Sudden Cardiac Death-A New Insight Into Potentially Fatal Genetic Markers

Research participant perceptions of personal utility in disclosure of individual research results from genomic analysis

This article elaborates research participant perspectives on the communication of individual research results from genomic analyses. While most analyses focus on how to communicate results from the perspectives of clinicians or researchers, there is insufficient data on user perspectives and how this information may be used, valued, and interpreted by patients and their families. The concept of personal utility, which considers factors related to quality of life, including on how information may impact the person's future decisions, has been shown to be particularly relevant to understand research participant perspectives and to move beyond clinical and analytic utility factors such as mortality and morbidity. This article draws from qualitative research of research participants awaiting genomic results in the case of sudden cardiac death. Our results show perspectives of personal utility in communication of genomic results, including cognitive, behavioral, and affective outcomes. Cognitive outcomes include gain of information, improved knowledge of etiology and inheritance characteristics, and curiosity for what might be found. Behavioral outcomes include being able to plan life decisions, while affective outcomes include various coping strategies used. We will also discuss the value of knowing negative results and incidental findings from the research participant's perspective. This contribution gives suggestions on best practices to guide genome analysis returns, including incorporating participant wishes on individualized communication at the consent stage; developing relational autonomy approaches; and engaging them throughout the research trajectory.

Implementing Whole Genome Sequencing (WGS) in Clinical Practice: Advantages, Challenges, and Future Perspectives

The integration of whole genome sequencing (WGS) into all aspects of modern medicine represents the next step in the evolution of healthcare. Using this technology, scientists and physicians can observe the entire human genome comprehensively, generating a plethora of new sequencing data. Modern computational analysis entails advanced algorithms for variant detection, as well as complex models for classification. Data science and machine learning play a crucial role in the processing and interpretation of results, using enormous databases and statistics to discover new and support current genotype-phenotype correlations. In clinical practice, this technology has greatly enabled the development of personalized medicine, approaching each patient individually and in accordance with their genetic and biochemical profile. The most propulsive areas include rare disease genomics, oncogenomics, pharmacogenomics, neonatal screening, and infectious disease genomics. Another crucial application of WGS lies in the field of multi-omics, working towards the complete integration of human biomolecular data. Further technological development of sequencing technologies has led to the birth of third and fourth-generation sequencing, which include long-read sequencing, single-cell genomics, and nanopore sequencing. These technologies, alongside their continued implementation into medical research and practice, show great promise for the future of the field of medicine.

Case report: State-of-the-art risk-modifying treatment of sudden cardiac death in an asymptomatic patient with a mutation in the SCN5A gene and a review of the literature

Brugada syndrome is a rare hereditary disorder characterized by distinct ECG findings, complex genetics, and a high risk of sudden cardiac death. Recognition of the syndrome is crucial as it represents a paradigm of sudden death tragedy in individuals at the peak of their lives. Notably, Brugada syndrome accounts for more than 20% of sudden cardiac deaths in individuals with structurally normal hearts. Although this syndrome follows an autosomal dominant inheritance pattern, it is more prevalent and severe in males. Diagnosis is primarily based on the characteristic ECG pattern observed in the right precordial leads. Mutations in the SCN5A gene, resulting in loss of function, are the most common genetic cause. We presented a 36-year-old proband with a family history of sudden cardiac death. Although the patient was asymptomatic for Brugada syndrome, his father had experienced sudden death at the age of 36. The proband was admitted to St. Catherine's Specialty Hospital where blood was taken and subjected to next-generation sequencing (NGS) using a "Sudden cardiac death" panel. The analysis identified a pathogenic variant in the SCN5A gene [c.4222G > A(p.Gly1408Arg)], which is associated with autosomal dominant Brugada syndrome. Based on the positive genetic test result, the patient was referred for further examination. ECG with modified precordial lead positioning confirmed the presence of the Brugada phenotype, displaying the type-2 and type-1 ECG patterns. Therefore, we made the diagnosis and decided to implant an implantable cardioverter-defibrillator (ICD) based on the results of broad genetic NGS testing, diagnostic criteria (ECG), and considering the high burden of sudden cardiac death in the patient's family, as well as his concerns that limited his everyday activities. This case shows that genetics and personalized medicine hold immense potential in the primary prevention, diagnosis, and treatment of Brugada syndrome and sudden cardiac death.

Laser Doppler flow for the hemodynamic differentiation of tachycardia

BACKGROUND

Implantable cardioverter defibrillators (ICDs) offer effective therapy for the prevention of sudden cardiac death (SCD) due to ventricular arrhythmias. However, inappropriate shocks have detrimental effects on survival and quality of life. The addition of hemodynamic monitoring may be useful in discriminating clinically important ventricular arrhythmias.

OBJECTIVE

In this study, we assess the ability of laser Doppler flowmetry to assess the hemodynamic effect of paced atrial and ventricular arrhythmias using mean arterial blood pressure as the reference.

METHODS

In this acute human study in patients undergoing an elective electrophysiological study, laser Doppler flowmetry, arterial blood pressure, and surface ECG were acquired during high-rate atrial and ventricular pacing to simulate supraventricular and ventricular tachycardias.

RESULTS

Arterial blood pressure and laser Doppler flow signals correlated well during atrial and ventricular pacing (rho = 0.694, p < .001). The hemodynamic impairment detected by both methods was greater during ventricular pacing than atrial pacing (-1.0% vs. 19.0%, p < .001). Laser Doppler flowmetry performed better than rate alone to identify hemodynamic impairments.

CONCLUSION

In this acute study, laser Doppler flowmetry tissue perfusion served as a good surrogate measure for arterial pressure, which could be incorporated into future ICDs.

Exploring the Risk Factors of Sudden Cardiac Death Using an Electrocardiography and Medical Ultrasonography for the General Population Without a History of Coronary Artery Disease or Left Ventricular Ejection Fraction <35% and Aged >35 Years - A Novel Point-Based Prediction Model Based on the Chin-Shan Community Cardiovascular Cohort

BACKGROUND

Most of the factors and prediction models of sudden cardiac death (SCD) have been developed without considering the Asia population. The purpose of this study is to construct a point-based prediction model for the general population in Asia.

METHODS AND RESULTS

Chin-Shan Community Cardiovascular Cohort (CCCC) is a community-based longitudinal cohort initiated between 1990 and 1991, enrolling participants aged ≥35 years and following them up until 2005. Participants with coronary artery disease (CAD) or a left ventricular ejection fraction (LVEF) of 35% were excluded from this study. The Framingham risk score function was used to derive a simple point-based prediction model. Based on bootstrapping, a novel model (CCCC-SCD-Score) was validated. A total of 2,105 participants were analyzed. The incidence rate of SCD was 0.406 per 1,000 person-years. The CCCC-SCD-Score score was calculated using age groups (maximal points=4), left ventricular hypertrophy, hypertension, left ventricular ejection fraction <40%, aortic flow rate >190 cm/s, and carotid plaque scores ≥5 (point=1 for each risk factor). The C-index of the CCCC-SCD-Score in predicting SCD risks was 0.888 (95% confidence interval: 0.807-0.969).

CONCLUSIONS

For the general Asian population without a history of CAD or a LVEF <35% and who are aged >35 years, the novel model-based scoring system effectively identifies the risk for SCD using the clinical factors, electrocardiographic and echocardiographic data.