Chances of getting sick during life may be predictable

Chances of getting sick during life may be predictable


By analyzing the millions of tiny genetic differences in the genome, it is possible to predict a person’s chance of developing a disease during their lifetime. Over the past decade, researchers have developed risk scores for dozens of diseases in the hope that one day patients can use the information to reduce their risk. In a recent study published in the journal Nature Medicine, a team from the Broad Institute of MIT and Harvard outlined how they selected, optimized and validated detection methods for 10 common diseases.

Most current polygenic risk scores were developed based on genetic data from populations of European ancestry, raising questions about whether these scores are applicable to other ancestry populations.

The researchers collaborated with the National Electronic Medical Records and Genomics Network. The network studies how genetic data from a wide range of patients can be integrated with their electronic medical records to improve clinical care and health outcomes.

To refine the scoring system, Neil Lennon, chief scientific officer at Broad Clinical Laboratories, and his team first combed the literature, looking for polygenic risk scores that had been tested in people with at least two different genetic ancestry. They also searched for scores that patients could reduce their risk of disease through medical treatment, screening and lifestyle changes.

The team selected 10 diseases that the polygenic risk score focuses on: atrial fibrillation, breast cancer, chronic kidney disease, coronary heart disease, hypercholesterolemia, prostate cancer, asthma, type 1 diabetes, type 2 diabetes, and obesity.

For each case, the researchers identified the exact site in the genome and analyzed it to calculate a risk score. By comparing the test results with the whole-genome sequence of each patient’s blood sample, they verified that all of these loci could be accurately genotyped.

Researchers analyzed disease risk in an ancestrally diverse group of 2,500 people. About one-fifth of the participants were found to have at least one of 10 conditions. Most importantly, the ancestral backgrounds of these participants varied widely, suggesting that the recalibrated polygenic risk score was not biased toward people of European ancestry but was valid across all populations.

The researchers say they can’t fix all bias in risk scores, but they can ensure that if a person is at high risk for a disease, they will be identified regardless of their genetic ancestry.

People always want to “nip trouble in the bud”, and being prepared for the unknown is also a habit that has been engraved in human bones since the primitive times. Therefore, people naturally want to know what diseases they may suffer from in the future, and it is always good to have an idea. This time, researchers used a variety of methods, combined with patients’ genetic data and electronic medical records, to provide a more accurate and effective method for predicting diseases for all groups of people. I don’t know how much it will cost to add a physical examination package. After all, if it is to be promoted, the price cannot be too expensive. Of course, people still need to view “probability” rationally and use good living habits to resist these disease risks lurking on the road of life.


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