104 research outputs found
Detection of regulator genes and eQTLs in gene networks
Genetic differences between individuals associated to quantitative phenotypic
traits, including disease states, are usually found in non-coding genomic
regions. These genetic variants are often also associated to differences in
expression levels of nearby genes (they are "expression quantitative trait
loci" or eQTLs for short) and presumably play a gene regulatory role, affecting
the status of molecular networks of interacting genes, proteins and
metabolites. Computational systems biology approaches to reconstruct causal
gene networks from large-scale omics data have therefore become essential to
understand the structure of networks controlled by eQTLs together with other
regulatory genes, and to generate detailed hypotheses about the molecular
mechanisms that lead from genotype to phenotype. Here we review the main
analytical methods and softwares to identify eQTLs and their associated genes,
to reconstruct co-expression networks and modules, to reconstruct causal
Bayesian gene and module networks, and to validate predicted networks in
silico.Comment: minor revision with typos corrected; review article; 24 pages, 2
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A comparative study on gene-set analysis methods for assessing differential expression associated with the survival phenotype
Abstract Background Many gene-set analysis methods have been previously proposed and compared through simulation studies and analysis of real datasets for binary phenotypes. We focused on the survival phenotype and compared the performances of Gene Set Enrichment Analysis (GSEA), Global Test (GT), Wald-type Test (WT) and Global Boost Test (GBST) methods in a simulation study and on two ovarian cancer data sets. We considered two versions of GSEA by allowing different weights: GSEA1 uses equal weights, yielding results similar to the Kolmogorov-Smirnov test; while GSEA2's weights are based on the correlation between genes and the phenotype. Results We compared GSEA1, GSEA2, GT, WT and GBST in a simulation study with various settings for the correlation structure of the genes and the association parameter between the survival outcome and the genes. Simulation results indicated that GT, WT and GBST consistently have higher power than GSEA1 and GSEA2 across all scenarios. However, the power of the five tests depends on the combination of correlation structure and association parameter. For the ovarian cancer data set, using the FDR threshold of q Conclusion Simulation studies and a real data example indicate that GT, WT and GBST tend to have high power, whereas GSEA1 and GSEA2 have lower power. We also found that the power of the five tests is much higher when genes are correlated than when genes are independent, when survival is positively associated with genes. It seems that there is a synergistic effect in detecting significant gene sets when significant genes have within-class correlation and the association between survival and genes is positive or negative (i.e., one-direction correlation).</p
Recursive SVM feature selection and sample classification for mass-spectrometry and microarray data
BACKGROUND: Like microarray-based investigations, high-throughput proteomics techniques require machine learning algorithms to identify biomarkers that are informative for biological classification problems. Feature selection and classification algorithms need to be robust to noise and outliers in the data. RESULTS: We developed a recursive support vector machine (R-SVM) algorithm to select important genes/biomarkers for the classification of noisy data. We compared its performance to a similar, state-of-the-art method (SVM recursive feature elimination or SVM-RFE), paying special attention to the ability of recovering the true informative genes/biomarkers and the robustness to outliers in the data. Simulation experiments show that a 5 %-~20 % improvement over SVM-RFE can be achieved regard to these properties. The SVM-based methods are also compared with a conventional univariate method and their respective strengths and weaknesses are discussed. R-SVM was applied to two sets of SELDI-TOF-MS proteomics data, one from a human breast cancer study and the other from a study on rat liver cirrhosis. Important biomarkers found by the algorithm were validated by follow-up biological experiments. CONCLUSION: The proposed R-SVM method is suitable for analyzing noisy high-throughput proteomics and microarray data and it outperforms SVM-RFE in the robustness to noise and in the ability to recover informative features. The multivariate SVM-based method outperforms the univariate method in the classification performance, but univariate methods can reveal more of the differentially expressed features especially when there are correlations between the features
Exome Sequencing Implicates Impaired GABA Signaling and Neuronal Ion Transport in Trigeminal Neuralgia
Trigeminal neuralgia (TN) is a common, debilitating neuropathic face pain syndrome often resistant to therapy. The familial clustering of TN cases suggests that genetic factors play a role in disease pathogenesis. However, no unbiased, large-scale genomic study of TN has been performed to date. Analysis of 290 whole exome-sequenced TN probands, including 20 multiplex kindreds and 70 parent-offspring trios, revealed enrichment of rare, damaging variants in GABA receptor-binding genes in cases. Mice engineered with a TN-associated de novo mutation (p.Cys188Trp) in the GABAA receptor Clβ channel Ξ³-1 subunit (GABRG1) exhibited trigeminal mechanical allodynia and face pain behavior. Other TN probands harbored rare damaging variants in Na+ and Ca+ channels, including a significant variant burden in the Ξ±-1H subunit of the voltage-gated Ca2+ channel Cav3.2 (CACNA1H). These results provide exome-level insight into TN and implicate genetically encoded impairment of GABA signaling and neuronal ion transport in TN pathogenesis
Surgical management and outcome of spinal alveolar soft part sarcoma (ASPA): a case series of five patients and literature review
Exome sequencing implicates genetic disruption of prenatal neuro-gliogenesis in sporadic congenital hydrocephalus
Congenital hydrocephalus (CH), characterized by enlarged brain ventricles, is considered a disease of excessive cerebrospinal fluid (CSF) accumulation and thereby treated with neurosurgical CSF diversion with high morbidity and failure rates. The poor neurodevelopmental outcomes and persistence of ventriculomegaly in some post-surgical patients highlight our limited knowledge of disease mechanisms. Through whole-exome sequencing of 381 patients (232 trios) with sporadic, neurosurgically treated CH, we found that damaging de novo mutations account for >17% of cases, with five different genes exhibiting a significant de novo mutation burden. In all, rare, damaging mutations with large effect contributed to ~22% of sporadic CH cases. Multiple CH genes are key regulators of neural stem cell biology and converge in human transcriptional networks and cell types pertinent for fetal neuro-gliogenesis. These data implicate genetic disruption of early brain development, not impaired CSF dynamics, as the primary pathomechanism of a significant number of patients with sporadic CH
Variations in influenza vaccination coverage among the high-risk population in Sweden in 2003/4 and 2004/5: a population survey
<p>Abstract</p> <p>Background</p> <p>In Sweden, the vaccination campaign is the individual responsibility of the counties, which results in different arrangements. The aim of this study was to find out whether influenza vaccination coverage rates (VCRs) had increased between 2003/4 and 2004/5 among population at high risk and to find out the influence of personal preferences, demographic characteristics and health care system characteristics on VCRs.</p> <p>Methods</p> <p>An average sample of 2500 persons was interviewed each season (2003/4 and 2004/5). The respondents were asked whether they had had an influenza vaccination, whether they suffered from chronic conditions and the reasons of non-vaccination. For every county the relevant health care system characteristics were collected via a questionnaire sent to the medical officers of communicable diseases.</p> <p>Results</p> <p>No difference in VCR was found between the two seasons. Personal invitations strongly increased the chance of having had a vaccination. For the elderly, the number of different health care professionals in a region involved in administering vaccines decreased this chance.</p> <p>Conclusion</p> <p>Sweden remained below the WHO-recommendations for population at high risk due to disease. To meet the 2010 WHO-recommendation further action may be necessary to increase vaccine uptake. Increasing the number of personal invitations and restricting the number of different administrators responsible for vaccination may be effective in increasing VCRs among the elderly.</p
Mechanisms and treatment of ischaemic stroke: insights from genetic associations
The precise pathophysiology of ischaemic stroke is unclear, and a greater understanding of the different mechanisms that underlie large-artery, cardioembolic and lacunar ischaemic stroke subtypes would enable the development of more-effective, subtype-specific therapies. Genome-wide association studies (GWASs) are identifying novel genetic variants that associate with the risk of stroke. These associations provide insight into the pathophysiological mechanisms, and present opportunities for novel therapeutic approaches. In this Review, we summarize the genetic variants that have been linked to ischaemic stroke in GWASs to date and discuss the implications of these associations for both our understanding and treatment of ischaemic stroke. The majority of genetic variants identified are associated with specific subtypes of ischaemic stroke, implying that these subtypes have distinct genetic architectures and pathophysiological mechanisms. The findings from the GWASs highlight the need to consider whether therapies should be subtype-specific. Further GWASs that include large cohorts are likely to provide further insights, and emerging technologies will complement and build on the GWAS findings
Imaginal Discs β A New Source of Chromosomes for Genome Mapping of the Yellow Fever Mosquito Aedes aegypti
Dengue fever is an emerging health threat to as much as half of the human population around the world. No vaccines or drug treatments are currently available. Thus, disease prevention is largely based on efforts to control its major mosquito vector Ae. aegypti. Novel vector control strategies, such as population replacement with pathogen-incompetent transgenic mosquitoes, rely on detailed knowledge of the genome organization for the mosquito. However, the current genome assembly of Ae. aegypti is highly fragmented and requires additional physical mapping onto chromosomes. The absence of readable polytene chromosomes makes genome mapping for this mosquito extremely challenging. In this study, we discovered and investigated a new source of chromosomes useful for the cytogenetic analysis in Ae. aegypti β mitotic chromosomes from imaginal discs of 4th instar larvae. Using natural banding patterns of these chromosomes, we developed a new band-based approach for physical mapping of DNA probes to the precise chromosomal positions. Further application of this approach for genome mapping will greatly enhance the utility of the existing draft genome sequence assembly for Ae. aegypti and thereby facilitate application of advanced genome technologies for investigating and developing novel genetic control strategies for dengue transmission
Nicotinic Receptor Gene CHRNA4 Interacts with Processing Load in Attention
Background: Pharmacological studies suggest that cholinergic neurotransmission mediates increases in attentional effort in response to high processing load during attention demanding tasks [1]. Methodology/Principal Findings: In the present study we tested whether individual variation in CHRNA4, a gene coding for a subcomponent in a4b2 nicotinic receptors in the human brain, interacted with processing load in multiple-object tracking (MOT) and visual search (VS). We hypothesized that the impact of genotype would increase with greater processing load in the MOT task. Similarly, we predicted that genotype would influence performance under high but not low load in the VS task. Two hundred and two healthy persons (age range = 39β77, Mean = 57.5, SD = 9.4) performed the MOT task in which twelve identical circular objects moved about the display in an independent and unpredictable manner. Two to six objects were designated as targets and the remaining objects were distracters. The same observers also performed a visual search for a target letter (i.e. X or Z) presented together with five non-targets while ignoring centrally presented distracters (i.e. X, Z, or L). Targets differed from non-targets by a unique feature in the low load condition, whereas they shared features in the high load condition. CHRNA4 genotype interacted with processing load in both tasks. Homozygotes for the T allele (N = 62) had better tracking capacity in the MOT task and identified targets faster in the high load trials of the VS task. Conclusion: The results support the hypothesis that the cholinergic system modulates attentional effort, and that commo
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