See Events

PhD Defence Jan Hendriks

saving the joint: new methods for early diagnosis and treatment

Jan Hendriks is a PhD student in the department of Developmental BioEngineering. His supervisors are prof.dr. H.B.J. Karperien from the faculty of Science and Technology and prof.dr. D.B.F. Saris from the Mayo Clinic, Rochester, US.

Osteoarthritis (OA) is a debilitating joint disease affecting millions of patients worldwide, with the prevalence set to increase further due to an aging population. Despite high morbidity and associated health costs, no curative treatment yet exists. This is caused in part by the highly complex nature of the disease, with multiple phenotypes, and by late diagnosis reducing efficacy of therapies. This results in the reality that most patients experience severe joint pain for multiple years before they inevitably undergo total joint replacement. The goal of this thesis is to make steps to upend this status quo through saving the joint by applying new methods for early diagnosis and treatment of osteoarthritis.

As mentioned, the disease is highly complex and is only diagnosed at a late stage. In the current situation, osteoarthritis is diagnosed via X-Ray many years after disease onset and limited information can be obtained on the specific subtype experienced by the patient. This demands for new diagnostic tools that can identify the multiple phenotypes of the disease at an early stage, to allow for effective personalized treatments. A promising approach is to measure biomarkers that present information on disease progression, locally in the effected joints. This requires a tool that can measure multiple biomarkers simultaneously, to detect the different phenotypes, with large sensitivity, for early diagnosis, in small volumes of joint fluids. Currently, no diagnostic tool exists that can meet these requirements.

In this work, we have developed a diagnostic method based on surface plasmon resonance array imaging (SPRi) which allows us to measure the desired biomarkers in multiplex. To achieve the required sensitivity for early diagnosis we applied a signal enhancement cascade using gold nanoparticles. In a proof of concept study, we showed we could measure relevant OA biomarkers below physiological limits with broad dynamic range in multiplex in small volumes of joint fluids. To improve the applicability of this method in a clinical setting, we developed a toolbox for extensive quality control, calibration free measurements and simple assay optimization. This was achieved by kinetically defining the SPRi enhancement cascade, allowing for prediction of the signal at any biomarker concentration. This diagnostic tool has large potential in the early specific diagnosis of OA and can therefore help improve the efficacy of existing treatment options.

However, in order to save the joint new improved early treatment options are required. Early treatment of articular cartilage defects has shown potential in this respect. Promising results have been shown by injecting a combination of cells and biomaterials at a defect site in the affected joint. While injection is suitable for small defects, larger irregular defects could benefit from spraying the cell-biomaterial combination. In this work, we looked at the effect of spraying on the viability of the cells after impact. We developed a validated analytical model that can predict cell survival based on spraying parameters. We showed that the viability is dependent on the air pressure applied to the nozzle, impact distance, viscosity and surface stiffness and that our model accurately recapitulates these processes. Subsequently, we expanded this model by determining the effect of cell type and cellular properties on the survival. We showed that the cell type has a large influence on survival, captured by the cellular properties in our model. Furthermore, we demonstrated that changing these cellular properties could improve the survival in the spraying. Finally, we applied a custom controllable droplet impact set-up to validate our model in a large parameter space. This resulted in further improvements in our model and expanded its use to other biofrabrication methods. To further improve this treatment, we developed a toolbox for optimal biomaterials for joint repair. We demonstrated an injectable hydrogel with tuneable mechanical and biological properties that can be tailored to obtain an optimal cell response. Together, this work can result in the effective application of optimal cell/biomaterial combinations to the joint with an increased cell survival leading to a promising early treatment.

With the combination of new methods for early diagnosis and early treatment we have made steps to address the main challenges facing our joints. While no single step is ever large enough, we believe this work is a significant leap in saving the joint.