Genetic, Environmental and Lifestyle Factors in Assessment of Personalized Disease Risk
Principal Investigator:
Dr Baiba Vilne
Approved Research ID:
61684
Approval date:
June 24th 2020
Lay summary
Diseases such as cancer, arrhythmias and type 2 diabetes currently impose a huge burden not only on the patients and their families, but also on the health system and thus the society in general. Early and accurate prediction of disease risk is an essential component for the individual-centered or so called personalized medicine. Currently, it is well-known that genetic predisposition, various environmental exposures (pollutants, viruses and bacteria) and lifestyle choices (e.g. sedentary lifestyle, smoking, high-fat and sugar diet) contribute to morbidity. Moreover, several disorders may be observed simultaneously in one patient and, hence, there is a reason to believe that these may be caused by the same/shared genetic and/or environmental/lifestyle factors. Therefore, these factors should be taken into account, when establishing personal risk profile. Recently, novel methods have been developed, in order to consider each individual's genome as a whole, by either calculating the so called genetic risk scores (i.e. by summing-up the effects of each individual's all genetic variants) or by using artificial intelligence in order to !learn', how different genome compositions may be related to different diseases or their combinations. This proposed project is expected to last for three years and its main public health impact is expected to be the generation of more comprehensive personal disease risk assessment models that would be of improved clinical utility in personalized medicine applications.