Mysteriet med den dolda ärftligheten bakom hjärt-kärlsjukdomar, diabetes och astma

Only a small proportion of the genetic contribution to common diseases is explained by the genetic variants identified till date. It is likely that much of the remaining genetic contribution, the hidden heritability, is due to: a) the effect of rare genetic variants not assessed in previous studies, b) common variants with small effects that are not detected in studies performed so far, and c) interactions between genes and environment, or between pairs of genes.

This proposal aims to bring together genetic and proteomic research to identify DNA sequence variants and interactions between genetic and environmental factors that influence the risk for common cardiovascular diseases such as, myocardial infarction, stroke and hypertension, as well as asthma and diabetes. The project has three specific aims. Firstly, to investigate how rare genetic variants influences the disease risk.

Secondly, to develop models to identify high-risk individuals for developing disease, and thirdly investigate molecules that influence disease development.

Two unique population-based cohorts will be used, making this project manifold more powerful compared to previous studies. In the first cohort, the NSPHS from Sweden, whole-genome sequencing has been performed, and hundreds of protein biomarkers in blood have been measured, positioning the cohort among the most well-measured, in molecularly terms, worldwide.

The second cohort, UK Biobank, is the world’s largest population-based cohort with genetic data and extensive information on diet, lifestyle and medical conditions, from registries and self-reported, available. We will use and develop novel methods for data analyses that will allow for estimating the effect of common and rare genetic variants, and prediction modelling with artificial intelligence tools and traditional polygenic risk scores.

To test for causal effects of potential risk factors and biomarkers and disease development we will use Mendelian randomization.

Genetic studies can give leads on disease mechanism which can be valuable for treating symptoms and stratify patients. Identification of disease related biomarkers that directly influence the pathogenies of a disease, can be used for developing now drugs that targets the biomarker. Identifying high-risk individuals, can be used for preventive treatments and more frequent screening, which can lead to lower disease incidence rate. The overall long-term goal with my research is to increase population health.