Determination of the differentially expressed genes in microarray experiments using local FDR

Background  

Thousands of genes in a genomewide data set are tested against some null hypothesis, for detecting differentially expressed genes in microarray experiments. The expected proportion of false positive genes in a set of genes, called the False Discovery Rate (FDR), has been proposed to measure the statistical significance of this set. Various procedures exist for controlling the FDR. However the threshold (generally 5%) is arbitrary and a specific measure associated with each gene would be worthwhile.     

Effects of dependence in high-dimensional multiple testing problems

Background  

We consider effects of dependence among variables of high-dimensional data in multiple hypothesis testing problems, in particular the False Discovery Rate (FDR) control procedures. Recent simulation studies consider only simple correlation structures among variables, which is hardly inspired by real data features. Our aim is to systematically study effects of several network features like sparsity and correlation strength by imposing dependence structures among variables using random correlation matrices.     

Kerfdr: a semi-parametric kernel-based approach to local false discovery rate estimation

Background  

The use of current high-throughput genetic, genomic and post-genomic data leads to the simultaneous evaluation of a large number of statistical hypothesis and, at the same time, to the multiple-testing problem. As an alternative to the too conservative Family-Wise Error-Rate (FWER), the False Discovery Rate (FDR) has appeared for the last ten years as more appropriate to handle this problem. However one drawback of FDR is related to a given rejection region for the considered statistics, attributing the same value to those that are close to the boundary and those that are not. As a result, the local FDR has been recently proposed to quantify the specific probability for a given null hypothesis to be true.     

Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data

Background  

The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustment methods for multiple comparisons such as family-wise error rate (FWER) have been found to be too conservative in analyzing large-screening microarray data, and the False Discovery Rate (FDR), the expected proportion of false positives among all positives, has been recently suggested as an alternative for controlling false positives. Several statistical approaches have been used to estimate and control FDR, but these may not provide reliable FDR estimation when applied to microarray data sets with a small number of replicates.     

An Integrated Mass-Spectrometry Pipeline Identifies Novel Protein Coding-Regions in the Human Genome

Background

Most protein mass spectrometry (MS) experiments rely on searches against a database of known or predicted proteins, limiting their ability as a gene discovery tool.

Results

Using a search against an in silico translation of the entire human genome, combined with a series of annotation filters, we identified 346 putative novel peptides [False Discovery Rate (FDR)<5%] in a MS dataset derived from two human breast epithelial cell lines. A subset of these were then successfully validated by a different MS technique. Two of these correspond to novel isoforms of Heterogeneous Ribonuclear Proteins, while the rest correspond to novel loci.

Conclusions

MS technology can be used for ab initio gene discovery in human data, which, since it is based on different underlying assumptions, identifies protein-coding genes not found by other techniques. As MS technology continues to evolve, such approaches will become increasingly powerful.     

Genes affecting progression of bacteriophage P22 infection in Salmonella identified by transposon and single gene deletion screens

Bacteriophages rely on their hosts for replication, and many host genes critically determine either viral progeny production or host success via phage resistance. A random insertion transposon library of 240,000 mutants in Salmonella enterica serovar Typhimurium was used to monitor effects of individual bacterial gene disruptions on bacteriophage P22 lytic infection. These experiments revealed candidate host genes that alter the timing of phage P22 propagation. Using a False Discovery Rate of < 0.1, mutations in 235 host genes either blocked or delayed progression of P22 lytic infection, including many genes for which this role was previously unknown. Mutations in 77 genes reduced the survival time of host DNA after infection, including mutations in genes for enterobacterial common antigen (ECA) synthesis and osmoregulated periplasmic glucan (OPG). We also screened over 2000 Salmonella single gene deletion mutants to identify genes that impacted either plaque formation or culture growth rates. The gene encoding the periplasmic membrane protein YajC was newly found to be essential for P22 infection. Targeted mutagenesis of yajC shows that an essentially full‐length protein is required for function, and potassium efflux measurements demonstrated that YajC is critical for phage DNA ejection across the cytoplasmic membrane.     

Over expression of the selectable marker blasticidin S deaminase gene is toxic to human keratinocytes and murine BALB/MK cells

Background  

The blasticidin S resistance gene (bsr) is a selectable marker used for gene transfer experiments. The bsr gene encodes for blasticidin S (BS) deaminase, which has a specific activity upon BS. Therefore, its expression is supposed to be harmless in cells. The work reported on herein consisted of experiments to verify a possible toxicity of bsr on mammalian cells, which include several cell lines and primary cultures.     

Meta-Analysis Identifies NF-κB as a Therapeutic Target in Renal Cancer

Objective

To determine the expression patterns of NF-κB regulators and target genes in clear cell renal cell carcinoma (ccRCC), their correlation with von Hippel Lindau (VHL) mutational status, and their association with survival outcomes.

Methods

Meta-analyses were carried out on published ccRCC gene expression datasets by RankProd, a non-parametric statistical method. DEGs with a False Discovery Rate of < 0.05 by this method were considered significant, and intersected with a curated list of NF-κB regulators and targets to determine the nature and extent of NF-κB deregulation in ccRCC.

Results

A highly-disproportionate fraction (~40%; p < 0.001) of NF-κB regulators and target genes were found to be up-regulated in ccRCC, indicative of elevated NF-κB activity in this cancer. A subset of these genes, comprising a key NF-κB regulator (IKBKB) and established mediators of the NF-κB cell-survival and pro-inflammatory responses (MMP9, PSMB9, and SOD2), correlated with higher relative risk, poorer prognosis, and reduced overall patient survival. Surprisingly, levels of several interferon regulatory factors (IRFs) and interferon target genes were also elevated in ccRCC, indicating that an ‘interferon signature’ may represent a novel feature of this disease. Loss of VHL gene expression correlated strongly with the appearance of NF-κB- and interferon gene signatures in both familial and sporadic cases of ccRCC. As NF-κB controls expression of key interferon signaling nodes, our results suggest a causal link between VHL loss, elevated NF-κB activity, and the appearance of an interferon signature during ccRCC tumorigenesis.

Conclusions

These findings identify NF-κB and interferon signatures as clinical features of ccRCC, provide strong rationale for the incorporation of NF-κB inhibitors and/or and the exploitation of interferon signaling in the treatment of ccRCC, and supply new NF-κB targets for potential therapeutic intervention in this currently-incurable malignancy.     

A meta‐analysis of the association between Helicobacter pylori (H. pylori) infection and hyperemesis gravidarum

Background

Hyperemesis gravidarum remains a common, distressing, and significant yet poorly understood disorder during pregnancy. The association between maternal Helicobacter pylori (H. pylori) infection and hyperemesis gravidarum has been increasingly recognized and investigated. This study thus aimed to provide an updated review and meta‐analysis of the topic.

Methods

Using the search terms (H. pyloriOR Helicobacter ORHelicobacter pyloriOR infection) AND (pregnancy OR emesis OR hyperemesis gravidarum OR nausea OR vomiting), a preliminary search on the PubMed, Ovid, Web of Science, Google Scholar, and WanFang database yielded 372 papers published in English between January 1st, 1960 and June 1st, 2017.

Results

A total of 38 cross‐sectional and case‐control studies, with a total of 10 289 patients were eligible for review. Meta‐analysis revealed a significant association between H. pylori infection and hyperemesis gravidarum during pregnancy, with a pooled odds ratio of 1.348 (95% CI: 1.156‐1.539, P < .001). Subgroup analysis found that serologic and stool antigen tests were comparable methods of detecting H. pylori as they yielded similar odds ratios.

Limitations

Although the studies did not have high heterogeneity (I² = 28%), publication bias was observed, and interstudy discrepancies in the diagnostic criteria adopted for hyperemesis gravidarum limit the reliability of findings. Also, 15 of the included studies were from the same country (Turkey), which could limit the generalizability of current findings. The prevalence of H. pylori infection varies throughout the world, and there may also be pathogenic differences as most strains of H. pylori in East Asia carry the cytotoxin‐associated gene A gene.

Conclusion

H. pylori infection was associated with an increased likelihood of hyperemesis gravidarum during pregnancy. Given the high prevalence of H. pylori infections worldwide, detecting H. pylori infection and the eradication of maternal H. pylori infection could be part of maternal hyperemesis gravidarum management. Further confirmation with robust longitudinal studies and mechanistic investigations are needed.     

Global methylation patterns in idiopathic pulmonary fibrosis

Background

Idiopathic Pulmonary Fibrosis (IPF) is characterized by profound changes in the lung phenotype including excessive extracellular matrix deposition, myofibroblast foci, alveolar epithelial cell hyperplasia and extensive remodeling. The role of epigenetic changes in determining the lung phenotype in IPF is unknown. In this study we determine whether IPF lungs exhibit an altered global methylation profile.

Methodology/Principal Findings

Immunoprecipitated methylated DNA from 12 IPF lungs, 10 lung adenocarcinomas and 10 normal histology lungs was hybridized to Agilent human CpG Islands Microarrays and data analysis was performed using BRB-Array Tools and DAVID Bioinformatics Resources software packages. Array results were validated using the EpiTYPER MassARRAY platform for 3 CpG islands. 625 CpG islands were differentially methylated between IPF and control lungs with an estimated False Discovery Rate less than 5%. The genes associated with the differentially methylated CpG islands are involved in regulation of apoptosis, morphogenesis and cellular biosynthetic processes. The expression of three genes (STK17B, STK3 and HIST1H2AH) with hypomethylated promoters was increased in IPF lungs. Comparison of IPF methylation patterns to lung cancer or control samples, revealed that IPF lungs display an intermediate methylation profile, partly similar to lung cancer and partly similar to control with 402 differentially methylated CpG islands overlapping between IPF and cancer. Despite their similarity to cancer, IPF lungs did not exhibit hypomethylation of long interspersed nuclear element 1 (LINE-1) retrotransposon while lung cancer samples did, suggesting that the global hypomethylation observed in cancer was not typical of IPF.

Conclusions/Significance

Our results provide evidence that epigenetic changes in IPF are widespread and potentially important. The partial similarity to cancer may signify similar pathogenetic mechanisms while the differences constitute IPF or cancer specific changes. Elucidating the role of these specific changes will potentially allow better understanding of the pathogenesis of IPF.     

In situ analysis of cross-hybridisation on microarrays and the inference of expression correlation

Background

When conducting multiple hypothesis tests, it is important to control the number of false positives, or the False Discovery Rate (FDR). However, there is a tradeoff between controlling FDR and maximizing power. Several methods have been proposed, such as the q-value method, to estimate the proportion of true null hypothesis among the tested hypotheses, and use this estimation in the control of FDR. These methods usually depend on the assumption that the test statistics are independent (or only weakly correlated). However, many types of data, for example microarray data, often contain large scale correlation structures. Our objective was to develop methods to control the FDR while maintaining a greater level of power in highly correlated datasets by improving the estimation of the proportion of null hypotheses.

Results

We showed that when strong correlation exists among the data, which is common in microarray datasets, the estimation of the proportion of null hypotheses could be highly variable resulting in a high level of variation in the FDR. Therefore, we developed a re-sampling strategy to reduce the variation by breaking the correlations between gene expression values, then using a conservative strategy of selecting the upper quartile of the re-sampling estimations to obtain a strong control of FDR.

Conclusion

With simulation studies and perturbations on actual microarray datasets, our method, compared to competing methods such as q-value, generated slightly biased estimates on the proportion of null hypotheses but with lower mean square errors. When selecting genes with controlling the same FDR level, our methods have on average a significantly lower false discovery rate in exchange for a minor reduction in the power.     

Alterations in Cerebrospinal Fluid Proteins in a Presymptomatic Primary Glioma Model

Background

Understanding the early relationship between brain tumor cells and their environment could lead to more sensitive biomarkers and new therapeutic strategies. We have been using a rodent model of neurocarcinogenesis in which all animals develop brain tumors by six months of age to establish two early landmarks in glioma development: the appearance of a nestin⁺ cell at thirty days of age and the appearance of cellular hyperplasia between 60 and 120 days of age. We now report an assessment of the CSF proteome to determine the changes in protein composition that occur during this period.

Materials and Methods

Nestin⁺ cell clusters and microtumors were assessed in 63 ethylnitrosourea-exposed rats on 30, 60, and 90 days of age. CSF was obtained from the cisterna magna from 101 exposed and control rats at 30, 60, and 90 days and then analyzed using mass spectrometry. Differentially expressed peaks were isolated and identified.

Results

Nestin⁺ cells were noted in all ethylnitrosourea-exposed rats assessed pathologically. Small microtumors were noted in 0%, 18%, and 67% of 30-, 60-, and 90-day old rats, respectively (p<0.05, Chi square). False Discovery Rate analysis of peak intensities showed that the number of true discoveries with p<0.05 increased markedly with increasing age. Isolation and identification of highly differentially detected proteins at 90 days of age revealed increases in albumin and a fragment of α1 macroglobulin and alterations in glutathionylated transthyretin.

Conclusions

The presence of increased albumin, fragments of cerebrospinal fluid proteins, and glutathione breakdown in temporal association with the development of cellular hyperplasia, suggests that, similar to many other systemic cancers, inflammation and oxidative stress is playing an important early role in the host’s response to brain tumor development and may be involved in affecting the early growth of brain tumor.     

Promoter polymorphisms in the chitinase 3-like 1 gene influence the serum concentration of YKL-40 in Danish patients with rheumatoid arthritis and in healthy subjects

Introduction  

The present study investigates the association between single nucleotide polymorphisms (SNPs) in the chitinase 3-like 1 (CHI3L1) gene and serum concentrations of YKL-40 in Danish patients with rheumatoid arthritis (RA) and healthy controls as well as the association with RA in the Danish population. The CHI3L1 gene is located on chromosome 1q32.1 and encodes the YKL-40 glycoprotein. YKL-40 concentrations are elevated in the serum of patients with RA compared to healthy subjects, and YKL-40 has been suggested to be an auto-antigen and may play a role in development of RA and in inflammation.     

Large-scale RNAi screens identify novel genes that interact with the <Emphasis Type="Italic">C. elegans</Emphasis> retinoblastoma pathway as well as splicing-related components with synMuv B activity

Background  

The retinoblastoma tumor suppressor (Rb) acts in a conserved pathway that is deregulated in most human cancers. Inactivation of the single Rb-related gene in Caenorhabditis elegans, lin-35, has only limited effects on viability and fertility, yet causes changes in cell-fate and cell-cycle regulation when combined with inactivation of specific other genes. For instance, lin-35 Rb is a synthetic multivulva (synMuv) class B gene, which causes a multivulva phenotype when inactivated simultaneously with a class A or C synMuv gene.