According to new research by University of Alberta, in most cases, your genes
have less than five percent to do with your risk of developing a particular disease.
The researchers examined two decades of data from studies on the relationships between common gene
mutations, also known as single nucleotide polymorphisms (SNPs), and different diseases and conditions in a largest meta-analysis of its kind ever conducted. The results show that the links between most human diseases and genetics
are shaky at best.
University of Alberta computational biologist David Wishart, who was a co-author on the study told Thailand Medical
News, "Simply put, DNA is not your destiny, and SNPs are duds for disease
prediction. The vast majority of diseases including many cancers, diabetes and Alzheimer's disease have a genetic
contribution of five to 10 percent at best."
The new research also highlights some notable exceptions, including Crohn's disease, celiac disease
and macular degeneration, which have a genetic
contribution of about 40 to 50 percent.
Wishart added, "Despite these rare exceptions, it is becoming increasingly clear that the risks for getting most diseases arise from your metabolism, your environment, your lifestyle or your exposure to various kinds of nutrients, chemicals, bacteria or viruses."
The research findings fly in the face of many modern gene
testing business models, which suggest gene
testing can accurately predict someone's risk for disease
The researchers suggested non-genetic
indicators that may provide a much more accurate measure of human disease
risk and are also more accurate for diagnosis.
Wishart further added,"The bottom line is that if you want to have an accurate measure of your health, your propensity for disease
or what you can do about it, it's better to measure your metabolites, your microbes or your proteins not your genes
.This research also highlights the need to understand our environment and the safety or quality of our food, air and water."
The research study, "Assessing the Performance of Genome-Wide Association Studies for Predicting Disease
Risk," was published in PLOS ONE
Reference : Jonas Patron et al. Assessing the performance of genome-wide association studies for predicting disease risk, PLOS ONE (2019). DOI: 10.1371/journal.pone.0220215