Reclassification of coronary artery disease risk using genetic risk score among subjects with borderline or intermediate clinical risk.
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ABSTRACT:
SUBMITTER: Ahmed R
PROVIDER: S-EPMC9579501 | biostudies-literature | 2022 Dec
REPOSITORIES: biostudies-literature
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Reclassification of coronary artery disease risk using genetic risk score among subjects with borderline or intermediate clinical risk.
Ahmed Razina A RA Shi Zhuqing Z Rifkin Andrew S AS Wei Jun J Lilly Zheng S S Helfand Brian T BT Hulick Peter J PJ Woo Jonathan S H JSH Qamar Arman A Davidson David J DJ Billings Liana K LK Xu Jianfeng J
International journal of cardiology. Heart & vasculature 20221013
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Project description:To determine the potential of a non-invasive acoustic device (CADScor®System) to reclassify patients with intermediate pre-test probability (PTP) and clinically suspected stable coronary artery disease (CAD) into a low probability group thereby ruling out significant CAD. Audio recordings and clinical data from three studies were collected in a single database. In all studies, patients with a coronary CT angiography indicating CAD were referred to coronary angiography. Audio recordings of heart sounds were processed to construct a CAD-score. PTP was calculated using the updated Diamond-Forrester score and patients were classified according to the current ESC guidelines for stable CAD: low < 15%, intermediate 15-85% and high > 85% PTP. Intermediate PTP patients were re-classified to low probability if the CAD-score was ≤ 20. Of 2245 patients, 212 (9.4%) had significant CAD confirmed by coronary angiography ( ≥ 50% diameter stenosis). The average CAD-score was higher in patients with significant CAD (38.4 ± 13.9) compared to the remaining patients (25.1 ± 13.8; p < 0.001). The reclassification increased the proportion of low PTP patients from 13.6% to 41.8%, reducing the proportion of intermediate PTP patients from 83.4% to 55.2%. Before reclassification 7 (3.1%) low PTP patients had CAD, whereas post-reclassification this number increased to 28 (4.0%) (p = 0.52). The net reclassification index was 0.209. Utilization of a low-cost acoustic device in patients with intermediate PTP could potentially reduce the number of patients referred for further testing, without a significant increase in the false negative rate, and thus improve the cost-effectiveness for patients with suspected stable CAD.
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Project description:The current guidelines recommend the new risk score, Atherosclerotic Cardiovascular Disease score (ASCVD), to assess an individual׳s risk of future cardiovascular disease (CVD) events. No data exist on the predictive utility of ASCVD score with the incremental value of coronary artery calcium scoring (CACS) across ethnicities and gender. Multi-Ethnic Study of Atherosclerosis (MESA) is a population based study (n=6814) of White (38%), Black (28%), Chinese (22%) and Hispanic (12%) subjects, aged 45-84 years, free from clinical cardiovascular disease. We performed a post-hoc analysis of 6742 participants (mean age 62, 53% female) from the MESA cohort. We evaluated the predictive accuracy for the ASCVD score for each participant in accord with the American College of Cardiology/American Heart Association guidelines using pooled cohort equations. Similar to the publication by Fudim et al. "The Metabolic Syndrome, Coronary Artery Calcium Score and Cardiovascular Risk Reclassification" [1] the analytic properties of models incorporating the ASCVD score with and without CACS were compared for cardiovascular disease CVD prediction. Here the analysis focused on ASCVD score (with and without CACS) performance across gender and ethnicities.
| S-EPMC4731459 | biostudies-literature
Project description:BackgroundCoronary artery disease (CAD) risk traditionally has been assessed using clinical risk factors. We evaluated whether molecular genetic markers for CAD risk could add information to traditional variables.MethodsWe developed a false discovery rate 267-marker genetic risk score (FDR267) from markers that were significantly associated with CAD in the UK Biobank cohort meta-analysis. FDR267 was tested in the Atherosclerosis Risk in Communities cohort using logistic regression and Cox proportional hazards analyses in the European and African American groups.ResultsOur genetic risk score (FDR267) was associated with a 1.45 (95% confidence interval, 1.39-1.51) increase in odds ratio and a 1.32 (95% confidence interval, 1.26-1.38) increase in hazard ratio per standard deviation of the score. The score modestly improved the area under the curve (AUC) statistic when added to a clinical model (ΔAUC = 0.0112, P = 0.0002). FDR267 predicted incident CAD (C-index = 0.60), although it did not improve on clinical risk factors (ΔAUC = 0.0159, P = 0.0965). Individuals in the top quintile of FDR267 genetic risk were at approximately 2-fold increased risk compared with the bottom quintile, which is comparable to risk associated with self-reported family history. The performance of FDR267 was less robust in the African American sample.ConclusionsFDR267 is significantly associated with CAD in the European sample, with an effect size comparable to self-reported family history. FDR267 discriminated between individuals with and without CAD, but did not improve CAD risk prediction over clinical variables. FDR267 was less predictive of CAD risk in African Americans.
| S-EPMC7063618 | biostudies-literature
Project description:AimThe modest added predictive value of the existing genetic risk scores (GRSs) for coronary artery disease (CAD) could be partly due to missing genetic components, hidden in the genetic architecture of intermediate phenotypes such as coronary artery calcification (CAC). In this study, we investigated the predictive ability of CAC GRS for CAD.Materials and methodsWe investigated the association of CAC GRSs with CAD and coronary calcification among the participants in the Ludwigshafen Risk and Cardiovascular Health study (LURIC) (n = 2742), the Tampere Vascular Study (TVS) (n = 133), and the Tampere Sudden Death Study (TSDS) (n = 660) using summary data from the largest multi-ancestry GWAS meta-analysis of CAC to date. Added predictive value of the CAC GRS over the traditional CVD risk factors as well as metaGRS, a GRS for CAD constructed with 1.7 million genetic variants, was tested with standard train-test machine learning approach using the LURIC data, which had the largest sample size.ResultsCAC GRS was significantly associated with CAD in LURIC (OR=1.41, 95 % CI [1.28-1.55]), TVS (OR=1.79, 95 % CI [1.05-3.21]) as well as in TSDS (OR=4.20, 95 % CI [1.74-10.52]). CAC GRS showed strong association with calcification areas in left (OR=1.78, 95 % CI [1.16-2.74]) and right (OR=1.71, 95 % CI [1.98-2.67]) coronary arteries. There was statistically significant added predictive value of the CAC GRS for CAD over the used traditional CVD risk factors (AUC 0.734 vs 0.717, p-value = 0.02). Furthermore, CAC GRS improved the prediction accuracy for CAD when combined with metaGRS.ConclusionsThis study showed that CAC GRS is a new risk marker for CAD in three European cohorts, with added predictive value over the traditional CVD risk factors.
| S-EPMC11525111 | biostudies-literature
Project description:BackgroundThe value of polygenic risk scores (PRSs) towards improving guideline-recommended clinical risk models for coronary artery disease (CAD) prediction is controversial. Here we examine whether an integrated polygenic risk score improves the prediction of CAD beyond pooled cohort equations. METHODS: An observation study of 291,305 unrelated White British UK Biobank participants enrolled from 2006 to 2010 was conducted. A case-control sample of 9499 prevalent CAD cases and an equal number of randomly selected controls was used for tuning and integrating of the polygenic risk scores. A separate cohort of 272,307 individuals (with follow-up to 2020) was used to examine the risk prediction performance of pooled cohort equations, integrated polygenic risk score, and PRS-enhanced pooled cohort equation for incident CAD cases. The performance of each model was analyzed by discrimination and risk reclassification using a 7.5% threshold.ResultsIn the cohort of 272,307 individuals (mean age, 56.7 years) used to analyze predictive accuracy, there were 7036 incident CAD cases over a 12-year follow-up period. Model discrimination was tested for integrated polygenic risk score, pooled cohort equation, and PRS-enhanced pooled cohort equation with reported C-statistics of 0.640 (95% CI, 0.634-0.646), 0.718 (95% CI, 0.713-0.723), and 0.753 (95% CI, 0.748-0.758), respectively. Risk reclassification for the addition of the integrated polygenic risk score to the pooled cohort equation at a 7.5% risk threshold resulted in a net reclassification improvement of 0.117 (95% CI, 0.102 to 0.129) for cases and - 0.023 (95% CI, - 0.025 to - 0.022) for noncases [overall: 0.093 (95% CI, 0.08 to 0.104)]. For incident CAD cases, this represented 14.2% correctly reclassified to the higher-risk category and 2.6% incorrectly reclassified to the lower-risk category.ConclusionsAddition of the integrated polygenic risk score for CAD to the pooled cohort questions improves the predictive accuracy for incident CAD and clinical risk classification in the White British from the UK Biobank. These findings suggest that an integrated polygenic risk score may enhance CAD risk prediction and screening in the White British population.
| S-EPMC9639312 | biostudies-literature
Project description:BackgroundHigh-risk coronary artery plaque (HRP) is associated with increased risk of acute coronary syndrome. We aimed to investigate the prevalence of HRP in asymptomatic patients with type 2 diabetes (T2D), and its relation to patient characteristics including cardiovascular risk factors, diabetes profile, and coronary artery calcium score (CACS).MethodsAsymptomatic patients with T2D and no previous coronary artery disease (CAD) were studied using coronary computed tomography angiography (CCTA) in this descriptive study. Plaques with two or more high-risk features (HRP) defined by low attenuation, positive remodeling, spotty calcification, and napkin-ring sign were considered HRP. In addition, total atheroma volume (TAV), proportions of dense calcium, fibrous, fibrous-fatty and necrotic core volumes were assessed. The CACS was obtained from non-enhanced images by the Agatston method. Cardiovascular and diabetic profiles were assessed in all patients.ResultsIn 230 patients CCTA was diagnostic and 161 HRP were detected in 86 patients (37%). Male gender (OR 4.19, 95% CI 1.99-8.87; p < 0.01), tobacco exposure in pack years (OR 1.02, 95% CI 1.00-1.03; p = 0.03), and glycated hemoglobin (HbA1c) (OR 1.04, 95% CI 1.02-1.07; p < 0.01) were independent predictors of HRP. No relationship was found to other risk factors. HRP was not associated with increased CACS, and 13 (23%) patients with zero CACS had at least one HRP.ConclusionA high prevalence of HRP was detected in this population of asymptomatic T2D. The presence of HRP was associated with a particular patient profile, but was not ruled out by the absence of coronary artery calcium. CCTA provides important information on plaque morphology, which may be used to risk stratify this high-risk population. Trial registration This trial was retrospectively registered at clinical trials.gov January 11, 2017 trial identifier NCT03016910.
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Project description:Current guidelines recommend that coronary artery calcium (CAC) screening should only be used for intermediate risk groups (Framingham risk score [FRS] of 10%-20%). The CAC distributions and coronary artery disease (CAD) prevalence in various FRS strata were determined. The benefit to lower risk populations of CAC score-based screening was also assessed. In total, 1,854 participants (aged 40-79 years) without history of CAD, stroke, or diabetes were enrolled. CAC scores of > 0, ≥ 100, and ≥ 300 were present in 33.8%, 8.2%, and 2.9% of the participants, respectively. The CAC scores rose significantly as the FRS grew more severe (P < 0.01). The total CAD prevalence was 6.1%. The occult CAD prevalence in the FRS ≤ 5%, 6%-10%, 11%-20%, and > 20% strata were 3.4%, 6.7%, 9.0%, and 11.6% (P < 0.001). In multivariate logistic regression analysis adjusting, not only the intermediate and high risk groups but also the low risk (FRS 6%-10%) group had significantly increased odds ratio for occult CAD compared to the very low-risk (FRS ≤ 5%) group (1.89 [95% confidence interval, CI, 1.09-3.29] in FRS 6%-10%; 2.48 [95% CI, 1.47-4.20] in FRS 11%-20%; and 3.10 [95% CI, 1.75-5.47] in FRS > 20%; P < 0.05). In conclusion, the yield of screening for significant CAC and occult CAD is low in the very low risk population but it rises in low and intermediate risk populations.
| S-EPMC4853669 | biostudies-literature
Project description:AimsInsulin resistance associates with development of metabolic syndrome and risk of cardiovascular disease. The link between insulin resistance and cardiovascular disease is complex and multifactorial. Confirming the genetic link between insulin resistance, type 2 diabetes, and coronary artery disease, as well as the extent of coronary artery disease, is important and may provide better risk stratification for patients at risk. We investigated whether a genetic risk score of 53 single nucleotide polymorphisms known to be associated with insulin resistance phenotypes was associated with diabetes and burden of coronary artery disease.Methods and resultsWe genotyped patients with a coronary angiography performed in the capital region of Denmark from 2010-2014 and constructed a genetic risk score of the 53 single nucleotide polymorphisms. Logistic regression using quartiles of the genetic risk score was performed to determine associations with diabetes and coronary artery disease. Associations with the extent of coronary artery disease, defined as one-, two- or three-vessel coronary artery disease, was determined by multinomial logistic regression. We identified 4,963 patients, of which 17% had diabetes and 55% had significant coronary artery disease. Of the latter, 27%, 14% and 14% had one, two or three-vessel coronary artery disease, respectively. No significant increased risk of diabetes was identified comparing the highest genetic risk score quartile with the lowest. An increased risk of coronary artery disease was found for patients with the highest genetic risk score quartile in both unadjusted and adjusted analyses, OR 1.21 (95% CI: 1.03, 1.42, p = 0.02) and 1.25 (95% CI 1.06, 1.48, p<0.01), respectively. In the adjusted multinomial logistic regression, patients in the highest genetic risk score quartile were more likely to develop three-vessel coronary artery disease compared with patients in the lowest genetic risk score quartile, OR 1.41 (95% CI: 1.10, 1.82, p<0.01).ConclusionsAmong patients referred for coronary angiography, only a strong genetic predisposition to insulin resistance was associated with risk of coronary artery disease and with a greater disease burden.
| S-EPMC8213191 | biostudies-literature
Project description:ImportanceThe incremental value of polygenic risk scores in addition to well-established risk prediction models for coronary artery disease (CAD) is uncertain.ObjectiveTo examine whether a polygenic risk score for CAD improves risk prediction beyond pooled cohort equations.Design, setting, and participantsObservational study of UK Biobank participants enrolled from 2006 to 2010. A case-control sample of 15 947 prevalent CAD cases and equal number of age and sex frequency-matched controls was used to optimize the predictive performance of a polygenic risk score for CAD based on summary statistics from published genome-wide association studies. A separate cohort of 352 660 individuals (with follow-up to 2017) was used to evaluate the predictive accuracy of the polygenic risk score, pooled cohort equations, and both combined for incident CAD.ExposuresPolygenic risk score for CAD, pooled cohort equations, and both combined.Main outcomes and measuresCAD (myocardial infarction and its related sequelae). Discrimination, calibration, and reclassification using a risk threshold of 7.5% were assessed.ResultsIn the cohort of 352 660 participants (mean age, 55.9 years; 205 297 women [58.2%]) used to evaluate the predictive accuracy of the examined models, there were 6272 incident CAD events over a median of 8 years of follow-up. CAD discrimination for polygenic risk score, pooled cohort equations, and both combined resulted in C statistics of 0.61 (95% CI, 0.60 to 0.62), 0.76 (95% CI, 0.75 to 0.77), and 0.78 (95% CI, 0.77 to 0.79), respectively. The change in C statistic between the latter 2 models was 0.02 (95% CI, 0.01 to 0.03). Calibration of the models showed overestimation of risk by pooled cohort equations, which was corrected after recalibration. Using a risk threshold of 7.5%, addition of the polygenic risk score to pooled cohort equations resulted in a net reclassification improvement of 4.4% (95% CI, 3.5% to 5.3%) for cases and -0.4% (95% CI, -0.5% to -0.4%) for noncases (overall net reclassification improvement, 4.0% [95% CI, 3.1% to 4.9%]).Conclusions and relevanceThe addition of a polygenic risk score for CAD to pooled cohort equations was associated with a statistically significant, yet modest, improvement in the predictive accuracy for incident CAD and improved risk stratification for only a small proportion of individuals. The use of genetic information over the pooled cohort equations model warrants further investigation before clinical implementation.
| S-EPMC7042853 | biostudies-literature
Project description:ObjectiveThe correlation between the extent of fatty streaks, more advanced atherosclerotic lesions, and community rates of coronary artery disease (CAD) is substantially higher for the coronary artery compared to the aorta. We sought to determine whether a genetic basis contributes to these differences.Approach and resultsWe conducted a cluster analysis of 6 subclinical atherosclerosis phenotypes documented in 564 white participants of the Pathobiological Determinants of Atherosclerosis in Youth study including the extent of fatty streaks and raised lesions in the coronary artery (CF and CR), thoracic aorta (TF and TR), and abdominal aorta (AF and AR) followed by a genetic association analysis of the same phenotypes. Our cluster analysis grouped all raised lesions and fatty streaks in the coronary into one cluster (CF, CR, TR, and AR) and the fatty streaks in the aorta into a second cluster (TF and AF). We found a genetic risk score of high-risk alleles at 57 susceptibility loci for CAD to be variably associated with the phenotypes in the first cluster (OR: 1.30 p = 0.009 for being in top quartile of degree of involvement of CF, 1.34 p = 0.005 for CR, 1.25: p = 0.11 for TR, and 1.19 p = 0.08 for AR) but not at all with the phenotypes in the second cluster (OR: 1.01, p = 0.95 for TF and 0.98, p = 0.82 for AF).ConclusionsThe genetic determinants of fatty streaks in the aorta do not appear to overlap substantially with the genetic determinants of fatty streaks in the coronary as well as raised lesions in both the coronary and the aorta. These findings may explain why a larger fraction of fatty streaks in the aorta are less likely to progress to raised lesions compared to the coronary artery.
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