Developing a molecular tool to stratify the acute joint presentation: facilitating early diagnosis of septic arthritis.

Keywords: Sepsis, biomarker, arthritis, diagnosis

Abstract:
Atraumatic acute joint swelling, a limping child or a child unwilling to weight-bear/move a joint due to pain are common presentations to the Emergency Department. The key diagnostic differential is between septic arthritis, which is defined as inflammation of a joint secondary to bacterial infection, and non-infectious causes of inflammation e.g. gout and transient synovitis. However, distinguishing between infectious and non-infectious arthritis represents a diagnostic challenge as clinical signs and symptoms may be subtle with considerable overlap between the two groups and screening laboratory/imaging studies and synovial fluid/blood cultures are relatively insensitive.
Previous work has demonstrated that bacteria and their toxins are highly destructive to joint tissues such as bone and cartilage and therefore a delay in diagnosis and initiation of treatment, which typically involves a combination of intravenous antibiotics coupled with joint irrigation, may have severe clinical consequences. Septic arthritis however comprises only a minority of acute joint presentations, yet almost all such patients are admitted to hospital, undergo potentially invasive procedures and universally receive anti-infective therapeutics, with their attendant risks in the context of expanding antibiotic resistance, overuse and expense. The rapid and accurate clinical stratification of the acute joint presentation would thus be extremely desirable. This may be achieved through the identification of novel blood, synovial fluid and urinary biomarkers unique to infectious arthritis. In addition, for those patients with microbiologically confirmed septic arthritis, genome sequencing of isolated bacteria may identify unique molecular signatures associated with poor structural or systemic prognosis, which could be utilised ultimately to develop novel antimicrobial treatments to improve clinical outcome in such patients.
This studentship therefore proposes to analyse blood, synovial fluid and urine samples of patients presenting with suspected septic arthritis utilising established metabolomic, proteomic and transcriptomic techniques coupled with advanced bioinformatic approaches for dataset analysis. Samples from patients recruited to this study will be collected during routine investigations and treatments (joint aspiration/surgical washout) and thus no patients will undergo invasive procedures solely for the purpose of the study. Genome sequencing will be conducted on all bacteria isolated from routine synovial fluid and blood cultures. In addition the studentship will provide hands on training in cell culture and ex vivo infection model development to enhance the skill set and breadth of training on offer.