Explore the vast range of titles available.

A scalable, robust, and integrated differentiation platform for large‐scale production of human pluripotent stem cell‐cardiomyocyte (hPSC‐CM) in a stirred suspension bioreactor as a single‐unit operation was developed. This platform could become a valuable tool for mass production of functional hPSC‐CMs as a prerequisite for realizing their promising potential for therapeutic and industrial applications including drug discovery and toxicity assays. Recent advances in the generation of cardiomyocytes (CMs) from human pluripotent stem cells (hPSCs), in conjunction with the promising outcomes from preclinical and clinical studies, have raised new hopes for cardiac cell therapy. We report the development of a scalable, robust, and integrated differentiation platform for large‐scale production of hPSC‐CM aggregates in a stirred suspension bioreactor as a single‐unit operation. Precise modulation of the differentiation process by small molecule activation of WNT signaling, followed by inactivation of transforming growth factor‐β and WNT signaling and activation of sonic hedgehog signaling in hPSCs as size‐controlled aggregates led to the generation of approximately 100% beating CM spheroids containing virtually pure (∼90%) CMs in 10 days. Moreover, the developed differentiation strategy was universal, as demonstrated by testing multiple hPSC lines (5 human embryonic stem cell and 4 human inducible PSC lines) without cell sorting or selection. The produced hPSC‐CMs successfully expressed canonical lineage‐specific markers and showed high functionality, as demonstrated by microelectrode array and electrophysiology tests. This robust and universal platform could become a valuable tool for the mass production of functional hPSC‐CMs as a prerequisite for realizing their promising potential for therapeutic and industrial applications, including drug discovery and toxicity assays. Significance Recent advances in the generation of cardiomyocytes (CMs) from human pluripotent stem cells (hPSCs) and the development of novel cell therapy strategies using hPSC‐CMs (e.g., cardiac patches) in conjunction with promising preclinical and clinical studies, have raised new hopes for patients with end‐stage cardiovascular disease, which remains the leading cause of morbidity and mortality globally. In this study, a simplified, scalable, robust, and integrated differentiation platform was developed to generate clinical grade hPSC‐CMs as cell aggregates under chemically defined culture conditions. This approach resulted in approximately 100% beating CM spheroids with virtually pure (∼90%) functional cardiomyocytes in 10 days from multiple hPSC lines. This universal and robust bioprocessing platform can provide sufficient numbers of hPSC‐CMs for companies developing regenerative medicine technologies to rescue, replace, and help repair damaged heart tissues and for pharmaceutical companies developing advanced biologics and drugs for regeneration of lost heart tissue using high‐throughput technologies. It is believed that this technology can expedite clinical progress in these areas to achieve a meaningful impact on improving clinical outcomes, cost of care, and quality of life for those patients disabled and experiencing heart disease.

Background A wide range of tools are available for the detection of copy number variants (CNVs) from whole-genome sequencing (WGS) data. However, none of them focus on clinically-relevant CNVs, such as those that are associated with known genetic syndromes. Such variants are often large in size, typically 1–5 Mb, but currently available CNV callers have been developed and benchmarked for the discovery of smaller variants. Thus, the ability of these programs to detect tens of real syndromic CNVs remains largely unknown. Results Here we present ConanVarvar, a tool which implements a complete workflow for the targeted analysis of large germline CNVs from WGS data. ConanVarvar comes with an intuitive R Shiny graphical user interface and annotates identified variants with information about 56 associated syndromic conditions. We benchmarked ConanVarvar and four other programs on a dataset containing real and simulated syndromic CNVs larger than 1 Mb. In comparison to other tools, ConanVarvar reports 10–30 times less false-positive variants without compromising sensitivity and is quicker to run, especially on large batches of samples. Conclusions ConanVarvar is a useful instrument for primary analysis in disease sequencing studies, where large CNVs could be the cause of disease.

Congenital heart diseases (CHDs) frequently impact the right ventricular outflow tract, resulting in a significant incidence of pulmonary valve replacement in the pediatric population. While contemporary pediatric pulmonary valve replacements (PPVRs) allow satisfactory patient survival, their biocompatibility and durability remain suboptimal and repeat operations are commonplace, especially for very young patients. This places enormous physical, financial, and psychological burdens on patients and their parents, highlighting an urgent clinical need for better PPVRs. An important reason for the clinical failure of PPVRs is biofouling, which instigates various adverse biological responses such as thrombosis and infection, promoting research into various antifouling chemistries that may find utility in PPVR materials. Another significant contributor is the inevitability of somatic growth in pediatric patients, causing structural discrepancies between the patient and PPVR, stimulating the development of various growth‐accommodating heart valve prototypes. This review offers an interdisciplinary perspective on these challenges by exploring clinical experiences, physiological understandings, and bioengineering technologies that may contribute to device development. It thus aims to provide an insight into the design requirements of next‐generation PPVRs to advance clinical outcomes and promote patient quality of life.

Background Congenital heart disease (CHD) is the most common congenital anomaly. Almost 90% of isolated cases have an unexplained genetic etiology after clinical testing. Non-canonical splice variants that disrupt mRNA splicing through the loss or creation of exon boundaries are not routinely captured and/or evaluated by standard clinical genetic tests. Recent computational algorithms such as SpliceAI have shown an ability to predict such variants, but are not specific to cardiac-expressed genes and transcriptional isoforms. Methods We used genome sequencing (GS) ( n  = 1101 CHD probands) and myocardial RNA-Sequencing (RNA-Seq) ( n  = 154 CHD and n  = 43 cardiomyopathy probands) to identify and validate splice disrupting variants, and to develop a heart-specific model for canonical and non-canonical splice variants that can be applied to patients with CHD and cardiomyopathy. Two thousand five hundred seventy GS samples from the Medical Genome Reference Bank were analyzed as healthy controls. Results Of 8583 rare DNA splice-disrupting variants initially identified using SpliceAI, 100 were associated with altered splice junctions in the corresponding patient myocardium affecting 95 genes. Using strength of myocardial gene expression and genome-wide DNA variant features that were confirmed to affect splicing in myocardial RNA, we trained a machine learning model for predicting cardiac-specific splice-disrupting variants (AUC 0.86 on internal validation). In a validation set of 48 CHD probands, the cardiac-specific model outperformed a SpliceAI model alone (AUC 0.94 vs 0.67 respectively). Application of this model to an additional 947 CHD probands with only GS data identified 1% patients with canonical and 11% patients with non-canonical splice-disrupting variants in CHD genes. Forty-nine percent of predicted splice-disrupting variants were intronic and > 10 bp from existing splice junctions. The burden of high-confidence splice-disrupting variants in CHD genes was 1.28-fold higher in CHD cases compared with healthy controls. Conclusions A new cardiac-specific in silico model was developed using complementary GS and RNA-Seq data that improved genetic yield by identifying a significant burden of non-canonical splice variants associated with CHD that would not be detectable through panel or exome sequencing.

IntroductionAdvances in the care of patients with single-ventricle congenital heart disease have led to a new generation of individuals living with a Fontan circulation. For people with Fontan physiology, physical, psychological and neurodevelopmental challenges are common. The objective of this study is to describe and develop a deeper understanding of the factors that contribute to quality of life (QOL) among children, adolescents and adults living with a Fontan circulation across Australia and New Zealand, their parents and siblings.Methods and AnalysisThis article presents the protocol for the Australian and New Zealand Fontan Registry (ANZFR) QOL Study, a cross-sectional, population-based study designed to examine QOL among people of all ages with a Fontan circulation, their parents and siblings. Study eligibility criteria includes (1) individuals with a Fontan circulation aged ≥6 years, at least 12 months post-Fontan procedure and enrolled in the ANZFR; (2) parents of individuals enrolled in the ANZFR; and (3) siblings aged ≥6 years of an individual enrolled in the ANZFR. A novel, online research platform is used to distribute personalised assessments tailored to participant age and developmental stage. A suite of validated psychometric self-report and parent-proxy report instruments capture potential correlates and predictors of QOL, including symptoms of psychological distress, personality attributes, coping and cognitive appraisals, family functioning, healthcare experiences and costs, access to emotional support and socioeconomic factors. Clinical characteristics are captured via self-report and parent-proxy report, as well as the ANZFR. Descriptive analyses and multilevel models will be used to examine QOL across groups and to investigate potential explanatory variables.Ethics and DisseminationApproval has been obtained from all relevant Human Research Ethics Committees (HRECs), including the Sydney Children’s Hospitals Network and the Royal Children’s Hospital Melbourne HRECs. Study findings will be published in peer-reviewed journals and presented at national and international meetings and seminars.

Application of the ‘hybrid approach’, where the major operation involving aortic arch reconstruction is deferred beyond the neonatal period, has been used mostly to manage patients with high-risk characteristics for routine first-stage surgery. The first was a comparison between different surgical strategies to create a source of pulmonary blood flow during the first operation (the Single Ventricle Reconstruction (SVR) trial).4 It was conducted in largely academic centres in mostly normal-risk patients and provided a contemporary (2005–2014) understanding of survival after surgery for HLH. Neurodevelopmental disability affects around 30% of survivors, with a range of outcomes from delay in reaching developmental milestones, through learning and behavioural disorders such as autism, and in rare cases cerebral palsy. [...]HLH is the end result of a pan-cardiac developmental disorder including the cardiomyocyte.7 Our operations address inflows and outflows but the development of ventricular dysfunction is an important and common pathway towards deterioration in clinical performance and sometimes death.

Genetic variants causing loss of function in the synthesis of nicotinamide adenine dinucleotide were shown to cause congenital malformations that comprise the VACTERL association. Niacin supplementation during gestation prevented similar defects in mouse models.

To compare clinical assessment of cardiac performance with an invasive method of haemodynamic monitoring. Prospective observational study in a 16-bed tertiary paediatric intensive care unit. Infants and children undergoing cardiopulmonary bypass and surgical repair of congenital heart lesions. Based on physical examination and routinely available haemodynamic monitoring in the paediatric intensive care unit, medical and nursing staff assessed cardiac index, systemic vascular resistance index and volume status. Clinical assessment was compared with cardiac index, systemic vascular resistance index and global end diastolic volume index, obtained by femoral artery thermodilution. A total of 76 clinical estimations of the three parameters were made in 16 infants and children undergoing biventricular repair of congenital heart lesions. Agreement was poor between clinical and invasive methods of determining all three studied parameters of cardiac performance. Cardiac index was significantly underestimated clinically; mean difference was 0.71 l min(-1) m(-2) (95% range of agreement +/-2.7). Clinical estimates of systemic vascular resistance (weighted kappa=0.15) and volume status (weighted kappa=0.04) showed poor levels of agreement with measured values and were overestimated clinically. There was one complication related to a femoral arterial catheter and one device failure. Routine clinical assessment of parameters of cardiac performance agreed poorly with invasive determinations of these indices. Management decisions based on inaccurate clinical assessments may be detrimental to patients. Invasive haemodynamic monitoring using femoral artery thermodilution warrants cautious further evaluation as there is little agreement with clinical assessment which is presently standard accepted care in this patient population.

The most common cyanotic congenital heart disease (CHD) requiring management as a neonate is transposition of great arteries (TGA). Clinically, up to 50% of TGA patients develop some form of neurodevelopmental disability (NDD), thought to have a significant genetic component. A “ciliopathy” and links with laterality disorders have been proposed. This first report of whole genome sequencing in TGA, sought to identify clinically relevant variants contributing to heart, brain and laterality defects. Initial whole genome sequencing analyses on 100 TGA patients focussed on established disease genes related to CHD (n = 107), NDD (n = 659) and heterotaxy (n = 74). Single variant as well as copy number variant analyses were conducted. Variant pathogenicity was assessed using the American College of Medical Genetics and Genomics-Association for Molecular Pathology guidelines. Fifty-five putatively damaging variants were identified in established disease genes associated with CHD, NDD and heterotaxy; however, no clinically relevant variants could be attributed to disease. Notably, case-control analyses identified significantly more predicted-damaging, silent and total variants in TGA cases than healthy controls in established CHD genes (P < .001), NDD genes (P < .001) as well as across the three gene panels (P < .001). We present compelling evidence that the majority of TGA is not caused by monogenic rare variants and is most likely oligogenic and/or polygenic in nature, highlighting the complex genetic architecture and multifactorial influences on this CHD sub-type and its long-term sequelae. Assessment of variant burden in key heart, brain and/or laterality genes may be required to unravel the genetic contributions to TGA and related disabilities.

Purpose Congenital heart disease (CHD) affects up to 1% of live births. However, a genetic diagnosis is not made in most cases. The purpose of this study was to assess the outcomes of genome sequencing (GS) of a heterogeneous cohort of CHD patients. Methods Ninety-seven families with probands born with CHD requiring surgical correction were recruited for genome sequencing. At minimum, a proband–parents trio was sequenced per family. GS data were analyzed via a two-tiered method: application of a high-confidence gene screen (hcCHD), and comprehensive analysis. Identified variants were assessed for pathogenicity using the American College of Medical Genetics and Genomics–Association for Molecular Pathology (ACMG-AMP) guidelines. Results Clinically relevant genetic variants in known and emerging CHD genes were identified. The hcCHD screen identified a clinically actionable variant in 22% of families. Subsequent comprehensive analysis identified a clinically actionable variant in an additional 9% of families in genes with recent disease associations. Overall, this two-tiered approach provided a clinically relevant variant for 31% of families. Conclusions Interrogating GS data using our two-tiered method allowed identification of variants with high clinical utility in a third of our heterogeneous cohort. However, association of emerging genes with CHD etiology, and development of novel technologies for variant assessment and interpretation, will increase diagnostic yield during future reassessment of our GS data.