Circulation: Genomic and Precision Medicine

Background and Aims: Polygenic risk scores (PRSs) for atherosclerotic cardiovascular disease (ASCVD) can perform equivalently at the population level yet disagree for individual patients. We examined whether such intra-individual variability reflects genuinely complementary risk information or mainly statistical and methodological uncertainty, and whether it affects clinical classification once PRSs are integrated into SCORE2-OP. Methods: In 4,137 ASCVD-free participants of the CoLaus|PsyCoLaus cohort (478 incident events over a median 14.4 years), we identified 16 ASCVD-PRSs with practically equivalent population-level performance using Bayesian equivalence testing. We quantified intra-individual variability (standard deviation, coefficient of variation, intraclass correlation, Cohen's kappa, extreme discordance), tested whether discordance exceeded chance, decomposed scores into shared and unique genetic components, and assessed variability after integration into SCORE2-OP, benchmarked against perturbation of systolic blood pressure. Results: For a typical individual, risk estimates varied by 18 percentile points across PRSs. Discordance matched chance expectations under a shared-signal model, with no distinct phenotypic profile among discordant individuals, and predictive power resided overwhelmingly in the shared genetic component. Variability tracked PRS size and weighting rather than distinct variants. After integration into SCORE2-OP, 75.6% of participants were placed in different categories by at least one model and 54.6% as both low and high risk; instability was concentrated near guideline thresholds and far exceeded that from blood-pressure measurement error. Conclusions: Equivalent population-level performance is not sufficient to treat PRSs as interchangeable at the individual level, and methodological standardisation and pragmatic clinical trials remain necessary to determine whether PRS integration improves long-term cardiovascular outcomes.

Background: Cardiovascular disease (CVD) is the leading cause of mortality in New Zealand, with significant inequities affecting M[a]ori and Pacific peoples. Familial hypercholesterolaemia (FH) affects approximately 1 in 313 individuals globally, yet over 90% remain undiagnosed. Standard polygenic risk scores (PRS) derived from European cohorts may not be portable to diverse ancestries. We developed the HoloQ Omniscan Waka Te Ira, a custom Illumina Global Screening Array (GSA) v3 enriched with FH mutations, coronary artery disease (CAD) PRS markers, and network medicine-derived content. Methods: We customised the GSA v3 by adding 43,437 single nucleotide polymorphisms (SNPs) targeting FH and CAD. Content included 6,717 unique variants in primary FH genes; 14,005 pathogenic or likely pathogenic cardiovascular and pharmacogene variants; and 5,845 copy number variant probes. We further incorporated 5,232 network medicine derived CAD SNPs, 14,806 rare variants for a multiancestry PRS, and 407 globally diverse and population-specific variants. The final design comprised 47,027 target SNPs. Validation utilised large-scale genotype and whole-genome sequencing (WGS) datasets with PRS benchmarking. Results: In a large European-ancestry dataset, we observed high recovery for common PRS loci but low recovery for population-specific founder variants. The array captured 938 (84%) of all pathogenic or likely pathogenic FH variants catalogued in ClinVar, representing a 26.4% expansion beyond the standard backbone array. WGS validation identified additional carriers of rare high impact variants present only in the custom content. The selected CAD PRS model achieved an adjusted area under the receiver operating characteristic curve of 0.786. Conclusion: The HoloQ Omniscan Waka Te Ira enhances detection of clinically relevant FH variants and provides robust PRS coverage. The low recovery of population-specific alleles underscores the necessity of this custom array for equitable genomic medicine in New Zealand's multi-ethnic population.

Background. Polygenic scores (PRS) for coronary artery disease (CAD) are derived almost entirely from European-ancestry data. Their portability to Southeast Asian populations, including the Vietnamese, is largely uncharacterised and clinically consequential when scores are used with risk thresholds. Methods. We evaluated four independent European-derived CAD scores from the PGS Catalog (PGS000058, PGS000349, PGS002809, PGS004198; 70 - 5,723 variants) in 2,504 individuals from the 1000 Genomes Project, focusing on the Vietnamese Kinh (KHV) and Dai (CDX) samples. Per-individual scores were computed with PLINK2 and standardised. We assessed (i) the cross-ancestry distribution (calibration) and (ii) a clinically-relevant consequence: the proportion of each population flagged high genetic risk when the European top-20% threshold is applied (20% if perfectly calibrated). Results. For the primary score (PGS000058) the standardised PRS differed across super-populations (ANOVA F(4, 2499) = 121.1, p < 0.001); the Vietnamese Kinh mean was +0.47 SD above the European mean (Welch t = 7.77, p = 2.0 x 10^ -14). Applying the European top-20% high-risk threshold, the fraction of Vietnamese Kinh flagged ranged from 22.2% to 57.6% across the four scores, and of Dai from 21.5% to 43.0%, versus the intended 20%. Three of the four scores over-flagged Vietnamese (25-58%); the largest score (PGS004198) was approximately calibrated for East/Southeast Asians ([~]22%) but markedly over-flagged Africans (69.3%). Conclusions. European-derived CAD polygenic scores are inconsistently calibrated in Vietnamese and other Southeast Asian samples, and most substantially over-flag high genetic risk when a European threshold is applied. The magnitude and even the direction of miscalibration depend on the specific score, so no such score can be assumed transferable without local validation and recalibration. Distribution shift bounds, but does not by itself quantify, loss of predictive accuracy, which requires phenotyped data.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia and a major cause of cardioembolic stroke. Although polygenic risk scores (PRS) are well characterized to quantify inherited susceptibility for AF, they provide limited insight into the pathways and tissues underlying genetic risk, which are critical to uncover for individual risk prediction. In this study, we develop a pathway-level multi-omics representation learning framework that converts individual genetic profiles into interpretable biological features by integrating GWAS-derived pathway burden scores with tissue-specific transcriptomic pathway signals. We constructed machine learning models to assess population-level AF risk prediction performance across genomic and transcriptomic tissue contexts; the pathway-based global attention models substantially improved risk prediction performance over PRS and other baselines (AUROC improved from 0.601 to 0.738). Transformer and graph neural network frameworks then assessed individual-level pathway interpretability, revealing heterogeneous contributions from electrical signaling, cardiac development, and DNA repair pathways to AF risk. This added interpretability highlights the potential of this pathway approach to enable more mechanistically informed risk stratification than static PRS by capturing underlying heterogeneity. To independently assess whether prioritized pathways reflected cardiac regulatory biology, we compared pathway rankings with transcriptional effects predicted by the AlphaGenome foundation model. Variants in highly ranked pathways showed significantly greater predicted effects on expression in atrial and ventricular tissues (FDR = 0.032) relative to controls, providing orthogonal evidence that the model identifies biologically relevant mechanisms. Overall, this work reframes polygenic risk from a single measure of susceptibility to tissue-informed pathway mechanisms, providing a framework for interpretable genomic stratification in complex diseases.

Background: Familial hypercholesterolemia (FH) is a semi-dominant genetic disorder characterized by lifelong elevation of low-density lipoprotein cholesterol (LDL-C) and a markedly increased risk of premature atherosclerotic cardiovascular disease (CVD). Despite this elevated risk, some individuals with FH survive beyond 70 years of age without developing clinical CVD. This study aimed to identify genetic variants associated with protection against cardiovascular events and to uncover mechanisms contributing to this resilience phenotype. Methods: Whole-exome sequencing (WES) was performed in 243 French-Canadian heterozygous FH individuals carrying the pathogenic LDLR c.259T>G (p.Trp87Gly) variant. After stratification by age and cardiovascular event (CVE) status, 35 individuals with premature CVE and 20 individuals aged [&ge;]70 years who remained free of CVE despite spending several decades in the pre-statin era were selected for comparative analysis. Results: Variant annotation and quality-control validation using Firth logistic regression identified 12 genetic variants potentially associated with cardiovascular resilience. Among these, a stop-gain variant resulting from the single-nucleotide polymorphism rs4985556 in IL34 demonstrated the strongest association with event-free survival (allele frequency in CVE- = 0.25 vs. CVE+ = 0.00; {chi}2 = 19.25; P = 1.15 x 10-5). The IL34 stop-gain variant (c.639C>A [p.Tyr213*]) was associated with a markedly increased likelihood of cardiovascular event-free survival (OR = 20.9; 95% CI, 2.7-2841.7; P = 3.45 x 10-4). Conclusion: These findings identify IL34 as a potential cardiovascular resilience gene and highlight novel genetic determinants that may protect against cardiovascular events despite lifelong exposure to elevated LDL-C levels. In addition to IL34, eleven variants showed strong associations with a CVE-free phenotype and warrant further investigation to elucidate their biological mechanisms and potential relevance for cardiovascular disease prevention.

Background: Cardiomyopathy and channelopathy (CC) gene variants have been linked to sudden cardiac arrest (SCA) or death (SCD) in small, selected pedigree or post-mortem studies of arrhythmic mitral valve prolapse (MVP). However, the utility of clinical whole exome sequencing (WES) panels as a risk stratification tool in unselected MVP samples is unknown. Objectives: The goal of the study was to test the utility of clinical WES panels with CC variant screening for arrhythmic risk stratification in MVP. Methods: We performed research based WES in 203 consecutive MVPs without other arrhythmic substrate. Variants were filtered for rare (<0.1%) and protein altering variants in 157 CC genes within an existing clinical panel and annotated with a clinical significance predictor. Overall frequency of CC variants was compared to a sample of general population exomes from gnomad v4.1.0. We assessed a composite severe arrhythmic outcome of SCD or frequent ectopy/ventricular tachycardia or ventricular fibrillation/SCA requiring catheter ablation or defibrillator implantation, respectively. Results: CC variants were more common in MVPs compared to the general population (RR: 4.3, p < 0.01). Pathogenic/Likely Pathogenic (P/LP) variants were identified in 18 MVPs (9%; 8 CC variants among 12 genes). P/LP variants were independently associated with the composite arrhythmic outcome after adjustment for traditional imaging parameters of risk including mitral annular disjunction and bileaflet involvement (OR: 1.23 [95% CI: 1.03 to 1.47], p = 0.01). P/LP variant carriers were at greater arrhythmic risk in time to event analyses starting at birth (HR: 2.87 [95% CI: 1.24 to 6.62], p = 0.01). Conclusions: A subset of MVPs with P/LP variants in CC genes are at higher arrhythmic risk. A clinical WES panel inclusive of CC variants may represent a valuable arrhythmic risk stratification tool in MVP beyond traditional imaging parameters.

Background: Genome-wide polygenic risk scores (PRSs) for coronary artery disease (CAD) aggregate genetic effects across the genome and may obscure biologically distinct mechanisms. We aimed to develop cell-type-specific PRSs (csPRSs) using single-cell RNA sequencing (scRNA-seq) data and investigate their interactions with lipids on CAD risk. Methods: Using publicly available scRNA-seq data from human heart tissue, we identified cell-type-specific genes across 13 major cell types and 64 subpopulations and grouped them into 10 cell clusters. Variants from a CAD genome-wide association study (GWAS) were mapped to cluster-specific genes to construct csPRSs for European-ancestry participants from the UK Biobank (UKB). Interactions between csPRSs and lipid-related phenotypes were evaluated using Cox proportional hazards models and stratified analyses, with significant findings further assessed in an internal validation dataset. Results: Distinct interaction patterns with lipid phenotypes were observed across csPRSs. Low-density lipoprotein (LDL)-related lipid traits, including apolipoprotein B (ApoB), low-density lipoprotein cholesterol (LDL-C), and total cholesterol (cholesterol), primarily interacted with adipocytes (Adip), whereas high-density lipoprotein (HDL) traits interacted with endothelial-mesothelial (EC-Meso), fibroblast (FB), and immune-cell csPRSs. Notably, interactions for Adip csPRSs were replicated in internal validation analyses. Conclusions: Cell-type-specific decomposition of genome-wide PRSs for CAD identified biologically distinct lipid interactions that were not captured by the genome-wide PRS. Adipocyte genetic factors may influence how LDL lipids affect CAD risk. These findings highlight the potential of cell-type-informed PRSs to improve the biological interpretation of PRSs and provide insights into the heterogeneous mechanisms underlying CAD.

Background: Clinically significant carotid stenosis remains a major cause of ischemic stroke (IS), yet prediction of disease progression is limited. Polygenic risk scores (PRSs) for coronary artery disease (CAD) and peripheral artery disease (PAD) have demonstrated associations with atherosclerosis burden and major cardiovascular disease (CVD) events, but whether these insights extend to carotid stenosis is unclear. We evaluated the association and discriminative performance of validated PRSs for CAD, PAD, IS, and carotid intima-media thickness (cIMT) with carotid stenosis. Methods: Carotid stenosis was identified in genotyped Mass General Brigham Biobank participants using validated ICD- and CPT-based phenotyping algorithms. Logistic regression adjusted for age, sex, and 10 ancestry principal components assessed PRS associations. Incremental discrimination was evaluated using changes in Harrell's C-statistic. Results: Compared with 52,636 controls, 670 participants with carotid stenosis were more frequently male (61.5% vs 44.1%), older (70.8 SD 9.0 vs 53.4 SD 17.2 years), and more likely to be European (95.7% vs 84.1%). The IS (OR 1.31, 95% CI 1.21?1.41), CAD (OR 1.62, 95% CI 1.50?1.75), and PAD (OR 1.66, 95% CI 1.54?1.80) PRSs were each associated with carotid stenosis (all p<0.0001), while the cIMT PRS was not (p=0.28). The PAD PRS demonstrated the greatest improvement in discrimination beyond age, sex, and ancestry (?C-statistic 0.017; C-statistic 0.845, 95% CI 0.833?0.856). A fully adjusted model incorporating established CVD risk factors achieved a C-statistic of 0.852 (95% CI 0.841?0.862), with modest improvement after PAD PRS inclusion (?C-statistic 0.008). Individuals in the top 5% of the PAD PRS and top 4% of CAD PRS distribution demonstrated 3-fold greater odds of carotid stenosis. Conclusions: A PAD and CAD PRS may help identify individuals at high likelihood for carotid stenosis, though broad discriminative performance remains limited. These findings support further investigation of CVD PRSs as adjunctive risk stratification tools.

Aims: Arrhythmogenic cardiomyopathy (ACM) is a genetic disease defined by arrhythmias and myocardial fibrosis with impaired cardiac function and increased risk of sudden cardiac death. Pathogenic variants are mostly identified in desmosomal genes such as desmoglein-2 (DSG2). We identified a novel disease phenotype in patients homozygous for the DSG2 variant c.523+2T>C (splice site of exon 5/intron 5), characterized by cardioembolic events in addition to classical ACM features. Here, we evaluate this new thromboembolic phenotype by comparing the clinical data to specific murine disease models. Methods and Results: We describe three unrelated patients presenting with an embolic event and/or left ventricular thrombus. Clinical evaluation revealed a shared right ventricular ACM phenotype characterized by arrhythmias, impaired function, and fibrotic remodeling. In addition, patients exhibited localized fibrotic changes of the left ventricular apex with formation of an aneurysm and predisposition to thrombus formation. Genetic analysis identified the DSG2 variant c.523+2T>C as a founder variant from the "Bernese Oberland". To elucidate the variant's functional impact, a mouse model deficient for Dsg2 exon 5 (Dsg2{Delta}ex5) was established and compared to a model carrying the adhesion-deficient Dsg2-W2A variant. Echocardiography, ECG, and histology in Dsg2{Delta}ex5 mice revealed similar disease patterns to patients and a loss of DSG2 expression. Importantly, these animals exhibited left apical fibrosis with aneurysm formation and left ventricular thrombus formation. In contrast, the Dsg2-W2A model presented with a biventricular ACM-phenotype but without left ventricular thrombi. Conclusions: We identified a novel ACM phenotype in patients homozygous for the DSG2 founder variant c.523+2T>C characterized by left ventricular apical fibrosis. Dsg2{Delta}ex5 mice recapitulate the patients' phenotype suggesting a causative link between left ventricular aneurysm due to DSG2 deficiency and thrombus formation with subsequent embolism. This highlights a novel pathological feature of ACM and the need for variant and phenotype-specific therapy.

Background and Aims Genetic testing in dilated cardiomyopathy (DCM) guides risk stratification and family screening. Likely pathogenic or pathogenic (LP/P) variants are identified in approximately one-third of patients, leaving many without a genetic diagnosis. Cohort studies suggest that "gene-elusive" patients have a lower risk of adverse events. This study aims to better characterise this group and identify factors associated with adverse outcomes. Methods Consecutive and unrelated DCM patients undergoing genetic testing and returning no LP/P variants were retrospectively recruited and compared to two control cohorts of DCM patients carrying LP/P variants in LMNA and TTN for a primary composite endpoint of end-stage heart failure (ESHF) or malignant ventricular arrhythmia (MVA). Results Among patients without prior MVA, the composite endpoint occurred in 36/423 (8.5%) gene-elusive, 14/39 (35.9%) LMNA and 11/100 (11%) TTN cardiomyopathy patients (log-rank p<0.001 for LMNA vs gene-elusive and LMNA vs TTN; p=0.96 for TTN vs gene-elusive). For gene-elusive patients, lower left ventricular ejection fraction, larger left ventricular internal diameter in diastole, absence of LBBB and ventricular ectopy on ECG were independent predictors of the primary endpoint. Gene-elusive patients with LBBB had less atrial arrhythmia and a lower burden of ventricular ectopy at baseline and a low risk of the primary composite endpoint (HR 0.3 [0.1-0.8], p-value 0.01). Conclusions Gene-elusive DCM patients have a risk of adverse events similar to TTN cardiomyopathy. Gene-elusive patients with LBBB form a particularly low-risk subgroup, likely reflecting a distinct aetiology of left ventricular systolic dysfunction.

Background: The rare cardiovascular diseases of Brugada Syndrome, takotsubo Cardiomyopathy, and primary pulmonary arterial hypertension remain comparatively under-investigated despite their substantial morbidity and mortality. While common cardiovascular diseases have benefited from extensive genomic and therapeutic research, the molecular mechanisms underlying rarer cardiovascular conditions remain incompletely understood. This study aimed to investigate the genetic architecture and potential causal protein mediators of these rare cardiovascular diseases using integrated genomic and proteomic analyses. Methods: Genome-wide association analyses were performed within the UK Biobank cohort for Brugada syndrome, takotsubo cardiomyopathy, and pulmonary arterial hypertension. Significant loci were identified following standard quality-control procedures and annotated using publicly available genomic databases. Protein-protein interaction networks were generated using STRING to investigate known and predicted biological relationships among identified genes and to explore potential shared disease mechanisms. Proteomic Mendelian randomisation analyses were subsequently conducted using protein quantitative trait loci (pQTLs) and Generalised Summary Mendelian Randomisation (GSMR) to evaluate whether genetically predicted circulating protein levels were associated with disease risk. Results: Distinct genetic architectures were observed across phenotypes. Brugada syndrome demonstrated a concentrated association signal within the THSD7B locus alongside a variant in TRPC4. Takotsubo cardiomyopathy demonstrated associations involving ANKRD31 and PREX1, while primary pulmonary arterial hypertension identified loci involving ANO10 and SHF. Several significant variants could not be mapped to annotated genes, particularly within takotsubo cardiomyopathy, suggesting potential contributions from non-coding or regulatory genomic regions. Interaction network analyses identified biologically plausible relationships between identified loci and established cardiovascular pathways. Evaluation of circulating proteins as potential mediators of disease risk identified limited evidence for causal effects, although LPA emerged as a candidate protein associated with takotsubo cardiomyopathy and other ill-defined heart diseases. Conclusions: These findings demonstrate substantial genetic heterogeneity across Brugada syndrome, primary pulmonary arterial hypertension, and takotsubo cardiomyopathy whilst highlighting shared biological themes involving electrophysiological regulation, calcium signalling, inflammation, and tissue remodelling. The integration of genomic association analyses, interaction-network approaches, and proteomic causal inference provides additional insight into the molecular pathways underlying these three cardiovascular diseases and may help prioritise targets for future functional investigation.

Background: Chronic low-grade inflammation drives cardiovascular-kidney-metabolic (CKM) syndrome. Clonal hematopoiesis of indeterminate potential (CHIP), an age-related driver of systemic inflammation, is linked to several cardiometabolic disorders. However, whether CHIP modifies CKM progression and contributes to heterogeneity in cardiovascular disease (CVD) risk within the CKM framework remains uninvestigated. Methods: This cohort study included 307,025 UK Biobank participants at CKM stages 0-3 free of baseline CVD. CHIP status was identified via whole-exome sequencing (WES). The association between CHIP and baseline CKM severity was examined, along with the independent and joint effects of CHIP and CKM stages on incident CVD risk. The joint effects of CHIP and polygenic risk scores (PRS) were further assessed, and the incremental predictive value of incorporating CHIP into the AHA PREVENT equations was evaluated. Results: CHIP carriers were more likely to present with advanced CKM stages [OR 1.14 (1.09-1.20), P < 0.001] and exhibited higher incident CVD risk during follow-up [HR 1.13 (1.08-1.18), P < 0.001]. Significant joint effects between CHIP and CKM stages were observed, with the highest risk among CHIP carriers at CKM stage 3 [HR 1.63 (1.50-1.78), P < 0.001]. Large or multiple CHIP mutations conferred greater hazards, with distinct gene-specific effects observed. Moreover, CHIP and high genetic risk also jointly amplified CVD susceptibility. Most importantly, incorporating CHIP into AHA PREVENT significantly improved risk discrimination. Conclusions: CHIP is a significant risk factor associated with more advanced CKM stages and amplifies incident CVD risk. Integrating CHIP into existing prevention strategies may refine CVD risk stratification.

Background: Genetic testing is a Class I recommendation for patients with hypertrophic cardiomyopathy (HCM). As knowledge and frameworks continue to evolve, genetic variant classifications may change with new evidence over time. Classifications rely on evidence sought from publicly available case data, improved classification rules, and gene-disease validity. We evaluated the frequency and reasons for variant reclassification from a large multi-center international HCM registry (Sarcomeric Human Cardiomyopathy Registry; SHaRe). Methods: Participants were clinically evaluated at specialised HCM centres. Genetic variants were sought from the genetic test report, with classifications based on either the initial report, an updated report or some underwent further SHaRe adjudication. All variants were computationally reannotated and reevaluated. Variants underwent expedited curation if no new evidence was present. The remainder underwent full manual curation using accepted criteria and classified as pathogenic/likely pathogenic (P/LP), variant of uncertain significance (VUS) and benign/likely benign (B/LB). Results: Of 12,187 HCM patients, 8,054 (66%) had genetic testing between 1989-2020, and 4,923 (61%) had a variant identified in one of 29 HCM genes (1606 unique variants). Expedited curation was performed for 704 (44%) variants and 902 (56%) underwent manual curation. There were 1275 (79%) variants that retained their classification: 146 B/LB, 660 VUS, and 468 P/LP. While 276 (17%) variants (n=672 patients) were reclassified (n=276), including 73 upgrades: 61 from VUS to P/LP (199 patients), and 12 from B/LB to VUS. There were 203 downgrades: 108 from P/LP to VUS (n=196 patients), and 95 from P/LP or VUS to B/LB. VUS were additionally subclassified: 90 VUS-High, 129 VUS-Mid, 115 VUS-Low. Sub-classification of VUS resulted in less uncertainty, with 369 (40.6%) variants reclassified as VUS-Low or B/LB, indicating a very strong probability of not being HCM associated. Conclusions: Clinically meaningful reclassification occurred in 10% of variants identified in HCM probands. Most VUS were unlikely to be causal, and sub-classification has potential to reduce their burden on clinicians and families. Periodic reevaluation is essential for accurate clinical interpretation.

Background: Current clinical guidelines recommend serial ECG and echocardiographic surveillance for first-degree relatives of probands with Hypertrophic Cardiomyopathy (HCM). Objectives: To evaluate the accuracy and validity of ECG alone as a pre-screening tool for the diagnosis of HCM and to develop a random forest (RF) model for HCM phenotype prediction. Method: Pediatric relatives of primary HCM probands attending the cardiomyopathy screening program at The Hospital for Sick Children were included from 1993 to 2025. Subjects were followed until the last follow-up, censored at phenotype conversion. ECGs were classified as normal or abnormal based on predefined parameters. Associations between binary ECG variables and HCM phenotype were assessed using Phi ({varphi}) coefficient. A Random Forest classifier was developed using significant ECG variables (70:30 training: test split) and evaluated using precision, recall, specificity, negative predictive value, F1 score and AUROC. Feature importance was assessed using SHAP analysis. Variables with an impact of >5% were included in a simplified model, which was evaluated by repeating performance metrics and externally validated in a healthy cohort. Results: 350 screened relatives (44% female, mean follow-up 6.8 +\- 4.8 years) were included. At baseline, 13% (46\350) were phenotype-positive for HCM. 9 subjects converted during the surveillance. Thirteen ECG variables were significantly associated with phenotype-positive HCM and were included in the full random forest model. Four variables had >5% impact (Left ventricular hypertrophy, right ventricular hypertrophy, T-wave inversion and ST-segment depression) and were included in a simplified model, which maintained high specificity (93% vs 97%), negative predictive value (97% vs 93%) and AUROC (90% vs 96%). The simplified model classified 83% subjects as phenotype-negative, with eight being false-negative, all of whom developed an abnormal ECG in a mean of 1 year, and none had an interim adverse cardiac event. The simplified model was evaluated in an independent healthy cohort of 153 school-age subjects and correctly identified 98% as phenotype-negative with 100% NPV. Conclusion: ECG abnormalities were strongly associated with phenotype-positive status. A simplified ECG-based random forest model using four ECG variables demonstrated high specificity and negative predictive value for identifying phenotype-negative subjects. If prospectively validated, this could reduce the need for concurrent echocardiographic screening by up to 83% per encounter, lowering screening burden and cost.

Importance: Cardiac conduction disorders have traditionally been regarded as a secondary manifestation of underlying structural heart diseases. However, isolated conduction disorders may precede the onset of heart failure (HF) suggesting shared mechanisms. Objective: To evaluate the prevalence and clinical significance of pathogenic/likely pathogenic (P/LP) rare variants in cardiomyopathy genes among individuals with conduction disorders. Design, Setting, and Participants: Biobank analysis of 192,834 participants with whole genome sequence data from Vanderbilt's BioVU and 353,092 participants from the All of Us Research Program (AoU). Participants with primary conduction disorder (left bundle branch block [LBBB], right bundle branch block [RBBB], high-grade atrioventricular block [AVB]) were identified after excluding secondary causes. Exposures: P/LP variants in cardiomyopathy genes. Main Outcomes and Measures: Primary outcome was P/LP carrier status by age and HF status. Secondary outcomes included incident HF and composite ventricular arrhythmias/sudden cardiac death/mortality (VA/SCD/mortality). Results: Among 16,959 participants with conduction disorders in BioVU and 13,442 in AoU, 432 (2.6%) and 206 (1.5%) were P/LP carriers, respectively. Conduction disorder was independently associated with carrier status (BioVU p<0.001; AoU p=0.005). Carrier probability varied by age at conduction disorder onset and HF status. Among participants with HF at age 30 years, predicted carrier probability for LBBB was 7.5% in BioVU and 20.2% in AoU; for high-grade AVB, 7.7% and 8.5%, respectively, compared with 3.7% and 2.9% among those with HF without conduction disorder. P/LP carrier status among participants with conduction disorders was associated with increased risk of incident HF (BioVU p<0.001; AoU p<0.001) and ventricular arrhythmia/sudden death/mortality (BioVU p<0.001; AoU p<0.001). Carriers also demonstrated increased susceptibility to conduction disorder following HF diagnosis, including more than two-fold higher risk of third-degree AVB (BioVU aOR 2.48, 95% CI 1.85-3.32; AoU aOR 2.26, 95% CI 1.35-3.80). Conclusions: Adults with primary conduction disorders have an increased prevalence of P/LP variants in cardiomyopathy genes, which is most pronounced with diagnoses at early ages of adulthood. Furthermore, there is evidence of an interaction between P/LP carrier status and conduction disorder to increase HF risk and composite cardiovascular outcomes, underscoring the potential role of genetic evaluation in patients with primary conduction disorders to inform long-term outcomes.

Background: Neonatal-onset hypertrophic cardiomyopathy (HCM) is a rare condition with limited data regarding clinical presentation, genetic background, and long-term outcomes. We aimed to characterize the phenotype and prognosis of HCM presenting in neonates. Methods: This is a multicenter retrospective study including patients diagnosed with HCM before 1 year of age. Neonatal-onset HCM was defined as presentation {less than or equal to}28 days of life. Clinical, genetic, instrumental data, treatment, and outcomes were collected. Primary outcome included overall and cardiac survival, major arrhythmic events (MAEs), implantable cardioverter-defibrillator (ICD) implantation, and cardiac surgery. Results: Among 321 pediatric HCM, 21% were diagnosed during infancy and 75% were neonates. Median age at diagnosis was 1 day (IQR 0-6), 82% presented within the first week of life. Prenatal suspicion was in 25%. At presentation, 41% were symptomatic. RASopathies represented the most common etiology (41%), followed by gene-elusive (31%), mitochondrial/inborn errors of metabolism (18%), and sarcomeric (8%). Left ventricular outflow tract obstruction was frequent in sarcomeric and RASopathy. Overall survival was 92% and cardiac survival was 96% at 2 years; long-term survival was 88% at 30 years. ICDs were implanted in 8%; 21% required cardiac surgery. Survival free from ICD was 40% at 15 year and 47% from myectomy. All events occurred in patients presenting within the first weeks of life. Conclusions: Neonatal-onset HCM is characterized by etiologic heterogeneity, predominance of syndromic and non-sarcomeric etiologies, and long-term cardiovascular morbidity. Presentation within the first days of life identifies a high-risk subgroup requiring intensive surveillance and specialized multidisciplinary management.

Background: Previous studies of genotype-phenotype correlations in hypertrophic cardiomyopathy (HCM) have presented inconsistent conclusions, potentially reflecting small studies and non-uniform phenotyping. Objectives: We aimed to identify genotype-phenotype correlations in sarcomeric variant-positive HCM cardiac magnetic resonance (CMR) imaging and adverse outcome data in the National Heart, Lung, and Blood Institute (NHLBI) HCM Registry. Methods: Of 2750 overall patients, 915 sarcomeric variant-positive ones were subgrouped by genotype. CMR measures of left ventricular (LV) hypertrophy, fibrosis and function, and adverse events, were compared. Findings were meta-analyzed with prior studies from systematic review. Results: Patients with pathogenic variants in thick-filament genes had greater hypertrophy than those in thin-filament genes - maximal LV wall thickness (maxLVWT) (21.7 {+/-} 5.0 vs. 20.0 {+/-} 4.4mm, P<0.01) and indexed LV mass (81.9 {+/-} 26.0 vs. 71.7 {+/-} 13.3g/m2, P<0.001). Of the former, MYBPC3 carriers had greater maxLVWT than MYH7 carriers (22.2 {+/-} 5.2 vs. 20.9 {+/-} 4.5mm, P<0.01) but lower LV ejection fraction (63.1 {+/-} 8.4 vs. 65.3 {+/-} 8.4%, P<0.001). Findings remained significant after covariate adjustment and meta-analysis. 23 (~1%) patients had >1 disease-linked variants with only 3 (~0.11%) carrying >1 pathogenic variants. MYBPC3 carriers had lower risk of a multiple event composite than MYH7 carriers. Conclusions: In the largest CMR-based study to date, we identified significant phenotypic differences that characterize disease-gene subgroups and resolved prior discrepancies through systematic review and meta-analysis. However, carriage of >1 sarcomeric variants did not contribute much to variation in phenotypic severity in the general HCM population due to its rarity.

Genetic testing for cardiomyopathy and arrhythmia (CM/ARRH) provides diagnostic information and informs screening for at-risk relatives. Clinical guidelines recommend genetic testing for these conditions; however, data on how genetic test results influence clinical management recommendations are limited. Here, we determined the frequency of cardiologist-recommended management changes for patients following CM/ARRH genetic testing. This was a retrospective cross-sectional study of patients referred for multigene panel testing between April 2016 and April 2024. Genetically-experienced cardiologists at multicenter academic clinical practices were recruited for participation to complete surveys indicating clinical decision making on patients who had genetic testing. Cases for review were randomly selected to have both positive and non-positive results. Among 249 patients (138 positive, 111 non-positive), 136 (54.6%) received clinical management recommendations for their own or their at-risk relatives? care. Of these, 75 (55.1%) received recommendations for the patient?s own care, most frequently additional diagnostic tests/procedures (n=33). Compared to non-positive results, patients with positive results were more likely to receive recommendations for their own management (66/138, 47.8% vs 9/111, 8.1%; P<0.00001). Patients with positive results in arrhythmogenic cardiomyopathy genes had 263% higher odds of recommended management changes compared to those with TTN (OR=3.63, CI:1.40-9.84, P=0.009). The results from CM/ARRH genetic testing on affected patients influenced cardiologists? medical decision making and management recommendations. Additional research is needed to evaluate how genetic testing for CM/ARRH impact health outcomes.

Background: Non-monogenic arteriopathies are often classified as distinct entities according to the arterial territory involved, yet they share clinical features and may co-occur in the same individual. This pattern suggests shared susceptibility across anatomically distinct arteriopathies, potentially driven by common biological and genetic mechanisms. Methods: We investigated the shared genetic architecture of five arteriopathies (cervical artery dissection (CeAD), intracranial aneurysm (IA), spontaneous coronary artery dissection (SCAD), aortic aneurysm and dissection (AAD), and fibromuscular dysplasia (FMD)) using LD score regression, Association analysis based on SubSETs (ASSET), pairwise Multi-Trait Analysis of Genome-wide association summary statistics (MTAG), pleiotropy mapping and Mendelian randomization (MR) to identify shared loci and prioritise candidate causal genes. Results: LD score regression identified significant positive genetic correlations between CeAD-SCAD (rg = 0.64), IA-AAD (rg = 0.33), IA-SCAD (rg = 0.37), CeAD-AAD (rg = 0.56) and SCAD-AAD (rg = 0.20). ASSET identified 37 shared independent loci, and in MTAG analyses, one novel locus was identified for CeAD and SCAD (SLC39A8) and one for IA (FGF5). 13 loci showed strong cross-trait colocalization, including PHACTR1, LRP1, and CDKN2B-AS1. Using the Genotype-Phenotype Map, we found that arteriopathy-associated variants colocalized with blood pressure- and migraine-related traits, while many showed effect directions opposite to those observed for coronary artery disease. Proteome-wide MR identified 67 circulating proteins associated with at least one trait, including ECM1 and SHISA5 for CeAD and FGF5 for IA, with 17 supported by colocalization. Transcriptome-wide MR identified 204 colocalized tissue?specific signals, of which, 14 were shared across multiple traits. Enrichment analyses implicated pathways related to vascular development, smooth muscle cell function, extracellular matrix organization, and TGF-? signaling. Conclusions: These findings support shared genetic architecture across anatomically distinct arteriopathies, implicating pathways involved in vascular structure and prioritising therapeutic targets for future mechanistic investigation.

Aortic stenosis (AS) is a heterogeneous disease of aging characterized by valvular calcification and distinct structural, electrical, and hemodynamic remodeling that are incompletely captured by any single diagnostic measure. Here we show that three AI-derived digital biomarkers resolve AS-related remodeling into complementary structural (cine-CMR Digital AS Severity Index, DASSi), electrical (AI-ECG), and hemodynamic (phase-contrast CMR peak aortic velocity) axes. Among 68,714 UK Biobank participants, all three biomarkers were independently associated with prevalent AS and prospectively predicted aortic valve replacement. Genetic and transcriptomic analyses of the digital phenotypes revealed partially distinct, heritable architectures: peak aortic velocity aligned closely with clinical AS genetics, whereas DASSi and AI-ECG defined a shared myocardial-remodeling axis largely independent of clinical AS susceptibility. These findings support AS as a multidimensional remodeling syndrome and establish a novel digital phenotyping framework for dissecting complex cardiovascular disease into complementary, biologically informative axes.