Genetic imputation of kidney transcriptome, proteome and multi-omics illuminates new blood pressure and hypertension targets.

Genetic mechanisms of blood pressure (BP) regulation remain poorly defined. Using kidney-specific epigenomic annotations and 3D genome information we generated and validated gene expression prediction models for the purpose of transcriptome-wide association studies in 700 human kidneys. We identified 889 kidney genes associated with BP of which 399 were prioritised as contributors to BP regulation. Imputation of kidney proteome and microRNAome uncovered 97 renal proteins and 11 miRNAs associated with BP. Integration with plasma proteomics and metabolomics illuminated circulating levels of myo-inositol, 4-guanidinobutanoate and angiotensinogen as downstream effectors of several kidney BP genes (SLC5A11, AGMAT, AGT, respectively). We showed that genetically determined reduction in renal expression may mimic the effects of rare loss-of-function variants on kidney mRNA/protein and lead to an increase in BP (e.g., ENPEP). We demonstrated a strong correlation (r = 0.81) in expression of protein-coding genes between cells harvested from urine and the kidney highlighting a diagnostic potential of urinary cell transcriptomics. We uncovered adenylyl cyclase activators as a repurposing opportunity for hypertension and illustrated examples of BP-elevating effects of anticancer drugs (e.g. tubulin polymerisation inhibitors). Collectively, our studies provide new biological insights into genetic regulation of BP with potential to drive clinical translation in hypertension.

Identification of novel NRF2-dependent genes as regulators of lead and arsenic toxicity in neural progenitor cells.

Lead (Pb) and arsenic (As) are prevalent metal contaminants in the environment. Exposures to these metals are associated with impaired neuronal functions and adverse effects on neurodevelopment in children. However, the molecular mechanisms by which Pb and As impair neuronal functions remain poorly understood. Here, we identified F2RL2, TRIM16L, and PANX2 as novel targets of Nuclear factor erythroid 2-related factor 2 (NRF2)-the master transcriptional factor for the oxidative stress response-that are commonly upregulated with both Pb and As in human neural progenitor cells (NPCs). Using a ChIP (Chromatin immunoprecipitation)-qPCR assay, we showed that NRF2 directly binds to the promoter region of F2RL2, TRIM16L, and PANX2 to regulate expression of these genes. We demonstrated that F2RL2, PANX2, and TRIM16L have differential effects on cell death, proliferation, and differentiation of NPCs in both the presence and absence of metal exposures, highlighting their roles in regulating NPC function. Furthermore, the analyses of the transcriptomic data on NPCs derived from autism spectrum disorder (ASD) patients revealed that dysregulation of F2RL2, TRIM16L, and PANX2 was associated with ASD genetic backgrounds and ASD risk genes. Our findings revealed that Pb and As induce a shared NRF2-dependent transcriptional response in NPCs and identified novel genes regulating NPC function. While further in vivo studies are warranted, this study provides a novel mechanism linking metal exposures to NPC function and identifies potential genes of interest in the context of neurodevelopment.

CEBPD modulates the airway smooth muscle transcriptomic response to glucocorticoids.

BACKGROUND: CCAAT/Enhancer Binding Protein D (CEBPD), a pleiotropic glucocorticoid-responsive transcription factor, modulates inflammatory responses. Of relevance to asthma, expression of CEBPD in airway smooth muscle (ASM) increases with glucocorticoid exposure. We sought to characterize CEBPD-mediated transcriptomic responses to glucocorticoid exposure in ASM by measuring changes observed after knockdown of CEBPD and its impact on asthma-related ASM function. METHODS: Primary ASM cells derived from four donors were transfected with CEBPD or non-targeting (NT) siRNA and exposed to vehicle control, budesonide (100 nM, 18 h), TNFα (10 ng/ml, 18 h), or both budesonide and TNFα. Subsequently, RNA-Seq was used to measure gene expression levels, and pairwise differential expression results were obtained for exposures versus vehicle and knockdown versus control conditions. Weighted gene co-expression analysis was performed to identify groups of genes with similar expression patterns across the various experimental conditions (i.e., CEBPD knockdown status, exposures). RESULTS: CEBPD knockdown altered expression of 3037 genes under at least one exposure (q-value < 0.05). Co-expression analysis identified sets of 197, 152 and 290 genes that were correlated with CEBPD knockdown status, TNFα exposure status, and both, respectively. JAK-STAT signaling pathway genes, including IL6R and SOCS3, were among those influenced by both TNFα and CEBPD knockdown. Immunoblot assays revealed that budesonide-induced IL-6R protein expression and augmented IL-6-induced STAT3 phosphorylation levels were attenuated by CEBPD knockdown in ASM. CONCLUSIONS: CEBPD modulates glucocorticoid responses in ASM, in part via modulation of IL-6 receptor signaling.

REALGAR: a web app of integrated respiratory omics data.

MOTIVATION: In the post genome-wide association study (GWAS) era, omics techniques have characterized information beyond genomic variants to include cell and tissue type-specific gene transcription, transcription factor binding sites, expression quantitative trait loci (eQTL) and many other biological layers. Analysis of omics data and its integration has in turn improved the functional interpretation of disease-associated genetic variants. Over 170 000 transcriptomic and epigenomic datasets corresponding to studies of various cell and tissue types under specific disease, treatment and exposure conditions are available in the Gene Expression Omnibus resource. Although these datasets are valuable to guide the design of experimental validation studies to understand the function of disease-associated genetic loci, in their raw form, they are not helpful to experimental researchers who lack adequate computational resources or experience analyzing omics data. We sought to create an integrated re-source of tissue-specific results from omics studies that is guided by disease-specific knowledge to facilitate the design of experiments that can provide biologically meaningful insights into genetic associations. RESULTS: We designed the Reducing Associations by Linking Genes and omics Results web app to provide multi-layered omics information based on results from GWAS, transcriptomic, epigenomic and eQTL studies for gene-centric analysis and visualization. With a focus on asthma datasets, the integrated omics results it contains facilitate the formulation of hypotheses related to airways disease-associated genes and can be addressed with experimental validation studies. AVAILABILITY AND IMPLEMENTATION: The REALGAR web app is available at: http://realgar.org/. The source code is available at: https://github.com/HimesGroup/realgar. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Release of particulate matter from nano-enabled building materials (NEBMs) across their lifecycle: Potential occupational health and safety implications.

The present study investigates potential nanomaterial releases and occupational health risks across the lifecycle of nano-enabled building materials (NEBMs), namely, insulations and coatings. We utilized real-world degradation scenarios of a) sanding (mechanical), b) incineration (thermal), and c) accelerated UV-aging (environmental) followed by incineration. Extensive physicochemical characterization of the released lifecycle particulate matter (LCPM) was performed. The LCPM2.5 aerosol size fraction was used to assess the acute biological, cytotoxic and inflammatory effects on Calu-3 human lung epithelial cells. RNA-Seq analysis of exposed cells was performed to assess potential for systemic disease. Findings indicated that release dynamics and characteristics of LCPM depended on both the NEBM composition and the degradation scenario(s). Incineration emitted a much higher nanoparticle number concentration than sanding (nearly 4 orders of magnitude), which did not change with prior UV-aging. Released nanofillers during sanding were largely part of the matrix fragments, whereas those during incineration were likely physicochemically transformed. The LCPM from incineration showed higher bioactivity and inflammogenicity compared to sanding or sequential UV-aging and incineration, and more so when metallic nanofillers were present (such as Fe2O3). Overall, the study highlights the need for considering real-world exposure and toxicological data across the NEBM lifecycle to perform adequate risk assessments and to ensure workplace health and safety.

COVID-19 Pandemic-Related Reductions in Pediatric Asthma Exacerbations Corresponded with an Overall Decrease in Respiratory Viral Infections.

BACKGROUND: Respiratory viruses, air pollutants, and aeroallergens are all implicated in worsening pediatric asthma symptoms, but their relative contributions to asthma exacerbations are poorly understood. A significant decrease in asthma exacerbations has been observed during the coronavirus disease 2019 pandemic, providing a unique opportunity to study how major asthma triggers correlate with asthma activity. OBJECTIVE: To determine whether changes in respiratory viruses, air pollutants, and/or aeroallergens during the coronavirus disease 2019 pandemic were concomitant with decreased asthma exacerbations. METHODS: Health care utilization and respiratory viral testing data between January 1, 2015, and December 31, 2020, were extracted from the Children's Hospital of Philadelphia Care Network's electronic health record. Air pollution and allergen data were extracted from US Environmental Protection Agency public databases and a National Allergy Bureau-certified station, respectively. Pandemic data (2020) were compared with historical data. RESULTS: Recovery of in-person asthma encounters during phased reopening (June 6 to November 15, 2020) was uneven: primary care well and specialty encounters reached 94% and 74% of prepandemic levels, respectively, whereas primary care sick and hospital encounters reached 21% and 40% of prepandemic levels, respectively. During the pandemic, influenza A and influenza B decreased to negligible frequency when compared with prepandemic cases, whereas respiratory syncytial virus and rhinovirus infections decreased to low (though nonnegligible) prepandemic levels, as well. No changes in air pollution or aeroallergen levels relative to historical observations were noted. CONCLUSIONS: Our results suggest that viral respiratory infections are a primary driver of pediatric asthma exacerbations. These findings have broad relevance to both clinical practice and the development of health policies aimed at reducing asthma morbidity.

Multiomics analysis identifies BIRC3 as a novel glucocorticoid response-associated gene.

BACKGROUND: Inhaled corticosteroid (ICS) response among patients with asthma is influenced by genetics, but biologically actionable insights based on associations have not been found. Various glucocorticoid response omics data sets are available to interrogate their biological effects. OBJECTIVE: We sought to identify functionally relevant ICS-response genetic associations by integrating complementary multiomics data sets. METHODS: Variants with P values less than 10-4 from a previous ICS-response genome-wide association study were reranked on the basis of integrative scores determined from (1) glucocorticoid receptor- and (2) RNA polymerase II-binding regions inferred from ChIP-Seq data for 3 airway cell types, (3) glucocorticoid response element motifs, (4) differentially expressed genes in response to glucocorticoid exposure according to 20 transcriptomic data sets, and (5) expression quantitative trait loci from GTEx. Candidate variants were tested for association with ICS response and asthma in 6 independent studies. RESULTS: Four variants had significant (q value < 0.05) multiomics integrative scores. These variants were in a locus consisting of 52 variants in high linkage disequilibrium (r2 ≥ 0.8) near glucocorticoid receptor-binding sites by the gene BIRC3. Variants were also BIRC3 expression quantitative trait loci in lung, and 2 were within/near putative glucocorticoid response element motifs. BIRC3 had increased RNA polymerase II occupancy and gene expression, with glucocorticoid exposure in 2 ChIP-Seq and 13 transcriptomic data sets. Some BIRC3 variants in the 52-variant locus were associated (P < .05) with ICS response in 3 independent studies and others with asthma in 1 study. CONCLUSIONS: BIRC3 should be prioritized for further functional studies of ICS response.

Integrating Biomedical Informatics Training into Existing High School Curricula.

Growing demand for biomedical informaticists and expertise in areas related to this discipline has accentuated the need to integrate biomedical informatics training into high school curricula. The K-12 Bioinformatics professional development project educates high school teachers about data analysis, biomedical informatics and mobile learning, and partners with them to expose high school students to health and environment-related issues using biomedical informatics knowledge and current technologies. We designed low-cost pollution sensors and created interactive web applications that teachers from six Philadelphia public high schools used during the 2019-2020 school year to successfully implement a problem-based mobile learning unit that included collecting and interpreting air pollution data, as well as relating this data to asthma. Through this project, we sought to improve data and health literacy among the students and teachers, while inspiring student engagement by demonstrating how biomedical informatics can help address problems relevant to communities where students live.

Consolidated Environmental and Social Data Facilitates Neighborhood-Level Health Studies in Philadelphia.

A wide range of datasets containing geographically distributed measures of the environment and social factors is currently available, and as low-cost sensors and other devices become increasingly used, the volume of these data will continue to grow. Because such factors influence many health outcomes, researchers with varied interests often repeat tasks related to gathering and preparing these data for studies. We created Sensor-based Analysis of Pollution in the Philadelphia Region with Information on Neighborhoods and the Environment (SAPPHIRINE), offered as a web application and R package, to integrate pollution, crime, social disadvantage, and traffic data relevant to investigators, citizen scientists, and policy makers in the Greater Philadelphia Area. SAPPHIRINE's capabilities include providing interactive maps and customizable data retrieval to aid in the visual identification of pollution and other factor hotspots, as well as hypothesis generation regarding relationships among these factors and health outcomes.

Pediatric Asthma Health Care Utilization, Viral Testing, and Air Pollution Changes During the COVID-19 Pandemic.

BACKGROUND: The coronavirus disease 2019 (COVID-19) pandemic caused dramatic changes in daily routines and health care utilization and delivery patterns in the United States. Understanding the influence of these changes and associated public health interventions on asthma care is important to determine effects on patient outcomes and identify measures that will ensure optimal future health care delivery. OBJECTIVE: We sought to identify changes in pediatric asthma-related health care utilization, respiratory viral testing, and air pollution during the COVID-19 pandemic. METHODS: For the time period January 17 to May 17, 2015 to 2020, asthma-related encounters and weekly summaries of respiratory viral testing data were extracted from Children's Hospital of Philadelphia electronic health records, and pollution data for 4 criteria air pollutants were extracted from AirNow. Changes in encounter characteristics, viral testing patterns, and air pollution before and after Mar 17, 2020, the date public health interventions to limit viral transmission were enacted in Philadelphia, were assessed and compared with data from 2015 to 2019 as a historical reference. RESULTS: After March 17, 2020, in-person asthma encounters decreased by 87% (outpatient) and 84% (emergency + inpatient). Video telemedicine, which was not previously available, became the most highly used asthma encounter modality (61% of all visits), and telephone encounters increased by 19%. Concurrently, asthma-related systemic steroid prescriptions and frequency of rhinovirus test positivity decreased, although air pollution levels did not substantially change, compared with historical trends. CONCLUSIONS: The COVID-19 pandemic in Philadelphia was accompanied by changes in pediatric asthma health care delivery patterns, including reduced admissions and systemic steroid prescriptions. Reduced rhinovirus infections may have contributed to these patterns.

Facilitating Analysis of Publicly Available ChIP-Seq Data for Integrative Studies.

ChIP-Seq, a technique that allows for quantification of DNA sequences bound by transcription factors or histones, has been widely used to characterize genome-wide DNA-protein binding at baseline and induced by specific exposures. Integrating results of multiple ChIP-Seq datasets is a convenient approach to identify robust DNA- protein binding sites and determine their cell-type specificity. We developed brocade, a computational pipeline for reproducible analysis of publicly available ChIP-Seq data that creates R markdown reports containing information on datasets downloaded, quality control metrics, and differential binding results. Glucocorticoids are commonly used anti-inflammatory drugs with tissue-specific effects that are not fully understood. We demonstrate the utility of brocade via the analysis of five ChIP-Seq datasets involving glucocorticoid receptor (GR), a transcription factor that mediates glucocorticoid response, to identify cell type-specific and shared GR binding sites across the five cell types. Our results show that brocade facilitates analysis of individual ChIP-Seq datasets and comparative studies involving multiple datasets.