VAERS Vasculitis Adverse Events Retrospective Study: Etiology Model of Immune Complexes Activating Fc Receptors in Kawasaki Disease and Multisystem Inflammatory Syndromes.

BACKGROUND: Vasculitis diseases include Kawasaki disease (KD), Kawasaki disease shock syndrome (KDSS), Multisystem Inflammatory Syndrome (MIS), Henoch-Schönlein purpura (HS), or IgA vasculitis, and additional vasculitis diseases. These diseases are often preceded by infections or immunizations. Disease incidence rates are higher in children than in adults. These diseases have been extensively studied, but understanding of the disease etiology remains to be established. OBJECTIVE: Many studies have failed to demonstrate an association between vasculitis diseases and vaccination; this study examines possible associations. METHODS: Herein, the Vaccine Adverse Event Reporting System (VAERS) database is retrospectively examined for associations between vasculitis diseases and immunizations. RESULTS: For some vaccines, the number of rare cases of KD, MIS, and HS are higher than the background rates. These rare cases are predicted to occur in individuals with (1) genetic risk factors with (2) antibody titer levels above the primary immune response level. Herein, the model of humoral immune response antibodies bound to antigens (pathogen or vaccine) creating immune complexes is proposed. These immune complexes are proposed to bind Fc receptors on immune cells and platelets, resulting in cell activation and the release of inflammatory molecules including histamine and serotonin. Immune complexes and inflammatory molecules including serotonin and histamine likely trigger vasculitis. Elevated serotonin and possibly histamine drive initial vasoconstrictions, disrupting blood flow. Increased blood flow pressure from cardiac capillary vasoconstrictions is predicted to trigger coronary artery aneurysms (CAA) or lesions (CAL) in some patients. For KDSS and MIS patients, these cardiac capillary vasoconstrictions are predicted to result in ischemia followed by ventricular dysfunction. Ongoing ischemia can result in long-term cardiac damage. Cases associated with pathogens are likely to have persistent infections triggering disease onset. CONCLUSION: The proposed model of immune complexes driving disease initial disease etiology by Fc receptor activation of immune cells and platelets, resulting in elevated histamine and serotonin levels, is testable and is consistent with disease symptoms and current treatments.

Omics Analysis and Quality Control Pipelines in a High-Performance Computing Environment.

Data quality is often an overlooked feature in the analysis of omics data. This is particularly relevant in studies of chemical and pathogen exposures that can modify an individual's epigenome and transcriptome with persistence over time. Portable, quality control (QC) pipelines for multiple different omics datasets are therefore needed. To meet these goals, portable quality assurance (QA) metrics, metric acceptability criterion, and pipelines to compute these metrics were developed and consolidated into one framework for 12 different omics assays. Performance of these QA metrics and pipelines were evaluated on human data generated by the Defense Advanced Research Projects Agency (DARPA) Epigenetic CHaracterization and Observation (ECHO) program. Twelve analytical pipelines were developed leveraging standard tools when possible. These QC pipelines were containerized using Singularity to ensure portability and scalability. Datasets for these 12 omics assays were analyzed and results were summarized. The quality thresholds and metrics used were described. We found that these pipelines enabled early identification of lower quality datasets, datasets with insufficient reads for additional sequencing, and experimental protocols needing refinements. These omics data analysis and QC pipelines are available as open-source resources as reported and discussed in this article for the omics and life sciences communities.

Using FastID to analyze complex SNP mixtures from indoor dust.

Forensically relevant single nucleotide polymorphisms (SNPs) can provide valuable supplemental information to short tandem repeats (STRs) for investigative leads, and genotyping can now be streamlined using massively parallel sequencing (MPS). Dust is an attractive evidence source, as it accumulates on undisturbed surfaces, often is overlooked by perpetrators, and contains sufficient human DNA for analysis. To assess whether SNPs genotyped from indoor dust using MPS could be used to detect known household occupants, 13 households were recruited and provided buccal samples from each occupant and dust from five predefined indoor locations. Thermo Fisher Scientific Precision ID Identity and Ancestry Panels were utilized for SNP genotyping, and sequencing was completed using Illumina® chemistry. FastID, a software developed to permit mixture analysis and identity searching, was used to assess whether known occupants could be detected from associated household dust samples. A modified "subtraction" method was also used in FastID to estimate the percentage of alleles in each dust sample contributed by known and unknown occupants. On average, 72% of autosomal SNPs were recovered from dust samples. When using FastID, (a) 93% of known occupants were detected in at least one indoor dust sample and could not be excluded as contributors to the mixture, and (b) non-contributor alleles were detected in 54% of dust samples (29 ± 11 alleles per dust sample). Overall, this study highlights the potential of analyzing human DNA present in indoor dust to detect known household occupants, which could be valuable for investigative leads.

Elevated Histamine Etiology Model for Most Major Vaccine Associated Adverse Events including SARS-CoV-2 Spike Vaccines.

Vaccinees experience no adverse events, mild adverse events, multiple adverse events, or serious adverse events post vaccination. Many of these vaccine adverse events occur with different vaccines with different occurrence frequencies. Many of these adverse events are generally considered as associated with immune responses to the active vaccine components (antigens) and/or to possibly one or more of the vaccine excipients. Most of these vaccine adverse events are self-limiting and resolve within days. Many of these adverse events symptoms overlap symptoms associated with elevated histamine levels. Based on these observations, the hypothesis that the majority of vaccine associated reactogenicity adverse events are caused by temporal histamine intolerance in vaccinees is proposed. This hypothesis is based on a model of innate immune responses releasing a surge of inflammatory molecules including histamine; this surge is hypothesized to exceed the normal histamine tolerance level for vaccinees with reactogenicity adverse events. Further, these symptoms resolve as histamine levels fall below the vaccinee's tolerance threshold. This model can be evaluated by the detection of elevated histamine levels in vaccinees corresponding to timing of symptoms onset. If confirmed, a direct consequence of this model predicts that some antihistamine treatments, mast cell stabilizers, and possibly diamine oxidase enzyme may reduce the incidence or severity of adverse events experienced by vaccinees post vaccinations for most or all high reactogenicity vaccines including coronavirus disease 2019 (COVID-19) Spike vaccines.

Models for SARS-CoV-2 associated thrombocytopenia associated with hemophagocytic histiocytes.

A subset of COVID-19 patients is experiencing secondary immune thrombocytopenia, also called immune thrombocytopenic purpura (ITP) or secondary hemophagocytic lymphohistiocytosis (HLH). The pathogenesis of SARS-CoV-2 associated thrombocytopenia is unknown. Very rare cases of vaccine induced prothrombotic immune thrombocytopenia (VIPIT) are occurring associated with COVID-19 vaccines. COVID-19 VIPIT is associated with autoantibodies targeting platelet factor 4 (PF4) for COVID-19 adenovirus vaccines. Herein, four models for hemophagocytic histocytes contributions to the etiology of thrombocytopenia associated with SARS-CoV-2 are proposed. One of the models proposes potential involvement of hemophagocytic histocytes targeting platelets bound by autoantibodies consistent with observed PF4 autoantibodies in COVID-19 VIPIT.

Models for COVID-19 Early Cardiac Pathology Following SARS-CoV-2 Infection.

OBJECTIVES: The clinical manifestations of COVID-19 associated cardiac complications are heterogeneous, ranging from asymptomatic to severe symptoms, including arrhythmias and cardiogenic shock. For COVID-19 patients with cardiac sequela, only a small subset of patients have myocarditis; the pathogenesis of cardiac sequela caused by SARS-CoV-2 other than microthrombi associated sequela remains to be determined. METHODS: Retrospective analysis of 71 heart autopsy specimens from COVID-19 and putative COVID-19 in the NIH COVID Digital Pathology Repository. RESULTS: The most consistent observation was localized myocardial cell death not associated with either myocarditis or microthrombi. Red blood cells were typically absent from capillaries but, when observed, were predominately in linear clusters (stacks) of adjacent cells. CONCLUSIONS: Based on our retrospective analysis, we propose that localized ischemia and subsequent cell death by anoxia contributes to the cardiac pathogenesis in some COVID-19 patients. We propose two new models predicting vasoconstriction of cardiac pericyte cells induced by elevated histamine from hyper-activated mast cells or direct infection. We propose that impeded blood flow and cell death by anoxia are initial steps in the development of SARS-CoV-2 induced cardiac injury in COVID-19 patients independent of microthrombi or myocarditis.

COVID-19 Disease, Women's Predominant Non-Heparin Vaccine-Induced Thrombotic Thrombocytopenia and Kounis Syndrome: A Passepartout Cytokine Storm Interplay.

Coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) constitute one of the deadliest pandemics in modern history demonstrating cardiovascular, gastrointestinal, hematologic, mucocutaneous, respiratory, neurological, renal and testicular manifestations and further complications. COVID-19-induced excessive immune response accompanied with uncontrolled release of cytokines culminating in cytokine storm seem to be the common pathogenetic mechanism of these complications. The aim of this narrative review is to elucidate the relation between anaphylaxis associated with profound hypotension or hypoxemia with pro-inflammatory cytokine release. COVID-19 relation with Kounis syndrome and post-COVID-19 vaccination correlation with heparin-induced thrombocytopenia with thrombosis (HITT), especially serious cerebral venous sinus thrombosis, were also reviewed. METHODS: A current literature search in PubMed, Embase and Google databases was performed to reveal the pathophysiology, prevalence, clinical manifestation, correlation and treatment of COVID-19, anaphylaxis with profuse hypotension, Kounis acute coronary syndrome and thrombotic events post vaccination. RESULTS: The same key immunological pathophysiology mechanisms and cells seem to underlie COVID-19 cardiovascular complications and the anaphylaxis-associated Kounis syndrome. The myocardial injury in patients with COVID-19 has been attributed to coronary spasm, plaque rupture and microthrombi formation, hypoxic injury or cytokine storm disposing the same pathophysiology with the three clinical variants of Kounis syndrome. COVID-19-interrelated vaccine excipients as polysorbate, polyethelene glycol (PEG) and trometamol constitute potential allergenic substances. CONCLUSION: Better acknowledgement of the pathophysiological mechanisms, clinical similarities, multiorgan complications of COVID-19 or other viral infections as dengue and human immunodeficiency viruses along with the action of inflammatory cells inducing the Kounis syndrome could identify better immunological approaches for prevention, treatment of the COVID-19 pandemic as well as post-COVID-19 vaccine adverse reactions.

COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. SARS-CoV-2 infection is necessary but not sufficient for development of clinical COVID-19 disease. Currently, there are no approved pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We have investigated several plausible hypotheses for famotidine activity including antiviral and host-mediated mechanisms of action. We propose that the principal mechanism of action of famotidine for relieving COVID-19 symptoms involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release. Based on these findings and associated hypothesis, new COVID-19 multi-drug treatment strategies based on repurposing well-characterized drugs are being developed and clinically tested, and many of these drugs are available worldwide in inexpensive generic oral forms suitable for both outpatient and inpatient treatment of COVID-19 disease.

Two Different Antibody-Dependent Enhancement (ADE) Risks for SARS-CoV-2 Antibodies.

COVID-19 (SARS-CoV-2) disease severity and stages varies from asymptomatic, mild flu-like symptoms, moderate, severe, critical, and chronic disease. COVID-19 disease progression include lymphopenia, elevated proinflammatory cytokines and chemokines, accumulation of macrophages and neutrophils in lungs, immune dysregulation, cytokine storms, acute respiratory distress syndrome (ARDS), etc. Development of vaccines to severe acute respiratory syndrome (SARS), Middle East Respiratory Syndrome coronavirus (MERS-CoV), and other coronavirus has been difficult to create due to vaccine induced enhanced disease responses in animal models. Multiple betacoronaviruses including SARS-CoV-2 and SARS-CoV-1 expand cellular tropism by infecting some phagocytic cells (immature macrophages and dendritic cells) via antibody bound Fc receptor uptake of virus. Antibody-dependent enhancement (ADE) may be involved in the clinical observation of increased severity of symptoms associated with early high levels of SARS-CoV-2 antibodies in patients. Infants with multisystem inflammatory syndrome in children (MIS-C) associated with COVID-19 may also have ADE caused by maternally acquired SARS-CoV-2 antibodies bound to mast cells. ADE risks associated with SARS-CoV-2 has implications for COVID-19 and MIS-C treatments, B-cell vaccines, SARS-CoV-2 antibody therapy, and convalescent plasma therapy for patients. SARS-CoV-2 antibodies bound to mast cells may be involved in MIS-C and multisystem inflammatory syndrome in adults (MIS-A) following initial COVID-19 infection. SARS-CoV-2 antibodies bound to Fc receptors on macrophages and mast cells may represent two different mechanisms for ADE in patients. These two different ADE risks have possible implications for SARS-CoV-2 B-cell vaccines for subsets of populations based on age, cross-reactive antibodies, variabilities in antibody levels over time, and pregnancy. These models place increased emphasis on the importance of developing safe SARS-CoV-2 T cell vaccines that are not dependent upon antibodies.

COVID-19: Famotidine, Histamine, Mast Cells, and Mechanisms.

SARS-CoV-2 infection is required for COVID-19, but many signs and symptoms of COVID-19 differ from common acute viral diseases. Currently, there are no pre- or post-exposure prophylactic COVID-19 medical countermeasures. Clinical data suggest that famotidine may mitigate COVID-19 disease, but both mechanism of action and rationale for dose selection remain obscure. We explore several plausible avenues of activity including antiviral and host-mediated actions. We propose that the principal famotidine mechanism of action for COVID-19 involves on-target histamine receptor H2 activity, and that development of clinical COVID-19 involves dysfunctional mast cell activation and histamine release.

Analysis of complex DNA mixtures using massively parallel sequencing of SNPs with low minor allele frequencies.

DNA mixtures from 3 or more contributors have proven difficult to analyze using the current state-of-the-art method of short-tandem repeat (STR) amplification followed by capillary electrophoresis (CE). Here we analyze samples from both laboratory-defined mixtures and complex multi-contributor touch samples using a single nucleotide polymorphism (SNP) panel comprised of 2311 low-minor-allele-frequency loci, combined with massively parallel sequencing (MPS). This approach demonstrates that as many as 10 people can be identified in touch samples using a threshold of -Log P(RMNE) of 6, and a detection rate of 18-94 % across 10 different materials using a threshold of -Log P(RMNE) of 2. Thirty-two false positives were observed in 100 touch samples.

Predicting Influenza A Tropism with End-to-End Learning of Deep Networks.

The type of host that a virus can infect, referred to as host specificity or tropism, influences infectivity and thus is important for disease diagnosis, epidemic response, and prevention. Advances in DNA sequencing technology have enabled rapid metagenomic analyses of viruses, but the prediction of virus phenotype from genome sequences is an active area of research. As such, automatic prediction of host tropism from analysis of genomic information is of considerable utility. Previous research has applied machine learning methods to accomplish this task, although deep learning (particularly deep convolutional neural network, CNN) techniques have not yet been applied. These techniques have the ability to learn how to recognize critical hierarchical structures within the genome in a data-driven manner. We designed deep CNN models to identify host tropism for human and avian influenza A viruses based on protein sequences and performed a detailed analysis of the results. Our findings show that deep CNN techniques work as well as existing approaches (with 99% mean accuracy on the binary prediction task) while performing end-to-end learning of the prediction model (without the need to specify handcrafted features). The findings also show that these models, combined with standard principal component analysis, can be used to quantify and visualize viral strain similarity.

Estimating Individual Contributions to Complex DNA SNP Mixtures.

High-throughput sequencing (HTS) of large panels of single nucleotide polymorphisms (SNPs) provides an alternative or complimentary approach to short tandem repeats (STRs) panels for the analysis of complex DNA mixture forensic samples. For STRs, methods to estimate individual contribution concentrations compare capillary electrophoresis peak heights, peak areas, or HTS allele read counts within a mixture. This article introduces three approaches (mean, median, and slope methods) for estimating individual DNA contributions to forensic mixtures for HTS/massively parallel sequencing (MPS) SNP panels. For SNPs, the major:minor allele ratios or counts, unique to each contributor, were compared to estimate contributor proportion within the mixture using the mean, median, and slope intercept for these alleles. The estimates for these three methods were typically within 5% of planned experimental contributions for defined mixtures.

GrigoraSNPs: Optimized Analysis of SNPs for DNA Forensics.

High-throughput sequencing (HTS) of single nucleotide polymorphisms (SNPs) enables additional DNA forensic capabilities not attainable using traditional STR panels. However, the inclusion of sets of loci selected for mixture analysis, extended kinship, phenotype, biogeographic ancestry prediction, etc., can result in large panel sizes that are difficult to analyze in a rapid fashion. GrigoraSNP was developed to address the allele-calling bottleneck that was encountered when analyzing SNP panels with more than 5000 loci using HTS. GrigoraSNPs uses a MapReduce parallel data processing on multiple computational threads plus a novel locus-identification hashing strategy leveraging target sequence tags. This tool optimizes the SNP calling module of the DNA analysis pipeline with runtimes that scale linearly with the number of HTS reads. Results are compared with SNP analysis pipelines implemented with SAMtools and GATK. GrigoraSNPs removes a computational bottleneck for processing forensic samples with large HTS SNP panels.

Association Between Single Gene Polymorphisms and Bone Biomarkers and Response to Calcium and Vitamin D Supplementation in Young Adults Undergoing Military Training.

Initial military training (IMT) is associated with increased stress fracture risk. In prior studies, supplemental calcium (Ca) and vitamin D provided daily throughout IMT reduced stress fracture incidence, suppressed parathyroid hormone (PTH), and improved measures of bone health compared with placebo. Data were analyzed from a randomized, double-blind, placebo-controlled trial to determine whether single-nucleotide polymorphisms (SNPs) in Ca and vitamin D-related genes were associated with circulating biomarkers of bone metabolism in young adults entering IMT, and whether responses to Ca and vitamin D supplementation were modulated by genotype. Associations between SNPs, including vitamin D receptor (VDR), vitamin D binding protein (DBP), and 1-alpha-hydroxylase (CYP27B1), and circulating biomarkers were measured in fasting blood samples from volunteers (n = 748) starting IMT. Volunteers were block randomized by race and sex to receive Ca (2000 mg) and vitamin D (1000 IU) or placebo daily throughout Army or Air Force IMT (7 to 9 weeks). Total Ca and vitamin D intakes were calculated as the sum of supplemental intake based on intervention compliance and dietary intake. Relationships between SNPs, Ca, and vitamin D intake tertile and change in biomarkers were evaluated in trial completers (n = 391). At baseline, the minor allele of a DBP SNP (rs7041) was positively associated with both 25OHD (B = 4.46, p = 1.97E-10) and 1,25(OH)2 D3 (B = 9.63, p < 0.001). Combined genetic risk score (GRS) for this SNP and a second SNP in the VDR gene (rs1544410) was inversely associated with baseline 25OHD (r = -0.28, p < 0.001) and response to Ca and vitamin D intake differed by GRS (p < 0.05). In addition, presence of the minor allele of a second VDR SNP (rs2228570) was associated with lower P1NP (B = -4.83, p = 0.04) and osteocalcin (B = -0.59, p = 0.03). These data suggest that VDR and DBP SNPs are associated with 25OHD status and bone turnover and those with the highest GRS require the greatest vitamin D intake to improve 25OHD during IMT. © 2016 American Society for Bone and Mineral Research.

In vivo Monitoring of Transcriptional Dynamics After Lower-Limb Muscle Injury Enables Quantitative Classification of Healing.

Traumatic lower-limb musculoskeletal injuries are pervasive amongst athletes and the military and typically an individual returns to activity prior to fully healing, increasing a predisposition for additional injuries and chronic pain. Monitoring healing progression after a musculoskeletal injury typically involves different types of imaging but these approaches suffer from several disadvantages. Isolating and profiling transcripts from the injured site would abrogate these shortcomings and provide enumerative insights into the regenerative potential of an individual's muscle after injury. In this study, a traumatic injury was administered to a mouse model and healing progression was examined from 3 hours to 1 month using high-throughput RNA-Sequencing (RNA-Seq). Comprehensive dissection of the genome-wide datasets revealed the injured site to be a dynamic, heterogeneous environment composed of multiple cell types and thousands of genes undergoing significant expression changes in highly regulated networks. Four independent approaches were used to determine the set of genes, isoforms, and genetic pathways most characteristic of different time points post-injury and two novel approaches were developed to classify injured tissues at different time points. These results highlight the possibility to quantitatively track healing progression in situ via transcript profiling using high- throughput sequencing.

Genomic approaches to drug discovery.

Considerable progress has been made in exploiting the enormous amount of genomic and genetic information for the identification of potential targets for drug discovery and development. New tools that incorporate pathway information have been developed for gene expression data mining to reflect differences in pathways in normal and disease states. In addition, forward and reverse genetics used in a high-throughput mode with full-length cDNA and RNAi libraries enable the direct identification of components of signaling pathways. The discovery of the regulatory function of microRNAs highlights the importance of continuing the investigation of the genome with sophisticated tools. Furthermore, epigenetic information including DNA methylation and histone modifications that mediate important biological processes add to the possibilities to identify novel drug targets and patient populations that will benefit from new therapies.