Approved Research

Multiomic signature of digestive disorders

Lay summary

Our research project, titled "Multiomic Signature of Digestive Disorders," seeks to provide insights into the diagnosis, prognosis, and treatment of digestive diseases. These conditions, such as celiac or liver diseases, often go undetected or are diagnosed too late due to their unspecific symptoms. We aim to change this by studying a wide range of potential biomarkers that can help identify these diseases and the associated organ damage early on.

In our previous studies, we have performed comprehensive analyses of various biological markers in patients with multiple digestive disorders, such as alcoholic liver disease, alpha1-antitrypsin deficiency, liver cirrhosis, and acute liver failure. However, a significant challenge is determining how useful these biomarkers are in the broader population, as previous studies focused on specific patient groups.

To bridge this gap, we plan to evaluate these biomarkers using the extensive data available in the UK Biobank dataset. To be able to do that, we will need the Tier 2 dataset, including (but not limited to)  i) routine blood assays; (ii) available phenotyping and medical history data including ICD codes; (iii) proteomic and metabolomics data; (iv) patient reported outcome data; (v) mortality data.

The biomarker levels will be compared to clinical data covering medical histories, diagnostic information, disease severity, treatment details, and outcomes. Longitudinal data tracking changes in health status as well as disease-specific mortality will provide valuable insights.

The ultimate goal of our research is to enhance our understanding of the processes driving the development and progression of digestive disorders. By uncovering reliable biomarkers, we hope to be able to estimate individual risks for morbidity and mortality associated with specific diseases. While digestive disorders are our primary focus, we will also monitor risks related to other organs, such as cardiovascular morbidity and mortality, to provide a comprehensive prediction useful in everyday clinical practice.