Investigating somatic and germline variation in complex diseases and their trajectories in aging populations
Approved Research ID: 73446
Approval date: June 16th 2021
Background & Scientific Rationale: Multiple diseases diagnoses in an individual are a major health burden and drastically increase the risk to die. Since the life expectancy in Western societies has increased significantly in the last decades largely due to medical advances, there is a growing need to understand which factors contribute to the occurrence of multiple and consecutive diseases with advanced age. Currently, little is known about genetic changes that contribute to the occurrence of consecutive diseases or related traits. However, identification of the underlying genetics of disease paths can enable us to understand the molecular basis of co-occuring/concurrent diseases and allow the identification of genes involved in healthy aging
Aims: This proposal has three main aims. First, we aim to identify genetic changes that contribute to the occurrence of subsequent diseases in individuals which have been diagnosed with common diseases such as heart disease, diabetes, lung disease or cancer. Second, the identified genetic changes will be further characterized with computational tools to identify the responsible gene that is contributing to the observed disease courses. Building on those results, we finally aim to understand the biological mechanisms that contribute to multiple disease diagnoses in aging individuals to uncover novel ways to prevent or treat multimorbidity.
Project Duration: Around 4 years from the time we have received the data.
Public Health Impact: The identification of genetic markers that are involved in multiple disease diagnoses can be useful to identify patients at risk for subsequent diseases. Furthermore, the identified genetic variants point towards genes and pathways involved in multiple disease diagnoses, which can be targeted to develop new ways to treat or prevent diseases. Therefore, understanding the genetic architecture of disease trajectories is important to reduce the burden of multiple age-related disease diagnoses and to improve public health.