Validation of Polygenic Scores for QT Interval in Clinical Populations

A polygenic risk score for the QT interval is an independent predictor of drug-induced QT prolongation

Drug-induced QT prolongation (diLQTS), and subsequent risk of torsade de pointes, is a major concern with use of many medications, including for non-cardiac conditions. The possibility that genetic risk, in the form of polygenic risk scores (PGS), could be integrated into prediction of risk of diLQTS has great potential, although it is unknown how genetic risk is related to clinical risk factors as might be applied in clinical decision-making. In this study, we examined the PGS for QT interval in 2500 subjects exposed to a known QT-prolonging drug on prolongation of the QT interval over 500ms on subsequent ECG using electronic health record data. We found that the normalized QT PGS was higher in cases than controls (0.212±0.954 vs. -0.0270±1.003, P = 0.0002), with an unadjusted odds ratio of 1.34 (95%CI 1.17-1.53, P<0.001) for association with diLQTS. When included with age and clinical predictors of QT prolongation, we found that the PGS for QT interval provided independent risk prediction for diLQTS, in which the interaction for high-risk diagnosis or with certain high-risk medications (amiodarone, sotalol, and dofetilide) was not significant, indicating that genetic risk did not modify the effect of other risk factors on risk of diLQTS. We found that a high-risk cutoff (QT PGS ≥ 2 standard deviations above mean), but not a low-risk cutoff, was associated with risk of diLQTS after adjustment for clinical factors, and provided one method of integration based on the decision-tree framework. In conclusion, we found that PGS for QT interval is an independent predictor of diLQTS, but that in contrast to existing theories about repolarization reserve as a mechanism of increasing risk, the effect is independent of other clinical risk factors. More work is needed for external validation in clinical decision-making, as well as defining the mechanism through which genes that increase QT interval are associated with risk of diLQTS.

Genetic variants and effect modifiers of QT interval prolongation in patients with sickle cell disease

BACKGROUND

Sickle cell disease (SCD) is a common inherited blood disorder among African Americans (AA), with premature mortality which has been associated with prolongation of the heart rate-corrected QT interval (QTc), a known risk factor for sudden cardiac death. Although numerous genetic variants have been identified as contributors to QT interval prolongation in the general population, their impact on SCD patients remains unclear. This study used an unweighted polygenic risk score (PRS) to validate the previously identified associations between SNPs and QTc interval in SCD patients, and to explore possible interactions with other factors that prolong QTc interval in AA individuals with SCD.

METHODS

In SCD patients, candidate genetic variants associated with the QTc interval were genotyped. To identify any risk SNPs that may be correlated with QTc interval prolongation, linear regression was employed, and an unweighted PRS was subsequently constructed. The effect of PRS on the QTc interval was evaluated using linear regression, while stratification analysis was used to assess the influence of serum alanine transaminase (ALT), a biomarker for liver disease, on the PRS effect. We also evaluated the PRS with the two subcomponents of QTc, the QRS and JTc intervals.

RESULTS

Out of 26 candidate SNPs, five risk SNPs were identified for QTc duration under the recessive model. For every unit increase in PRS, the QTc interval prolonged by 4.0 ms (95% CI: [2.0, 6.1]; p-value: <0.001) in the additive model and 9.4 ms in the recessive model (95% CI: [4.6, 14.1]; p-value: <0.001). Serum ALT showed a modification effect on PRS-QTc prolongation under the recessive model. In the normal ALT group, each PRS unit increased QTc interval by 11.7 ms (95% CI: [6.3, 17.1]; p-value: 2.60E-5), whereas this effect was not observed in the elevated ALT group (0.9 ms; 95% CI: [-7.0, 8.8]; p-value: 0.823).

CONCLUSION

Several candidate genetic variants are associated with QTc interval prolongation in SCD patients, and serum ALT acts as a modifying factor. The association of a CPS1 gene variant in both QTc and JTc duration adds to NOS1AP as evidence of involvement of the urea cycle and nitric oxide metabolism in cardiac repolarization in SCD. Larger replication studies are needed to confirm these findings and elucidate the underlying mechanisms.

Clinical and Laboratory Correlates of QTc Duration in Adult and Pediatric Sickle Cell Disease

Background

Sickle cell disease, a common genetic disorder in African Americans, manifests an increased risk of sudden death, the basis of which is incompletely understood. Prolongation of heart rate-corrected QT (QTc) interval on the electrocardiogram, a standard clinical measure of cardiac repolarization, may contribute to sudden death by predisposing to torsades de pointes ventricular tachycardia.

Methods

We established a cohort study of 293 adult and 121 pediatric sickle cell disease patients drawn from the same geographic region as the Jackson Heart Study (JHS) cohort, in which significant correlates of QT duration have been characterized and quantitatively modeled. Herein, we establish clinical and laboratory correlates of QTc duration in our cohort using stepwise multivariate linear regression analysis. We then compared our adult sickle cell disease data to effect-size predictions from the published JHS statistical model of QT interval duration.

Results

In adult sickle cell disease, gender, diuretic use, QRS duration, serum ALT levels, anion gap, and diastolic blood pressure show positive correlation; hemoglobin levels show inverse correlation; in pediatric sickle cell disease, age, hemoglobin levels, and serum bicarbonate and creatinine levels show inverse correlation. The mean QTc in our adult sickle cell disease cohort is 7.8 milliseconds longer than in the JHS cohort, even though the JHS statistical model predicts that the mean QTc in our cohort should be > 11 milliseconds shorter than in the much older JHS cohort, a differential of > 18 milliseconds.

Conclusion

Sickle cell disease patients have substantial QTc prolongation relative to their age, driven by factors some overlapping, in adult and pediatric sickle cell disease, and distinct from those that have been defined in the general African American community.

Genetics of congenital arrhythmia syndromes: the challenge of variant interpretation

Congenital arrhythmia syndromes are rare genetic disorders that can cause a high risk of sudden cardiac death. Expert panels have affirmed 15 genes that are linked to congenital arrhythmias. These genes mostly encode cardiac ion channel proteins or associated regulatory proteins that generate the cardiac action potential. Common genetic variation modulates the risk of rare variants and partially explains the incomplete penetrance of these disorders. As genetic testing becomes more prevalent, a major challenge is that most detected variants are annotated as variants of uncertain significance. This review will highlight emerging methods that are refining our understanding of arrhythmia genetics, including phenotype risk scores, large cohorts, in vitro functional assays, structural models, and computational predictions.

Increasing Adiposity Is Associated With QTc Interval Prolongation and Increased Ventricular Arrhythmic Risk in the Context of Metabolic Dysfunction: Results From the UK Biobank

Background

Small-scale studies have linked obesity (Ob) and metabolic ill-health with proarrhythmic repolarisation abnormalities. Whether these are observed at a population scale, modulated by individuals' genetics, and confer higher risks of ventricular arrhythmias (VA) are not known.

Methods and Results

Firstly, using the UK Biobank, the association between adiposity and QTc interval was assessed in participants with a resting 12-lead ECG (n = 23,683), and a polygenic risk score (PRS) was developed to investigate any modulatory effect of genetics. Participants were also categorised into four phenotypes according to the presence (+) or absence (-) of Ob, and if they were metabolically unhealthy (MU+) or not (MU-). QTc was positively associated with body mass index (BMI), body fat (BF), waist:hip ratio (WHR), and hip and waist girths. Individuals' genetics had no significant modulatory effect on QTc-prolonging effects of increasing adiposity. QTc interval was comparably longer in those with metabolic perturbation without obesity (Ob-MU+) and obesity alone (Ob+MU-) compared with individuals with neither (Ob-MU-), and their co-existence (Ob+MU+) had an additive effect on QTc interval. Secondly, for 502,536 participants in the UK Biobank, odds ratios (ORs) for VA were computed for the four clinical phenotypes above using their past medical records. Referenced to Ob-MU-, ORs for VA in Ob-MU+ men and women were 5.96 (95% CI: 4.70-7.55) and 5.10 (95% CI: 3.34-7.80), respectively. ORs for Ob+MU+ were 6.99 (95% CI: 5.72-8.54) and 3.56 (95% CI: 2.66-4.77) in men and women, respectively.

Conclusion

Adiposity and metabolic perturbation increase QTc to a similar degree, and their co-existence exerts an additive effect. These effects are not modulated by individuals' genetics. Metabolic ill-health is associated with a higher OR for VA than obesity.

Monogenic and Polygenic Contributions to QTc Prolongation in the Population

BACKGROUND

Rare sequence variation in genes underlying cardiac repolarization and common polygenic variation influence QT interval duration. However, current clinical genetic testing of individuals with unexplained QT prolongation is restricted to examination of monogenic rare variants. The recent emergence of large-scale biorepositories with sequence data enables examination of the joint contribution of rare and common variations to the QT interval in the population.

METHODS

We performed a genome-wide association study of the QTc in 84 630 UK Biobank participants and created a polygenic risk score (PRS). Among 26 976 participants with whole-genome sequencing and ECG data in the TOPMed (Trans-Omics for Precision Medicine) program, we identified 160 carriers of putative pathogenic rare variants in 10 genes known to be associated with the QT interval. We examined QTc associations with the PRS and with rare variants in TOPMed.

RESULTS

Fifty-four independent loci were identified by genome-wide association study in the UK Biobank. Twenty-one loci were novel, of which 12 were replicated in TOPMed. The PRS composed of 1 110 494 common variants was significantly associated with the QTc in TOPMed (ΔQTc/decile of PRS=1.4 ms [95% CI, 1.3 to 1.5]; P=1.1×10-196). Carriers of putative pathogenic rare variants had longer QTc than noncarriers (ΔQTc=10.9 ms [95% CI, 7.4 to 14.4]). Of individuals with QTc>480 ms, 23.7% carried either a monogenic rare variant or had a PRS in the top decile (3.4% monogenic, 21% top decile of PRS).

CONCLUSIONS

QTc duration in the population is influenced by both rare variants in genes underlying cardiac repolarization and polygenic risk, with a sizeable contribution from polygenic risk. Comprehensive assessment of the genetic determinants of QTc prolongation includes incorporation of both polygenic and monogenic risk.

Polygenic risk scores: An overview from bench to bedside for personalised medicine

Since the first polygenic risk score (PRS) in 2007, research in this area has progressed significantly. The increasing number of SNPs that have been identified by large scale GWAS analyses has fuelled the development of a myriad of PRSs for a wide variety of diseases and, more recently, to PRSs that potentially identify differential response to specific drugs. PRSs constitute a composite genomic biomarker and potential applications for PRSs in clinical practice encompass risk prediction and disease screening, early diagnosis, prognostication, and drug stratification to improve efficacy or reduce adverse drug reactions. Nevertheless, to our knowledge, no PRSs have yet been adopted into routine clinical practice. Beyond the technical considerations of PRS development, the major challenges that face PRSs include demonstrating clinical utility and circumnavigating the implementation of novel genomic technologies at scale into stretched healthcare systems. In this review, we discuss progress in developing disease susceptibility PRSs across multiple medical specialties, development of pharmacogenomic PRSs, and future directions for the field.

Genetics and genomics of arrhythmic risk: current and future strategies to prevent sudden cardiac death

A genetic risk of sudden cardiac arrest and sudden death due to an arrhythmic cause, known as sudden cardiac death (SCD), has become apparent from epidemiological studies in the general population and in patients with ischaemic heart disease. However, genetic susceptibility to sudden death is greatest in young people and is associated with uncommon, monogenic forms of heart disease. Despite comprehensive pathology and genetic evaluations, SCD remains unexplained in a proportion of young people and is termed sudden arrhythmic death syndrome, which poses challenges to the identification of relatives from affected families who might be at risk of SCD. In this Review, we assess the current understanding of the epidemiology and causes of SCD and evaluate both the monogenic and the polygenic contributions to the risk of SCD in the young and SCD associated with drug therapy. Finally, we analyse the potential clinical role of genomic testing in the prevention of SCD in the general population.

Antipsychotics in routine treatment are minor contributors to QT prolongation compared to genetics and age

BACKGROUND

Drug-induced prolongation of cardiac repolarization limits the treatment with many psychotropic drugs. Recently, the contribution of polygenic variation to the individual duration of the QT interval was identified.

AIMS

To explore the interaction between antipsychotic drugs and the individual polygenic influence on the QT interval.

METHODS

Retrospective analysis of clinical and genotype data of 804 psychiatric inpatients diagnosed with a psychotic disorder. The individual polygenic influence on the QT interval was calculated according to the method of Arking et al.

RESULTS

Linear regression modelling showed a significant association of the individual polygenic QT interval score (ß_std = 0.176, p < 0.001) and age (ß_std = 0.139, p < 0.001) with the QTc interval corrected according to Fridericia's formula. Sex showed a nominal trend towards significance (ß_std = 0.064, p = 0.064). No association was observed for the number of QT prolonging drugs according to AZCERT taken. Subsample analysis (n = 588) showed a significant association of potassium serum concentrations with the QTc interval (ß_std = -0.104, p = 0.010). Haloperidol serum concentrations were associated with the QTc interval only in single medication analysis (n = 26, ß_std = 0.101, p = 0.004), but not in multivariate regression analysis. No association was observed for aripiprazole, clozapine, quetiapine and perazine, while olanzapine and the sum of risperidone and its metabolite showed a negative association.

CONCLUSIONS

Individual genetic factors and age are main determinants of the QT interval. Antipsychotic drug serum concentrations within the therapeutic range contribute to QTc prolongation on an individual level.

Corrected QT Interval–Polygenic Risk Score and Its Contribution to Type 1, Type 2, and Type 3 Long-QT Syndrome in Probands and Genotype-Positive Family Members

Background:

Long-QT syndrome (LQTS) is characterized by a prolonged heart rate–corrected QT interval (QTc). Genome-wide association studies identified common genetic variants that collectively explain ≈8% to 10% of QTc variation in the general population.

Methods:

Overall, 423 patients with LQT1, LQT2, or LQT3 were genotyped for 61 QTc-associated genetic variants used in a prototype QTc–polygenic risk score (QTc-PRS). A weighted QTc-PRS (range, 0–154.8 ms) was calculated for each patient, and the FHS (Framingham Heart Study) population-based reference cohort (n=853).

Results:

The average QTc-PRS in LQTS was 88.0±7.2 and explained only ≈2.0% of the QTc variability. The QTc-PRS in LQTS probands (n=137; 89.3±6.8) was significantly greater than both FHS controls (87.2±7.4, difference-in-means±SE: 2.1±0.7, P <0.002) and LQTS genotype-positive family members (87.5±7.4, difference-in-mean, 1.8±.7, P <0.009). There was no difference in QTc-PRS between symptomatic (n=156, 88.6±7.3) and asymptomatic patients (n=267; 87.7±7.2, difference-in-mean, 0.9±0.7, P=0.15). LQTS patients with a QTc≥480 ms (n=120) had a significantly higher QTc-PRS (89.3±6.7) than patients with a QTc<480 ms (n=303, 87.6±7.4, difference-in-mean, 1.7±0.8, P <0.05). There was no difference in QTc-PRS or QTc between genotypes.

Conclusions:

The QTc-PRS explained <2% of the QTc variability in our LQT1, LQT2, and LQT3 cohort, contributing 5× less to their QTc value than in the general population. This prototype QTc-PRS does not distinguish/predict the clinical outcomes of individuals with LQTS.

Transethnic Genome-Wide Association Study Provides Insights in the Genetic Architecture and Heritability of Long QT Syndrome

Supplemental Digital Content is available in the text.

Long QT syndrome (LQTS) is a rare genetic disorder and a major preventable cause of sudden cardiac death in the young. A causal rare genetic variant with large effect size is identified in up to 80% of probands (genotype positive) and cascade family screening shows incomplete penetrance of genetic variants. Furthermore, a proportion of cases meeting diagnostic criteria for LQTS remain genetically elusive despite genetic testing of established genes (genotype negative). These observations raise the possibility that common genetic variants with small effect size contribute to the clinical picture of LQTS. This study aimed to characterize and quantify the contribution of common genetic variation to LQTS disease susceptibility.

The evolution of gene-guided management of inherited arrhythmia syndromes: Peering beyond monogenic paradigms towards comprehensive genomic risk scores

Inherited arrhythmia syndromes have traditionally been viewed as monogenic forms of disease whose pathophysiology is driven by a single highly penetrant rare genetic variant. Although an accurate depiction of a proportion of genetic variants, the variable penetrance frequently noted in genotype positive families and the presence of sporadic genotype negative cases have long highlighted a more nuanced truth being operative. Coupled with our more recent recognition that many rare variants implicated in inherited arrhythmia syndromes possess unexpectedly high allele frequencies within the general population, these observations have contributed to the realization that a spectrum of pathogenicity exists among clinically relevant genetic variants. Notably, variable mutation pathogenicity and corresponding variable degrees of penetrance emphasize a limitation of contemporary guidelines, which attempt to dichotomize genetic variants as pathogenic or benign. Recognition of the existence of low and intermediate penetrant variants insufficient to be causative for disease in isolation has served to emphasize the importance of additional genetic, clinical, and environmental factors in the pathogenesis of rare inherited arrhythmia syndromes. Despite being rare, it has also become increasingly evident that common genetic variants play critical roles in both heritable channelopathies and cardiomyopathies and in aggregate may even be the primary drivers in certain instances, such as genotype negative Brugada syndrome. Our growing realization that the genetic substrates of inherited arrhythmia syndromes have intricacies that extend beyond traditionally perceived monogenic paradigms has highlighted a potential value of leveraging more comprehensive genomic risk scores for predicting disease development and arrhythmic risk.

Validity of polygenic risk scores: are we measuring what we think we are?

Polygenic risk scores (PRSs) have become the standard for quantifying genetic liability in the prediction of disease risks. PRSs are generally constructed as weighted sum scores of risk alleles using effect sizes from genome-wide association studies as their weights. The construction of PRSs is being improved with more appropriate selection of independent single-nucleotide polymorphisms (SNPs) and optimized estimation of their weights but is rarely reflected upon from a theoretical perspective, focusing on the validity of the risk score. Borrowing from psychometrics, this paper discusses the validity of PRSs and introduces the three main types of validity that are considered in the evaluation of tests and measurements: construct, content, and criterion validity. This introduction is followed by a discussion of three topics that challenge the validity of PRS, namely, their claimed independence of clinical risk factors, the consequences of relaxing SNP inclusion thresholds and the selection of SNP weights. This discussion of the validity of PRS reminds us that we need to keep questioning if weighted sums of risk alleles are measuring what we think they are in the various scenarios in which PRSs are used and that we need to keep exploring alternative modeling strategies that might better reflect the underlying biological pathways.