Polygenic Risk Scores in Predicting Coronary Artery Disease in Symptomatic Patients. A Validation Study.

AIM: Clinical risk scores for coronary artery disease (CAD) are used in clinical practice to select patients for diagnostic testing and therapy. Several studies have proposed that polygenic risk scores (PRSs) can improve the prediction of CAD, but the scores need to be validated in clinical populations with accurately characterized phenotypes. We assessed the predictive power of the three most promising PRSs for the prediction of coronary atherosclerosis and obstructive CAD. METHODS: This study was conducted on 943 symptomatic patients with suspected CAD for whom the phenotype was accurately characterized using anatomic and functional imaging. Previously published genome-wide polygenic scores were generated to compare a genetic model based on PRSs with a model based on clinical data. The test and PRS cohorts were predominantly Caucasian of northern European ancestry. RESULTS: All three PRSs predicted coronary atherosclerosis and obstructive CAD statistically significantly. The predictive accuracy of the models combining clinical data and different PRSs varied between 0.778 and 0.805 in terms of the area under the receiver operating characteristic (AUROC), being close to the model including only clinical variables (AUROC 0.769). The difference between the clinical model and combined clinical + PRS model was not significant for PRS1 (p=0.627) and PRS3 (p=0.061). Only PRS2 slightly improved the predictive power of the model (p=0.04). The likelihood ratios showed the very weak diagnostic power of all PRSs. CONCLUSION: The addition of PRSs to conventional risk factors did not clinically significantly improve the predictive accuracy for either coronary atherosclerosis or obstructive CAD, showing that current PRSs are not justified for routine clinical use in CAD.

Incremental prognostic value of downstream positron emission tomography perfusion imaging after coronary computed tomography angiography: a study using machine learning.

AIMS: To evaluate the incremental value of positron emission tomography (PET) myocardial perfusion imaging (MPI) over coronary computed tomography angiography (CCTA) in predicting short- and long-term outcome using machine learning (ML) approaches. METHODS AND RESULTS: A total of 2411 patients with clinically suspected coronary artery disease (CAD) underwent CCTA, out of whom 891 patients were admitted to downstream PET MPI for haemodynamic evaluation of obstructive coronary stenosis. Two sets of Extreme Gradient Boosting (XGBoost) ML models were trained, one with all the clinical and imaging variables (including PET) and the other with only clinical and CCTA-based variables. Difference in the performance of the two sets was analysed by means of area under the receiver operating characteristic curve (AUC). After the removal of incomplete data entries, 2284 patients remained for further analysis. During the 8-year follow-up, 210 adverse events occurred including 59 myocardial infarctions, 35 unstable angina pectoris, and 116 deaths. The PET MPI data improved the outcome prediction over CCTA during the first 4 years of the observation time and the highest AUC was at the observation time of Year 1 (0.82, 95% confidence interval 0.804-0.827). After that, there was no significant incremental prognostic value by PET MPI. CONCLUSION: PET MPI variables improve the prediction of adverse events beyond CCTA imaging alone for the first 4 years of follow-up. This illustrates the complementary nature of anatomic and functional information in predicting the outcome of patients with suspected CAD.

The impact of diabetes on the relationship of coronary artery disease and outcome: a study using multimodality imaging.

BACKGROUND: Patients with prediabetes or diabetes are at increased risk of developing cardiovascular disease and adverse outcomes. First-line coronary computed tomography angiography (CTA) followed by selective use of positron emission tomography (PET) myocardial perfusion imaging is a feasible strategy to diagnose and risk-stratify patients with suspected coronary artery disease (CAD). The aim of the present study was to study whether diabetes changes the relationship of CAD and long-term outcome. METHODS: We retrospectively identified consecutive symptomatic patients who underwent coronary CTA for suspected CAD. In patients with suspected obstructive CAD on CTA, myocardial ischemia was evaluated by 15O-water PET myocardial perfusion imaging. The relationship of the phenotype of CAD and long-term outcome in patients with no diabetes, prediabetes, or type 2 diabetes was investigated. A composite endpoint included all-cause mortality, myocardial infarction (MI), and unstable angina pectoris (UAP). RESULTS: A total of 1743 patients were included: 1214 (70%) non-diabetic, 259 (15%) prediabetic, and 270 (16%) type 2 diabetic patients. During 6.43 years of median follow-up, 164 adverse events occurred (106 deaths, 41 MIs, 17 UAPs). The prevalence of normal coronary arteries on CTA was highest in the non-diabetic patients (39%). The prevalence of hemodynamically significant CAD (abnormal perfusion) increased from 14% in non-diabetic patients to 20% in prediabetic and 27% in diabetic patients. The event rate was lowest in patients with normal coronary arteries and highest in patients with concomitant type 2 diabetes and hemodynamically significant CAD (annual event rate 0.2% vs. 4.7%). However, neither prediabetes nor diabetes were independent predictors of the composite adverse outcome after adjustment for the clinical risk factors and imaging findings. CONCLUSIONS: Coronary CTA followed by selective downstream use of PET myocardial perfusion imaging predicts long-term outcome similarly in non-diabetic and diabetic patients.

Prognostic value of combined coronary CT angiography and myocardial perfusion imaging in women and men.

AIMS: Combined anatomical and functional imaging enables detection of non-obstructive and obstructive coronary artery disease (CAD) as well as myocardial ischaemia. We evaluated sex differences in disease profile and outcomes after combined computed tomography angiography (CTA) and positron emission tomography (PET) perfusion imaging in patients with suspected obstructive CAD. METHODS AND RESULTS: We retrospectively evaluated 1948 patients (59% women) referred for coronary CTA due to suspected CAD during the years 2008-2016. Patients with a suspected obstructive lesion on coronary CTA (n = 657) underwent 15O-water PET to assess stress myocardial blood flow (MBF). During a mean follow-up of 6.8 years, 182 adverse events (all-cause death, myocardial infarction, or unstable angina) occurred. Women had more often normal coronary arteries (42% vs. 22%, P < 0.001) and less often abnormal stress MBF (9% vs. 28%, P < 0.001) than men. The annual adverse event rate was lower in women vs. men (1.2% vs. 1.7%, P = 0.02). Both in women and men, coronary calcification, non-obstructive CAD, and abnormal stress MBF were independent predictors of events. Abnormal stress MBF was associated with 5.0- and 5.6-fold adverse event rates in women and men, respectively. There was no interaction between sex and coronary calcification, non-obstructive CAD, or abnormal stress MBF in terms of predicting adverse events. CONCLUSION: Among patients evaluated for chronic chest pain, women have a lower prevalence of ischaemic CAD and a lower rate of adverse events. Combined coronary CTA and PET myocardial perfusion imaging predict outcomes equally in women and men.