- A new genetic screen predicted that about 2 percent of those tested were at a high risk to develop osteoporosis (about 17 times more likely than others) and subsequent bone fracture (nearly twice as likely) in their lifetime
- An algorithm in the screen identified 1,362 independent genetic differences that correlated with low bone-mineral density readings among the 400,000 participants studied
are at risk of osteoporosis or bone fracture later in life can be predicted by
a genetic screen, according to a study by a researcher at the Stanford
University School of Medicine. The most extensive study of its kind identified 899 regions in the human genome associated with
low bone-mineral density, out of which a majority of the genes (613) were new
affects 2 million people each year and accounts for $19 billion in annual
health care costs.
‘A Stanford professor has developed an algorithm to find correlations between naturally occurring genetic differences among people who have low bone-mineral density. The screen can predict whether the individuals are susceptible to osteoporosis onset and bone fracture later in life.’
are lots of ways to reduce the risk of a stress fracture, including vitamin D,
calcium and weight-bearing exercise,” said Stuart Kim, PhD, an emeritus
professor of developmental biology. “But currently there is no protocol to
predict in one’s 20s or 30s who is likely to be at higher risk, and who should
pursue these interventions before any sign of bone weakening. A test like this
could be an important clinical tool.”
author of the study is Kim, and it is published in PLOS ONE.
In osteoporosis or porous bone, there is a reduction in bone
mass due to bone loss or defects in bone production, or both. The
weakened bone is not able to withstand the stress of slips and falls, or
sometimes even regular daily activity and is susceptible to bone fracture. It
affects millions of Americans and is responsible for fractures in every 2nd woman and
every 4th man over
the age of 50.
Osteoporosis measure by low bone-mineral density
Kim saw the correlation between people predicted to have the highest
risk of low bone-mineral density and the development of
osteoporosis and fracture in a chance discovery while actually investigating whether
elite athletes or members of the military were at risk of bone injury during
have earlier identified that there is a genetic
component to osteoporosis, meaning you have a family history of the condition; they
have also identified behavior
(what you eat, how much you exercise, your weight and gender) as a
significant role player in bone health.
studies on large groups of individuals have recently shown the likely
involvement of hundreds of genes, each doing its own bit to either increase or
decrease risk of the disease.
Radiologists use a bone-mineral density test to diagnose
osteoporosis. The test uses X-rays to measure the amount of minerals, such as calcium, in a
person’s hip, spine or heel. However, the tests are usually only performed on
people who have suffered a recent fracture from a simple fall and those with a
family history of osteoporosis.
most common clinical algorithm used to detect or predict osteoporosis is called
FRAX,” Kim said. “But the catch is that the two largest components of
the FRAX algorithm are bone-mineral density and prior fracture. So it’s kind of
a circular argument.”
Computer algorithm developed
- Kim selected the data of nearly 400,000 people in the UK Biobank; the Biobank has a vast collection of information that is freely available to public health researchers around the world.
- He analyzed the genetic data and health information of the participants, and for each of them, he collected data on bone-mineral density, age, height, weight and, sex, as well that participant’s genome sequence.
- He then developed a computer algorithm to find out if there were any naturally occurring genetic differences among people who had low bone-mineral density.
- The algorithm helped to identify 1,362 independent differences, or single-nucleotide polymorphisms, that correlated with low bone-mineral density readings.
- Kim then used a machine-learning method called LASSO, developed in 1996, to further refine the data.
resulting algorithm assigned a risk score for low bone-mineral density to each
of the 400,000 participants; further analyses showed that the people who had very low scores or those in the bottom 2.2
percent of these scores were seventeen times more likely than similar people to
have been diagnosed with osteoporosis and nearly twice as likely to have
experienced a bone
comparison, a much lower percentage of women (about 0.2 percent) tested will
have a cancer-associated mutation in the BRCA2 gene, putting them at risk of breast cancer to about six times that of a woman
without a BRCA2 mutation.
analysis worked really well,” Kim said. “This is one of the largest genome wide association studies ever completed for
osteoporosis, and it clearly shows the genetic architecture that
underlies this important public health problem.”
planning a clinical trial in the future to investigate whether simple
preventive measures can increase the bone-mineral density of the elite athletes
and select members of the military identified by the algorithm as high-risk
candidates for osteoporosis and potential fracture. He
is also interested in conducting a similar study among younger people who do not
have any visible clinical symptoms of bone weakening.
million people in this country have already accessed their genome sequences
using direct-to-consumer testing services,” Kim said. “I think this
analysis has the potential to become the standard of care in the coming years.
It would be a relatively simple measure to identify those who should have their
bone-mineral density tested and perhaps take
steps at an early age to ensure their
future bone health.”
- Osteoporosis, fracture risk predicted with genetic screen – (https://med.stanford.edu/news/all-news/2018/07/osteoporosis-fracture-risk-predicted-with-genetic-screen.html)