Human genetics and its impact on cardiovascular disease

Cardiovascular Disease in Childhood, Adolescent, and Young Adult Cancer Survivors: The Impact of Family History of Premature Heart Disease

Purpose: Childhood, adolescent, and young adult (CAYA) cancer survivors (age 0-39 years at diagnosis) are at increased risk of cardiovascular disease (CVD). Family history of early heart disease increases the risk of CVD in the general population; however, it is unknown whether this association is seen in CAYA cancer survivors. Methods: Self-report data from the National Health and Nutrition Examination Survey (2005-2018) were used to identify CAYA survivors (>5 years post-diagnosis). The risk of CVD based on family history status (parent or sibling with a diagnosis of heart attack or angina before age 50 years), personal sociodemographic factors, personal medical history factors, and personal behavioral risk factors was determined using logistic regression models. Results: Included were 95 CAYA survivors with CVD and 491 CAYA survivors without CVD. The odds of CVD were significantly higher in survivors with a first-degree family history of early heart disease (odds ratio [OR]: 2.06, 95% confidence interval [CI]: 1.14-3.74). A history of diabetes (OR: 2.61, 95% CI: 1.41-4.84), hypertension (OR: 1.81, 95% CI: 1.04-3.16), and any smoking (OR: 2.19, 95% CI: 1.19-4.02) was also associated with higher odds of CVD in CAYA survivors. Reporting any physical activity in the past month was associated with lower odds (OR: 0.54, 95% CI: 0.30-0.97) of CVD. Conclusions: Family history of early heart disease was associated with increased odds of CVD in CAYA cancer survivors. Obtaining complete and accurate family history information is important both at time of diagnosis and throughout follow-up.

Characterizing the polygenic overlap and shared loci between rheumatoid arthritis and cardiovascular diseases

BACKGROUND

Despite substantial research revealing that patients with rheumatoid arthritis (RA) have excessive morbidity and mortality of cardiovascular disease (CVD), the mechanism underlying this association has not been fully known. This study aims to systematically investigate the phenotypic and genetic correlation between RA and CVD.

METHODS

Based on UK Biobank, we conducted two cohort studies to evaluate the phenotypic relationships between RA and CVD, including atrial fibrillation (AF), coronary artery disease (CAD), heart failure (HF), and stroke. Next, we used linkage disequilibrium score regression, Local Analysis of [co]Variant Association, and bivariate causal mixture model (MiXeR) methods to examine the genetic correlation and polygenic overlap between RA and CVD, using genome-wide association summary statistics. Furthermore, we explored specific shared genetic loci by conjunctional false discovery rate analysis and association analysis based on subsets.

RESULTS

Compared with the general population, RA patients showed a higher incidence of CVD (hazard ratio [HR] = 1.21, 95% confidence interval [CI]: 1.15-1.28). We observed positive genetic correlations of RA with AF and stroke, and a mixture of negative and positive local genetic correlations underlying the global genetic correlation for CAD and HF, with 13 ~ 33% of shared genetic variants for these trait pairs. We further identified 23 pleiotropic loci associated with RA and at least one CVD, including one novel locus (rs7098414, TSPAN14, 10q23.1). Genes mapped to these shared loci were enriched in immune and inflammatory-related pathways, and modifiable risk factors, such as high diastolic blood pressure.

CONCLUSIONS

This study revealed the shared genetic architecture of RA and CVD, which may facilitate drug target identification and improved clinical management.

Evaluating cardiovascular disease risk stratification using multiple-polygenic risk scores and pooled cohort equations: insights from a 17-year longitudinal Korean cohort study

Cardiovascular disease (CVD) remains the leading cause of mortality worldwide, caused by a complex interplay of genetic and environmental factors. This study aimed to evaluate the combined efficacy of multi-polygenic risk scores and pooled cohort equations (PCE) for predicting future CVD risks in the Korean population. In this longitudinal study, 7,612 individuals from the Ansan and Ansung cohorts were analyzed over a 17-year follow-up period. The participants were genotyped using the Korea Biobank Array, and quality-controlled genetic data were subjected to imputation analysis. The weighted sum of the PRSs (wPRSsum) was calculated using PRS-CS with summary statistics from myocardial infarction, ischemic stroke, coronary artery disease, and hypertension genome-wide association studies. The recalibrated PCE was used to assess clinical risk, and the participants were stratified into risk groups based on the wPRSsum and PCE. Associations between these risk scores and incident CVD were evaluated using Cox proportional hazards models and Kaplan-Meier analysis. The wPRSsum approach showed a significant association with incident CVD (HR = 1.15, p = 7.49 × 10-5), and the top 20% high-risk genetic group had an HR of 1.50 (p = 5.04 × 10-4). The recalibrated PCE effectively differentiated between the low and high 10-year CVD risk groups, with a marked difference in survival rates. The predictive models constructed using the wPRSsum and PCE demonstrated a slight improvement in prediction accuracy, particularly among males aged <55 years (C-index = 0.640). We demonstrated that while the integration of wPRSsum with PCE did not significantly outperform the PCE-only model (C-index: 0.703 for combined and 0.704 for PCE-only), it provided enhanced stratification of CVD risk. The highest risk group, identified through the combination of high wPRSsum and PCE scores, exhibited an HR of 4.99 for incident CVD (p = 1.45 × 10-15). These findings highlight the potential of integrating genetic risk assessments with traditional clinical tools for effective CVD risk stratification. Although the addition of wPRSsum to the PCE provided a marginal predictive improvement, it proved valuable in identifying high-risk individuals and supporting personalized treatment strategies. This study reinforces the utility of multi-PRS in conjunction with clinical risk assessment tools, paving the way for more tailored approaches for CVD prevention and management in diverse populations.

A novel and cost-effective method for high-throughput 3D culturing and rhythmic assessment of hiPSC-derived cardiomyocytes using retroreflective Janus microparticles

BACKGROUND

Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) gain attention as a potent cell source in regenerative medicine and drug discovery. With the necessity of the demands for experimental models to create a more physiologically relevant model of the heart in vitro we herein investigate a 3D culturing platform and a method for assessing rhythm in hiPSC-CMs.

METHODS

The 3D cell culture PAMCELL™ plate is designed to enable cells to attach exclusively to adhesive patterned areas. These cell adhesive zones, named as micro-patterned pads, feature micron silica beads that are surface-modified with the well-known arginyl-glycyl-aspartic acid (RGD) peptide. RGD binding to the surface of hiPSC-CMs facilitates cell-cell attachment and the formation of uniform-size spheroids, which is controlled by the diameter of the micro-patterned pads. The assessment and evaluation of 3D hiPSC-CMs beating pattern are carried out using reflective properties of retroreflective Janus micro-particle (RJP). These RJPs are modified with an antibody targeting the gap junction protein found on the surface of hiPSC-CM spheroids. The signal assessment system comprises a camera attached to an optical microscope and a white light source.

RESULTS

The 3D PAMCELL™ R100 culture plate efficiently generate approximately 350 uniform-sized hiPSC-CM spheroids in each well of a 96-well plate and supported a 20-day culture. Analysis of genes and protein expression levels reveal that iPSC-CM spheroids grown on PAMCELL™ R100 retain cardiac stem cell characteristics and functions, outperforming traditional 2D culture platform. Additionally, the RJPs enable monitoring and evaluation of in vitro beating properties of cardiomyocytes without using complex monitoring setup. The system demonstrates its capability to identify alteration in the rhythmic activity of cardiac cells when exposed to ion channel blockers, nifedipine and E4031.

CONCLUSIONS

The integration of the 3D culture method and RJPs in this study establishes a platform for evaluating the rhythmic properties of 3D hiPSC-CMs. This approach holds significant potential for identifying arrhythmias or other cardiac abnormalities, ultimately contributing to the development of more effective therapies for heart diseases.

Polygenic risk score for embryo selection—not ready for prime time

Numerous chronic diseases have a substantial hereditary component. Recent advances in human genetics have allowed the extent of this to be quantified via genome-wide association studies, producing polygenic risk scores (PRS), which can then be applied to individuals to estimate their risk of developing a disease in question. This technology has recently been applied to embryo selection in the setting of IVF and preimplantation genetic testing, with limited data to support its utility. Furthermore, there are concerns that the inherent limitations of PRS makes it ill-suited for use as a screening test in this setting. There are also serious ethical and moral questions associated with this technology that are yet to be addressed. We conclude that further research and ethical reflection are required before embryo selection based on PRS is offered to patients outside of the research setting.

MALAT1 regulates hypertrophy of cardiomyocytes by modulating the miR-181a/HMGB2 pathway

Noncoding RNAs are important for the regulation of cardiac hypertrophy. The function of MALAT1 (a long noncoding mRNA), miR-181a, and HMGB2, their contribution to cardiac hypertrophy, and the regulatory relationship between them during this process remain unknown. In the present study, we treated primary cardiomyocytes with angiotensin II (Ang II) to mimic cardiac hypertrophy. MALAT1 expression was significantly downregulated in Ang II-treated cardiomyocytes compared with control cardiomyocytes. Ang II-induced cardiac hypertrophy was suppressed by overexpression of MALAT1 and promoted by genetic knockdown of MALAT1. A dual-luciferase reporter assay demonstrated that MALAT1 acted as a sponge for miR-181a and inhibited its expression during cardiac hypertrophy. Cardiac hypertrophy was suppressed by overexpression of an miR-181a inhibitor and enhanced by overexpression of an miR-181a mimic. HMGB2 was downregulated during cardiac hypertrophy and was identified as a target of miR-181a by bioinformatics analysis and a dual-luciferase reporter assay. miR-181a overexpression decreased the mRNA and protein levels of HMGB2. Rescue experiments indicated that MALAT1 overexpression reversed the effect of miR-181a on HMGB2 expression. In summary, the results of the present study show that MALAT1 acts as a sponge for miR-181a and thereby regulates expression of HMGB2 and development of cardiac hypertrophy. The novel MALAT1/miR-181a/HMGB2 axis might play a crucial role in cardiac hypertrophy and serve as a new therapeutic target.

Volatile Organic Compounds as Potential Biomarkers for Noninvasive Disease Detection by Nanosensors: A Comprehensive Review

Biomarkers are biological molecules associated with physiological changes of the body and aids in the detecting the onset of disease in patients. There is an urgent need for self-monitoring and early detection of cardiovascular and other health complications. Several blood-based biomarkers have been well established in diagnosis and monitoring the onset of diseases. However, the detection level of biomarkers in bed-side analysis is difficult and complications arise due to the endothelial dysfunction. Currently single volatile organic compounds (VOCs) based sensors are available for the detection of human diseases and no dedicated nanosensor is available for the elderly. Moreover, accuracy of the sensors based on a single analyte is limited. Hence, breath analysis has received enormous attention in healthcare due to its relatively inexpensive, rapid, and noninvasive methods for detecting diseases. This review gives a detailed analysis of how biomarker imprinted nanosensor can be used as a noninvasive method for detecting VOC to health issues early using exhaled breath analysis.