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Approved Research

Dissecting the heterogeneity and pathway nature of genetic risk: towards better diagnosis and prognosis

Principal Investigator: Urko Marigorta
Approved Research ID: 74382
Approval date: July 27th 2021

Lay summary

The overarching hypothesis of our project is that more targeted studies are needed to understand the specific genetic and lifestyle factors that characterize the health and disease landscape in each person. This involves deliberate attempts to escape from the broad group approach that characterizes current genetic research. At present, we study questions such as: what are the genetic variants that increase the risk to develop diabetes? What are the mechanisms by which these genes exert their effects? What are the best lifestyle guidelines for decreasing the prevalence of a given disease? All of them are good, and indeed a big number-based approach has permitted to discover, for the first time, about hundreds of genetic and lifestyle factors that trigger disease. Yet, we worry that this approach to identify the culprits necessarily hampers our understanding of the nuances that matter the most in each person. Some of this factors may act, for instance, only in a fraction of patients. For this reason, we propose to devise more fine-grained studies.

Our project involves carrying out three main substudies (see A2 section above). The first one involves applying a new statistical method to understand the function of each chunk of DNA present in the population. Rather than studying individual mutations, we plan to infer what are the risks associated with each combination of variants. The second one will focus on performing the first evaluation about what are the specific molecular groups of genes that are altered in each patient of inflammatory bowel disease. This will serve to detect groups of patients that share underlying etiological factors, which will lead to more refined genetic studies to discover new genes associated with this disease. Finally, we will explore a new way of using genetic data for preventive purposes: rather than calculating what is the risk of each metabolic and cardiovascular risk, we will explore whether there are specific lifestyle interventions that are particularly suited to the genome of each person. Overall, we are planning a 30-month effort. If successful, this study will help to open new paths for analysing and extracting the information in our genomes for health purposes.