Genetic screening could cut 33% of global cardiovascular deaths

Cardiovascular diseases (CVD) cause about one in three deaths worldwide. The World Health Organization (WHO) estimates 19.8 million CVD deaths in 2022, roughly 32% of all deaths. Care remains reactive and generic.

AI-powered integration of multi-omics and genomic data improves risk prediction and speeds diagnosis beyond traditional tools, study shows. With the support of advanced genetic technology, clinician can choose the right therapy to the right person, thus easing the burden on patients and health systems.

The stakes are high. New projections in the European Journal of Preventive Cardiology warn crude CVD deaths may reach around 35.6 million by 2050 as populations age, even while age-standardized mortality falls; high systolic blood pressure remains the top driver.

Traditional risk models—such as European Society of Cardiology SCORE2, which estimates 10-year CVD risk from age, sex, blood pressure, cholesterol, and smoking—can miss people who later have events. Imaging often lags disease biology.

Multi-omics fills that gap. Genomics flags inherited risk that standard tests overlook. Metabolomics shows real-time pathway activity tied to diet, microbiome, and environment. Proteomics tracks protein networks that shift before symptoms emerge. AI then connects these signals to outcomes and turns them into simple, usable predictions for clinicians.

Genetics Testing Improving Outcomes

“In the clinic, I often see patients with a family history of cardiovascular disease, and I am trying to tease apart how much of their risk is due to shared lifestyle versus shared genetics,” says Dr. Krishna Aragam, cardiologist at Mass General Brigham, Massachusetts.

One study he led, published in Nature Genetics, described the discovery and systematic characterization of risk variants and genes for coronary artery disease in nearly 1.4 million participants. That research used datasets from several large genomic studies and biobanks that resulted in more than 210,000 cases of cardiovascular disease.

“Seeing and managing these patients definitely informs my research in big-data genomics, where we're looking at hundreds of thousands and sometimes millions of people to figure out which patients are at the highest risk for a disease based on genetic factors,” states the doctor.

Risk programs are moving from broad screening to targeted prevention. “This is one situation where polygenic risk scores are becoming relevant,” adds Dr. Aragam. Genetic risk tests for heart attack, high blood pressure, cholesterol disorders, and rhythm disease are being prepared for clinical use. By leveraging this data, clinics can confirm or rule out inherited disease sooner and guide families with clarity. Hospitals cut readmissions by spotting decompensation earlier from shifting protein and metabolite patterns. Patients get fewer false alarms and more targeted care. Systems see better outcomes with less waste.

Family History Increases CVD Risk

A real case shows why this matters. Katherine Wilemon had a heart attack while gardening at the age of 39, fit and young. The diagnosis, later confirmed as familial hypercholesterolemia, which has the prevalence of about 1 in 250 people.

Genetic diagnosis led to statins plus newer LDL-lowering injections, dropping her LDL (the “bad” cholesterol that fuels artery plaque) from ~385 mg/dL into the mid-20s to low-30s. With familial hypercholesterolemia keeping LDL extremely high, the added injections helped her reach safer levels and spurred cascade screening in her family.

From Genes to Decisions

Genomics is a strong first step. Many families live with undiagnosed monogenic conditions that raise the risk of sudden cardiac events or early heart failure. Fast interpretation is the bottleneck.

BGI Genomics CardioGen connects genotype to phenotype so clinicians can move from “variant found” to an actionable diagnosis, faster and with more confidence. The goal is simple: deliver answers that inform therapy, device decisions, and cascade testing for relatives who may be at risk.

AI makes all of this usable at scale. Journal of Clinical Medicine reviews show multi-omics combined with machine-learning enables earlier diagnosis, sharper risk stratification, and targeted therapy with fewer side effects. It turns high-dimensional molecular data into actionable signals and keeps learning as outcomes accrue.

The shift to precision medicine is about better timing and better matching. See risk earlier. Treat what matters. Monitor what changes. That is how to reduce the global burden of cardiovascular disease—patient by patient, pathway by pathway, decision by decision.

About CardioGen

The total current number of monogenic cardiovascular disease patients worldwide exceeds 10 million. BGI Genomics launched the CardioGen automated interpretation system to help make more accurate clinical interpretations after receiving genetic test results.

About BGI Genomics

BGI Genomics, headquartered in Shenzhen, China, is the world's leading integrated solutions provider of precision medicine. Our services cover more than 100 countries and regions, involving more than 2,300 medical institutions. In July 2017, as a subsidiary of BGI Group, BGI Genomics (300676.SZ) was officially listed on the Shenzhen Stock Exchange.