Atrial fibrillation (AF), the most common cardiac arrhythmia, has been linked to numerous loci identified by genome-wide association studies (GWAS). However, the causal genes and underlying mechanisms remain unclear.

We conducted a cross-tissue transcriptome-wide association studies (TWAS) using the unified test for molecular signatures (UTMOST), integrating genetic data from the FinnGen R11 cohort (287 805 individuals) with gene expression profiles from the genotype-tissue expression (GTEx) project. To enhance reliability, we applied functional summary-based imputation (FUSION), fine-mapping of causal gene sets (FOCUS), and multi-marker analysis of GenoMic annotation (MAGMA) for gene prioritization, followed by Mendelian randomization (MR) and colocalization analyses. GeneMANIA was used to explore gene functions.

By integrating four TWAS approaches, this study identified five novel susceptibility genes significantly associated with AF risk. MR analysis further revealed that the gene expression levels of FKBP7, CEP68, and CAMK2D were positively associated with AF risk, while SPATS2L exhibited a significant protective effect. Colocalization analysis demonstrated that CEP68 and SPATS2L share causal variants with AF. Through comprehensive evaluation of multidimensional functional annotations and existing biological evidence, this study highlighted SPATS2L and CEP68 as potential functional candidate genes in AF pathogenesis.

This cross-tissue TWAS identified five novel AF susceptibility genes (CAMK2D, SPAST2L, CEP68, FKBP7, and SHRMOO3). Elevated expression of FKBP7, CEP68, and CAMK2D increases AF risk, while SPATS2L showed a protective effect, with colocalization analysis implicating CEP68 and SPATS2L as prioritized candidates. The integration of multi-omics approaches effectively unravels AF's genetic mechanisms.

Identifying causal variants among tens or hundreds of associated variants at each locus in genome-wide association studies (GWAS) is challenging. As the vast majority of GWAS variants are noncoding, sequence variation at cis-regulatory elements (CREs) affecting transcriptional expression of specific genes is a widely accepted molecular hypothesis. Following this hypothesis, combined with the observation that open chromatin is a universal hallmark of all types of CREs, we aimed to identify candidate causal cis-regulatory variants underlying QT interval GWAS loci.

Common variants in high linkage disequilibrium with genome-wide significant variants were identified using variant call format tools. Genome-wide maps of cardiac putative CREs were generated by MACS2-based peak calling in human cardiac left ventricular DNase I sequencing and Assay for Transposase-Accessible Chromatin using sequencing data sets (n=13). Variant-CRE overlap was performed using custom tracks in the Table Browser tool at the UCSC Genome Browser. Luciferase reporter-based enhancer assays for variant-centered test elements were performed in mouse HL1 cardiomyocyte cells. Reporter activities of allelic pairs were compared using a Student t test.

At a dozen GWAS loci, selected for higher effect sizes and better understanding of the likely causal genes, we identified all genome-wide significant variants (n=1401) and included all common variants (minor allele frequency >1%) in high linkage disequilibrium (r2>0.9) with them as candidate variants (n=3482). Candidate variants were filtered for overlap with cardiac left ventricular putative CREs to identify candidate causal cis-regulatory variants (n=476), which were further assessed for being a known cardiac expression quantitative trait locus variant as additional functional evidence (n=243). Functional evaluation of a subset of seven candidate variants by luciferase reporter-based enhancer assays in HL1 cells using variant-centered test elements led to the identification of 6 enhancer variants with significant allelic differences.

These efforts have generated a comprehensive set of candidate causal variants expected to be enriched for cis-regulatory potential and thereby, explaining the observed genetic associations.

Patients with end-stage renal disease (ESRD) are at a higher risk of cardiovascular (CV) complications and mortality compared to the general population. This study aimed to investigate the genetic polymorphisms of KCNN2, a key gene encoding a subtype of small-conductance calcium-activated potassium (SK) channels, which regulate an important SK current pathway potentially involved in the development of CV complications, particularly arrhythmias, in ESRD patients. A total of 169 ESRD patients were enrolled in this study. The patients were divided into two groups based on the presence of CV complications: Group I, consisting of 84 patients without CV complications, and Group II, comprising 85 patients with CV complications. Twelve tagging single nucleotide polymorphisms (tSNPs) in KCNN2 were examined. Polymerase chain reaction (PCR) was performed, and genotyping was correlated with CV complications in each group. The TC and CC genotypes of rs10076582, and the GT and TT genotypes of rs11738819 in the KCNN2 gene, were associated with an increased risk of CV complications in ESRD patients. After adjusting for potential risk factors, these associations remained significant. Additionally, KCNN2 haplotypes with the allele combinations GGCCCTCCGAG and AGTCCTCCGGT were significantly associated with a higher risk of CV complications in ESRD patients. In conclusion, our findings report that specific genetic polymorphisms in the KCNN2 gene, particularly the rs10076582 and rs11738819 variants, as well as GGCCCTCCGAG and AGTCCTCCGGT haplotypes, are significantly associated with an increased risk of cardiovascular complications in ESRD patients. These genetic markers may serve as potential biomarkers for identifying individuals at high risk of cardiovascular complications in this vulnerable population.

KCNQ1 loss of function variants are thought to cause type 1 long QT syndrome by reducing I Ks. However, we have recently reported that pharmacologic block of I Ks in human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) produced minimal increases in action potential duration at 90% repolarization (APD90), while genetic loss of KCNQ1 markedly prolonged APD90. We sought here to define mechanisms underlying APD prolongation by genetic loss of KCNQ1.

We studied iPSC-CMs from population controls, an isogenic KCNQ1 knock out (KO) line created by a homozygous edit for the R518X loss of function variant, and 2 unrelated patients with the Jervell and Lange-Nielsen syndrome (JLN) due to compound heterozygosity for loss of function KCNQ1 variants.

In both JLN and the KCNQ1-KO lines, I Ks was absent, APD90 was markedly prolonged, and L-type Ca channel (LTCC) current (I Ca-L) was significantly increased, 2-3-fold, compared to the control cells with no change in kinetics or gating. RNA-sequencing identified 298 and 584 genes that were up- and down-regulated, respectively, by KCNQ1-KO compared to the isogenic control cells. Gene ontology analysis identified down-regulation of 6 Ca2+ channel negative regulatory genes (p=0.0002, FDR=0.02), and in knockdown experiments in wild-type iPSC-CMs, three of these, CBARP, FKBP1B, and RRAD, increased I Ca-L, and RRAD increased APD90. A therapeutic low concentration (1 μM) of the Ca channel antagonist diltiazem significantly shortened APD90 in the two JLN cell lines and in KCNQ1-KO cells. A single low dose of intravenous diltiazem in one of the JLN patients shortened QTc.

These data further support the concept that delayed repolarization in JLN cannot be explained solely by loss of I Ks. Our findings demonstrate that KCNQ1 mutations lead to down-regulation of Ca2+ channel inhibitory genes, with resultant increased I Ca-L that underlies delayed repolarization in JLN. We further propose that diltiazem can be repurposed for treatment of patients with JLN.

Despite significant efforts to understand pathophysiological processes underlying cardiac diseases, the molecular causes for the most part remain unresolved. Rapid advancements in -omics technologies, and their application in cardiac research, offer new insight into cardiac remodeling in disease states. This review aims to provide an accessible overview of recent advances in omics approaches for studying cardiac remodeling, catering to readers without extensive prior expertise.

We provide a methodologically focused overview of current methods for performing transcriptomics and proteomics, including their extensions for single-cell and spatial measurements. We discuss approaches to integrate data across modalities, resolutions and time. Key recent applications within the cardiac field are highlighted. Each -omics modality can provide insight, yet each existing experimental method has technical or conceptual limitations. Integrating data across multiple modalities can leverage strengths and mitigate weaknesses, ultimately enhancing our understanding of cardiac pathophysiology.

Genome-wide association studies (GWAS) have identified >30 loci with multiple common noncoding variants explaining interindividual electrocardiographic QT interval (QTi) variation. Of the many types of noncoding functional elements, here we sought to identify transcriptional enhancers with sequence variation and their cognate transcription factors (TFs) that alter the expression of proximal cardiac genes to affect QTi variation. We used massively parallel reporter assays (MPRA) in mouse cardiomyocyte HL-1 cells to screen for functional enhancer variants among 1,018 QTi-associated GWAS variants that overlap candidate cardiac enhancers across 31 loci. We identified 445 GWAS variant-containing enhancers of which 79 showed significant allelic difference in enhancer activity across 21 GWAS loci, with multiple enhancer variants per locus. Of these, we predicted differential binding by cardiac TFs, including AP-1, ATF-1, GATA2, MEF2, NKX2.5, SRF and TBX5 which are known to play key roles in development and homeostasis, at 49 enhancer variants. Finally, we used expression quantitative trait locus mapping and predicted promoter-enhancer contacts to identify 14 candidate target genes through analyses of 36 enhancer variants at 16 loci. This study provides strong evidence for 14 cardiac genes, 10 of them novel, impacting on QTi variation, beyond explaining observed genetic associations.

Electrocardiography is one of the most valuable noninvasive diagnostic tools in determining the presence of many cardiovascular diseases. Genetic factors are important in determining ECG abnormalities and their link to cardiovascular diseases. Genome-wide association studies and polygenic risk scores (PRSs) have been conducted for various ECG traits such as QT interval and QRS duration. However, these studies mainly focused on cohorts of European descent.

In this cohort study, genome-wide association studies for 6 ECG traits (RR, PR, corrected QT interval [QTc], QRS, JT, and P wave duration) were conducted in a Middle Eastern cohort from the Qatar Precision Health Institute, comprising 13 827 subjects with whole-genome sequence data. Middle Eastern PRSs were developed using clumping and thresholding, and their performance was compared with 26 published PRSs. Genetic predisposition to long QT syndrome was explored using rare variant analysis.

Seventy-four independent loci were obtained with genome-wide significance across the 6 traits (P<5×10-8). Of the 74 loci, 67 (90.5%) were previously reported, and 7 loci (9.5%) were novel and contained 6 genes: STAC and CSMD1 for PR, ANK1 and NCOA2 for QRS, LSP1 for QTc, and MKLN1 for P wave duration. All 26 published PRSs showed good performance in our cohort. PGS002276 showed the best performance for QTc (R2=0.059, P=4.83×10-185), PGS002166 showed the best performance for QRS (R2=0.024, P=1.53×10-75), and PGS000905 showed the best performance for PR (R2=0.053, P=2.57×10-165). Some of these PRSs were associated with cardiovascular diseases. For example, PGS003500, a QTc PRS, was significantly associated with cardiomyopathy (odds ratio per 1 SD=1.58 [95% CI, 1.23-2.01]; P=2.42×10-4). Middle Eastern PRSs substantially outperformed published PRSs and did not perform well in the UK Biobank data. Ten pathogenic variants, including 3 that are specific to Qatari individuals, were observed in 17 long QT syndrome genes and were carried by 19 individuals. The QTc average was larger for mutation carriers (415.6±23.5 versus 402.3±18.5 in noncarriers). Five-year follow-up data did not show a significant change in ECG patterns, regardless of mutation status and PRS values. Four of 2302 individuals had prolonged QTc intervals over the 2 time points.

In this first genome-wide association study for ECG traits in the Middle East using whole-genome sequence data, 7 novel loci (6 genes) were identified. Published PRSs performed well, but newly developed Middle Eastern-specific PRSs performed the best. Novel variants in long QT syndrome genes were observed for the first time in Qatari individuals. Follow-up data did not show significant changes in ECG patterns.

The goal of this study was to evaluate the association between a polygenic risk score (PRS) for QT prolongation (QTc-PRS), corrected QT intervals (QTc) and sudden cardiac death (SCD) in participants enrolled in the UK Biobank with and without sleep-disordered breathing (SDB).

The QTc-PRS was calculated using allele copy number and previously reported effect estimates for each single nuclear polymorphism. Competing-risk regression models adjusting for age, sex, body mass index, QT prolonging medication, race, and comorbid cardiovascular conditions were used for SCD analyses.

A total of 500,584 participants were evaluated (56.5 ± 8 years, 54% female, 1.4% diagnosed with sleep apnea). A higher QTc-PRS was independently associated with the increased QTc interval duration (P < .0001). The mean QTc for the top QTc-PRS quintile was 15 msec longer than the bottom quintile (P < .001). SDB was found to be an effect modifier in the relationship between QTc-PRS and SCD. The adjusted hazard ratio per 5-unit change in QTc-PRS for SCD was 1.64 (95% confidence interval 1.16-2.31, P = .005) among those with SDB and 1.04 (95% confidence interval 0.95-1.14, P = .44) among those without SDB (P for interaction = .01). Black participants with SDB had significantly elevated adjusted risk of SCD (hazard ratio = 9.6, 95% confidence interval 1.24-74, P = .03).

In the UK Biobank population, the QTc-PRS was associated with SCD among participants with SDB but not among those without SDB, indicating that SDB is a significant modifier of the genetic risk. Black participants with SDB had a particularly high risk of SCD.

Arora A, Zareba W, Woosley RL, et al. Genetic QT score as a predictor of sudden cardiac death in participants with sleep-disordered breathing in the UK Biobank. J Clin Sleep Med. 2025;21(3):549-557.

Transcriptional dysregulation, possibly affected by genetic variation, contributes to disease etiology. Due to dissimilarities in development, function, and remodeling during disease progression, transcriptional differences between the left atrium (LA) and right atrium (RA) may provide insight into diseases such as atrial fibrillation.

Lateral differences in atrial transcription were evaluated in CATCH ME (Characterizing Atrial fibrillation by Translating its Causes into Health Modifiers in the Elderly) using a 2-stage discovery and replication design. The design took advantage of the availability of 32 paired samples, for which both LA and RA tissue were obtained, as a discovery cohort, and 98 LA and 69 RA unpaired samples utilized as a replication cohort.

A total of 714 transcripts were identified and replicated as differentially expressed (DE) between LA and RA, as well as 98 exons in 55 genes. Approximately 50% of DE transcripts were colocated with another frequently correlated DE transcript (PFDR ≤0.05 for 579 regions). These "transcription disequilibrium" blocks contained examples including side-specific differential exon usage, such as the PITX2 locus, where ENPEP showed evidence of differential exon usage. Analysis of this region in conjunction with BMP10 identified rs9790621 as associated with ENPEP transcription in LA, while rs7687878 was associated with BMP10 expression in RA. In RA, BMP10 and ENPEP were strongly correlated in noncarriers, which was attenuated in risk-allele carriers, where BMP10 and PITX2 expression were strongly correlated.

These results significantly expand knowledge of the intricate, tissue-specific transcriptional landscape in human atria, including DE transcripts and side-specific isoform expression. Furthermore, they suggest the existence of blocks of transcription disequilibrium influenced by genetics.

Males and females exhibit distinct anatomic and functional characteristics of the heart, predisposing them to specific disease states.

We identified microRNAs (miRNAs/miR) with sex-differential expression in mouse hearts.

Four conserved miRNAs are present in a single locus on the X-chromosome and are expressed at higher levels in females than males. We show miRNA, miR-871, is responsible for decreased expression of the protein SRL (sarcalumenin) in females. SRL is involved in calcium signaling, and we show it contributes to differences in electrophysiology between males and females. miR-871 overexpression mimics the effects of the cardiac physiology of conditional cardiomyocyte-specific Srl-null mice. Inhibiting miR-871 with an antagomir in females shortened ventricular repolarization. The human orthologue of miR-871, miR-888, coevolved with the SRL 3' untranslated region and regulates human SRL.

These data highlight the importance of sex-differential miRNA mechanisms in mediating sex-specific functions and their potential relevance to human cardiac diseases.

Several empirical and theoretical studies suggest the presence of multiple enhancers per gene that collectively regulate gene expression, and that common sequence variation impacting on the activities of these enhancers is a major source of inter-individual gene expression variability. However, for the vast majority of genes, enhancers and the underlying regulatory variation remains unknown. Even for the genes with well-characterized enhancers, the nature of the combined effects from multiple enhancers and their variants, when known, on gene expression regulation remains unexplored. Here, we have evaluated the combined effects from five SCN5A enhancers and their regulatory variants that are known to collectively correlate with SCN5A cardiac expression and underlie QT interval association in the general population. Using small deletions centered at the regulatory variants in episomal reporter assays in a mouse cardiomyocyte cell line, we demonstrate that the variants and their flanking sequences play critical role in individual enhancer activities, likely being a transcription factor (TF) binding site. By oligonucleotide-based pulldown assays on predicted TFs, we identify the TFs likely driving allele-specific enhancer activities. Using all 32 possible allelic synthetic constructs in reporter assays, representing the five bi-allelic enhancers, we demonstrate combined additive effects on overall enhancer activities. Using transient enhancer assays in zebrafish embryos we demonstrate that four elements act as enhancers in vivo. Together, these studies uncover the TFs driving the enhancer activities of QT interval associated SCN5A regulatory variants, reveal the additive effects from allelic combinations of these regulatory variants, and prove their potential to act as enhancers in vivo.

To study the associations of NOS1AP gene polymorphisms with the duration of the QT interval (QTc) in patients with schizophrenia receiving antipsychotics.

One hundred and sixty-eight patients (78 men and 90 women) with an established diagnosis of schizophrenia were examined. The patients received basic antipsychotic therapy. At the time of admission to the hospital, a standard 12-lead electrocardiogram recording was performed. The calculation of the QTc interval was carried out using the Bazett formula. Three NOS1AP polymorphisms (rs12029454, rs10494366 and rs12143842) were selected for genotyping.

Spearman's correlation revealed a significant relationship between CPZeq and the duration of the QTc interval in the group of men (rs=0.262; p=0.021; pBonf=0.042). CPZeq was positively correlated with the duration of the QTc interval in men with AA and AG rs12029454 (rs=0.717; p=0.00025; pbonf=0.0015), GG and GT rs10494366 (rs=0.381; p=0.008; pbonf=0.048), TT and CT rs12143842 (rs=0.389; p=0.003; pbonf=0.018) genotypes. We did not find any significant correlations in the group of women.

Genetic variants rs12029454, rs10494366 and rs12143842 of the NOS1AP gene are associated with the duration of the QTc interval in men with schizophrenia in response to antipsychotics. The AA/AG rs12029454, GG/GT rs10494366 and TT/CT rs12143842 genotypes in men contribute to the prolongation of the QTc interval and the development of undesirable cardiovascular disorders against the background of antipsychotic therapy.

Drug-induced long QT syndrome (diLQTS) is an adverse reaction from over 150 FDA-approved medications, posing the risk of triggering torsades de pointes and sudden death. While common genetic variants may modestly impact QT interval individually, their collective effect can significantly amplify risk of diLQTS. Consequently, this study aimed to validate a polygenic risk score (PRS) for diLQTS previously proposed by Strauss et al .

A retrospective cohort study was conducted utilizing patients from the Michigan Genomics Initiative prescribed 27 high-risk QT-prolonging drugs and an ECG during the prescription. The primary outcome was marked prolongation of the QTc interval (either >60 ms change from baseline or >500 ms absolute value) during treatment with a high-risk QT-prolonging drug.

The primary outcome occurred in 12.0% of n  = 6070 self-reported White, 12.4% of 558 African American, and 8.2% of 110 Asian patients. The PRS significantly associated with diLQTS in White patients [adjusted odds ratio = 1.44 (95% CI: 1.09-1.89); P  = 0.009]. However the study lacked sufficient statistical power to confirm the PRS as a risk factor in African Americans [adjusted odds ratio = 2.18 (95% CI: 0.98-5.49); P  = 0.073] and Asians [adjusted odds ratio = 3.21 (95% CI: 0.69-16.87); P  = 0.139] due to smaller sample sizes in these groups.

The previously published PRS for diLQTS was validated in a large, real-world cohort, demonstrating its potential as a tool for identifying high-risk patients. Incorporating this PRS into routine clinical practice could enable proactive measures to prevent life-threatening diLQTS.

Mendelian randomization (MR) uses genetic variants associated with an exposure (eg, high blood pressure) as instrumental variables to test causal effects on an outcome (eg, atrial fibrillation [AF]). By leveraging the random assortment of genetic variants during gamete formation, MR reduces biases like confounding and reverse causation. We screened 391 papers, examining 277 that applied MR to investigate arrhythmia and, in others, cardiovascular traits, lifestyle, behavioral traits, and body composition. Our analysis focused on MR studies of arrhythmia and cardiovascular traits. Key findings highlight high systolic blood pressure, low resting heart rate, elevated cardiac troponin I levels, coronary artery disease, and heart failure as risk factors for AF, whereas AF itself increases heart failure risk. As genetic data become more accessible, MR's relevance grows. Sensitivity analyses and integrating MR with other methodologies in a triangulation framework enhance the robustness of causal inferences by navigating different biases.

To systematically assess clinical studies involving patients undergoing drug therapy, comparing different genotypes to assess the relationship with changes in QT intervals, with no limitations on study design, setting, population, dosing regimens, or duration.

This systematic review followed PRISMA guidelines and a pre-registered protocol. Clinical human studies on PGx markers of diQTP were identified, assessed using standardized tools, and categorized by design. Gene associations were classified as pharmacokinetic or pharmacodynamic. Identified genes underwent pathway enrichment analyses. Drugs were classified by third-level Anatomical Therapeutic Chemical (ATC) codes. Descriptive statistics were computed by study category and drug classes.

Of 4,493 reports, 84 studies were included, identifying 213 unique variants across 42 drug classes, of which 10% were replicated. KCNE1-Asp85Asn was the most consistent variant. Most findings (82%) were derived from candidate gene studies, suggesting bias toward known markers. The diQTP-associated genes were mainly linked to "cardiac conduction" and "muscle contraction" pathways (false discovery rate = 4.71 × 10-14). We also found an overlap between diQTP-associated genes and congenital long QT syndrome genes.

Key genes, drugs, and pathways were identified, but few consistent PGx markers emerged. Extensive, unbiased studies with diverse populations are crucial to advancing the field.

A protocol was pre-registered at PROSPERO under registration number CRD42022296097.

Data sets generated by this review are available at figshare: DOI: 10.6084/m9.figshare.27959616.

Genome-wide association studies (GWAS) have identified genetic variants, usually single-nucleotide polymorphisms (SNPs), associated with human traits, including disease and disease risk. These variants (or causal variants in linkage disequilibrium with them) usually affect the regulation or function of a nearby gene. A GWAS locus can span many genes, however, and prioritizing which gene or genes in a locus are most likely to be causal remains a challenge. Better prioritization and prediction of causal genes could reveal disease mechanisms and suggest interventions.

We describe a new Bayesian method, termed SigNet for significance networks, that combines information both within and across loci to identify the most likely causal gene at each locus. The SigNet method builds on existing methods that focus on individual loci with evidence from gene distance and expression quantitative trait loci (eQTL) by sharing information across loci using protein-protein and gene regulatory interaction network data. In an application to cardiac electrophysiology with 226 GWAS loci, only 46 (20%) have within-locus evidence from Mendelian genes, protein-coding changes, or colocalization with eQTL signals. At the remaining 180 loci lacking functional information, SigNet selects 56 genes other than the minimum distance gene, equal to 31% of the information-poor loci and 25% of the GWAS loci overall. Assessment by pathway enrichment demonstrates improved performance by SigNet. Review of individual loci shows literature evidence for genes selected by SigNet, including PMP22 as a novel causal gene candidate.

Genetic overdiagnosis of long QT syndrome (LQTS) becomes a critical concern due to the high clinical significance of DNA diagnosis. Current guidelines for LQTS genetic testing recommend a limited scope and strict referral based on the Schwartz score. Nevertheless, LQTS may be underdiagnosed in patients with borderline phenotypes. We aimed to evaluate the total yield of rare variants in cardiac genes in LQTS patients. The cohort of 82 patients with LQTS referral diagnosis underwent phenotyping, Schwartz score counting, and exome sequencing. We assessed known LQTS genes for diagnostics, as per guidelines, and a broader set of genes for research. Diagnostic testing yield reached 75% in index patients; all causal variants were found in KCNQ1, KCNH2, and SCN5A genes. Research testing of 248 heart-related genes achieved a 50% yield of molecular diagnosis in patients with a low Schwartz score (<3.5). In patients with LQTS-causing variants, each additional rare variant in heart-related genes added 0.94 points to the Schwartz score (p value = 0.04), reflecting the more severe disease in such patients than in those with causal variants but without additional findings. We conclude that the current LQTS genetic diagnosis framework is highly specific but may lack sensitivity for patients with a Schwartz score <3.5. Improving referral criteria for these patients could enhance DNA diagnosis. Also, our results suggest that additional variants in cardiac genes may affect the severity of the disease in the carriers of LQTS-causing variants, which may aid in identifying new modifier genes.

Ventricular repolarization time (ECG QT and JT intervals) is associated with malignant arrhythmia. Genome-wide association studies have identified 230 independent loci for QT and JT; however, 50% of their heritability remains unexplained. Previous work supports a causal effect of lower serum calcium concentrations on longer ventricular repolarization time. We hypothesized calcium interactions with QT and JT variant associations could explain a proportion of the missing heritability.

We performed genome-wide calcium interaction analyses for QT and JT intervals. Participants were stratified by their calcium level relative to the study distribution (top or bottom 20%). We performed a 2-stage analysis (genome-wide discovery [N=62 532] and replication [N=59 861] of lead variants) and a single-stage genome-wide meta-analysis (N=122 393, [European ancestry N=117 581, African ancestry N=4812]). We also calculated 2-degrees of freedom joint main and interaction and 1-degree of freedom interaction P values. In 2-stage and single-stage analyses, 50 and 98 independent loci, respectively, were associated with either QT or JT intervals (2-degrees of freedom joint main and interaction P value <5×10-8). No lead variant had a significant interaction result after correcting for multiple testing and sensitivity analyses provided similar findings. Two loci in the single-stage meta-analysis were not reported previously (SPPL2B and RFX6).

We have found limited support for an interaction effect of serum calcium on QT and JT variant associations despite sample sizes with suitable power to detect relevant effects. Therefore, such effects are unlikely to explain a meaningful proportion of the heritability of QT and JT, and factors including rare variation and other environmental interactions need to be considered.

The electrocardiogram (ECG) can capture obesity-related cardiac changes. Artificial intelligence-enhanced ECG (AI-ECG) can identify subclinical disease. We trained an AI-ECG model to predict body mass index (BMI) from the ECG alone. Developed from 512,950 12-lead ECGs from the Beth Israel Deaconess Medical Center (BIDMC), a secondary care cohort, and validated on UK Biobank (UKB) (n = 42,386), the model achieved a Pearson correlation coefficient (r) of 0.65 and 0.62, and an R2 of 0.43 and 0.39 in the BIDMC cohort and UK Biobank, respectively for AI-ECG BMI vs. measured BMI. We found delta-BMI, the difference between measured BMI and AI-ECG-predicted BMI (AI-ECG-BMI), to be a biomarker of cardiometabolic health. The top tertile of delta-BMI showed increased risk of future cardiometabolic disease (BIDMC: HR 1.15, p < 0.001; UKB: HR 1.58, p < 0.001) and diabetes mellitus (BIDMC: HR 1.25, p < 0.001; UKB: HR 2.28, p < 0.001) after adjusting for covariates including measured BMI. Significant enhancements in model fit, reclassification and improvements in discriminatory power were observed with the inclusion of delta-BMI in both cohorts. Phenotypic profiling highlighted associations between delta-BMI and cardiometabolic diseases, anthropometric measures of truncal obesity, and pericardial fat mass. Metabolic and proteomic profiling associates delta-BMI positively with valine, lipids in small HDL, syntaxin-3, and carnosine dipeptidase 1, and inversely with glutamine, glycine, colipase, and adiponectin. A genome-wide association study revealed associations with regulators of cardiovascular/metabolic traits, including SCN10A, SCN5A, EXOG and RXRG. In summary, our AI-ECG-BMI model accurately predicts BMI and introduces delta-BMI as a non-invasive biomarker for cardiometabolic risk stratification.

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.

The most frequent adverse event associated with bedaquiline (BDQ) is the QTc interval prolongation; however, there was no biomarkers that could be used to predict the occurrence of QTc prolongation in BDQ-treated patients. In this study, we employed the ultra-high performance liquid chromatography-MS/MS (UHPLC-MS/MS) to generate metabolic profiling for the discovery of potential predictive urine biomarkers of QTc prolongation in these patients. Untargeted metabolomic technique was used to concentrate the differential metabolic pathway, and targeted metabolomic technique was subsequently performed to identify predictive biomarkers for QTc prolongation. A total of 45 rifampicin-resistant TB (RR-TB) and multidrug-resistant TB (MDR-TB) patients were enrolled in our study, including 15 RR/MDR-TB patients with QTc interval prolongation (QIP) and 30 RR/MDR-TB patients with QTc interval un-prolongations (QIU). Untargeted technique revealed that the lipid metabolism was the most differential metabolic pathway between two groups. Further targeted technique identified four differential metabolites, including betaine, LPE (18:2), LPE (20:3), and LPE (20:4). The combined analysis of metabolisms revealed that the combined use of LPE (20:3) and LPE (20:4) had the best performance for predicting the occurrence of QTc prolongation in TB patients, yielding a sensitivity of 87.4% and a specificity of 78.5%. In addition, with the progression of BDQ treatment, the LPEs exhibited persistent difference in the BDQ-treated TB patients experiencing QTc interval prolongation. In conclusion, our data demonstrate that the combined use of LPE (20:3) and LPE (20:4) yields promising performance for predicting the occurrence of QTc interval prolongation in BDQ-treated patients.

During the neonatal stage, the cardiomyocyte undergoes a constellation of molecular, cytoarchitectural, and functional changes known collectively as cardiomyocyte maturation to increase myocardial contractility and cardiac output. Despite the importance of cardiomyocyte maturation, the molecular mechanisms governing this critical process remain largely unexplored.

We leveraged an in vivo mosaic knockout system to characterize the role of Carm1, the founding member of protein arginine methyltransferase, in cardiomyocyte maturation. Using a battery of assays, including immunohistochemistry, immuno-electron microscopy imaging, and action potential recording, we assessed the effect of loss of Carm1 function on cardiomyocyte cell growth, myofibril expansion, T-tubule formation, and electrophysiological maturation. Genome-wide transcriptome profiling, H3R17me2a chromatin immunoprecipitation followed by sequencing, and assay for transposase-accessible chromatin with high-throughput sequencing were used to investigate the mechanisms by which CARM1 (coactivator-associated arginine methyltransferase 1) regulates cardiomyocyte maturation. Finally, we interrogated the human syntenic region to the H3R17me2a chromatin immunoprecipitation followed by sequencing peaks for single-nucleotide polymorphisms associated with human heart diseases.

We report that mosaic ablation of Carm1 disrupts multiple aspects of cardiomyocyte maturation cell autonomously, leading to reduced cardiomyocyte size and sarcomere thickness, severe loss and disorganization of T tubules, and compromised electrophysiological maturation. Genomics study demonstrates that CARM1 directly activates genes that underlie cardiomyocyte cytoarchitectural and electrophysiological maturation. Moreover, our study reveals significant enrichment of human heart disease-associated single-nucleotide polymorphisms in the human genomic region syntenic to the H3R17me2a chromatin immunoprecipitation followed by sequencing peaks.

This study establishes a critical and multifaceted role for CARM1 in regulating cardiomyocyte maturation and demonstrates that deregulation of CARM1-dependent cardiomyocyte maturation gene expression may contribute to human heart diseases.

We report a long QT syndrome 15 whose diagnosis was suspected during foetal life and confirmed at birth and was associated with congenital heart disease. Genetic testing revealed a rare mutation associated with the CALM2 gene. At 23 weeks of gestation, severe foetal sinus bradycardia (∼100 bpm) was detected. In the third trimester, the foetus developed severe right ventricular hypertrophy. At birth, the electrocardiogram showed a long QT interval of 640 ms, and after 1 hour, the newborn showed functional 2:1 atrioventricular block at ventricular rate of 50 bpm. After further pharmacological therapies, epicardial wires were surgically implanted for transient pacing in VVI mode at 90 bpm. Echocardiogram showed aneurysmatic left atrial appendage, dilated right segments, hypertrophied right ventricle, ostium secundum type atrial septal defect, and muscular ventricular septal defect. At two weeks of postpartum, a permanent dual-chamber pacemaker was implanted in the DDD mode and the patient was discharged with a prescription of beta-blockers and calcium therapy.

Cardiac arrhythmias pose a major threat to a patient's health, yet prove to be often difficult to predict, prevent and treat. A key mechanism in the occurrence of arrhythmias is disturbed Ca2+ homeostasis in cardiac muscle cells. As a Ca2+-activated non-selective cation channel, TRPM4 has been linked to Ca2+-induced arrhythmias, potentially contributing to translating an increase in intracellular Ca2+ concentration into membrane depolarisation and an increase in cellular excitability. Indeed, evidence from genetically modified mice, analysis of mutations in human patients and the identification of a TRPM4 blocking compound that can be applied in vivo further underscore this hypothesis. Here, we provide an overview of these data in the context of our current understanding of Ca2+-dependent arrhythmias.

Inherited arrhythmias are a heterogeneous group of conditions that confer risk of sudden death. Many inherited arrhythmias have been linked to pathogenic genetic variants that result in ion channel dysfunction, although current genetic testing panels fail to identify variants in many patients, potentially secondary to their underlying substrates being oligogenic or polygenic. Here we review the current state of knowledge surrounding the cellular mechanisms of inherited arrhythmias generated from stem cell models with a focus on integrating genetic and mechanistic data. The utility and limitations of human induced pluripotent stem cell models in disease modeling and drug development are also explored with a particular focus on examples of pharmacogenetics and precision medicine. We submit that progress in understanding inherited arrhythmias is likely to be made by using human induced pluripotent stem cells to model probable polygenic cases as well as to interrogate the diverse and potentially complex molecular networks implicated by genome-wide association studies.

Identifying causal variants among tens or hundreds of associated variants at each locus mapped by genome-wide association studies (GWAS) of complex traits is a challenge. As vast majority of GWAS variants are noncoding, sequence variation at cis -regulatory elements affecting transcriptional expression of specific genes is a widely accepted molecular hypothesis. Following this cis -regulatory hypothesis and combining it with the observation that nucleosome-free open chromatin is a universal hallmark of all types of cis -regulatory elements, we aimed to identify candidate causal regulatory variants underlying electrocardiographic QT interval GWAS loci. At a dozen loci, selected for higher effect sizes and a better understanding of the likely causal gene, we identified and included all common variants in high linkage disequilibrium with the GWAS variants as candidate variants. Using ENCODE DNase-seq and ATAC-seq from multiple human adult cardiac left ventricle tissue samples, we generated genome-wide maps of open chromatin regions marking putative regulatory elements. QT interval associated candidate variants were filtered for overlap with cardiac left ventricle open chromatin regions to identify candidate causal cis -regulatory variants, which were further assessed for colocalizing with a known cardiac GTEx expression quantitative trait locus variant as additional evidence for their causal role. Together, these efforts have generated a comprehensive set of candidate causal variants that are expected to be enriched for cis -regulatory potential and thereby, explaining the observed genetic associations.

Several empirical and theoretical studies suggest presence of multiple enhancers per gene that collectively regulate gene expression, and that common sequence variation impacting on the activities of these enhancers is a major source of inter-individual variability in gene expression. However, for vast majority of genes, enhancers and the underlying regulatory variation remains unknown. Even for the genes with well-characterized enhancers, the nature of the combined effects from multiple enhancers and their variants, when known, on gene expression regulation remains unexplored. Here, we have evaluated the combined effects from five SCN5A enhancers and their regulatory variants that are known to collectively correlate with SCN5A cardiac expression and underlie QT interval association in the general population. Using small deletions centered at the regulatory variants in episomal reporter assays in a mouse cardiomyocyte cell line we demonstrate that the variants and their flanking sequences play critical role in individual enhancer activities, likely being a transcription factor (TF) binding site. By performing oligonucleotide-based pulldown assays on predicted TFs we identify the TFs likely driving allele-specific enhancer activities. Using all 32 possible allelic synthetic constructs in reporter assays, representing the five biallelic enhancers in tandem in their genomic order, we demonstrate combined additive effects on overall enhancer activities. Using transient enhancer assays in developing zebrafish embryos we demonstrate the four out the five enhancer elements act as enhancers in vivo . Together, these studies extend the previous findings to uncover the TFs driving the enhancer activities of QT interval associated SCN5A regulatory variants, reveal the additive effects from allelic combinations of these regulatory variants, and prove their potential to act as enhancers in vivo .

Genome-wide association studies have reported a correlation between a SNP of the RING finger E3 ubiquitin protein ligase rififylin (RFFL) and QT interval variability in humans (Newton-Cheh et al., 2009). Previously, we have shown that RFFL downregulates expression and function of the human-like ether-a-go-go-related gene potassium channel and corresponding rapidly activating delayed rectifier potassium current (IKr) in adult rabbit ventricular cardiomyocytes. Here, we report that RFFL also affects the transient outward current (Ito), but in a peculiar way. RFFL overexpression in adult rabbit ventricular cardiomyocytes significantly decreases the contribution of its fast component (Ito,f) from 35% to 21% and increases the contribution of its slow component (Ito,s) from 65% to 79%. Since Ito,f in rabbits is mainly conducted by Kv4.3, we investigated the effect of RFFL on Kv4.3 expressed in HEK293A cells. We found that RFFL overexpression reduced Kv4.3 expression and corresponding Ito,f in a RING domain-dependent manner in the presence or absence of its accessory subunit Kv channel-interacting protein 2. On the other hand, RFFL overexpression in Kv1.4-expressing HEK cells leads to an increase in both Kv1.4 expression level and Ito,s, similarly in a RING domain-dependent manner. Our physiologically detailed rabbit ventricular myocyte computational model shows that these yin and yang effects of RFFL overexpression on Ito,f, and Ito,s affect phase 1 of the action potential waveform and slightly decrease its duration in addition to suppressing IKr. Thus, RFFL modifies cardiac repolarization reserve via ubiquitination of multiple proteins that differently affect various potassium channels and cardiac action potential duration.

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.

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.

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).

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.

Inherited forms of cardiac arrhythmias mostly are rare diseases (prevalence <1:2000) and considered to be either "primary electrical heart disorders" due to the absence of structural heart abnormalities or "cardiac ion channel disorders" due to the myocellular structures involved. Precise knowledge of the electrocardiographic features of these diseases and their genetic classification will enable early disease recognition and prevention of cardiac events including sudden cardiac death.The genetic background of these diseases is complex and heterogeneous. In addition to the predominant "private character" of a mutation in each family, locus heterogeneity involving many ion channel genes for the same familial arrhythmia syndrome is typical. Founder pathogenic variants or mutational hot spots are uncommon. Moreover, phenotypes may vary and overlap even within the same family and mutation carriers. For the majority of arrhythmias, the clinical phenotype of an ion channel mutation is restricted to cardiac tissue, and therefore, the disease is nonsyndromic.Recent and innovative methods of parallel DNA analysis (so-called next-generation sequencing, NGS) will enhance further mutation and other variant detection as well as arrhythmia gene identification.