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A new DNA tool created by Michigan State University can accurately predict the size of people and, more importantly, potentially assess their risk of serious diseases, such as heart disease and cancer.
For the first time, the tool, or algorithm, builds predictors of human characteristics such as height, bone density and even the level of education that a person can achieve, only from his genome. But applications may not stop there.
"While we have validated this tool for these three findings, we can now apply this method to predict other complex traits related to health risks such as heart disease, diabetes, and breast cancer," said Stephen Hsu, principal investigator of the study and vice president. for research and graduate studies at the MSU. "It's only the beginning," Hsu told Science Daily.
Other applications could significantly advance the practice of accuracy in health, which would allow physicians to intervene as early as possible in patient care and prevent or delay the disease.
The research, presented in the October issue of Genetics, analyzed the complete genetic makeup of nearly 500,000 adults in the UK using machine learning, where a computer pulls data lessons.
During validation testing, the computer accurately predicted everyone's size in about an inch. Although the predictors of bone density and level of education were not as accurate, they were accurate enough to identify peripheral people who were at risk of having very low bone density associated with osteoporosis. or fight at school.
Traditional genetic tests typically look for a specific change in a person's genes or chromosomes that may indicate a higher risk of diseases such as breast cancer. The Hsu model takes into account many genomic differences and builds a predictor based on tens of thousands of variations.
Using data from the UK Biobank, an international resource for health information, Hsu and his team applied the algorithm, evaluating the DNA of each participant and teaching them about the problem. computer to clear these distinct differences.
"The algorithm takes into account the genetic makeup and size of each person.The computer draws lessons from each person and ultimately produces a predictor to determine the height of its genome," said Dr. Hsu .
The Hsu team will continue to improve the algorithms while leveraging larger and more diverse datasets. This would further validate the techniques and continue to help define the genetic architecture of these important traits and disease risks.
With more computing power and reduced costs associated with DNA sequencing, what we thought would be in five to ten years is now much closer to this kind of work, added M Hsu.
"Our team thinks that the future of medicine is promised.For the patient, a genomic test can be as simple as a levy on the cheek, at a cost of about $ 50. that we have calculated the predictive factors for genetic diseases, early intervention can save dollars in treatment costs and, more importantly, save lives, "he said.
UNI XC RJ 1422
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