Epigenetic Profiling of PTPN11 Mutant JMML Hematopoietic Stem and Progenitor Cells Reveals an Aberrant Histone Landscape.

Juvenile myelomonocytic leukemia (JMML) is a deadly pediatric leukemia driven by RAS pathway mutations, of which >35% are gain-of-function in PTPN11. Although DNA hypermethylation portends severe clinical phenotypes, the landscape of histone modifications and chromatin profiles in JMML patient cells have not been explored. Using global mass cytometry, Epigenetic Time of Flight (EpiTOF), we analyzed hematopoietic stem and progenitor cells (HSPCs) from five JMML patients with PTPN11 mutations. These data revealed statistically significant changes in histone methylation, phosphorylation, and acetylation marks that were unique to JMML HSPCs when compared with healthy controls. Consistent with these data, assay for transposase-accessible chromatin with sequencing (ATAC-seq) analysis revealed significant alterations in chromatin profiles at loci encoding post-translational modification enzymes, strongly suggesting their mis-regulated expression. Collectively, this study reveals histone modification pathways as an additional epigenetic abnormality in JMML patient HSPCs, thereby uncovering a new family of potential druggable targets for the treatment of JMML.

Ancestry-based differences in the immune phenotype are associated with lupus activity.

Systemic lupus erythematosus (SLE) affects 1 in 537 Black women, which is >2-fold more than White women. Black patients develop the disease at a younger age, have more severe symptoms, and have a greater chance of early mortality. We used a multiomics approach to uncover ancestry-associated immune alterations in patients with SLE and healthy controls that may contribute biologically to disease disparities. Cell composition, signaling, epigenetics, and proteomics were evaluated by mass cytometry; droplet-based single-cell transcriptomics and proteomics; and bead-based multiplex soluble mediator levels in plasma. We observed altered whole blood frequencies and enhanced activity in CD8+ T cells, B cells, monocytes, and DCs in Black patients with more active disease. Epigenetic modifications in CD8+ T cells (H3K27ac) could distinguish disease activity level in Black patients and differentiate Black from White patient samples. TLR3/4/7/8/9-related gene expression was elevated in immune cells from Black patients with SLE, and TLR7/8/9 and IFN-α phospho-signaling and cytokine responses were heightened even in immune cells from healthy Black control patients compared with White individuals. TLR stimulation of healthy immune cells recapitulated the ancestry-associated SLE immunophenotypes. This multiomic resource defines ancestry-associated immune phenotypes that differ between Black and White patients with SLE, which may influence the course and severity of SLE and other diseases.

Mass-Cytometry-Based Quantification of Global Histone Post-Translational Modifications at Single-Cell Resolution Across Peripheral Immune Cells in IBD.

BACKGROUND AND AIMS: Current understanding of histone post-translational modifications [histone modifications] across immune cell types in patients with inflammatory bowel disease [IBD] during remission and flare is limited. The present study aimed to quantify histone modifications at a single-cell resolution in IBD patients during remission and flare and how they differ compared to healthy controls. METHODS: We performed a case-control study of 94 subjects [83 IBD patients and 11 healthy controls]. IBD patients had either ulcerative colitis [n = 38] or Crohn's disease [n = 45] in clinical remission or flare. We used epigenetic profiling by time-of-flight [EpiTOF] to investigate changes in histone modifications within peripheral blood mononuclear cells from IBD patients. RESULTS: We discovered substantial heterogeneity in histone modifications across multiple immune cell types in IBD patients. They had a higher proportion of less differentiated CD34+ haematopoietic progenitors, and a subset of CD56bright natural killer [NK] cells and γδ T cells characterized by distinct histone modifications associated with gene transcription. The subset of CD56bright NK cells had increases in several histone acetylations. An epigenetically defined subset of NK cells was associated with higher levels of C-reactive protein in peripheral blood. CD34+ monocytes from IBD patients had significantly decreased cleaved H3T22, suggesting they were epigenetically primed for macrophage differentiation. CONCLUSION: We describe the first systems-level quantification of histone modifications across immune cells from IBD patients at a single-cell resolution, revealing the increased epigenetic heterogeneity that is not possible with traditional ChIP-seq profiling. Our data open new directions in investigating the association between histone modifications and IBD pathology using other epigenomic tools.

New-onset IgG autoantibodies in hospitalized patients with COVID-19.

COVID-19 is associated with a wide range of clinical manifestations, including autoimmune features and autoantibody production. Here we develop three protein arrays to measure IgG autoantibodies associated with connective tissue diseases, anti-cytokine antibodies, and anti-viral antibody responses in serum from 147 hospitalized COVID-19 patients. Autoantibodies are identified in approximately 50% of patients but in less than 15% of healthy controls. When present, autoantibodies largely target autoantigens associated with rare disorders such as myositis, systemic sclerosis and overlap syndromes. A subset of autoantibodies targeting traditional autoantigens or cytokines develop de novo following SARS-CoV-2 infection. Autoantibodies track with longitudinal development of IgG antibodies recognizing SARS-CoV-2 structural proteins and a subset of non-structural proteins, but not proteins from influenza, seasonal coronaviruses or other pathogenic viruses. We conclude that SARS-CoV-2 causes development of new-onset IgG autoantibodies in a significant proportion of hospitalized COVID-19 patients and are positively correlated with immune responses to SARS-CoV-2 proteins.

The single-cell epigenomic and transcriptional landscape of immunity to influenza vaccination.

Emerging evidence indicates a fundamental role for the epigenome in immunity. Here, we mapped the epigenomic and transcriptional landscape of immunity to influenza vaccination in humans at the single-cell level. Vaccination against seasonal influenza induced persistently diminished H3K27ac in monocytes and myeloid dendritic cells (mDCs), which was associated with impaired cytokine responses to Toll-like receptor stimulation. Single-cell ATAC-seq analysis revealed an epigenomically distinct subcluster of monocytes with reduced chromatin accessibility at AP-1-targeted loci after vaccination. Similar effects were observed in response to vaccination with the AS03-adjuvanted H5N1 pandemic influenza vaccine. However, this vaccine also stimulated persistently increased chromatin accessibility at interferon response factor (IRF) loci in monocytes and mDCs. This was associated with elevated expression of antiviral genes and heightened resistance to the unrelated Zika and Dengue viruses. These results demonstrate that vaccination stimulates persistent epigenomic remodeling of the innate immune system and reveal AS03's potential as an epigenetic adjuvant.

Repression of CTSG, ELANE and PRTN3-mediated histone H3 proteolytic cleavage promotes monocyte-to-macrophage differentiation.

Chromatin undergoes extensive reprogramming during immune cell differentiation. Here we report the repression of controlled histone H3 amino terminus proteolytic cleavage (H3ΔN) during monocyte-to-macrophage development. This abundant histone mark in human peripheral blood monocytes is catalyzed by neutrophil serine proteases (NSPs) cathepsin G, neutrophil elastase and proteinase 3. NSPs are repressed as monocytes mature into macrophages. Integrative epigenomic analysis reveals widespread H3ΔN distribution across the genome in a monocytic cell line and primary monocytes, which becomes largely undetectable in fully differentiated macrophages. H3ΔN is enriched at permissive chromatin and actively transcribed genes. Simultaneous NSP depletion in monocytic cells results in H3ΔN loss and further increase in chromatin accessibility, which likely primes the chromatin for gene expression reprogramming. Importantly, H3ΔN is reduced in monocytes from patients with systemic juvenile idiopathic arthritis, an autoinflammatory disease with prominent macrophage involvement. Overall, we uncover an epigenetic mechanism that primes the chromatin to facilitate macrophage development.

New-Onset IgG Autoantibodies in Hospitalized Patients with COVID-19.

Coronavirus Disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), is associated with a wide range of clinical manifestations, including autoimmune features and autoantibody production. We developed three different protein arrays to measure hallmark IgG autoantibodies associated with Connective Tissue Diseases (CTDs), Anti-Cytokine Antibodies (ACA), and anti-viral antibody responses in 147 hospitalized COVID-19 patients in three different centers. Autoantibodies were identified in approximately 50% of patients, but in <15% of healthy controls. When present, autoantibodies largely targeted autoantigens associated with rare disorders such as myositis, systemic sclerosis and CTD overlap syndromes. Anti-nuclear antibodies (ANA) were observed in ∼25% of patients. Patients with autoantibodies tended to demonstrate one or a few specificities whereas ACA were even more prevalent, and patients often had antibodies to multiple cytokines. Rare patients were identified with IgG antibodies against angiotensin converting enzyme-2 (ACE-2). A subset of autoantibodies and ACA developed de novo following SARS-CoV-2 infection while others were transient. Autoantibodies tracked with longitudinal development of IgG antibodies that recognized SARS-CoV-2 structural proteins such as S1, S2, M, N and a subset of non-structural proteins, but not proteins from influenza, seasonal coronaviruses or other pathogenic viruses. COVID-19 patients with one or more autoantibodies tended to have higher levels of antibodies against SARS-CoV-2 Nonstructural Protein 1 (NSP1) and Methyltransferase (ME). We conclude that SARS-CoV-2 causes development of new-onset IgG autoantibodies in a significant proportion of hospitalized COVID-19 patients and are positively correlated with immune responses to SARS-CoV-2 proteins.

Using Long Short-Term Memory (LSTM) Neural Networks to Predict Emergency Department Wait Time.

Emergency Department (ED) overcrowding is a major global healthcare issue. Many research studies have been conducted to predict ED wait time using various machine learning prediction models to enhance patient experience and improve care efficiency and resource allocation. In this paper, we used Long Short-Term Memory (LSTM) recurrent neural networks to build a model to predict ED wait time in the next 2 hours using a randomly generated patient timestamp dataset of a typical patient hospital journey. Compared with Linear Regression model, the average mean absolute error for the LSTM model is decreased by 9.7% (3 minutes) (p < 0.01). The LSTM model statistically outperforms the LR model, however, both models could be practically useful in ED wait time prediction.

Using Long Short-Term Memory (LSTM) Neural Networks to Predict Emergency Department Wait Time.

Emergency Department (ED) overcrowding is a major global healthcare issue. In this paper, we used Long Short-Term Memory (LSTM) recurrent neural networks to build a model to predict ED wait time in the next 2 hours using a randomly generated patient timestamp dataset of a typical patient hospital journey. Compared with Linear Regression model, the average mean absolute error for the LSTM model is decreased by 15% (3 minutes) (p<0.001). The LSTM model statistically outperforms the LR model, however, both models could be practically useful in ED wait time prediction.

Monitoring Physical Activity Levels Using Twitter Data: Infodemiology Study.

BACKGROUND: Social media technology such as Twitter allows users to share their thoughts, feelings, and opinions online. The growing body of social media data is becoming a central part of infodemiology research as these data can be combined with other public health datasets (eg, physical activity levels) to provide real-time monitoring of psychological and behavior outcomes that inform health behaviors. Currently, it is unclear whether Twitter data can be used to monitor physical activity levels. OBJECTIVE: The aim of this study was to establish the feasibility of using Twitter data to monitor physical activity levels by assessing whether the frequency and sentiment of physical activity-related tweets were associated with physical activity levels across the United States. METHODS: Tweets were collected from Twitter's application programming interface (API) between January 10, 2017 and January 2, 2018. We used Twitter's garden hose method of collecting tweets, which provided a random sample of approximately 1% of all tweets with location metadata falling within the United States. Geotagged tweets were filtered. A list of physical activity-related hashtags was collected and used to further classify these geolocated tweets. Twitter data were merged with physical activity data collected as part of the Behavioral Risk Factor Surveillance System. Multiple linear regression models were fit to assess the relationship between physical activity-related tweets and physical activity levels by county while controlling for population and socioeconomic status measures. RESULTS: During the study period, 442,959,789 unique tweets were collected, of which 64,005,336 (14.44%) were geotagged with latitude and longitude coordinates. Aggregated data were obtained for a total of 3138 counties in the United States. The mean county-level percentage of physically active individuals was 74.05% (SD 5.2) and 75.30% (SD 4.96) after adjusting for age. The model showed that the percentage of physical activity-related tweets was significantly associated with physical activity levels (beta=.11; SE 0.2; P<.001) and age-adjusted physical activity (beta=.10; SE 0.20; P<.001) on a county level while adjusting for both Gini index and education level. However, the overall explained variance of the model was low (R2=.11). The sentiment of the physical activity-related tweets was not a significant predictor of physical activity level and age-adjusted physical activity on a county level after including the Gini index and education level in the model (P>.05). CONCLUSIONS: Social media data may be a valuable tool for public health organizations to monitor physical activity levels, as it can overcome the time lag in the reporting of physical activity epidemiology data faced by traditional research methods (eg, surveys and observational studies). Consequently, this tool may have the potential to help public health organizations better mobilize and target physical activity interventions.

Single-cell technologies - studying rheumatic diseases one cell at a time.

Cells, the basic units of life, have striking differences at transcriptomic, proteomic and epigenomic levels across tissues, organs, organ systems and organisms. The coordination of individual immune cells is essential for the generation of effective immune responses to pathogens while immune tolerance is maintained to protect the host. In rheumatic diseases, when immune responses are dysregulated, pathologically important cells might represent only a small fraction of the immune system. Interrogation of the contributions of individual immune cells to pathogenesis and disease progression should therefore reveal important insights into the complicated aetiology of rheumatic diseases. Technological advances are enabling the high-dimensional dissection of single cells at multiple omics levels, which could facilitate the identification of dysregulated molecular mechanisms in patients with rheumatic diseases and the discovery of new therapeutic targets and biomarkers. The single-cell technologies that have been developed over the past decade and the experimental platforms that enable multi-omics integrative analyses have already made inroads into immunology-related fields of study and have potential for use in rheumatology. Layers of omics data derived from single cells are likely to fundamentally change our understanding of the molecular pathways that underpin the pathogenesis of rheumatic diseases.

A Hadoop/MapReduce Based Platform for Supporting Health Big Data Analytics.

In this paper, we report our practical experience in designing and implementing a platform with Hadoop/MapReduce framework for supporting health Big Data Analytics. Three billion of emulated health raw data was constructed and cross-referenced with data profiles and metadata based on existing health data at the Island Health Authority, BC, Canada. The patient data was stored over a Hadoop Distributed File System to simulate a presentation of an entire health authority's information system. Then, a High Performance Computing platform called WestGrid was used to benchmark the performance of the platform via several data query tests. The work is important as very few implementation studies existed that tested a BDA platform applied to patient data of a health authority system.

System Dynamics in Remote Monitoring Service for Cardiovascular Implantable Electronic Devices.

This methodological paper describes how system dynamics was applied in evaluating the effect of remote monitoring (RM) of cardiovascular implantable electronic device (CIED) workload on clinical resource utilization. The development of a causal loop diagram and a stock and flow diagram and the construction of the simulation model for comparison of an in-person clinic group and RM clinic group are described.

Design and Usability Evaluation of Mobile Cloud Healthcare System for Diabetes Prevention.

In this study, a mobile cloud healthcare system was implemented to assist middle- and old-aged people with diabetes preventive healthcare. First of all, a prototype system was developed. It was a system relying on data mining computing technology and big data analytics. Besides, it was constructed under the environment architecture of VMware cloud computing. This mobile cloud healthcare system was developed via mobile devices. Its purpose was to set up a diabetes preventive healthcare service for users, and to further assess the usability of this mobile cloud care system.

Single-cell epigenetics - Chromatin modification atlas unveiled by mass cytometry.

Modifications of histone proteins are fundamental to the regulation of epigenetic phenotypes. Dysregulations of histone modifications have been linked to the pathogenesis of diverse human diseases. However, identifying differential histone modifications in patients with immune-mediated diseases has been challenging, in part due to the lack of a powerful analytic platform to study histone modifications in the complex human immune system. We recently developed a highly multiplexed platform, Epigenetic landscape profiling using cytometry by Time-Of-Flight (EpiTOF), to analyze the global levels of a broad array of histone modifications in single cells using mass cytometry. In this review, we summarize the development of EpiTOF and discuss its potential applications in biomedical research. We anticipate that this platform will provide new insights into the roles of epigenetic regulation in hematopoiesis, immune cell functions, and immune system aging, and reveal aberrant epigenetic patterns associated with immune-mediated diseases.

Single-Cell Chromatin Modification Profiling Reveals Increased Epigenetic Variations with Aging.

Post-translational modifications of histone proteins and exchanges of histone variants of chromatin are central to the regulation of nearly all DNA-templated biological processes. However, the degree and variability of chromatin modifications in specific human immune cells remain largely unknown. Here, we employ a highly multiplexed mass cytometry analysis to profile the global levels of a broad array of chromatin modifications in primary human immune cells at the single-cell level. Our data reveal markedly different cell-type- and hematopoietic-lineage-specific chromatin modification patterns. Differential analysis between younger and older adults shows that aging is associated with increased heterogeneity between individuals and elevated cell-to-cell variability in chromatin modifications. Analysis of a twin cohort unveils heritability of chromatin modifications and demonstrates that aging-related chromatin alterations are predominantly driven by non-heritable influences. Together, we present a powerful platform for chromatin and immunology research. Our discoveries highlight the profound impacts of aging on chromatin modifications.

Implementation of clinical practice changes by experienced anesthesiologists after simulation-based ultrasound-guided regional anesthesia training.

BACKGROUND: Anesthesiologists who have finished formal training and want to learn ultrasound-guided regional anesthesia (UGRA) commonly attend 1 day workshops. However, it is unclear whether participation actually changes clinical practice. We assessed change implementation after completion of a 1 day simulation-based UGRA workshop. METHODS: Practicing anesthesiologists who participated in a 1 day UGRA course from January 2012 through May 2014 were surveyed. The course consisted of clinical observation of UGRA procedures, didactic lectures, ultrasound scanning, hands-on perineural catheter placement, and mannequin simulation. The primary outcome was the average number of UGRA blocks per month reported at follow-up versus baseline. Secondary outcomes included preference for ultrasound as the nerve localization technique, ratings of UGRA teaching methods, and obstacles to performing UGRA. RESULTS: Survey data from 46 course participants (60% response rate) were included for analysis. Participants were (median [10th-90th percentile]) 50 (37-63) years old, had been in practice for 17 (5-30) years, and were surveyed 27 (10-34) months after their UGRA training. Participants reported performing 24 (4-90) blocks per month at follow-up compared to 10 (2-24) blocks at baseline (P < 0.001). Compared to baseline, more participants at follow-up preferred ultrasound for nerve localization. The major obstacle to implementing UGRA in clinical practice was time pressure. CONCLUSIONS: Participation in a 1 day simulation-based UGRA course may increase UGRA procedural volume by practicing anesthesiologists.

Registry Data-Valuable Lessons But Beware the Confounders.

A mature national joint registry with widespread adoption and audit can successfully demonstrate trends and influence future orthopedic practice. Correlations can be identified; however, this should not be misinterpreted as causality. It is essential to consider confounding when analyzing observational datasets.

Integration of Health Information Systems Using HL7: A Case Study.

Interoperability is a prerequisite for health information systems (HIS) that will reduce waste of unnecessary costs, errors, delays, and futile repetition. Many previous studies had proposed different approaches in the attempt to solve interoperability challenges. In this paper, we report our experiences in using Health Level 7 (HL7) standard and adopting the Common Gateway Model for exchanging heath data. The benefits and challenges of using standards for data interoperability are also described.