Principal Investigator: Dr Christoph Nowak
Karolinska Institutet (Sweden)Tags: 42176, cancer, cardiovascular, diabetes, Mendelian randomisation, metabolic, risk prediction
Previous studies have shown that cancer and common non-cancer diseases such as type 2 diabetes and heart disease share several risk factors. In many cases, however, these associations have not been assessed in subgroups of the population, for example in pre- and post-menopausal women. Whether or not shared risk factors play a causal role either in cancer development or cardiovascular disease risk is also largely unknown. We will use genetic and observed data in the UK Biobank to characterise in detail the relationship between heart disease and type 2 diabetes on the one hand, and risk of the most common types of cancer (breast, prostate, gut and lung cancer). The project will take about three years and the results could not only advance our understanding of how cancer develops, but only help to prevent long-term negative cardiovascular consequences of cancer treatment. Fortunately, more people treated for cancer than ever before survive into old age and it is therefore important to identify cancer-related risk factors for cardiovascular and diabetic disease to prevent their occurrence on later life. In conclusion, our project in the intersection between common cancer and non-cancer diseases can benefit persons affected by both disease groups.
Project extension – 13-9-2019
We also want to study potential associations and causal effects between cardiometabolic risk factors and chronic kidney disease (including end-stage renal disease). Chronic renal disease is closely associated with cardiometabolic and oncogenic risk factors, and the current scope omits renal endpoints and a wider focus on (common) cardiometabolic risk factors. We would like to include these renal health-related outcomes, including relevant blood and urine biomarkers (e.g. creatinine, cystatin C) in our research scope.
We aim to characterise the relationships between, e.g., obesity, lipids and diabetes, and risk of commons cancers, as well as a range of cardiovascular and kidney diseases (e.g. risk prediction for end-stage renal disease based on cardiovascular history and blood/urinary biomarkers). Our approach will use observational epidemiologic and genetic methods such as Mendelian randomization to assess causality. We will also test if cardiovascular and kidney-related phenotypes (including blood- and urinary biomarkers) can improve risk prediction for cardiovascular outcomes (e.g. heart failure), cancer (e.g. breast cancer) and renal outcomes (e.g. worsening CKD category).
Last updated Sep 16, 2019