Scanning electron micrograph (SEM) of human bone, osteoporosis

An international team of researchers has developed a new genetic risk score that could dramatically improve screening for osteoporosis. The team, which includes scientists from the University of Sheffield, developed the gSOS scoring system based on clinical information from more than 340,000 individuals who donated health data to the UK Biobank. The study was published in the journal PLOS Medicine https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003152

“As the population ages, the urgency of improving preventive measures becomes all the more intense,” says Eugene McCloskey, professor in Adult Bone Diseases at the University of Sheffield. He adds that, “Bone strength, a key component underlying fracture risk, is highly heritable (up to 85 per cent determined by our genes), and is therefore a strong candidate for assessment through genetic screening.”

This study looked at whether a risk score gathered from a panel of over 20,000 genes could substitute a commonly used measure of bone strength called heel quantitative ultrasound speed of sound (SOS). The new risk score, termed gSOS, was developed based on data from the UK Biobank, which contains health and well-being data from 500,000 volunteer participants. The Biobank collects such data to support research on prevention, diagnosi, and treatment of common serious disease, including cancer, heart disease, diabetes arthritis, forms of dementia and more.

The researchers trained a polygenic risk score for SOS in 2 separate subsets of UK Biobank data (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed “gSOS.” It was then tested for its ability to predict fractures in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines.

All patients whose data was used were genome-wide genotyped and had fracture risk factors. The international research team applied gSOS alongside the Sheffield-developed FRAX tool, which evaluates the fracture risk of patients based on individual models that integrate clinical risk factors as well as bone mineral density.

The team estimated that the application of gSOS could reduce the number of FRAX tests and bone mineral density-based FRAX tests (a related measure) by 37 per cent and 41 per cent, respectively, while maintaining a high sensitivity and specificity to identify individuals who should be recommended for intervention.

“While the impact of this research is not immediate as it requires each individual’s genome to be available for calculation of their gSOS, it is of great importance for the future of medical practice,” says McCloskey.

It’s estimated that over 200 million people suffer from osteoporosis worldwide, but early detection is difficult and many people who undergo screening are actually at low risk of developing the disease.

A full genome profile can be generated for approximately $45-50 per patient, a cost that is comparable to or lower than the cost of an X-ray to measure bone mineral density.  As a result, by generating a single genomic profile, researchers could identify multiple risk factors for osteoporosis and other conditions, such as cancer, cardiovascular disease and dementia.  Incorporating genetic testing into routine clinical practice, the researchers argue, could improve the efficiency and cut costs of screening for common diseases.

Brent Richards, lead of the team, said: “By generating a single genomic profile, we can identify multiple risk factors for diseases like cancer, cardiovascular disease and osteoporosis.” Richards is a geneticist at the Lady Davis Institute’s Centre for Clinical Epidemiology and Professor of Medicine, Human Genetics, and Epidemiology and Biostatistics at McGill University,

“Importantly, we could reduce the number of specific tests to which we need to subject our patients if we knew whether they have the genetic markers predisposing them to particular conditions,” he adds. “A simple investment in genotyping would give us a more refined understanding of who should be screened, allowing us to concentrate on individuals at higher risk.”

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