Bon-EV: an improved multiple testing procedure for controlling false discovery rates

BACKGROUND

Stability of multiple testing procedures, defined as the standard deviation of total number of discoveries, can be used as an indicator of variability of multiple testing procedures. Improving stability of multiple testing procedures can help to increase the consistency of findings from replicated experiments. Benjamini-Hochberg's and Storey's q-value procedures are two commonly used multiple testing procedures for controlling false discoveries in genomic studies. Storey's q-value procedure has higher power and lower stability than Benjamini-Hochberg's procedure. To improve upon the stability of Storey's q-value procedure and maintain its high power in genomic data analysis, we propose a new multiple testing procedure, named Bon-EV, to control false discovery rate (FDR) based on Bonferroni's approach.

RESULTS

Simulation studies show that our proposed Bon-EV procedure can maintain the high power of the Storey's q-value procedure and also result in better FDR control and higher stability than Storey's q-value procedure for samples of large size(30 in each group) and medium size (15 in each group) for either independent, somewhat correlated, or highly correlated test statistics. When sample size is small (5 in each group), our proposed Bon-EV procedure has performance between the Benjamini-Hochberg procedure and the Storey's q-value procedure. Examples using RNA-Seq data show that the Bon-EV procedure has higher stability than the Storey's q-value procedure while maintaining equivalent power, and higher power than the Benjamini-Hochberg's procedure.

CONCLUSIONS

For medium or large sample sizes, the Bon-EV procedure has improved FDR control and stability compared with the Storey's q-value procedure and improved power compared with the Benjamini-Hochberg procedure. The Bon-EV multiple testing procedure is available as the BonEV package in R for download at https://CRAN.R-project.org/package=BonEV .

Controlling the Rate of GWAS False Discoveries

With the rise of both the number and the complexity of traits of interest, control of the false discovery rate (FDR) in genetic association studies has become an increasingly appealing and accepted target for multiple comparison adjustment. While a number of robust FDR-controlling strategies exist, the nature of this error rate is intimately tied to the precise way in which discoveries are counted, and the performance of FDR-controlling procedures is satisfactory only if there is a one-to-one correspondence between what scientists describe as unique discoveries and the number of rejected hypotheses. The presence of linkage disequilibrium between markers in genome-wide association studies (GWAS) often leads researchers to consider the signal associated to multiple neighboring SNPs as indicating the existence of a single genomic locus with possible influence on the phenotype. This a posteriori aggregation of rejected hypotheses results in inflation of the relevant FDR. We propose a novel approach to FDR control that is based on prescreening to identify the level of resolution of distinct hypotheses. We show how FDR-controlling strategies can be adapted to account for this initial selection both with theoretical results and simulations that mimic the dependence structure to be expected in GWAS. We demonstrate that our approach is versatile and useful when the data are analyzed using both tests based on single markers and multiple regression. We provide an R package that allows practitioners to apply our procedure on standard GWAS format data, and illustrate its performance on lipid traits in the North Finland Birth Cohort 66 cohort study.

Multiple confidence intervals for selected parameters adjusted for the false coverage rate in monotone dose-response microarray experiments

Benjamini and Yekutieli () introduced the concept of the false coverage-statement rate (FCR) to account for selection when the confidence intervals (CIs) are constructed only for the selected parameters. Dose-response analysis in dose-response microarray experiments is conducted only for genes having monotone dose-response relationship, which is a selection problem. In this paper, we consider multiple CIs for the mean gene expression difference between the highest dose and control in monotone dose-response microarray experiments for selected parameters adjusted for the FCR. A simulation study is conducted to study the performance of the method proposed. The method is applied to a real dose-response microarray experiment with 16, 998 genes for illustration.

Weighted false discovery rate controlling procedures for clinical trials

Having identified that the lack of replicability of results in earlier phases of clinical medical research stems largely from unattended selective inference, we offer a new hierarchical weighted false discovery rate controlling testing procedure alongside the single-level weighted procedure. These address the special structure of clinical research, where the comparisons of treatments involve both primary and secondary endpoints, by assigning weights that reflect the relative importance of the endpoints in the error being controlled. In the hierarchical method, the primary endpoints and a properly weighted intersection hypothesis that represents all secondary endpoints are tested. Should the intersection hypothesis be among the rejected, individual secondary endpoints are tested. We identify configurations where each of the two procedures has the advantage. Both offer higher power than competing hierarchical (gatekeeper) familywise error-rate controlling procedures being used for drug approval. By their design, the advantage of the proposed methods is the increased power to discover effects on secondary endpoints, without giving up the rigor of addressing their multiplicity.

An improved cumulative sum-based procedure for prospective disease surveillance for count data in multiple regions

We present an improved procedure for detecting outbreaks in multiple spatial regions using count data. We combine well-known methods for disease surveillance with recent developments from other areas to provide a more powerful procedure that is still relatively simple and fast to implement. Disease counts from neighboring regions are aggregated to compute a Poisson cumulative sum statistic for each region of interest. Instead of controlling the average run length criterion in the monitoring process, we instead utilize the FDR, which is more appropriate in a public health context. Additionally, p-values are used to make decisions instead of traditional critical values. The use of the FDR and p-values in testing allows us to utilize recently developed multiple testing methodologies, greatly increasing the power of this procedure. This is verified using a simulation experiment. The simplicity and rapid detection ability of this procedure make it useful in disease surveillance settings. The procedure is successfully applied in detecting the 2011 Salmonella Newport outbreak in 16 German federal states. Copyright © 2016 John Wiley & Sons, Ltd.

DecoyPyrat: Fast Non-redundant Hybrid Decoy Sequence Generation for Large Scale Proteomics

Accurate statistical evaluation of sequence database peptide identifications from tandem mass spectra is essential in mass spectrometry based proteomics experiments. These statistics are dependent on accurately modelling random identifications. The target-decoy approach has risen to become the de facto approach to calculating FDR in proteomic datasets. The main principle of this approach is to search a set of decoy protein sequences that emulate the size and composition of the target protein sequences searched whilst not matching real proteins in the sample. To do this, it is commonplace to reverse or shuffle the proteins and peptides in the target database. However, these approaches have their drawbacks and limitations. A key confounding issue is the peptide redundancy between target and decoy databases leading to inaccurate FDR estimation. This inaccuracy is further amplified at the protein level and when searching large sequence databases such as those used for proteogenomics. Here, we present a unifying hybrid method to quickly and efficiently generate decoy sequences with minimal overlap between target and decoy peptides. We show that applying a reversed decoy approach can produce up to 5% peptide redundancy and many more additional peptides will have the exact same precursor mass as a target peptide. Our hybrid method addresses both these issues by first switching proteolytic cleavage sites with preceding amino acid, reversing the database and then shuffling any redundant sequences. This flexible hybrid method reduces the peptide overlap between target and decoy peptides to about 1% of peptides, making a more robust decoy model suitable for large search spaces. We also demonstrate the anti-conservative effect of redundant peptides on the calculation of q-values in mouse brain tissue data.

Single-pollen genotyping to estimate mode of unreduced pollen formation in Citrus tamurana cv. Nishiuchi Konatsu

2n pollen formed by FDR in citrus. The Japanese local citrus cultivar, Nishiuchi Konatsu (Citrus tamurana hort. ex Tanaka; NK hereafter), has the ability to produce unreduced 2n pollen grains, allowing generation of polyploid progenies via sexual polyploidization. In this study, we developed a method of single-pollen genotyping for citrus and applied it to the analysis of transmission of heterozygosity in NK 2n pollen grains. Heterozygosity transmission was expressed as the percentage inheritance of a set of heterozygous alleles from the parent to the 2n gamete. The pathway of 2n pollen development was investigated by applying the observed heterozygosity transmission and genetic distance to two different map functions, for first division restitution (FDR) and second division restitution (SDR). The fit of the values observed for both functions was calculated, while virtually moving the centromere position. We screened for six heterozygous SSR (codominant microsatellite marker loci) in NK, all of which were expected to lie within the same linkage group. Pollen germination prior to DNA extraction was essential for this work, and 6-h incubation proved to be optimal for subsequent PCR amplification. Single-pollen genotyping unreduced NK 2n pollen grains revealed that heterozygosity transmission exceeded 50 % in all six alleles, and fitness tests indicated that the FDR map function better fitted the heterozygosity transmission observed rather than the SDR function. Our data thus strongly indicate that 2n pollen in NK is a result of first division restitution.

Sample size calculation while controlling false discovery rate for differential expression analysis with RNA-sequencing experiments

Background

RNA-Sequencing (RNA-seq) experiments have been popularly applied to transcriptome studies in recent years. Such experiments are still relatively costly. As a result, RNA-seq experiments often employ a small number of replicates. Power analysis and sample size calculation are challenging in the context of differential expression analysis with RNA-seq data. One challenge is that there are no closed-form formulae to calculate power for the popularly applied tests for differential expression analysis. In addition, false discovery rate (FDR), instead of family-wise type I error rate, is controlled for the multiple testing error in RNA-seq data analysis. So far, there are very few proposals on sample size calculation for RNA-seq experiments.

Results

In this paper, we propose a procedure for sample size calculation while controlling FDR for RNA-seq experimental design. Our procedure is based on the weighted linear model analysis facilitated by the voom method which has been shown to have competitive performance in terms of power and FDR control for RNA-seq differential expression analysis. We derive a method that approximates the average power across the differentially expressed genes, and then calculate the sample size to achieve a desired average power while controlling FDR. Simulation results demonstrate that the actual power of several popularly applied tests for differential expression is achieved and is close to the desired power for RNA-seq data with sample size calculated based on our method.

Conclusions

Our proposed method provides an efficient algorithm to calculate sample size while controlling FDR for RNA-seq experimental design. We also provide an R package ssizeRNA that implements our proposed method and can be downloaded from the Comprehensive R Archive Network (http://cran.r-project.org).

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-016-0994-9) contains supplementary material, which is available to authorized users.

microRNA-449a functions as a tumor suppressor in neuroblastoma through inducing cell differentiation and cell cycle arrest

microRNA-449a (miR-449a) has been identified to function as a tumor suppressor in several types of cancers. However, the role of miR-449a in neuroblastoma has not been intensively investigated. We recently found that the overexpression of miR-449a significantly induces neuroblastoma cell differentiation, suggesting its potential tumor suppressor function in neuroblastoma. In this study, we further investigated the mechanisms underlying the tumor suppressive function of miR-449a in neuroblastoma. We observed that miR-449a inhibits neuroblastoma cell survival and growth through 2 mechanisms--inducing cell differentiation and cell cycle arrest. Our comprehensive investigations on the dissection of the target genes of miR-449a revealed that 3 novel targets- MFAP4, PKP4 and TSEN15 -play important roles in mediating its differentiation-inducing function. In addition, we further found that its function in inducing cell cycle arrest involves down-regulating its direct targets CDK6 and LEF1. To determine the clinical significance of the miR-449a-mediated tumor suppressive mechanism, we examined the correlation between the expression of these 5 target genes in neuroblastoma tumor specimens and the survival of neuroblastoma patients. Remarkably, we noted that high tumor expression levels of all the 3 miR-449a target genes involved in regulating cell differentiation, but not the target genes involved in regulating cell cycle, are significantly correlated with poor survival of neuroblastoma patients. These results suggest the critical role of the differentiation-inducing function of miR-449a in determining neuroblastoma progression. Overall, our study provides the first comprehensive characterization of the tumor-suppressive function of miR-449a in neuroblastoma, and reveals the potential clinical significance of the miR-449a-mediated tumor suppressive pathway in neuroblastoma prognosis.

Tract Orientation and Angular Dispersion Deviation Indicator (TOADDI): A framework for single-subject analysis in diffusion tensor imaging

The purpose of this work is to develop a framework for single-subject analysis of diffusion tensor imaging (DTI) data. This framework is termed Tract Orientation and Angular Dispersion Deviation Indicator (TOADDI) because it is capable of testing whether an individual tract as represented by the major eigenvector of the diffusion tensor and its corresponding angular dispersion are significantly different from a group of tracts on a voxel-by-voxel basis. This work develops two complementary statistical tests based on the elliptical cone of uncertainty, which is a model of uncertainty or dispersion of the major eigenvector of the diffusion tensor. The orientation deviation test examines whether the major eigenvector from a single subject is within the average elliptical cone of uncertainty formed by a collection of elliptical cones of uncertainty. The shape deviation test is based on the two-tailed Wilcoxon-Mann-Whitney two-sample test between the normalized shape measures (area and circumference) of the elliptical cones of uncertainty of the single subject against a group of controls. The False Discovery Rate (FDR) and False Non-discovery Rate (FNR) were incorporated in the orientation deviation test. The shape deviation test uses FDR only. TOADDI was found to be numerically accurate and statistically effective. Clinical data from two Traumatic Brain Injury (TBI) patients and one non-TBI subject were tested against the data obtained from a group of 45 non-TBI controls to illustrate the application of the proposed framework in single-subject analysis. The frontal portion of the superior longitudinal fasciculus seemed to be implicated in both tests (orientation and shape) as significantly different from that of the control group. The TBI patients and the single non-TBI subject were well separated under the shape deviation test at the chosen FDR level of 0.0005. TOADDI is a simple but novel geometrically based statistical framework for analyzing DTI data. TOADDI may be found useful in single-subject, graph-theoretic and group analyses of DTI data or DTI-based tractography techniques.

A new genome-wide method to track horizontally transferred sequences: application to Drosophila

Because of methodological breakthroughs and the availability of an increasing amount of whole-genome sequence data, horizontal transfers (HTs) in eukaryotes have received much attention recently. Contrary to similar analyses in prokaryotes, most studies in eukaryotes usually investigate particular sequences corresponding to transposable elements (TEs), neglecting the other components of the genome. We present a new methodological framework for the genome-wide detection of all putative horizontally transferred sequences between two species that requires no prior knowledge of the transferred sequences. This method provides a broader picture of HTs in eukaryotes by fully exploiting complete-genome sequence data. In contrast to previous genome-wide approaches, we used a well-defined statistical framework to control for the number of false positives in the results, and we propose two new validation procedures to control for confounding factors. The first validation procedure relies on a comparative analysis with other species of the phylogeny to validate HTs for the nonrepeated sequences detected, whereas the second one built upon the study of the dynamics of the detected TEs. We applied our method to two closely related Drosophila species, Drosophila melanogaster and D. simulans, in which we discovered 10 new HTs in addition to all the HTs previously detected in different studies, which underscores our method’s high sensitivity and specificity. Our results favor the hypothesis of multiple independent HTs of TEs while unraveling a small portion of the network of HTs in the Drosophila phylogeny.

Distinct effects of duration of untreated psychosis on brain cortical activities in different treatment phases of schizophrenia: a multi-channel near-infrared spectroscopy study

BACKGROUND

Duration of untreated psychosis (DUP) has been shown to be associated with both poor short-term and long-term outcomes in schizophrenia. Even so, few studies have used functional neuroimaging to investigate DUP in schizophrenia. In the present study, we used near-infrared spectroscopy (NIRS) to investigate the influence of DUP on brain functions during a verbal fluency test (VFT) in patients with schizophrenia.

METHODS

A total of 62 patients with schizophrenia were included. They were categorized into either short treatment (≤6months, n=33) or long treatment (>6months, n=29) groups based on their duration of treatment. Hemodynamic changes over the frontotemporal regions during a VFT were measured using multi-channel NIRS. We examined the associations between DUP and hemodynamic changes in each group to explore if there were different effects of DUP on brain cortical activity at different treatment durations.

RESULTS

In the long treatment group, we found significant associations between a longer DUP and decreased cortical activity approximately at the left inferior frontal gyrus, left middle frontal gyrus, left postcentral gyrus, right precentral gyrus, bilateral superior temporal gyrus, and bilateral middle temporal gyrus, whereas no associations between DUP and brain cortical activity were observed in the short treatment group.

CONCLUSIONS

Our results indicated that longer DUP may be associated with decreased level of cortical activities over the frontotemporal regions in the long-term. Early detection and intervention of psychosis that shortens DUP might help to improve the long-term outcomes in patients with schizophrenia.

Transcriptome and metabolome analysis of citrus fruit to elucidate puffing disorder

A systems-level analysis reveals details of molecular mechanisms underlying puffing disorder in Citrus fruit. Flavedo, albedo and juice sac tissues of normal fruits and fruits displaying symptoms of puffing disorder were studied using metabolomics at three developmental stages. Microarrays were used to compare normal and puffed fruits for each of the three tissues. A protein-protein interaction network inferred from previous work on Arabidopsis identified hub proteins whose transcripts show significant changes in expression. Glycolysis, the backbone of primary metabolism, appeared to be severely affected by the disorder, based on both transcriptomic and metabolomic results. Significantly less citric acid was observed consistently in puffed fruits. Gene set enrichment analysis suggested that glycolysis and carbohydrate metabolism were significantly altered in puffed samples in both albedo and flavedo. Expression of invertases and genes for sucrose export, amylose-starch and starch-maltose conversion was higher in puffed fruits. These changes may significantly alter source-sink communications. Genes associated with gibberellin and cytokinin signaling were downregulated in symptomatic albedo tissues, suggesting that these hormones play key roles in the disorder. Findings may be applied toward the development of early diagnostic methods based on host response genes and metabolites (i.e. citric acid), and toward therapeutics based on hormones.

The increasing incidence of young-onset colorectal cancer: a call to action

In the United States, colorectal cancer (CRC) is the third most common and second most lethal cancer. More than one-tenth of CRC cases (11% of colon cancers and 18% of rectal cancers) have a young onset (ie, occurring in individuals younger than 50 years). The CRC incidence and mortality rates are decreasing among all age groups older than 50 years, yet increasing in younger individuals for whom screening use is limited and key symptoms may go unrecognized. Familial syndromes account for approximately 20% of young-onset CRCs, and the remainder are typically microsatellite stable cancers, which are more commonly diploid than similar tumors in older individuals. Young-onset CRCs are more likely to occur in the distal colon or rectum, be poorly differentiated, have mucinous and signet ring features, and present at advanced stages. Yet, stage-specific survival in patients with young-onset CRC is comparable to that of patients with later-onset cancer. Primary care physicians have an important opportunity to identify high-risk young individuals for screening and to promptly evaluate CRC symptoms. Risk modification, targeted screening, and prophylactic surgery may benefit individuals with a predisposing hereditary syndrome or condition (eg, inflammatory bowel disease) or a family history of CRC or advanced adenomatous polyps. When apparently average-risk young adults present with CRC-like symptoms (eg, unexplained persistent rectal bleeding, anemia, and abdominal pain), endoscopic work-ups can expedite diagnosis. Early screening in high-risk individuals and thorough diagnostic work-ups in symptomatic young adults may improve young-onset CRC trends.

Gene expression and genetic variation in human atria

BACKGROUND

The human left and right atria have different susceptibilities to develop atrial fibrillation (AF). However, the molecular events related to structural and functional changes that enhance AF susceptibility are still poorly understood.

OBJECTIVE

The purpose of this study was to characterize gene expression and genetic variation in human atria.

METHODS

We studied the gene expression profiles and genetic variations in 53 left atrial and 52 right atrial tissue samples collected from the Myocardial Applied Genomics Network (MAGNet) repository. The tissues were collected from heart failure patients undergoing transplantation and from unused organ donor hearts with normal ventricular function. Gene expression was profiled using the Affymetrix GeneChip Human Genome U133A Array. Genetic variation was profiled using the Affymetrix Genome-Wide Human SNP Array 6.0.

RESULTS

We found that 109 genes were differentially expressed between left and right atrial tissues. A total of 187 and 259 significant cis-associations between transcript levels and genetic variants were identified in left and right atrial tissues, respectively. We also found that a single nucleotide polymorphism at a known AF locus, rs3740293, was associated with the expression of MYOZ1 in both left and right atrial tissues.

CONCLUSION

We found a distinct transcriptional profile between the right and left atrium and extensive cis-associations between atrial transcripts and common genetic variants. Our results implicate MYOZ1 as the causative gene at the chromosome 10q22 locus for AF.

Molecular polymorphism related to flowering trait variation in a Phaseolus vulgaris L. collection

The aim of this study was to investigate the flowering variation and the molecular polymorphism in key regulatory genes that control flowering in a Phaseolus vulgaris L. collection of 94 accessions from Europe and the Americas. The analysis of variance revealed that the difference in days-to-flowering between accessions was significant, with European accessions characterized by flowering precocity. Population structure analysis corroborated previous data on the genetic distinction between the Andean and Mesoamerican gene pools. A low level of admixture was detected. Genomic sequences of 15 gene fragments were obtained. About 7.0 kb per accession were sequenced and a total of 48 nucleotide substitutions identified. A Mixed Linear Model analysis, including population structure and kinship, was used to identify marker-trait associations. Haplotype tagging single nucleotide polymorphisms (htSNPs) associated with the studied traits were detected: in PvVRN1 and PvPHYB with days-to-flowering, in PvMYB29 with number of flower buds per inflorescence and in PvTFL1z and PvFCA with inflorescence length. The two genes associated with days-to-flowering control belong to the photoperiod and vernalization pathways. In particular, the PvVRN1 gene appears to play an important role in regulating the adaptation process of common bean.

Moving from unsequenced to sequenced genome: reanalysis of the proteome of Leishmania donovani

The kinetoplastid protozoan parasite, Leishmania donovani, is the causative agent of kala azar or visceral leishmaniasis. Kala azar is a severe form of leishmaniasis that is fatal in the majority of untreated cases. Studies on proteomic analysis of L. donovani thus far have been carried out using homology-based identification based on related Leishmania species (L. infantum, L. major and L. braziliensis) whose genomes have been sequenced. Recently, the genome of L. donovani was fully sequenced and the data became publicly available. We took advantage of the availability of its genomic sequence to carry out a more accurate proteogenomic analysis of L. donovani proteome using our previously generated dataset. This resulted in identification of 17,504 unique peptides upon database-dependent search against the annotated proteins in L. donovani. These peptides were assigned to 3999 unique proteins in L. donovani. 2296 proteins were identified in both the life stages of L. donovani, while 613 and 1090 proteins were identified only from amastigote and promastigote stages, respectively. The proteomic data was also searched against six-frame translated L. donovani genome, which led to 255 genome search-specific peptides (GSSPs) resulting in identification of 20 novel genes and correction of 40 existing gene models in L. donovani.

BIOLOGICAL SIGNIFICANCE

Leishmania donovani genome sequencing was recently completed, which permitted us to use a proteogenomic approach to map its proteome and to carry out annotation of it genome. This resulted in mapping of 50% (3999 proteins) of L. donovani proteome. Our study identified 20 novel genes previously not predicted from the L. donovani genome in addition to correcting annotations of 40 existing gene models. The identified proteins may help in better understanding of stage-specific protein expression profiles in L. donovani and to identify novel stage-specific drug targets in L. donovani which could be used in the treatment of leishmaniasis. This article is part of a Special Issue entitled: Trends in Microbial Proteomics.

Correspondence of executive function related functional and anatomical alterations in aging brain

Neurocognitive aging studies have focused on age-related changes in neural activity or neural structure but few studies have focused on relationships between the two. The present study quantitatively reviewed 24 studies of age-related changes in fMRI activation across a broad spectrum of executive function tasks using activation likelihood estimation (ALE) and 22 separate studies of age-related changes in gray matter using voxel-based morphometry (VBM). Conjunction analyses between functional and structural alteration maps were constructed. Overlaps were only observed in the conjunction of dorsolateral prefrontal cortex (DLPFC) gray matter reduction and functional hyperactivation but not hypoactivation. It was not evident that the conjunctions between gray matter and activation were related to task performance. Theoretical implications of these results are discussed.

Psychosis effect on hippocampal reduction in schizophrenia

INTRODUCTION

In schizophrenia, disruption of the neurodevelopmental processes may lead to brain changes and subsequent clinical manifestations of the illness. Reports of the progressive nature of these morphological brain changes raise questions about their causes. The possible toxic effects of repeated stressful psychotic episodes may contribute to the disease progression.

OBJECTIVES

To analyze the influence of illness duration and previous psychotic episodes on hippocampal gray matter volume (GMV) in schizophrenia.

METHODS

We performed an analysis of hippocampal GMV correlations with illness duration, number of previous psychotic episodes, and age in 24 schizophrenia patients and 24 matched healthy controls.

RESULTS

We found a cluster of GMV voxels in the left hippocampal tail that negatively correlated with the number of previous psychotic episodes, independent from the effect of age. On the other hand we found no effect of illness duration independent of age on the hippocampal GMV. Finally, we found a cluster of significant group-by-age interaction in the left hippocampal head.

CONCLUSIONS

We found an additive adverse effect of psychotic episodes on hippocampal morphology in schizophrenia. Our findings support toxicity of psychosis concept, together with etiological heterogeneity of brain changes in schizophrenia.

Genetic variations in VDR associated with prostate cancer risk and progression in a Korean population

Low levels of vitamin D are implicated as a potential risk factor for prostate cancer, and the vitamin D receptor (VDR) gene may be important in the onset and progression of prostate cancer. In this study, sequence variants in the VDR gene were investigated in a Korean study cohort to determine whether they are associated with prostate cancer risk. We evaluated the association between 47 single nucleotide polymorphisms (SNPs) in the VDR gene and prostate cancer risk as well as clinical characteristics (prostate-specific antigen level, clinical stage, pathological stage and Gleason score) in Korean men (272 prostate cancer patients and 173 benign prostatic hyperplasia patient who underwent a prostate biopsy, which was negative for malignancy) using unconditional logistic regression. The statistical analysis suggested that two VDR sequence variants (rs2408876 and rs2239182) had a significant association with prostate cancer risk (odds ratio [OR]. 1.41; p=0.03; OR, 0.73; p=0.05, respectively). Logistic analyses of the VDR polymorphisms with several prostate cancer related factors showed that several SNPs were significant; nine SNPs to PSA level, three to clinical stage, two to pathological stage, and three SNPs to the Gleason score. The results suggest that some VDR gene polymorphisms in Korean men might not only be associated with prostate cancer risk but also significantly related to prostate cancer-related risk factors such as PSA level, tumor stage, and Gleason score. However, current limitation for small cohort with not-healthy control group might have false positive effects; therefore it should be overcome via further large-scale validating studies.

Open source libraries and frameworks for mass spectrometry based proteomics: a developer's perspective

Data processing, management and visualization are central and critical components of a state of the art high-throughput mass spectrometry (MS)-based proteomics experiment, and are often some of the most time-consuming steps, especially for labs without much bioinformatics support. The growing interest in the field of proteomics has triggered an increase in the development of new software libraries, including freely available and open-source software. From database search analysis to post-processing of the identification results, even though the objectives of these libraries and packages can vary significantly, they usually share a number of features. Common use cases include the handling of protein and peptide sequences, the parsing of results from various proteomics search engines output files, and the visualization of MS-related information (including mass spectra and chromatograms). In this review, we provide an overview of the existing software libraries, open-source frameworks and also, we give information on some of the freely available applications which make use of them. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

Maternal-fetal metabolic gene-gene interactions and risk of neural tube defects

Single-gene analyses indicate that maternal genes associated with metabolic conditions (e.g., obesity) may influence the risk of neural tube defects (NTDs). However, to our knowledge, there have been no assessments of maternal-fetal metabolic gene-gene interactions and NTDs. We investigated 23 single nucleotide polymorphisms among 7 maternal metabolic genes (ADRB3, ENPP1, FTO, LEP, PPARG, PPARGC1A, and TCF7L2) and 2 fetal metabolic genes (SLC2A2 and UCP2). Samples were obtained from 737 NTD case-parent triads included in the National Birth Defects Prevention Study for birth years 1999-2007. We used a 2-step approach to evaluate maternal-fetal gene-gene interactions. First, a case-only approach was applied to screen all potential maternal and fetal interactions (n = 76), as this design provides greater power in the assessment of gene-gene interactions compared to other approaches. Specifically, ordinal logistic regression was used to calculate the odds ratio (OR) and 95% confidence interval (CI) for each maternal-fetal gene-gene interaction, assuming a log-additive model of inheritance. Due to the number of comparisons, we calculated a corrected p-value (q-value) using the false discovery rate. Second, we confirmed all statistically significant interactions (q < 0.05) using a log-linear approach among case-parent triads. In step 1, there were 5 maternal-fetal gene-gene interactions with q < 0.05. The "top hit" was an interaction between maternal ENPP1 rs1044498 and fetal SLC2A2 rs6785233 (interaction OR = 3.65, 95% CI: 2.32-5.74, p = 2.09×10(-8), q=0.001), which was confirmed in step 2 (p = 0.00004). Our findings suggest that maternal metabolic genes associated with hyperglycemia and insulin resistance and fetal metabolic genes involved in glucose homeostasis may interact to increase the risk of NTDs.

Spinal gene expression profiling and pathways analysis of a CB2 agonist (MDA7)-targeted prevention of paclitaxel-induced neuropathy

AIMS

Patients receiving paclitaxel often develop peripheral neuropathies. We found that a novel selective cannabinoid CB2 receptor agonist (MDA7) prevents paclitaxel-induced mechanical allodynia in rats and mice. Here we investigated gene expression profiling in the lumbar spinal cord after 14-day treatment of MDA7 in paclitaxel animals and analyzed possible signaling pathways underlying the preventive effect of MDA7 on paclitaxel-induced neuropathy.

METHODS

Peripheral mechanical allodynia was induced in rats or mice receiving intraperitoneal (i.p.) injection of paclitaxel at a dose of 1mg/kg daily for four consecutive days. MDA7 was administered at a dose of 15mg/kg 15min before paclitaxel and then continued daily for another 10days. Whole-genome gene expression profiling in the lumbar spinal cord of MDA7 and paclitaxel-treated rats was investigated using microarray analysis. The Ingenuity pathway analysis was performed to determine the potential relevant canonical pathways responsible for the effect of MDA7 on paclitaxel-induced peripheral neuropathy.

RESULTS

We observed that the inflammatory molecular networks including tumor necrosis factor (TNF), nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB), transforming growth factor beta (TGFβ), and mitogen-activated protein kinases (MAPK) signaling are most relevant to the preventive effect of MDA7 on paclitaxel-induced peripheral neuropathy. In addition, genes encoding molecules that are important in central sensitization such as glutamate transporters and N-methyl-d-aspartate receptor 2B (NMDAR2B), and neuro-immune-related genes such as neuronal nitric oxide synthase (nNOS1), chemokine CX3CL1 (a mediator for microglial activation), toll-like receptor 2 (TLR2), and leptin were differentially modulated by MDA7.

CONCLUSION

The preventive effect of MDA7 on paclitaxel-induced peripheral allodynia in rats may be associated with genes involved in signal pathways in central sensitization, microglial activation, and neuroinflammation in the spinal cord.

Lack of BDNF expression through promoter IV disturbs expression of monoamine genes in the frontal cortex and hippocampus

Brain-derived neurotrophic factor (BDNF) is implicated in the pathophysiology of psychiatric conditions including major depression and schizophrenia. Mice lacking activity-driven BDNF expression through promoter IV (knock-in promoter IV: KIV) exhibit depression-like behavior, inflexible learning, and impaired response inhibition. Monoamine systems (serotonin, dopamine, and noradrenaline) are suggested to be involved in depression and schizophrenia since many of the current antidepressants and antipsychotics increase the brain levels of monoamines and/or act on monoamine receptors. To elucidate the impact of activity-driven BDNF on the monoamine systems, we examined mRNA levels for 30 monoamine-related genes, including receptors, transporters, and synthesizing enzymes, in KIV and control wild-type mice by using quantitative reverse-transcription polymerase chain reaction (qRT-PCR). mRNA levels were measured in the frontal cortex and hippocampus, which are regions related to depression and schizophrenia and where promoter IV is active. The frontal cortex of KIV mice showed reduced levels of mRNA expression for serotonin receptors 1b, 2a, and 5b (5HTR1b, 5HTR2a, 5HTR5b), dopamine D2 receptors (DRD2), and adrenergic receptors alpha 1a and 1d (AdRα1a and AdRα1b), but increased levels for serotonin synthesizing enzyme, tryptophan hydroxylase (TPH), and dopamine D4 receptor (DRD4) when compared to control wild-type mice. The hippocampus of KIV mice showed decreased levels of 5HTR5b. Our results provide causal evidence that lack of promoter IV-driven BDNF disturbs expression of monoaminergic genes in the frontal cortex and hippocampus. These disturbed expression changes in the monoamine systems may mediate the depression- and schizophrenia-like behavior of KIV mice. Our results also suggest that antidepressant and antipsychotic treatments may actually interfere with and normalize the disturbed monoamine systems caused by reduced activity-dependent BDNF, while the treatment responses to these drugs may differ in the subject with reduced BDNF levels caused by stress and lack of neuronal activity.

Serological autoantibody profiling of type 1 diabetes by protein arrays

The need for biomarkers that illuminate the pathophysiology of type 1 diabetes (T1D), enhance early diagnosis and provide additional avenues for therapeutic intervention is well recognized in the scientific community. We conducted a proteome-scale, two-stage serological AAb screening followed by an independent validation study. In the first stage, the immunoreactivity was compared between T1D cases and healthy controls against ~6000 human proteins using the nucleic acid programmable protein array (NAPPA). Genes identified with higher signal intensities in patients were challenged with a larger sample set during the second stage. Statistical analysis revealed 26 novel autoantigens and a known T1D-associated autoantigen. During validation, we verified the presence of AAbs to dual specificity tyrosine-phosphorylation-regulated kinase 2 (DYRK2) using the Luciferase ImmunoPrecipitation System (LIPS) assay (36% sensitivity, 98% specificity). The AUC for a combination of DYRK2A and the classical T1D AAb IA-2A was 0.90 compared to 0.72 for DYRK2A and 0.64 for IA-2A alone. This is the first systematic screening for seroreactivity against a large number of human proteins in T1D patients. We demonstrated the application of protein microarrays to identify novel autoantigens in T1D, expanded the current T1D "autoantigenome" and help fulfill the goal of searching for novel biomarker candidates for T1D.

BIOLOGICAL SIGNIFICANCE

Protein microarrays provide a high-throughput platform that enables the profiling of serum antibodies to a large number of protein antigens. The value of AAb biomarkers in diagnosis, prognosis and treatment is well recognized in autoimmune diseases including T1D. We performed a systematic screening for new T1D-associated autoantigens by adapting the innovative protein array platform NAPPA. We believe that the discovery in this study will add information on candidate autoantigens that could potentially improve the diagnosis and help uncover the pathophysiology of T1D. The successful use of NAPPA for T1D AAb profiling will open the window for larger studies including more human antigen genes and other autoimmune diseases.