Researchers developed a comprehensive CAD risk prediction model that includes both germline and somatic genomic data. Evaluated in 391,536 UK Biobank participants and validated in 34,177 from TOPMed, it identified hidden risks in individuals previously missed by traditional scores, offering potential for refined early prevention strategies.
The model's clinical value lies in its ability to detect high-risk individuals without major genetic factors and low-risk individuals even when carrying known high-risk variants, suggesting a broader insight into CAD risk factors.