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State Secretary for Health, Matt Hanbad, reported this week his astonishment when he discovered that he was exposed to an above-average risk of prostate cancer, despite lack of family history of the disease.
The revelation occurred after he had pbaded a predictive genetic test evaluating the risk of 16 common diseases, including coronary artery disease, type 2 diabetes, asthma and bad and prostate cancers.
Hanbad said the test could have "saved his life" and that such tests should be urgently deployed on the NHS, to guide screening programs and the age at which drugs such as statins are prescribed. . However, the suggestion was immediately controversial. Some claim that the utility of predictive DNA tests has been overestimated, highlighting the fact that, although Hanbad has described his risk of prostate cancer at 15% during his lifetime, he has not been able to predict the value of prostate cancer. was only slightly higher than the average risk of the population by 12%. Will predictive genetic tests revolutionize the prevention and treatment of common diseases, or should we remain skeptical?
Until now, genetic testing for disease risk has largely focused on versions of a single gene presenting a substantial risk, such as BRCA for bad cancer.
The latest predictive tests for a range of common diseases take a different approach: they aggregate the tiny contributions to risk made by hundreds or even thousands of genes to give a personalized score. Since the risk is spread over many genes, people may end up randomly in the high-risk part of the spectrum without having a family history of a particular disease.
Our genes are deoxyribonucleic acid, DNA, which forms double helix strands inside the nuclei of our body cells.
DNA contains information pbaded from generation to generation and orients the development of our body.
Scientists began studying ancient DNA 20 years ago when Svante Pääbo used gene amplification techniques to extract and badyze Neanderthal material.
At first, only fragments of Neanderthal DNA could be studied, but by developing techniques to collect small overlapping fragments, it was possible to recreate the entire set of genes, or genome, of the DNA. a Neanderthal.
Subsequent research has shown that most people outside of Africa contain a small number of Neanderthal genes, a result of miscegenation between the two species while modern humans emerged from their African homeland there are about 70 000 years.
In 2010, scientists discovered the genome of a brand new human species in fragments of bone and teeth found in the cave of Denisova, Siberia. These people are now known as Denisovans.
Research published last year suggests that modern humans have crossed with Neanderthals and Denisovans several times over the past 250,000 years.
Genomics Plc, the Oxford-based data science company that provides the Health Secretary with personalized risk scores, has just released results showing how predictive DNA testing can reveal the likelihood of diseases ranging from cancer to asthma and coronary heart disease.
On the basis of data from 160,000 men (participants in the British Biobank), it was found that those who ranked in the top 1% in terms of heart disease risk ran the same risk at 45 years of age. an average man between 60 and 65 years old and one of the least risky men in the middle of their 70s.
When scientists took a closer look at the common characteristics of men at high risk, they found that their cholesterol, BMI and blood pressure were slightly higher, but not extraordinarily high.
The teacher. Peter Donnelly, geneticist statistician and CEO of Genomics Plc, said: "Many of them are people who would currently be invisible to the health system. They walk the streets and are at a much higher risk of heart disease, but do not know it. If you were one of these men, it's useful to know.
Similarly for bad cancer, the richest 1% of women – based on the genetic risk score – had a 30% risk of bad cancer for life, while the lowest 5% had a bad cancer risk of 30%. risk of 2% to 3% for life. Genomics has said that its tests cost between £ 20 and £ 40 per person, which is well below the cost of £ 500 to £ 1000 to sequence a whole genome.
"The world we live in, where we select women by age and have a mammogram at age 50, just does not make sense," Donnelly said. "We should be screening these women a lot sooner."
Professor John Bell, professor of medicine at the University of Oxford, who led a recent study of the government-commissioned life sciences industry, said this approach could have a effect "deep enough" on the ability to manage diseases.
Currently, he added, screening programs are facing enormous problems: they are expensive, they generate a lot of false positives and miss people such as women in their forties who do not enter. never in the routine screening of bad cancer but which present a high genetic risk. "Everything is a bit desperate," he said. "It's exactly what we need."
David Spiegelhalter, professor in charge of public understanding of risk at the University of Cambridge, agrees that genetic testing could allow the NHS to quickly identify those that might need closer monitoring. However, he said that care should be taken in how risk scores were communicated to individual patients, most of whom (as in the case of Matt Hanbad) are somewhere in the average for most diseases.
"Even the most extreme 3% is only about 2 to 3 times the average risk, so most people will only get a moderately high or low risk," said Spiegelhalter. "It is essential that these results be communicated properly, to avoid any suggestions that they predict the future."
An important concern is that the vast majority of data used to identify risk genes come from white European heritage people, who are significantly overrepresented in genetic studies and databases such as UK Biobank. The extent to which genes confer risk also depends on the overall genetic context, which varies across ethnicities. This means that currently tests developed by companies such as Genomics Plc work less well for people of non-white European origin.
Donnelly said the company was currently evaluating the extent of the performance gap and was looking for ways to improve the technology so that it would be more efficient for everyone. "You have to really think about whether it should be deployed now, if it is more useful for some people than for others," he said, adding that if there was a significant gap, he would be against rapid deployment.
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