Abstract
Risk-guided intervention in the US, informed by the pooled cohort equations (PCE) risk calculator, is the accepted practice for prevention of atherosclerotic cardiovascular disease (ASCVD). We recently showed that a polygenic risk score (PRS, summarising common genetic risk) can be integrated with PCE into an integrated risk tool (IRT) and we validated its utility across multiple contexts including sex, age, genetic ancestry and self-identified ethnicity (Weale et al 2021). The addition of PRS is always beneficial, but its contribution varies by context. When meta-analysed across multiple cohorts, the PRS is more predictive in men (odds ratio per standard deviation, ORsd=1.57) than women (ORsd=1.46). Across ethnicities, the group with the lowest effect size is African American (ORsd=1.14 in men, ORsd=1.11 in women), a result that predominantly reflects a lack of available training samples. The availability of a CVD IRT has practical clinical implications. Because the IRT substantially spreads the risk scores in a given patient stratum, the inclusion of genetic factors can result in some individuals crossing actionable risk thresholds in both directions. Using UK Biobank, a large UK population cohort aged 45-64 with extensive medical and genetic information, we show that the rates of up/down classification are 7.8%/4.2% in younger men (40-54yo), 1.9%/11.6% in older men (55-69yo), 1.0%/0.2% in younger women, and 6.5%/6.6% in older women. This implies a tendency to under-treat in younger and over-treat in older individuals under current guidelines. Model discrimination (Harrell’s C, a measure of area-under-the-curve for survival data) is also greatest in the younger (C=0.751/0.732 in men/women) vs older (C=0.666/0.697 in men/women) age group. Given the increased up-classification and discrimination in the younger group, the addition of genetics provides an opportunity for earlier intervention in those most at risk.
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