Active Genetics & Molecular Biology Infection & Immunity
Paleo-Evolutionary Medicine: Using ancient DNA to study the origins of common complex diseases
Summary
Original abstract (not yet simplified)Common diseases, such as cancer, dementia and heart disease, are the leading causes of death globally. In the UK, it is estimated that 1 in 2 people will develop cancer in their lifetime, 1 in 3 will develop dementia, and 1 in 4 will die from cardiovascular disease. However, the risks of developing common diseases are not shared equally between...
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Common diseases, such as cancer, dementia and heart disease, are the leading causes of death globally. In the UK, it is estimated that 1 in 2 people will develop cancer in their lifetime, 1 in 3 will develop dementia, and 1 in 4 will die from cardiovascular disease. However, the risks of developing common diseases are not shared equally between individuals or populations. Genetic susceptibility to disease is a major contributor to disease prevalence, alongside diet, lifestyle and other environmental factors. Understanding the genetic component of disease risk is a critical issue in epidemiology, as it directly informs public health policy, disease prevention and the development of vaccines and novel therapeutics. Most of the existing research in this area has focused on the underlying genetics of risk, while relatively little is known about the evolutionary origins of common diseases. This is a major omission, as understanding the origins of genetic risk can improve health outcomes in the present.In this ERC Starting Grant, I will use ancient DNA to model the evolutionary origins of genetic susceptibility to the leading causes of death and ill health worldwide, including cancer, dementia, cardiovascular, metabolic, autoimmune, respiratory and infectious diseases. I will build and apply state-of-the-art computational tools to (i) model the effects of natural selection on disease risk in the human genome; to (ii) reconstruct the evolutionary history of human and zoonotic pathogens; and to (iii) model the effects of pathogens, and other environmental factors, on the evolution of human disease susceptibility.
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