Genomic and Imaging Markers to Understand and Predict Progression of Joint Damage After Injury

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PROJECT SUMMARY Posttraumatic osteoarthritis (PTOA) is a major complication that follows an episode anterior cruciate ligament (ACL) rupture. In the US, there are over 100,000 ACL ruptures per year, from which 70% occur in physically active subjects under 40 years of age. At 10 to 20 years after ACL rupture the prevalence of PTOA is estimated to be 50–70%, regardless of surgical or non-surgical interventions. The failure of surgery to prevent PTOA leads to the hypothesis that the acute changes in the joint following directly after injury triggers a cascade of events leading to PTOA. However, little is known about how biological response to injury links to the subsequent joint damage. Therefore, it is important to have tools available that provide comprehensive assessment of response to injury and predict who will develop PTOA after ACL injury. Even though candidate biomarkers have been investigated, their practical use is still very limited. The goal of this proposal is to investigate if biological response to injury by measuring soluble biomarkers in synovial fluid (SF) and analyzing the genomic profile of extracellular vesicles (EVs) isolated from SF obtained during the acute and sub-acute phases of ACL injuries of 18- to 40- years old patients has the potential to predict joint degradation at 3-4 and 6-7 years after injury. Differences between patients in the biological responses to ACL injury involve the presence of different cell types and different cellular responses. EVs, which are being released by all cell types, are attractive candidates as all-in- one, complex biomarkers able to provide a multi-faceted, integrated, snapshot “omics” joint profile of the entire joint environment. In addition, given that these lipid bilayer–delimited particles carry cargos of proteins, different types of RNA, and lipids derived from their parent cells, and that EVs can modulate target cells, make these particles even more attractive as biomarkers. To measure progression of joint damage we will use advanced MRI biomarkers developed in our labs that can detect early tissue degeneration, especially of articular cartilage, a tissue, which is key in the early diagnosis of PTOA. Even more importantly, our MRI markers have shown ability to predict progression. We aim to test our hypothesis that early response to injury captured by the cargo of EVs will provide a new window into early biological changes directly after joint injury is associated with progression of joint damage leading to PTOA. To achieve our goal to establish a biomarker profile that predicts the biological response to the injury and ultimately the development of PTOA, we propose two aims. Aim 1 will provide a panel of biomarkers directly after injury (2 to 3 weeks after injury) and at time of surgery (8 to 12 weeks after injury) establishing the biological response to injury, and determine the relation of these biomarkers to baseline MRI measures of joint damage. In Aim 2, we will test whether these biomarkers can predict changes in the clinical and imaging outcomes determined 3-4 years and 6-7 years after injury. Finally, we will establish a panel of predictive biomarkers for joint degradation validated by cost-effective methods employed in the clinical setting.