Hypertrophic Obstructive Cardiomyopathy

Secondary findings in a large Pakistani cohort tested with whole genome sequencing

Studies on genomic secondary findings (SFs) are diverse in participants' characteristics, sequencing methods, and versions of the ACMG SF list. Based on whole genome sequencing and the version 3.1 of the ACMG SF list, we studied SFs in 863 individuals from five different regions in Pakistan. We identified 24 ACMG SFs in 23 (2.7%) of 863 individuals: 18 of 24 were related to cardiovascular disease and four to cancer syndromes. In addition to ACMG SFs, we identified 16 (1.9%) participants with pathogenic and likely pathogenic variants in genes that were not related to the participants' clinical conditions but with clear medical actionability (non-ACMG SFs): 4 of 16 were related to eye diseases, two to metabolic disorders, and two to urinary system disorders. By testing a large Pakistani cohort with whole genome sequencing, we concluded that in countries such as Pakistan, the ACMG SF list could be expanded, and our non-ACMG SF list is one example.

Multi-factor regulatory network and different clusters in hypertrophic obstructive cardiomyopathy

BACKGROUND

Practical biosignatures and thorough understanding of regulatory processes of hypertrophic obstructive cardiomyopathy (HOCM) are still lacking.

METHODS

Firstly, public data from GSE36961 and GSE89714 datasets of Gene Expression Omnibus (GEO), Gene database of NCBI (National Center of Biotechnology Information) and Online Mendelian Inheritance in Man (OMIM) database were merged into a candidate gene set of HOCM. Secondly, weighted gene co-expression network analysis (WGCNA) for the candidate gene set was carried out to determine premier co-expressed genes. Thirdly, significant regulators were found out by virtue of a multi-factor regulatory network of long non-coding RNAs (lncRNAs), messenger RNAs (mRNAs), microRNAs (miRNAs) and transcription factors (TFs) with molecule interreactions from starBase v2.0 database and TRRUST v2 database. Ultimately, HOCM unsupervised clustering and "tsne" dimensionality reduction was employed to gain hub genes, whose classification performance was evaluated by a multinomial model of lasso logistic regression analysis binded with receiver operating characteristic (ROC) curve.

RESULTS

Two HOCM remarkably-interrelated modules were from WGCNA, followed by the recognition of 32 crucial co-expressed genes. The multi-factor regulatory network disclosed 7 primary regulatory agents, containing lncRNAs (XIST, MALAT1, and H19), TFs (SPI1 and SP1) and miRNAs (hsa-miR-29b-39 and has-miR-29a-3p). Four clusters of HOCM and 4 hub genes (COMP, FMOD, AEBP1 and SULF1) significantly expressing in preceding four subtypes were obtained, while ROC curve demonstrated satisfactory performance of clustering and 4 genes.

CONCLUSIONS

Our consequences furnish valuable resource which may bring about prospective mechanistic and therapeutic anatomization in HOCM.

Correlations between cardiac troponin I and nonsustained ventricular tachycardia in hypertrophic obstructive cardiomyopathy

BACKGROUND

Nonsustained ventricular tachycardia (NSVT) is an independent risk factor for sudden cardiac death (SCD) in patients with hypertrophic obstructive cardiomyopathy (HOCM). However, data concerning the correlations of cardiac biomarkers and NSVT in HOCM are rather limited.

HYPOTHESIS

Our study aimed to investigate the associations between the occurrence of NSVT and circulating biomarkers representing myocardial injury (cardiac troponin I, cTnI), cardiac function (N-terminal pro-brain natriuretic peptide, NT-pro BNP), and inflammation (high-sensitivity C-reactive protein) in a large Chinese HOCM cohort.

METHODS

A total of 755 consecutive HOCM patients were recruited. Systematic cardiac evaluations and circulating biomarkers were examined routinely in all subjects under the clinically stable status. According to the results of 24-hour Holter monitoring, patients were divided into the NSVT group (n = 138) and the nonventricular tachycardia (non-VT) group (n = 617).

RESULTS

Compared with the non-VT group, circulating levels of both cTnI and NT-pro BNP elevated significantly in patients with positive NSVT episodes (P < .001). Multivariable analyses demonstrated that cTnI was independently associated with the presence of NSVT (OR = 1.675, 95% CI: 1.406-1.994, P < .001). Concentrations of cTnI increased progressively not only with the aggravation of ventricular arrhythmic events (P < .001), but also with the growing risk of SCD in HOCM patients (P < .001). Serum cTnI ≥ 0.0265 ng/mL indicated predictive value for the occurrence of NSVT in the HOCM cohort (area under the curve = 0.707, 95% CI: 0.660-0.754, P < .001).

CONCLUSIONS

Elevated cTnI was an independent determinant of NSVT, and it seemed to be valuable for assessing the clinical status of ventricular arrhythmias and the risk of SCD in patients with HOCM.

Soluble ST2, Galectin-3 and clinical prognosis of patients with hypertrophic cardiomyopathy undergoing ventricular septal myectomy: a correlation analysis

Background

Hypertrophic cardiomyopathy (HCM) is the most common chromosomal abnormal heart disease. The pathophysiological mechanism of HCM is complex. Several studies have suggested that the level of Soluble ST2 (sST2) may be a biomarker of chronic systolic heart failure, however, the role of sST2 in HCM remains unclear. So we performed this study to analyze the role of Soluble ST2 (sST2), Galectin-3 (Gal-3) and its correlations with clinical prognosis of patients with hypertrophic cardiomyopathy (HCM) undergoing ventricular septal myectomy.

Methods

HCM patients who underwent modified Morrow surgery in our hospital during June 2016-June 2018 were included. We divided the patients into different groups stratified by sST2 and Gal-3 level. Besides, we included volunteers without heart disease for medical examination as normal controls. Biochemical analyses were conducted to identify the biomarkers difference. The predictive value of sST2 and Gal-3 on all-cause mortality was evaluated with Cox regression analysis.

Results

A total of 125 HCM patients were included in this present study. The sST2 and Gal-3 levels in HCM patients were significantly higher than that in control group (all P<0.001); there were significant differences in the incidence of all-cause mortality for HCM patients stratified by the sST2 and Gal-3 level; Cox univariate regression survival analysis showed that the hypertension (HR =1.19, 95% CI: 1.01-1.38), maximum wall thickness (HR =1.48, 95% CI: 1.04-1.98), Log sST2 (HR =1.02, 95% CI: 1.01-1.05), Log Gal-3 (HR =1.17, 95% CI: 1.09-1.32) were the predictors for all-cause mortality in patients with HCM, and Cox multivariate risk regression showed that maximum wall thickness was the independent predictors of all-cause mortality in patients with HCM (HR =1.63, 95% CI: 1.35-1.97).

Conclusions

Even through sST2 and Gal-3 were not associated with clinical prognosis of patients with HCM undergoing ventricular septal myectomy, it may be involved in the progress of HCM, more studies are warranted to identify the potential mechanism and reverence value.