Student research

PhD Project Kathrin Bogensberger (PhD Medical Science PMU Salzburg)

The most prevalent musculoskeletal disease worldwide is osteoarthritis (OA), which is characterised as a degenerative joint disease associated with pain, loss of function and reduced quality of life. OA is a heterogeneous disease that affects various aspects of daily life, including participation in work, social activities, and health-related pursuits. Given its widespread effects, OA represents a significant economic and individual burden that requires consideration in public health priorities. As the number of older people is predicted to increase in the upcoming decades, it is also expected that the prevalence of OA will concomitantly rise.

The current approach to disease management is primarily focused on providing symptom relief and functional improvement. However, these interventions frequently do not provide adequate outcomes. This may be attributable to the presence of comorbidities, such as depression, which is also recognised as a significant global health burden. It has been estimated that approximately 3-10% of the general population in Europe suffers from depression, with a prevalence of approximately 4% in Austria. In comparison, the prevalence of comorbid depression in OA is estimated to be as high as 20%. The coexistence of OA and depression can have a significant impact on individuals, the economy, and society. It has been demonstrated that depressive illness can hinder treatment approaches, including physical activity, which is recommended to reduce pain intensity and disability in patients with OA. This can result in an increased perception of pain and less successful outcomes. Moreover, those affected are at an elevated risk of increased healthcare utilisation and diminished treatment satisfaction. Therefore, early detection and intervention of depression in individuals with OA is crucial.

Despite the importance of early detection, there is currently a lack of accessible clinical prediction models. Accordingly, the objective of this PhD project is to develop such a clinical prediction tool for comorbid depression in OA, with the aim of facilitating early identification of at-risk patients, tailoring of interventions and treatment plans, enhancing patient monitoring and follow-up, and ensuring timely care. In light of the above, it is evident that the development of a clinical prediction model for comorbid depression in OA will contribute to the reduction of the overall disease burden associated with the co-occurrence of these chronic diseases.

Kathrin Morasek is a sociologist and healthcare professional. At the Medical University of Vienna she is enrolled in the PhD programme ‘Public Health’ under the supervision of Tanja Stamm.

Chronic wounds are associated with a significant decline in health-related quality of life. A wound is considered chronic if not healed within eight weeks despite appropriate local treatment or if the underlying diagnosis requires ongoing treatment. The progression of chronic wounds is associated with pain, unpleasant odor, loss of mobility, increased risk for infection and sepsis as well as limitation of daily activities and restrictions of participation. The treatment of chronic wounds is associated with high healthcare costs, a trend that is going to increase due to the longevity of the population. However, there is no recent estimate of the prevalence and incidence of chronic wounds in Austria, which is segmented by age group, gender, or province. The prevalence estimate provides a crucial foundation for service planning and serves as a basis for a health economic assessment of the problem.

This study therefore aims to address this gap in knowledge by examining the care of patients with chronic wounds under routine conditions. Furthermore, a support network in the form of a self-help group for those affected will be established.

A population-based, retrospective analysis of real-world data from both inpatient and outpatient sectors will be conducted with the objective of identifying patients with chronic wounds. The study will be conducted in two phases, starting with an analysis of patient records from an outpatient wound clinic in Vienna. The results are then used in a second phase to derive characteristics that can be used to identify patients with chronic wounds from social insurance data. This allows us to break down prevalence and incidence rates for chronic wounds across Austria according to diagnoses, different age groups, gender and regions.

Team members: Kathrin Morasek, Valentin Ritschl, Tanja Stamm

Partners: Raffael Himmelsbach (Ludwig Boltzmann Institute for Traumatology, The Research Center in Cooperation with AUVA), Alexander Pötscher (Wound Centre Vienna 22), Cornelia Schneider (Ludwig Boltzmann Institute for Traumatology, The Research Center in Cooperation with AUVA), Sabine Wieser (Austrian Health Insurance Fund)

Christine Strauss is a PhD student at the Medical University of Vienna in the program ‘Musculoskeletal and Dental Research’. Together with her supervisors Stefan Toegel and Silvia Hayer, she is investigating the glycobiology of different joint tissues in degenerative and inflammatory musculoskeletal diseases. Her particular focus is on galectins and their involvement in the pathophysiological crosstalk between different tissues and cell types. Therefore, she studies (1) the molecular activity of galectins in human primary cells and tissues as well as their glycophenotype, (2) the role of galectins in extracellular vesicle-based crosstalk between joint tissues, and (3) the function of galectins in various mouse models of OA and RA using galectin-1 and -3 knock out mice

Mirjam Dellinger is a PhD student in the research group of Michel Bonelli at the Division of Rheumatology of the Medical University of Vienna. Her main research interest focuses on the role of cell-cell interaction in the pathogenesis of the chronic inflammatory disease rheumatoid arthritis. In her project, she aims to get a better understanding of the development of cellular and molecular heterogeneity in the synovium of RA patients, thus explaining heterogenous treatment responses. For taking a closer look at interactions between fibroblast-like synoviocytes (FLS) and immune cells, co-cultures of these cells are used to model the inflamed joint. Cell-cell interactions are profiled with an image-based platform using high-content confocal fluorescence microscopy that not only allows visualization and identification of different immune cell subsets but also quantification of interaction levels with FLS. Consequences of interaction such as immune cell activation are further characterized using spectral cytometry, RNA seqeuencing, and other moleculobiological methods. This platform is also used to test perturbations of cell-cell interactions in the context of joint inflammation.