Coronary Heart Disease Genetic Risk Score Predicts Cardiovascular Disease Risk in Men, Not Women

The Role of Genetics in the Management of Heart Failure Patients

Over the last decades, the relevance of genetics in cardiovascular diseases has expanded, especially in the context of cardiomyopathies. Its relevance extends to the management of patients diagnosed with heart failure (HF), given its capacity to provide invaluable insights into the etiology of cardiomyopathies and identify individuals at a heightened risk of poor outcomes. Notably, the identification of an etiological genetic variant necessitates a comprehensive evaluation of the family lineage of the affected patients. In the future, these genetic variants hold potential as therapeutic targets with the capability to modify gene expression. In this complex setting, collaboration among cardiologists, specifically those specializing in cardiomyopathies and HF, and geneticists becomes paramount to improving individual and family health outcomes, as well as therapeutic clinical results. This review is intended to offer geneticists and cardiologists an updated perspective on the value of genetic research in HF and its implications in clinical practice.

A multi-ancestry polygenic risk score improves risk prediction for coronary artery disease

Identification of individuals at highest risk of coronary artery disease (CAD)-ideally before onset-remains an important public health need. Prior studies have developed genome-wide polygenic scores to enable risk stratification, reflecting the substantial inherited component to CAD risk. Here we develop a new and significantly improved polygenic score for CAD, termed GPSMult, that incorporates genome-wide association data across five ancestries for CAD (>269,000 cases and >1,178,000 controls) and ten CAD risk factors. GPSMult strongly associated with prevalent CAD (odds ratio per standard deviation 2.14, 95% confidence interval 2.10-2.19, P < 0.001) in UK Biobank participants of European ancestry, identifying 20.0% of the population with 3-fold increased risk and conversely 13.9% with 3-fold decreased risk as compared with those in the middle quintile. GPSMult was also associated with incident CAD events (hazard ratio per standard deviation 1.73, 95% confidence interval 1.70-1.76, P < 0.001), identifying 3% of healthy individuals with risk of future CAD events equivalent to those with existing disease and significantly improving risk discrimination and reclassification. Across multiethnic, external validation datasets inclusive of 33,096, 124,467, 16,433 and 16,874 participants of African, European, Hispanic and South Asian ancestry, respectively, GPSMult demonstrated increased strength of associations across all ancestries and outperformed all available previously published CAD polygenic scores. These data contribute a new GPSMult for CAD to the field and provide a generalizable framework for how large-scale integration of genetic association data for CAD and related traits from diverse populations can meaningfully improve polygenic risk prediction.

Genomic Innovation in Early Life Cardiovascular Disease Prevention and Treatment

Cardiovascular disease (CVD) is a leading cause of morbidity and mortality globally. Although CVD events do not typically manifest until older adulthood, CVD develops gradually across the life-course, beginning with the elevation of risk factors observed as early as childhood or adolescence and the emergence of subclinical disease that can occur in young adulthood or midlife. Genomic background, which is determined at zygote formation, is among the earliest risk factors for CVD. With major advances in molecular technology, including the emergence of gene-editing techniques, along with deep whole-genome sequencing and high-throughput array-based genotyping, scientists now have the opportunity to not only discover genomic mechanisms underlying CVD but use this knowledge for the life-course prevention and treatment of these conditions. The current review focuses on innovations in the field of genomics and their applications to monogenic and polygenic CVD prevention and treatment. With respect to monogenic CVD, we discuss how the emergence of whole-genome sequencing technology has accelerated the discovery of disease-causing variants, allowing comprehensive screening and early, aggressive CVD mitigation strategies in patients and their families. We further describe advances in gene editing technology, which might soon make possible cures for CVD conditions once thought untreatable. In relation to polygenic CVD, we focus on recent innovations that leverage findings of genome-wide association studies to identify druggable gene targets and develop predictive genomic models of disease, which are already facilitating breakthroughs in the life-course treatment and prevention of CVD. Gaps in current research and future directions of genomics studies are also discussed. In aggregate, we hope to underline the value of leveraging genomics and broader multiomics information for characterizing CVD conditions, work which promises to expand precision approaches for the life-course prevention and treatment of CVD.

Genetic Risk Score for Prediction of Coronary Heart Disease in the Korean Genome and Epidemiology Study

Background

Using a genetic risk score (GRS) to predict coronary heart disease (CHD) may detect disease earlier. The current study aims to assess whether GRS is associated with CHD incidence and whether it is clinically useful for improving prediction using traditional risk factors (TRFs) as well as family history.

Methods

Data from a total of 48,941 participants in the Korean Genome and Epidemiology Study were analyzed in the current study. The weighted GRS was constructed using 55 single-nucleotide polymorphisms based on published genome-wide association studies. The association of GRS with incident CHD was analyzed using Cox proportional hazard model. Discrimination and reclassification were assessed to demonstrate the clinical utility of GRS. The analyses were performed separately by sex.

Results

After adjusting for family history and TRFs, GRS was significantly associated with CHD incidence in men; compared to the low GRS group, men in the high GRS group had a 2.07-fold increased risk of CHD (95% confidence interval [CI]: 1.51-2.85). In men, the combination of TRFs, family history, and GRS had better performance than TRFs alone (C statistics for TRF-only model, 0.66, 95% CI, 0.64-0.69; C statistics for combination model, 0.68, 95% CI, 0.65-0.71; category-free reclassification index, 15%). In women, however, there was no significant association between GRS and CHD and no improvement between models.

Conclusions

GRS was associated with CHD incidence and contributed to a small improvement of CHD prediction in men. The potential clinical use of GRS may not outweigh the value of family history.

Sex-Specific Survival Bias and Interaction Modeling in Coronary Artery Disease Risk Prediction

BACKGROUND

The 10-year Atherosclerotic Cardiovascular Disease risk score is the standard approach to predict risk of incident cardiovascular events, and recently, addition of coronary artery disease (CAD) polygenic scores has been evaluated. Although age and sex strongly predict the risk of CAD, their interaction with genetic risk prediction has not been systematically examined. This study performed an extensive evaluation of age and sex effects in genetic CAD risk prediction.

METHODS

The population-based Norwegian HUNT2 (Trøndelag Health Study 2) cohort of 51 036 individuals was used as the primary dataset. Findings were replicated in the UK Biobank (372 410 individuals). Models for 10-year CAD risk were fitted using Cox proportional hazards, and Harrell concordance index, sensitivity, and specificity were compared.

RESULTS

Inclusion of age and sex interactions of CAD polygenic score to the prediction models increased the C-index and sensitivity by accounting for nonadditive effects of CAD polygenic score and likely countering the observed survival bias in the baseline. The sensitivity for females was lower than males in all models including genetic information. We identified a total of 82.6% of incident CAD cases by using a 2-step approach: (1) Atherosclerotic Cardiovascular Disease risk score (74.1%) and (2) the CAD polygenic score interaction model for those in low clinical risk (additional 8.5%).

CONCLUSIONS

These findings highlight the importance and complexity of genetic risk in predicting CAD. There is a need for modeling age- and sex-interaction terms with polygenic scores to optimize detection of individuals at high risk, those who warrant preventive interventions. Sex-specific studies are needed to understand and estimate CAD risk with genetic information.

Multiple polygenic scores improve bone mineral density prediction in an independent sample of Caucasian women

PURPOSE OF THE STUDY

To determine if multiple Genetic Risk Scores (GRSs) improve bone mineral density (BMD) prediction over single GRS in an independent sample of Caucasian women.

STUDY DESIGN

Based on summary statistics of four genome-wide association studies related to two osteoporosis-associated traits, namely BMD and heel quantitative ultrasound derived estimated BMD (eBMD), four GRSs were derived for 1205 individuals in the Genome-Wide Scan for Female Osteoporosis Gene Study. The effect of each GRS on BMD variation was assessed using multivariable linear regression, with conventional risk factors adjusted for. Next, the eBMD-related GRS that explained the most variance in BMD was selected to be entered into a multi-score model, along with the BMD-related GRS. Elastic net regularised regression was used to develop the multiscore model, which estimated the joint effect of two GRSs (GRS_BMD and GRS_eBMD) on BMD variation, after being adjusted for conventional risk factors.

RESULTS

With the same clinical risk factors having been adjusted for, the model that included GRS_BMD performed best by explaining 32.53% of the variance in BMD; the single-score model that included GRS_eBMD explained 34.03% of BMD variance. The model that includes both GRS_BMD and GRS_ eBMD, as well as the clinical risk factors, aggregately explained 35.05% in BMD variation. Compared with the single GRS models, the multiscore model explained significantly more variance in BMD.

CONCLUSIONS

The multipolygenic score model explained a considerable amount of BMD variation. Compared with single score models, multipolygenic score model provided significant improvement in explaining BMD variation.

Missense Variant rs28362680 in BTNL2 Reduces Risk of Coronary Heart Disease

Background

The pathological basis of coronary heart disease (CHD) is atherosclerosis. BTNL2 can inhibit the activation of T cells. We aimed to explore the association between BTNL2 genetic variants and CHD risk in the southern Chinese Han population.

Methods

We recruited 1419 participants to perform an association analysis between missense variants in BTNL2 and CHD risk through SNPStats online software. Genotyping of all candidate SNPs were completed by the Agena MassARRAY. In addition, we used false-positive report probability analysis to detect whether the positive findings were noteworthy observations. We also used Haploview 4.2 software and SNPStats online software to conduct the haplotype analysis and analysis of linkage disequilibrium (LD). Finally, the interaction of SNP-SNP in CHD risk was evaluated by multi-factor dimensionality reduction (MDR).

Results

The results showed that BTNL2-rs35624343, -rs117896888, -rs41441651, -rs41417449, -rs28362680 and -rs2076523 were significantly associated with the CHD susceptibility. Especially for BTNL2-rs28362680, the allele A (OR = 0.68, p < 0.0001), genotype AA (OR = 0.40, p = 0.001) or GA (OR = 0.68, p < 0.0001) were associated with the reducing CHD risk. And -rs28362680 significantly reduced the CHD risk under all genetic models (dominant: OR = 0.64, p < 0.0001; recessive: OR = 0.47, p = 0.003; overdominant: OR = 0.73, p = 0.004; log-additive: OR = 0.66, p < 0.0001). And -rs28362680 was also closely associated with CHD risk reduction in all stratified analyses (age, gender, smoking, drinking, hypertension and diabetes). In addition, haplotype analysis showed that the “C_rs117896888C_rs41441651T_rs41417449A_rs28362680” (OR = 0.65, p < 0.0001) and “G_rs117896888T_rs41441651C_rs41417449A_rs28362680” (OR = 0.68, p = 0.013) may reduce CHD risk.

Conclusion

Missense variants (rs35624343, rs117896888, rs41441651, rs41417449, rs28362680, rs2076523) may be protective factors for the CHD risk. In particular, there were sufficient evidences that BTNL2-rs28362680 can protective CHD risk.

MicroRNA-208a-3p participates in coronary heart disease by regulating the growth of hVSMCs by targeting BTG1

Human vascular smooth muscle cells (hVSMCs) are crucial in the progression of coronary heart disease (CHD). The present study aimed to investigate the role of microRNA-208a-3p (miR-208a-3p) in hVSMCs. Reverse transcription quantitative-PCR was performed to detect the levels of miR-208a-3p in the peripheral blood samples of patients with CHD and healthy volunteers. The results showed that miR-208a-3p was significantly upregulated in peripheral blood samples from patients with CHD compared with in healthy volunteers. Bioinformatics analysis and dual-luciferase reporter assays indicated that B-cell translocation gene 1 (BTG1) was a direct target gene of miR-208a-3p, and was downregulated in the peripheral blood samples of patients with CHD. Furthermore, this study also suggested that miR-208a-3p served an inhibitory role in the proliferation of hVSMCs, induced cell apoptosis, promoted the protein expression of Bax and reduced Bcl-2 protein expression; however, these effects were reversed by BTG1 silencing. In addition, the role of the PI3K/AKT pathway in mediating hVSMC apoptosis was examined via western blot analysis. Results indicated that inhibition of miR-208a-3p decreased phosphorylated (p)-AKT protein expression levels and the ratio of p-AKT/AKT in hVSMCs; however, BTG1-small interfering RNA abolished these effects. Taken together, these findings revealed that miR-208a-3p served a critical role in CHD development, regulating hVSMC function via targeting of BTG1, which was associated with the PI3K/AKT signaling pathway. Therefore, downregulated miR-208a-3p may serve as an ideal therapeutic target for CHD diagnosis and therapy.

Genetic risk model for in-stent restenosis of second-and third-generation drug-eluting stents

The new generation, i.e., second- and third-generation, drug-eluting stents (DESs) remain a risk of in-stent restenosis (ISR). We evaluated the power of a genetic risk score (GRS) model to identify high-risk populations for new generation DES ISR. We enrolled patients with coronary artery disease (CAD) treated with new generations DESs by a single-center cohort study in Taiwan and evaluated their genetic profile. After propensity score matching, there were 343 patients and 153 patients in the derivation and validation cohorts, respectively. Five selected single-nucleotide polymorphisms (SNPs), i.e., SNPs in CAMLG, GALNT2, C11orf84, THOC5, and SAMD11, were included to calculate the GRS for new generation DES ISR. In the derivation and the validation cohorts, patients with a GRS greater than or equal to 3 had significantly higher new generation DES ISR rates. We provide biological information for interventional cardiologists prior to percutaneous coronary intervention by specific five SNP-derived GRS.

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A validated GRS model identified high-risk population for new generation DES ISR

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This GRS includes 5 SNPs in exons: CAMLG, GALNT2, C11orf84, THOC5, and SAMD11

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The patients with high GRSs (≥3) had higher rates of new generation DES ISR

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The GRS provides crucial information in shared decision-making process clinically

The Role of Electronic Health Records in Advancing Genomic Medicine

Recent advances in genomic technology and widespread adoption of electronic health records (EHRs) have accelerated the development of genomic medicine, bringing promising research findings from genome science into clinical practice. Genomic and phenomic data, accrued across large populations through biobanks linked to EHRs, have enabled the study of genetic variation at a phenome-wide scale. Through new quantitative techniques, pleiotropy can be explored with phenome-wide association studies, the occurrence of common complex diseases can be predicted using the cumulative influence of many genetic variants (polygenic risk scores), and undiagnosed Mendelian syndromes can be identified using EHR-based phenotypic signatures (phenotype risk scores). In this review, we trace the role of EHRs from the development of genome-wide analytic techniques to translational efforts to test these new interventions to the clinic. Throughout, we describe the challenges that remain when combining EHRs with genetics to improve clinical care.

Heterogeneity of the Predictive Polygenic Risk Scores for Coronary Heart Disease Age-at-Onset in Three Different Coronary Heart Disease Family-Based Ascertainments

BACKGROUND

Polygenic risk scores (PRS) for coronary heart disease (CHD) may contribute to assess the overall risk of CHD. We evaluated how PRS may influence CHD risk when the distribution of age-at-onset, sex, and family health history differ significantly.

METHODS

Our study included 3 family-based ascertainments: LLFS (Long Life Family Study, N_Individuals=4572), which represents a low CHD risk, and Family Heart Study, which consists of randomly selected families (FamHS-random, N_Individuals=1806), and high CHD risk families (FamHS-high risk, N_Individuals=2301). We examined the effects of PRS, sex, family ascertainment, PRS interaction with sex (PRS*sex) and with family ascertainment (PRS*LLFS and PRS*FamHS-high risk) on CHD, corrected for traditional cardiovascular risk factors using Cox proportional hazard regression models.

RESULTS

Healthy-aging LLFS presented ≈17 years delayed for CHD age-at-onset compared with FamHS-high risk (P<1.0×10^-4). Sex-specific association (P<1.0×10^-17) and PRS*sex (P=2.7×10^-3) predicted prevalent CHD. CHD age-at-onset was associated with PRS (hazard ratio [HR], 1.57; P=1.3×10^-5), LLFS (HR, 0.54; P=2.6×10^-5), and FamHS-high risk (HR, 2.86; P=6.70x10^-15) in men, and with PRS (HR, 1.76; P=7.70×10^-3), FamHS-high risk (HR, 4.88; P=8.70×10^-10), and PRS×FamHS-high risk (HR, 0.61; P=3.60×10^-2) in women. In the PRS extreme quartile distributions, CHD age-at-onset was associated (P<0.05) with PRS, FamHS-high risk, and PRS interactions with both low and high CHD risk families for women. For men, the PRS quartile results remained similar to the whole distribution.

CONCLUSIONS

Differences in CHD family-based ascertainments show evidence of PRS interacting with sex to predict CHD risk. In women, CHD age-at-onset was associated with PRS, CHD family history, and interactions of PRS with family history. In men, PRS and CHD family history were the major effects on the CHD age-at-onset. Understanding the heterogeneity of risks associated with CHD end points at both the personal and familial levels may shed light on the underlying genetic effects influencing CHD and lead to more personalized risk prediction.

Polygenic Risk Score: Clinically Useful Tool for Prediction of Cardiovascular Disease and Benefit from Lipid-Lowering Therapy?

Improvement in risk prediction of atherosclerotic cardiovascular disease (ASCVD) using information on the genetic predisposition at an individual level might offer new possibilities for the successful management of such complex trait. Latest developments in genetic research with the conduction of genome-wide association studies have facilitated a broader utility of polygenic risk score (PRS) as a potent risk prognosticator, being strongly associated with future cardiovascular events. Although its discriminative ability beyond traditional risk factors is still a matter of controversy, PRS possesses at least comparable risk information to that provided by traditional risk tools. More importantly, increased genetic risk for ASCVD might be discovered at younger ages, much longer before conventional risk factors become manifest, thereby providing a potent instrument for aggressive primordial and primary prevention in those at high risk. Furthermore, there is strong evidence that inherited risk may be successfully modulated by a healthy lifestyle or medication use (e.g., statins or PCSK-9 inhibitors). Here, we provide a short overview of the current research related to the possible application of PRS in clinical routine and critically discuss existing pitfalls, which still limit a widespread utility of PRS outside a research setting.

Risk prediction for coronary heart disease by a genetic risk score - results from the Heinz Nixdorf Recall study

BACKGROUND

A Genetic risk score for coronary artery disease (CAD) improves the ability of predicting coronary heart disease (CHD). It is unclear whether i) the use of a CAD genetic risk score is superior to the measurement of coronary artery calcification (CAC) for CHD risk assessment and ii) the CHD risk assessment using a CAD genetic risk score differs between men and women.

METHODS

We included 4041 participants (age-range: 45-76 years, 1919 men) of the Heinz Nixdorf Recall study without CHD or stroke at baseline. A standardized weighted CAD genetic risk score was constructed using 70 known genetic variants. The risk score was divided into quintiles (Q1-Q5). We specified low (Q1), intermediate (Q2-Q4) and high (Q5) genetic risk groups. Incident CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. The association between the genetic risk score and genetic risk groups with incident CHD was assessed using Cox models to estimate hazard ratios (HR) and 95%-confidence intervals (CI). The models were adjusted by age and sex (Model1), as well as by established CHD risk factors (RF) and CAC (Model2). The analyses were further stratified by sex and controlled for multiple testing.

RESULTS

During a median follow-up time of 11.6 ± 3.7 years, 343 participants experienced CHD events (219 men). Per-standard deviation (SD) increase in the genetic risk score was associated with 18% increased risk for incident CHD (Model1: p = 0.002) which did not change after full adjustment (Model2: HR = 1.18 per-SD (p = 0.003)). In Model2 we observed a 60% increased CHD risk in the high (p = 0.009) compared to the low genetic risk group. Stratifying by sex, only men showed statistically significantly higher risk for CHD (Model2: HR = 1.23 per-SD (p = 0.004); intermediate: HR = 1.52 (p = 0.04) and high: HR = 1.88 (p = 0.008)) with no statistically significant risk observed in women.

CONCLUSION

Our results suggest that the CAD genetic risk score could be useful for CHD risk prediction, at least in men belonging to the higher genetic risk group, but it does not outbalance the value of CT-based quantification of CAC which works independently on both men and women and allows better risk stratification in both the genders.

The polygenic architecture of left ventricular mass mirrors the clinical epidemiology

Left ventricular (LV) mass is a prognostic biomarker for incident heart disease and all-cause mortality. Large-scale genome-wide association studies have identified few SNPs associated with LV mass. We hypothesized that a polygenic discovery approach using LV mass measurements made in a clinical population would identify risk factors and diseases associated with adverse LV remodeling. We developed a polygenic single nucleotide polymorphism-based predictor of LV mass in 7,601 individuals with LV mass measurements made during routine clinical care. We tested for associations between this predictor and 894 clinical diagnoses measured in 58,838 unrelated genotyped individuals. There were 29 clinical phenotypes associated with the LV mass genetic predictor at FDR q < 0.05. Genetically predicted higher LV mass was associated with modifiable cardiac risk factors, diagnoses related to organ dysfunction and conditions associated with abnormal cardiac structure including heart failure and atrial fibrillation. Secondary analyses using polygenic predictors confirmed a significant association between higher LV mass and body mass index and, in men, associations with coronary atherosclerosis and systolic blood pressure. In summary, these analyses show that LV mass-associated genetic variability associates with diagnoses of cardiac diseases and with modifiable risk factors which contribute to these diseases.

Predictive Accuracy of a Polygenic Risk Score Compared With a Clinical Risk Score for Incident Coronary Heart Disease

IMPORTANCE

Polygenic risk scores comprising millions of single-nucleotide polymorphisms (SNPs) could be useful for population-wide coronary heart disease (CHD) screening.

OBJECTIVE

To determine whether a polygenic risk score improves prediction of CHD compared with a guideline-recommended clinical risk equation.

DESIGN, SETTING, AND PARTICIPANTS

A retrospective cohort study of the predictive accuracy of a previously validated polygenic risk score was assessed among 4847 adults of white European ancestry, aged 45 through 79 years, participating in the Atherosclerosis Risk in Communities (ARIC) study and 2390 participating in the Multi-Ethnic Study of Atherosclerosis (MESA) from 1996 through December 31, 2015, the final day of follow-up. The performance of the polygenic risk score was compared with that of the 2013 American College of Cardiology and American Heart Association pooled cohort equations.

EXPOSURES

Genetic risk was computed for each participant by summing the product of the weights and allele dosage across 6 630 149 SNPs. Weights were based on an international genome-wide association study.

MAIN OUTCOMES AND MEASURES

Prediction of 10-year first CHD events (including myocardial infarctions, fatal coronary events, silent infarctions, revascularization procedures, or resuscitated cardiac arrest) assessed using measures of model discrimination, calibration, and net reclassification improvement (NRI).

RESULTS

The study population included 4847 adults from the ARIC study (mean [SD] age, 62.9 [5.6] years; 56.4% women) and 2390 adults from the MESA cohort (mean [SD] age, 61.8 [9.6] years; 52.2% women). Incident CHD events occurred in 696 participants (14.4%) and 227 participants (9.5%), respectively, over median follow-up of 15.5 years (interquartile range [IQR], 6.3 years) and 14.2 (IQR, 2.5 years) years. The polygenic risk score was significantly associated with 10-year CHD incidence in ARIC with hazard ratios per SD increment of 1.24 (95% CI, 1.15 to 1.34) and in MESA, 1.38 (95% CI, 1.21 to 1.58). Addition of the polygenic risk score to the pooled cohort equations did not significantly increase the C statistic in either cohort (ARIC, change in C statistic, -0.001; 95% CI, -0.009 to 0.006; MESA, 0.021; 95% CI, -0.0004 to 0.043). At the 10-year risk threshold of 7.5%, the addition of the polygenic risk score to the pooled cohort equations did not provide significant improvement in reclassification in either ARIC (NRI, 0.018, 95% CI, -0.012 to 0.036) or MESA (NRI, 0.001, 95% CI, -0.038 to 0.076). The polygenic risk score did not significantly improve calibration in either cohort.

CONCLUSIONS AND RELEVANCE

In this analysis of 2 cohorts of US adults, the polygenic risk score was associated with incident coronary heart disease events but did not significantly improve discrimination, calibration, or risk reclassification compared with conventional predictors. These findings suggest that a polygenic risk score may not enhance risk prediction in a general, white middle-aged population.

Cardiovascular Predictive Value and Genetic Basis of Ventricular Repolarization Dynamics

BACKGROUND

Early prediction of cardiovascular risk in the general population remains an important issue. The T-wave morphology restitution (TMR), an ECG marker quantifying ventricular repolarization dynamics, is strongly associated with cardiovascular mortality in patients with heart failure. Our aim was to evaluate the cardiovascular prognostic value of TMR in a UK middle-aged population and identify any genetic contribution.

METHODS

We analyzed ECG recordings from 55 222 individuals from a UK middle-aged population undergoing an exercise stress test in UK Biobank (UKB). TMR was used to measure ventricular repolarization dynamics, exposed in this cohort by exercise (TMR during exercise, TMR^ex) and recovery from exercise (TMR during recovery, TMR^rec). The primary end point was cardiovascular events; secondary end points were all-cause mortality, ventricular arrhythmias, and atrial fibrillation with median follow-up of 7 years. Genome-wide association studies for TMR^ex and TMR^rec were performed, and genetic risk scores were derived and tested for association in independent samples from the full UKB cohort (N=360 631).

RESULTS

A total of 1743 (3.2%) individuals in UKB who underwent the exercise stress test had a cardiovascular event, and TMR^rec was significantly associated with cardiovascular events (hazard ratio, 1.11; P=5×10^-7), independent of clinical variables and other ECG markers. TMR^rec was also associated with all-cause mortality (hazard ratio, 1.10) and ventricular arrhythmias (hazard ratio, 1.16). We identified 12 genetic loci in total for TMR^ex and TMR^rec, of which 9 are associated with another ECG marker. Individuals in the top 20% of the TMR^rec genetic risk score were significantly more likely to have a cardiovascular event in the full UKB cohort (18 997, 5.3%) than individuals in the bottom 20% (hazard ratio, 1.07; P=6×10^-3).

CONCLUSIONS

TMR and TMR genetic risk scores are significantly associated with cardiovascular risk in a UK middle-aged population, supporting the hypothesis that increased spatio-temporal heterogeneity of ventricular repolarization is a substrate for cardiovascular risk and the validity of TMR as a cardiovascular risk predictor.

Circulating microRNAs in suspected stable coronary artery disease: A coronary computed tomography angiography study

OBJECTIVES

To explore the diagnostic performance of circulating microRNAs (miRNAs) as biomarkers in patients with suspected stable coronary artery disease (CAD).

METHODS

Plasma samples were collected from 237 consecutive patients referred for coronary computed tomography angiography (CCTA). Presence, extension and severity of coronary stenosis were evaluated using the indexes: presence of diameter stenosis ≥ 50%, segment involvement score (SIS), segment stenosis score (SSS) and 3-vessel plaque score. A panel of 10 miRNAs previously associated with CAD was analysed using RT-qPCR. Multivariate analyses were used to analyse the associations between biomarkers and indexes. Discrimination was evaluated using the area under the ROC curve (AUC). Decision trees were generated using chi-squared Automatic Interaction Detector (CHAID) prediction models.

RESULTS

After comprehensive adjustment including cardiovascular risk factors, medication use, confounding factors and protein-based biomarkers (hs-TnT and hs-CRP), several circulating miRNAs were inversely associated with coronary atherosclerosis extension (SIS and 3-vessel plaque score) and severity (SSS). In the whole population, circulating miRNAs showed a poor discrimination value for all indexes (AUC = 0.539-0.644) and did not increase the discrimination capacity of a clinical model of coronary stenosis presence, extension and severity based on conventional cardiovascular risk factors. Conversely, the inclusion of circulating miRNAs in decision trees produces models that improve the classification of cases and controls in specific patient subgroups.

CONCLUSIONS

This study identifies a group of circulating miRNAs that failed to improve the discrimination capacity of cardiovascular risk factors but that has the potential to define specific subpopulations of patients with suspected stable CAD.

The evolution of genetic-based risk scores for lipids and cardiovascular disease

PURPOSE OF REVIEW

With improved next-generation sequencing technology, open-access genetic databases and increased awareness of complex trait genetics, we are entering a new era of risk assessment in which genetic-based risk scores (GRSs) will play a clinical role. We review the concepts underlying polygenic models of disease susceptibility and challenges in clinical implementation.

RECENT FINDINGS

Polygenic risk scores are currently used in genetic research on dyslipidemias and cardiovascular disease (CVD). Although the underlying principles for constructing polygenic scores for lipids are established, the lack of consensus on which score to use is indicated by the large number - about 50 - that have been published. Recently, large-scale polygenic scores for CVD appear to afford superior risk prediction compared to small-scale scores. Despite the potential benefits of GRSs, certain biases towards ethnicity and sex need to be worked through.

SUMMARY

We are on the verge of clinical application of GRSs to provide incremental information on dyslipidemia and CVD risk above and beyond traditional clinical variables. Additional work is required to develop a consensus of how such scores will be constructed and measured in a validated manner, as well as clinical indications for their use.