Most ‘pathogenic’ genetic variants have a low risk of causing disease


Researchers at Mount Sinai School of Medicine have found that mutations that cause most diseases actually have a lower risk of causing the disease. Credits: Do lab, Mount Sinai, NY, NY

Imagine a positive genetic test. Doctors say you have a “pathogenic gene mutation,” a DNA sequence that is known to increase your chances of getting a disease such as breast cancer or diabetes. But what exactly are those possibilities? Is it 10 percent? 50 percent? hundred? Currently, it’s not an easy question to answer.

To address this need, researchers at Mount Sinai School of Medicine analyzed DNA sequences and electronic health record data from thousands of individuals stored in two giant biobanks. Overall, they found that pathogenic genetic variation was relatively unlikely to actually cause the disease, about 7 percent. Nonetheless, they also found that some mutations, such as those associated with breast cancer, are associated with a wide range of risks to the disease. Result is, JAMA, May change the way doctors report risks associated with these variants, and one day help guide doctors to interpret Genetic testing result.

“The main goal of this study was to produce useful and sophisticated statistics that quantitatively assess the impact of genetic variation that causes known diseases on an individual’s disease risk,” genetics said. Dr. Ron Do, an associate professor of the. A member of the Charles Bronfman Institute of Personal Medicine, Genomics and Mount Sinai School of Medicine.

Over the last two decades, scientists have discovered hundreds of thousands of mutants that can cause a variety of diseases. However, due to the nature of these discoveries, it has been difficult to estimate the true risk of this occurring in each gene variant or to provide statistics. So far, most estimates have been based on studies of a small number of subjects who were part of a family member who had had the disease or were recruited in a disease-specific clinic. However, such studies that do not use a large, randomly selected population may overestimate the risks posed by the variant.

In this study, researchers address this issue by searching for 37,780 known variants in large DNA sequencing data from 72,434 individuals and scanning each individual’s health record to make a corresponding disease diagnosis. I did.Extensive search included 29,039 participants in Bio Sinaimyself 43,395 participants who were part of the Biobank Program and the UK Biobank.

This study was led by Iain S. Forrest of MD-Ph.D. A candidate for Dr. Do’s lab inspired by previous clinical experience as part of a post-baccalauréat fellowship at the National Institutes of Health (NIH).

“The idea for this study came from a brainstorming session,” says Forrest. “Dr. De and I discussed the need for a better system for classifying disease risk. Currently, variants are categorized by a wide range of labels, such as” pathogenic “and” benign. ” As we learned in the clinic, these labels have a lot of gray areas. At that time, I realized that a biobank that links DNA sequence data to electronic medical records is an unparalleled opportunity to meet this need. “

Early results were that 157 diseases in the dataset were defined as “pathogenic” by the widely referenced NIH-supported public library, ClinVar, or predicted by bioinformatics algorithms. We have shown that we can link to 5,360 variants defined as. .. On average, “penetrance,” or variant, was unlikely to be associated with the diagnosis of the disease, specifically 6.9%. Similarly, the mean risk difference, which represents an increased risk of illness between those with and without the mutation, was also low.

“At first, I was very surprised at the result. The risks we found were lower than I expected,” Dr. De said. “These results raise the question of how to classify the risks of these variants.”

Despite these results, the risk associated with some genetic mutations remained high. for example, Breast cancer gene BRCA1 When BRCA2 Both have an average penetration of 38% and the individual variants are between 0 and 100%.

Further results show other benefits of using biobank data. In one example, researchers were able to calculate the risk of individual mutations associated with age-related disorders, such as type 2 diabetes, breast cancer, and some forms of prostate cancer. On average, the penetrance of these variants was about 10% for individuals over 70 years old, compared to about 8% for individuals over 20 years old.

The team also discovered that the presence of several subspecies could be dependent on the ethnicity of the individual and identified more than 100 subspecies specifically found in individuals of non-European offspring.

Finally, the author listed some potential ways in which the study itself may have underestimated or overestimated the reported risks.

“We need to do more research, but I feel that this research is ultimately a good first step in providing doctors and patients with the accurate and subtle information needed to make a more accurate diagnosis. “I am,” said Dr. Do.

Researchers develop tests to measure the effects of breast cancer gene variants

For more information:
Forrest, IS, et al; Population-based penetration of adverse clinical mutations, JAMA, January 25, 2022, DOI: 10.1001 / jama.2021.23686

Quote: Most “pathogenic” gene mutations are at risk of causing the disease obtained from https: // on January 25, 2022. Low (January 25, 2022)

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