Approved Research

Inflammatory processes leading to chronic disease, acute cardiometabolic events and relation to COVID-19 infection and severity.

Lay summary

Cardiovascular disease, Rheumatoid Arthritis, Psoriasis, Diabetes and Celiac Disease are examples of common inflammatory diseases that all affect the cells and tissues of the body, leading to tissue destruction, pain, swelling, stiffness and more. These diseases overlap in the sense that many individuals are affected by several diseases at the same time. The immune system recognizes parts of our own tissues as a threat, not unlike a virus or a bacterium, and therefore starts attacking them destroying the cells within. Sometimes this destruction is confined to a tissue (or one disease) but often many parts of the body will be included. Taking medications can in several cases slow down or stop some damage but only when taken in good time and not without side effects.

For some of these diseases there are good biological markers which can be detected in a blood sample but for some, there are no such markers for diagnosis. Patients can even go for years undetected and untreated. The aim of this project is to investigate new ways to combine information from several types of biological markers together with clinical information to make molecular diagnostics tools more available to the patient. In this way we hope to prevent damage to tissue and other health side effects while waiting to get treatment.

We will look at different biological markers in patients with and without inflammatory disease to compare these with each other and to look for differences. By studying common diseases together, including metabolic disease such as diabetes and infectious diseases like Coronavirus disease, COVID19 we hope to reveal how these different conditions affect one another on a molecular level. Doing this we do not only expect to find clues for new medications, but also clues that can be used to prevent disease in the first place.

This study will be valuable and unique due to several factors; i) the very large group of patients of various diseases and comorbidities that can be compared with unaffected individuals, ii) the many different biological markers analysed together with nutritional data, and finally iii) the possibility to combine genetic, clinical, and environmental exposure data. This way our results will add important knowledge to the field that will help make an earlier and better diagnosis for patients. This reduces the risk of getting health- and disease-related complications and will contribute to a better overall health in the future.