"We study chronic inflammatory diseases"
Meet Johan Askling, research group leader at the Division of Clinical Epidemiology (KEP), Department of medicine, Solna.
My research group consists of seven teams that adress questions about the mechanisms of origin, treatment, and course of chronic inflammatory diseases. Team Johan Askling primarily works with rheumatoid arthritis and similar chronic inflammatory joint diseases, team Ola Olén with inflammatory bowel diseases, team Elizabeth Arkema with SLE and sarcoidosis, team Marie Holmqvist with rheumatic connective tissue diseases and team Thomas Frisell with multiple sclerosis. Team Martin Neovius concentrates on health economic aspects and Björn Pasternak's team focuses on pharmaco-epidemiological studies.
Different diseases – similar questions
What unites us is that we, with the help of clinical epidemiological methods applied to combinations of clinical and other registry data, biomarker data, and other types of data, often try to answer quite similar research questions but in the different diseases. Just like a lab, we share analytical methods (for example, various forms of biostatistics analysis, including machine learning methods) and equipment (for example, our IT environment for handling large amounts of register data).
Some of the clinical questions that we address concern for example co-morbidity (how much and why does the risk of various cardiovascular diseases increase in these chronic inflammatory diseases?); treatment effectiveness (how effective are different treatment options, put against each other?); drug safety (how great are the risks of various known or suspected side effects of newer types of immunomodulatory therapy for chronic inflammatory diseases?); indirect consequences (how is work ability affected by getting a chronic inflammatory disease?) and effects at the societal level (how much do the diseases and their treatment cost, and what drives these costs)?
Besides studies of the clinical course, we also study risk factors that can contribute to the occurrence of disease. For example, we study genetic factors and how these may explain some of the co-morbidities, i.e. if the same genetics can increase the risk of two different diseases. In several projects, we study how biomarkers, genetics and lifestyle interact on the risk of developing disease and how we can use different prediction models to predict which individuals are at the highest risk of developing disease, who have the greatest chance of responding well to a treatment, and who are most at risk of developing some form of side effect from the same treatment.
Results in clinical benefit
Many of our projects are performed with the help of national data in national collaborations, or in international collaboration with research groups that work with data from elsewhere but with the same research questions. An increasing proportion of our projects also use information from blood samples and biomarker analyses and are therefore carried out in close collaboration with translational researchers within MedS and in other parts of KI, at CMM, and at other universities.
One of the issues we are currently studying is the effects and risks of so-called JAK inhibitors, the newest class of drugs against rheumatoid arthritis, inflammatory bowel disease and several similar chronic inflammatory conditions. The safety profile and the safety signals that have emerged around the JAK inhibitors and other immunomodulatory therapies in clinical trials serves as good examples of why long-term follow-up of these drugs, as used in clinical practice, is needed. They also serve as good examples of how our research quite immediately as well as globally can makes a difference to how we treat these diseases in practice.
Clinician, researcher and research group leader
As a clinician, it is exciting to bring clinical questions to research and try to answer them with the help of clinical data. As a researcher, it's satisfying to see that the results of all the toil of getting data together, analyzing, and arranging paperwork and other bureaucracy, can be of clinical benefit. As a research group leader in a large research group with many different competencies and everything from junior to senior employees, it is satisfying to see how questions and methodology can be transferred from one disease state to another, how a doctoral student who research rheumatoid arthritis can learn from a doctoral student who work in multiple sclerosis, and how clinicians, engineers, computer scientists, statisticians, mathematicians, economists and epidemiologists can work together and make the whole become so much greater than sum of its parts.