| Title: | The genetic landscape of complex diseases/traits - Exploring genetic risk scores to identify shared genetics and functional pathways |
| Lead Institution: | University of Regensburg |
| Principal investigator: | Professor Bernhard Weber |
Application 44862
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About
Manifestation of a wide-spread disease such as type 2 diabetes or high blood pressure is generally determined by diverse risk factors, often interacting in a complex and poorly understood mode of action. Importantly, genetic variation within one's genome contributes to disease development and, if known, may help to decipher the molecular pathways of disease pathology. This, in turn, can lead to targeted and thus disease-specific approaches for treatment with little or no side effects for the patient. As we increasingly learn more about the genetic factors associated with a specific disease, it has been proposed that many diseases/traits share common genetic profiles, suggesting that disease etiologies may overlap to some extent. To further extend on such studies and to precisely delineate overlapping genetic factors involved in disease processes, we plan to investigate more than 80 diseases/traits within the UK Biobank cohort. We will use the existing genetic information to generate a simplified personal score for each disease/trait (e.g. anthropometric traits, autoimmune conditions, eye diseases, or cancer subtypes). On the basis of the calculated scores we will estimate to what extent the individual scores are related to each other. This aims at precisely mapping the genetic variants responsible for the overlapping disease risk and thus may give further insight into functional aspects. This should greatly improve our knowledge of disease pathologies providing an unprecedented opportunity to devise targeted treatment options. We also want to learn more about the distribution of high risk score profiles within the UK Biobank cohort. This will give us a solid estimate of the percentage of individuals carrying at least one high risk score for a defined disease. Predictions within the highest 1% risk quantile have an excellent positive predictive value allowing reliable testing for individuals at risk for developing disease. Such data could be used in counselling and subsequently for offering preventive measures before first signs of the disease develop. Altogether, we seek to study the UK Biobank cohort to deepen our understanding of genetic factors associated with disease development of over 80 wide-spread diseases in Western countries. As these diseases usually develop later in life, knowledge of an individual's genetic risk profile is of medical importance to appreciate the precise biological disease processes, and by that to possibly open up individual medical treatment options. Altogether, this project is planned for a duration of 2 years.1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 9240 | Pleiotropic Locus 15q24.1 Reveals a Gender-Specific Association with Neovascular but Not Atrophic Age-Related Macular Degeneration (AMD) | Christina Kiel (+4) | 2020 | Cells |
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