Using Gene Expression Signatures to Identify Novel Treatment Strategies in Gulf War Illness

Background Gulf War Illness (GWI) is a complex multi-symptom disorder that affects up to one in three veterans of this 1991 conflict and for which no effective treatment has been found. Discovering novel treatment strategies for such a complex chronic illness is extremely expensive, carries a high probability of failure and a lengthy cycle time. Repurposing Food and Drug Administration approved drugs offers a cost-effective solution with a significantly abbreviated timeline. Methods Here, we explore drug re-purposing opportunities in GWI by combining systems biology and bioinformatics techniques with pharmacogenomic information to find overlapping elements in gene expression linking GWI to successfully treated diseases. Gene modules were defined based on cellular function and their activation estimated from the differential expression of each module’s constituent genes. These gene modules were then cross-referenced with drug atlas and pharmacogenomic databases to identify agents currently used successfully for treatment in other diseases. To explore the clinical use of these drugs in illnesses similar to GWI we compared gene expression patterns in modules that were significantly expressed in GWI with expression patterns in those same modules in other illnesses. Results We found 19 functional modules with significantly altered gene expression patterns in GWI. Within these modules, 45 genes were documented drug targets. Illnesses with highly correlated gene expression patterns overlapping considerably with GWI were found in 18 of the disease conditions studied. Brain, muscular and autoimmune disorders composed the bulk of these. Conclusion Of the associated drugs, immunosuppressants currently used in treating rheumatoid arthritis, and hormone based therapies were identified as the best available candidates for treating GWI symptoms

Myocardial Alternative RNA Splicing and Gene Expression Profiling in Early Stage Hypoplastic Left Heart Syndrome

Hypoplastic Left Heart Syndrome (HLHS) is a congenital defect characterized by underdevelopment of the left ventricle and pathological compensation of the right ventricle. If untreated, HLHS is invariably lethal due to the extensive increase in right ventricular workload and eventual failure. Despite the clinical significance, little is known about the molecular pathobiological state of HLHS. Splicing of mRNA transcripts is an important regulatory mechanism of gene expression. Tissue specific alterations of this process have been associated with several cardiac diseases, however, transcriptional signature profiles related to HLHS are unknown. In this study, we performed genome-wide exon array analysis to determine differentially expressed genes and alternatively spliced transcripts in the right ventricle (RV) of six neonates with HLHS, compared to the RV and left ventricle (LV) from non-diseased control subjects. In HLHS, over 180 genes were differentially expressed and 1800 were differentially spliced, leading to changes in a variety of biological processes involving cell metabolism, cytoskeleton, and cell adherence. Additional hierarchical clustering analysis revealed that differential gene expression and mRNA splicing patterns identified in HLHS are unique compared to non-diseased tissue. Our findings suggest that gene expression and mRNA splicing are broadly dysregulated in the RV myocardium of HLHS neonates. In addition, our analysis identified transcriptome profiles representative of molecular biomarkers of HLHS that could be used in the future for diagnostic and prognostic stratification to improve patient outcome

Integrated whole transcriptome and DNA methylation analysis identifies gene networks specific to late-onset Alzheimer’s disease

Previous transcriptome studies observed disrupted cellular processes in late-onset Alzheimer\u27s disease (LOAD), yet it is unclear whether these changes are specific to LOAD, or are common to general neurodegeneration. In this study, we address this question by examining transcription in LOAD and comparing it to cognitively normal controls and a cohort of disease controls. Differential transcription was examined using RNA-seq, which allows for the examination of protein coding genes, non-coding RNAs, and splicing. Significant transcription differences specific to LOAD were observed in five genes: C10orf105, DIO2, a lincRNA, RARRES3, and WIF1. These findings were replicated in two independent publicly available microarray data sets. Network analyses, performed on 2,504 genes with moderate transcription differences in LOAD, reveal that these genes aggregate into seven networks. Two networks involved in myelination and innate immune response specifically correlated to LOAD. FRMD4B and ST18, hub genes within the myelination network, were previously implicated in LOAD. Of the five significant genes, WIF1 and RARRES3 are directly implicated in the myelination process; the other three genes are located within the network. LOAD specific changes in DNA methylation were located throughout the genome and substantial changes in methylation were identified within the myelination network. Splicing differences specific to LOAD were observed across the genome and were decreased in all seven networks. DNA methylation had reduced influence on transcription within LOAD in the myelination network when compared to both controls. These results hint at the molecular underpinnings of LOAD and indicate several key processes, genes, and networks specific to the disease

Retinoblastoma treatment: impact of the glycolytic inhibitor 2-deoxy-d-glucose on molecular genomics expression in LHBETATAG retinal tumors

Purpose: The purpose of this study was to evaluate the effect of 2-deoxy-D-glucose (2-DG) on the spatial distribution of the genetic expression of key elements involved in angiogenesis, hypoxia, cellular metabolism, and apoptosis in LHBETATAG retinal tumors. Methods: The right eye of each LHBETATAG transgenic mouse (n = 24) was treated with either two or six subconjunctival injections of 2-DG (500 mg/kg) or saline control at 16 weeks of age. A gene expression array analysis was performed on five different intratumoral regions (apex, center, base, anterior-lateral, and posterior-lateral) using Affymetrix GeneChip Mouse Gene 1.0 ST arrays. To test for treatment effects of each probe within each region, a two-way analysis of variance was used. Results: Significant differences between treatment groups (ie, 0, 2, and 6 injections) were found as well as differences among the five retinal tumor regions evaluated (P \u3c 0.01). More than 100 genes were observed to be dysregulated by ≥2-fold difference in expression between the three treatment groups, and their dysregulation varied across the five regions assayed. Several genes involved in pathways important for tumor cell growth (ie, angiogenesis, hypoxia, cellular metabolism, and apoptosis) were identified. Conclusions: 2-DG was found to significantly alter the gene expression in LHBETATAG retinal tumor cells according to their location within the tumor as well as the treatment schedule. 2-DG’s effects on genetic expression found here correlate with previous reported results on varied processes involved in its in vitro and in vivo activity in inhibiting tumor cell growth

Cardiac performance, biomarkers and gene expression studies in previously sedentary men participating in half-marathon training

BACKGROUND: The mechanisms through which exercise reduces cardiovascular disease are not fully understood. We used echocardiograms, cardiac biomarkers and gene expression to investigate cardiovascular effects associated with exercise training. METHODS: Nineteen sedentary men (22-37 years) completed a 17-week half-marathon training program. Serial measurements of resting heart rate, blood pressure, maximum oxygen consumption, lipids, C-reactive protein, cardiac troponin T, echocardiograms and blood for gene expression were obtained from baseline to peak training. Controls included 22 sedentary men who did not exercise. RESULTS: Among the training group, VO2 max increased from 37.1 to 42.0 ml/kg/min (p \u3c 0.001). Significant changes were seen in left ventricular wall thickness and mass, stroke volume, resting heart rate and blood pressure (p \u3c 0.001). The control group demonstrated no significant changes. Expression profiling in the training group identified 10 significantly over-expressed and 53 significantly under-expressed loci involved in inflammatory pathways. Dividing the training group into high and low responders based on percent change in VO2 max identified loci that differentiated these two groups at baseline and after training. CONCLUSION: Intensive exercise training leads to significant increase in cardiac and hemodynamic performance, and significant changes in expression of genes involved in immune and inflammatory response.

INPP4B protects from metabolic syndrome and associated disorders

A high fat diet and obesity have been linked to the development of metabolic dysfunction and the promotion of multiple cancers. The causative cellular signals are multifactorial and not yet completely understood. In this report, we show that Inositol Polyphosphate-4-Phosphatase Type II B (INPP4B) signaling protects mice from diet-induced metabolic dysfunction. INPP4B suppresses AKT and PKC signaling in the liver thereby improving insulin sensitivity. INPP4B loss results in the proteolytic cleavage and activation of a key regulator in de novo lipogenesis and lipid storage, SREBP1. In mice fed with the high fat diet, SREBP1 increases expression and activity of PPARG and other lipogenic pathways, leading to obesity and non-alcoholic fatty liver disease (NAFLD). Inpp4b−/− male mice have reduced energy expenditure and respiratory exchange ratio leading to increased adiposity and insulin resistance. When treated with high fat diet, Inpp4b−/− males develop type II diabetes and inflammation of adipose tissue and prostate. In turn, inflammation drives the development of high-grade prostatic intraepithelial neoplasia (PIN). Thus, INPP4B plays a crucial role in maintenance of overall metabolic health and protects from prostate neoplasms associated with metabolic dysfunction

Genetic Predisposition for Immune System, Hormone, and Metabolic Dysfunction in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Pilot Study

Introduction: Myalgic Encephalomyelitis/ Chronic Fatigue Syndrome (ME/CFS) is a multifactorial illness of unknown etiology with considerable social and economic impact. To investigate a putative genetic predisposition to ME/CFS we conducted genome-wide single-nucleotide polymorphism (SNP) analysis to identify possible variants.Methods: 383 ME/CFS participants underwent DNA testing using the commercial company 23andMe. The deidentified genetic data was then filtered to include only non-synonymous and nonsense SNPs from exons and microRNAs, and SNPs close to splice sites. The frequencies of each SNP were calculated within our cohort and compared to frequencies from the Kaviar reference database. Functional annotation of pathway sets containing SNP genes with high frequency in ME/CFS was performed using over-representation analysis via ConsensusPathDB. Furthermore, these SNPs were also scored using the Combined Annotation Dependent Depletion (CADD) algorithm to gauge their deleteriousness.Results: 5693 SNPs were found to have at least 10% frequency in at least one cohort (ME/CFS or reference) and at least two-fold absolute difference for ME/CFS. Functional analysis identified the majority of SNPs as related to immune system, hormone, metabolic, and extracellular matrix organization. CADD scoring identified 517 SNPs in these pathways that are among the 10% most deleteriousness substitutions to the human genome

Unravelling myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) : Gender-specific changes in the microRNA expression profiling in ME/CFS

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a multisystem illness characterized by medically unexplained debilitating fatigue with suggested altered immunological state. Our study aimed to explore peripheral blood mononuclear cells (PBMCs) for microRNAs (miRNAs) expression in ME/CFS subjects under an exercise challenge. The findings highlight the immune response and inflammation links to differential miRNA expression in ME/CFS. The present study is particularly important in being the first to uncover the differences that exist in miRNA expression patterns in males and females with ME/CFS in response to exercise. This provides new evidence for the understanding of differential miRNA expression patterns and post-exertional malaise in ME/CFS. We also report miRNA expression pattern differences associating with the nutritional status in individuals with ME/CFS, highlighting the effect of subjects' metabolic state on molecular changes to be considered in clinical research within the NINDS/CDC ME/CFS Common Data Elements. The identification of gender-based miRNAs importantly provides new insights into gender-specific ME/CFS susceptibility and demands exploration of sex-suited ME/CFS therapeutics

Evidence of novel finescale structural variation at autism spectrum disorder candidate loci

Background: Autism spectrum disorders (ASD) represent a group of neurodevelopmental disorders characterized by a core set of social-communicative and behavioral impairments. Gamma-aminobutyric acid (GABA) is the major inhibitory neurotransmitter in the brain, acting primarily via the GABA receptors (GABR). Multiple lines of evidence, including altered GABA and GABA receptor expression in autistic patients, indicate that the GABAergic system may be involved in the etiology of autism. Methods: As copy number variations (CNVs), particularly rare and de novo CNVs, have now been implicated in ASD risk, we examined the GABA receptors and genes in related pathways for structural variation that may be associated with autism. We further extended our candidate gene set to include 19 genes and regions that had either been directly implicated in the autism literature or were directly related (via function or ancestry) to these primary candidates. For the high resolution CNV screen we employed custom-designed 244 k comparative genomic hybridization (CGH) arrays. Collectively, our probes spanned a total of 11 Mb of GABA-related and additional candidate regions with a density of approximately one probe every 200 nucleotides, allowing a theoretical resolution for detection of CNVs of approximately 1 kb or greater on average. One hundred and sixty-eight autism cases and 149 control individuals were screened for structural variants. Prioritized CNV events were confirmed using quantitative PCR, and confirmed loci were evaluated on an additional set of 170 cases and 170 control individuals that were not included in the original discovery set. Loci that remained interesting were subsequently screened via quantitative PCR on an additional set of 755 cases and 1,809 unaffected family members. Results: Results include rare deletions in autistic individuals at JAKMIP1, NRXN1, Neuroligin4Y, OXTR, and ABAT. Common insertion/deletion polymorphisms were detected at several loci, including GABBR2 and NRXN3. Overall, statistically significant enrichment in affected vs. unaffected individuals was observed for NRXN1 deletions. Conclusions: These results provide additional support for the role of rare structural variation in ASD