LungMAP Portal Ecosystem: Systems-level Exploration of the Lung

An improved understanding of the human lung necessitates advanced systems models informed by an ever-increasing repertoire of molecular omics, cellular imaging, and pathological datasets. To centralize and standardize information across broad lung research efforts, we expanded the LungMAP.net website into a new gateway portal. This portal connects a broad spectrum of research networks, bulk and single-cell multiomics data, and a diverse collection of image data that span mammalian lung development and disease. The data are standardized across species and technologies using harmonized data and metadata models that leverage recent advances, including those from the Human Cell Atlas, diverse ontologies, and the LungMAP CellCards initiative. To cultivate future discoveries, we have aggregated a diverse collection of single-cell atlases for multiple species (human, rhesus, and mouse) to enable consistent queries across technologies, cohorts, age, disease, and drug treatment. These atlases are provided as independent and integrated queryable datasets, with an emphasis on dynamic visualization, figure generation, reanalysis, cell-type curation, and automated reference-based classification of user-provided single-cell genomics datasets (Azimuth). As this resource grows, we intend to increase the breadth of available interactive interfaces, supported data types, data portals and datasets from LungMAP, and external research efforts.

Bering: joint cell segmentation and annotation for spatial transcriptomics with transferred graph embeddings

Single-cell spatial transcriptomics such as in-situ hybridization or sequencing technologies can provide subcellular resolution that enables the identification of individual cell identities, locations, and a deep understanding of subcellular mechanisms. However, accurate segmentation and annotation that allows individual cell boundaries to be determined remains a major challenge that limits all the above and downstream insights. Current machine learning methods heavily rely on nuclei or cell body staining, resulting in the significant loss of both transcriptome depth and the limited ability to learn latent representations of spatial colocalization relationships. Here, we propose Bering, a graph deep learning model that leverages transcript colocalization relationships for joint noise-aware cell segmentation and molecular annotation in 2D and 3D spatial transcriptomics data. Graph embeddings for the cell annotation are transferred as a component of multi-modal input for cell segmentation, which is employed to enrich gene relationships throughout the process. To evaluate performance, we benchmarked Bering with state-of-the-art methods and observed significant improvement in cell segmentation accuracies and numbers of detected transcripts across various spatial technologies and tissues. To streamline segmentation processes, we constructed expansive pre-trained models, which yield high segmentation accuracy in new data through transfer learning and self-distillation, demonstrating the generalizability of Bering.

Guided construction of single cell reference for human and mouse lung

Accurate cell type identification is a key and rate-limiting step in single-cell data analysis. Single-cell references with comprehensive cell types, reproducible and functionally validated cell identities, and common nomenclatures are much needed by the research community for automated cell type annotation, data integration, and data sharing. Here, we develop a computational pipeline utilizing the LungMAP CellCards as a dictionary to consolidate single-cell transcriptomic datasets of 104 human lungs and 17 mouse lung samples to construct LungMAP single-cell reference (CellRef) for both normal human and mouse lungs. CellRefs define 48 human and 40 mouse lung cell types catalogued from diverse anatomic locations and developmental time points. We demonstrate the accuracy and stability of LungMAP CellRefs and their utility for automated cell type annotation of both normal and diseased lungs using multiple independent methods and testing data. We develop user-friendly web interfaces for easy access and maximal utilization of the LungMAP CellRefs.

Single cell transcriptomic analysis of HPV16-infected epithelium identifies a keratinocyte subpopulation implicated in cancer

Persistent HPV16 infection is a major cause of the global cancer burden. The viral life cycle is dependent on the differentiation program of stratified squamous epithelium, but the landscape of keratinocyte subpopulations which support distinct phases of the viral life cycle has yet to be elucidated. Here, single cell RNA sequencing of HPV16 infected compared to uninfected organoids identifies twelve distinct keratinocyte populations, with a subset mapped to reconstruct their respective 3D geography in stratified squamous epithelium. Instead of conventional terminally differentiated cells, an HPV-reprogrammed keratinocyte subpopulation (HIDDEN cells) forms the surface compartment and requires overexpression of the ELF3/ESE-1 transcription factor. HIDDEN cells are detected throughout stages of human carcinogenesis including primary human cervical intraepithelial neoplasias and HPV positive head and neck cancers, and a possible role in promoting viral carcinogenesis is supported by TCGA analyses. Single cell transcriptome information on HPV-infected versus uninfected epithelium will enable broader studies of the role of individual keratinocyte subpopulations in tumor virus infection and cancer evolution.

Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record?

BACKGROUND

In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as ​​reflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to identify informative patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients.

METHODS

We collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern.

RESULTS

With these analyses, we identified mapping issues faced in seven out of 15 sites. We also identified nuances in data collection and variable definition for the various sites. Temporal trend analyses may support the use of laboratory test result missingness patterns in identifying severe COVID-19 patients. Lastly, using missingness patterns, we determined relationships between various labs that reflect clinical behaviors.

CONCLUSION

In this work, we use computational approaches to relate missingness patterns to hospital treatment capacity and highlight the heterogeneity of looking at COVID-19 over time and at multiple sites, where there might be different phases, policies, etc. Changes in missingness could suggest a change in a patient's condition, and patterns of missingness among laboratory measurements could potentially identify clinical outcomes. This allows sites to consider missing data as informative to analyses and help researchers identify which sites are better poised to study particular questions.

Hospitalizations Associated With Mental Health Conditions Among Adolescents in the US and France During the COVID-19 Pandemic

Importance

The COVID-19 pandemic has been associated with an increase in mental health diagnoses among adolescents, though the extent of the increase, particularly for severe cases requiring hospitalization, has not been well characterized. Large-scale federated informatics approaches provide the ability to efficiently and securely query health care data sets to assess and monitor hospitalization patterns for mental health conditions among adolescents.

Objective

To estimate changes in the proportion of hospitalizations associated with mental health conditions among adolescents following onset of the COVID-19 pandemic.

Design, Setting, and Participants

This retrospective, multisite cohort study of adolescents 11 to 17 years of age who were hospitalized with at least 1 mental health condition diagnosis between February 1, 2019, and April 30, 2021, used patient-level data from electronic health records of 8 children's hospitals in the US and France.

Main Outcomes and Measures

Change in the monthly proportion of mental health condition-associated hospitalizations between the prepandemic (February 1, 2019, to March 31, 2020) and pandemic (April 1, 2020, to April 30, 2021) periods using interrupted time series analysis.

Results

There were 9696 adolescents hospitalized with a mental health condition during the prepandemic period (5966 [61.5%] female) and 11 101 during the pandemic period (7603 [68.5%] female). The mean (SD) age in the prepandemic cohort was 14.6 (1.9) years and in the pandemic cohort, 14.7 (1.8) years. The most prevalent diagnoses during the pandemic were anxiety (6066 [57.4%]), depression (5065 [48.0%]), and suicidality or self-injury (4673 [44.2%]). There was an increase in the proportions of monthly hospitalizations during the pandemic for anxiety (0.55%; 95% CI, 0.26%-0.84%), depression (0.50%; 95% CI, 0.19%-0.79%), and suicidality or self-injury (0.38%; 95% CI, 0.08%-0.68%). There was an estimated 0.60% increase (95% CI, 0.31%-0.89%) overall in the monthly proportion of mental health-associated hospitalizations following onset of the pandemic compared with the prepandemic period.

Conclusions and Relevance

In this cohort study, onset of the COVID-19 pandemic was associated with increased hospitalizations with mental health diagnoses among adolescents. These findings support the need for greater resources within children's hospitals to care for adolescents with mental health conditions during the pandemic and beyond.

CellDrift: inferring perturbation responses in temporally sampled single-cell data

Cells and tissues respond to perturbations in multiple ways that can be sensitively reflected in the alterations of gene expression. Current approaches to finding and quantifying the effects of perturbations on cell-level responses over time disregard the temporal consistency of identifiable gene programs. To leverage the occurrence of these patterns for perturbation analyses, we developed CellDrift (https://github.com/KANG-BIOINFO/CellDrift), a generalized linear model-based functional data analysis method that is capable of identifying covarying temporal patterns of various cell types in response to perturbations. As compared to several other approaches, CellDrift demonstrated superior performance in the identification of temporally varied perturbation patterns and the ability to impute missing time points. We applied CellDrift to multiple longitudinal datasets, including COVID-19 disease progression and gastrointestinal tract development, and demonstrated its ability to identify specific gene programs associated with sequential biological processes, trajectories and outcomes.

International electronic health record-derived post-acute sequelae profiles of COVID-19 patients

The risk profiles of post-acute sequelae of COVID-19 (PASC) have not been well characterized in multi-national settings with appropriate controls. We leveraged electronic health record (EHR) data from 277 international hospitals representing 414,602 patients with COVID-19, 2.3 million control patients without COVID-19 in the inpatient and outpatient settings, and over 221 million diagnosis codes to systematically identify new-onset conditions enriched among patients with COVID-19 during the post-acute period. Compared to inpatient controls, inpatient COVID-19 cases were at significant risk for angina pectoris (RR 1.30, 95% CI 1.09–1.55), heart failure (RR 1.22, 95% CI 1.10–1.35), cognitive dysfunctions (RR 1.18, 95% CI 1.07–1.31), and fatigue (RR 1.18, 95% CI 1.07–1.30). Relative to outpatient controls, outpatient COVID-19 cases were at risk for pulmonary embolism (RR 2.10, 95% CI 1.58–2.76), venous embolism (RR 1.34, 95% CI 1.17–1.54), atrial fibrillation (RR 1.30, 95% CI 1.13–1.50), type 2 diabetes (RR 1.26, 95% CI 1.16–1.36) and vitamin D deficiency (RR 1.19, 95% CI 1.09–1.30). Outpatient COVID-19 cases were also at risk for loss of smell and taste (RR 2.42, 95% CI 1.90–3.06), inflammatory neuropathy (RR 1.66, 95% CI 1.21–2.27), and cognitive dysfunction (RR 1.18, 95% CI 1.04–1.33). The incidence of post-acute cardiovascular and pulmonary conditions decreased across time among inpatient cases while the incidence of cardiovascular, digestive, and metabolic conditions increased among outpatient cases. Our study, based on a federated international network, systematically identified robust conditions associated with PASC compared to control groups, underscoring the multifaceted cardiovascular and neurological phenotype profiles of PASC.

International comparisons of laboratory values from the 4CE collaborative to predict COVID-19 mortality

Given the growing number of prediction algorithms developed to predict COVID-19 mortality, we evaluated the transportability of a mortality prediction algorithm using a multi-national network of healthcare systems. We predicted COVID-19 mortality using baseline commonly measured laboratory values and standard demographic and clinical covariates across healthcare systems, countries, and continents. Specifically, we trained a Cox regression model with nine measured laboratory test values, standard demographics at admission, and comorbidity burden pre-admission. These models were compared at site, country, and continent level. Of the 39,969 hospitalized patients with COVID-19 (68.6% male), 5717 (14.3%) died. In the Cox model, age, albumin, AST, creatine, CRP, and white blood cell count are most predictive of mortality. The baseline covariates are more predictive of mortality during the early days of COVID-19 hospitalization. Models trained at healthcare systems with larger cohort size largely retain good transportability performance when porting to different sites. The combination of routine laboratory test values at admission along with basic demographic features can predict mortality in patients hospitalized with COVID-19. Importantly, this potentially deployable model differs from prior work by demonstrating not only consistent performance but also reliable transportability across healthcare systems in the US and Europe, highlighting the generalizability of this model and the overall approach.

Spaceflight Analogue Culture Enhances the Host-Pathogen Interaction Between Salmonella and a 3-D Biomimetic Intestinal Co-Culture Model

Physical forces associated with spaceflight and spaceflight analogue culture regulate a wide range of physiological responses by both bacterial and mammalian cells that can impact infection. However, our mechanistic understanding of how these environments regulate host-pathogen interactions in humans is poorly understood. Using a spaceflight analogue low fluid shear culture system, we investigated the effect of Low Shear Modeled Microgravity (LSMMG) culture on the colonization of Salmonella Typhimurium in a 3-D biomimetic model of human colonic epithelium containing macrophages. RNA-seq profiling of stationary phase wild type and Δhfq mutant bacteria alone indicated that LSMMG culture induced global changes in gene expression in both strains and that the RNA binding protein Hfq played a significant role in regulating the transcriptional response of the pathogen to LSMMG culture. However, a core set of genes important for adhesion, invasion, and motility were commonly induced in both strains. LSMMG culture enhanced the colonization (adherence, invasion and intracellular survival) of Salmonella in this advanced model of intestinal epithelium using a mechanism that was independent of Hfq. Although S. Typhimurium Δhfq mutants are normally defective for invasion when grown as conventional shaking cultures, LSMMG conditions unexpectedly enabled high levels of colonization by an isogenic Δhfq mutant. In response to infection with either the wild type or mutant, host cells upregulated transcripts involved in inflammation, tissue remodeling, and wound healing during intracellular survival. Interestingly, infection by the Δhfq mutant led to fewer transcriptional differences between LSMMG- and control-infected host cells relative to infection with the wild type strain. This is the first study to investigate the effect of LSMMG culture on the interaction between S. Typhimurium and a 3-D model of human intestinal tissue. These findings advance our understanding of how physical forces can impact the early stages of human enteric salmonellosis.

Data Augmentation Using Generative Adversarial Networks for Multi-Class Segmentation of Lung Confocal IF Images

The human lung is a complex organ with high cellular heterogeneity, and its development and maintenance require interactive gene networks and dynamic cross-talk among multiple cell types. We focus on the confocal immunofluorescent (IF) images of lung tissues from the LungMAP database to reveal lung development. Using the current state-of-the-art deep learning-based model, the authors consider obtaining accurate multi-class segmentation of lung confocal IF images. One of the primary bottlenecks in using deep Convolutional Neural Network (CNN) models is the lack of availability of large-scale training or ground-truth segmentation labels. Then, we implement the multi-class segmentation with Generative Adversarial Network (GAN) models to expand the training dataset, improve overall segmentation accuracy, and discuss the effectiveness of created synthetic images in the segmentation of IF images. Consequently, experimental results indicated that 15.1% increased the accuracy of six-class segmentation using Mask R-CNN. In particular, the accuracy of our few data was mainly improved by using our proposed method. Therefore, the synthetic dataset can moderate the imbalanced data and be used for expanding the dataset.

Endosomal Sequestration of TLR4 Antibody Induces Myeloid-Derived Suppressor Cells and Reverses Acute Type 1 Diabetes

We previously showed that treating NOD mice with an agonistic monoclonal anti-TLR4/MD2 antibody (TLR4-Ab) reversed acute type 1 diabetes (T1D). Here, we show that TLR4-Ab reverses T1D by induction of myeloid-derived suppressor cells (MDSCs). Unbiased gene expression analysis after TLR4-Ab treatment demonstrated upregulation of genes associated with CD11b+Ly6G+ myeloid cells and downregulation of T-cell genes. Further RNA sequencing of purified, TLR4-Ab-treated CD11b+ cells showed significant upregulation of genes associated with bone marrow-derived CD11b+ cells and innate immune system genes. TLR4-Ab significantly increased percentages and numbers of CD11b+ cells. TLR4-Ab-induced CD11b+ cells, derived ex vivo from TLR4-Ab-treated mice, suppress T cells, and TLR4-Ab-conditioned bone marrow cells suppress acute T1D when transferred into acutely diabetic mice. Thus, the TLR4-Ab-induced CD11b+ cells, by the currently accepted definition, are MDSCs able to reverse T1D. To understand the TLR4-Ab mechanism, we compared TLR4-Ab with TLR4 agonist lipopolysaccharide (LPS), which cannot reverse T1D. TLR4-Ab remains sequestered at least 48 times longer than LPS within early endosomes, alters TLR4 signaling, and downregulates inflammatory genes and proteins, including nuclear factor-κB. TLR4-Ab in the endosome, therefore, induces a sustained, attenuated inflammatory response, providing an ideal "second signal" for the activation/maturation of MDSCs that can reverse acute T1D.

A census of the lung: CellCards from LungMAP

The human lung plays vital roles in respiration, host defense, and basic physiology. Recent technological advancements such as single-cell RNA sequencing and genetic lineage tracing have revealed novel cell types and enriched functional properties of existing cell types in lung. The time has come to take a new census. Initiated by members of the NHLBI-funded LungMAP Consortium and aided by experts in the lung biology community, we synthesized current data into a comprehensive and practical cellular census of the lung. Identities of cell types in the normal lung are captured in individual cell cards with delineation of function, markers, developmental lineages, heterogeneity, regenerative potential, disease links, and key experimental tools. This publication will serve as the starting point of a live, up-to-date guide for lung research at https://www.lungmap.net/cell-cards/. We hope that Lung CellCards will promote the community-wide effort to establish, maintain, and restore respiratory health.

An interactive single cell web portal identifies gene and cell networks in COVID-19 host responses

Numerous studies have provided single-cell transcriptome profiles of host responses to SARS-CoV-2 infection. Critically lacking however is a data mine that allows users to compare and explore cell profiles to gain insights and develop new hypotheses. To accomplish this, we harmonized datasets from COVID-19 and other control condition blood, bronchoalveolar lavage, and tissue samples, and derived a compendium of gene signature modules per cell type, subtype, clinical condition, and compartment. We demonstrate approaches to interacting with, exploring, and functional evaluating these modules via a new interactive web portal ToppCell (http://toppcell.cchmc.org/). As examples, we develop three hypotheses: (1) alternatively-differentiated monocyte-derived macrophages form a multicelllar signaling cascade that drives T cell recruitment and activation; (2) COVID-19-generated platelet subtypes exhibit dramatically altered potential to adhere, coagulate, and thrombose; and (3) extrafollicular B maturation is driven by a multilineage cell activation network that expresses an ensemble of genes strongly associated with risk for developing post-viral autoimmunity.

Stratification of risk of progression to colectomy in ulcerative colitis via measured and predicted gene expression

An important goal of clinical genomics is to be able to estimate the risk of adverse disease outcomes. Between 5% and 10% of individuals with ulcerative colitis (UC) require colectomy within 5 years of diagnosis, but polygenic risk scores (PRSs) utilizing findings from genome-wide association studies (GWASs) are unable to provide meaningful prediction of this adverse status. By contrast, in Crohn disease, gene expression profiling of GWAS-significant genes does provide some stratification of risk of progression to complicated disease in the form of a transcriptional risk score (TRS). Here, we demonstrate that a measured TRS based on bulk rectal gene expression in the PROTECT inception cohort study has a positive predictive value approaching 50% for colectomy. Single-cell profiling demonstrates that the genes are active in multiple diverse cell types from both the epithelial and immune compartments. Expression quantitative trait locus (QTL) analysis identifies genes with differential effects at baseline and week 52 follow-up, but for the most part, differential expression associated with colectomy risk is independent of local genetic regulation. Nevertheless, a predicted polygenic transcriptional risk score (PPTRS) derived by summation of transcriptome-wide association study (TWAS) effects identifies UC-affected individuals at 5-fold elevated risk of colectomy with data from the UK Biobank population cohort studies, independently replicated in an NIDDK-IBDGC dataset. Prediction of gene expression from relatively small transcriptome datasets can thus be used in conjunction with TWASs for stratification of risk of disease complications.

Cancer Informatics for Cancer Centers: Scientific Drivers for Informatics, Data Science, and Care in Pediatric, Adolescent, and Young Adult Cancer

Cancer Informatics for Cancer Centers (CI4CC) is a grassroots, nonprofit 501c3 organization intended to provide a focused national forum for engagement of senior cancer informatics leaders, primarily aimed at academic cancer centers anywhere in the world but with a special emphasis on the 70 National Cancer Institute-funded cancer centers. This consortium has regularly held topic-focused biannual face-to-face symposiums. These meetings are a place to review cancer informatics and data science priorities and initiatives, providing a forum for discussion of the strategic and pragmatic issues that we faced at our respective institutions and cancer centers. Here, we provide meeting highlights from the latest CI4CC Symposium, which was delayed from its original April 2020 schedule because of the COVID-19 pandemic and held virtually over three days (September 24, October 1, and October 8) in the fall of 2020. In addition to the content presented, we found that holding this event virtually once a week for 6 hours was a great way to keep the kind of deep engagement that a face-to-face meeting engenders. This is the second such publication of CI4CC Symposium highlights, the first covering the meeting that took place in Napa, California, from October 14-16, 2019. We conclude with some thoughts about using data science to learn from every child with cancer, focusing on emerging activities of the National Cancer Institute's Childhood Cancer Data Initiative.

A First-In-Class, Humanized Antibody Targeting Alternatively Spliced Tissue Factor: Preclinical Evaluation in an Orthotopic Model of Pancreatic Ductal Adenocarcinoma

In 2021, pancreatic ductal adenocarcinoma (PDAC) is the 3^rd leading cause of cancer deaths in the United States. This is largely due to a lack of symptoms and limited treatment options, which extend survival by only a few weeks. There is thus an urgent need to develop new therapies effective against PDAC. Previously, we have shown that the growth of PDAC cells is suppressed when they are co-implanted with RabMab1, a rabbit monoclonal antibody specific for human alternatively spliced tissue factor (asTF). Here, we report on humanization of RabMab1, evaluation of its binding characteristics, and assessment of its in vivo properties. hRabMab1 binds asTF with a K_D in the picomolar range; suppresses the migration of high-grade Pt45.P1 cells in Boyden chamber assays; has a long half-life in circulation (~ 5 weeks); and significantly slows the growth of pre-formed orthotopic Pt45.P1 tumors in athymic nude mice when administered intravenously. Immunohistochemical analysis of tumor tissue demonstrates the suppression of i) PDAC cell proliferation, ii) macrophage infiltration, and iii) neovascularization, whereas RNAseq analysis of tumor tissue reveals the suppression of pathways that promote cell division and focal adhesion. This is the first proof-of-concept study whereby a novel biologic targeting asTF has been investigated as a systemically administered single agent, with encouraging results. Given that hRabMab1 has a favorable PK profile and is able to suppress the growth of human PDAC cells in vivo, it comprises a promising candidate for further clinical development.

Implicating Gene and Cell Networks Responsible for Differential COVID-19 Host Responses via an Interactive Single Cell Web Portal

Numerous studies have provided single-cell transcriptome profiles of host responses to SARS-CoV-2 infection. Critically lacking however is a datamine that allows users to compare and explore cell profiles to gain insights and develop new hypotheses. To accomplish this, we harmonized datasets from COVID-19 and other control condition blood, bronchoalveolar lavage, and tissue samples, and derived a compendium of gene signature modules per cell type, subtype, clinical condition, and compartment. We demonstrate approaches to probe these via a new interactive web portal (http://toppcell.cchmc.org/COVID-19). As examples, we develop three hypotheses: (1) a multicellular signaling cascade among alternatively differentiated monocyte-derived macrophages whose tasks include T cell recruitment and activation; (2) novel platelet subtypes with drastically modulated expression of genes responsible for adhesion, coagulation and thrombosis; and (3) a multilineage cell activator network able to drive extrafollicular B maturation via an ensemble of genes strongly associated with risk for developing post-viral autoimmunity.

International Analysis of Electronic Health Records of Children and Youth Hospitalized With COVID-19 Infection in 6 Countries

IMPORTANCE

Additional sources of pediatric epidemiological and clinical data are needed to efficiently study COVID-19 in children and youth and inform infection prevention and clinical treatment of pediatric patients.

OBJECTIVE

To describe international hospitalization trends and key epidemiological and clinical features of children and youth with COVID-19.

DESIGN, SETTING, AND PARTICIPANTS

This retrospective cohort study included pediatric patients hospitalized between February 2 and October 10, 2020. Patient-level electronic health record (EHR) data were collected across 27 hospitals in France, Germany, Spain, Singapore, the UK, and the US. Patients younger than 21 years who tested positive for COVID-19 and were hospitalized at an institution participating in the Consortium for Clinical Characterization of COVID-19 by EHR were included in the study.

MAIN OUTCOMES AND MEASURES

Patient characteristics, clinical features, and medication use.

RESULTS

There were 347 males (52%; 95% CI, 48.5-55.3) and 324 females (48%; 95% CI, 44.4-51.3) in this study's cohort. There was a bimodal age distribution, with the greatest proportion of patients in the 0- to 2-year (199 patients [30%]) and 12- to 17-year (170 patients [25%]) age range. Trends in hospitalizations for 671 children and youth found discrete surges with variable timing across 6 countries. Data from this cohort mirrored national-level pediatric hospitalization trends for most countries with available data, with peaks in hospitalizations during the initial spring surge occurring within 23 days in the national-level and 4CE data. A total of 27 364 laboratory values for 16 laboratory tests were analyzed, with mean values indicating elevations in markers of inflammation (C-reactive protein, 83 mg/L; 95% CI, 53-112 mg/L; ferritin, 417 ng/mL; 95% CI, 228-607 ng/mL; and procalcitonin, 1.45 ng/mL; 95% CI, 0.13-2.77 ng/mL). Abnormalities in coagulation were also evident (D-dimer, 0.78 ug/mL; 95% CI, 0.35-1.21 ug/mL; and fibrinogen, 477 mg/dL; 95% CI, 385-569 mg/dL). Cardiac troponin, when checked (n = 59), was elevated (0.032 ng/mL; 95% CI, 0.000-0.080 ng/mL). Common complications included cardiac arrhythmias (15.0%; 95% CI, 8.1%-21.7%), viral pneumonia (13.3%; 95% CI, 6.5%-20.1%), and respiratory failure (10.5%; 95% CI, 5.8%-15.3%). Few children were treated with COVID-19-directed medications.

CONCLUSIONS AND RELEVANCE

This study of EHRs of children and youth hospitalized for COVID-19 in 6 countries demonstrated variability in hospitalization trends across countries and identified common complications and laboratory abnormalities in children and youth with COVID-19 infection. Large-scale informatics-based approaches to integrate and analyze data across health care systems complement methods of disease surveillance and advance understanding of epidemiological and clinical features associated with COVID-19 in children and youth.

What Every Reader Should Know About Studies Using Electronic Health Record Data but May Be Afraid to Ask

Coincident with the tsunami of COVID-19–related publications, there has been a surge of studies using real-world data, including those obtained from the electronic health record (EHR). Unfortunately, several of these high-profile publications were retracted because of concerns regarding the soundness and quality of the studies and the EHR data they purported to analyze. These retractions highlight that although a small community of EHR informatics experts can readily identify strengths and flaws in EHR-derived studies, many medical editorial teams and otherwise sophisticated medical readers lack the framework to fully critically appraise these studies. In addition, conventional statistical analyses cannot overcome the need for an understanding of the opportunities and limitations of EHR-derived studies. We distill here from the broader informatics literature six key considerations that are crucial for appraising studies utilizing EHR data: data completeness, data collection and handling (eg, transformation), data type (ie, codified, textual), robustness of methods against EHR variability (within and across institutions, countries, and time), transparency of data and analytic code, and the multidisciplinary approach. These considerations will inform researchers, clinicians, and other stakeholders as to the recommended best practices in reviewing manuscripts, grants, and other outputs from EHR-data derived studies, and thereby promote and foster rigor, quality, and reliability of this rapidly growing field.

International Comparisons of Harmonized Laboratory Value Trajectories to Predict Severe COVID-19: Leveraging the 4CE Collaborative Across 342 Hospitals and 6 Countries: A Retrospective Cohort Study

Objectives

To perform an international comparison of the trajectory of laboratory values among hospitalized patients with COVID-19 who develop severe disease and identify optimal timing of laboratory value collection to predict severity across hospitals and regions.

Design

Retrospective cohort study.

Setting

The Consortium for Clinical Characterization of COVID-19 by EHR (4CE), an international multi-site data-sharing collaborative of 342 hospitals in the US and in Europe.

Participants

Patients hospitalized with COVID-19, admitted before or after PCR-confirmed result for SARS-CoV-2.

Primary and secondary outcome measures

Patients were categorized as "ever-severe" or "never-severe" using the validated 4CE severity criteria. Eighteen laboratory tests associated with poor COVID-19-related outcomes were evaluated for predictive accuracy by area under the curve (AUC), compared between the severity categories. Subgroup analysis was performed to validate a subset of laboratory values as predictive of severity against a published algorithm. A subset of laboratory values (CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin) was compared between North American and European sites for severity prediction.

Results

Of 36,447 patients with COVID-19, 19,953 (43.7%) were categorized as ever-severe. Most patients (78.7%) were 50 years of age or older and male (60.5%). Longitudinal trajectories of CRP, albumin, LDH, neutrophil count, D-dimer, and procalcitonin showed association with disease severity. Significant differences of laboratory values at admission were found between the two groups. With the exception of D-dimer, predictive discrimination of laboratory values did not improve after admission. Sub-group analysis using age, D-dimer, CRP, and lymphocyte count as predictive of severity at admission showed similar discrimination to a published algorithm (AUC=0.88 and 0.91, respectively). Both models deteriorated in predictive accuracy as the disease progressed. On average, no difference in severity prediction was found between North American and European sites.

Conclusions

Laboratory test values at admission can be used to predict severity in patients with COVID-19. Prediction models show consistency across international sites highlighting the potential generalizability of these models.

Therapeutic Opportunities for Intestinal Angioectasia- Targeting PPARγ and Oxidative Stress

Recurrent and acute bleeding from intestinal tract angioectasia (AEC) presents a major challenge for clinical intervention. Current treatments are empiric, with frequent poor clinical outcomes. Improvements in understanding the pathophysiology of these lesions will help guide treatment. Using data from the US Food and Drug Administration (FDA)'s Adverse Event Reporting System (FAERS), we analyzed 12 million patient reports to identify drugs inversely correlated with gastrointestinal bleeding and potentially limiting AEC severity. FAERS analysis revealed that drugs used in patients with diabetes and those targeting PPARγ-related mechanisms were associated with decreased AEC phenotypes (P < 0.0001). Electronic health records (EHRs) at University of Cincinnati Hospital were analyzed to validate FAERS analysis. EHR data showed a 5.6% decrease in risk of AEC and associated phenotypes in patients on PPARγ agonists. Murine knockout models of AEC phenotypes were used to construct a gene-regulatory network of candidate drug targets and pathways, which revealed that wound healing, vasculature development and regulation of oxidative stress were impacted in AEC pathophysiology. Human colonic tissue was examined for expression differences across key pathway proteins, PPARγ, HIF1α, VEGF, and TGFβ1. In vitro analysis of human AEC tissues showed lower expression of PPARγ and TGFβ1 compared with controls (0.55 ± 0.07 and 0.49 ± 0.05). National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) RNA-Seq data was analyzed to substantiate human tissue findings. This integrative discovery approach showing altered expression of key genes involved in oxidative stress and injury repair mechanisms presents novel insight into AEC etiology, which will improve targeted mechanistic studies and more optimal medical therapy for AEC.

Mucosal Inflammatory and Wound Healing Gene Programs Reveal Targets for Stricturing Behavior in Pediatric Crohn's Disease

BACKGROUND AND AIMS

Ileal strictures are the major indication for resective surgery in Crohn's disease (CD). We aimed to define ileal gene programs present at diagnosis linked with future stricturing behavior during five year follow-up, and to identify potential small molecules to reverse these gene signatures.

METHODS

Antimicrobial serologies and pre-treatment ileal gene expression were assessed in a representative subset of 249 CD patients within the RISK multicenter pediatric CD inception cohort study, including 113 that are unique to this report. These data were used to define genes associated with stricturing behavior and for model testing to predict stricturing behavior. A bioinformatics approach to define small molecules which may reverse the stricturing gene signature was applied.

RESULTS

19 of the 249 patients developed isolated B2 stricturing behavior during follow-up, while 218 remained B1 inflammatory. Using deeper RNA sequencing than in our prior report, we have now defined an inflammatory gene signature including an oncostatin M co-expression signature, tightly associated with extra-cellular matrix (ECM) gene expression in those who developed stricturing complications. We further computationally prioritize small molecules targeting macrophage and fibroblast activation and angiogenesis which may reverse the stricturing gene signature. A model containing ASCA and CBir1 serologies and a refined eight ECM gene set was significantly associated with stricturing development by year five after diagnosis (AUC (95th CI) = 0.82 (0.7-0.94)).

CONCLUSION

An ileal gene program for macrophage and fibroblast activation is linked to stricturing complications in treatment naïve pediatric CD, and may inform novel small molecule therapeutic approaches.

Abstract 837: Different Disease States in Heart Have Distinct Cardiac Interstitial Cells Contributing to Fibrosis

Cardiac fibrosis is a grim consequence for almost all myocardial injuries. In myocardial infarction (MI), what starts as a protective scarring process to prevent ventricular wall rupture becomes a pathological remodeling of the tissue with the accumulation of excess extracellular matrix (ECM) proteins. Eventually, this adaptation impedes the mechanical and electrical properties of the myocardium resulting in heart failure. Recently, we showed that periostin (Postn) expressing resident cardiac fibroblasts (CFs) are a potential therapeutic target since they differentiate into the scar associated, matrix-producing myofibroblasts (MFs) after injury. In fact, deletion of these cells after an acute injury eliminates interstitial fibrosis but results in ventricular rupture which is a hallmark outcome of impaired ECM deposition during the acute phase of MI. On the other hand, ablation of these cells during a chronic injury such as pressure overload-induced cardiac fibrosis model, we observe sustained perivascular fibrosis. Previous studies report heterogeneity of origin and function for ECM producing cells associated with different cardiac diseases. Here we utilized several novel mouse models that permit lineage tracing of all activated MFs as well as perivascular mural cells in the heart to elucidate the role and fate of these distinct cardiac interstitial cells during fibrogenesis. Cells were lineage traced with a tamoxifen-inducible cre recombinase cDNA knock-in alleles (PostnMCM and Gli1CreER) in combination with a Rosa26-eGFP cre-dependent reporter. Hearts subjected to MI, TAC or Angiotensin injury were processed for extensive histological and RNAseq analyses. Results show that interstitial fibrosis in acute MI injury is a result of Postn+ MFs activity, whereas a subset of Gli1+ mural cells are responsible for the perivascular fibrosis observed after pressure overload models. Therefore, we concluded that pathological ECM deposition resulting in fibrosis comes from disease-specific specialized sub-populations of interstitial cells of the heart with distinct gene expressions and require manipulation of alternative cell- and state-specific therapeutic targets.

Single-cell RNA sequencing identifies inflammatory tissue T cells in eosinophilic esophagitis

T cell heterogeneity is highly relevant to allergic disorders. We resolved the heterogeneity of human tissue CD3+ T cells during allergic inflammation, focusing on a tissue-specific allergic disease, eosinophilic esophagitis (EoE). We investigated 1088 single T cells derived from patients with a spectrum of disease activity. Eight disparate tissue T cell subtypes (designated T1-T8) were identified, with T7 and T8 enriched in the diseased tissue. The phenotypes of T7 and T8 resemble putative Treg (FOXP3+) and effector Th2-like (GATA3+) cells, respectively. Prodigious levels of IL-5 and IL-13 were confined to HPGDS+ CRTH2+IL-17RB+FFAR3+CD4+ T8 effector Th2 cells. EoE severity closely paralleled a lipid/fatty acid-induced activation node highlighted by the expression of the short-chain fatty acid receptor FFAR3. Ligands for FFAR3 induced Th2 cytokine production from human and murine T cells, including in an in vivo allergy model. Therefore, we elucidated the defining characteristics of tissue-residing CD3+ T cells in EoE, a specific enrichment of CD4+ Treg and effector Th2 cells, confinement of type 2 cytokine production to the CD4+ effector population, a highly likely role for FFAR3 in amplifying local Th2 responses in EoE, and a resource to further dissect tissue lymphocytes and allergic responses.

The Pediatric Cell Atlas: Defining the Growth Phase of Human Development at Single-Cell Resolution

Single-cell gene expression analyses of mammalian tissues have uncovered profound stage-specific molecular regulatory phenomena that have changed the understanding of unique cell types and signaling pathways critical for lineage determination, morphogenesis, and growth. We discuss here the case for a Pediatric Cell Atlas as part of the Human Cell Atlas consortium to provide single-cell profiles and spatial characterization of gene expression across human tissues and organs. Such data will complement adult and developmentally focused HCA projects to provide a rich cytogenomic framework for understanding not only pediatric health and disease but also environmental and genetic impacts across the human lifespan.

Genetic and Transcriptomic Variation Linked to Neutrophil Granulocyte-Macrophage Colony-Stimulating Factor Signaling in Pediatric Crohn's Disease

BACKGROUND

Granulocyte-macrophage colony-stimulating factor auto-antibodies (GMAbs) suppress neutrophil-extrinsic GM-CSF signaling and increase risk for stricturing behavior in Crohn's disease (CD). We aimed to define clinical, genomic, and functional associations with neutrophil-intrinsic GM-CSF signaling.

METHODS

Missense mutations in CSF2RA, CSF2RB, JAK2, STAT5A, and STAT5B were identified using whole-exome sequencing in 543 pediatric inflammatory bowel disease (IBD) patients. Neutrophil-intrinsic GM-CSF signaling was defined using the GM-CSF-induced STAT5 stimulation index (GMSI) in 180 pediatric IBD patients and 26 non-IBD controls. Reduced GM-CSF signaling (GMSI-Lo) was defined as the 20th percentile within the control group. Variation in neutrophil phospho-protein abundance, bacterial killing, and the global pattern of gene expression with the GMSI was determined.

RESULTS

We validated 18 potentially damaging missense mutations in CSF2RA and CSF2RB. CSF2RA A17G carriage increased from 10% in those with intact neutrophil GMSI to 32% in those with low GMSI (P = 0.02). The frequency of reduced Staphylococcus aureus killing increased from 17% in those with intact neutrophil GMSI to 35% in GMSI-Lo neutrophils (P = 0.043). Crohn's disease neutrophils with low GMSI exhibited specific alterations in phospho-protein networks and genes regulating cytokine production, wound healing, and cell survival and proliferation. Stricturing behavior increased from 7% in patients with both low GMAb and intact GMSI to 64% in patients with both elevated GMAb and low GMSI (P < 0.0001).

CONCLUSIONS

Low/normal neutrophil-intrinsic GM-CSF signaling is associated with CSF2RA missense mutations, alterations in gene expression networks, and higher rates of disease complications in pediatric CD.

Spatial distribution of marker gene activity in the mouse lung during alveolarization

This data is a curated collection of visual images of gene expression patterns from the pre- and post-natal mouse lung, accompanied by associated mRNA probe sequences and RNA-Seq expression profiles. Mammalian lungs undergo significant growth and cellular differentiation before and after the transition to breathing air. Documenting normal lung development is an important step in understanding abnormal lung development, as well as the challenges faced during a preterm birth. Images in this dataset indicate the spatial distribution of mRNA transcripts for over 500 different genes that are active during lung development, as initially determined via RNA-Seq. Images were systematically acquired using high-throughput in situ hybridization with non-radioactive digoxigenin-labeled mRNA probes across mouse lungs from developmental time points E16.5, E18.5, P7, and P28. The dataset was produced as part of The Molecular Atlas of Lung Development Program (LungMAP) and is hosted at https://lungmap.net. This manuscript describes the nature of the data and the protocols for generating the dataset.

Ulcerative colitis mucosal transcriptomes reveal mitochondriopathy and personalized mechanisms underlying disease severity and treatment response

Molecular mechanisms driving disease course and response to therapy in ulcerative colitis (UC) are not well understood. Here, we use RNAseq to define pre-treatment rectal gene expression, and fecal microbiota profiles, in 206 pediatric UC patients receiving standardised therapy. We validate our key findings in adult and paediatric UC cohorts of 408 participants. We observe a marked suppression of mitochondrial genes and function across cohorts in active UC, and that increasing disease severity is notable for enrichment of adenoma/adenocarcinoma and innate immune genes. A subset of severity genes improves prediction of corticosteroid-induced remission in the discovery cohort; this gene signature is also associated with response to anti-TNFα and anti-α4β7 integrin in adults. The severity and therapeutic response gene signatures were in turn associated with shifts in microbes previously implicated in mucosal homeostasis. Our data provide insights into UC pathogenesis, and may prioritise future therapies for nonresponders to current approaches.

mTOR kinase inhibition reduces tissue factor expression and growth of pancreatic neuroendocrine tumors

Essentials Tissue factor (TF) isoforms are expressed in pancreatic neuroendocrine tumors (pNET). TF knockdown inhibits proliferation of human pNET cells in vitro. mTOR kinase inhibitor sapanisertib/MLN0128 suppresses TF expression in human pNET cells. Sapanisertib suppresses TF expression and activity and reduces the growth of pNET tumors in vivo. SUMMARY: Background Full-length tissue factor (flTF) and alternatively spliced TF (asTF) contribute to growth and spread of pancreatic ductal adenocarcinoma. It is unknown, however, if flTF and/or asTF contribute to the pathobiology of pancreatic neuroendocrine tumors (pNETs). Objective To assess TF expression in pNETs and the effects of mTOR complex 1/2 (mTORC1/2) inhibition on pNET growth. Methods Human pNET specimens were immunostained for TF. Human pNET cell lines QGP1 and BON were evaluated for TF expression and responsiveness to mTOR inhibition. shRNA were used to knock down TF in BON. TF cofactor activity was assessed using a two-step FXa generation assay. TF promoter activity was assessed using transient transfection of human TF promoter-driven reporter constructs into cells. Mice bearing orthotopic BON tumors were treated with the mTORC1/2 ATP site competitive inhibitor sapanisertib/MLN0128 (3 mg kg-1 , oral gavage) for 34 days. Results Immunostaining of pNET tissue revealed flTF and asTF expression. BON and QGP1 expressed both TF isoforms, with BON exhibiting higher levels. shRNA directed against TF suppressed BON proliferation in vitro. Treatment of BON with sapanisertib inhibited mTOR signaling and suppressed TF levels. BON tumors grown in mice treated with sapanisertib had significantly less TF protein and cofactor activity, and were smaller compared with tumors grown in control mice. Conclusions TF isoforms are expressed in pNETs. Sapanisertib suppresses TF mRNA and protein expression as well as TF cofactor activity in vitro and in vivo. Thus, further studies are warranted to evaluate the clinical utility of TF-suppressing mTORC1/2 inhibitor sapanisertib in pNET management.

Expression Profiling of Fibroblasts in Chronic and Acute Disease Models Reveals Novel Pathways in Kidney Fibrosis

BACKGROUND

Renal interstitial fibrosis results from activation and proliferation of fibroblasts to myofibroblasts, secretion and accumulation of extracellular matrix, and displacement of normal renal tubules. In contrast to chronic renal disease, acute injury may be repaired, a process that includes a decrease in the number of myofibroblasts in the interstitium and degradation of the accumulated extracellular matrix, leaving little evidence of prior injury.

METHODS

To investigate whether activated fibroblasts demonstrate changes in gene expression that correspond with regression after acute injury but are not observed in chronic models of fibrosis, we used microarrays to analyze gene expression patterns among fibroblast populations at different stages of injury or repair. We then mined the data for signaling pathways in fibroblasts corresponding to the acute proliferative, regression, and chronic phases of renal injury.

RESULTS

We identified multiple gene clusters with changes that correlate with the three phases of renal injury, including changes in levels of receptors for the antifibrotic factor PGE2. In adult renal fibroblast cultures, PGE2 was able to upregulate many genes that are suppressed by the profibrotic cytokine TGF-β, whereas many PGE2-downregulated genes were activated by TGF-β. High levels of TGF-β suppressed expression of a subset of PG receptors in fibroblast cultures, making these cells resistant to any effects of PGE2.

CONCLUSIONS

Inherent gene expression changes in activated fibroblasts accompany the transition from AKI to repair and regeneration. In chronic models, however, activated fibroblasts are resistant to the antifibrotic effects of PGE2 due to suppression of a subset of PGE receptors.

H3K9 methyltransferases and demethylases control lung tumor-propagating cells and lung cancer progression

Epigenetic regulators are attractive anticancer targets, but the promise of therapeutic strategies inhibiting some of these factors has not been proven in vivo or taken into account tumor cell heterogeneity. Here we show that the histone methyltransferase G9a, reported to be a therapeutic target in many cancers, is a suppressor of aggressive lung tumor-propagating cells (TPCs). Inhibition of G9a drives lung adenocarcinoma cells towards the TPC phenotype by de-repressing genes which regulate the extracellular matrix. Depletion of G9a during tumorigenesis enriches tumors in TPCs and accelerates disease progression metastasis. Depleting histone demethylases represses G9a-regulated genes and TPC phenotypes. Demethylase inhibition impairs lung adenocarcinoma progression in vivo. Therefore, inhibition of G9a is dangerous in certain cancer contexts, and targeting the histone demethylases is a more suitable approach for lung cancer treatment. Understanding cellular context and specific tumor populations is critical when targeting epigenetic regulators in cancer for future therapeutic development.

Microbiota-sensitive epigenetic signature predicts inflammation in Crohn's disease

Altered response to the intestinal microbiota strongly associates with inflammatory bowel disease (IBD); however, how commensal microbial cues are integrated by the host during the pathogenesis of IBD is not understood. Epigenetics represents a potential mechanism that could enable intestinal microbes to modulate transcriptional output during the development of IBD. Here, we reveal a histone methylation signature of intestinal epithelial cells isolated from the terminal ilea of newly diagnosed pediatric IBD patients. Genes characterized by significant alterations in histone H3-lysine 4 trimethylation (H3K4me3) showed differential enrichment in pathways involving immunoregulation, cell survival and signaling, and metabolism. Interestingly, a large subset of these genes was epigenetically regulated by microbiota in mice and several microbiota-sensitive epigenetic targets demonstrated altered expression in IBD patients. Remarkably though, a substantial proportion of these genes exhibited H3K4me3 levels that correlated with the severity of intestinal inflammation in IBD, despite lacking significant differential expression. Collectively, these data uncover a previously unrecognized epigenetic profile of IBD that can be primed by commensal microbes and indicate sensitive targets in the epithelium that may underlie how microbiota predispose to subsequent intestinal inflammation and disease.

miR-196b target screen reveals mechanisms maintaining leukemia stemness with therapeutic potential

We have shown that antagomiR inhibition of miRNA miR-21 and miR-196b activity is sufficient to ablate MLL-AF9 leukemia stem cells (LSC) in vivo. Here, we used an shRNA screening approach to mimic miRNA activity on experimentally verified miR-196b targets to identify functionally important and therapeutically relevant pathways downstream of oncogenic miRNA in MLL-r AML. We found Cdkn1b (p27Kip1) is a direct miR-196b target whose repression enhanced an embryonic stem cell-like signature associated with decreased leukemia latency and increased numbers of leukemia stem cells in vivo. Conversely, elevation of p27Kip1 significantly reduced MLL-r leukemia self-renewal, promoted monocytic differentiation of leukemic blasts, and induced cell death. Antagonism of miR-196b activity or pharmacologic inhibition of the Cks1-Skp2-containing SCF E3-ubiquitin ligase complex increased p27Kip1 and inhibited human AML growth. This work illustrates that understanding oncogenic miRNA target pathways can identify actionable targets in leukemia.

Automatic disease stage classification of glioblastoma multiforme histopathological images using deep convolutional neural network

In the field of computational histopathology, computer-assisted diagnosis systems are important in obtaining patient-specific diagnosis for various diseases and help precision medicine. Therefore, many studies on automatic analysis methods for digital pathology images have been reported. In this work, we discuss an automatic feature extraction and disease stage classification method for glioblastoma multiforme (GBM) histopathological images. In this paper, we use deep convolutional neural networks (Deep CNNs) to acquire feature descriptors and a classification scheme simultaneously. Further, comparisons with other popular CNNs objectively as well as quantitatively in this challenging classification problem is undertaken. The experiments using Glioma images from The Cancer Genome Atlas shows that we obtain 96.5 % average classification accuracy for our network and for higher cross validation folds other networks perform similarly with a higher accuracy of 98.0 % . Deep CNNs could extract significant features from the GBM histopathology images with high accuracy. Overall, the disease stage classification of GBM from histopathological images with deep CNNs is very promising and with the availability of large scale histopathological image data the deep CNNs are well suited in tackling this challenging problem.

Chromatin-associated APC regulates gene expression in collaboration with canonical WNT signaling and AP-1

Mutation of the APC gene occurs in a high percentage of colorectal tumors and is a central event driving tumor initiation in the large intestine. The APC protein performs multiple tumor suppressor functions including negative regulation of the canonical WNT signaling pathway by both cytoplasmic and nuclear mechanisms. Published reports that APC interacts with β-catenin in the chromatin fraction to repress WNT-activated targets have raised the possibility that chromatin-associated APC participates more broadly in mechanisms of transcriptional control. This screening study has used chromatin immunoprecipitation and next-generation sequencing to identify APC-associated genomic regions in colon cancer cell lines. Initial target selection was performed by comparison and statistical analysis of 3,985 genomic regions associated with the APC protein to whole transcriptome sequencing data from APC-deficient and APC-wild-type colon cancer cells, and two types of murine colon adenomas characterized by activated Wnt signaling.

289 transcripts altered in expression following APC loss in human cells were linked to APC-associated genomic regions. High-confidence targets additionally validated in mouse adenomas included 16 increased and 9 decreased in expression following APC loss, indicating that chromatin-associated APC may antagonize canonical WNT signaling at both WNT-activated and WNT-repressed targets. Motif analysis and comparison to ChIP-seq datasets for other transcription factors identified a prevalence of binding sites for the TCF7L2 and AP-1 transcription factors in APC-associated genomic regions. Our results indicate that canonical WNT signaling can collaborate with or antagonize the AP-1 transcription factor to fine-tune the expression of shared target genes in the colorectal epithelium. Future therapeutic strategies for APC-deficient colorectal cancers might be expanded to include agents targeting the AP-1 pathway.

Clinical and Genomic Correlates of Neutrophil Reactive Oxygen Species Production in Pediatric Patients With Crohn's Disease

BACKGROUND & AIMS

Individuals with monogenic disorders of phagocyte function develop chronic colitis that resembles Crohn's disease (CD). We tested for associations between mutations in genes encoding reduced nicotinamide adenine dinucleotide phosphate (NADPH) oxidases, neutrophil function, and phenotypes of CD in pediatric patients.

METHODS

We performed whole-exome sequence analysis to identify mutations in genes encoding NADPH oxidases (such as CYBA, CYBB, NCF1, NCF2, NCF4, RAC1, and RAC2) using DNA from 543 pediatric patients with inflammatory bowel diseases. Blood samples were collected from an additional 129 pediatric patients with CD and 26 children without IBD (controls); we performed assays for neutrophil activation, reactive oxygen species (ROS) production, and bacteria uptake and killing. Whole-exome sequence analysis was performed using DNA from 46 of the children with CD to examine associations with NADPH gene mutations; RNA sequence analyses were performed using blood cells from 46 children with CD to test for variations in neutrophil gene expression associated with ROS production.

RESULTS

We identified 26 missense mutations in CYBA, CYBB, NCF1, NCF2, and NCF4. Patients with CD who carried mutations in these genes were 3-fold more likely to have perianal disease (P = .0008) and stricturing complications (P = .002) than children with CD without these mutations. Among patients with CD with none of these mutations, 9% had undergone abdominal surgery; among patients with mutations in these NADPH oxidase genes, 31% had undergone abdominal surgery (P = .0004). A higher proportion of neutrophils from children with CD had low ROS production (47%) than from controls (15%) among the 129 patients tested for ROS (P = .002). Minor alleles of the NADPH genes were detected in 7% of children with CD whose neutrophils produced normal levels of ROS vs 38% of children whose neutrophils produced low levels of ROS (P = .009). Neutrophils that produced low levels of ROS had specific alterations in genes that regulate glucose metabolism and antimicrobial responses.

CONCLUSIONS

We identified missense mutations in genes that encode NADPH oxidases in children with CD; these were associated with a more aggressive disease course and reduced ROS production by neutrophils from the patients.

Whole-exome sequencing uncovers oxidoreductases DHTKD1 and OGDHL as linkers between mitochondrial dysfunction and eosinophilic esophagitis

Eosinophilic esophagitis (EoE) is an allergic inflammatory esophageal disorder with a complex underlying genetic etiology often associated with other comorbidities. Using whole-exome sequencing (WES) of 63 patients with EoE and 60 unaffected family members and family-based trio analysis, we sought to uncover rare coding variants. WES analysis identified 5 rare, damaging variants in dehydrogenase E1 and transketolase domain-containing 1 (DHTKD1). Rare variant burden analysis revealed an overabundance of putative, potentially damaging DHTKD1 mutations in EoE (P = 0.01). Interestingly, we also identified 7 variants in the DHTKD1 homolog oxoglutarate dehydrogenase-like (OGDHL). Using shRNA-transduced esophageal epithelial cells and/or patient fibroblasts, we further showed that disruption of normal DHTKD1 or OGDHL expression blunts mitochondrial function. Finally, we demonstrated that the loss of DHTKD1 expression increased ROS production and induced the expression of viperin, a gene previously shown to be involved in production of Th2 cytokines in T cells. Viperin had increased expression in esophageal biopsies of EoE patients compared with control individuals and was upregulated by IL-13 in esophageal epithelial cells. These data identify a series of rare genetic variants implicating DHTKD1 and OGDHL in the genetic etiology of EoE and underscore a potential pathogenic role for mitochondrial dysfunction in EoE.

Genetic variants and pathways implicated in a pediatric inflammatory bowel disease cohort

In the United States, approximately 5% of individuals with inflammatory bowel disease (IBD) are younger than 20 years old. Studies of pediatric cohorts can provide unique insights into genetic architecture of IBD, which includes Crohn's disease (CD) and ulcerative colitis (UC). Large genome-wide association studies have found more than 200 IBD-associated loci but explain a minority of disease variance for CD and UC. We sought to characterize the contribution of rare variants to disease development, comparing exome sequencing of 368 pediatric IBD patients to publicly available exome sequencing (dbGaP) and aggregate frequency data (ExAC). Using dbGaP data, we performed logistic regression for common variants and optimal unified association tests (SKAT-O) for rare, likely-deleterious variants. We further compared rare variants to ExAC counts with Fisher's exact tests. We did pathway enrichment analysis on the most significant genes from each comparison. Many variants overlapped with known IBD-associated genes (e.g. NOD2). Rare variants were enriched in CD-associated loci (p = 0.009) and showed suggestive enrichment in neutrophil function genes (p = 0.05). Pathway enrichment implicated immune-related pathways, especially cell killing and apoptosis. Variants in extracellular matrix genes also emerged as an important theme in our analysis.

Peroxisomal β-oxidation regulates whole body metabolism, inflammatory vigor, and pathogenesis of nonalcoholic fatty liver disease

Nonalcoholic fatty liver disease (NAFLD), a metabolic predisposition for development of hepatocellular carcinoma (HCC), represents a disease spectrum ranging from steatosis to steatohepatitis to cirrhosis. Acox1, a rate-limiting enzyme in peroxisomal fatty acid β-oxidation, regulates metabolism, spontaneous hepatic steatosis, and hepatocellular damage over time. However, it is unknown whether Acox1 modulates inflammation relevant to NAFLD pathogenesis or if Acox1-associated metabolic and inflammatory derangements uncover and accelerate potential for NAFLD progression. Here, we show that mice with a point mutation in Acox1 (Acox1Lampe1) exhibited altered cellular metabolism, modified T cell polarization, and exacerbated immune cell inflammatory potential. Further, in context of a brief obesogenic diet stress, NAFLD progression associated with Acox1 mutation resulted in significantly accelerated and exacerbated hepatocellular damage via induction of profound histological changes in hepatocytes, hepatic inflammation, and robust upregulation of gene expression associated with HCC development. Collectively, these data demonstrate that β-oxidation links metabolism and immune responsiveness and that a better understanding of peroxisomal β-oxidation may allow for discovery of mechanisms central for NAFLD progression.

Reconstructing differentiation networks and their regulation from time series single-cell expression data

Generating detailed and accurate organogenesis models using single-cell RNA-seq data remains a major challenge. Current methods have relied primarily on the assumption that descendant cells are similar to their parents in terms of gene expression levels. These assumptions do not always hold for in vivo studies, which often include infrequently sampled, unsynchronized, and diverse cell populations. Thus, additional information may be needed to determine the correct ordering and branching of progenitor cells and the set of transcription factors (TFs) that are active during advancing stages of organogenesis. To enable such modeling, we have developed a method that learns a probabilistic model that integrates expression similarity with regulatory information to reconstruct the dynamic developmental cell trajectories. When applied to mouse lung developmental data, the method accurately distinguished different cell types and lineages. Existing and new experimental data validated the ability of the method to identify key regulators of cell fate.

Thermoneutral housing exacerbates nonalcoholic fatty liver disease in mice and allows for sex-independent disease modeling

Nonalcoholic fatty liver disease (NAFLD), a common prelude to cirrhosis and hepatocellular carcinoma, is the most common chronic liver disease worldwide. Defining the molecular mechanisms underlying the pathogenesis of NAFLD has been hampered by a lack of animal models that closely recapitulate the severe end of the disease spectrum in humans, including bridging hepatic fibrosis. Here we demonstrate that a novel experimental model employing thermoneutral housing, as opposed to standard housing, resulted in lower stress-driven production of corticosterone, augmented mouse proinflammatory immune responses and markedly exacerbated high-fat diet (HFD)-induced NAFLD pathogenesis. Disease exacerbation at thermoneutrality was conserved across multiple mouse strains and was associated with augmented intestinal permeability, an altered microbiome and activation of inflammatory pathways that are associated with the disease in humans. Depletion of Gram-negative microbiota, hematopoietic cell deletion of Toll-like receptor 4 (TLR4) and inactivation of the IL-17 axis resulted in altered immune responsiveness and protection from thermoneutral-housing-driven NAFLD amplification. Finally, female mice, typically resistant to HFD-induced obesity and NAFLD, develop full disease characteristics at thermoneutrality. Thus, thermoneutral housing provides a sex-independent model of exacerbated NAFLD in mice and represents a novel approach for interrogation of the cellular and molecular mechanisms underlying disease pathogenesis.

Prediction of complicated disease course for children newly diagnosed with Crohn's disease: a multicentre inception cohort study

BACKGROUND

Stricturing and penetrating complications account for substantial morbidity and health-care costs in paediatric and adult onset Crohn's disease. Validated models to predict risk for complications are not available, and the effect of treatment on risk is unknown.

METHODS

We did a prospective inception cohort study of paediatric patients with newly diagnosed Crohn's disease at 28 sites in the USA and Canada. Genotypes, antimicrobial serologies, ileal gene expression, and ileal, rectal, and faecal microbiota were assessed. A competing-risk model for disease complications was derived and validated in independent groups. Propensity-score matching tested the effect of anti-tumour necrosis factor α (TNFα) therapy exposure within 90 days of diagnosis on complication risk.

FINDINGS

Between Nov 1, 2008, and June 30, 2012, we enrolled 913 patients, 78 (9%) of whom experienced Crohn's disease complications. The validated competing-risk model included age, race, disease location, and antimicrobial serologies and provided a sensitivity of 66% (95% CI 51-82) and specificity of 63% (55-71), with a negative predictive value of 95% (94-97). Patients who received early anti-TNFα therapy were less likely to have penetrating complications (hazard ratio [HR] 0·30, 95% CI 0·10-0·89; p=0·0296) but not stricturing complication (1·13, 0·51-2·51; 0·76) than were those who did not receive early anti-TNFα therapy. Ruminococcus was implicated in stricturing complications and Veillonella in penetrating complications. Ileal genes controlling extracellular matrix production were upregulated at diagnosis, and this gene signature was associated with stricturing in the risk model (HR 1·70, 95% CI 1·12-2·57; p=0·0120). When this gene signature was included, the model's specificity improved to 71%.

INTERPRETATION

Our findings support the usefulness of risk stratification of paediatric patients with Crohn's disease at diagnosis, and selection of anti-TNFα therapy.

FUNDING

Crohn's and Colitis Foundation of America, Cincinnati Children's Hospital Research Foundation Digestive Health Center.

Profound loss of esophageal tissue differentiation in patients with eosinophilic esophagitis

BACKGROUND

A key question in the allergy field is to understand how tissue-specific disease is manifested. Eosinophilic esophagitis (EoE) is an emerging tissue-specific allergic disease with an unclear pathogenesis.

OBJECTIVE

Herein we tested the hypothesis that a defect in tissue-specific esophageal genes is an integral part of EoE pathogenesis.

METHODS

We interrogated the pattern of expression of esophagus-specific signature genes derived from the Human Protein Atlas in the EoE transcriptome and in EPC2 esophageal epithelial cells. Western blotting and immunofluorescence were used for evaluating expression of esophageal proteins in biopsy specimens from control subjects and patients with active EoE. Whole-exome sequencing was performed to identify mutations in esophagus-specific genes.

RESULTS

We found that approximately 39% of the esophagus-specific transcripts were altered in patients with EoE, with approximately 90% being downregulated. The majority of transcriptional changes observed in esophagus-specific genes were reproduced in vitro in esophageal epithelial cells differentiated in the presence of IL-13. Functional enrichment analysis revealed keratinization and differentiation as the most affected biological processes and identified IL-1 cytokines and serine peptidase inhibitors as the most dysregulated esophagus-specific protein families in patients with EoE. Accordingly, biopsy specimens from patients with EoE evidenced a profound loss of tissue differentiation, decreased expression of keratin 4 (KRT4) and cornulin (CRNN), and increased expression of KRT5 and KRT14. Whole-exome sequencing of 33 unrelated patients with EoE revealed 39 rare mutations in 18 esophagus-specific differentially expressed genes.

CONCLUSIONS

A tissue-centered analysis has revealed a profound loss of esophageal tissue differentiation (identity) as an integral and specific part of the pathophysiology of EoE and implicated protease- and IL-1-related activities as putative central pathways in disease pathogenesis.

PRECISION MEDICINE: DATA AND DISCOVERY FOR IMPROVED HEALTH AND THERAPY

The major goal of precision medicine is to improve human health. A feature that unites much research in the field is the use of large datasets such as genomic data and electronic health records. Research in this field includes examination of variation in the core bases of DNA and their methylation status, through variations in metabolic and signaling molecules, all the way up to broader systems level changes in physiology and disease presentation. Intermediate goals include understanding the individual drivers of disease that differentiate the cause of disease in each individual. To match this development of approaches to physical and activitybased measurements, computational approaches to using these new streams of data to better understand improve human health are being rapidly developed by the thriving biomedical informatics research community. This session of the 2017 Pacific Symposium of Biocomputing presents some of the latest advances in the capture, analysis and use of diverse biomedical data in precision medicine.

Integrated Genomic Analysis of Diverse Induced Pluripotent Stem Cells from the Progenitor Cell Biology Consortium

The rigorous characterization of distinct induced pluripotent stem cells (iPSC) derived from multiple reprogramming technologies, somatic sources, and donors is required to understand potential sources of variability and downstream potential. To achieve this goal, the Progenitor Cell Biology Consortium performed comprehensive experimental and genomic analyses of 58 iPSC from ten laboratories generated using a variety of reprogramming genes, vectors, and cells. Associated global molecular characterization studies identified functionally informative correlations in gene expression, DNA methylation, and/or copy-number variation among key developmental and oncogenic regulators as a result of donor, sex, line stability, reprogramming technology, and cell of origin. Furthermore, X-chromosome inactivation in PSC produced highly correlated differences in teratoma-lineage staining and regulator expression upon differentiation. All experimental results, and raw, processed, and metadata from these analyses, including powerful tools, are interactively accessible from a new online portal at https://www.synapse.org to serve as a reusable resource for the stem cell community.

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Comprehensive portal for diverse iPSC, protocols, metadata, and genomic assays

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Recurrent CNV occur during reprogramming, impact oncogenes and tumor suppressors

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DNA methylation is influenced by cell of origin in iPSC

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PSC X-chromosome inactivation impacts lineage differentiation outcomes