The Inferred Cardiogenic Gene Regulatory Network in the Mammalian Heart

Cardiac development is a complex, multiscale process encompassing cell fate adoption, differentiation and morphogenesis. To elucidate pathways underlying this process, a recently developed algorithm to reverse engineer gene regulatory networks was applied to time-course microarray data obtained from the developing mouse heart. Approximately 200 genes of interest were input into the algorithm to generate putative network topologies that are capable of explaining the experimental data via model simulation. To cull specious network interactions, thousands of putative networks are merged and filtered to generate scale-free, hierarchical networks that are statistically significant and biologically relevant. The networks are validated with known gene interactions and used to predict regulatory pathways important for the developing mammalian heart. Area under the precision-recall curve and receiver operator characteristic curve are 9% and 58%, respectively. Of the top 10 ranked predicted interactions, 4 have already been validated. The algorithm is further tested using a network enriched with known interactions and another depleted of them. The inferred networks contained more interactions for the enriched network versus the depleted network. In all test cases, maximum performance of the algorithm was achieved when the purely data-driven method of network inference was combined with a data-independent, functional-based association method. Lastly, the network generated from the list of approximately 200 genes of interest was expanded using gene-profile uniqueness metrics to include approximately 900 additional known mouse genes and to form the most likely cardiogenic gene regulatory network. The resultant network supports known regulatory interactions and contains several novel cardiogenic regulatory interactions. The method outlined herein provides an informative approach to network inference and leads to clear testable hypotheses related to gene regulation

Activin-A and Bmp4 Levels Modulate Cell Type Specification during CHIR-Induced Cardiomyogenesis

The use of human pluripotent cell progeny for cardiac disease modeling, drug testing and therapeutics requires the ability to efficiently induce pluripotent cells into the cardiomyogenic lineage. Although direct activation of the Activin-A and/or Bmp pathways with growth factors yields context-dependent success, recent studies have shown that induction of Wnt signaling using low molecular weight molecules such as CHIR, which in turn induces the Activin-A and Bmp pathways, is widely effective. To further enhance the reproducibility of CHIR-induced cardiomyogenesis, and to ultimately promote myocyte maturation, we are using exogenous growth factors to optimize cardiomyogenic signaling downstream of CHIR induction. As indicated by RNA-seq, induction with CHIR during Day 1 (Days 0–1) was followed by immediate expression of Nodal ligands and receptors, followed later by Bmp ligands and receptors. Co-induction with CHIR and high levels of the Nodal mimetic Activin-A (50–100 ng/ml) during Day 0–1 efficiently induced definitive endoderm, whereas CHIR supplemented with Activin-A at low levels (10 ng/ml) consistently improved cardiomyogenic efficiency, even when CHIR alone was ineffective. Moreover, co-induction using CHIR and low levels of Activin-A apparently increased the rate of cardiomyogenesis, as indicated by the initial appearance of rhythmically beating cells by Day 6 instead of Day 8. By contrast, co-induction with CHIR plus low levels (3–10 ng/ml) of Bmp4 during Day 0–1 consistently and strongly inhibited cardiomyogenesis. These findings, which demonstrate that cardiomyogenic efficacy is improved by optimizing levels of CHIR-induced growth factors when applied in accord with their sequence of endogenous expression, are consistent with the idea that Nodal (Activin-A) levels toggle the entry of cells into the endodermal or mesodermal lineages, while Bmp levels regulate subsequent allocation into mesodermal cell types

Non-Invasive Prenatal Detection of Trisomy 21 Using Tandem Single Nucleotide Polymorphisms

BACKGROUND: Screening tests for Trisomy 21 (T21), also known as Down syndrome, are routinely performed for the majority of pregnant women. However, current tests rely on either evaluating non-specific markers, which lead to false negative and false positive results, or on invasive tests, which while highly accurate, are expensive and carry a risk of fetal loss. We outline a novel, rapid, highly sensitive, and targeted approach to non-invasively detect fetal T21 using maternal plasma DNA. METHODS AND FINDINGS: Highly heterozygous tandem Single Nucleotide Polymorphism (SNP) sequences on chromosome 21 were analyzed using High-Fidelity PCR and Cycling Temperature Capillary Electrophoresis (CTCE). This approach was used to blindly analyze plasma DNA obtained from peripheral blood from 40 high risk pregnant women, in adherence to a Medical College of Wisconsin Institutional Review Board approved protocol. Tandem SNP sequences were informative when the mother was heterozygous and a third paternal haplotype was present, permitting a quantitative comparison between the maternally inherited haplotype and the paternally inherited haplotype to infer fetal chromosomal dosage by calculating a Haplotype Ratio (HR). 27 subjects were assessable; 13 subjects were not informative due to either low DNA yield or were not informative at the tandem SNP sequences examined. All results were confirmed by a procedure (amniocentesis/CVS) or at postnatal follow-up. Twenty subjects were identified as carrying a disomy 21 fetus (with two copies of chromosome 21) and seven subjects were identified as carrying a T21 fetus. The sensitivity and the specificity of the assay was 100% when HR values lying between 3/5 and 5/3 were used as a threshold for normal subjects. CONCLUSIONS: In summary, a targeted approach, based on calculation of Haplotype Ratios from tandem SNP sequences combined with a sensitive and quantitative DNA measurement technology can be used to accurately detect fetal T21 in maternal plasma when sufficient fetal DNA is present in maternal plasma

Human gene copy number spectra analysis in congenital heart malformations

The clinical significance of copy number variants (CNVs) in congenital heart disease (CHD) continues to be a challenge. Although CNVs including genes can confer disease risk, relationships between gene dosage and phenotype are still being defined. Our goal was to perform a quantitative analysis of CNVs involving 100 well-defined CHD risk genes identified through previously published human association studies in subjects with anatomically defined cardiac malformations. A novel analytical approach permitting CNV gene frequency “spectra” to be computed over prespecified regions to determine phenotype-gene dosage relationships was employed. CNVs in subjects with CHD (n = 945), subphenotyped into 40 groups and verified in accordance with the European Paediatric Cardiac Code, were compared with two control groups, a disease-free cohort (n = 2,026) and a population with coronary artery disease (n = 880). Gains (≥200 kb) and losses (≥100 kb) were determined over 100 CHD risk genes and compared using a Barnard exact test. Six subphenotypes showed significant enrichment (P ≤ 0.05), including aortic stenosis (valvar), atrioventricular canal (partial), atrioventricular septal defect with tetralogy of Fallot, subaortic stenosis, tetralogy of Fallot, and truncus arteriosus. Furthermore, CNV gene frequency spectra were enriched (P ≤ 0.05) for losses at: FKBP6, ELN, GTF2IRD1, GATA4, CRKL, TBX1, ATRX, GPC3, BCOR, ZIC3, FLNA and MID1; and gains at: PRKAB2, FMO5, CHD1L, BCL9, ACP6, GJA5, HRAS, GATA6 and RUNX1. Of CHD subjects, 14% had causal chromosomal abnormalities, and 4.3% had likely causal (significantly enriched), large, rare CNVs. CNV frequency spectra combined with precision phenotyping may lead to increased molecular understanding of etiologic pathways

Impact of \u3cem\u3eMYH6\u3c/em\u3e Variants in Hypoplastic Left Heart Syndrome

Hypoplastic left heart syndrome (HLHS) is a clinically and anatomically severe form of congenital heart disease (CHD). Although prior studies suggest that HLHS has a complex genetic inheritance, its etiology remains largely unknown. The goal of this study was to characterize a risk gene in HLHS and its effect on HLHS etiology and outcome. We performed next-generation sequencing on a multigenerational family with a high prevalence of CHD/HLHS, identifying a rare variant in the α-myosin heavy chain (MYH6) gene. A case-control study of 190 unrelated HLHS subjects was then performed and compared with the 1000 Genomes Project. Damaging MYH6 variants, including novel, missense, in-frame deletion, premature stop, de novo, and compound heterozygous variants, were significantly enriched in HLHS cases (P \u3c 1 × 10−5). Clinical outcomes analysis showed reduced transplant-free survival in HLHS subjects with damaging MYH6 variants (P \u3c 1 × 10−2). Transcriptome and protein expression analyses with cardiac tissue revealed differential expression of cardiac contractility genes, notably upregulation of the β-myosin heavy chain (MYH7) gene in subjects with MYH6 variants (P \u3c 1 × 10−3). We subsequently used patient-specific induced pluripotent stem cells (iPSCs) to model HLHS in vitro. Early stages of in vitro cardiomyogenesis in iPSCs derived from two unrelated HLHS families mimicked the increased expression of MYH7 observed in vivo (P \u3c 1 × 10−2), while revealing defective cardiomyogenic differentiation. Rare, damaging variants in MYH6 are enriched in HLHS, affect molecular expression of contractility genes, and are predictive of poor outcome. These findings indicate that the etiology of MYH6-associated HLHS can be informed using iPSCs and suggest utility in future clinical applications

3D-bioprinting of patient-derived cardiac tissue models for studying congenital heart disease.

INTRODUCTION: Congenital heart disease is the leading cause of death related to birth defects and affects 1 out of every 100 live births. Induced pluripotent stem cell technology has allowed for patient-derived cardiomyocytes to be studied in vitro. An approach to bioengineer these cells into a physiologically accurate cardiac tissue model is needed in order to study the disease and evaluate potential treatment strategies. METHODS: To accomplish this, we have developed a protocol to 3D-bioprint cardiac tissue constructs comprised of patient-derived cardiomyocytes within a hydrogel bioink based on laminin-521. RESULTS: Cardiomyocytes remained viable and demonstrated appropriate phenotype and function including spontaneous contraction. Contraction remained consistent during 30 days of culture based on displacement measurements. Furthermore, tissue constructs demonstrated progressive maturation based on sarcomere structure and gene expression analysis. Gene expression analysis also revealed enhanced maturation in 3D constructs compared to 2D cell culture. DISCUSSION: This combination of patient-derived cardiomyocytes and 3D-bioprinting represents a promising platform for studying congenital heart disease and evaluating individualized treatment strategies

Human Genotyping and An Experimental Model Reveal NPR-C as A Possible Contributor to Morbidity In Coarctation Of The Aorta

Coarctation of the aorta (CoA) is a common congenital cardiovascular (CV) defect characterized by a stenosis of the descending thoracic aorta. Treatment exists, but many patients develop hypertension (HTN). Identifying the cause of HTN is challenging because of patient variability (e.g., age, follow-up duration, severity) and concurrent CV abnormalities. Our objective was to conduct RNA sequencing of aortic tissue from humans with CoA to identify a candidate gene for mechanistic studies of arterial dysfunction in a rabbit model of CoA devoid of the variability seen with humans. We present the first known evidence of natriuretic peptide receptor C (NPR-C; aka NPR3) downregulation in human aortic sections subjected to high blood pressure (BP) from CoA versus normal BP regions (validated to PCR). These changes in NPR-C, a gene associated with BP and proliferation, were replicated in the rabbit model of CoA. Artery segments from this model were used with human aortic endothelial cells to reveal the functional relevance of altered NPR-C activity. Results showed decreased intracellular calcium ([Ca2+]i) activity to C-type natriuretic peptide (CNP). Normal relaxation induced by CNP and atrial natriuretic peptide was impaired for aortic segments exposed to elevated BP from CoA. Inhibition of NPR-C (M372049) also impaired aortic relaxation and [Ca2+]i activity. Genotyping of NPR-Cvariants predicted to be damaging revealed that rs146301345 was enriched in our CoA patients, but sample size limited association with HTN. These results may ultimately be used to tailor treatment for CoA based on mechanical stimuli, genotyping, and/or changes in arterial function

GSEPD: a Bioconductor package for RNA-seq gene set enrichment and projection display

Abstract Background RNA-seq, wherein RNA transcripts expressed in a sample are sequenced and quantified, has become a widely used technique to study disease and development. With RNA-seq, transcription abundance can be measured, differential expression genes between groups and functional enrichment of those genes can be computed. However, biological insights from RNA-seq are often limited by computational analysis and the enormous volume of resulting data, preventing facile and meaningful review and interpretation of gene expression profiles. Particularly, in cases where the samples under study exhibit uncontrolled variation, deeper analysis of functional enrichment would be necessary to visualize samples’ gene expression activity under each biological function. Results We developed a Bioconductor package rgsepd that streamlines RNA-seq data analysis by wrapping commonly used tools DESeq2 and GOSeq in a user-friendly interface and performs a gene-subset linear projection to cluster heterogeneous samples by Gene Ontology (GO) terms. Rgsepd computes significantly enriched GO terms for each experimental condition and generates multidimensional projection plots highlighting how each predefined gene set’s multidimensional expression may delineate samples. Conclusions The rgsepd serves to automate differential expression, functional annotation, and exploratory data analyses to highlight subtle expression differences among samples based on each significant biological function

A Systematic Review of Ebstein’s Anomaly with Left Ventricular Noncompaction

Traditional definitions of Ebstein’s anomaly (EA) and left ventricular noncompaction (LVNC), two rare congenital heart defects (CHDs), confine disease to either the right or left heart, respectively. Around 15–29% of patients with EA, which has a prevalence of 1 in 20,000 live births, commonly manifest with LVNC. While individual EA or LVNC literature is extensive, relatively little discussion is devoted to the joint appearance of EA and LVNC (EA/LVNC), which poses a higher risk of poor clinical outcomes. We queried PubMed, Medline, and Web of Science for all peer-reviewed publications from inception to February 2022 that discuss EA/LVNC and found 58 unique articles written in English. Here, we summarize and extrapolate commonalities in clinical and genetic understanding of EA/LVNC to date. We additionally postulate involvement of shared developmental pathways that may lead to this combined disease. Anatomical variation in EA/LVNC encompasses characteristics of both CHDs, including tricuspid valve displacement, right heart dilatation, and left ventricular trabeculation, and dictates clinical presentation in both age and severity. Disease treatment is non-specific, ranging from symptomatic management to invasive surgery. Apart from a few variant associations, mainly in sarcomeric genes MYH7 and TPM1, the genetic etiology and pathogenesis of EA/LVNC remain largely unknown