Abstract Body (Do not enter title and authors here):
Introduction
Polygenic risk scores (PRS) provide a summation of small-effect genetic variants that predict cardiovascular (CV) disease risk. Socioeconomic status (SES) can also impact CV risk, but it is unknown whether SES modifies the effects of PRS on CV events.

Hypothesis
The association between CV PRS and CV events is modified by SES.

Methods
Participants without CV disease at baseline from the UK Biobank prospective cohort study were followed from recruitment (2006-2010) through 2023. We included participants with genetic data (for CV PRS) and CV risk factors assessed at baseline (hemoglobin A1c, total cholesterol, blood pressure, body mass index, physical activity, tobacco use, and sleep). The CV PRS was centered at zero and standardized to one unit variance within each ancestry group. SES was defined by tertiles of index of multiple deprivation (from housing, crime, income, education, employment, health deprivation and disability, and neighborhood environment). The primary outcome was CV events (myocardial infarction, heart failure hospitalization, stroke, or death). Using Cox proportional hazard models, we estimated the total effect of PRS on CV events, tested for interaction of SES in the association between PRS and CV events, and estimated the direct effect of PRS on CV events by adjusting for age, sex, CV risk factors, and SES.

Results
There were 201,374 participants (mean age 55.9 (± 8.1), 53.4% female). CV events occurred in 21,916 (10.9%) participants: 5,754 (2.9 %) myocardial infarctions, 4,061 (2.0%) strokes, 4,312 (2.1%) heart failure hospitalizations, and 12,782 (6.4%) deaths. Each unit of PRS was associated with 1.17 times the risk of CV events (HR 1.17, 95%CI 1.15 to 1.18, p-value < .001, adjusted for age and sex). People with the lowest SES had 1.22 times the risk of CV events (HR 1.22; 95%CI 1.18 to 1.26; p-value <.001) and the middle SES had 1.07 times the risk of CV events (HR 1.07; 95%CI 1.03 to 1.10; p-value <.001) compared to the highest SES, adjusted for age, sex, and CV risk factors. PRS remained associated with CV events (HR 1.15, 95%CI 1.13 to 1.16, p-value<.001) after adjusting for age, sex, CV risk factors, and SES. There was no significant multiplicative interaction between SES and PRS for CV events (interaction p-value = 0.45).

Conclusions
SES is associated with CV events but does not modify the effect of PRS on CV events. Genetic risk remains independently important in CV event risk beyond traditional CV risk factors and SES.