Researchers at Northwestern Medicine developing an integrated genomic risk score to predict heart rhythm risks, shown working in a lab with genetic data and heart monitors.
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Northwestern Medicine develops genetic test for heart rhythm risks

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Researchers at Northwestern Medicine created an integrated genomic risk score that aims to predict dangerous heart rhythms early by combining rare‑variant, polygenic and whole‑genome data. The peer‑reviewed study in Cell Reports Medicine analyzed 1,119 people.

Scientists at Northwestern University Feinberg School of Medicine report an integrated genomic risk score to forecast dangerous heart rhythms, with the peer‑reviewed paper focusing on non‑ischemic ventricular arrhythmias linked to sudden cardiac death. The approach merges information from rare (monogenic) and common (polygenic) variants with whole‑genome sequencing data, according to the authors. The study was published November 11, 2025, in Cell Reports Medicine. (pubmed.ncbi.nlm.nih.gov)

The team enrolled 523 people with clinically confirmed arrhythmias—some also had heart failure—reviewing medical records and implanted device data, and compared them with 596 control participants from Northwestern’s NUgene biobank who were age 40 or older and had no known cardiac disease, for a total sample of 1,119. (sciencedaily.com)

Co‑corresponding author Dr. Elizabeth M. McNally described the method as combining rare and common variants with non‑coding genomic information to create a fuller picture of risk. McNally is director of Northwestern’s Center for Genetic Medicine and a professor of medicine (cardiology) and of biochemistry and molecular genetics. (sciencedaily.com)

The authors report that the integrated score outperformed any single genetic input, with McNally noting the combined model can substantially improve identification of those at highest risk. The PubMed record summarizes the components—18 polygenic scores, clinical panel variants, and non‑coding regulatory regions—and states the combined predictor outperformed individual components and replicated in validation. (pubmed.ncbi.nlm.nih.gov)

In clinical practice, McNally said she uses genetic testing alongside standard assessments such as symptoms, family history, EKGs, echocardiograms and MRIs, and that in high‑risk cases the findings can inform decisions like whether to implant a defibrillator. “Knowledge is power,” she said. (sciencedaily.com)

Despite potential benefits, uptake of genetic testing remains low. McNally estimated that only 1% to 5% of people who could benefit receive testing, and even in oncology the rate is roughly 10% to 20%, citing limited workforce training as a barrier. The team also suggested the framework could be adapted to other complex conditions, including cancer, Parkinson’s disease and autism. (sciencedaily.com)

The paper is titled “A combined genomic arrhythmia propensity score delineates cumulative risk” (DOI: 10.1016/j.xcrm.2025.102455). Northwestern departmental listings and publication pages identify McNally as Center for Genetic Medicine director and list the study among recent publications. (pubmed.ncbi.nlm.nih.gov)

Watu wanasema nini

Discussions on X about Northwestern Medicine's new genetic test for heart rhythm risks are emerging, primarily consisting of neutral shares from scientists, health bloggers, and journals highlighting the integrated genomic risk score's potential for early prediction of arrhythmias using combined genetic data. Reactions emphasize its promise for improved detection and personalized medicine, with no prominent negative or skeptical views identified yet.

Makala yanayohusiana

Illustration of Mayo Clinic study revealing 90% gap in genetic screening for familial hypercholesterolemia, featuring lab scientists, DNA data, heart plaque model, and screening call-to-action.
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Researchers have developed a genomic mapping technique that reveals how thousands of genes work together to influence disease risk, helping to bridge gaps left by traditional genetic studies. The approach, described in a Nature paper led by Gladstone Institutes and Stanford University scientists, combines large-scale cell experiments with population genetics data to highlight promising targets for future therapies and deepen understanding of conditions such as blood disorders and immune-mediated diseases.

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