Tuesday 16 September 2025
A new approach to predicting risk of disease has been developed, one that takes into account both common and rare genetic variants. The research, published in a leading genetics journal, uses a method called collapsing receiver operating characteristic (CROC) to improve the accuracy of risk prediction models.
For years, researchers have relied on common genetic variants to predict an individual’s risk of developing certain diseases. However, with the advent of next-generation sequencing technology, which allows for the rapid identification of millions of genetic variants, scientists are now able to study rare genetic variants as well. These rare variants can be just as important in determining disease risk as common ones.
The problem is that traditional methods of analyzing genetic data don’t account for these rare variants very well. They’re often ignored or lumped together with more common variants, which can lead to inaccurate predictions.
That’s where the CROC method comes in. By collapsing rare variants into pseudo-common variants and then analyzing them alongside common ones, researchers are able to get a more complete picture of an individual’s genetic makeup and its relationship to disease risk.
In a test using simulated data from the Genetic Analysis Workshop 17, the CROC method was shown to be more accurate than traditional methods. When applied to real-world data, it could potentially lead to improved diagnosis and treatment of diseases.
One of the key advantages of the CROC method is that it’s able to account for bidirectional effects between genetic variants. This means that it can take into account how different genetic variants interact with each other to influence disease risk.
The researchers behind the study say that their approach could be particularly useful in fields such as medicine, where accurate prediction of disease risk is crucial for making informed treatment decisions. They also suggest that it could be used to identify individuals who are at high risk of developing a particular disease, even if they don’t have any symptoms yet.
While more research is needed to fully understand the potential of the CROC method, its developers are optimistic about its future impact on our understanding and prediction of genetic diseases.
Cite this article: “New Approach to Predicting Disease Risk Takes into Account Both Common and Rare Genetic Variants”, The Science Archive, 2025.
Genetic Variants, Disease Risk, Croc Method, Receiver Operating Characteristic, Next-Generation Sequencing, Genetic Analysis, Rare Variants, Common Variants, Bidirectional Effects, Prediction Models
