2018 George Lyman Duff Memorial Lecture: Genetics and Genomics of Coronary Artery Disease: A Decade of Progress

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.

Pharmacogenomics-based systematic review of coronary artery disease based on personalized medicine procedure

Background

Coronary artery disease (CAD) is the most common reason for mortality and disability-adjusted life years (DALYs) lost globally. This study aimed to suggest a new gene list for the treatment of CAD by a systematic review of bioinformatics analyses of pharmacogenomics impacts of potential genes and variants.

Methods

PubMed search was filtered by the title including Coronary Artery Disease during 2020-2023. To find the genes with pharmacogenetic impact on the CAD, additional filtrations were considered according to the variant annotations. Protein-Protein Interactions (PPIs), Gene-miRNA Interactions (GMIs), Protein-Drug Interactions (PDIs), and variant annotation assessments (VAAs) performed by STRING-MODEL (ver. 12), Cytoscape (ver. 3.10), miRTargetLink.2., NetworkAnalyst (ver 0.3.0), and PharmGKB.

Results

Results revealed 5618 publications, 1290 papers were qualified, and finally, 650 papers were included. 4608 protein-coding genes were extracted, among them, 1432 unique genes were distinguished and 530 evidence-based repeated genes remained. 71 genes showed a pharmacogenetics-related variant annotation in at least (entirely 6331 annotations). Variant annotation assessment (VAA) showed 532 potential variants for the final report, and finally, the concluding PGs list represented 175 variants. Based on the function and MAF, 57 nonsynonymous variants of 29 Pharmacogenomics-related genes were associated with CAD.

Conclusion

Conclusively, evaluating circulating miR33a in individuals' plasma with CAD, and genotyping of rs2230806, rs2230808, rs2487032, rs12003906, rs2472507, rs2515629, and rs4149297 (ABCA1 variants) lead to precisely prescribing of well-known drugs. Also, the findings of this review can be used in both whole-genome sequencing (WGS) and whole-exome sequencing (WES) analysis in the prognosis and diagnosis of CAD.

Incremental Value of Polygenic Risk Scores in Primary Prevention of Coronary Heart Disease: A Review

IMPORTANCE

Risk prediction for coronary heart disease (CHD) is a cornerstone of primary prevention strategies. Polygenic risk scores (PRSs) have emerged as a new approach to predict risk in asymptomatic people. Polygenic risk scores for CHD have been studied in several populations, but there is lack of agreement about the incremental value of PRS beyond traditional risk factor scores in the primary prevention of CHD.

OBSERVATIONS

This narrative review critically appraised the 5 most highly cited studies published through 2021 that also included a large number (>45 000) of single-nucleotide variations (formerly single-nucleotide polymorphisms) and evaluated the incremental value of PRS in CHD risk prediction according to published PRS reporting standards. The cohorts studied included the Atherosclerosis Risk in Communities Study, FINRISK, the Framingham Heart Study, the Multi-Ethnic Study of Atherosclerosis, and the UK Biobank. All of the studies focused predominantly on populations of European ancestry. The hazard ratio per standard deviation of PRS ranged from 1.24 (95% CI, 1.15-1.34) to 1.74 (95% CI, 1.61-1.86). The C statistic for PRS alone ranged from 0.549 to 0.623. The change in C statistic when PRS was added to a standard risk factor model ranged between -0.001 to +0.021. Net reclassification index was reported in 4 of the 5 studies and varied from 0.001 to 0.097. At a sensitivity (true-positive rate) of 90%, positive predictive values ranged from 1.8% to 16.6%, and false-positive rates ranged from 77.1% to 85.7%.

CONCLUSIONS AND RELEVANCE

In this review, PRS was significantly associated with CHD risk in all studies. The degree of improvement in C statistic and the net reclassification indexes when PRS was added to traditional risk scores ranged from negligible to modest. Based on established metrics to assess risk prediction scores, the addition of PRS to traditional risk scores does not appear to provide meaningful improvements in clinical decision-making in primary prevention populations.

Coronary artery disease risk factors affected by RNA modification-related genetic variants

Background

Single nucleotide polymorphisms that affect RNA modification (RNAm-SNPs) may have functional roles in coronary artery disease (CAD). The aim of this study was to identify RNAm-SNPs in CAD susceptibility loci and highlight potential risk factors.

Methods

CAD-associated RNAm-SNPs were identified in the CARDIoGRAMplusC4D and UK Biobank genome-wide association studies. Gene expression and circulating protein levels affected by the RNAm-SNPs were identified by QTL analyses. Cell experiments and Mendelian randomization (MR) methods were applied to test whether the gene expression levels were associated with CAD.

Results

We identified 81 RNAm-SNPs that were associated with CAD or acute myocardial infarction (AMI), including m6A-, m1A-, m5C-, A-to-I- and m7G-related SNPs. The m6A-SNPs rs3739998 in JCAD, rs148172130 in RPL14 and rs12190287 in TCF21 and the m7G-SNP rs186643756 in PVT1 were genome-wide significant. The RNAm-SNPs were associated with gene expression (e.g., MRAS, DHX36, TCF21, JCAD and SH2B3), and the expression levels were associated with CAD. Differential m6A methylation and differential expression in FTO-overexpressing human aorta smooth muscle cells and peripheral blood mononuclear cells of CAD patients and controls were detected. The RNAm-SNPs were associated with circulating levels of proteins with specific biological functions, such as blood coagulation, and the proteins (e.g., cardiotrophin-1) were confirmed to be associated with CAD and AMI in MR analyses.

Conclusion

The present study identified RNAm-SNPs in CAD susceptibility genes, gene expression and circulating proteins as risk factors for CAD and suggested that RNA modification may play a role in the pathogenesis of CAD.

Effect of parental arterial stiffness in offspring: the Kailuan study

OBJECTIVE

The aim of this study was to examine effect of parental arterial stiffness in offspring.

METHODS

The individuals who participated in the second or subsequent follow-up and had parent-offspring relationship and completed measurements of brachial-ankle pulse wave velocity (baPWV) from the Kailuan study were recruited. The individuals were divided into groups by the 10-year intervals and sex. Arterial stiffness was defined as the 75th percentiles in each age category. Multivariable generalized estimating equations was used to analyse the effect of parental baPWV and blood pressure in offspring. Multivariable logistic regression using generalized estimating equations was used to analyse the effect of parental arterial stiffness in offspring.

RESULTS

A total of 4514 parents and offspring who met the inclusion criteria, including 1785 paternal offspring and 625 maternal offspring was recruited. Mean age of paternal offspring and maternal offspring were 36.26 (SD 7.86) and 36.42 (SD 7.57) years, while their mean baPWV were 1294.40 (SD 225.32) and 1270.74 (SD 241.42) cm/s, respectively. In multivariate linear regression analyses, after adjusted for the covariate risk factors, an increase of 1 cm/s in the paternal and maternal baPWV of resulted in an increase of 0.05 and 0.30 cm/s in offspring, respectively. In multivariate logistic regression analyses, the risk of arterial stiffness in the offspring of paternal and maternal arterial stiffness increased by 50 and 77%, respectively.

CONCLUSION

Paternal and maternal baPWV are linear positively correlated with baPWV in offspring. Parental arterial stiffness is a risk factor for arterial stiffness of offspring and is independent of traditional risk factors of offspring arterial stiffness.