Asatryan, Babken

Despite advances in cardiovascular care and improved outcomes, fragmented healthcare systems, nonequitable access to health care, and nonuniform and unbiased collection and access to healthcare data have exacerbated disparities in healthcare provision and further delayed the technological-enabled implementation of precision medicine. Precision medicine relies on a foundation of accurate and valid omics and phenomics that can be harnessed at scale from electronic health records. Big data approaches in noncardiovascular healthcare domains have helped improve efficiency and expedite the development of novel therapeutics; therefore, applying such an approach to cardiovascular precision medicine is an opportunity to further advance the field. Several endeavors, including the American Heart Association Precision Medicine platform and public-private partnerships (such as BigData@Heart in Europe), as well as cloud-based platforms, such as Terra used for the National Institutes of Health All of Us, are attempting to temporally and ontologically harmonize data. This state-of-the-art review summarizes best practices used in cardiovascular genomic and precision medicine and provides recommendations for systems’ requirements that could enhance and accelerate the integration of these platforms.

Background: Mitral valve prolapse (MVP) is a common valvular abnormality. Observational studies demonstrate an association between MVP and increased risk of sudden cardiac death from ventricular arrhythmias, coined arrhythmogenic MVP. A genetic component has been postulated but remains under-investigated. Hypothesis: Predicted deleterious variants in Mendelian cardiomyopathy and arrhythmia genes are more frequent in arrhythmogenic MVP (aMVP) compared to non-arrhythmogenic MVP. Aims: To comprehensively phenotype and genotype a single-center aMVP cohort and compare to non-aMVP from two large population-based cohorts and investigate their clinical outcomes. Methods: The aMVP cohort included 46 prospectively enrolled patients from a regional referral center for inherited cardiovascular disease and had undergone multi-modality imaging and clinical gene panel testing. The non-aMVP comparator cohorts included 453 participants from the UK Biobank (UKBB), a prospective cohort of 500,000 UK residents, and 1,418 participants from the National Institutes of Health (NIH) All of Us (AoU), a prospective cohort of 450,000 USA participants. Gene variants were annotated in ANNOVAR. Participants with and without pathogenic/likely pathogenic (P/LP) variants reported on ClinVar with ≥2-star level of evidence were considered genotype positive (G+) and negative (G-) respectively. Results: The demographics for aMVP (age 61.2 ± 12.8 years, 56.5% female) and non-aMVP (UKBB: age 59.8 ± 7.3 years, 50.7% female and AoU: age 65.3 ± 13.4 years, 76.2% female) were comparable. G+ participants were more prevalent in the aMVP cohort 10/46 (21.7%) versus non-aMVP in the UKBB 8/453 (1.8%) and in the AoU 21/1418 (1.5%); p<0.001. The most frequently implicated gene in aMVP was TTN . Of 46 in aMVP cohort, 33 (71%) underwent CMR. G+ participants had a higher frequency of late gadolinium enhancement [6/6 (100%) vs. 14/27 (51.8%), p<0.001] and wall motion abnormalities [3/6 (50%) vs. 1/27 (3.7%), p<0.001] compared to G- participants. The aMVP cohort had significantly more implantable cardioverter defibrillator (ICD) implants compared to non-aMVP cohort [5/46 (10.9%) vs. 1/453 in UKBB (0.2%), p<0.001]. G+ aMVP cohort showed a trend for developing heart failure and ICD implants compared to G- aMVP . Conclusion: P/LP variants in cardiomyopathy and arrhythmia genes are more prevalent in aMVP participants compared to non-aMVP participants. This could be a hitherto unrecognized effect modifier predicting aMVP .

Precision medicine, which among other aspects includes an individual's genomic data in diagnosis and management, has become the standard‐of‐care for Mendelian cardiovascular disease (CVD). However, early identification and management of asymptomatic patients with potentially lethal and manageable Mendelian CVD through screening, which is the promise of precision health, remains an unsolved challenge. The reduced costs of genomic sequencing have enabled the creation of biobanks containing in‐depth genetic and health information, which have facilitated the understanding of genetic variation, penetrance, and expressivity, moving us closer to the genotype‐first screening of asymptomatic individuals for Mendelian CVD. This approach could transform health care by diagnostic refinement and facilitating prevention or therapeutic interventions. Yet, potential benefits must be weighed against the potential risks, which include evolving variant pathogenicity assertion or identification of variants with low disease penetrance; costly, stressful, and inappropriate diagnostic evaluations; negative psychological impact; disqualification for employment or of competitive sports; and denial of insurance. Furthermore, the natural history of Mendelian CVD is often unpredictable, making identification of those who will benefit from preventive measures a priority. Currently, there is insufficient evidence that population‐based genetic screening for Mendelian CVD can reduce adverse outcomes at a reasonable cost to an extent that outweighs the harms of true‐positive and false‐positive results. Besides technical, clinical, and financial burdens, ethical and legal aspects pose unprecedented challenges. This review highlights key developments in the field of genotype‐first approaches to Mendelian CVD and summarizes challenges with potential solutions that can pave the way for implementing this approach for clinical care.

Background Marfan syndrome (MFS) is an autosomal dominant connective tissue disorder affecting multiple systems, particularly the cardiovascular system. The leading causes of death in MFS are aortopathies and valvular disease. We wanted to identify the frequency of arrhythmia and postural orthostatic tachycardia syndrome, length of hospital stay, health care–associated costs (HAC), and in‐hospital mortality in patients with MFS. Methods and Results The National Inpatient Sample database from 2005 to 2014 was queried using International Classification of Diseases, Ninth Revision, Clinical Modification ( ICD‐9‐CM ) codes for MFS and arrhythmias. Patients were classified into subgroups: supraventricular tachycardia, ventricular tachycardia (VT), atrial fibrillation, atrial flutter, and without any type of arrhythmia. Data about length of stay, HAC, and in‐hospital mortality were also abstracted from National Inpatient Sample database. Adjusted HAC was calculated as multiplying HAC and cost‐to‐charge ratio; 12 079 MFS hospitalizations were identified; 1893 patients (15.7%) had an arrhythmia; and 4.9% of the patients had postural orthostatic tachycardia syndrome. Median values of length of stay and adjusted HAC in VT group were the highest among the groups (VT: 6 days, $18 975.8; supraventricular tachycardia: 4 days, $11 906.6; atrial flutter: 4 days, $11 274.5; atrial fibrillation: 5 days, $10431.4; without any type of arrhythmia: 4 days, $8336.6; both P =0.0001). VT group had highest in‐patient mortality (VT: 5.3%, atrial fibrillation: 4.1%, without any type of arrhythmia: 2.1%, atrial flutter: 1.7%, supraventricular tachycardia: 0%; P <0.0001) even after adjustment for potential confounders (without any type of arrhythmia versus VT; odds ratio [95% CI]: 3.18 [1.62–6.24], P =0.001). Conclusions Arrhythmias and postural orthostatic tachycardia syndrome in MFS were high and associated with increased length of stay, HAC, and in‐hospital mortality especially in patients with VT.

Background: There is a paucity of data regarding the phenotype of dilated cardiomyopathy (DCM) gene variants in the general population. We aimed to determine the frequency and penetrance of DCM-associated putative pathogenic gene variants in a general adult population, with a focus on the expression of clinical and subclinical phenotype, including structural, functional, and arrhythmic disease features. Methods: UK Biobank participants who had undergone whole exome sequencing, ECG, and cardiovascular magnetic resonance imaging were selected for study. Three variant-calling strategies (1 primary and 2 secondary) were used to identify participants with putative pathogenic variants in 44 DCM genes. The observed phenotype was graded DCM (clinical or cardiovascular magnetic resonance diagnosis); early DCM features, including arrhythmia or conduction disease, isolated ventricular dilation, and hypokinetic nondilated cardiomyopathy; or phenotype-negative. Results: Among 18 665 individuals included in the study, 1463 (7.8%) possessed ≥1 putative pathogenic variant in 44 DCM genes by the main variant calling strategy. A clinical diagnosis of DCM was present in 0.34% and early DCM features in 5.7% of individuals with putative pathogenic variants. ECG and cardiovascular magnetic resonance analysis revealed evidence of subclinical DCM in an additional 1.6% and early DCM features in an additional 15.9% of individuals with putative pathogenic variants. Arrhythmias or conduction disease (15.2%) were the most common early DCM features, followed by hypokinetic nondilated cardiomyopathy (4%). The combined clinical/subclinical penetrance was ≤30% with all 3 variant filtering strategies. Clinical DCM was slightly more prevalent among participants with putative pathogenic variants in definitive/strong evidence genes as compared with those with variants in moderate/limited evidence genes. Conclusions: In the UK Biobank, ≈1 of 6 of adults with putative pathogenic variants in DCM genes exhibited early DCM features potentially associated with DCM genotype, most commonly manifesting with arrhythmias in the absence of substantial ventricular dilation or dysfunction.

Arrhythmogenic cardiomyopathy (ACM) is a primary disease of the myocardium, predominantly caused by genetic defects in proteins of the cardiac intercalated disc, particularly, desmosomes. Transmission is mostly autosomal dominant with incomplete penetrance. ACM also has wide phenotype variability, ranging from premature ventricular contractions to sudden cardiac death and heart failure. Among other drivers and modulators of phenotype, inflammation in response to viral infection and immune triggers have been postulated to be an aggravator of cardiac myocyte damage and necrosis. This theory is supported by multiple pieces of evidence, including the presence of inflammatory infiltrates in more than two-thirds of ACM hearts, detection of different cardiotropic viruses in sporadic cases of ACM, the fact that patients with ACM often fulfill the histological criteria of active myocarditis, and the abundance of anti–desmoglein-2, antiheart, and anti-intercalated disk autoantibodies in patients with arrhythmogenic right ventricular cardiomyopathy. In keeping with the frequent familial occurrence of ACM, it has been proposed that, in addition to genetic predisposition to progressive myocardial damage, a heritable susceptibility to viral infections and immune reactions may explain familial clustering of ACM. Moreover, considerable in vitro and in vivo evidence implicates activated inflammatory signaling in ACM. Although the role of inflammation/immune response in ACM is not entirely clear, inflammation as a driver of phenotype and a potential target for mechanism-based therapy warrants further research. This review discusses the present evidence supporting the role of inflammatory and immune responses in ACM pathogenesis and proposes opportunities for translational and clinical investigation.

Arrhythmogenic cardiomyopathy (ACM) is an inherited cardiomyopathy characterised by ventricular arrhythmia and an increased risk of sudden cardiac death (SCD). Numerous genetic determinants and phenotypic manifestations have been discovered in ACM, posing a significant clinical challenge. Further to this, wider evaluation of family members has revealed incomplete penetrance and variable expressivity in ACM, suggesting a complex genotype-phenotype relationship. This review details the genetic basis of ACM with specific genotype-phenotype associations, providing the reader with a nuanced perspective of this condition; whilst also proposing a future roadmap to delivering precision medicine-based management in ACM.