:108-116. doi: 10.1016/j.ijid.2020.07.039. Epub 2020 Jul 25. PMID: 32721535.
[10] Hantouly AT, Alzobi O, Toubasi AA, Zikria B, Al Dosari MAA, Ahmed G. Higher sensitivity and accuracy of synovial next-generation sequencing in comparison to culture in diagnosing periprosthetic joint infection: a systematic review and meta-analysis. Knee Surg Sports Traumatol Arthrosc. 2023 Sep;31(9):3672-3683. doi: 10.1007/s00167-022-07196-9. Epub 2022 Oct 16. PMID: 36244018; PMCID: PMC10435641.
[11] Sierra JM, García S, Martínez-Pastor JC, Tomás X, Gallart X, Vila J, Bori G, Maculé F, Mensa J, Riba J, Soriano A. Relationship between the degree of osteolysis and cultures obtained by sonication of the prostheses in patients with aseptic loosening of a hip or knee arthroplasty. Arch Orthop Trauma Surg. 2011 Oct;131(10):1357-61. doi: 10.1007/s00402-011-1307-4. Epub 2011 May 11. PMID: 21559986.
[12] Parvizi J, Tan TL, Goswami K, Higuera C, Della Valle C, Chen AF, Shohat N. The 2018 Definition of Periprosthetic Hip and Knee Infection: An Evidence-Based and Validated Criteria. J Arthroplasty. 2018 May;33(5):1309-1314.e2. doi: 10.1016/j.arth.2018.02.078. Epub 2018 Feb 26. PMID: 29551303.

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 the implant (osteolysis), damage, 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.