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Phenylalanine hydroxylase deficient phenylketonuria (PKU) is the paradigm for a treatable inborn error of metabolism where maintaining plasma phenylalanine (Phe) in the therapeutic range relates to improved clinical outcomes. While Phe is the presumed intoxicating analyte causal in neurologic damage, the mechanism(s) of Phe toxicity has remained elusive. Altered DNA methylation is a recognized response associated with exposure to numerous small molecule toxic agents. Paralleling this effect, we hypothesized that chronic Phe over-exposure in the brain would lead to aberrant DNA methylation with secondary influence upon gene regulation that would ultimately contribute to PKU neuropathology. The PAH enu2 mouse models human PKU with intrinsic hyperphenylalaninemia, abnormal response to Phe challenge, and neurologic deficit. To examine this hypothesis, we assessed DNA methylation patterns in brain tissues using methylated DNA immunoprecipitation and paired end sequencing in adult PAH enu2 animals maintained under either continuous dietary Phe restriction or chronic hyperphenylalaninemia. Heterozygous PAH enu2/WT litter mates served as controls for normal Phe exposure. Extensive repatterning of DNA methylation was observed in brain tissue of hyperphenylalaninemic animals while Phe restricted animals displayed an attenuated pattern of aberrant DNA methylation. Affected gene coding regions displayed aberrant hypermethylation and hypomethylation. Gene body methylation of noncoding RNA genes was observed and among these microRNA genes were prominent. Of particular note, observed only in hyperphenylalaninemic animals, was hypomethylation of miRNA genes within the imprinted Dlk1-Dio3 locus on chromosome 12. Aberrant methylation of microRNA genes influenced their expression which has secondary effects upon the expression of targeted protein coding genes. Differential hypermethylation of gene promoters was exclusive to hyperphenylalaninemic PAH enu2 animals. Genes with synaptic involvement were targets of promoter hypermethylation that resulted in down-regulation of their expression. Gene dysregulation secondary to abnormal DNA methylation may be contributing to PKU neuropathology. These results suggest drugs that prevent or correct aberrant DNA methylation may offer a novel therapeutic option to management of neurological symptoms in PKU patients. [ABSTRACT FROM AUTHOR]

Abstract Background Decision analysis techniques can be applied in complex situations involving uncertainty and the consideration of multiple objectives. Classical decision modeling techniques require elicitation of too many parameter estimates and their conditional (joint) probabilities, and have not therefore been applied to the problem of identifying high-performance, cost-effective combinations of clinical options for diagnosis or treatments where many of the objectives are unknown or even unspecified. Methods We designed a Java-based software resource, the Clinical Decision Modeling System (CDMS), to implement Naïve Decision Modeling, and provide a use case based on published performance evaluation measures of various strategies for breast and lung cancer detection. Because cost estimates for many of the newer methods are not yet available, we assume equal cost. Our use case reveals numerous potentially high-performance combinations of clinical options for the detection of breast and lung cancer. Results Naïve Decision Modeling is a highly practical applied strategy which guides investigators through the process of establishing evidence-based integrative translational clinical research priorities. CDMS is not designed for clinical decision support. Inputs include performance evaluation measures and costs of various clinical options. The software finds trees with expected emergent performance characteristics and average cost per patient that meet stated filtering criteria. Key to the utility of the software is sophisticated graphical elements, including a tree browser, a receiver-operator characteristic surface plot, and a histogram of expected average cost per patient. The analysis pinpoints the potentially most relevant pairs of clinical options ('critical pairs') for which empirical estimates of conditional dependence may be critical. The assumption of independence can be tested with retrospective studies prior to the initiation of clinical trials designed to estimate clinical impact. High-performance combinations of clinical options may exist for breast and lung cancer detection. Conclusion The software could be found useful in simplifying the objective-driven planning of complex integrative clinical studies without requiring a multi-attribute utility function, and it could lead to efficient integrative translational clinical study designs that move beyond simple pair wise competitive studies. Collaborators, who traditionally might compete to prioritize their own individual clinical options, can use the software as a common framework and guide to work together to produce increased understanding on the benefits of using alternative clinical combinations to affect strategic and cost-effective clinical workflows.

Abstract Background Microarray studies in cancer compare expression levels between two or more sample groups on thousands of genes. Data analysis follows a population-level approach (e.g., comparison of sample means) to identify differentially expressed genes. This leads to the discovery of 'population-level' markers, i.e., genes with the expression patterns A > B and B > A. We introduce the PPST test that identifies genes where a significantly large subset of cases exhibit expression values beyond upper and lower thresholds observed in the control samples. Results Interestingly, the test identifies A > B and B < A pattern genes that are missed by population-level approaches, such as the t-test, and many genes that exhibit both significant overexpression and significant underexpression in statistically significantly large subsets of cancer patients (ABA pattern genes). These patterns tend to show distributions that are unique to individual genes, and are aptly visualized in a 'gene expression pattern grid'. The low degree of among-gene correlations in these genes suggests unique underlying genomic pathologies and high degree of unique tumor-specific differential expression. We compare the PPST and the ABA test to the parametric and non-parametric t-test by analyzing two independently published data sets from studies of progression in astrocytoma. Conclusions The PPST test resulted findings similar to the nonparametric t-test with higher self-consistency. These tests and the gene expression pattern grid may be useful for the identification of therapeutic targets and diagnostic or prognostic markers that are present only in subsets of cancer patients, and provide a more complete portrait of differential expression in cancer.

Background: The COVID-19 pandemic has placed significant stressors on the medical community and on the general public. Part of this includes patients skipping well-child visits to reduce risk of exposure to SARS-CoV-2 virus. Published estimates of the duration of whole-body aluminum (Al) toxicity from vaccines in infants from birth to six months indicate that CDC's recommended vaccination schedule leads to unacceptably long periods of time in which infants are in aluminum toxicity (as measured by %AlumTox)., Methods: We utilize these established clearance and accumulation models to calculate expected per-body-weight whole-body toxicity of aluminum from vaccines considering for children of all ages under CDC's Catch-Up schedule from birth to ten years, assuming social distancing for 6 months. Our updated Pediatric Dose Limit (PDL) model assumes a linear improvement in renal function from birth to two years., Results: Our results indicate that due diligence in considering alternative spacing and use of non-aluminum containing vaccines when possible will reduce whole body toxicity and may reduce risk of morbidity associated with exposure to aluminum., Conclusions: While reduction or elimination of aluminum exposure from all sources is always a good idea, our results indicate that careful consideration of expected aluminum exposures during regular and Catch-Up vaccination is found to be especially important for infants and children below 2 years of age. We urge caution in the mass re-starting of vaccination under CDC's Catch-Up schedule for children under 12 months and offer alternative strategies to minimize per-day/week/month exposure to aluminum hydroxide following the COVID-19 period of isolation., (Copyright © 2020 The Author(s). Published by Elsevier GmbH.. All rights reserved.)

We performed a retrospective analysis spanning ten years of pediatric practice focused on patients with variable vaccination born into a practice, presenting a unique opportunity to study the effects of variable vaccination on outcomes. The average total incidence of billed office visits per outcome related to the outcomes were compared across groups (Relative Incidence of Office Visit (RIOV)). RIOV is shown to be more powerful than odds ratio of diagnoses. Full cohort, cumulative incidence analyses, matched for days of care, and matched for family history analyses were conducted across quantiles of vaccine uptake. Increased office visits related to many diagnoses were robust to days-of-care-matched analyses, family history, gender block, age block, and false discovery risk. Many outcomes had high RIOV odds ratios after matching for days-of-care (e.g., anemia (6.334), asthma (3.496), allergic rhinitis (6.479), and sinusitis (3.529), all significant under the Z-test). Developmental disorders were determined to be difficult to study due to extremely low prevalence in the practice, potentially attributable to high rates of vaccine cessation upon adverse events and family history of autoimmunity. Remarkably, zero of the 561 unvaccinated patients in the study had attention deficit hyperactivity disorder (ADHD) compared to 0.063% of the (partially and fully) vaccinated. The implications of these results for the net public health effects of whole-population vaccination and with respect for informed consent on human health are compelling. Our results give agency to calls for research conducted by individuals who are independent of any funding sources related to the vaccine industry. While the low rates of developmental disorders prevented sufficiently powered hypothesis testing, it is notable that the overall rate of autism spectrum disorder (0.84%) in the cohort is half that of the US national rate (1.69%). The practice-wide rate of ADHD was roughly half of the national rate. The data indicate that unvaccinated children in the practice are not unhealthier than the vaccinated and indeed the overall results may indicate that the unvaccinated pediatric patients in this practice are healthier overall than the vaccinated.

Fibrosis is a chronic disease with heterogeneous clinical presentation, rate of progression, and occurrence of comorbidities. Systemic sclerosis (scleroderma, SSc) is a rare rheumatic autoimmune disease that encompasses several aspects of fibrosis, including highly variable fibrotic manifestation and rate of progression. The development of effective treatments is limited by these variabilities. The fibrotic response is characterized by both chronic inflammation and extracellular remodeling. Therefore, there is a need for improved understanding of which inflammation-related genes contribute to the ongoing turnover of extracellular matrix that accompanies disease. We have developed a multi-tiered method using Naïve Bayes modeling that is capable of predicting level of disease and clinical assessment of patients based on expression of a curated 60-gene panel that profiles inflammation and extracellular matrix production in the fibrotic disease state. Our novel modeling design, incorporating global and parametric-based methods, was highly accurate in distinguishing between severity groups, highlighting the importance of these genes in disease. We refined this gene set to a 12-gene index that can accurately identify SSc patient disease state subsets and informs knowledge of the central regulatory pathways in disease progression., Competing Interests: The authors have declared that no competing interests exist.

Homology between human and viral proteins is an established factor in viral- or vaccine-induced autoimmunity. Failure of SARS and MERS vaccines in animal trials involved pathogenesis consistent with an immunological priming that could involve autoimmunity in lung tissues due to previous exposure to the SARS and MERS spike protein. Exposure pathogenesis to SARS-CoV-2 in COVID-19 likely will lead to similar outcomes. Immunogenic peptides in viruses or bacteria that match human proteins are good candidates for pathogenic priming peptides (similar to the more diffuse idea of "immune enhancement"). Here I provide an assessment of potential for human pathogenesis via autoimmunity via exposure, via infection or injection. SAR-CoV-2 spike proteins, and all other SARS-CoV-2 proteins, immunogenic epitopes in each SARS-CoV-2 protein were compared to human proteins in search of high local homologous matching. Only one immunogenic epitope in a SARS-CoV-2 had no homology to human proteins. If all of the parts of the epitopes that are homologous to human proteins are excluded from consideration due to risk of pathogenic priming, the remaining immunogenic parts of the epitopes may be still immunogenic and remain as potentially viable candidates for vaccine development. Mapping of the genes encoding human protein matches to pathways point to targets that could explain the observed presentation of symptoms in COVID-19 disease. It also strongly points to a large number of opportunities for expected disturbances in the immune system itself, targeting elements of MHC Class I and Class II antigen presentation, PD-1 signaling, cross-presentation of soluble exogenous antigens and the ER-Phagosome pathway. Translational consequences of these findings are explored., Competing Interests: Dr. Lyons-Weiler has, in the past, served as expert witness in the National Vaccine Injury Compensation Program., (© 2020 The Author(s).)

Like the mechanisms of action as adjuvants, the pharmacodynamics of injected forms of aluminum commonly used in vaccines are not well-characterized, particularly with respect to how differences in schedules impact accumulation and how factors such as genetics and environmental influences on detoxification influence clearance. Previous modeling efforts are based on very little empirical data, with the model by Priest based on whole-body clearance rates estimated from a study involving a single human subject. In this analysis, we explore the expected acute exposures and longer-term whole-body accumulation/clearance across three vaccination schedules: the current US Centers for Disease Control and Prevention (CDC) schedule, the current CDC schedule using low aluminum or no aluminum vaccines, and Dr. Paul Thomas' "Vaccine Friendly Plan" schedule. We then study the effects of an implicit assumption of the Priest model on whether clearance dynamics from successive doses are influenced by the current level of aluminum or modeled by the assumption that a new dose has its own whole-body dynamics "reset" on the day of injection. We model two additional factors: variation (deficiency) in aluminum detoxification, and a factor added to the Priest equation to model the potential impact of aluminum itself on cellular and whole-body detoxification. These explorations are compared to a previously estimated pediatric dose limit (PDL) of whole-body aluminum exposure and provide a new statistic: %alumTox, the (expected) percentage of days (or weeks) an infant is in aluminum toxicity, reflecting chronic toxicity. We show that among three schedules, the CDC schedule results in the highest %alumTox regardless of model assumptions, and the Vaccine Friendly Plan schedule, which avoids >1 ACV per office visit results in the lowest (expected) %alumTox. These results are conservative, as the MSL is derived from data used by FDA to estimate safety of aluminum in adult humans. These results demonstrate high potential utility of modeling variation in patient responses to aluminum. More empirical data from individuals who are suspected of being intolerant of aluminum from vaccines, evidenced by high aluminum retention, neurodevelopmental disorders and/or a myriad of chronic illnesses would help answer questions on whether the model predictions can be used to estimate parameter values tied to genetic factors including genomic sequence variation and family history of chronic illnesses tied to aluminum exposure., Competing Interests: Declaration of Competing Interest JLW is a (sometimes) compensated expert witness in cases in the US National Vaccine Injury Compensation Program involving cases in which ACVs have been identified as a potential cause of autoimmune disorders. PT receives income in the form of royalties from the sale of his book, and he receives income from the sale and administration of vaccines in his practice. EL and GM have no potential conflicts of interest to report., (Copyright © 2019 The Authors. Published by Elsevier GmbH.. All rights reserved.)

FDA regulations require safety testing of constituent ingredients in drugs (21 CFR 610.15). With the exception of extraneous proteins, no component safety testing is required for vaccines or vaccine schedules. The dosing of aluminum in vaccines is based on the production of antibody titers, not safety science. Here we estimate a Pediatric Dose Limit that considers body weight. We identify several serious historical missteps in past analyses of provisional safe levels of aluminum in vaccines, and provide updates relevant to infant aluminum exposure in the pediatric schedule considering pediatric body weight. When aluminum doses are estimated from Federal Regulatory Code given body weight, exposure from the current vaccine schedule are found to exceed our estimate of a weight-corrected Pediatric Dose Limit. Our calculations show that the levels of aluminum suggested by the currently used limits place infants at risk of acute, repeated, and possibly chronic exposures of toxic levels of aluminum in modern vaccine schedules. Individual adult exposures are on par with Provisional Tolerable Weekly Intake "limits", but some individuals may be aluminum intolerant due to genetics or previous exposures. Vaccination in neonates and low birth-weight infants must be re-assessed; other implications for the use of aluminum-containing vaccines, and additional limitations in our understanding of neurotoxicity and safety levels of aluminum in biologics are discussed., (Copyright © 2018 The Authors. Published by Elsevier GmbH.. All rights reserved.)

Mycobacterium tuberculosis (Mtb) is a global health threat, compounded by the emergence of drug-resistant strains. A hallmark of pulmonary tuberculosis (TB) is the formation of hypoxic necrotic granulomas, which upon disintegration, release infectious Mtb. Furthermore, hypoxic necrotic granulomas are associated with increased disease severity and provide a niche for drug-resistant Mtb. However, the host immune responses that promote the development of hypoxic TB granulomas are not well described. Using a necrotic Mtb mouse model, we show that loss of Mtb virulence factors, such as phenolic glycolipids, decreases the production of the proinflammatory cytokine IL-17 (also referred to as IL-17A). IL-17 production negatively regulates the development of hypoxic TB granulomas by limiting the expression of the transcription factor hypoxia-inducible factor 1α (HIF1α). In human TB patients, HIF1α mRNA expression is increased. Through genotyping and association analyses in human samples, we identified a link between the single nucleotide polymorphism rs2275913 in the IL-17 promoter (-197G/G), which is associated with decreased IL-17 production upon stimulation with Mtb cell wall. Together, our data highlight a potentially novel role for IL-17 in limiting the development of hypoxic necrotic granulomas and reducing disease severity in TB.

Misfolded membrane proteins are retained in the endoplasmic reticulum (ER) and are subject to ER-associated degradation, which clears the secretory pathway of potentially toxic species. While the transcriptional response to environmental stressors has been extensively studied, limited data exist describing the cellular response to misfolded membrane proteins. To this end, we expressed and then compared the transcriptional profiles elicited by the synthesis of three ER retained, misfolded ion channels: The α-subunit of the epithelial sodium channel, ENaC, the cystic fibrosis transmembrane conductance regulator, CFTR, and an inwardly rectifying potassium channel, Kir2.1, which vary in their mass, membrane topologies, and quaternary structures. To examine transcriptional profiles in a null background, the proteins were expressed in yeast, which was previously used to examine the degradation requirements for each substrate. Surprisingly, the proteins failed to induce a canonical unfolded protein response or heat shock response, although messages encoding several cytosolic and ER lumenal protein folding factors rose when αENaC or CFTR was expressed. In contrast, the levels of these genes were unaltered by Kir2.1 expression; instead, the yeast iron regulon was activated. Nevertheless, a significant number of genes that respond to various environmental stressors were upregulated by all three substrates, and compared with previous microarray data we deduced the existence of a group of genes that reflect a novel misfolded membrane protein response. These data indicate that aberrant proteins in the ER elicit profound yet unique cellular responses., (Copyright © 2015 the American Physiological Society.)

While phenylalanine (PHE) is the toxic insult in phenylketonuria (PKU), mechanisms underlying PHE toxicity remain ill-defined. Altered DNA methylation in response to toxic exposures is well-recognized. DNA methylation patterns were assessed in blood and brain from PKU patients to determine if PHE toxicity impacts methylation. Methylome assessment, utilizing methylated DNA immunoprecipitation and paired-end sequencing, was performed in DNA obtained from brain tissue of classical PKU patients, leukocytes from poorly controlled PKU patients, leukocytes from well controlled PKU patients, and appropriate control tissues. In PKU brain tissue, expression analysis determined the impact of methylation on gene function. Differential methylation was observed in brain tissue of PKU patients and expression studies identified downstream impact on gene expression. Altered patterns of methylation were observed in leukocytes of well controlled and poorly controlled patients with more extensive methylation in patients with high PHE exposure. Differential methylation of noncoding RNA genes was extensive in patients with high PHE exposure but minimal in well controlled patients. Methylome repatterning leading to altered gene expression was present in brain tissue of PKU patients, suggesting a role in neuropathology. Aberrant methylation is observed in leukocytes of PKU patients and is influenced by PHE exposure. DNA methylation may provide a biomarker relating to historic PHE exposure., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Background: Circadian gene disruptions are associated with the development of psychiatric disorders, including addiction. However, the mechanisms by which circadian genes regulate reward remain poorly understood., Methods: We used mice with a mutation in Npas2 and adeno-associated virus-short hairpin RNA mediated knockdown of Npas2 and Clock in the nucleus accumbens (NAc). We performed conditioned place preference assays. We utilized cell sorting quantitative real-time polymerase chain reaction, and chromatin immunoprecipitation followed by deep sequencing., Results: Npas2 mutants exhibit decreased sensitivity to cocaine reward, which is recapitulated with a knockdown of neuronal PAS domain protein 2 (NPAS2) specifically in the NAc, demonstrating the importance of NPAS2 in this region. Interestingly, reducing circadian locomotor output cycles kaput (CLOCK) (a homologue of NPAS2) in the NAc had no effect, suggesting an important distinction in NPAS2 and CLOCK function. Furthermore, we found that NPAS2 expression is restricted to Drd1 expressing neurons while CLOCK is ubiquitous. Moreover, NPAS2 and CLOCK have distinct temporal patterns of DNA binding, and we identified novel and unique binding sites for each protein. We identified the Drd3 dopamine receptor as a direct transcriptional target of NPAS2 and found that NPAS2 knockdown in the NAc disrupts its diurnal rhythm in expression. Chronic cocaine treatment likewise disrupts the normal rhythm in Npas2 and Drd3 expression in the NAc, which may underlie behavioral plasticity in response to cocaine., Conclusions: Together, these findings identify an important role for the circadian protein, NPAS2, in the NAc in the regulation of dopamine receptor expression and drug reward., (Copyright © 2015 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

We have recently reported the creation and initial characterization of an etiology-based recombinant mouse model of a severe and inherited form of Major Depressive Disorder (MDD). This was achieved by replacing the corresponding mouse DNA sequence with a 6-base DNA sequence from the human CREB1 promoter that is associated with MDD in individuals from families with recurrent, early-onset MDD (RE-MDD). In the current study, we explored the effect of the pathogenic Creb1 allele on gene expression in the mouse hippocampus, a brain region that is altered in structure and function in MDD. Mouse whole-genome profiling was performed using the Illumina MouseWG-6 v2.0 Expression BeadChip microarray. Univariate analysis identified 269 differentially-expressed genes in the hippocampus of the mutant mouse. Pathway analyses highlighted 11 KEGG pathways: the phosphatidylinositol signaling system, which has been widely implicated in MDD, Bipolar Disorder, and the action of mood stabilizers; gap junction and long-term potentiation, which mediate cognition and memory functions often impaired in MDD; cardiac muscle contraction, insulin signaling pathway, and three neurodegenerative brain disorders (Alzheimer's, Parkinson's, and Huntington's Diseases) that are associated with MDD; ribosome and proteasome pathways affecting protein synthesis/degradation; and the oxidative phosphorylation pathway that is key to energy production. These findings illustrate the merit of this congenic C57BL/6 recombinant mouse as a model of RE-MDD, and demonstrate its potential for highlighting molecular and cellular pathways that contribute to the biology of MDD. The results also inform our understanding of the mechanisms that underlie the comorbidity of MDD with other disorders., (© 2014 Wiley Periodicals, Inc.)

Experimental investigations into the effects of traumatic brain injury (TBI) have demonstrated significant alterations in dopaminergic systems. Dopaminergic fibers originating within the substantia nigra and ventral tegmental area (VTA) are important for reward learning, addiction, movement, and behavior. However, little is known about the effect of TBI on substantia nigra and VTA function. Environmental enrichment (EE) has been shown to improve functional outcome after TBI, and a number of studies suggest that it may exert some benefits via dopaminergic signaling. To better understand the role of dopamine in chronic TBI pathophysiology and the effect of EE, we examined the mRNA expression profile within the substantia nigra and VTA at 4 weeks post-injury. Specifically, three comparisons were made: 1) TBI versus sham, 2) sham+EE versus sham+standard (STD) housing, and 3) TBI+EE versus TBI+STD. There were differential expressions of 25, 4, and 40 genes in these comparisons, respectively. Chronic alterations in genes post-injury within the substantia nigra and VTA included genes important for cellular membrane homeostasis and transcription. EE-induced gene alterations after TBI included genes important for signal transduction, in particular calcium signaling pathways, membrane homeostasis, and metabolism. Elucidation of these alterations in gene expression within the substantia nigra and VTA provides new insights into chronic changes in dopamine signaling post-TBI, and the potential role of EE in TBI rehabilitation.

Background: We previously demonstrated that donor treatment with inhaled hydrogen protects lung grafts from cold ischemia/reperfusion (I/R) injury during lung transplantation. To elucidate the mechanisms underlying hydrogen's protective effects, we conducted a gene array analysis to identify changes in gene expression associated with hydrogen treatment., Methods: Donor rats were exposed to mechanical ventilation with 98% oxygen and 2% nitrogen or 2% hydrogen for 3 h before harvest; lung grafts were stored for 4h in cold Perfadex. Affymetrix gene array analysis of mRNA transcripts was performed on the lung tissue prior to implantation., Results: Pretreatment of donor lungs with hydrogen altered the expression of 229 genes represented on the array (182 upregulated; 47 downregulated). Hydrogen treatment induced several lung surfactant-related genes, ATP synthase genes and stress-response genes. The intracellular surfactant pool, tissue adenosine triphosphate (ATP) levels and heat shock protein 70 (HSP70) expression increased in the hydrogen-treated grafts. Hydrogen treatment also induced the transcription factors C/EBPα and C/EBPβ, which are known regulators of surfactant-related genes., Conclusion: Donor ventilation with hydrogen significantly increases expression of surfactant-related molecules, ATP synthases and stress-response molecules in lung grafts. The induction of these molecules may underlie hydrogen's protective effects against I/R injury during transplantation., (Copyright © 2012 Elsevier Inc. All rights reserved.)

Preeclampsia is a common and potentially lethal pregnancy disorder with lifelong increased risk of cardiovascular disease in survivors. Our prior global gene expression microarray analysis led to a novel set of 36 candidates in first trimester placentas of women who subsequently developed preeclampsia. In this report, we present preliminary studies demonstrating biomarkers of genotype and methylation variations in a subset of these candidate genes in maternal leukocyte and fetoplacental DNA of 28 case and 27 control dyads. We tested 84 single nucleotide polymorphisms (SNPs) using MassArray iPLEX and 50 CpG sites using EpiTYPER assays. Promising prediction modeling was identified with 25 SNPs selected using Fisher's exact tests (p ≤ 0.05) and 20 CpG sites selected on fold change. Genotype Distribution Analysis identified SNP variations that differed between nine paired cases versus paired controls. The findings validate the examined candidate genes and support feasibility of methods for further biomarker development. The integrative approach that was implemented begins to translate the 36 candidates toward clinical utility as a screening modality for preeclampsia., (© 2012 Wiley Periodicals, Inc.)

Dendritic cells (DCs) are the most potent APCs. Whereas immature DCs down-regulate T-cell responses to induce/maintain immunologic tolerance, mature DCs promote immunity. To amplify their functions, DCs communicate with neighboring DCs through soluble mediators, cell-to-cell contact, and vesicle exchange. Transfer of nanovesicles (< 100 nm) derived from the endocytic pathway (termed exosomes) represents a novel mechanism of DC-to-DC communication. The facts that exosomes contain exosome-shuttle miRNAs and DC functions can be regulated by exogenous miRNAs, suggest that DC-to-DC interactions could be mediated through exosome-shuttle miRNAs, a hypothesis that remains to be tested. Importantly, the mechanism of transfer of exosome-shuttle miRNAs from the exosome lumen to the cytosol of target cells is unknown. Here, we demonstrate that DCs release exosomes with different miRNAs depending on the maturation of the DCs. By visualizing spontaneous transfer of exosomes between DCs, we demonstrate that exosomes fused with the target DCs, the latter followed by release of the exosome content into the DC cytosol. Importantly, exosome-shuttle miRNAs are functional, because they repress target mRNAs of acceptor DCs. Our findings unveil a mechanism of transfer of exosome-shuttle miRNAs between DCs and its role as a means of communication and posttranscriptional regulation between DCs.

Objective: Pulmonary complications, including pulmonary fibrosis (PF) and pulmonary arterial hypertension (PAH), are the leading cause of mortality in patients with systemic sclerosis (SSc). The aim of this study was to compare the molecular fingerprint of lung tissue and matching primary fibroblasts from patients with SSc with that of lung tissue and fibroblasts from normal donors, patients with idiopathic pulmonary fibrosis (IPF), and patients with idiopathic pulmonary arterial hypertension (IPAH)., Methods: Lung tissue samples were obtained from 33 patients with SSc who underwent lung transplantation. Tissues and cells from a subgroup of SSc patients with predominantly PF or PAH were compared to those from normal donors, patients with IPF, and patients with IPAH. Microarray data were analyzed using efficiency analysis for determination of the optimal data-processing methods. Real-time polymerase chain reaction and immunohistochemistry were used to confirm differential levels of messenger RNA and protein, respectively., Results: Consensus efficiency analysis identified 242 and 335 genes that were differentially expressed in lungs and primary fibroblasts, respectively. SSc-PF and IPF lungs shared enriched functional groups in genes implicated in fibrosis, insulin-like growth factor signaling, and caveolin-mediated endocytosis. Gene functional groups shared by SSc-PAH and IPAH lungs included those involved in antigen presentation, chemokine activity, and interleukin-17 signaling., Conclusion: Using microarray analysis on carefully phenotyped SSc and comparator lung tissues, we demonstrated distinct molecular profiles in tissues and fibroblasts from patients with SSc-associated lung disease compared to idiopathic forms of lung disease. Unique molecular signatures were generated that are disease specific (SSc) and phenotype specific (PF versus PAH). These signatures provide new insights into the pathogenesis and potential therapeutic targets of SSc-related lung disease., (Copyright © 2011 by the American College of Rheumatology.)

EBV-immortalized B-lymphoblastoid cell lines are used as models for cellular transformation and as antigen-presenting cells in immunological assays. LCLs vary in surface markers and other phenotypic properties, but it is not known how this heterogeneity relates to the EBV life cycle. To explore correlations, we examined 62 LCLs for cellular and viral phenotypes. LCLs generated from pediatric and adult donors could similarly be categorized as either low in EBV copy number or fluctuating within a high range. High-copy status accompanied higher lytic viral gene expression and lower latent gene expression. Inhibiting lytic EBV replication did not affect cellular phenotype or lytic switch protein expression, indicating that an LCL's lytic permissivity was a stable property. Among the cellular genes overexpressed in permissive LCLs were unfolded protein response genes and plasma cell markers. Among genes overexpressed in non-permissive LCLs were transcription factors involved in maintaining B cell lineage, in particular EBF1. This study suggests previously undetected mechanisms by which cellular pathways influence the lytic reactivation of EBV., (Copyright 2010 Elsevier Inc. All rights reserved.)

The availability of different scoring schemes and filter settings of protein database search algorithms has greatly expanded the number of search methods for identifying candidate peptides from MS/MS spectra. We have previously shown that consensus-based methods that combine three search algorithms yield higher sensitivity and specificity compared to the use of a single search engine (individual method). We hypothesized that union of four search engines (Sequest, Mascot, X!Tandem and Phenyx) can further enhance sensitivity and specificity. ROC plots were generated to measure the sensitivity and specificity of 5460 consensus methods derived from the same dataset. We found that Mascot outperformed individual methods for sensitivity and specificity, while Phenyx performed the worst. The union consensus methods generally produced much higher sensitivity, while the intersection consensus methods gave much higher specificity. The union methods from four search algorithms modestly improved sensitivity, but not specificity, compared to union methods that used three search engines. This suggests that a strategy based on specific combination of search algorithms, instead of merely 'as many search engines as possible', may be key strategy for success with peptide identification. Lastly, we provide strategies for optimizing sensitivity or specificity of peptide identification in MS/MS spectra for different user-specific conditions.

Objectives: The assessment of statistical significance of survivorship differences of model-predicted groups is an important step in survivorship studies. Some models determined to be significant using current methodologies are assumed to have predictive capabilities. These methods compare parameters from predicted classes, not random samples from homogenous populations, and they may be insensitive to prediction errors. Type I-like errors can result wherein models with high prediction error rates are accepted. We have developed and evaluated an alternate statistic for determining the significance of survivorship between or among model-derived survivorship classes., Methods: We propose and evaluate a new statistical test, the F* test, which incorporates parameters that reflect prediction errors that are unobserved by the current methods of evaluation., Results: We found that the Log Rank test identified fewer failed models than the F* test. When both the tests were significant, we found a more accurate model. Using two prediction models applied to eight datasets, we found that the F* test gave a correct inference five out of eight times, whereas the Log Rank test only identified one model out of the eight correctly., Conclusion: Our empirical evaluation reveals that the hypothesis testing inferences derived using the F* test exhibit better parity with the accuracy of prediction models than the other options. The generalizable prediction accuracy of prediction models should be of paramount importance for model-based survivorship prediction studies.

Correct identification of peptides and proteins in complex biological samples from proteomic mass-spectra is a challenging problem in bioinformatics. The sensitivity and specificity of identification algorithms depend on underlying scoring methods, some being more sensitive, and others more specific. For high-throughput, automated peptide identification, control over the algorithms' performance in terms of trade-off between sensitivity and specificity is desirable. Combinations of algorithms, called 'consensus methods', have been shown to provide more accurate results than individual algorithms. However, due to the proliferation of algorithms and their varied internal settings, a systematic understanding of relative performance of individual and consensus methods are lacking. We performed an in-depth analysis of various approaches to consensus scoring using known protein mixtures, and evaluated the performance of 2310 settings generated from consensus of three different search algorithms: Mascot, Sequest, and X!Tandem. Our findings indicate that the union of Mascot, Sequest, and X!Tandem performed well (considering overall accuracy), and methods using 80-99.9% protein probability and/or minimum 2 peptides and/or 0-50% minimum peptide probability for protein identification performed better (on average) among all consensus methods tested in terms of overall accuracy. The results also suggest method selection strategies to provide direct control over sensitivity and specificity.

Background: Preeclampsia is a pregnancy-specific disorder that remains a leading cause of maternal, fetal and neonatal morbidity and mortality, and is associated with risk for future cardiovascular disease. There are no reliable predictors, specific preventative measures or treatments other than delivery. A widely held view is that the antecedents of preeclampsia lie with impaired placentation in early pregnancy. Accordingly, we hypothesized dysregulation of global gene expression in first trimester placentas of women who later manifested preeclampsia., Methods: Surplus chorionic villus sampling (CVS) tissues were collected at 10-12 weeks gestation in 160 patients with singleton fetuses. Four patients developed preeclampsia, and their banked CVS specimens were matched to 8 control samples from patients with unaffected pregnancies. Affymetrix HG-U133 Plus 2.0 GeneChips were utilized for microarray analysis. Naïve Bayes prediction modeling and pathway analysis were conducted. qRT-PCR examined three of the dysregulated genes., Results: Thirty-six differentially expressed genes were identified in the preeclampsia placentas. qRT-PCR verified the microarray analysis. Thirty-one genes were down-regulated. Many were related to inflammation/immunoregulation and cell motility. Decidual gene dysregulation was prominent. No evidence was found for alterations in hypoxia and oxidative stress regulated genes., Conclusions: To our knowledge, this is the first study to show dysregulation of gene expression in the early placentas of women approximately 6 months before developing preeclampsia, thereby reinforcing a placental origin of the disorder. We hypothesize that placentation in preeclampsia is compromised in the first trimester by maternal and fetal immune dysregulation, abnormal decidualization, or both, thereby impairing trophoblast invasion. Several of the genes provide potential targets for the development of clinical biomarkers in maternal blood during the first trimester. Supplementary materials are available for this article via the publisher's online edition.

Typically, in high-throughput data, the number of features is often substantially greater than the number of samples. One approach to this statistical challenge is to perform feature selection and usually, only predictive accuracy is used to perform feature selection. We present a new feature selection method called Wrapper Consistency Analysis that strives to optimize both the predictive accuracy as well as a measure called overlap (or consistency). We believe this analysis provides additional information about the goodness of a selected set of features.

In this study, we introduce and use Efficiency Analysis to compare differences in the apparent internal and external consistency of competing normalization methods and tests for identifying differentially expressed genes. Using publicly available data, two lung adenocarcinoma datasets were analyzed using caGEDA (http://bioinformatics2.pitt.edu/GE2/GEDA.html) to measure the degree of differential expression of genes existing between two populations. The datasets were randomly split into at least two subsets, each analyzed for differentially expressed genes between the two sample groups, and the gene lists compared for overlapping genes. Efficiency Analysis is an intuitive method that compares the differences in the percentage of overlap of genes from two or more data subsets, found by the same test over a range of testing methods. Tests that yield consistent gene lists across independently analyzed splits are preferred to those that yield less consistent inferences. For example, a method that exhibits 50% overlap in the 100 top genes from two studies should be preferred to a method that exhibits 5% overlap in the top 100 genes. The same procedure was performed using all available normalization and transformation methods that are available through caGEDA. The 'best' test was then further evaluated using internal cross-validation to estimate generalizable sample classification errors using a Naïve Bayes classification algorithm. A novel test, termed D1 (a derivative of the J5 test) was found to be the most consistent, and to exhibit the lowest overall classification error, and highest sensitivity and specificity. The D1 test relaxes the assumption that few genes are differentially expressed. Efficiency Analysis can be misleading if the tests exhibit a bias in any particular dimension (e.g. expression intensity); we therefore explored intensity-scaled and segmented J5 tests using data in which all genes are scaled to share the same intensity distribution range. Efficiency Analysis correctly predicted the 'best' test and normalization method using the Beer dataset and also performed well with the Bhattacharjee dataset based on both efficiency and classification accuracy criteria.

Oral microbes that colonize in the mouths of humans contribute to disease susceptibility, but it is unclear if host genetic factors mediate colonization. We therefore tested the hypothesis that the levels at which oral microbes colonize in the mouth are heritable. Dental plaque biofilms were sampled from intact tooth surfaces of 118 caries-free twins. An additional 86 caries-active twins were sampled for plaque from carious lesions and intact tooth surfaces. Using a reverse capture checkerboard assay the relative abundance of 82 bacterial species was determined. An integrative computational predictive model determined microbial abundance patterns of microbial species in caries-free twins as compared to caries-active twins. Heritability estimates were calculated for the relative microbial abundance levels of the microbial species in both groups. The levels of 10 species were significantly different in healthy individuals than in caries-active individuals, including, A. defectiva, S. parasanguinis, S. mitis/oralis, S. sanguinis, S. cristatus, S. salivarius, Streptococcus sp. clone CH016, G. morbillorum and G. haemolysans. Moderate to high heritability estimates were found for these species (h(2) = 56%-80%, p < .0001). Similarity of the overall oral microbial flora was also evident in caries-free twins from multivariate distance matrix regression analysis. It appears that genetic and/or familial factors significantly contribute to the colonization of oral beneficial species in twins.

Motivation: The 'reproducibility' of mass spectrometry proteomic profiling has become an intensely controversial topic. The mere mention of concern over the 'reproducibility' of data generated from any particular platform can lead to the anxiety over the generalizability of its results and its role in the future of discovery proteomics. In this study, we examine the reproducibility of proteomic profiles generated by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) across multiple data-generation sessions. We analyze the problem in terms of the reproducibility of signals, reproducibility of discriminative features and reproducibility of multivariate classification models on profiles for serum samples from early lung cancer and healthy control subjects., Results: Proteomic profiles in individual data-generation sessions experience within-session variability. We show that combining data from multiple sessions introduces additional (inter-session) noise. While additional noise can affect the discriminative analysis, we show that its average effect on profiles in our study is relatively small. Moreover, for the purposes of prediction on future (previously unseen) data, classifiers trained on multi-session data are able to adapt to inter-session noise and improve their classification accuracy.

Background: Decision analysis techniques can be applied in complex situations involving uncertainty and the consideration of multiple objectives. Classical decision modeling techniques require elicitation of too many parameter estimates and their conditional (joint) probabilities, and have not therefore been applied to the problem of identifying high-performance, cost-effective combinations of clinical options for diagnosis or treatments where many of the objectives are unknown or even unspecified., Methods: We designed a Java-based software resource, the Clinical Decision Modeling System (CDMS), to implement Naïve Decision Modeling, and provide a use case based on published performance evaluation measures of various strategies for breast and lung cancer detection. Because cost estimates for many of the newer methods are not yet available, we assume equal cost. Our use case reveals numerous potentially high-performance combinations of clinical options for the detection of breast and lung cancer., Results: Naïve Decision Modeling is a highly practical applied strategy which guides investigators through the process of establishing evidence-based integrative translational clinical research priorities. CDMS is not designed for clinical decision support. Inputs include performance evaluation measures and costs of various clinical options. The software finds trees with expected emergent performance characteristics and average cost per patient that meet stated filtering criteria. Key to the utility of the software is sophisticated graphical elements, including a tree browser, a receiver-operator characteristic surface plot, and a histogram of expected average cost per patient. The analysis pinpoints the potentially most relevant pairs of clinical options ('critical pairs') for which empirical estimates of conditional dependence may be critical. The assumption of independence can be tested with retrospective studies prior to the initiation of clinical trials designed to estimate clinical impact. High-performance combinations of clinical options may exist for breast and lung cancer detection., Conclusion: The software could be found useful in simplifying the objective-driven planning of complex integrative clinical studies without requiring a multi-attribute utility function, and it could lead to efficient integrative translational clinical study designs that move beyond simple pair wise competitive studies. Collaborators, who traditionally might compete to prioritize their own individual clinical options, can use the software as a common framework and guide to work together to produce increased understanding on the benefits of using alternative clinical combinations to affect strategic and cost-effective clinical workflows.

Astrocytoma is graded as pilocytic (WHO grade I), diffuse (WHO grade II), anaplastic (WHO grade III), and glioblastoma multiforme (WHO grade IV). The progression from low- to high-grade astrocytoma is associated with distinct molecular changes that vary with patient age, yet the prognosis of high-grade tumors in children and adults is equally dismal. Whether specific gene expression changes are consistently associated with all high-grade astrocytomas, independent of patient age, is not known. To address this question, we reanalyzed the microarray datasets comprising astrocytomas from children and adults, respectively. We identified nine genes consistently dysregulated in high-grade tumors, using four novel tests for identifying differentially expressed genes. Four genes encoding ribosomal proteins (RPS2, RPS8, RPS18, RPL37A) were upregulated, and five genes (APOD, SORL1, SPOCK2, PRSS11, ID3) were downregulated in high-grade by all tests. Expression results were validated using a third astrocytoma dataset. APOD, the most differentially expressed gene, has been shown to inhibit tumor cell and vascular smooth muscle cell proliferation. This suggests that dysregulation of APOD may be critical for malignant astrocytoma formation, and thus a possible novel universal target for therapeutic intervention. Further investigation is needed to evaluate the role of APOD, as well as the other genes identified, in malignant astrocytoma development.

Circumstantial evidence demonstrating a role for circadian rhythms in cancer has been presented but there is little direct molecular evidence to support this idea in human cancer. Herein, we report a significant similarity between fly genes with strong circadian rhythms and human genes under expressed in pancreatic cancer. The list of genes includes both circadian regulator genes, such as period 1 and DEC1, and downstream effectors, such as ubiquitin specific protease 30. This observation may indicate that the pancreas peripheral clock is disrupted in pancreatic cancer and are consistent with the recent proposals that circadian genes act as tumor suppressors.

The differentiation of BK virus-associated renal allograft nephropathy (BKVAN) from acute allograft rejection (AR) in renal transplant recipients is an important clinical problem because the treatment can be diametrically opposite for the two conditions. The aim of this discovery-phase biomarker development study was to examine feasibility of developing a noninvasive method to differentiate BKVAN from AR. Surface-enhanced laser desorption/ionization (SELDI) time-of-flight mass spectrometry analysis was used to compare proteomic profiles of urine samples of 21 patients with BKVAN, 28 patients with AR (Banff Ia to IIb), and 29 patients with stable graft function. SELDI analysis showed proteomic profiles that were significantly different in the BKVAN group versus the AR and stable transplant groups. Peaks that corresponded to m/z values of 5.872, 11.311, 11.929, 12.727, and 13.349 kD were significantly higher in patients with BKVAN. Bioinformatics analyses allowed distinction of profiles of patients with BKVAN from patients with AR and stable patients. SELDI profiles also showed a high degree of reproducibility. Proteomic analysis of urine may offer a noninvasive way to differentiate BKVAN from AR in clinical practice. The identification of individual proteomic peaks can improve further the clinical utility of this screening method.

Keloid scars after skin trauma are a significant clinical problem, especially in black populations, in which the incidence of keloids has been estimated at 4-16%. Keloids are abnormal dermal proliferative scars secondary to dysregulated wound healing. Despite several biochemical studies on the role of extracellular matrix proteins and growth factors during keloid formation, we still do not know what molecules and signals induce this change. Fibroblasts are thought to be the major inductive cell for keloid scar formation. The aim of this study was to identify gene expression patterns that characterize keloid fibroblasts; identifying such genetic disequilibrium may shed light on the molecular signaling events responsible for keloid formation. In this study, we performed gene expression analysis of fibroblasts isolated from keloid lesions from three individuals in comparison with the fibroblasts isolated from normal skin using the Affymetrix U133a chip (22,284 genes and expression sequence tags). We found through J5 test score expression analysis that among 22,284 genes, there were 43 genes that were overexpressed and five genes were underexpressed in keloid fibroblasts when compared with dermal fibroblasts from persons without keloids. The overexpression of three genes not previously reported as being up-regulated in keloids (annexin A2, Transgelin, and RPS18) was confirmed by real-time polymerase chain reaction. Certain overexpressed genes were similar to previous biochemical observations on the protein levels of these overexpressed genes during keloid formation. We also report for the first time that a few tumor-related genes are overexpressed in keloid fibroblasts.

Recent studies have evaluated proper acquisition and storage procedures for the use of serum or plasma for mass spectrometry (MS)-based proteomics. The present study examines the proteome stability of human cerebrospinal fluid (CSF) over time at 23°C (room temperature) and 4°C using surface-enhanced laser desorption/ionization time-of-flight MS. Data analysis revealed that statistically significant differences in protein profiles are apparent within 4 h at 23°C and between 6 and 8 h at 4°C. Inclusion of protease and phosphatase inhibitor cocktails into the CSF samples failed to significantly reduce proteome alterations over time. We conclude that MS-based proteomic analysis of CSF requires careful assessment of sample collection procedures for rapid and optimal sample acquisition and storage.