Citations

Hypoplastic left heart syndrome (HLHS) is one of the most challenging forms of congenital heart diseases. Previous studies were mainly focused on intrinsic defects in myocardium. However, this does not sufficiently explain the abnormal development of the cardiac valve, septum, and vasculature, known to originate from the endocardium. Here, using single-cell transcriptomic profiling, induced pluripotent stem cells (iPSC) derived endocardial cells (iEECs), human fetal heart tissue with underdeveloped left ventricle, as well as a Xenopus model, we identified a developmentally impaired endocardial population in HLHS. The intrinsic endocardial deficits contributed to abnormal endothelial to mesenchymal transition, NOTCH signaling, and extracellular matrix organization, all of which are key factors in valve formation. Consequently, in an endocardium-myocardium co-culture system, we found that endocardial abnormalities conferred reduced proliferation and maturation of iPSC derived cardiomyocyte (iPSC-CMs) judged by Ki67 staining, contractility, sarcomere organization, and related gene expressions through a disrupted fibronectin (FN1)-integrin interaction. Several recently described HLHS de novo mutations such as ETS1 and CHD7 showed reduced binding to FN1 promoter and enhancer in HLHS vs. control iEECs based on ChIP-qPCR analysis. Additionally, we found that suppression of the ETS1 in Xenopus caused reduced endocardial FN1 expression and impaired heart development. Supplementation of FN1 or ETS1 over-expression in HLHS iEECs could rescue dysfunctions in both endocardium and myocardium in HLHS. Our studies reveal a critical role of endocardial abnormality in causing HLHS, and provide a rationale for improving endocardial function in future regenerative strategies. Schematic illustration of the endocardial and myocardial defects in HLHS.

Abstract Background Across complex traits, common variants explain only a modest amount of variance, with SNP-heritability consistently below heritability estimates from close relatives. Here, we examined the contribution of rare variant to tobacco use risk in up to 26,000 individuals of European ancestry in the Trans-Omics for Precision Medicine (TOPMed) program with whole genome sequence (WGS;~30X coverage).Method We grouped about 35 million genetic variants by their minor allele frequencies (MAF) and linkage disequilibrium (LD) and estimated SNP-heritability for age of smoking initiation (N = 14,747), cigarettes smoked per day (N = 15,425), smoking cessation (N = 17,871) and initiation (N = 26,340) using linear mixed model. Rare variant population structure is detected and adjusted for by permutation procedure. We estimated an upper bound for narrow-sense heritability for tobacco use using available pedigrees consisting of close relatives in TOPMed.Results Rare variants with MAF 0.1–0.01%, mostly from non-protein altering region, accounted for 26% of variation in age of initiation and 15% for cessation. Follow-up analysis indicated that about one-third of these rare variants contribtion is potentially confounded with rare variants structure even after adjusting for principal components. After further conservative adjustment of population structure, we estimated SNP-based heritability to be 0.21 (SE = 0.08) for age of initiation, 0.15 (0.06) for cigarettes per day, 0.21 (0.09) for cessation, and 0.24 (0.07) for initiation, 1.8–4.5 times higher than previous SNP-based estimates. Our pedigree-based upper-bound for SNP-based heritability ranged from 0.18–0.35.Conclusion The substantial contribution of rare variants for several smoking phenotypes sheds light on the missing heritability and genetic etiology of tobacco use. It also informs fine-mapping strategies since the majority of the rare variant contribution was located in non-coding regulatory regions.

AbstractObjectivesInhibitors to the checkpoint proteins cytotoxic T‐lymphocyte‐associated protein 4 (CTLA‐4) and programmed cell death protein 1 (PD‐1) are becoming widely used in cancer treatment. However, a lack of understanding of the patient response to treatment limits accurate identification of potential responders to immunotherapy.MethodsIn this study, we assessed the expression of PD‐1 and CTLA‐4 on 19 leucocyte populations in the peripheral blood of 74 cancer patients. A reference data set for PD‐1 and CTLA‐4 was established for 40 healthy volunteers to determine the normal expression patterns for these checkpoint proteins.ResultsUnsupervised hierarchical clustering found four immune profiles shared across the solid tumor types, while chronic lymphocytic leukaemia patients had an immune profile largely unique to them. Furthermore, we measured these leucocyte populations on an additional cohort of 16 cancer patients receiving the PD‐1 inhibitor pembrolizumab in order to identify differences between responders and non‐responders, as well as compared to healthy volunteers (n = 20). We observed that cancer patients had pre‐treatment PD‐1 and CTLA‐4 expression on their leucocyte populations at different levels compared to healthy volunteers and identified two leucocyte populations positive for CTLA‐4 that had not been previously described. We found higher levels of PD‐1+ CD3+ CD4− CD8− cells in patients with progressive disease and have identified it as a potential biomarker of response, as well as identifying other significant differences in phenotypes between responders and non‐responders.ConclusionThese results are suggestive that categorisation of patients based on immune profiles may differentiate responders from non‐responders to immunotherapy for solid tumors.

Abstract A substantial number of chronic coronary syndrome (CCS) patients undergoing percutaneous coronary intervention (PCI) experience periprocedural myocardial injury or infarction. Accurate diagnosis of these PCI-related complications is required to guide further management given that their occurrence may be associated with increased risk of major adverse cardiac events (MACE). Due to lack of scientific data, the cut-off thresholds of post-PCI cardiac troponin (cTn) elevation used for defining periprocedural myocardial injury and infarction, have been selected based on expert consensus opinions, and their prognostic relevance remains unclear. In this Consensus Document from the ESC Working Group on Cellular Biology of the Heart and European Association of Percutaneous Cardiovascular Interventions (EAPCI), we recommend, whenever possible, the measurement of baseline (pre-PCI) cTn and post-PCI cTn values in all CCS patients undergoing PCI. We confirm the prognostic relevance of the post-PCI cTn elevation >5× 99th percentile URL threshold used to define type 4a myocardial infarction (MI). In the absence of periprocedural angiographic flow-limiting complications or electrocardiogram (ECG) and imaging evidence of new myocardial ischaemia, we propose the same post-PCI cTn cut-off threshold (>5× 99th percentile URL) be used to define prognostically relevant ‘major’ periprocedural myocardial injury. As both type 4a MI and major periprocedural myocardial injury are strong independent predictors of all-cause mortality at 1 year post-PCI, they may be used as quality metrics and surrogate endpoints for clinical trials. Further research is needed to evaluate treatment strategies for reducing the risk of major periprocedural myocardial injury, type 4a MI, and MACE in CCS patients undergoing PCI.

Abstract Funding Acknowledgements Type of funding sources: None. Background The incidence of respiratory failure and the provision of invasive and non-invasive mechanical ventilation (MV) in patients admitted to cardiac intensive care units (CICU) are increasing. While institutional MV volumes are associated with reduced mortality in medical and surgical ICUs, this relationship has not been characterized in the CICU population. Purpose By describing the relationship between institutional MV volume and outcomes in the CICUs, we hope to shed light on minimum volume benchmarks for providing MV. Methods National Canadian population-based data from 2005 to 2015 was used to identify patients admitted to CICUs requiring MV. CICUs were categorized into low (≤100), intermediate (101-300), and high (>300) volume centers based on spline knots identified in the association between annual MV volume and mortality (Figure). Outcomes of interests included all-cause in-hospital mortality, the proportion of patients requiring prolonged MV (>96 hours) and CICU length of stay (LOS). Results Among the 47,173 CICU admissions that required MV, 89.5% (42,200) required invasive mechanical ventilation. The median annual CICU MV volume was 127 (range 1-490). In-hospital mortality was lower in intermediate (29.2%, adjusted odds ratio [aOR] 0.84, 95% CI 0.72-0.97, p = 0.019) and high-volume (18.2%; aOR 0.82, 95% CI 0.66-1.02, p = 0.076) centers, compared to low volume centers (35.9%). The proportion of patients requiring prolonged MV was higher in low-volume (29.2%) compared to high-volume (14.8%, OR 0.70, 95% 0.55-0.89, p = 0.003) centers. Point estimates for mortality and prolonged MV were lower in PCI-capable and academic centers (Table). Significantly (p <0.01) lower CICU LOS was observed only in the subgroup of PCI-capable intermediate- and high-volume hospitals. Conclusions In a national dataset, we observed that higher CICU MV hospital volumes were associated with lower in-hospital mortality, CICU LOS, and fewer episodes of prolonged MV. Pending further validation, these data suggest minimum MV volume benchmarks for CICUs caring for patients with respiratory failure. Further research is warranted to explore these associations in more detail. Unadjusted volume-outcome relationshipsOutcomesGroup 1 Annual Volume ≤100Group 2 Annual Volume 101-300Group 3 Annual Volume >300Totalp-valueTotal N1770224351512047173In-hospital mortality6357 (35.0%)7122 (29.2%)933 (18.2%)14412 (30.6%)p < 0.0001Median CICU LOS(hours)85796679p < 0.0001Episodes of prolonged MV5161 (29.2%)5608 (23.0%)758 (14.8%)11527 (24.4%)p < 0.0001Abbreviations OR (odds ratio), RD (risk difference), CI (confidence interval), PCI (percutaneous coronary intervention), LOS (length of stay)Abstract Figure. Annual CICU MV volume and mortality