Gene expression analysis in children with complex seizures due to influenza A(H1N1)pdm09 or rotavirus gastroenteritis

Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures

PURPOSE

Combinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning (ML) based signatures (with 8-20% misclassification rates). These signatures can quantify therapeutically relevant as well as accidental radiation exposures. The prodromal symptoms of acute radiation syndrome (ARS) overlap those present in influenza and dengue fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy.

METHODS

This study investigated recall by previous and novel radiation signatures independently derived from multiple Gene Expression Omnibus datasets on common and rare non-neoplastic blood disorders and blood-borne infections (thromboembolism, S. aureus bacteremia, malaria, sickle cell disease, polycythemia vera, and aplastic anemia). Normalized expression levels of signature genes are used as input to ML-based classifiers to predict radiation exposure in other hematological conditions.

RESULTS

Except for aplastic anemia, these blood-borne disorders modify the normal baseline expression values of genes present in radiation signatures, leading to false-positive misclassification of radiation exposures in 8-54% of individuals. Shared changes, predominantly in DNA damage response and apoptosis-related gene transcripts in radiation and confounding hematological conditions, compromise the utility of these signatures for radiation assessment. These confounding conditions (sickle cell disease, thrombosis, S. aureus bacteremia, malaria) induce neutrophil extracellular traps, initiated by chromatin decondensation, DNA damage response and fragmentation followed by programmed cell death or extrusion of DNA fragments. Riboviral infections (e.g. influenza or dengue fever) have been proposed to bind and deplete host RNA binding proteins, inducing R-loops in chromatin. R-loops that collide with incoming replication forks can result in incompletely repaired DNA damage, inducing apoptosis and releasing mature virus. To mitigate the effects of confounders, we evaluated predicted radiation-positive samples with novel gene expression signatures derived from radiation-responsive transcripts encoding secreted blood plasma proteins whose expression levels are unperturbed by these conditions.

CONCLUSIONS

This approach identifies and eliminates misclassified samples with underlying hematological or infectious conditions, leaving only samples with true radiation exposures. Diagnostic accuracy is significantly improved by selecting genes that maximize both sensitivity and specificity in the appropriate tissue using combinations of the best signatures for each of these classes of signatures.

Measurement of Cellular Immune Response to Viral Infection and Vaccination

Combined cellular and humoral host immune response determine the clinical course of a viral infection and effectiveness of vaccination, but currently the cellular immune response cannot be measured on simple blood samples. As functional activity of immune cells is determined by coordinated activity of signaling pathways, we developed mRNA-based JAK-STAT signaling pathway activity assays to quantitatively measure the cellular immune response on Affymetrix expression microarray data of various types of blood samples from virally infected patients (influenza, RSV, dengue, yellow fever, rotavirus) or vaccinated individuals, and to determine vaccine immunogenicity. JAK-STAT1/2 pathway activity was increased in blood samples of patients with viral, but not bacterial, infection and was higher in influenza compared to RSV-infected patients, reflecting known differences in immunogenicity. High JAK-STAT3 pathway activity was associated with more severe RSV infection. In contrast to inactivated influenza virus vaccine, live yellow fever vaccine did induce JAK-STAT1/2 pathway activity in blood samples, indicating superior immunogenicity. Normal (healthy) JAK-STAT1/2 pathway activity was established, enabling assay interpretation without the need for a reference sample. The JAK-STAT pathway assays enable measurement of cellular immune response for prognosis, therapy stratification, vaccine development, and clinical testing.

Microarray Gene Expression Dataset Re-analysis Reveals Variability in Influenza Infection and Vaccination

Influenza, a communicable disease, affects thousands of people worldwide. Young children, elderly, immunocompromised individuals and pregnant women are at higher risk for being infected by the influenza virus. Our study aims to highlight differentially expressed genes in influenza disease compared to influenza vaccination, including variability due to age and sex. To accomplish our goals, we conducted a meta-analysis using publicly available microarray expression data. Our inclusion criteria included subjects with influenza, subjects who received the influenza vaccine and healthy controls. We curated 18 microarray datasets for a total of 3,481 samples (1,277 controls, 297 influenza infection, 1,907 influenza vaccination). We pre-processed the raw microarray expression data in R using packages available to pre-process Affymetrix and Illumina microarray platforms. We used a Box-Cox power transformation of the data prior to our down-stream analysis to identify differentially expressed genes. Statistical analyses were based on linear mixed effects model with all study factors and successive likelihood ratio tests (LRT) to identify differentially-expressed genes. We filtered LRT results by disease (Bonferroni adjusted p < 0.05) and used a two-tailed 10% quantile cutoff to identify biologically significant genes. Furthermore, we assessed age and sex effects on the disease genes by filtering for genes with a statistically significant (Bonferroni adjusted p < 0.05) interaction between disease and age, and disease and sex. We identified 4,889 statistically significant genes when we filtered the LRT results by disease factor, and gene enrichment analysis (gene ontology and pathways) included innate immune response, viral process, defense response to virus, Hematopoietic cell lineage and NF-kappa B signaling pathway. Our quantile filtered gene lists comprised of 978 genes each associated with influenza infection and vaccination. We also identified 907 and 48 genes with statistically significant (Bonferroni adjusted p < 0.05) disease-age and disease-sex interactions, respectively. Our meta-analysis approach highlights key gene signatures and their associated pathways for both influenza infection and vaccination. We also were able to identify genes with an age and sex effect. This gives potential for improving current vaccines and exploring genes that are expressed equally across ages when considering universal vaccinations for influenza.

Single-sample landscape entropy reveals the imminent phase transition during disease progression

Motivation

The time evolution or dynamic change of many biological systems during disease progression is not always smooth but occasionally abrupt, that is, there is a tipping point during such a process at which the system state shifts from the normal state to a disease state. It is challenging to predict such disease state with the measured omics data, in particular when only a single sample is available.

Results

In this study, we developed a novel approach, i.e. single-sample landscape entropy (SLE) method, to identify the tipping point during disease progression with only one sample data. Specifically, by evaluating the disorder of a network projected from a single-sample data, SLE effectively characterizes the criticality of this single sample network in terms of network entropy, thereby capturing not only the signals of the impending transition but also its leading network, i.e. dynamic network biomarkers. Using this method, we can characterize sample-specific state during disease progression and thus achieve the disease prediction of each individual by only one sample. Our method was validated by successfully identifying the tipping points just before the serious disease symptoms from four real datasets of individuals or subjects, including influenza virus infection, lung cancer metastasis, prostate cancer and acute lung injury.

Availability and implementation

https://github.com/rabbitpei/SLE.

Supplementary information

Supplementary data are available at Bioinformatics online.

Comparison of the detection performance of two different one-step-combined test strips with fluorescent microspheres or colored microspheres as tracers for influenza A and B viruses

Background

Influenza A and B viruses mainly cause respiratory infectious disease. Till now, few tests are able to simultaneously detect both, especially in primary medical establishments.

Methods

This study was designed to compare the performance of two different one-step-combined test strips for the detection of influenza A and B: one strip with fluorescent microspheres for tracers (FMT); and the other strip with colored microspheres for tracers (CMT). To test the strips, cultures of influenza A, B, and other pathogenic viruses were used, in addition to 1085 clinical specimens from symptomatic patients with respiratory infections. Real-time RT-PCR was also considered as a reference method used to detect the different results of FMT and CTM.

Results

Detection thresholds for influenza A and B cultures using serial dilutions revealed that the sensitivity of FMT was higher than that of CMT (both P < 0.05). With the culture mixtures of Coxsackie virus (A16), enteric cytopathic human orphan virus (ECHO type30), enterovirus (EV71), rotavirus (LLR strain), and enteric adenovirus (AdV 41), specificity assessment demonstrated that there was no cross reaction during the usage of the two test strips as shown by the results which were negative. In the detection of influenza A in 1085 clinical specimens, the total coincidence rate was 96.7%, the positive coincidence rate was 97.1%, and the negative coincidence rate was 96.7%. In the case of influenza B detection, the total coincidence rate was 99.1%, the positive coincidence rate was 92.6%, and the negative coincidence rate was 98.5%. In addition, with influenza A or B real-time RT-PCR detection method, the results showed that, for influenza A, 26 of the 33 specimens that negative with CMT but positive with FMT, showed positive results, and none of the 3 specimens that positive with CMT but negative with FMT showed a positive result; For influenza B, 12 of the 15 specimens that negative with CMT but positive with FMT, showed positive results, and none of the 5 specimens that positive with CMT but negative with FMT showed a positive result.

Conclusions

FMT performed better than CMT in the combined detection of influenza A and B viruses.

Rotavirus Gastroenteritis Associated with Encephalopathy, Myositis, Transaminitis and Hypoalbuminemia

Rotavirus is a common cause of acute gastroenteritis in children. Manifestations of rotavirus gastroenteritis beyond gastrointestinal tract are rare. Rotavirus has been reported to be associated with encephalopathy, myositis and elevated liver enzymes; but simultaneous presentation of all these conditions in the same child is extremely rare. The authors report a case of 17-mo-old girl who presented with acute rotavirus gastroenteritis with G3 + G9P[8] strain associated with hypernatremia, encephalopathy, myositis, transaminitis and hypoalbuminemia. Child had complete recovery with no neurological sequalae on follow-up, and liver enzymes and albumin returned to normal. The authors suggest that rotavirus infection should be considered in the differential diagnosis of a child with encephalopathy or myositis, particularly if associated with acute diarrhea.

A curated transcriptome dataset collection to investigate the blood transcriptional response to viral respiratory tract infection and vaccination

The human immune defense mechanisms and factors associated with good versus poor health outcomes following viral respiratory tract infections (VRTI), as well as correlates of protection following vaccination against respiratory viruses, remain incompletely understood. To shed further light into these mechanisms, a number of systems-scale studies have been conducted to measure transcriptional changes in blood leukocytes of either naturally or experimentally infected individuals, or in individual’s post-vaccination. Here we are making available a public repository, for research investigators for interpretation, a collection of transcriptome datasets obtained from human whole blood and peripheral blood mononuclear cells (PBMC) to investigate the transcriptional responses following viral respiratory tract infection or vaccination against respiratory viruses. In total, Thirty one31 datasets, associated to viral respiratory tract infections and their related vaccination studies, were identified and retrieved from the NCBI Gene Expression Omnibus (GEO) and loaded in a custom web application designed for interactive query and visualization of integrated large-scale data. Quality control checks, using relevant biological markers, were performed. Multiple sample groupings and rank lists were created to facilitate dataset query and interpretation. Via this interface, users can generate web links to customized graphical views, which may be subsequently inserted into manuscripts to report novel findings. The GXB tool enables browsing of a single gene across projects, providing new perspectives on the role of a given molecule across biological systems in the diagnostic and prognostic following VRTI but also in identifying new correlates of protection. This dataset collection is available at: http://vri1.gxbsidra.org/dm3/geneBrowser/list.

Review and Meta-Analyses of TAAR1 Expression in the Immune System and Cancers

Since its discovery in 2001, the major focus of TAAR1 research has been on its role in monoaminergic regulation, drug-induced reward and psychiatric conditions. More recently, TAAR1 expression and functionality in immune system regulation and immune cell activation has become a topic of emerging interest. Here, we review the immunologically-relevant TAAR1 literature and incorporate open-source expression and cancer survival data meta-analyses. We provide strong evidence for TAAR1 expression in the immune system and cancers revealed through NCBI GEO datamining and discuss its regulation in a spectrum of immune cell types as well as in numerous cancers. We discuss connections and logical directions for further study of TAAR1 in immunological function, and its potential role as a mediator or modulator of immune dysregulation, immunological effects of psychostimulant drugs of abuse, and cancer progression.

Different Metabolic Pathways Are Involved in Response of Saccharomyces cerevisiae to L-A and M Viruses

Competitive and naturally occurring yeast killer phenotype is governed by coinfection with dsRNA viruses. Long-term relationship between the host cell and viruses appear to be beneficial and co-adaptive; however, the impact of viral dsRNA on the host gene expression has barely been investigated. Here, we determined the transcriptomic profiles of the host Saccharomyces cerevisiae upon the loss of the M-2 dsRNA alone and the M-2 along with the L-A-lus dsRNAs. We provide a comprehensive study based on the high-throughput RNA-Seq data, Gene Ontology and the analysis of the interaction networks. We identified 486 genes differentially expressed after curing yeast cells of the M-2 dsRNA and 715 genes affected by the elimination of both M-2 and L-A-lus dsRNAs. We report that most of the transcriptional responses induced by viral dsRNAs are moderate. Differently expressed genes are related to ribosome biogenesis, mitochondrial functions, stress response, biosynthesis of lipids and amino acids. Our study also provided insight into the virus–host and virus–virus interplays.

A Four-Biomarker Blood Signature Discriminates Systemic Inflammation Due to Viral Infection Versus Other Etiologies

The innate immune system of humans and other mammals responds to pathogen-associated molecular patterns (PAMPs) that are conserved across broad classes of infectious agents such as bacteria and viruses. We hypothesized that a blood-based transcriptional signature could be discovered indicating a host systemic response to viral infection. Previous work identified host transcriptional signatures to individual viruses including influenza, respiratory syncytial virus and dengue, but the generality of these signatures across all viral infection types has not been established. Based on 44 publicly available datasets and two clinical studies of our own design, we discovered and validated a four-gene expression signature in whole blood, indicative of a general host systemic response to many types of viral infection. The signature’s genes are: Interferon Stimulated Gene 15 (ISG15), Interleukin 16 (IL16), 2′,5′-Oligoadenylate Synthetase Like (OASL), and Adhesion G Protein Coupled Receptor E5 (ADGRE5). In each of 13 validation datasets encompassing human, macaque, chimpanzee, pig, mouse, rat and all seven Baltimore virus classification groups, the signature provides statistically significant (p < 0.05) discrimination between viral and non-viral conditions. The signature may have clinical utility for differentiating host systemic inflammation (SI) due to viral versus bacterial or non-infectious causes.

Gene expression analysis of hypersensitivity to mosquito bite, chronic active EBV infection and NK/T-lymphoma/leukemia

The human herpes virus, Epstein-Barr virus (EBV), is a known oncogenic virus and plays important roles in life-threatening T/NK-cell lymphoproliferative disorders (T/NK-cell LPD) such as hypersensitivity to mosquito bite (HMB), chronic active EBV infection (CAEBV), and NK/T-cell lymphoma/leukemia. During the clinical courses of HMB and CAEBV, patients frequently develop malignant lymphomas and the diseases passively progress sequentially. In the present study, gene expression of CD16^(-)CD56⁽⁺⁾-, EBV⁽⁺⁾ HMB, CAEBV, NK-lymphoma, and NK-leukemia cell lines, which were established from patients, was analyzed using oligonucleotide microarrays and compared to that of CD56^brightCD16^dim/- NK cells from healthy donors. Principal components analysis showed that CAEBV and NK-lymphoma cells were relatively closely located, indicating that they had similar expression profiles. Unsupervised hierarchal clustering analyses of microarray data and gene ontology analysis revealed specific gene clusters and identified several candidate genes responsible for disease that can be used to discriminate each category of NK-LPD and NK-cell lymphoma/leukemia.

Febrile Seizures and Febrile Seizure Syndromes: An Updated Overview of Old and Current Knowledge

Febrile seizures are the most common paroxysmal episode during childhood, affecting up to one in 10 children. They are a major cause of emergency facility visits and a source of family distress and anxiety. Their etiology and pathophysiological pathways are being understood better over time; however, there is still more to learn. Genetic predisposition is thought to be a major contributor. Febrile seizures have been historically classified as benign; however, many emerging febrile seizure syndromes behave differently. The way in which human knowledge has evolved over the years in regard to febrile seizures has not been dealt with in depth in the current literature, up to our current knowledge. This review serves as a documentary of how scientists have explored febrile seizures, elaborating on the journey of knowledge as far as etiology, clinical features, approach, and treatment strategies are concerned. Although this review cannot cover all clinical aspects related to febrile seizures at the textbook level, we believe it can function as a quick summary of the past and current sources of knowledge for all varieties of febrile seizure types and syndromes.