Endothelial function and dysfunction are central to the focal origin and regional development of atherosclerosis; however, an in vivo endothelial phenotypic footprint of susceptibility to ...atherosclerosis preceding pathological change remains elusive.
To conduct a comparative multi-site genomics study of arterial endothelial phenotype in atherosusceptible and atheroprotected regions.
Transcript profiles of freshly isolated endothelial cells from 7 discrete arterial regions in normal swine were analyzed to determine the steady state in vivo endothelial phenotypes in regions of varying susceptibilities to atherosclerosis. The most abundant common feature of the endothelium of all atherosusceptible regions was the upregulation of genes associated with endoplasmic reticulum (ER) stress. The unfolded protein response pathway, induced by ER stress, was therefore investigated in detail in endothelium of the atherosusceptible aortic arch and was found to be partially activated. ER transmembrane signal transducers IRE1alpha and ATF6alpha and their downstream effectors, but not PERK, were activated concomitant with a higher transcript expression of protein folding enzymes and chaperones, indicative of ER stress in vivo.
The findings demonstrate the prevalence of chronic endothelial ER stress and activated unfolded protein response in vivo at atherosusceptible arterial sites. We propose that chronic localized biological stress is linked to spatial susceptibility of the endothelium to the initiation of atherosclerosis.
Deciphering the impact of genetic variation on gene regulation is fundamental to understanding common, complex human diseases. Although histone modifications are important markers of gene regulatory ...elements of the genome, any specific histone modification has not been assayed in more than a few individuals in the human liver. As a result, the effects of genetic variation on histone modification states in the liver are poorly understood. Here, we generate the most comprehensive genome-wide dataset of two epigenetic marks, H3K4me3 and H3K27ac, and annotate thousands of putative regulatory elements in the human liver. We integrate these findings with genome-wide gene expression data collected from the same human liver tissues and high-resolution promoter-focused chromatin interaction maps collected from human liver-derived HepG2 cells. We demonstrate widespread functional consequences of natural genetic variation on putative regulatory element activity and gene expression levels. Leveraging these extensive datasets, we fine-map a total of 74 GWAS loci that have been associated with at least one complex phenotype. Our results reveal a repertoire of genes and regulatory mechanisms governing complex disease development and further the basic understanding of genetic and epigenetic regulation of gene expression in the human liver tissue.
Disrupted sleep is a symptom of many psychiatric disorders, including substance use disorders. Most drugs of abuse, including opioids, disrupt sleep. However, the extent and consequence of ...opioid-induced sleep disturbance, especially during chronic drug exposure, is understudied. We have previously shown that sleep disturbance alters voluntary morphine intake. Here, we examine the effects of acute and chronic morphine exposure on sleep. Using an oral self-administration paradigm, we show that morphine disrupts sleep, most significantly during the dark cycle in chronic morphine, with a concomitant sustained increase in neural activity in the Paraventricular Nucleus of the Thalamus (PVT). Morphine binds primarily to Mu Opioid Receptors (MORs), which are highly expressed in the PVT. Translating Ribosome Affinity Purification (TRAP)-Sequencing of PVT neurons that express MORs showed significant enrichment of the circadian entrainment pathway. To determine whether MOR + cells in the PVT mediate morphine-induced sleep/wake properties, we inhibited these neurons during the dark cycle while mice were self-administering morphine. This inhibition decreased morphine-induced wakefulness but not general wakefulness, indicating that MORs in the PVT contribute to opioid-specific wake alterations. Overall, our results suggest an important role for PVT neurons that express MORs in mediating morphine-induced sleep disturbance.
Abstract
Objectives
Ascertain and compare the performances of Automated Machine Learning (AutoML) tools on large, highly imbalanced healthcare datasets.
Materials and Methods
We generated a large ...dataset using historical de-identified administrative claims including demographic information and flags for disease codes in four different time windows prior to 2019. We then trained three AutoML tools on this dataset to predict six different disease outcomes in 2019 and evaluated model performances on several metrics.
Results
The AutoML tools showed improvement from the baseline random forest model but did not differ significantly from each other. All models recorded low area under the precision-recall curve and failed to predict true positives while keeping the true negative rate high. Model performance was not directly related to prevalence. We provide a specific use-case to illustrate how to select a threshold that gives the best balance between true and false positive rates, as this is an important consideration in medical applications.
Discussion
Healthcare datasets present several challenges for AutoML tools, including large sample size, high imbalance, and limitations in the available features. Improvements in scalability, combinations of imbalance-learning resampling and ensemble approaches, and curated feature selection are possible next steps to achieve better performance.
Conclusion
Among the three explored, no AutoML tool consistently outperforms the rest in terms of predictive performance. The performances of the models in this study suggest that there may be room for improvement in handling medical claims data. Finally, selection of the optimal prediction threshold should be guided by the specific practical application.
In the arterial circulation, regions of disturbed flow (DF), which are characterized by flow separation and transient vortices, are susceptible to atherogenesis, whereas regions of undisturbed ...laminar flow (UF) appear protected. Coordinated regulation of gene expression by endothelial cells (EC) may result in differing regional phenotypes that either favor or inhibit atherogenesis. Linearly amplified RNA from freshly isolated EC of DF (inner aortic arch) and UF (descending thoracic aorta) regions of normal adult pigs was used to profile differential gene expression reflecting the steady state in vivo. By using human cDNA arrays, ≈2,000 putatively differentially expressed genes were identified through false-discovery-rate statistical methods. A sampling of these genes was validated by quantitative realtime PCR and/or immunostaining en face. Biological pathway analysis revealed that in DF there was up-regulation of several broad-acting inflammatory cytokines and receptors, in addition to elements of the NF-κB system, which is consistent with a proinflammatory phenotype. However, the NF-κB complex was predominantly cytoplasmic (inactive) in both regions, and no significant differences were observed in the expression of key adhesion molecules for inflammatory cells associated with early atherogenesis. Furthermore, there was no histological evidence of inflammation. Protective profiles were observed in DF regions, notably an enhanced antioxidative gene expression. This study provides a public database of regional EC gene expression in a normal animal, implicates hemodynamics as a contributory mechanism to athero-susceptibility, and reveals the coexistence of pro- and antiatherosclerotic transcript profiles in susceptible regions. The introduction of additional risk factors may shift this balance to favor lesion development.
The principal line of investigation in Genome Wide Association Studies (GWAS) is the identification of main effects, that is individual Single Nucleotide Polymorphisms (SNPs) which are associated ...with the trait of interest, independent of other factors. A variety of methods have been proposed to this end, mostly statistical in nature and differing in assumptions and type of model employed. Moreover, for a given model, there may be multiple choices for the SNP genotype encoding. As an alternative to statistical methods, machine learning methods are often applicable. Typically, for a given GWAS, a single approach is selected and utilized to identify potential SNPs of interest. Even when multiple GWAS are combined through meta-analyses within a consortium, each GWAS is typically analyzed with a single approach and the resulting summary statistics are then utilized in meta-analyses.
In this work we use as case studies a Type 2 Diabetes (T2D) and a breast cancer GWAS to explore a diversity of applicable approaches spanning different methods and encoding choices. We assess similarity of these approaches based on the derived ranked lists of SNPs and, for each GWAS, we identify a subset of representative approaches that we use as an ensemble to derive a union list of top SNPs. Among these are SNPs which are identified by multiple approaches as well as several SNPs identified by only one or a few of the less frequently used approaches. The latter include SNPs from established loci and SNPs which have other supporting lines of evidence in terms of their potential relevance to the traits.
Not every main effect analysis method is suitable for every GWAS, but for each GWAS there are typically multiple applicable methods and encoding options. We suggest a workflow for a single GWAS, extensible to multiple GWAS from consortia, where representative approaches are selected among a pool of suitable options, to yield a more comprehensive set of SNPs, potentially including SNPs that would typically be missed with the most popular analyses, but that could provide additional valuable insights for follow-up.
Abbreviations HCC Hepatocellular Carcinoma TLS Tertiary lymphoid structures TGFα transforming growth factor alpha CTNNB1 gene encoding beta-catenin PD-1 programmed cell death protein 1 IgG ...immunoglobulin G (control) IF immunofluorescence PD-L1 programmed cell death protein 1 ligand MHC-I major histocompatibility complex class 1 Treg regulatory T cell CTLA4 cytotoxic T-lymphocyte-associated protein 4 HAVCR2 hepatitis A virus cellular receptor 2 LAG3 lymphocyte-activation gene 3 TIGIT T cell immunoreceptor with Ig and ITIM domains Dear Editor Combinatorial immunotherapy has provided patients with advanced hepatocellular carcinoma (HCC) the potential for long-term survival. ...there is an unmet need for precision modeling to understand the different responses and uncover predictive biomarkers for treatment stratification. Remarkably, the combinatorial immunotherapy significantly reduced the burden of large tumors ( ≥$ \ge \;$2 mm-size) compared with IgG isotype control in N90-CTNNB1OE;TP53KO animals, but not in the MycOE;TGFαOE -driven model (Figure 1A, Supplementary Figure S3). ...immunologically “hot” N90-CTNNB1OE;TP53KO tumors responded more to combinatorial immunotherapy than immunologically “cold” MycOE;TGFαOE tumors. Next, we derived TLS-maturation and TLS-initiation scores based on the expression levels of these genes and found both to be significantly higher in N90-CTNNB1OE;TP53−/− versus MycOE;TGFαOE samples prior to and post combinatorial immunotherapy (Figure 1D, Supplementary Figure S5E). ...increased TLS initiation and maturation in the livers of N90-CTNNB1OE;TP53−/− mice were associated with their higher sensitivity to combinatorial immunotherapy. ...we examined which gene ontology pathways are significantly enriched in response to combinatorial immunotherapy.
Newly differentiated pancreatic β cells lack proper insulin secretion profiles of mature functional β cells. The global gene expression differences between paired immature and mature β cells have ...been studied, but the dynamics of transcriptional events, correlating with temporal development of glucose-stimulated insulin secretion (GSIS), remain to be fully defined. This aspect is important to identify which genes and pathways are necessary for β-cell development or for maturation, as defective insulin secretion is linked with diseases such as diabetes. In this study, we assayed through RNA sequencing the global gene expression across six β-cell developmental stages in mice, spanning from β-cell progenitor to mature β cells. A computational pipeline then selected genes differentially expressed with respect to progenitors and clustered them into groups with distinct temporal patterns associated with biological functions and pathways. These patterns were finally correlated with experimental GSIS, calcium influx, and insulin granule formation data. Gene expression temporal profiling revealed the timing of important biological processes across β-cell maturation, such as the deregulation of β-cell developmental pathways and the activation of molecular machineries for vesicle biosynthesis and transport, signal transduction of transmembrane receptors, and glucose-induced Ca
influx, which were established over a week before β-cell maturation completes. In particular, β cells developed robust insulin secretion at high glucose several days after birth, coincident with the establishment of glucose-induced calcium influx. Yet the neonatal β cells displayed high basal insulin secretion, which decreased to the low levels found in mature β cells only a week later. Different genes associated with calcium-mediated processes, whose alterations are linked with insulin resistance and deregulation of glucose homeostasis, showed increased expression across β-cell stages, in accordance with the temporal acquisition of proper GSIS. Our temporal gene expression pattern analysis provided a comprehensive database of the underlying molecular components and biological mechanisms driving β-cell maturation at different temporal stages, which are fundamental for better control of the
production of functional β cells from human embryonic stem/induced pluripotent cell for transplantation-based type 1 diabetes therapy.
Background
Unlike arteries, in which regionally distinct hemodynamics are associated with phenotypic heterogeneity, the relationships between endocardial endothelial cell phenotype and ...intraventricular flow remain largely unexplored. We investigated regional differences in left ventricular wall shear stress and their association with endocardial endothelial cell gene expression.
Methods and Results
Local wall shear stress was calculated from 4‐dimensional flow magnetic resonance imaging in 3 distinct regions of human (n=8) and pig (n=5) left ventricle: base, adjacent to the outflow tract; midventricle; and apex. In both species, wall shear stress values were significantly lower in the apex and midventricle relative to the base; oscillatory shear index was elevated in the apex. RNA sequencing of the endocardial endothelial cell transcriptome in pig left ventricle (n=8) at a false discovery rate ≤10% identified 1051 genes differentially expressed between the base and the apex and 327 between the base and the midventricle; no differentially expressed genes were detected at this false discovery rate between the apex and the midventricle. Enrichment analyses identified apical upregulation of genes associated with translation initiation including mammalian target of rapamycin, and eukaryotic initiation factor 2 signaling. Genes of mitochondrial dysfunction and oxidative phosphorylation were also consistently upregulated in the left ventricular apex, as were tissue factor pathway inhibitor (mean 50‐fold) and prostacyclin synthase (5‐fold)—genes prominently associated with antithrombotic protection.
Conclusions
We report the first spatiotemporal measurements of wall shear stress within the left ventricle and linked regional hemodynamics to heterogeneity in ventricular endothelial gene expression, most notably to translation initiation and anticoagulation properties in the left ventricular apex, in which oscillatory shear index is increased and wall shear stress is decreased.
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