7 - Polygenic Risk Scores

BackgroundTo externally validate the Prediction for ASCVD Risk in China (PAR) risk equation for predicting the 5-year atherosclerotic cardiovascular disease (ASCVD) risk in the Uyghur and Kazakh populations from rural areas in northwestern China and compare its performance with those of the pooled cohort equations (PCE) and Framingham risk score (FRS).MethodsThe final analysis included 3347 subjects aged 40–74 years without CVD at baseline. The 5-year ASCVD risk was calculated using the PAR, PCE, and FRS. Discrimination, calibration, and clinical usefulness of the three equations in predicting the 5-year ASCVD risk were assessed before and after recalibration.ResultsOf 3347 included subjects, 1839 were female. We observed 286 ASCVD events in within 5-year follow-up. All three risk equations had moderate discrimination in both men and women. C-indices of PAR, PCE, and FRS were 0.727 (95% CI, 0.725–0.729), 0.727 (95% CI, 0.725–0.729), and 0.740 (95% CI, 0.738–0.742), respectively, in men; the corresponding C-indices were 0.738 (95% CI, 0.737–0.739), 0.731 (95% CI, 0.730–0.732), and 0.761 (95% CI, 0.760–0.762), respectively, in women. PCE, PAR and FRS substantially underestimated the 5-year ASCVD risk in women by 70, 23 and 51%, respectively. However, PAR and FRS fairly predicted the risk in men and PAR was well calibrated. The calibrations of the three risk equations could be changed by recalibration. The decision curve analyses demonstrated that at the threshold risk of 5%, PCE was the most clinically useful in both men and women after recalibration.ConclusionsAll three risk equations underestimated the 5-year ASCVD risk in women, while PAR and FRS fairly predicted that in men. However, the results of predictive performances for three risk equations are inconsistent, more accurate risk equations are required in the primary prevention of ASCVD aiming to this Uyghur and Kazakh populations.

Introduction: Patients with atherosclerotic cardiovascular disease (ASCVD) have high risk for recurrent ASCVD events despite statin use. Pooled cohort equations (PCE) are used for ASCVD risk prediction in primary prevention but there are no validated models for recurrent risk prediction in secondary prevention. Machine learning (ML) demonstrates promise in developing novel risk prediction models using electronic health record (EHR) data. Methods: We included adults with prior ASCVD from EHR data from an outpatient Northern California system between January 1, 2009 and December 31, 2018 with at least 2 visits at least 1 year apart and 5 years of follow up. The outcome was a recurrent ASCVD event defined as the first myocardial infarction, stroke, or fatal coronary artery disease in the 5 year follow-up period. We trained ML models to predict recurrent ASCVD risk: random forests (RF), gradient boosted machines (GBM), extreme gradient boosted models (XGBoost), and logistic regression with a standard L 2 penalty (LR) and an L 1 penalty (Lasso). We evaluated performance of ML models and the PCE on a 20% held-out test cohort using the areas under the receiver operating characteristic curves (AUCs). Results: Our cohort consisted of 32,192 patients with ASCVD (Mean age 70 years, 46% women, 12% Asian and 6% Hispanic). Less than half (49%) were on guideline directed statins. XGBoost and GBM were the best performing models for recurrent ASCVD risk prediction, while the PCE performed poorly (Figure). The top 20 predictive variables for recurrent ASCVD risk included prior events (ischemic stroke, myocardial infarction), traditional risk factors (age, blood pressure, lipid levels) and socioeconomic factors (income, education). Conclusions: EHR-trained machine learning models facilitated recurrent ASCVD risk prediction in real-world secondary prevention patients. Machine learning models developed from large datasets may help bridge contemporary gaps in ASCVD risk prediction.

Background: It is unknown how the identification of undiagnosed DM (UDM) among Chinese changes the estimation of atherosclerotic cardiovascular disease (ASCVD) risk using the Chinese and the U.S. risk calculators. Methods: We included 1884 adults aged 30-75 free of ASCVD from 4 urban and rural communities in Shanxi Province, China. UDM was defined as newly found DM by glucose or HbA1c with no DM history or DM medication. 10-year ASCVD risk was estimated using the Prediction for ASCVD Risk in China (China-PAR) score and 2013 AHA/ACC Pooled Cohort Equation (PCE) and classified into risk categories. For those with UDM, the risk scores were calculated before and after DM diagnosis. Results: Among 266 (14.1%) DM patients, 161 (8.5%) were UDM. Compared to those with diagnosed DM, those with UDM had milder DM and better CVD risk profiles. The mean China-PAR among non-DM, UDM (before diagnosis) and diagnosed DM were 6.0% 14.3% and 18.8% and mean PCE were 2.5%, 5.3% and 13.0%, respectively. Among those with UDM, the mean China-PAR and PCE increased to 16.7% and 9.2% after DM diagnosis (both p <0.0001); 6.2% and 34.8% were reclassified into higher risk groups according to the Chinese and U.S. guidelines (Figure). Conclusion: Identification of UDM had greater impact on estimated ASCVD risk using PCE than China-PAR among Chinese and may change the preventive treatment by risk reclassification. Disclosure J. Yang: None. Y. Zhao: None. Y. Ren: None. L. Lan: None. L. Xu: None. J. Yin: None. Q. Xu: None. Y. Li: None. Funding Research Fund for Public Welfare, National Health, and Family Planning Commission of China (201402005)

Association between estimated glomerular filtration rate and 10-year atherosclerotic cardiovascular disease risk among community residents in Shanghai, China

Introduction: Lifestyle measures, such as adoption of the DASH diet, weight reduction, and exercise, are effective in lowering blood pressure. The degree to which these behaviors reduce the risk of cardiovascular events is not well-established. We examined the effect of dietary and weight management inventions used in the ENCORE study on the 10-year risk of atherosclerotic cardiovascular disease (ASCVD), as defined by the Pooled Cohort Equations. Methods: Participants included 129 overweight or obese men and women between the ages of 40 and 80 years who had blood pressure 130-160/80-99 mmHg and who were not treated with antihypertensive medications. Subjects were randomized to 16 weeks of DASH diet plus behavioral weight management (consisting of nutritional counseling and a behavioral weight management program)(DASH+WM), DASH diet alone (consisting of nutritional counseling without exercise or caloric restriction)(DASH), or usual care (UC). Results: The participants averaged 53.5±8.8 years of age; 68% were female, and 60% were white. One had diabetes and 11 (9%) were smokers. Systolic BP averaged 138±9 mmHg; total and HDL cholesterol averaged 203±36 mg/dl and 55±14 mg/dl, respectively. The average estimated 10-year risk of ASCVD for the entire cohort was 5.7%. The baseline characteristics of the subjects randomized to DASH+WM (n=46), DASH (n=39), and UC (n=44) were similar. Participants in the DASH+WM and DASH interventions had significant decreases in systolic blood pressure, and those in the DASH+WM group had a significant decrease in total cholesterol. Post-intervention estimated 10-year ASCVD risk [mean(SE)], adjusted for baseline values, was 4.4(0.2)% for DASH+WM, 5.0(0.3)% for DASH, and 5.7(0.2)% for UC (p<.001 for DASH+WM vs UC; p<.05 for DASH vs UC). The number of untreated subjects with an indication for consideration of statin therapy, as recommended in the 2013 ACC/AHA Guideline for the Treatment of Blood Cholesterol, fell from 11 to 6 in DASH+WM and from 12 to 10 in DASH, while remaining unchanged (11) in UC. Conclusions: In overweight or obese men and women with high BP, lifestyle interventions reduce the predicted 10-year risk of ASCVD and decrease the number of individuals in whom statin therapy is recommended.

We compared the atherosclerotic cardiovascular disease (ASCVD) risk prediction performance of the American Heart Association's Predicting Risk of Cardiovascular Disease Events (PREVENT) Base and PREVENT Full equations (includes urine albumin/creatinine ratio, glycated hemoglobin, and social deprivation index) with the pooled cohort equations (PCEs). We included adults, aged 40 to 75 years, with no history of ASCVD, diabetes, or statin use in 2009 from Kaiser Permanente Southern California and followed up through 2019. ASCVD was defined as myocardial infarction, fatal coronary heart disease, and fatal and nonfatal ischemic stroke. We compared model discrimination (Harrell C), mean calibration (estimated as the ratio of predicted/observed event rates), and calibration curve among the overall population and stratified by sex and race and ethnicity. Of the 559 241 adults (mean age, 54 years; 11% Asian, 11% non-Hispanic Black, and 32% Hispanic), 10 695 developed an ASCVD event (median follow-up, 10 years). Harrell C was 0.741 (95% CI, 0.736-0.745) for PREVENT Base, 0.743 (95% CI, 0.738-0.748) for PREVENT Full, and 0.741 (95% CI, 0.736-0.746) for the PCEs. Compared with the PCEs, both PREVENT equations improved Harrell C in men but not women, and in non-Hispanic Black adults but not in other races and ethnicities. Both PREVENT equations were well calibrated (mean calibration, 0.85-1.36; calibration slope, 0.69-1.27), whereas the PCEs overestimated 10-year ASCVD risk (mean calibration, 1.80-2.18; calibration slope, 0.32-0.45). Compared with the PCEs, PREVENT Base and Full equations better predict absolute 10-year ASCVD risk across sex and racial and ethnic groups in a contemporary US adult population.

Aims Chronic kidney disease (CKD) and diabetes mellitus increase atherosclerotic cardiovascular diseases (ASCVD) risk. However, the association between renal outcome of diabetic kidney disease (DKD) and ASCVD risk is unclear. Methods This retrospective study enrolled 218 type 2 diabetic patients with biopsy-proven DKD, and without known cardiovascular diseases. Baseline characteristics were obtained and the 10-year ASCVD risk score was calculated using the Pooled Cohort Equation (PCE). Renal outcome was defined as progression to end-stage renal disease (ESRD). The association between ASCVD risk and renal function and outcome was analyzed with logistic regression and Cox analysis. Results Among all patients, the median 10-year ASCVD risk score was 14.1%. The median of ASCVD risk score in CKD stage 1, 2, 3, and 4 was 10.9%, 12.3%, 16.5%, and 14.8%, respectively (p = 0.268). Compared with patients with lower ASCVD risk (＜14.1%), those with higher ASCVD risk had lower eGFR, higher systolic blood pressure, and more severe renal interstitial inflammation. High ASCVD risk (>14.1%) was an independent indicator of renal dysfunction in multivariable-adjusted logistic analysis (OR, 3.997; 95%CI, 1.385–11.530; p = 0.010), though failed to be an independent risk factor for ESRD in patients with DKD in univariate and multivariate Cox analysis. Conclusions DKD patients even in CKD stage 1 had comparable ASCVD risk score to patients in CKD stage 2, 3, and 4. Higher ASCVD risk indicated severe renal insufficiency, while no prognostic value of ASVCD risk for renal outcome was observed, which implied macroangiopathy and microangiopathy in patients with DKD were related, but relatively independent.

Utility of coronary artery calcium scoring in low-risk patients: The Multi-Ethnic Study of Atherosclerosis (MESA)

BackgroundIn 2023, the American Heart Association published the Predicting Risk of Cardiovascular Disease Events (PREVENT) equations for estimating atherosclerotic cardiovascular disease (ASCVD) risk in adults aged 30 to 79 years. We compared PREVENT's performance with existing US guideline recommended models—Pooled Cohort Equations for 10‐year ASCVD risk and FHS (Framingham Heart Study) equations for 30‐year ASCVD risk—among young adults.MethodsWe analyzed adults aged 20 to 39 years without baseline ASCVD from 2 sources: (1) pooled data from 2 large epidemiologic cohorts (CARDIA [Coronary Artery Risk Development in Young Adults] and FHS, n=7763), and (2) electronic health records from Kaiser Permanente Southern California (n=266 378). Incident ASCVD events were defined as nonfatal myocardial infarction, coronary heart disease death, and fatal/nonfatal stroke at 10 and 30 years.ResultsPREVENT improved 10‐year risk discrimination over Pooled Cohort Equations in both the epidemiologic cohorts (∆Harrell's C, 0.057 [95% CI, 0.013–0.101]) and Kaiser Permanente Southern California (∆Harrell's C=0.041 [95% CI, 0.034–0.049]). The Pooled Cohort Equations overestimated 10‐year risk (mean calibration 3.26 in the epidemiologic cohorts; 1.73 in Kaiser Permanente Southern California), whereas PREVENT was well calibrated in the epidemiologic cohorts (1.10 [95% CI, 0.83–1.73) but underestimated risk in KPSC (0.91 [95% CI, 0.86–0.96]), particularly among Black individuals (0.54 [95% CI, 0.48–0.61]). For 30‐year risk, PREVENT and FHS had similar discrimination, but PREVENT underestimated 30‐year risk (mean calibration 0.63) whereas FHS had good calibration (mean calibration 0.90 to 0.99]).ConclusionsPREVENT may be a better tool for short‐term ASCVD risk assessment in young adults than the PCEs, whereas the FHS equations may be better for long‐term risk assessment than PREVENT in this age group.

Introduction: The Dietary Approaches to Stop Hypertension (DASH) diet lowers estimated 10-year ASCVD (atherosclerotic cardiovascular disease) risk. The impact of sodium reduction, alone or in combination with the DASH diet, is not known. Objective: To determine the effects of the sodium reduction alone and when combined with the DASH diet on 10-year ASCVD risk. Methods: The DASH-Sodium trial randomized 412 adults with systolic blood pressure (BP) 120-159 mmHg and diastolic BP 80-95 mmHg to the DASH diet or a typical American diet (control). Within each arm, individuals consumed 3 different levels of sodium in random order: low (50 mmol/day), medium (100 mmol/day), and high (150 mmol/day). Each period lasted 4 weeks. Pooled cohort equation-estimated 10-year ASCVD risk scores were calculated at baseline and at 4, 8, and 12 weeks of feeding. Results: Among the 412 participants (mean [SD] age 48 [10] years; 57% female, 57% Black), sodium reduction decreased ASCVD risk scores in both DASH and control diets ( Figure 1 ). Compared to high sodium intake, low sodium intake changed ASCVD risk by -9.4% (95% CI -11.7, -7.0). Compared to a typical American diet, the DASH diet changed 10-year ASCVD by -5.3% (95% CI -9.3, -1.2). Compared to a high sodium-control diet, the combination of both low sodium intake with DASH changed ASCVD risk by -14.1% (95% CI -18.6, -9.3). Conclusions: Sodium reduction and the DASH diet both independently reduced 10-year ASCVD risk. Moreover, the combined impact was additive. These findings support dietary sodium reduction in addition to the DASH diet for ASCVD prevention.

Comparative performance of the two pooled cohort equations for predicting atherosclerotic cardiovascular disease

Age-based disparities in statin use for primary prevention in US adults: National Health and Nutrition Examination Surveys 2013–2020

Both traditional and HIV-specific risk factors contribute to greater incidence of cardiovascular disease in persons living with HIV (PLWH). Using state-of-the-art, high-resolution magnetic resonance (MR) imaging of the common carotid arteries, this study aimed to evaluate the relationship between carotid vessel wall thickness (c-VWT) and atherosclerotic cardiovascular disease (ASCVD) risk score in PLWH. Cross-sectional determinations of c-VWT using MR imaging in virally suppressed PLWH without known cardiovascular disease (n=32) and matched controls (n=13) were completed. Clinical data, including ASCVD risk and c-VWT, were compared between groups and regression analyses performed to identify predictors of c-VWT. PLWH had significantly higher c-VWT (1.15 ±0.11 mm versus 1.08 ±0.08 mm; P=0.02) as well as higher diastolic blood pressure compared to controls, but exhibited no differences in 10-year ASCVD risk score, systolic blood pressure or smoking. Ten-year ASCVD risk score (r=0.53, P-value =0.0002), age (r=0.30, P-value <0.05), triglycerides (r=0.33, P-value =0.03) and waist circumference (r=0.36, P-value =0.02) were significantly associated with increased c-VWT. Among PLWH, c-VWT did not differ by protease inhibitor use. In a multivariate regression analysis, ASCVD risk score was the only variable significantly associated with c-VWT (P-value =0.02), whereas, HIV status was not. In this cross-sectional study MR imaging demonstrated that c-VWT, a known marker for CVD risk, was increased in PLWH relative to controls, and that 10-year ASCVD risk was closely related to c-VWT, independent of HIV infection. Our data suggest that traditional cardiovascular disease risk factors in PLWH are adequately captured in the ASCVD risk score which was closely associated with subclinical carotid disease.

BackgroundPrimary prevention of atherosclerotic cardiovascular disease (ASCVD) is a vital component of care for people living with HIV (PLWH). Current guidelines recommend at least moderate intensity statin for low to moderate ASCVD risk and high intensity statin for high risk. Determining ASCVD risk in PLWH is difficult due to a paucity of precise risk calculators. We retrospectively compared available ASCVD risk calculators in a population who had known ASCVD events.MethodsWe included US Military HIV Natural History Study (NHS) participants between 2006-2019 who experienced a known ASCVD event as defined in Table 1. Participants missing data to perform all four calculators were excluded from the analysis. Four risk calculators: American College of Cardiology/American Heart Association Pooled Cohort Equation (PCE), Framingham Heart Study Risk Score (FRS), Data Collection on Adverse Effects of Anti-HIV Drugs (D:A:D) model, and the newly published HIV-CARDIO-PREDICT (HCP) were applied for each participant at 10, 5, and 2 years prior to the ASCVD event. Proportion of participants categorized as high risk was determined for each calculator. Paired calculators were compared by Fisher’s exact or Chi-squared tests.ResultsA total of 134 participants met initial inclusion criteria (Table 2). Of these, 113, 75, and 42 were excluded from the 10, 5, and 2 year analyses respectively due to missing data. HCP had the highest percentage of high-risk participants at any given time interval (Table 3). PCE had the lowest percentage of high-risk participants across all intervals. Head-to head comparison of PCE versus HCP demonstrated a significant difference in proportion of participants classified as high risk at all time intervals (p < 0.0001).ConclusionIn this military study cohort of PLWH who had a known ASCVD event, HCP had the highest sensitivity in classifying participants as high risk at all intervals. PCE, which is guideline recommended for ASCVD risk analysis, had the worst sensitivity. Further understanding of these calculator scores including their driving components over time (especially for HCP), their correlations with outcomes when non-cases are included, and their predictive ability among younger participants are needed.DisclosuresAll Authors: No reported disclosures

OBJECTIVESProper risk assessment is important for the primary prevention of atherosclerotic cardiovascular disease (ASCVD). However, no validated risk prediction tools are currently in use in Korea. This study sought to develop a 10-year risk prediction model for incident ASCVD.METHODSUsing the National Sample Cohort of Korea, 325,934 subjects aged 20-80 years without previous ASCVD were enrolled. ASCVD was defined as a composite of cardiovascular death, myocardial infarction, and stroke. The Korean atherosclerotic cardiovas cular disease risk prediction (K-CVD) model was developed separately for men and women using the development dataset and validated in the validation dataset. Furthermore, the model performance was compared with the Framingham risk score (FRS) and pooled cohort equation (PCE).RESULTSOver 10 years of follow-up, 4,367 ASCVD events occurred in the overall population. The predictors of ASCVD included in the model were age, smoking status, diabetes, systolic blood pressure, lipid profiles, urine protein, and lipid-lowering and blood pressure-lowering treatment. The K-CVD model had good discrimination and strong calibration in the validation dataset (time-dependent area under the curve=0.846; 95% confidence interval, 0.828 to 0.864; calibration χ2=4.73, goodness-of-fit p=0.32). Compared with our model, both FRS and PCE showed worse calibration, overestimating ASCVD risk in the Korean population.CONCLUSIONSThrough a nationwide cohort, we developed a model for 10-year ASCVD risk prediction in a contemporary Korean population. The K-CVD model showed excellent discrimination and calibration in Koreans. This population-based risk prediction tool would help to appropriately identify high-risk individuals and provide preventive interventions in the Korean population.