A new DNA tool created by Michigan State
University can accurately predict people's height, and more importantly, could
potentially assess their risk for serious illnesses, such as heart disease and
cancer.
For the
first time, the tool, or algorithm, builds predictors for human traits such as
height, bone density and even the level of education a person might achieve,
purely based on one's genome. But the applications may not stop there.
"While
we have validated this tool for these three outcomes, 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, lead investigator
of the study and vice president for research and graduate studies at MSU.
"This
is only the beginning," Mr Hsu told the Science Daily.Further applications
have the potential to dramatically advance the practice of precision health,
which allows physicians to intervene as early as possible in patient care and
prevent or delay illness.
The
research, featured in the October issue of Genetics, analysed 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 everyone's height within roughly an inch.
While bone density and educational attainment predictors were not as precise,
they were accurate enough to identify outlying 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.
Hsu's 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 alone," Mr Hsu said.
Hsu's
team will continue to improve the algorithms, while tapping into larger, more
diverse data sets. Doing this would further validate the techniques and
continue to help map out the genetic architecture of these important traits and
disease risks.
With
greater computing power and decreasing costs around DNA sequencing, what was
once thought to be five to 10 years out, is now a lot closer when it comes to
this type of work, Mr Hsu added.
"Our
team believes this is the future of medicine. For the patient, a genomic test
can be as simple as a cheek swab, with a cost of about $50. Once we calculate
the predictors for genetically based diseases, early intervention can save
billions of dollars in treatment costs, and more importantly, save lives,"
he said.(UNI)
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