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Updated: Jun 22, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Polygenic Risk, Rare Variants, and Family History: Independent and Additive Effects on Coronary Heart Disease
Seyedmohammad Saadatagah1, Mohammadreza Naderian1, Ozan Dikilitas2
1Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
Insights
A polygenic risk score (PRS) for coronary heart disease (CHD) improves risk prediction, especially in younger individuals. Genetic factors like familial hypercholesterolemia (FH) and family history (FamHx) add independently to PRS for comprehensive CHD risk assessment.
Area of Science:
- Cardiovascular Genetics
- Predictive Modeling
- Genomic Epidemiology
Background:
- Current coronary heart disease (CHD) prediction models often exclude genetic factors.
- Understanding the role of genetic predisposition is crucial for accurate risk assessment.
Purpose of the Study:
- To evaluate the predictive utility of a polygenic risk score (PRS) for CHD.
- To determine if risks from familial hypercholesterolemia (FH) and family history (FamHx) are independent and additive to PRS.
Main Methods:
- Utilized UK Biobank data with 323,373 participants for PRS calculation (PRSCHD) and risk estimation using Pooled Cohort Equations (PCE).
- Assessed predictive performance using Area Under the Curve (AUC) and Net Reclassification Improvement (NRI).
- Defined FH by pathogenic variants in *LDLR*, *APOB*, or *PCSK9*; FamHx by first-degree relative diagnosis.
Main Results:
- Incorporating PRSCHD into PCE increased AUC from 0.759 to 0.773, with greater improvement in those under 55.
- High PRS (≥95th percentile) conferred independent risk compared to FH and FamHx.
- Combined genetic risks from PRSCHD, FH, and FamHx were additive.
Conclusions:
- PRSCHD enhances CHD risk prediction, particularly in younger populations.
- The genetic risks associated with PRSCHD, FH, and FamHx are independent and additive.
- Combining these genetic factors provides a more comprehensive CHD risk assessment.
Background:
Genetic factors are not included in prediction models for coronary heart disease (CHD).
Objectives:
The authors assessed the predictive utility of a polygenic risk score (PRS) for CHD (defined as myocardial infarction, coronary revascularization, or cardiovascular death) and whether the risks due to monogenic familial hypercholesterolemia (FH) and family history (FamHx) are independent of and additive to the PRS.
Methods:
In UK-biobank participants, PRSCHD was calculated using metaGRS, and 10-year risk for incident CHD was estimated using the pooled cohort equations (PCE). The area under the curve (AUC) of the receiver operator curve and net reclassification improvement (NRI) were assessed. FH was defined as the presence of a pathogenic or likely pathogenic variant in LDLR, APOB, or PCSK9. FamHx was defined as a diagnosis of CHD in first-degree relatives. Independent and additive effects of PRSCHD, FH, and FamHx were evaluated in stratified analyses.
Results:
In 323,373 participants with genotype data, the addition of PRSCHD to PCE increased the AUC from 0.759 (95% CI: 0.755-0.763) to 0.773 (95% CI: 0.769-0.777). The AUC and NRIEvent for PRSCHD were higher before the age of 55 years. Of 199,997 participants with exome sequence data, 10,000 had a PRSCHD ≥95th percentile (PRSP95), 673 had FH, and 46,163 had FamHx. The CHD risk associated with PRSP95 was independent of FH and FamHx. The risks associated with combinations of PRSCHD, FH, and FamHx were additive and comprehensive estimates could be obtained by multiplying the risk from each genetic factor.
Conclusions:
Incorporating PRSCHD into the PCE improves risk prediction for CHD, especially at younger ages. The associations of PRSCHD, FH, and FamHx with CHD were independent and additive.
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