Congenital heart disease (CHD) is the most prevalent birth defect, often linked to genetic variations, environmental exposures, or combination of both. Epidemiological studies reveal that maternal pregestational diabetes is associated with ~5-fold higher risk of CHD in the offspring; however, the causal mechanisms affecting cardiac gene-regulatory-network (GRN) during early embryonic development remain poorly understood. In this study, we utilize an established murine model of pregestational diabetes to uncover the transcriptional responses in key cell-types of the developing heart exposed to maternal hyperglycemia (matHG). Here we show that matHG elicits diverse cellular responses in E9.5 and E11.5 embryonic hearts compared to non-diabetic hearts by single-cell RNA-sequencing. Through differential-gene-expression and cellular trajectory analyses, we identify perturbations in genes, predominantly affecting Isl1+ second heart field progenitors and Tnnt2+ cardiomyocytes with matHG. Using cell-fate mapping analysis in Isl1-lineage descendants, we demonstrate that matHG impairs cardiomyocyte differentiation and alters the expression of lineage-specifying cardiac genes. Finally, our work reveals matHG-mediated transcriptional changes in second heart field lineage that elevate CHD risk by perturbing Isl1-GRN during cardiomyocyte differentiation. Gene-environment interaction studies targeting the Isl1-GRN in cardiac progenitor cells will have a broader impact on understanding the mechanisms of matHG-induced risk of CHD associated with diabetic pregnancies.

Objective: To perform basic statistical analysis of laboratory lipoprotein data, i.e. the measures of very low density lipoprotein (VLDL), low density lipoprotein (LDL) and high density lipoprotein (HDL), to assist in their interpretation. In particular, to find any difference in male and female data that might explain the known difference in atherogenic susceptibility between the sexes. Method:The study subjects were patients of doctors in city and country New South Wales. Statistical methodology to find the inter-relations of the lipoproteins was the construction of the matrix of correlation, then by matrix algebra to display the independent trends in the data. Results and conclusions:The findings have been an atherogenicity function involving LDL and HDL and a risk function of myocardial infarction (MI) involving LDL, HDL and age, confirmed by reference to the age and sex incidence of MI in the Australian population. The principal conclusion is a simple mathematical model of the incidence of MI. Implications:The means given for identification of at-risk individuals before symptoms appear, also the means given of lowering whole population risk of MI by health education and lifestyle change with increased longevity for all. These concepts call for a prospective trial. M population incidence of myocardial infarction (MI) and blood total cholesterol levels.' We shift the focus from serum total cholesterol to the cholesterol-rich lipoprotein fractions very low density lipoprotein (VLDL), low density lipoprotein (LDL) and high density lipoprotein (HDL).These variables were measured in male and female patients attending general practices in city and country New South Wales. All specimens were taken after at least a 12-hour overnight fast. A small minority showing significant chylomicronaemia were rejected as introducing a confounding variable.The inter-relations of the variables are demonstrated first by their correlation matrix in the population, then by the mathematical procedure of calculating from this matrix the so-called eigenvectors, being independent combinations of the variables.* In this way, the three inter-related lipoproteins are shown to participate in two distinct biochemical processes. We show the clinical relevance of these processes.Until now, the interpretation of laboratory lipoprotein data has been somewhat subjective and imprecise, but this difficulty is solved by separating the discrete activities which are superimposed in the laboratory data.Our putative measure of atherogenicity stems from the difference observed between the sexes in the eigenvector that expresses LDL homeostasis. In the male, it involves LDL alone and in the female is LDL modified by HDL. This sole difference between the sexes in lipoprotein terms we relate hypothetically to the observed difference in atherogenicity between the sexes. It is a reasonable hypothesis that risk of MI is a function both of atherogenicity and the time span over which this has been operative. This paper develops such a risk function and co...

Congenital heart disease (CHD) represents a major class of birth defects worldwide and is associated with cardiac malformations that often require surgical intervention immediately after birth. Despite the intense efforts from multicentric genome/exome sequencing studies that have identified several genetic variants, the etiology of CHD remains diverse and often unknown. Genetically modified animal models with candidate gene deficiencies continue to provide novel molecular insights that are responsible for fetal cardiac development. However, the past decade has seen remarkable advances in the field of human induced pluripotent stem cell (hiPSC)‐based disease modeling approaches to better understand the development of CHD and discover novel preventative therapies. The iPSCs are derived from reprogramming of differentiated somatic cells to an embryonic‐like pluripotent state via overexpression of key transcription factors. In this review, we describe how differentiation of hiPSCs to specialized cardiac cellular identities facilitates our understanding of the development and pathogenesis of CHD subtypes. We summarize the molecular and functional characterization of hiPSC‐derived differentiated cells in support of normal cardiogenesis, those that go awry in CHD and other heart diseases. We illustrate how stem cell‐based disease modeling enables scientists to dissect the molecular mechanisms of cell–cell interactions underlying CHD. We highlight the current state of hiPSC‐based studies that are in the verge of translating into clinical trials. We also address limitations including hiPSC‐model reproducibility and scalability and differentiation methods leading to cellular heterogeneity. Last, we provide future perspective on exploiting the potential of hiPSC technology as a predictive model for patient‐specific CHD, screening pharmaceuticals, and provide a source for cell‐based personalized medicine. In combination with existing clinical and animal model studies, data obtained from hiPSCs will yield further understanding of oligogenic, gene–environment interaction, pathophysiology, and management for CHD and other genetic cardiac disorders.

Congenital heart disease (CHD) is the most frequently occurring structural malformations of the heart affecting ~1% of live births. Besides genetic predisposition, embryonic exposure to teratogens during pregnancy increases the risk of CHD. However, the dose and cell-type-specific responses to an adverse maternal environment remain poorly defined. Here, we report a dose-response relationship between maternal glucose levels and phenotypic severity of CHD in offspring, using a chemically-induced pregestational diabetes mellitus (PGDM) mouse model. Embryos from dams with low-level maternal hyperglycemia (matHG) displayed trabeculation defects, ventricular wall thinning, and ventricular septal defects (VSD). On the other hand, embryos from dams with high-level matHG display outflow tract malformations, ventricular wall thinning and an increased rate of VSD. Our findings show that increasing levels of matHG exacerbates CHD occurrence and severity in offspring compared to control embryos. We applied single-cell RNA- sequencing to define matHG-related transcriptional differences in E9.5 and E11.5 hearts as comparing to controls. Disease-dependent gene-expression changes were observed in Isl1+ second heart field (SHF) and Tnnt2+ cardiomyocyte subpopulations. Lineage tracing studies in Isl1-Cre; RosamTmG embryonic hearts showed Isl1+-SHF-derived cardiomyocyte differentiation was impaired with matHG. This study highlights the influence of matHG-dosage on cardiac morphogenesis and identifies perturbations in the Isl1-dependent gene-regulatory network that affect SHF-derived cardiomyocyte differentiation contributing to matPGDM-induced CHD.

Objective : To examine the clinical significance of a specific relationship between very low density lipoprotein (VLDL) and high density lipoprotein (HDL), namely their differential, in relation to Type 2 non‐insulin dependent diabetes mellitus (NIDDM). Methods : The study subjects were 300 female and 300 male patients of doctors in city and rural New South Wales referred for lipid studies. Their clinical notes suggested a relationship of VLDL‐HDL to diabetes mellitus (DM) and it was therefore hypothesised that this expression is a functional measure of diabeto‐genicity. Results : By incorporation of age, a calculated measure of risk of overt DM and consequent death can be derived. This is confirmed by comparing the age incidence of this risk function with the age incidence of death attributed to DM in the Australian population to give a simple linear correlation. The principal conclusion is drawn from a mathematical model of the population incidence of DM in terms of VLDL, HDL and age. Conclusion : From this model springs the inference that NIDDM is a cumulative dyslipidaemia‐over‐time process. If this inference is correct, NIDDM can properly be viewed as a societal disease of which all run a measurable risk that increases with age and from which all will die in the long term who do not die sooner from another cause. Implications : The implications for public health are the ability to identify the individuals at raised risk before DM becomes symptomatic by lipoprotein screening, and the ability to lower risk of DM over the whole population by preventive measures with increased longevity for all.