At GeneBlueprint, we are ushering in an era where fitness and nutrition will become more tailored to a client’s particular biology, genetics and environmental influences. Not everyone responds to fitness and nutrition interventions in the same way, and this individual response is largely determined by genetic variations present in our cells. Moving away from a one-size-fits-all approach to something more personalized is a novel approach to aid optimal health and wellness.
The GeneBlueprint Way
Genetic prediction scores generated at GeneBlueprint are powered by proprietary algorithms developed by Dr. Guillaume Paré, Chief Medical Officer. These algorithms use cutting-edge machine-learning tools to extract a maximum of information from genome-wide data. While other direct-to-consumer companies base their predictions on a few genetic variants for each trait considered, GeneBlueprint algorithms integrate information from hundreds of thousands of variants. It is recognized in genetic circles that most human traits are the result of the complex interplay of thousands of genetic variants, and it has already been demonstrated that algorithms that adopt this genome-wide approach are far superior to “traditional” gene scores, often by a factor of 10 or more. Dr. Guillaume Paré’s algorithms currently outperform all other methods, giving GeneBlueprint a definite competitive advantage and also a distinguishing feature compared to others.
Chief Scientific Officer
Dr. Guillaume Paré is a Principal Investigator and Associate Professor of Pathology and Molecular Medicine at McMaster University. He is also Director of the Genetic and Molecular Epidemiology Laboratory. Dr. Guillaume Paré is a Medical Biochemist with board certification from the Royal College of Physicians and Surgeons of Canada. Dr. Guillaume Paré completed a Master’s in Human Genetics at McGill University and further trained in genetic epidemiology at Harvard Medical School. Dr. Guillaume Paré currently holds a Canada Research Chair in Genetic and Molecular Epidemiology. His clinical interests are centered on lipoprotein disorders, obesity and cardiovascular disease prevention. His corresponding research interests are in cardiovascular genetics, biomarker development and pharmacogenomics. His latest contributions relate to the characterization of genetic determinants of cardiovascular disease, pharmacogenetics and development of novel bioinformatics algorithms for analysis of genetic data. He has published 146 papers and has given over 100 conferences worldwide.