Figueiral, Marta

ABSTRACT Pathogenic variants in AMMECR1 have been associated with a rare multisystem disorder characterized by midface hypoplasia, hearing impairment, elliptocytosis, and nephrocalcinosis (MFHIEN). To date, most reported cases involve copy number variants or presumed loss‐of‐function alterations, with only a single prior report describing a missense variant supported by functional studies. Here, we report a patient with a heterozygous de novo AMMECR1 missense variant, NM_015365.3:c.649G>A p.(Val217Met) presenting with clinical features consistent with MFHIEN, including midface hypoplasia, partial hearing impairment, nephrocalcinosis, and elliptocytosis identified on peripheral blood smear. Comparative review of the literature highlights that while previously reported missense variants in AMMECR1 demonstrated altered intranuclear protein distribution and reduced expression in functional assays, clinical evidence supporting pathogenicity of non‐truncating variants remains limited. The phenotypic overlap between our patient and prior report strengthens the association between missense variations and the MFHIEN phenotype. Our findings support the pathogenic relevance of missense variation in AMMECR1 and emphasize the importance of integrating detailed phenotyping, including hematologic evaluation, with genomic data in the diagnosis of rare multisystem disorders. Additional cases and functional studies are needed to clarify genotype–phenotype correlations and underlying disease mechanisms.

Abstract Pathogenic variants in cardiomyopathy genes confer substantial disease risk, yet clinical penetrance varies widely. The population-level prevalence, age-specific penetrance, and the extent to which polygenic susceptibility modifies disease risk across diverse ancestries remain poorly defined. This population-based cohort study leveraged genome sequencing and linked electronic health record data from the All of Us Research Program (n=414,830). This study found that P/LP variants in cardiomyopathy-associated genes were present in 0.91% of participants (95% CI, 0.88%–0.94%), with similar prevalence across ancestry groups. Compared with non-carriers, variant carriers had significantly higher odds of all-cause heart failure (ACHF, OR, 2.58; 95% CI, 2.31–2.89), non-ischemic heart failure (NIHF, OR, 2.74; 95% CI, 2.42–3.10), and non-ischemic cardiomyopathy (NICM, OR, 4.99; 95% CI, 4.44–5.63). Among carriers, by age 50 years, 24.5% (95% CI, 14.5%–33.4%) developed ACHF, 17.2% (95% CI, 8.8%–24.8%) developed NIHF, and 30.1% (95% CI, 19.5%–40.2%) developed NICM. Higher polygenic risk for heart failure was independently associated with increased risk of ACHF (OR, 1.81; 95% CI, 1.74–1.89), NIHF (OR, 1.66; 95% CI, 1.58–1.75), and NICM (OR, 1.69; 95% CI, 1.59–1.80). Among carriers with elevated polygenic risk, odds of disease were substantially higher than among non-carriers at average polygenic risk (ACHF: OR, 4.71; 95% CI, 4.17–5.32; NIHF: OR, 4.56; 95% CI, 3.99–5.22; NICM: OR, 8.51; 95% CI, 7.44–9.73). Results showed that P/LP variants in cardiomyopathy genes were relatively common in this large, ancestrally diverse cohort, and conferred increased risk of cardiomyopathy and HF, with incomplete but clinically meaningful penetrance. Polygenic risk for HF independently and additively increased disease risk across ancestries. Integrating both may improve risk stratification and enable more precise, equitable care.

Abstract Background Common genetic variation has been linked to an increased risk of developing dilated cardiomyopathy (DCM) in case-control studies. However, the phenotypic profile and biological mechanisms by which genetic background may predispose individuals to DCM and outcomes in the general population remain unclear. Aim The primary objectives of this study were twofold: (1) to validate a DCM polygenic score (PRS-1) based on a prior meta-analysis of case–control genetic association studies [Tadros R et al. Nat Genet (2021)]; and (2) To apply this PRS, along with two recently developed PRSs for DCM [PRS-2 from Zheng SL et al. Nat Genet (2024) and PRS-3 from Jurgens SJ et al. Nat Genet (2024)] to a general population that underwent comprehensive longitudinal phenotypic assessments and had long-term outcomes available. Methods While the PRS-1 was derived from only 13 SNPs, PRS-2 and PRS-3 were generated from 709,534 and 1,072,247 SNPs, respectively with significant overlap between them. These DCM-PRSs were applied to an unselected community-based cohort (n=1897) aged >45 years, who underwent a physical examination, echocardiogram, and blood sample at baseline. Subsequent clinical outcomes were collected over a median 16 year follow-up (IQR: 15-17). Results No significant differences between the quartiles were present in terms of age, sex (48% male), and cardiovascular risk factors (CV-RF) (such as hypertension, diabetes, and coronary artery disease). However, linear regression models demonstrated a significant correlation between all DCM-PRSs and left ventricular (LV) parameters, including LV ejection fraction, LV end-systolic diameter, and LV end-diastolic diameter (Table). Multivariable regression analysis confirmed that these correlations were independent of age, sex, CV-RF, and population stratification (adjusted for the first 10 principal components [PCs]). During follow-up, 47 individuals developed DCM. A logistic regression analysis, using a 3:1 matched cohort of non-DCM vs. DCM individuals based on age and sex and adjusted for the same 10 PCs, found a significant correlation between DCM development and both PRS-1 [OR=2.27 (1.06–4.85), p=0.03] and PRS-3 [OR=2.63 (1.20–5.75), p=0.02], while PRS-2 did not show a significant association [OR=1.85 (0.84–4.06), p=0.12]. No association was found between the DCM-PRSs and heart failure (HF) biomarkers (aldosterone, natriuretic peptides, ST2, Galectin-3) or HF outcomes (all-cause mortality/HF hospitalization). Conclusion PRS-1 for DCM despite being derived from only 13 risk alleles, performs at least as well as the newer and more extensive PRSs, in its correlation with LV function, dimensions, and DCM development (except for PRS-2) in a general population. The absence of correlation between these DCM-PRSs and the renin-angiotensin-aldosterone system or natriuretic peptides suggests that genetic background influences LV traits through mechanisms independent of these biological pathways.

ABSTRACTPlatelets are small, anucleate particles derived from bone marrow megakaryocytes that circulate in the blood and are central to hemostasis, atherothrombosis, and post‐angioplasty coronary restenosis. Initially thought to involve a simple process of platelet adhesion, activation, and aggregation, recent insights reveal an important interplay with genetics and other organ systems, especially in the setting of antiplatelet drug therapy. Interaction involving the hepatic cytochrome P450 enzymes, which regulate drug metabolism, and genetic variation in those enzymes affecting drug response, underscores the liver's role in modulating platelet function by attenuating circulating active drug metabolites with eventual cardiovascular implications. Circulating adhesive proteins such as von Willebrand Factor and fibronectin also significantly regulate platelet aggregation, a process that is further influenced by varying shear conditions within the vascular system. The efficacy of antiplatelet therapies can be attenuated by such individual genetic variation, which can affect multiple cellular pathways involved not only in drug metabolism and clearance but also the drug target itself. Identifying these genetic differences allows for tailored therapy, enhancing treatment outcomes and minimizing adverse effects. Genetic variation, particularly in the CYP2C19 gene, influences individual responses to the most commonly used antiplatelet drug other than aspirin, clopidogrel, with certain variants leading to reduced drug metabolism and antiplatelet effects. Therefore, genotype‐guided antiplatelet therapy has emerged as a promising approach to reduce ischemic events and minimize bleeding events. This personalized strategy requires an understanding of genetic variation, drug‐gene interaction, and the liver's role in impacting platelet function, the coagulation system, and cardiovascular systems.

ABSTRACT Aims Common genetic variants have been linked to an increased risk of non-ischaemic cardiomyopathy (NICM). The primary objective of this study was to evaluate the significance of these variants in a general population. Methods and results Thirteen NICM risk alleles, previously validated by meta-analyses of case-control genetic association studies, were used to determine genetic risk (GR) in a large, unselected cohort (n = 1897) of Olmsted County residents aged >45 years. Clinical and echocardiographic data, with biomarkers, were correlated with this NICM-GR over a median of 16 years of follow-up (interquartile range [IQR] 15–17). There were no significant differences between the study population quartiles, based on NICM-GR, in terms of age (median 61.6 [IQR 53.6–70.4]), sex (48% male), and cardiovascular risk factors. A significant correlation was detected by specific linear-regression models between NICM-GR and left ventricular (LV) ejection-fraction (beta [standard error]: −2.68 [0.68], p < 0.001), LV end-systolic-diameter (0.22 [0.06], p < 0.001), and LV end-diastolic-diameter (0.14 [0.06], p = 0.01). During follow-up, 46 subjects developed NICM. Using a 3:1 matched-cohort of non-NICM versus NICM patients, linear-regression analysis found a significant correlation between NICM-GR and NICM development (odds ratio 2.27, 95% confidence interval 1.06–4.85, p = 0.03). There was no significant association between these variants and heart failure biomarkers (aldosterone, natriuretic peptides, ST2, galectin-3). Conclusions The NICM-GR correlates with LV function and dimension, and subsequent development of NICM in the general population. The lack of correlation of these variants with cardiovascular risk factors and the renin–angiotensin–aldosterone axis or natriuretic peptides suggest different biological mechanisms involved. These findings support the need to explore newer pathophysiologic pathways in the development of NICM.

Background: Cardiomyopathies (CM) are a leading cause of heart failure. Identification of genetic risk preemptively may allow detection of the earliest phenotypic manifestations through implementation of interval-based cardiac screening. Previous population-based genetic screening studies have limited follow-up and inadequate phenotyping. Hypothesis: Disease penetrance of CM variants is significantly higher than previously reported. Aims: To determine the prevalence, penetrance, and disease expression of incidental CM-related genetic variants in an unselected, richly phenotyped, adult population. Methods: We analyzed a random sample of 10,000 patients from a quaternary medical center-based biobank cohort for reportable variants in 22-cardiomyopathy genes. Prioritization of genetic variants was performed using Semi-Automated Variant Interpretation, a novel software that has been previously developed and validated at our center. Prioritized variants were then manually curated by 2 independent variant interpretation specialists. Clinical phenotypes and outcomes of participants with likely pathogenic/pathogenic (LP/P) variants were determined. Results: LP/P cardiomyopathy variants were present in 1% of our cohort (n=104) within the following genes: TNNT2 (n=1), DES (n=2), LMNA (n=2), MYL2 (n=2), TNNI3 (n=2), DSG (n=4), FLNC (n=4), DSC2 (n=6), SCN5A (n=7), PKP2 (n=10), DSP (n=12), MYH7 (n=14), TTN (n=17), MYBPC3 (n=21). Only 1 participant carried two different LP/P variants. A definitive disease penetrance defined as heart failure or cardiomyopathy was found in 34% of genotype positive (G+) individuals. Possible disease penetrance defined as presence of structural heart disease identified by echocardiography was found in an additional 16% of participants (concentric left ventricular hypertrophy, diastolic dysfunction, biatrial and left atrial enlargement). Combined definitive and possible disease penetrance was found in 50% of G+ individuals. Arrhythmias and/or cardiac conduction disease (atrial fibrillation, atrioventricular block, ventricular arrhythmia) were present in 31% of G+ individuals. Conclusion: Cardiomyopathy associated LP/P variants are present in a small subset of a large quaternary medical center population as previously reported but unlike prior studies, disease penetrance manifesting as cardiac structural abnormalities and heart failure is high in G+ individuals.

Background: Patients with normal resting left ventricular ejection fraction (LVEF) without either coronary artery disease (CAD) or a hypertensive response can paradoxically develop reduced LVEF during exercise stress echocardiography (ESE). The clinical phenotype and outcomes of these patients is unknown. Hypothesis: Patients who paradoxically develop reduced LVEF during exercise may represent a sub-phenotype of heart failure with preserved LVEF (HFpEF). Aims: To describe the baseline characteristics and clinical outcomes of this unique patient population. Methods: Among all ESE performed between January 2003 and December 2022, patients without a hypertensive response to exercise and without CAD by angiogram within 90 days of ESE, who had a resting LVEF ≥50% with a ≥5% LVEF decrease during ESE were identified. All-cause mortality, HF hospitalization, and atrial fibrillation (AF) outcomes were assessed. Kaplan-Meier and Cox regression methods were used to analyze time-to-event outcomes. Results: Among 213,643 stress echocardiograms performed, 134 patients met eligibility criteria (Table 1). The mean age of the population was 66±10 years, 76% were women, and 16% had AF at baseline. Mean LVEF was 58±4% at rest and 43±4% at peak stress. Stress electrocardiogram met criteria for ischemia in 14%. The 10-year all-cause mortality risk was 12.9% (95% CI 5.5-20.3) with 10 (37%) of 27 deaths due to cancer (Figure 1, Panel A). The 10-year estimated risk of HF hospitalization was 17.6% (95% CI 9.0-26.2) (Figure 1, Panel B). Among 112 patients without AF at baseline, the 10-year risk of developing AF was 23.4% (95% CI 13.4-33.4). Conclusions: Patients with exercise-induced reduced LVEF in the absence of obstructive CAD have a high incidence of HF hospitalizations and AF. Given the preponderance of women, risk for AF, HF hospitalizations, and cancer-related deaths, the possibility that this condition is an early sub-phenotype of HFpEF should be investigated.

Background: Electrocardiography-based artificial intelligence (AI-ECG) validated models that detect cardiac disease are increasingly being applied in clinical practice. The utility of such tools to detect insidious cardiac disease in patients with normal baseline left ventricular ejection fraction (LVEF) who paradoxically develop reduced LVEF during exercise stress echocardiography (ESE), and do not have coronary artery disease (CAD) or hypertension, is unknown. Hypothesis: AI-ECG is useful to diagnose insidious cardiac disease and predict clinical outcomes in patients with exercise-induced cardiomyopathy. Aims: To assess the utility of AI ECG in patients with exercise-induced cardiomyopathy. Methods: Among all ESE performed between January 2003 and December 2022, patients without a hypertensive response to exercise and without CAD (confirmed by coronary angiography within 90 days after ESE), with resting LVEF ≥50% and a paradoxical ≥5% LVEF decrease during ESE were identified. A previously validated AI-ECG algorithm that predicts atrial fibrillation (AF), reduced LVEF, and cardiac amyloidosis (CA) was applied to the baseline ECG closest to the time of ESE. The predicted probability of AF, reduced LVEF, and CA if above the published thresholds, was determined. Results: There were 134 patients with exercise-induced cardiomyopathy who were identified. The mean age of this cohort was 66±10 years, 76% were women and 16% had AF at baseline. Mean LVEF was 58±4% at rest and 43±4% at peak stress. The median follow-up period was 6.8 years (IQR 3.0-12.2). Among patients without a baseline history of AF (n=112), AI-ECG identified 29% with a significant probability of AF, which was associated with a subsequent AF diagnosis at univariable analysis (HR 2.505, 95%CI 1.016-6.177, p=0.046). There were 10 patients with an AI-ECG prediction of reduced LVEF among whom 3 were subsequently hospitalized with HF. AI-ECG was positive for CA in 8 and 3 amongst these had subsequent HF hospitalizations (Table). Conclusions: Baseline AI-ECG may help predict subsequent AF and diagnose preclinical amyloid cardiomyopathy in patients who by resting echocardiography do not seem to have cardiac disease but with exercise develop reduced LVEF.

Introduction: Common genetic variation has been linked to an increased risk of developing dilated cardiomyopathy (DCM). However, the phenotypic profile, outcomes, and biological mechanisms by which such genetic background may predispose individuals to DCM are still unknown. Hypothesis: The primary objectives of this study were to develop a DCM polygenic risk score (PRS) based on prior case control-DCM GWAS and to apply this PRS to a well clinical characterized general population. Methods: The DCM-PRS was derived from 13 DCM risk alleles that were assayed in an unselected cohort (n=1897) of unrelated Olmsted County residents age >45 years who did not have a history of heart failure (HF) or CM and underwent physical examination, echocardiography, and blood analyses. Results: The entire population was equally divided into quartiles based on the DCM-PRS. No significant differences were present in terms of age (median 62 years) and sex (48% male). However, a significant correlation was detected between the DCM-PRS and left ventricle ejection fraction (LVEF) (Beta: -2.68, p<0.001), LV end-systolic diameter (Beta: 0.22, p<0.001), and LV end-diastolic diameter (Beta: 0.14, p=0.01). During a follow-up of 16 years (IQR: 15-17), 47 subjects developed DCM. Using a 3:1 non-DCM vs DCM matched cohort, a logistic regression analysis, found a significant correlation between median DCM-PRS and DCM development [OR=2.27 (1.06, 4.85), p=0.03]. However, there was no association between the DCM-PRS and HF biomarkers (aldosterone, natriuretic peptides, ST2, Galectin-3). Conclusions: DCM-PRS correlates with decreased LVEF, increased LV dimensions, and DCM development in a general population without significant differences in baseline clinical features. The absence of correlation between the DCM-PRS and available HF biomarkers suggests that this genetic background affects LV traits and DCM development independent of these biological mechanisms.