How Next-Gen Biotechnology Is Transforming Genetic Risk Prediction

By Bio-IT World Staff 

December 3, 2025 | As genetic testing becomes a routine part of modern medicine, researchers are grappling with an unintended consequence: a flood of never-before-seen genetic variants whose clinical significance is unknown. These variants of uncertain significance (VUS), now number in the tens of thousands, outpace the capacity of traditional scientific methods to determine whether they contribute to disease. In response, new tools are being invented to help scientists decode the functional impact of DNA changes, shifting from variant-by-variant investigation to massively parallel, high-throughput experimentation. 

At the heart of this innovative wave is CardioVar Consortium, a multi-institutional effort co-led by Dan Roden, M.D., senior vice president for personalized medicine at Vanderbilt University Medical Center. The consortium focuses on Mendelian heart diseases such as familial hypercholesterolemia (FH) and hypertrophic cardiomyopathy, conditions in which a single DNA mutation can dramatically increase disease risk. In a study recently published in Science (DOI: 10.1126/science.ady7186), researchers from the consortium mapped roughly 17,000 variants for the variant effects for the low-density lipoprotein receptor (LDLR) gene commonly mutated in FH, strongly associated with the development of premature atherosclerotic heart disease. 

To build this map, scientists used a suite of high-throughput cellular assays and advanced computational techniques to generate every conceivable mutation across the 860 amino acids of the LDL receptor protein. Each variant was inserted into a plasmid and expressed individually in cells, yet all were assayed simultaneously. This pooled experimental design enabled researchers to quantify how each mutation altered protein function, creating a color-coded atlas of pathogenicity across the entire gene. 

These functional scores were integrated with genetic and clinical data from massive population databases, including the UK Biobank and the All of Research program. By combining laboratory measurements with real-world phenotypes and polygenic risk scores, scientists demonstrated how single pathogenic variants and the cumulative effect of many small-effect variants jointly shape a person’s cholesterol profile and heart disease risk. Someone carrying a damaging LDLR mutation is three to four times more likely to have high LDL. If that individual also has a high polygenic risk score, the risk increases eightfold. 

Variant effect maps extend beyond cholesterol. They are also emerging for genes linked to cancer, arrhythmias, metabolic disease, and other conditions where early identification could save lives. The technology also highlights that genetics rarely act alone. Environmental factors, lifestyle behaviors, and gene–gene interactions all modify risk, making integrated assessments essential. 

To read the full story written by Deborah Borfitz, visit Diagnostics World News.