Construct and Compare Gene Coexpression Networks with DAPfinder and DAPview

Background: DAPfinder and DAPview are novel BRB-ArrayTools plug-ins to construct gene coexpression networks and identify significant differences in pairwise gene-gene coexpression between two phenotypes. Results: Each significant difference in gene-gene association represents a Differentially Associated Pair (DAP). Our tools include several choices of filtering methods, gene-gene association metrics, statistical testing methods and multiple comparison adjustments. Network results are easily displayed in Cytoscape. Analyses of glioma experiments and microarray simulations demonstrate the utility of these tools. Conclusions: DAPfinder is a new friendly-user tool for reconstruction and comparison of biological networks.

Phase II Trial of Infusional Fluorouracil, Irinotecan, and Bevacizumab for Metastatic Colorectal Cancer: Efficacy and Circulating Angiogenic Biomarkers Associated With Therapeutic Resistance

Purpose We investigated the efficacy of fluorouracil (FU), leucovorin, irinotecan, and bevacizumab (FOLFIRI + B) in a phase II trial in patients previously untreated for metastatic colorectal cancer (mCRC), and changes during treatment in plasma cytokines and angiogenic factors (CAFs) as potential markers of treatment response and therapeutic resistance. Patients and Methods We conducted a phase II, two-institution trial of FOLFIRI + B. Each 14-day cycle consisted of bevacizumab (5 mg/kg), irinotecan (180 mg/m(2)), bolus FU (400 mg/m(2)), and leucovorin (400 mg/m(2)) followed by a 46-hour infusion of FU (2,400 mg/m(2)). Levels of 37 CAFs were assessed using multiplex-bead assays and enzyme-linked immunosorbent assay at baseline, during treatment, and at the time of progressive disease (PD). Results Forty-three patients were enrolled. Median progression-free survival (PFS), the primary end point of the study, was 12.8 months. Median overall survival was 31.3 months, with a response rate of 65%. Elevated interleukin-8 at baseline was associated with a shorter PFS (11 v 15.1 months, P = .03). Before the radiographic development of PD, several CAFs associated with angiogenesis and myeloid recruitment increased compared to baseline, including basic fibroblast growth factor (P = .046), hepatocyte growth factor (P = .046), placental growth factor (P < .001), stromal-derived factor-1 (P = .04), and macrophage chemoattractant protein-3 (P < .001). Conclusion Efficacy and tolerability of FOLFIRI + B appeared favorable to historical controls in this single arm study. Before radiographic progression, there was a shift in balance of CAFs, with a rise in alternate pro-angiogenic cytokines and myeloid recruitment factors in subsets of patients that may represent mechanisms of resistance.

Global Analysis of Protein Palmitoylation in African Trypanosomes

Many eukaryotic proteins are posttranslationally modified by the esterification of cysteine thiols to long-chain fatty acids. This modification, protein palmitoylation, is catalyzed by a large family of palmitoyl acyltransferases that share an Asp-His-His-Cys Cys-rich domain but differ in their subcellular localizations and substrate specificities. In Trypanosoma brucei, the flagellated protozoan parasite that causes African sleeping sickness, protein palmitoylation has been observed for a few proteins, but the extent and consequences of this modification are largely unknown. We undertook the present study to investigate T. brucei protein palmitoylation at both the enzyme and substrate levels. Treatment of parasites with an inhibitor of total protein palmitoylation caused potent growth inhibition, yet there was no effect on growth by the separate, selective inhibition of each of the 12 individual T. brucei palmitoyl acyltransferases. This suggested either that T. brucei evolved functional redundancy for the palmitoylation of essential palmitoyl proteins or that palmitoylation of some proteins is catalyzed by a noncanonical transferase. To identify the palmitoylated proteins in T. brucei, we performed acyl biotin exchange chemistry on parasite lysates, followed by streptavidin chromatography, two-dimensional liquid chromatography-tandem mass spectrometry protein identification, and QSpec statistical analysis. A total of 124 palmitoylated proteins were identified, with an estimated false discovery rate of 1.0%. This palmitoyl proteome includes all of the known palmitoyl proteins in procyclic-stage T. brucei as well as several proteins whose homologues are palmitoylated in other organisms. Their sequences demonstrate the variety of substrate motifs that support palmitoylation, and their identities illustrate the range of cellular processes affected by palmitoylation in these important pathogens.

Transcriptional changes in U343 MG-a glioblastoma cell line exposed to ionizing radiation

Glioblastoma multiforme (GBM) is a highly invasive and radioresistant brain tumor. Aiming to study how glioma cells respond to gamma-rays in terms of biological processes involved in cellular responses, we performed experiments at cellular context and gene expression analysis in U343-MG-a GBM cells irradiated with 1 Gy and collected at 6 h post-irradiation. The survival rate was approximately 61% for 1 Gy and was completely reduced at 16 Gy. By performing the microarray technique, 859 cDNA clones were analyzed. The Significance Analysis of Microarray algorithm indicated 196 significant expressed genes (false discovery rate (FDR) = 0.42%): 67 down-regulated and 97 up-regulated genes, which belong to several classes: metabolism, adhesion/cytoskeleton, signal transduction, cell cycle/apoptosis, membrane transport, DNA repair/DNA damage signaling, transcription factor, intracellular signaling, and RNA processing. Differential expression patterns of five selected genes (HSPA9B, INPP5A, PIP5K1A, FANCG, and TPP2) observed by the microarray analysis were further confirmed by the quantitative real time RT-PCR method, which demonstrated an up-regulation status of those genes. These results indicate a broad spectrum of biological processes (which may reflect the radio-resistance of U343 cells) that were altered in irradiated glioma cells, so as to guarantee cell survival.

Rare genomic structural variants in complex disease: lessons from the replication of associations with obesity.

The limited ability of common variants to account for the genetic contribution to complex disease has prompted searches for rare variants of large effect, to partly explain the 'missing heritability'. Analyses of genome-wide genotyping data have identified genomic structural variants (GSVs) as a source of such rare causal variants. Recent studies have reported multiple GSV loci associated with risk of obesity. We attempted to replicate these associations by similar analysis of two familial-obesity case-control cohorts and a population cohort, and detected GSVs at 11 out of 18 loci, at frequencies similar to those previously reported. Based on their reported frequencies and effect sizes (OR≥25), we had sufficient statistical power to detect the large majority (80%) of genuine associations at these loci. However, only one obesity association was replicated. Deletion of a 220 kb region on chromosome 16p11.2 has a carrier population frequency of 2×10(-4) (95% confidence interval [9.6×10(-5)-3.1×10(-4)]); accounts overall for 0.5% [0.19%-0.82%] of severe childhood obesity cases (P = 3.8×10(-10); odds ratio = 25.0 [9.9-60.6]); and results in a mean body mass index (BMI) increase of 5.8 kg.m(-2) [1.8-10.3] in adults from the general population. We also attempted replication using BMI as a quantitative trait in our population cohort; associations with BMI at or near nominal significance were detected at two further loci near KIF2B and within FOXP2, but these did not survive correction for multiple testing. These findings emphasise several issues of importance when conducting rare GSV association, including the need for careful cohort selection and replication strategy, accurate GSV identification, and appropriate correction for multiple testing and/or control of false discovery rate. Moreover, they highlight the potential difficulty in replicating rare CNV associations across different populations. Nevertheless, we show that such studies are potentially valuable for the identification of variants making an appreciable contribution to complex disease.

Structured RNAs in the ENCODE selected regions of the human genome.

Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic-stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to approximately 2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3'-UTRs. While we estimate a significant false discovery rate of approximately 50%-70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).

Connectome alterations in schizophrenia

Introduction : DTI has proven to be an exquisite biomarker of tissue microstructure integrity. This technique has been successfully applied to schizophrenia in showing that fractional anisotropy (FA, a marker of white matter integrity) is diminished in several areas of the brain (Kyriakopoulos M et al (2008)). New ways of representing diffusion data emerged recently and achieved to create structural connectivity maps in healthy brains (Hagmann P et al. (2008)). These maps have the capacity to study alterations over the entire brain at the connection and network level. This is of high interest in complex disconnection diseases like schizophrenia. We report on the specific network alterations of schizophrenic patients. Methods : 13 patients with chronic schizophrenia were recruited from in-patient, day treatment, out-patient clinics. Comparison subjects were recruited and group-matched to patients on age, sex, handedness, and parental social economic-status. This study was approved by the local IRB and subjects had to give informed written consent. They were scanned with a 3T clinical MRI scanner. DTI and high-resolution anatomical T1w imaging were performed during the same session. The path from diffusion MRI to a multi-resolution structural connection matrices of the entire brain is a five steps process that was performed in a similar way as described in Hagmann P et al. (2008). (1) DTI and T1w MRI of the brain, (2) segmentation of white and gray matter, (3) white matter tractography, (4) segmentation of the cortex into 242 ROIs of equal surface area covering the entire cortex (Fig 1), (5) the connection network was constructed by measuring for each ROI to ROI connection the related average FA along the corresponding tract. Results : For every connection between 2 ROIs of the network we tested the hypothesis H0: "average FA along fiber pathway is larger or equal in patients than in controls". H0 was rejected for connections where average FA in a connection was significantly lower in patients than in controls. Threshold p-value was 0.01 corrected for multiple comparisons with false discovery rate. We identified consistently that temporal, occipito-temporal, precuneo-temporal as well as frontal inferior and precuneo-cingulate connections were altered (Fig 2: significant connections in yellow). This is in agreement with the known literature, which showed across several studies that FA is diminished in several areas of the brain. More precisely, abnormalities were reported in the prefrontal and temporal white matter and to some extent also in the parietal and occipital regions. The alterations reported in the literature specifically included the corpus callosum, the arcuate fasciculus and the cingulum bundle, which was the case here as well. In addition small world indexes are significantly reduced in patients (p<0.01) (Fig. 3). Conclusions : Using connectome mapping to characterize differences in structural connectivity between healthy and diseased subjects we were able to show widespread connectional alterations in schizophrenia patients and systematic small worldness decrease, which is a marker of network desorganization. More generally, we described a method that has the capacity to sensitively identify structure alterations in complex disconnection syndromes where lesions are widespread throughout the connectional network.

Assessment of left coronary artery beat-to-beat repositioning in order to propose an optimal acquisition window for coronary MRA

Introduction: Coronary magnetic resonance angiography (MRA) is a medical imaging technique that involves collecting data from consecutive heartbeats, always at the same time in the cardiac cycle, in order to minimize heart motion artifacts. This technique relies on the assumption that coronary arteries always follow the same trajectory from heartbeat to heartbeat. Until now, choosing the acquisition window in the cardiac cycle was based exclusively on the position of minimal coronary motion. The goal of this study was to test the hypothesis that there are time intervals during the cardiac cycle when coronary beat-to-beat repositioning is optimal. The repositioning uncertainty values in these time intervals were then compared with the intervals of low coronary motion in order to propose an optimal acquisition window for coronary MRA. Methods: Cine breath-hold x-ray angiograms with synchronous ECG were collected from 11 patients who underwent elective routine diagnostic coronarography. Twenty-three bifurcations of the left coronary artery were selected as markers to evaluate repositioning uncertainty and velocity during cardiac cycle. Each bifurcation was tracked by two observers, with the help of a user-assisted algorithm implemented in Matlab (The Mathworks, Natick, MA, USA) that compared the trajectories of the markers coming from consecutive heartbeats and computed the coronary repositioning uncertainty with steps of 50ms until 650ms after the R-wave. Repositioning uncertainty was defined as the diameter of the smallest circle encompassing the points to be compared at the same time after the R-wave. Student's t-tests with a false discovery rate (FDR, q=0.1) correction for multiple comparison were applied to see whether coronary repositioning and velocity vary statistically during cardiac cycle. Bland-Altman plots and linear regression were used to assess intra- and inter-observer agreement. Results: The analysis of left coronary artery beat-to-beat repositioning uncertainty shows a tendency to have better repositioning in mid systole (less than 0.84±0.58mm) and mid diastole (less than 0.89±0.6mm) than in the rest of the cardiac cycle (highest value at 50ms=1.35±0.64mm). According to Student's t-tests with FDR correction for multiple comparison (q=0.1), two intervals, in mid systole (150-200ms) and mid diastole (550-600ms), provide statistically better repositioning in comparison with the early systole and the early diastole. Coronary velocity analysis reveals that left coronary artery moves more slowly in end systole (14.35±11.35mm/s at 225ms) and mid diastole (11.78±11.62mm/s at 625ms) than in the rest of the cardiac cycle (highest value at 25ms: 55.96±22.34mm/s). This was confirmed by Student's t-tests with FDR correction for multiple comparison (q=0.1, FDR-corrected p-value=0.054): coronary velocity values at 225, 575 and 625ms are not much different between them but they are statistically inferior to all others. Bland-Altman plots and linear regression show that intra-observer agreement (y=0.97x+0.02 with R²=0.93 at 150ms) is better than inter-observer (y=0.8x+0.11 with R²=0.67 at 150ms). Discussion: The present study has demonstrated that there are two time intervals in the cardiac cycle, one in mid systole and one in mid diastole, where left coronary artery repositioning uncertainty reaches points of local minima. It has also been calculated that the velocity is the lowest in end systole and mid diastole. Since systole is less influenced by heart rate variability than diastole, it was finally proposed to test an acquisition window between 150 and 200ms after the R-wave.

Global and local connectivity changes in schizophrenia investigated by diffusion connectome

Background: New ways of representing diffusion data emerged recently and achieved to create structural connectivitymaps in healthy brains (Hagmann P et al. (2008)). These maps have the capacity to study alterations over the entire brain at the connection and network level. This is of high interest in complex disconnection diseases like schizophrenia. In this Pathology where multiple lines of evidence suggest the association of the pathology with abnormalities in neural circuitry and impaired structural connectivity, the diffusion imaging has been widely applied. Despite the large findings, most of the research using the diffusion just uses some scalar map derived from diffusion to show that some markers of white matter integrity are diminished in several areas of the brain (Kyriakopoulos M et al (2008)). Thanks to the structural connectionmatrix constructed by the whole brain tractography, we report in this work the network connectivity alterations in the schizophrenic patients. Methods: We investigated 13 schizophrenic patients as assessed by the DIGS (Diagnostic Interview for genetic studies, DSM IV criteria) and 13 healthy controls. We have got from each volunteer a DT-MRI as well as Qball imaging dataset and a high resolution anatomic T1 performed during the same session; with a 3 T clinical MRI scanner. The controls were matched on age, gender, handedness, and parental social economic-status. For all the subjects, a low resolution connection matrix is obtained by dividing the cortex into 66 gyral based ROIs. A higher resolution matrix is constructed using 250 ROIs as described in Hagmann P et al. (2008). These ROIs are respectively used jointly with the diffusion tractography to construct the high and low resolution densities connection matrices for each subject. In a first step the matrices of the groups are compared in term of connectivity, and not in term of density to check if the pathological group shows a loss of global connectivity. In this context the density connection matrices were binarized. As some local connectivity changes were also suspected, especially in frontal and temporal areas, we have also looked for the areas where the connectivity showed significant changes. Results: The statistical analysis revealed a significant loss of global connectivity in the schizophrenic's brains at level 5%. Furthermore, by constructing specific statistics which represent local connectivity within the anatomical regions (66 ROIs) using the data obtained by the finest resolution (250 ROIs) to improve the robustness, we found the regions that cause this significant loss of connectivity. The significance is observed after multiple testing corrections by the False Discovery Rate. Discussion: The detected regions are almost the same as those reported in the literature as the involved regions in schizophrenia. Most of the connectivity decreases are noted in both hemispheres in the fronto-frontal and temporo-temporal regions as well as some temporal ROIs with their adjacent ROIs in parietal and occipital lobes.

FGF21 signalling pathway and metabolic traits - genetic association analysis.

Fibroblast growth factor 21 (FGF21) is a novel master regulator of metabolic profile. The biological actions of FGF21 are elicited upon its klotho beta (KLB)-facilitated binding to FGF receptor 1 (FGFR1), FGFR2 and FGFR3. We hypothesised that common polymorphisms in the FGF21 signalling pathway may be associated with metabolic risk. At the screening stage, we examined associations between 63 common single-nucleotide polymorphisms (SNPs) in five genes of this pathway (FGF21, KLB, FGFR1, FGFR2, FGFR3) and four metabolic phenotypes (LDL cholesterol - LDL-C, HDL-cholesterol - HDL-C, triglycerides and body mass index) in 629 individuals from Silesian Hypertension Study (SHS). Replication analyses were performed in 5478 unrelated individuals of the Swiss CoLaus cohort (imputed genotypes) and in 3030 directly genotyped individuals of the German Myocardial Infarction Family Study (GerMIFS). Of 54 SNPs that met quality control criteria after genotyping in SHS, 4 (rs4733946 and rs7012413 in FGFR1; rs2071616 in FGFR2 and rs7670903 in KLB) showed suggestive association with LDL-C (P=0.0006, P=0.0013, P=0.0055, P=0.011, respectively) and 1 (rs2608819 in KLB) was associated with body mass index (P=0.011); all with false discovery rate q<0.5. Of these, only one FGFR2 polymorphism (rs2071616) showed replicated association with LDL-C in both CoLaus (P=0.009) and men from GerMIFS (P=0.017). The direction of allelic effect of rs2071616 upon LDL-C was consistent in all examined populations. These data show that common genetic variations in FGFR2 may be associated with LDL-C in subjects of white European ancestry.

Structured RNAs in the ENCODE selected regions of the human genome

Functional RNA structures play an important role both in the context of noncoding RNA transcripts as well as regulatory elements in mRNAs. Here we present a computational study to detect functional RNA structures within the ENCODE regions of the human genome. Since structural RNAs in general lack characteristic signals in primary sequence, comparative approaches evaluating evolutionary conservation of structures are most promising. We have used three recently introduced programs based on either phylogenetic–stochastic context-free grammar (EvoFold) or energy directed folding (RNAz and AlifoldZ), yielding several thousand candidate structures (corresponding to ∼2.7% of the ENCODE regions). EvoFold has its highest sensitivity in highly conserved and relatively AU-rich regions, while RNAz favors slightly GC-rich regions, resulting in a relatively small overlap between methods. Comparison with the GENCODE annotation points to functional RNAs in all genomic contexts, with a slightly increased density in 3′-UTRs. While we estimate a significant false discovery rate of ∼50%–70% many of the predictions can be further substantiated by additional criteria: 248 loci are predicted by both RNAz and EvoFold, and an additional 239 RNAz or EvoFold predictions are supported by the (more stringent) AlifoldZ algorithm. Five hundred seventy RNAz structure predictions fall into regions that show signs of selection pressure also on the sequence level (i.e., conserved elements). More than 700 predictions overlap with noncoding transcripts detected by oligonucleotide tiling arrays. One hundred seventy-five selected candidates were tested by RT-PCR in six tissues, and expression could be verified in 43 cases (24.6%).

Improved statistical evaluation of group differences in connectomes by screening-filtering strategy with application to study maturation of brain connections between childhood and adolescence.

Detecting local differences between groups of connectomes is a great challenge in neuroimaging, because the large number of tests that have to be performed and the impact on multiplicity correction. Any available information should be exploited to increase the power of detecting true between-group effects. We present an adaptive strategy that exploits the data structure and the prior information concerning positive dependence between nodes and connections, without relying on strong assumptions. As a first step, we decompose the brain network, i.e., the connectome, into subnetworks and we apply a screening at the subnetwork level. The subnetworks are defined either according to prior knowledge or by applying a data driven algorithm. Given the results of the screening step, a filtering is performed to seek real differences at the node/connection level. The proposed strategy could be used to strongly control either the family-wise error rate or the false discovery rate. We show by means of different simulations the benefit of the proposed strategy, and we present a real application of comparing connectomes of preschool children and adolescents.

Thermal evolution of gene expression profiles in Drosophila subobscura

Background: Despite its pervasiveness, the genetic basis of adaptation resulting in variation directly or indirectly related to temperature (climatic) gradients is poorly understood. By using 3-fold replicated laboratory thermal stocks covering much of the physiologically tolerable temperature range for the temperate (i.e., cold tolerant) species Drosophila subobscura we have assessed whole-genome transcriptional responses after three years of thermal adaptation, when the populations had already diverged for inversion frequencies, pre-adult life history components, and morphological traits. Total mRNA from each population was compared to a reference pool mRNA in a standard, highly replicated two-colour competitive hybridization experiment using cDNA microarrays.Results: A total of 306 (6.6%) cDNA clones were identified as 'differentially expressed' (following a false discovery rate correction) after contrasting the two furthest apart thermal selection regimes (i.e., 13°C vs . 22°C), also including four previously reported candidate genes for thermotolerance in Drosophila (Hsp26, Hsp68, Fst, and Treh). On the other hand, correlated patterns of gene expression were similar in cold- and warm-adapted populations. Analysis of functional categories defined by the Gene Ontology project point to an overrepresentation of genes involved in carbohydrate metabolism, nucleic acids metabolism and regulation of transcription among other categories. Although the location of differently expressed genes was approximately at random with respect to chromosomes, a physical mapping of 88 probes to the polytene chromosomes of D. subobscura has shown that a larger than expected number mapped inside inverted chromosomal segments.Conclusion: Our data suggest that a sizeable number of genes appear to be involved in thermal adaptation in Drosophila, with a substantial fraction implicated in metabolism. This apparently illustrates the formidable challenge to understanding the adaptive evolution of complex trait variation. Furthermore, some clustering of genes within inverted chromosomal sections was detected. Disentangling the effects of inversions will be obviously required in any future approach if we want to identify the relevant candidate genes.