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A new DNA tool created by Michigan State University can predict people’s height, and the risk for serious illnesses like heart disease and cancer correctly. The algorithm builds predictors for human traits such as height, bone density and the level of education a person might achieve, purely based on individual’s genome.
Genetics analyzed the complete genetic makeup of nearly 500,000 adults in the United Kingdom using machine learning, where a computer learns from data. In validation tests, the computer accurately predicted individual’s height within roughly an inch. While bone density and educational attainment predictors were not as precise, they were accurate enough to identify individuals who were at risk of having very low bone density associated with osteoporosis or were at risk of struggling in school.
Traditional genetic testing typically looks for a specific change in a person’s genes or chromosomes that can indicate a higher risk for diseases such as breast cancer. The model considers numerous genomic differences and builds a predictor based on the tens of thousands of variations.
Using data from the UK Biobank, an international resource for health information, Hsu and his team put the algorithm to work, evaluating each participant’s DNA and teaching the computer to pull out these distinct differences. The algorithm looks at the genetic makeup and height of each person. The computer learns from each person and ultimately produces a predictor that can determine how tall they are from their genome.