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Find video protocols related to scientific articles indexed in Pubmed.
TAILOR THE LONGITUDINAL ANAYSIS FOR NIH LONGITUDINAL NORMAL BRAIN DEVELOPMENTAL STUDY.
Proc IEEE Int Symp Biomed Imaging
PUBLISHED: 11-19-2014
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There are imminent needs for longitudinal analysis to make physiological inferences on NIH MRI study of normal brain development. But up to date, two critical aspects for longitudinal analysis, namely the selections of mean and covariance structures have not been addressed by the neuroimaging community. For the mean structure, we employed a linear free-knot B-spline regression in combination with quasi-least square estimating equations to approximate a nonlinear growth trajectory with piecewise linear segments for a friendly physiological interpretation. For covariance structure selection, we have proposed a novel time varying correlation structure considering not only the time separation between the repeated measures but also when these acquisitions occurred. We have demonstrated that the proposed covariance structure has a lower Akaike information criterion value than the commonly used Markov correlation structure.
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GPA: A Statistical Approach to Prioritizing GWAS Results by Integrating Pleiotropy and Annotation.
PLoS Genet.
PUBLISHED: 11-01-2014
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Results from Genome-Wide Association Studies (GWAS) have shown that complex diseases are often affected by many genetic variants with small or moderate effects. Identifications of these risk variants remain a very challenging problem. There is a need to develop more powerful statistical methods to leverage available information to improve upon traditional approaches that focus on a single GWAS dataset without incorporating additional data. In this paper, we propose a novel statistical approach, GPA (Genetic analysis incorporating Pleiotropy and Annotation), to increase statistical power to identify risk variants through joint analysis of multiple GWAS data sets and annotation information because: (1) accumulating evidence suggests that different complex diseases share common risk bases, i.e., pleiotropy; and (2) functionally annotated variants have been consistently demonstrated to be enriched among GWAS hits. GPA can integrate multiple GWAS datasets and functional annotations to seek association signals, and it can also perform hypothesis testing to test the presence of pleiotropy and enrichment of functional annotation. Statistical inference of the model parameters and SNP ranking is achieved through an EM algorithm that can handle genome-wide markers efficiently. When we applied GPA to jointly analyze five psychiatric disorders with annotation information, not only did GPA identify many weak signals missed by the traditional single phenotype analysis, but it also revealed relationships in the genetic architecture of these disorders. Using our hypothesis testing framework, statistically significant pleiotropic effects were detected among these psychiatric disorders, and the markers annotated in the central nervous system genes and eQTLs from the Genotype-Tissue Expression (GTEx) database were significantly enriched. We also applied GPA to a bladder cancer GWAS data set with the ENCODE DNase-seq data from 125 cell lines. GPA was able to detect cell lines that are biologically more relevant to bladder cancer. The R implementation of GPA is currently available at http://dongjunchung.github.io/GPA/.
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NLRP3 Inflammasome Activation Is Essential for Paraquat-Induced Acute Lung Injury.
Inflammation
PUBLISHED: 10-24-2014
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The innate immune response is important in paraquat-induced acute lung injury, but the exact pathways involved are not elucidated. The objectives of this study were to determine the specific role of the NLRP3 inflammasome in the process. Acute lung injury was induced by administering paraquat (PQ) intraperitoneally. NLRP3 inflammasome including NLRP3, ASC, and caspase-1 mRNA and protein expression in lung tissue and IL-1? and IL-18 levels in BALF were detected at 4, 8, 24, and 72 h after PQ administration in rats. Moreover, rats were pretreated with 10, 30, and 50 mg/kg NLRP3 inflammasome blocker glybenclamide, respectively, 1 h before PQ exposure. At 72 h after PQ administration, lung histopathology changes, NLRP3, ASC, and caspase-1 protein expression, as well as secretion of cytokines including IL-1? and IL-18 in BALF were investigated. The NLRP3 inflammasome including NLRP3, ASC, caspase-1 expression, and cytokines IL-1? and IL-18 levels in PQ poisoning rats were significantly higher than that in the control group. NLRP3 inflammasome blocker glybenclamide pretreatment attenuated lung edema, inhibited the NLRP3, ASC, and caspase-1 activation, and reduced IL-1? and IL-18 levels in BALF. In the in vitro experiments, IL-1? and IL-18 secreted from RAW264.7 mouse macrophages treated with paraquat were attenuated by glybenclamide. In conclusion, paraquat can induce IL-1?/IL-18 secretion via NLRP3-ASC-caspase-1 pathway, and the NLRP3 inflammasome is essential for paraquat-induced acute lung injury.
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PI3P phosphatase activity is required for autophagosome maturation and autolysosome formation.
EMBO Rep.
PUBLISHED: 08-14-2014
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Autophagosome formation is promoted by the PI3 kinase complex and negatively regulated by myotubularin phosphatases, indicating that regulation of local phosphatidylinositol 3-phosphate (PtdIns3P) levels is important for this early phase of autophagy. Here, we show that the Caenorhabditis elegans myotubularin phosphatase MTM-3 catalyzes PtdIns3P turnover late in autophagy. MTM-3 acts downstream of the ATG-2/EPG-6 complex and upstream of EPG-5 to promote autophagosome maturation into autolysosomes. MTM-3 is recruited to autophagosomes by PtdIns3P, and loss of MTM-3 causes increased autophagic association of ATG-18 in a PtdIns3P-dependent manner. Our data reveal critical roles of PtdIns3P turnover in autophagosome maturation and/or autolysosome formation.
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Tip-link protein protocadherin 15 interacts with transmembrane channel-like proteins TMC1 and TMC2.
Proc. Natl. Acad. Sci. U.S.A.
PUBLISHED: 08-11-2014
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The tip link protein protocadherin 15 (PCDH15) is a central component of the mechanotransduction complex in auditory and vestibular hair cells. PCDH15 is hypothesized to relay external forces to the mechanically gated channel located near its cytoplasmic C terminus. How PCDH15 is coupled to the transduction machinery is not clear. Using a membrane-based two-hybrid screen to identify proteins that bind to PCDH15, we detected an interaction between zebrafish Pcdh15a and an N-terminal fragment of transmembrane channel-like 2a (Tmc2a). Tmc2a is an ortholog of mammalian TMC2, which along with TMC1 has been implicated in mechanotransduction in mammalian hair cells. Using the above-mentioned two-hybrid assay, we found that zebrafish Tmc1 and Tmc2a can interact with the CD1 or CD3 cytoplasmic domain isoforms of Pcdh15a, and this interaction depends on the common region shared between the two Pcdh15 isoforms. Moreover, an interaction between mouse PCDH15-CD3 and TMC1 or TMC2 was observed in both yeast two-hybrid assays and coimmunoprecipitation experiments. To determine whether the Pcdh15-Tmc interaction is relevant to mechanotransduction in vivo, we overexpressed N-terminal fragments of Tmc2a in zebrafish hair cells. Overexpression of the Tmc2a N terminus results in mislocalization of Pcdh15a within hair bundles, together with a significant decrease in mechanosensitive responses, suggesting that a Pcdh15a-Tmc complex is critical for mechanotransduction. Together, these results identify an evolutionarily conserved association between the fish and mouse orthologs of PCDH15 and TMC1 and TMC2, supporting the notion that TMCs are key components of the transduction complex in hair cells.
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Association of IL-27 polymorphisms and cancer risk in Chinese population.
J. Recept. Signal Transduct. Res.
PUBLISHED: 07-23-2014
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Abstract A number of genetic studies have attempted to link interleukin-27 (IL-27) polymorphisms (rs153109, rs17855750 and rs181206) to the risk of cancer in Chinese population, including glioma, ovarian cancer, hepatocellular carcinoma, colorectal cancer, esophageal cancer, etc. However, the results were inconclusive. The aim of this study is to derive a more precise estimation of any association in a meta-analysis. We searched the PubMed database (up to 6 June 2014) for studies regarding the association of IL-27 polymorphisms (rs153109, rs17855750 and rs181206) and the risk of cancer in Chinese population. Odds ratios (ORs) together with their 95% confidence intervals (CIs) were calculated by using random/fixed effect model to assess the association. Sensitivity analyses were used to assess the stability of the results. Begg's test was performed to measure publication bias. A total of six eligible studies with 1684 patients and 1837 controls were included in this meta-analysis. IL-27 rs153109 polymorphism was significantly associated with cancer risk in Chinese population (GG versus AA: OR?=?1.24, 95% CI?=?1.00-1.54, p?=?0.05). However, there were no associations between IL-27 rs17855750 and rs181206 polymorphisms and cancer risk in Chinese population. In conclusion, this meta-analysis indicated that IL-27 rs153109 polymorphism was associated with cancer risk in Chinese population.
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Genome-Wide Association Study of Copy Number Variations (CNVs) with Opioid Dependence.
Neuropsychopharmacology
PUBLISHED: 07-19-2014
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Single-nucleotide polymorphisms that have been associated with opioid dependence (OD) altogether account for only a small proportion of the known heritability. Most of the genetic risk factors are unknown. Some of the 'missing heritability' might be explained by copy number variations (CNVs) in the human genome. We used Illumina HumanOmni1 arrays to genotype 5152 African-American and European-American OD cases and screened controls and implemented combined CNV calling methods. After quality control measures were applied, a genome-wide association study (GWAS) of CNVs with OD was performed. For common CNVs, two deletions and one duplication were significantly associated with OD genome-wide (eg, P=2 × 10(-8) and OR (95% CI)=0.64 (0.54-0.74) for a chromosome 18q12.3 deletion). Several rare or unique CNVs showed suggestive or marginal significance with large effect sizes. This study is the first GWAS of OD using CNVs. Some identified CNVs harbor genes newly identified here to be of biological importance in addiction, whereas others affect genes previously known to contribute to substance dependence risk. Our findings augment our specific knowledge of the importance of genomic variation in addictive disorders, and provide an addiction CNV pool for further research. These findings require replication.Neuropsychopharmacology advance online publication, 19 November 2014;doi:10.1038/npp.2014.290.
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Unconventional route to encapsulated ultrasmall gold nanoparticles for high-temperature catalysis.
ACS Nano
PUBLISHED: 07-07-2014
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Ultrasmall gold nanoparticles (us-AuNPs, <3 nm) have been recently recognized as surprisingly active and extraordinarily effective green catalysts. Their stability against sintering during reactions, however, remains a serious issue for practical applications. Encapsulating such small nanoparticles in a layer of porous silica can dramatically enhance the stability, but it has been extremely difficult to achieve using conventional sol-gel coating methods due to the weak metal/oxide affinity. In this work, we address this challenge by developing an effective protocol for the synthesis of us-AuNP@SiO2 single-core/shell nanospheres. More specifically, we take an alternative route by starting with ultrasmall gold hydroxide nanoparticles, which have excellent affinity to silica, then carrying out controllable silica coating in reverse micelles, and finally converting gold hydroxide particles into well-protected us-AuNPs. With a single-core/shell configuration that prevents sintering of nearby us-AuNPs and amino group modification of the Au/SiO2 interface that provides additional coordinating interactions, the resulting us-AuNP@SiO2 nanospheres are highly stable at high temperatures and show high activity in catalytic CO oxidation reactions. A dramatic and continuous increase in the catalytic activity has been observed when the size of the us-AuNPs decreases from 2.3 to 1.5 nm, which reflects the intrinsic size effect of the Au nanoparticles on an inert support. The synthesis scheme described in this work is believed to be extendable to many other ultrasmall metal@oxide nanostructures for much broader catalytic applications.
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Incorporating functional annotation information in prioritizing disease associated SNPs from genome wide association studies.
Sci China Life Sci
PUBLISHED: 06-06-2014
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With recent advances in genotyping and sequencing technologies, many disease susceptibility loci have been identified. However, much of the genetic heritability remains unexplained and the replication rate between independent studies is still low. Meanwhile, there have been increasing efforts on functional annotations of the entire human genome, such as the Encyclopedia of DNA Elements (ENCODE) project and other similar projects. It has been shown that incorporating these functional annotations to prioritize genome wide association signals may help identify true association signals. However, to our knowledge, the extent of the improvement when functional annotation data are considered has not been studied in the literature. In this article, we propose a statistical framework to estimate the improvement in replication rate with annotation data, and apply it to Crohn's disease and DNase I hypersensitive sites. The results show that with cell line specific functional annotations, the expected replication rate is improved, but only at modest level.
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Flexible and scalable genotyping-by-sequencing strategies for population studies.
BMC Genomics
PUBLISHED: 05-28-2014
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Many areas critical to agricultural production and research, such as the breeding and trait mapping in plants and livestock, require robust and scalable genotyping platforms. Genotyping-by-sequencing (GBS) is a one such method highly suited to non-human organisms. In the GBS protocol, genomic DNA is fractionated via restriction digest, then reduced representation is achieved through size selection. Since many restriction sites are conserved across a species, the sequenced portion of the genome is highly consistent within a population. This makes the GBS protocol highly suited for experiments that require surveying large numbers of markers within a population, such as those involving genetic mapping, breeding, and population genomics. We have modified the GBS technology in a number of ways. Custom, enzyme specific adaptors have been replaced with standard Illumina adaptors compatible with blunt-end restriction enzymes. Multiplexing is achieved through a dual barcoding system, and bead-based library preparation protocols allows for in-solution size selection and eliminates the need for columns and gels.
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A spatial simulation approach to account for protein structure when identifying non-random somatic mutations.
BMC Bioinformatics
PUBLISHED: 05-27-2014
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Current research suggests that a small set of "driver" mutations are responsible for tumorigenesis while a larger body of "passenger" mutations occur in the tumor but do not progress the disease. Due to recent pharmacological successes in treating cancers caused by driver mutations, a variety of methodologies that attempt to identify such mutations have been developed. Based on the hypothesis that driver mutations tend to cluster in key regions of the protein, the development of cluster identification algorithms has become critical.
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[Comparison of long-term outcomes between Billroth-I( and Roux-en-Y reconstruction after distal gastrectomy].
Zhonghua Wei Chang Wai Ke Za Zhi
PUBLISHED: 05-27-2014
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To compare the long-term outcomes of Billroth-I( and Roux-en-Y reconstruction after distal gastrectomy.
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Differentially co-expressed genes in postmortem prefrontal cortex of individuals with alcohol use disorders: influence on alcohol metabolism-related pathways.
Hum. Genet.
PUBLISHED: 05-24-2014
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Chronic alcohol consumption may induce gene expression alterations in brain reward regions such as the prefrontal cortex (PFC), modulating the risk of alcohol use disorders (AUDs). Transcriptome profiles of 23 AUD cases and 23 matched controls (16 pairs of males and 7 pairs of females) in postmortem PFC were generated using Illumina's HumanHT-12 v4 Expression BeadChip. Probe-level differentially expressed genes and gene modules in AUD subjects were identified using multiple linear regression and weighted gene co-expression network analyses. The enrichment of differentially co-expressed genes in alcohol dependence-associated genes identified by genome-wide association studies (GWAS) was examined using gene set enrichment analysis. Biological pathways overrepresented by differentially co-expressed genes were uncovered using DAVID bioinformatics resources. Three AUD-associated gene modules in males [Module 1 (561 probes mapping to 505 genes): r = 0.42, P(correlation) = 0.020; Module 2 (815 probes mapping to 713 genes): r = 0.41, P(correlation) = 0.020; Module 3 (1,446 probes mapping to 1,305 genes): r = -0.38, P(correlation) = 0.030] and one AUD-associated gene module in females [Module 4 (683 probes mapping to 652 genes): r = 0.64, P(correlation) = 0.010] were identified. Differentially expressed genes mapped by significant expression probes (P(nominal) ? 0.05) clustered in Modules 1 and 2 were enriched in GWAS-identified alcohol dependence-associated genes [Module 1 (134 genes): P = 0.028; Module 2 (243 genes): P = 0.004]. These differentially expressed genes, including ALDH2, ALDH7A1, and ALDH9A1, are involved in cellular functions such as aldehyde detoxification, mitochondrial function, and fatty acid metabolism. Our study revealed differentially co-expressed genes in postmortem PFC of AUD subjects and demonstrated that some of these differentially co-expressed genes participate in alcohol metabolism.
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T cell-intrinsic role of IL-6 signaling in primary and memory responses.
Elife
PUBLISHED: 05-21-2014
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Innate immune recognition is critical for the induction of adaptive immune responses; however the underlying mechanisms remain incompletely understood. In this study, we demonstrate that T cell-specific deletion of the IL-6 receptor ? chain (IL-6R?) results in impaired Th1 and Th17 T cell responses in vivo, and a defect in Tfh function. Depletion of Tregs in these mice rescued the Th1 but not the Th17 response. Our data suggest that IL-6 signaling in effector T cells is required to overcome Treg-mediated suppression in vivo. We show that IL-6 cooperates with IL-1? to block the suppressive effect of Tregs on CD4(+) T cells, at least in part by controlling their responsiveness to IL-2. In addition, although IL-6R?-deficient T cells mount normal primary Th1 responses in the absence of Tregs, they fail to mature into functional memory cells, demonstrating a key role for IL-6 in CD4(+) T cell memory formation.DOI: http://dx.doi.org/10.7554/eLife.01949.001.
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Uncertainty estimation in diffusion MRI using the nonlocal bootstrap.
IEEE Trans Med Imaging
PUBLISHED: 04-29-2014
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In this paper, we propose a new bootstrap scheme, called the nonlocal bootstrap (NLB) for uncertainty estimation. In contrast to the residual bootstrap, which relies on a data model, or the repetition bootstrap, which requires repeated signal measurements, NLB is not restricted by the data structure imposed by a data model and obviates the need for time-consuming multiple acquisitions. NLB hinges on the observation that local imaging information recurs in an image. This self-similarity implies that imaging information coming from spatially distant (nonlocal) regions can be exploited for more effective estimation of statistics of interest. Evaluations using in silico data indicate that NLB produces distribution estimates that are in closer agreement with those generated using Monte Carlo simulations, compared with the conventional residual bootstrap. Evaluations using in vivo data demonstrate that NLB produces results that are in agreement with our knowledge on white matter architecture.
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Novel genetic variants modify the effect of smoking on carotid plaque burden in Hispanics.
J. Neurol. Sci.
PUBLISHED: 04-15-2014
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Smoking greatly increases the risk of atherosclerotic plaque and the effect may vary from individual to individual. A genome-wide scan was performed for smoking×single nucleotide polymorphism (SNP) interactions on carotid plaque burden (CPB) to identify the potential genetic moderators in Hispanics.
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The genetics of functional disability in schizophrenia and bipolar illness: Methods and initial results for VA cooperative study #572.
Am. J. Med. Genet. B Neuropsychiatr. Genet.
PUBLISHED: 04-15-2014
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Given the prominence of cognitive impairments and disability associated with schizophrenia and bipolar disorder, substantial interest has arisen in identifying determinants of the diseases and their features. Genetic variation has been linked to skills that underlie disability ("functional capacity" or FC), highlighting need for understanding of these relationships. We describe the design and methods of a large, multisite, observational study focusing on the genetics of functional disability in schizophrenia and bipolar disorder, presenting initial data on recruitment, and characterization of the sample. Known as Veterans Affairs (VA) Cooperative Studies Program (CSP)#572, this study is recruiting, diagnosing, and assessing U.S. Veterans with either schizophrenia or bipolar I disorder. Assessments include neuropsychological (NP) testing, FC, suicidality, and co-morbid conditions such as posttraumatic stress disorder (PTSD). A sample of "psychiatrically healthy" Veterans from another project serves as a comparison group. An interim total of 8,140 participants (42.1% schizophrenia) have been recruited and assessed as of September 30, 2013, with 9 months of enrollment remaining and with a target sample size of 9,500. Veterans with schizophrenia were more likely to never have married, whereas lifetime PTSD and suicidality were more common in the bipolar veterans. Performance on the FC measures and NP tests was consistent with previous results, with mean t-scores of 35 (-1.5?SD) for schizophrenia and 41 (-0.9?SD) for the bipolar Veterans. This large population is representative of previous studies in terms of patient performance and co-morbidities. Subsequent genomic analyses will examine the genomic correlates of performance-based measures. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.
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OsCYCP1;1, a PHO80 homologous protein, negatively regulates phosphate starvation signaling in the roots of rice (Oryza sativa L.).
Plant Mol. Biol.
PUBLISHED: 04-10-2014
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Phosphorus is one of the most essential and limiting nutrients in all living organisms, thus the organisms have evolved complicated and precise regulatory mechanisms for phosphorus acquisition, storage and homeostasis. In the budding yeast, Saccharomyces cerevisiae, the modification of PHO4 by the PHO80 and PHO85 complex is a core regulation system. However, the existence and possible functions in phosphate signaling of the homologs of the PHO80 and PHO85 components in plants has yet to be determined. Here we describe the identification of a family of seven PHO80 homologous genes in rice named OsCYCPs. Among these, the OsCYCP1;1 gene was able to partially rescue the pho80 mutant strain of yeast. The OsCYCP1;1 protein was predominantly localized in the nucleus, and was ubiquitously expressed throughout the whole plant and during the entire growth period of rice. Consistent with the negative role of PHO80 in phosphate signaling in yeast, OsCYCP1;1 expression was reduced by phosphate starvation in the roots. This reduction was dependent on PHR2, the central regulator of phosphate signaling in rice. Overexpression and suppression of the expression of OsCYCP1;1 influenced the phosphate starvation signaling response. The inducible expression of phosphate starvation inducible and phosphate transporter genes was suppressed in the OsCYCP1;1 overexpression lines and was relatively enhanced in the OsCYCP1;1 RNAi plants by phosphate starvation. Together, these results demonstrate the role of PHO80 homologs in the phosphate starvation signaling pathway in rice.
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Imaging Oxygen Metabolism In Acute Stroke Using MRI.
Curr Radiol Rep
PUBLISHED: 04-08-2014
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The ability to image the ischemic penumbra during hyper-acute stroke promises to identify patients who may benefit from treatment intervention beyond population-defined therapeutic time windows. MR blood oxygenation level dependent (BOLD) contrast imaging has been explored in ischemic stroke. This review provides an overview of several BOLD-based methods, including susceptibility weighted imaging (SWI), R2, R2*, R2', R2* under oxygen challenge, MR_OEF and MROMI approaches to assess cerebral oxygen metabolism in ischemic stroke. We will review the underlying pathophysiological basis of the imaging approaches, followed by a brief introduction of BOLD contrast. Finally, we will discuss the applications of the BOLD approaches in patients with ischemic stroke. BOLD-based methods hold promise for imaging tissue oxygenation during acute ischemia. Further technical refinement and validation studies in stroke patients against positron emission tomography (PET) measurements are needed.
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Valproic acid protects septic mice from renal injury by reducing the inflammatory response.
J. Surg. Res.
PUBLISHED: 03-28-2014
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Valproic acid (VPA), a histone deacetylase inhibitor, has extensive activities against inflammation, oxidation, and malignancy. This study was designed to investigate the protective effect of VPA on the systemic inflammatory response and renal injury in septic mice.
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An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge.
Catherine A Brownstein, Alan H Beggs, Nils Homer, Barry Merriman, Timothy W Yu, Katherine C Flannery, Elizabeth T DeChene, Meghan C Towne, Sarah K Savage, Emily N Price, Ingrid A Holm, Lovelace J Luquette, Elaine Lyon, Joseph Majzoub, Peter Neupert, David McCallie, Peter Szolovits, Huntington F Willard, Nancy J Mendelsohn, Renee Temme, Richard S Finkel, Sabrina W Yum, Livija Medne, Shamil R Sunyaev, Ivan Adzhubey, Christopher A Cassa, Paul I W de Bakker, Hatice Duzkale, Piotr Dworzynski, William Fairbrother, Laurent Francioli, Birgit H Funke, Monica A Giovanni, Robert E Handsaker, Kasper Lage, Matthew S Lebo, Monkol Lek, Ignaty Leshchiner, Daniel G MacArthur, Heather M McLaughlin, Michael F Murray, Tune H Pers, Paz P Polak, Soumya Raychaudhuri, Heidi L Rehm, Rachel Soemedi, Nathan O Stitziel, Sara Vestecka, Jochen Supper, Claudia Gugenmus, Bernward Klocke, Alexander Hahn, Max Schubach, Mortiz Menzel, Saskia Biskup, Peter Freisinger, Mario Deng, Martin Braun, Sven Perner, Richard J H Smith, Janeen L Andorf, Jian Huang, Kelli Ryckman, Val C Sheffield, Edwin M Stone, Thomas Bair, E Ann Black-Ziegelbein, Terry A Braun, Benjamin Darbro, Adam P DeLuca, Diana L Kolbe, Todd E Scheetz, Aiden E Shearer, Rama Sompallae, Kai Wang, Alexander G Bassuk, Erik Edens, Katherine Mathews, Steven A Moore, Oleg A Shchelochkov, Pamela Trapane, Aaron Bossler, Colleen A Campbell, Jonathan W Heusel, Anne Kwitek, Tara Maga, Karin Panzer, Thomas Wassink, Douglas Van Daele, Hela Azaiez, Kevin Booth, Nic Meyer, Michael M Segal, Marc S Williams, Gerard Tromp, Peter White, Donald Corsmeier, Sara Fitzgerald-Butt, Gail Herman, Devon Lamb-Thrush, Kim L McBride, David Newsom, Christopher R Pierson, Alexander T Rakowsky, Ales Maver, Luca Lovrecic, Anja Palandačić, Borut Peterlin, Ali Torkamani, Anna Wedell, Mikael Huss, Andrey Alexeyenko, Jessica M Lindvall, Måns Magnusson, Daniel Nilsson, Henrik Stranneheim, Fulya Taylan, Christian Gilissen, Alexander Hoischen, Bregje Van Bon, Helger Yntema, Marcel Nelen, Weidong Zhang, Jason Sager, Lu Zhang, Kathryn Blair, Deniz Kural, Michael Cariaso, Greg G Lennon, Asif Javed, Saloni Agrawal, Pauline C Ng, Komal S Sandhu, Shuba Krishna, Vamsi Veeramachaneni, Ofer Isakov, Eran Halperin, Eitan Friedman, Noam Shomron, Gustavo Glusman, Jared C Roach, Juan Caballero, Hannah C Cox, Denise Mauldin, Seth A Ament, Lee Rowen, Daniel R Richards, F Anthony San Lucas, Manuel L Gonzalez-Garay, C Thomas Caskey, Yu Bai, Ying Huang, Fang Fang, Yan Zhang, Zhengyuan Wang, Jorge Barrera, Juan M García-Lobo, Domingo González-Lamuño, Javier Llorca, María C Rodriguez, Ignacio Varela, Martin G Reese, Francisco M De La Vega, Edward Kiruluta, Michele Cargill, Reece K Hart, Jon M Sorenson, Gholson J Lyon, David A Stevenson, Bruce E Bray, Barry M Moore, Karen Eilbeck, Mark Yandell, Hongyu Zhao, Lin Hou, Xiaowei Chen, Xiting Yan, Mengjie Chen, Cong Li, Can Yang, Murat Günel, Peining Li, Yong Kong, Austin C Alexander, Zayed I Albertyn, Kym M Boycott, Dennis E Bulman, Paul M K Gordon, A Micheil Innes, Bartha M Knoppers, Jacek Majewski, Christian R Marshall, Jillian S Parboosingh, Sarah L Sawyer, Mark E Samuels, Jeremy Schwartzentruber, Isaac S Kohane, David M Margulies.
Genome Biol.
PUBLISHED: 03-25-2014
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There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance.
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Data Pre-Processing for Label-Free Multiple Reaction Monitoring (MRM) Experiments.
Biology (Basel)
PUBLISHED: 03-17-2014
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Multiple Reaction Monitoring (MRM) conducted on a triple quadrupole mass spectrometer allows researchers to quantify the expression levels of a set of target proteins. Each protein is often characterized by several unique peptides that can be detected by monitoring predetermined fragment ions, called transitions, for each peptide. Concatenating large numbers of MRM transitions into a single assay enables simultaneous quantification of hundreds of peptides and proteins. In recognition of the important role that MRM can play in hypothesis-driven research and its increasing impact on clinical proteomics, targeted proteomics such as MRM was recently selected as the Nature Method of the Year. However, there are many challenges in MRM applications, especially data pre?processing where many steps still rely on manual inspection of each observation in practice. In this paper, we discuss an analysis pipeline to automate MRM data pre?processing. This pipeline includes data quality assessment across replicated samples, outlier detection, identification of inaccurate transitions, and data normalization. We demonstrate the utility of our pipeline through its applications to several real MRM data sets.
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A graph theoretic approach to utilizing protein structure to identify non-random somatic mutations.
BMC Bioinformatics
PUBLISHED: 03-11-2014
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It is well known that the development of cancer is caused by the accumulation of somatic mutations within the genome. For oncogenes specifically, current research suggests that there is a small set of "driver" mutations that are primarily responsible for tumorigenesis. Further, due to recent pharmacological successes in treating these driver mutations and their resulting tumors, a variety of approaches have been developed to identify potential driver mutations using methods such as machine learning and mutational clustering. We propose a novel methodology that increases our power to identify mutational clusters by taking into account protein tertiary structure via a graph theoretical approach.
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CB2 receptor activation ameliorates the proinflammatory activity in acute lung injury induced by paraquat.
Biomed Res Int
PUBLISHED: 03-08-2014
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Paraquat, a widely used herbicide, is well known to exhibit oxidative stress and lung injury. In the present study, we investigated the possible underlying mechanisms of cannabinoid receptor-2 (CB2) activation to ameliorate the proinflammatory activity induced by PQ in rats. JWH133, a CB2 agonist, was administered by intraperitoneal injection 1 h prior to PQ exposure. After PQ exposure for 4, 8, 24, and 72 h, the bronchoalveolar lavage fluid was collected to determine levels of TNF-? and IL-1?, and the arterial blood samples were collected for detection of PaO2 level. At 72 h after PQ exposure, lung tissues were collected to determine the lung wet-to-dry weight ratios, myeloperoxidase activity, lung histopathology, the protein expression level of CB2, MAPKs (ERK1/2, p38MAPK, and JNK1/2), and NF-?Bp65. After rats were pretreated with JWH133, PQ-induced lung edema and lung histopathological changes were significantly attenuated. PQ-induced TNF-? and IL-1? secretion in BALF, increases of PaO2 in arterial blood, and MPO levels in the lung tissue were significantly reduced. JWH133 could efficiently activate CB2, while inhibiting MAPKs and NF-?B activation. The results suggested that activating CB2 receptor exerted protective activity against PQ-induced ALI, and it potentially contributed to the suppression of the activation of MAPKs and NF-?B pathways.
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Identification of methylation quantitative trait loci (mQTLs) influencing promoter DNA methylation of alcohol dependence risk genes.
Hum. Genet.
PUBLISHED: 03-04-2014
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Interaction of DNA methylation and sequence variants that are methylation quantitative trait loci (mQTLs) may influence susceptibility to diseases such as alcohol dependence (AD). We used genome-wide genotype data from 268 African Americans (AAs: 129 AD cases and 139 controls) and 143 European Americans (EAs: 129 AD cases and 14 controls) to identify mQTLs that were associated with promoter CpGs in 82 AD risk genes. 282 significant mQTL-CpG pairs (9.9 × 10(-100) ? P(nominal) ? 7.7 × 10(-8)) in AAs and 313 significant mQTL-CpG pairs (2.7 × 10(-53) ? P(nominal) ? 9.9 × 10(-8)) in EAs were identified [i.e., mQTL-CpG associations survived multiple-testing correction, q values (false discovery rate) ? 0.05]. The most significant mQTL was rs1800759, which was strongly associated with CpG cg12011299 in both AAs (P(nominal) = 9.9 × 10(-100); q = 6.7 × 10(-91)) and EAs (P(nominal) = 2.7 × 10(-53); q = 1.4 × 10(-44)). Rs1800759 (previously known to be associated to AD) and CpG cg12011299 (distance: 37 bp) are both located in alcohol dehydrogenase (ADH) 4 gene (ADH4) promoter region. In general, the strength of association between mQTLs and CpGs was inversely correlated with the distance between them. Association was also influenced by race and AD. Additionally, 48.3 % of the mQTLs identified in AAs and 65.6 % of the mQTLs identified in EAs were predicted to be expression QTLs. Three mQTLs (rs2173201, rs4147542, and rs4147541 in ADH1B-AHD1C gene cluster region) found in AAs were previously identified by our genome-wide association studies as being significantly associated with AD in AAs. Thus, DNA methylation, which can be influenced by sequence variants and is implicated in gene expression regulation, appears to at least partially underlie the association of genetic variation with AD.
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Divergence in a master variator generates distinct phenotypes and transcriptional responses.
Genes Dev.
PUBLISHED: 02-18-2014
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Genetic basis of phenotypic differences in individuals is an important area in biology and personalized medicine. Analysis of divergent Saccharomyces cerevisiae strains grown under different conditions revealed extensive variation in response to both drugs (e.g., 4-nitroquinoline 1-oxide [4NQO]) and different carbon sources. Differences in 4NQO resistance were due to amino acid variation in the transcription factor Yrr1. Yrr1(YJM789) conferred 4NQO resistance but caused slower growth on glycerol, and vice versa with Yrr1(S96), indicating that alleles of Yrr1 confer distinct phenotypes. The binding targets of Yrr1 alleles from diverse yeast strains varied considerably among different strains grown under the same conditions as well as for the same strain under different conditions, indicating that distinct molecular programs are conferred by the different Yrr1 alleles. Our results demonstrate that genetic variations in one important control gene (YRR1), lead to distinct regulatory programs and phenotypes in individuals. We term these polymorphic control genes "master variators."
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Identifying gene-environment and gene-gene interactions using a progressive penalization approach.
Genet. Epidemiol.
PUBLISHED: 02-08-2014
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In genomic studies, identifying important gene-environment and gene-gene interactions is a challenging problem. In this study, we adopt the statistical modeling approach, where interactions are represented by product terms in regression models. For the identification of important interactions, we adopt penalization, which has been used in many genomic studies. Straightforward application of penalization does not respect the "main effect, interaction" hierarchical structure. A few recently proposed methods respect this structure by applying constrained penalization. However, they demand very complicated computational algorithms and can only accommodate a small number of genomic measurements. We propose a computationally fast penalization method that can identify important gene-environment and gene-gene interactions and respect a strong hierarchical structure. The method takes a stagewise approach and progressively expands its optimization domain to account for possible hierarchical interactions. It is applicable to multiple data types and models. A coordinate descent method is utilized to produce the entire regularized solution path. Simulation study demonstrates the superior performance of the proposed method. We analyze a lung cancer prognosis study with gene expression measurements and identify important gene-environment interactions.
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Extensive sequence variation in the 3' untranslated region of the KRAS gene in lung and ovarian cancer cases.
Cell Cycle
PUBLISHED: 02-03-2014
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While cancer is a serious health issue, there are very few genetic biomarkers that predict predisposition, prognosis, diagnosis, and treatment response. Recently, sequence variations that disrupt microRNA (miRNA)-mediated regulation of genes have been shown to be associated with many human diseases, including cancer. In an early example, a variant at one particular single nucleotide polymorphism (SNP) in a let-7 miRNA complementary site in the 3' untranslated region (3' UTR) of the KRAS gene was associated with risk and outcome of various cancers. The KRAS oncogene is an important regulator of cellular proliferation, and is frequently mutated in cancers. To discover additional sequence variants in the 3' UTR of KRAS with the potential as genetic biomarkers, we resequenced the complete region of the 3' UTR of KRAS in multiple non-small cell lung cancer and epithelial ovarian cancer cases either by Sanger sequencing or capture enrichment followed by high-throughput sequencing. Here we report a comprehensive list of sequence variations identified in cases, with some potentially dysregulating expression of KRAS by altering putative miRNA complementary sites. Notably, rs712, rs9266, and one novel variant may have a functional role in regulation of KRAS by disrupting complementary sites of various miRNAs, including let-7 and miR-181.
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Signaling through the adaptor molecule MyD88 in CD4+ T cells is required to overcome suppression by regulatory T cells.
Immunity
PUBLISHED: 01-21-2014
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Innate immune recognition controls adaptive immune responses through multiple mechanisms. The MyD88 signaling adaptor operates in many cell types downstream of Toll-like receptors (TLRs) and interleukin-1 (IL-1) receptor family members. Cell-type-specific functions of MyD88 signaling remain poorly characterized. Here, we have shown that the T cell-specific ablation of MyD88 in mice impairs not only T helper 17 (Th17) cell responses, but also Th1 cell responses. MyD88 relayed signals of TLR-induced IL-1, which became dispensable for Th1 cell responses in the absence of T regulatory (Treg) cells. Treg cell-specific ablation of MyD88 had no effect, suggesting that IL-1 acts on naive CD4(+) T cells instead of Treg cells themselves. Together, these findings demonstrate that IL-1 renders naive CD4(+) T cells refractory to Treg cell-mediated suppression in order to allow their differentiation into Th1 cells. In addition, IL-1 was also important for the generation of functional CD4(+) memory T cells.
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Cytogenomic mapping and bioinformatic mining reveal interacting brain expressed genes for intellectual disability.
Mol Cytogenet
PUBLISHED: 01-10-2014
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Microarray analysis has been used as the first-tier genetic testing to detect chromosomal imbalances and copy number variants (CNVs) for pediatric patients with intellectual and developmental disabilities (ID/DD). To further investigate the candidate genes and underlying dosage-sensitive mechanisms related to ID, cytogenomic mapping of critical regions and bioinformatic mining of candidate brain-expressed genes (BEGs) and their functional interactions were performed. Critical regions of chromosomal imbalances and pathogenic CNVs were mapped by subtracting known benign CNVs from the Databases of Genomic Variants (DGV) and extracting smallest overlap regions with cases from DatabasE of Chromosomal Imbalance and Phenotype in Humans using Ensembl Resources (DECIPHER). BEGs from these critical regions were revealed by functional annotation using Database for Annotation, Visualization, and Integrated Discovery (DAVID) and by tissue expression pattern from Uniprot. Cross-region interrelations and functional networks of the BEGs were analyzed using Gene Relationships Across Implicated Loci (GRAIL) and Ingenuity Pathway Analysis (IPA).
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Rare deleterious mutations of the gene EFR3A in autism spectrum disorders.
Mol Autism
PUBLISHED: 01-01-2014
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Whole-exome sequencing studies in autism spectrum disorder (ASD) have identified de novo mutations in novel candidate genes, including the synaptic gene Eighty-five Requiring 3A (EFR3A). EFR3A is a critical component of a protein complex required for the synthesis of the phosphoinositide PtdIns4P, which has a variety of functions at the neural synapse. We hypothesized that deleterious mutations in EFR3A would be significantly associated with ASD.
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Characterization of multidrug-resistant Salmonella enterica serovars Indiana and Enteritidis from chickens in Eastern China.
PLoS ONE
PUBLISHED: 01-01-2014
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A total of 310 Salmonella isolates were isolated from 6 broiler farms in Eastern China, serotyped according to the Kauffmann-White classification. All isolates were examined for susceptibility to 17 commonly used antimicrobial agents, representative isolates were examined for resistance genes and class I integrons using PCR technology. Clonality was determined by pulsed-field gel electrophoresis (PFGE). There were two serotypes detected in the 310 Salmonella strains, which included 133 Salmonella enterica serovar Indiana isolates and 177 Salmonella enterica serovar Enteritidis isolates. Antimicrobial sensitivity results showed that the isolates were generally resistant to sulfamethoxazole, ampicillin, tetracycline, doxycycline and trimethoprim, and 95% of the isolates sensitive to amikacin and polymyxin. Among all Salmonella enterica serovar Indiana isolates, 108 (81.2%) possessed the blaTEM, floR, tetA, strA and aac (6')-Ib-cr resistance genes. The detected carriage rate of class 1 integrons was 66.5% (206/310), with 6 strains carrying gene integron cassette dfr17-aadA5. The increasing frequency of multidrug resistance rate in Salmonella was associated with increasing prevalence of int1 genes (rs = 0.938, P = 0.00039). The int1, blaTEM, floR, tetA, strA and aac (6')-Ib-cr positive Salmonella enterica serovar Indiana isolates showed five major patterns as determined by PFGE. Most isolates exhibited the common PFGE patterns found from the chicken farms, suggesting that many multidrug-resistant isolates of Salmonella enterica serovar Indiana prevailed in these sources. Some isolates with similar antimicrobial resistance patterns represented a variety of Salmonella enterica serovar Indiana genotypes, and were derived from a different clone.
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Guilt by Rewiring: Gene Prioritization through Network Rewiring in Genome Wide Association Studies.
Hum. Mol. Genet.
PUBLISHED: 12-30-2013
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Although Genome Wide Association Studies (GWAS) have identified many susceptibility loci for common diseases, they only explain a small portion of heritability. It is challenging to identify the remaining disease loci because their association signals are likely weak and difficult to identify among millions of candidates. One potentially useful direction to increase statistical power is to incorporate functional genomics information, especially gene expression networks, to prioritize GWAS signals. Most current methods utilizing network information to prioritize disease genes are based on the "guilt by association" principle, in which networks are treated as static, and disease associated genes are assumed to locate closer with each other than random pairs in the network. In contrast, we propose a novel "guilt by rewiring" principle. Studying the dynamics of gene networks between controls and patients, this principle assumes that disease genes more likely undergo rewiring in patients, whereas most of the network remains unaffected in disease condition. To demonstrate this principle, we consider the changes of co-expression networks in Crohns disease patients and controls, and how network dynamics reveals information on disease associations. Our results demonstrate that network rewiring is abundant in the immune system, and disease associated genes are more likely to be rewired in patients. To integrate this network rewiring feature and GWAS signals, we propose to use the Markov random field framework to integrate network information to prioritize genes. Applications in Crohns disease and Parkinsons disease show that this framework leads to more replicable results, and implicates potentially disease associated pathways.
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Genome-Wide Interaction Study Identifies RCBTB1 as a Modifier for Smoking Effect on Carotid Intima-Media Thickness.
Arterioscler. Thromb. Vasc. Biol.
PUBLISHED: 11-07-2013
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Carotid intima-media thickness (cIMT), a marker for atherosclerosis, is affected by smoking and has substantial interindividual variation. We sought to identify the genetic moderators influencing the effect of smoking on cIMT.
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Allergic conditions reduce the risk of glioma: a meta-analysis based on 128,936 subjects.
Tumour Biol.
PUBLISHED: 11-03-2013
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Many studies have investigated the association between the allergic conditions and the risk of glioma. However, the evidence is inadequate to draw robust conclusions because most studies were generally small and conducted in heterogeneous populations. To shed light on these inconclusive findings, we conducted a meta-analysis of studies relating the allergic conditions to the risk of glioma. We identified the relevant studies by searching ISI Web of Science, PubMed, EMBASE, Chinese National Knowledge Infrastructure (CNKI) databases, and Wanfang database by October 2013. We included studies that reported odds ratio (OR) or hazard ratio (HR) with its 95 % confidence interval (CI) for the association between the allergic condition and the risk of glioma. Eighteen independent publications, with 9,986 glioma cases and 118,950 controls, were included. Our results showed that allergic condition was reversely associated with the risk of glioma (OR?=?0.78, 95 % CI 0.73-0.83, P?
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Estimating the Proportion of True Null Hypotheses Using the Pattern of Observed p-values.
J Appl Stat
PUBLISHED: 10-01-2013
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Estimating the proportion of true null hypotheses, ?0, has attracted much attention in the recent statistical literature. Besides its apparent relevance for a set of specific scientific hypotheses, an accurate estimate of this parameter is key for many multiple testing procedures. Most existing methods for estimating ?0 in the literature are motivated from the independence assumption of test statistics, which is often not true in reality. Simulations indicate that most existing estimators in the presence of the dependence among test statistics can be poor, mainly due to the increase of variation in these estimators. In this paper, we propose several data-driven methods for estimating ?0 by incorporating the distribution pattern of the observed p-values as a practical approach to address potential dependence among test statistics. Specifically, we use a linear fit to give a data-driven estimate for the proportion of true-null p-values in (?, 1] over the whole range [0, 1] instead of using the expected proportion at 1 - ?. We find that the proposed estimators may substantially decrease the variance of the estimated true null proportion and thus improve the overall performance.
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The co-occurrence of risk alleles in or near genes modulating insulin secretion predisposes obese youth to prediabetes.
Diabetes Care
PUBLISHED: 09-23-2013
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Background and aimsParalleling the rise of pediatric obesity, the prevalence of impaired glucose tolerance (IGT) and type 2 diabetes (T2D) is increasing among youths. In this study we asked whether the co-occurrence of risk alleles in or near 5 genes modulating insulin secretion (TCF7L2 rs7903146, IGF2BP2 rs4402960, CDKAL1 rs7754840, HHEX rs1111875, and HNF1A rs1169288) is associated with a higher risk of IGT/ T2D in obese children and adolescents.MethodsWe studied 714 obese subjects (290 boys and 424 girls; mean age 13.6±3.1 years; mean z-score BMI 2.2±0.4), evaluated the insulin secretion by using the oral minimal model and, in a subgroup of 37 subjects, the hyperglycemic clamp. Also, 203 were followed-up for a mean of 2.1 years.ResultsWe observed that the increase of risk alleles was associated with a progressive worsening of insulin secretion (P<.001) mainly due to an impairment of the dynamic phase of insulin secretion (p=0.004). The higher was the number of the risk alleles the higher was the chance of progression from NGT to IGT/T2D (p=0.022), also for those who were IGT at baseline, a higher risk score was associated with a lower odds to revert to NGT (p=0.026).ConclusionObese children and adolescents developing IGT/T2D have a higher genetic predisposition than those who do not show these diseases and this predisposition is mainly related to gene variants modulating the early phase of insulin secretion. Although these data are very interesting, they need to be replicated in other cohorts.
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HUMAN IMPACTS HAVE SHAPED HISTORICAL AND RECENT EVOLUTION IN AEDES AEGYPTI, THE DENGUE AND YELLOW FEVER MOSQUITO.
Evolution
PUBLISHED: 09-20-2013
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Though anthropogenic impacts are often considered harmful to species, human modifications to the landscape can actually create novel niches to which other species can adapt. These "domestication" processes are especially important in the context of arthropod disease vectors, where ecological overlap of vector and human populations may lead to epidemics. Here, we present results of a global genetic study of one such species, the dengue and yellow fever mosquito, Aedes aegypti, whose evolutionary history and current distribution have been profoundly shaped by humans. We used DNA sequences of four nuclear genes and 1504 SNP markers developed with RAD-tag sequencing to test the hypothesis that Ae. aegypti originated in Africa, where a domestic form arose and spread throughout the tropical and subtropical world with human trade and movement. Results confirmed African ancestry of the species, and supported a single subspeciation event leading to the pantropical domestic form. Additionally, genetic data strongly supported the hypothesis that human trade routes first moved domestic Ae. aegypti out of Africa into the New World, followed by a later invasion from the New World into Southeast Asia and the Pacific. These patterns of domestication and invasion are relevant to many species worldwide, as anthropogenic forces increasingly impact evolutionary processes. This article is protected by copyright. All rights reserved.
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Exploring the genetic architecture of alcohol dependence in African-Americans via analysis of a genomewide set of common variants.
Hum. Genet.
PUBLISHED: 09-17-2013
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Alcohol dependence (AD) is a complex psychiatric disorder that affects about 12.5 % of US adults. Genetic factors play a major role in the development of AD. We conducted a genomewide association study in 2,875 African-Americans including 1,719 AD cases and 1,156 controls. We used the Illumina Omni 1-Quad microarray, which yielded 769,498 single-nucleotide polymorphisms (SNPs) after quality control. To explore the genetic architecture of AD, we estimated the variance that could be explained by all SNPs and subsets of SNPs using two different approaches to genome partitioning. We found that 23.9 % (s.e. 9.3 %) of the phenotypic variance could be explained by using all of the common SNPs on the array. We also found a significant linear relationship between the proportion of the top SNPs used and the phenotypic variance explained by them. Based on genome partitioning of common variants, we also observed a significant linear relationship between the variance explained by a chromosome and its length. Chromosome 4, known to contain several AD risk genes, accounted for excess risk in proportion to its length. By functional partitioning, we found that the genetic variants within 20 kb of genes explained 17.5 % (s.e. 11.4 %) of the phenotypic variance. Our findings are consistent with the generally accepted view that AD is a highly polygenic trait, i.e., the genetic risk in AD appears to be conferred by multiple variants, each of which may have a small or moderate effect.
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[FEA technology applied in the design of CT table].
Zhongguo Yi Liao Qi Xie Za Zhi
PUBLISHED: 09-11-2013
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In this paper, we develop a method to build FEA model, boundary conditions and to analyse static strength and rigidity of the object based on the CT patient table. Especially to introduce the examples of how to simplify the actual models to ideal models which can easily add some loads. In the end of the paper, we compare the results analysis of FEA with the results of experiment and we confirm the high accuracy of FEA, so we summarize that FEA technology is very important for the development of medical equipments.
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Statistical properties on semiparametric regression for evaluating pathway effects.
J Stat Plan Inference
PUBLISHED: 09-10-2013
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Most statistical methods for microarray data analysis consider one gene at a time, and they may miss subtle changes at the single gene level. This limitation may be overcome by considering a set of genes simultaneously where the gene sets are derived from prior biological knowledge. We call a pathway as a predefined set of genes that serve a particular cellular or physiological function. Limited work has been done in the regression settings to study the effects of clinical covariates and expression levels of genes in a pathway on a continuous clinical outcome. A semiparametric regression approach for identifying pathways related to a continuous outcome was proposed by Liu et al. (2007), who demonstrated the connection between a least squares kernel machine for nonparametric pathway effect and a restricted maximum likelihood (REML) for variance components. However, the asymptotic properties on a semiparametric regression for identifying pathway have never been studied. In this paper, we study the asymptotic properties of the parameter estimates on semiparametric regression and compare Liu et al.s REML with our REML obtained from a profile likelihood. We prove that both approaches provide consistent estimators, have [Formula: see text] convergence rate under regularity conditions, and have either an asymptotically normal distribution or a mixture of normal distributions. However, the estimators based on our REML obtained from a profile likelihood have a theoretically smaller mean squared error than those of Liu et al.s REML. Simulation study supports this theoretical result. A profile restricted likelihood ratio test is also provided for the non-standard testing problem. We apply our approach to a type II diabetes data set (Mootha et al., 2003).
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No association between polymorphisms in the calcium homeostasis modulator 1 gene and mesial temporal lobe epilepsy risk in a Chinese population.
Seizure
PUBLISHED: 08-29-2013
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Mesial temporal lobe epilepsy (MTLE) is one of the most common forms of epilepsies in adults. The calcium homeostasis modulator 1 gene (CALHM1) has been considered one of the candidate genes that play a role in epileptogenesis due to its function in calcium homeostasis and amyloid ? (A?) regulation. Recently, the association of a single nucleotide polymorphism (rs11191692) of CALHM1 has been reported to be associated with MTLE in Han Chinese, but independent replication is needed. In the present study, rs11191692 and rs2986017 of CALHM1 were determined in 512 MTLE patients and 412 control subjects to investigate the possible involvement of CALHM1 in the etiology of MTLE.
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Association of Gamma-Aminobutyric Acid A Receptor ?2 Gene (GABRA2) with Alcohol Use Disorder.
Neuropsychopharmacology
PUBLISHED: 08-27-2013
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Gamma-aminobutyric acid (GABA) is a major inhibitory neurotransmitter in mammalian brain. GABA receptor are involved in a number of complex disorders, including substance abuse. No variants of the commonly studied GABA receptor genes that have been associated with substance dependence have been determined to be functional or pathogenic. To reconcile the conflicting associations with substance dependence traits, we performed a meta-analysis of variants in the GABAA receptor genes (GABRB2, GABRA6, GABRA1, and GABRG2 on chromosome 5q and GABRA2 on chromosome 4p12) using genotype data from 4739 cases of alcohol, opioid, or methamphetamine dependence and 4924 controls. Then, we combined the data from candidate gene association studies in the literature with two alcohol dependence (AD) samples, including 1691 cases and 1712 controls from the Study of Addiction: Genetics and Environment (SAGE), and 2644 cases and 494 controls from our own study. Using a Bonferroni-corrected threshold of 0.007, we found strong associations between GABRA2 and AD (P=9 × 10(-6) and odds ratio (OR) 95% confidence interval (CI)=1.27 (1.15, 1.4) for rs567926, P=4 × 10(-5) and OR=1.21 (1.1, 1.32) for rs279858), and between GABRG2 and both dependence on alcohol and dependence on heroin (P=0.0005 and OR=1.22 (1.09, 1.37) for rs211014). Significant association was also observed between GABRA6 rs3219151 and AD. The GABRA2 rs279858 association was observed in the SAGE data sets with a combined P of 9 × 10(-6) (OR=1.17 (1.09, 1.26)). When all of these data sets, including our samples, were meta-analyzed, associations of both GABRA2 single-nucleotide polymorphisms remained (for rs567926, P=7 × 10(-5) (OR=1.18 (1.09, 1.29)) in all the studies, and P=8 × 10(-6) (OR=1.25 (1.13, 1.38)) in subjects of European ancestry and for rs279858, P=5 × 10(-6) (OR=1.18 (1.1, 1.26)) in subjects of European ancestry. Findings from this extensive meta-analysis of five GABAA receptor genes and substance abuse support their involvement (with the best evidence for GABRA2) in the pathogenesis of AD. Further replications with larger samples are warranted.Neuropsychopharmacology advance online publication, 13 November 2013; doi:10.1038/npp.2013.291.
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Integrating GWASs and Human Protein Interaction Networks Identifies a Gene Subnetwork Underlying Alcohol Dependence.
Am. J. Hum. Genet.
PUBLISHED: 08-14-2013
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Despite a significant genetic contribution to alcohol dependence (AD), few AD-risk genes have been identified to date. In the current study, we aimed to integrate genome-wide association studies (GWASs) and human protein interaction networks to investigate whether a subnetwork of genes whose protein products interact with one another might collectively contribute to AD. By using two discovery GWAS data sets of the Study of Addiction: Genetics and Environment (SAGE) and the Collaborative Study on the Genetics of Alcoholism (COGA), we identified a subnetwork of 39 genes that not only was enriched for genes associated with AD, but also collectively associated with AD in both European Americans (p < 0.0001) and African Americans (p = 0.0008). We replicated the association of the gene subnetwork with AD in three independent samples, including two samples of European descent (p = 0.001 and p = 0.006) and one sample of African descent (p = 0.0069). To evaluate whether the significant associations are likely to be false-positive findings and to ascertain their specificity, we examined the same gene subnetwork in three other human complex disorders (bipolar disorder, major depressive disorder, and type 2 diabetes) and found no significant associations. Functional enrichment analysis revealed that the gene subnetwork was enriched for genes involved in cation transport, synaptic transmission, and transmission of nerve impulses, all of which are biologically meaningful processes that may underlie the risk for AD. In conclusion, we identified a gene subnetwork underlying AD that is biologically meaningful and highly reproducible, providing important clues for future research into AD etiology and treatment.
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Improving genetic risk prediction by leveraging pleiotropy.
Hum. Genet.
PUBLISHED: 08-09-2013
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An important task of human genetics studies is to predict accurately disease risks in individuals based on genetic markers, which allows for identifying individuals at high disease risks, and facilitating their disease treatment and prevention. Although hundreds of genome-wide association studies (GWAS) have been conducted on many complex human traits in recent years, there has been only limited success in translating these GWAS data into clinically useful risk prediction models. The predictive capability of GWAS data is largely bottlenecked by the available training sample size due to the presence of numerous variants carrying only small to modest effects. Recent studies have shown that different human traits may share common genetic bases. Therefore, an attractive strategy to increase the training sample size and hence improve the prediction accuracy is to integrate data from genetically correlated phenotypes. Yet, the utility of genetic correlation in risk prediction has not been explored in the literature. In this paper, we analyzed GWAS data for bipolar and related disorders and schizophrenia with a bivariate ridge regression method, and found that jointly predicting the two phenotypes could substantially increase prediction accuracy as measured by the area under the receiver operating characteristic curve. We also found similar prediction accuracy improvements when we jointly analyzed GWAS data for Crohns disease and ulcerative colitis. The empirical observations were substantiated through our comprehensive simulation studies, suggesting that a gain in prediction accuracy can be obtained by combining phenotypes with relatively high genetic correlations. Through both real data and simulation studies, we demonstrated pleiotropy can be leveraged as a valuable asset that opens up a new opportunity to improve genetic risk prediction in the future.
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The role of macrophage migration inhibitory factor in autoimmune liver disease.
Hepatology
PUBLISHED: 07-28-2013
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The role of the cytokine, macrophage migration inhibitory factor (MIF), and its receptor, CD74, was assessed in autoimmune hepatitis (AIH) and primary biliary cirrhosis (PBC). Two MIF promoter polymorphisms, a functional -794 CATT5-8 microsatellite repeat (rs5844572) and a -173 G/C single-nucleotide polymorphism (rs755622), were analyzed in DNA samples from over 500 patients with AIH, PBC, and controls. We found a higher frequency of the proinflammatory and high-expression -794 CATT7 allele in AIH, compared to PBC, whereas lower frequency was found in PBC, compared to both AIH and healthy controls. MIF and soluble MIF receptor (CD74) were measured by enzyme-linked immunosorbent assay in 165 serum samples of AIH, PBC, and controls. Circulating serum and hepatic MIF expression was elevated in patients with AIH and PBC versus healthy controls. We also identified a truncated circulating form of the MIF receptor, CD74, that is released from hepatic stellate cells and that binds MIF, neutralizing its signal transduction activity. Significantly higher levels of CD74 were found in patients with PBC versus AIH and controls. Conclusions: These data suggest a distinct genetic and immunopathogenic basis for AIH and PBC at the MIF locus. Circulating MIF and MIF receptor profiles distinguish PBC from the more inflammatory phenotype of AIH and may play a role in pathogenesis and as biomarkers of these diseases. (Hepatology 2013; 00:000-000).
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Deep resequencing of 17 glutamate system genes identifies rare variants in DISC1 and GRIN2B affecting risk of opioid dependence.
Addict Biol
PUBLISHED: 07-16-2013
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The N-methyl-D-aspartate (NMDA) glutamate receptors play important roles in the pathophysiology of substance dependence (SD), but no strong genetic evidence has associated common variants in NMDAR-related genes to SD. We hypothesized that rare variants (RVs) with minor allele frequency <1% in the NMDAR-related genes might exert large effects on SD risk. We sequenced 34?544?bp of coding and flanking intronic regions of 17 genes involved in the NMDA system in 760 subjects, all with co-occurring alcohol dependence, cocaine dependence and opioid dependence (OD), and 760 healthy control subjects. One hundred percent of the target regions were sequenced at >1000× coverage. We identified 454 variants, including 380 RVs. Based on case-control allele count differences, we genotyped 11 exonic RVs in 6751 additional subjects, and the 1520 subjects from the sequencing stage for validation. All alleles of the 11 RVs called in the sequencing stage were confirmed. We found a statistically significant association of the 11 RVs with OD in African Americans (P?=?0.00080). Results from gene-based association tests showed that the association signal derived mostly from DISC1 (P?=?0.0010) and GRIN2B (P?=?0.00085). DISC1 is a well-validated schizophrenia risk gene. This is the first demonstration that RVs affect the risk of OD and the first demonstration of biological convergence of schizophrenia and OD risk-via DISC1.
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Characteristics of magnetic resonance imaging biomarkers in a natural history study of golden retriever muscular dystrophy.
Neuromuscul. Disord.
PUBLISHED: 07-13-2013
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The goal of this study was to assess whether magnetic resonance imaging (MRI) biomarkers can quantify disease progression in golden retriever muscular dystrophy (GRMD) via a natural history study. The proximal pelvic limbs of ten GRMD and eight normal dogs were scanned at 3, 6, and 9-12months of age. Several MRI imaging and texture analysis biomarkers were quantified in seven muscles. Almost all MRI biomarkers readily distinguished GRMD from control dogs; however, only selected biomarkers tracked with longitudinal disease progression. The biomarkers that performed best were full-length muscle volume and a texture analysis biomarker, termed heterogeneity index. The biceps femoris, semitendinosus and cranial sartorius muscles showed differential progression in GRMD versus control dogs. MRI features in GRMD dogs showed dynamic progression that was most pronounced over the 3- to 6-month period. Volumetric biomarkers and water map values correlated with histopathological features of necrosis/regeneration at 6-months. In conclusion, selected MRI biomarkers (volume and heterogeneity index) in particular muscles (biceps femoris, semitendinosus, and cranial sartorius) adjusted for age effect allow distinction of differential longitudinal progression in GRMD dogs. These biomarkers may be used as surrogate outcome measures in preclinical GRMD trials.
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Joint analysis of expression profiles from multiple cancers improves the identification of microRNA-gene interactions.
Bioinformatics
PUBLISHED: 06-14-2013
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MicroRNAs (miRNAs) play a crucial role in tumorigenesis and development through their effects on target genes. The characterization of miRNA-gene interactions will lead to a better understanding of cancer mechanisms. Many computational methods have been developed to infer miRNA targets with/without expression data. Because expression datasets are in general limited in size, most existing methods concatenate datasets from multiple studies to form one aggregated dataset to increase sample size and power. However, such simple aggregation analysis results in identifying miRNA-gene interactions that are mostly common across datasets, whereas specific interactions may be missed by these methods. Recent releases of The Cancer Genome Atlas data provide paired expression profiling of miRNAs and genes in multiple tumors with sufficiently large sample size. To study both common and cancer-specific interactions, it is desirable to develop a method that can jointly analyze multiple cancers to study miRNA-gene interactions without combining all the data into one single dataset.
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Fiber-driven resolution enhancement of diffusion-weighted images.
Neuroimage
PUBLISHED: 06-13-2013
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Diffusion-weighted imaging (DWI), while giving rich information about brain circuitry, is often limited by insufficient spatial resolution and low signal-to-noise ratio (SNR). This paper describes an algorithm that will increase the resolution of DW images beyond the scan resolution, allowing for a closer investigation of fiber structures and more accurate assessment of brain connectivity. The algorithm is capable of generating a dense vector-valued field, consisting of diffusion data associated with the full set of diffusion-sensitizing gradients. The fundamental premise is that, to best preserve information, interpolation should always be performed along axonal fibers. To achieve this, at each spatial location, we probe neighboring voxels in various directions to gather diffusion information for data interpolation. Based on the fiber orientation distribution function (ODF), directions that are more likely to be traversed by fibers will be given greater weights during interpolation and vice versa. This ensures that data interpolation is only contributed by diffusion data coming from fibers that are aligned with a specific direction. This approach respects local fiber structures and prevents blurring resulting from averaging of data from significantly misaligned fibers. Evaluations suggest that this algorithm yields results with significantly less blocking artifacts, greater smoothness in anatomical structures, and markedly improved structural visibility.
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On Estimation of Allele Frequencies via Next-Generation DNA Resequencing with Barcoding.
Stat Biosci
PUBLISHED: 06-05-2013
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Next Generation Sequencing (NGS) has revolutionized biomedical research in recent years. It is now commonly used to identify rare variants through re-sequencing individual genomes. Due to the cost of NGS, researchers have considered pooling samples as a cost-effective alternative to individual sequencing. In this article, we consider the estimation of allele frequencies of rare variants through the NGS technologies with pooled DNA samples with or without barcodes. We consider three methods for estimating allele frequencies from such data, including raw sequencing counts, inferred genotypes, and expected minor allele counts and compare their performance. Our simulation results suggest that the estimator based on inferred genotypes overall performs better than or as well as the other two estimators. When the sequencing coverage is low, biases and MSEs can be sensitive to the choice of the prior probabilities of genotypes for the estimators based on inferred genotypes and expected minor allele counts so that more accurate specification of prior probabilities is critical to lower biases and MSEs. Our study shows that the optimal number of barcodes in a pool is relatively robust to the frequencies of rare variants at a specific coverage depth. We provide general guidelines on using DNA pooling with barcoding for the estimation of allele frequencies of rare variants.
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Genome-Wide Association Study of Opioid Dependence: Multiple Associations Mapped to Calcium and Potassium Pathways.
Biol. Psychiatry
PUBLISHED: 05-31-2013
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We report a genome-wide association study (GWAS) of two populations, African-American and European-American (AA, EA) for opioid dependence (OD) in three sets of subjects, to identify pathways, genes, and alleles important in OD risk.
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A pilot study of regional perfusion and oxygenation in calf muscles of diabetes with a noninvasive measure.
J. Vasc. Surg.
PUBLISHED: 05-31-2013
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To assess alterations in the regional perfusion and oxygenation of the calf muscles in individuals with diabetes.
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Multisample aCGH data analysis via total variation and spectral regularization.
IEEE/ACM Trans Comput Biol Bioinform
PUBLISHED: 05-25-2013
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DNA copy number variation (CNV) accounts for a large proportion of genetic variation. One commonly used approach to detecting CNVs is array-based comparative genomic hybridization (aCGH). Although many methods have been proposed to analyze aCGH data, it is not clear how to combine information from multiple samples to improve CNV detection. In this paper, we propose to use a matrix to approximate the multisample aCGH data and minimize the total variation of each sample as well as the nuclear norm of the whole matrix. In this way, we can make use of the smoothness property of each sample and the correlation among multiple samples simultaneously in a convex optimization framework. We also developed an efficient and scalable algorithm to handle large-scale data. Experiments demonstrate that the proposed method outperforms the state-of-the-art techniques under a wide range of scenarios and it is capable of processing large data sets with millions of probes.
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HapBoost: a fast approach to boosting haplotype association analyses in genome-wide association studies.
IEEE/ACM Trans Comput Biol Bioinform
PUBLISHED: 05-25-2013
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Genome-wide association study (GWAS) has been successful in identifying genetic variants that are associated with complex human diseases. In GWAS, multilocus association analyses through linkage disequilibrium (LD), named haplotype-based analyses, may have greater power than single-locus analyses for detecting disease susceptibility loci. However, the large number of SNPs genotyped in GWAS poses great computational challenges in the detection of haplotype associations. We present a fast method named HapBoost for finding haplotype associations, which can be applied to quickly screen the whole genome. The effectiveness of HapBoost is demonstrated by using both synthetic and real data sets. The experimental results show that the proposed approach can achieve comparably accurate results while it performs much faster than existing methods.
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A genome wide association study of plasma uric acid levels in obese cases and never-overweight controls.
Obesity (Silver Spring)
PUBLISHED: 05-24-2013
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To identify plasma uric acid-related genes in extremely obese and normal weight individuals using genome-wide association studies (GWASs).
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The influence of depression on quality of life in patients with inflammatory bowel disease.
Inflamm. Bowel Dis.
PUBLISHED: 05-15-2013
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Inflammatory bowel disease is a chronic inflammatory disorder of the gastrointestinal tract that significantly impacts the health-related quality of life (HR-QOL). A decreased HR-QOL has been demonstrated in patients with active disease compared with patients in remission. In this cross-sectional study, we examined the role of depression and disease activity as independent factors in predicting patients HR-QOL.
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Role of Epg5 in selective neurodegeneration and Vici syndrome.
Autophagy
PUBLISHED: 05-14-2013
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Autophagy activity is essential for the survival of neural cells. Impairment of autophagy has been implicated in the pathogenesis of neurodegenerative disorders. Unlike the massive neuron loss in mice deficient for autophagy genes essential for autophagosome formation, we demonstrated that mice deficient for the metazoan-specific autophagy gene Epg5 develop selective neuronal damage and exhibit key characteristics of amyotrophic lateral sclerosis. Epg5 deficiency blocks the maturation of autophagosomes into degradative autolysosomes, slows endocytic degradation and also impairs endocytic recycling. Recessive mutations in human EPG5 have recently been causally associated with the multisystem disorder Vici syndrome. Here we show that while Epg5 knockout mice display some features of Vici syndrome, many phenotypes are absent.
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Identification of genes critical for resistance to infection by West Nile virus using RNA-Seq analysis.
Viruses
PUBLISHED: 05-08-2013
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The West Nile virus (WNV) is an emerging infection of biodefense concern and there are no available treatments or vaccines. Here we used a high-throughput method based on a novel gene expression analysis, RNA-Seq, to give a global picture of differential gene expression by primary human macrophages of 10 healthy donors infected in vitro with WNV. From a total of 28 million reads per sample, we identified 1,514 transcripts that were differentially expressed after infection. Both predicted and novel gene changes were detected, as were gene isoforms, and while many of the genes were expressed by all donors, some were unique. Knock-down of genes not previously known to be associated with WNV resistance identified their critical role in control of viral infection. Our study distinguishes both common gene pathways as well as novel cellular responses. Such analyses will be valuable for translational studies of susceptible and resistant individuals--and for targeting therapeutics--in multiple biological settings.
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MSClust: A Multi-Seeds based Clustering algorithm for microbiome profiling using 16S rRNA sequence.
J. Microbiol. Methods
PUBLISHED: 05-02-2013
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Recent developments of next generation sequencing technologies have led to rapid accumulation of 16S rRNA sequences for microbiome profiling. One key step in data processing is to cluster short sequences into operational taxonomic units (OTUs). Although many methods have been proposed for OTU inferences, a major challenge is the balance between inference accuracy and computational efficiency, where inference accuracy is often sacrificed to accommodate the need to analyze large numbers of sequences. Inspired by the hierarchical clustering method and a modified greedy network clustering algorithm, we propose a novel multi-seeds based heuristic clustering method, named MSClust, for OTU inference. MSClust first adaptively selects multi-seeds instead of one seed for each candidate cluster, and the reads are then processed using a greedy clustering strategy. Through many numerical examples, we demonstrate that MSClust enjoys less memory usage, and better biological accuracy compared to existing heuristic clustering methods while preserving efficiency and scalability.
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Genome-wide association study identifies new susceptibility loci for posttraumatic stress disorder.
Biol. Psychiatry
PUBLISHED: 04-11-2013
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Genetic factors influence the risk for posttraumatic stress disorder (PTSD), a potentially chronic and disabling psychiatric disorder that can arise after exposure to trauma. Candidate gene association studies have identified few genetic variants that contribute to PTSD risk.
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Tdrkh is essential for spermatogenesis and participates in primary piRNA biogenesis in the germline.
EMBO J.
PUBLISHED: 04-08-2013
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Piwi proteins and Piwi-interacting RNAs (piRNAs) repress transposition, regulate translation, and guide epigenetic programming in the germline. Here, we show that an evolutionarily conserved Tudor and KH domain-containing protein, Tdrkh (a.k.a. Tdrd2), is required for spermatogenesis and involved in piRNA biogenesis. Tdrkh partners with Miwi and Miwi2 via symmetrically dimethylated arginine residues in Miwi and Miwi2. Tdrkh is a mitochondrial protein often juxtaposed to pi-bodies and piP-bodies and is required for Tdrd1 cytoplasmic localization and Miwi2 nuclear localization. Tdrkh mutants display meiotic arrest at the zygotene stage, attenuate methylation of Line1 DNA, and upregulate Line1 RNA and protein, without inducing apoptosis. Furthermore, Tdrkh mutants have severely reduced levels of mature piRNAs but accumulate a distinct population of 1U-containing, 2O-methylated 31-37?nt RNAs that largely complement the missing mature piRNAs. Our results demonstrate that the primary piRNA biogenesis pathway involves 3?5 processing of 31-37?nt intermediates and that Tdrkh promotes this final step of piRNA biogenesis but not the ping-pong cycle. These results shed light on mechanisms underlying primary piRNA biogenesis, an area in which information is conspicuously absent.
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Mice deficient in Epg5 exhibit selective neuronal vulnerability to degeneration.
J. Cell Biol.
PUBLISHED: 03-11-2013
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The molecular mechanism underlying the selective vulnerability of certain neuronal populations associated with neurodegenerative diseases remains poorly understood. Basal autophagy is important for maintaining axonal homeostasis and preventing neurodegeneration. In this paper, we demonstrate that mice deficient in the metazoan-specific autophagy gene Epg5/epg-5 exhibit selective damage of cortical layer 5 pyramidal neurons and spinal cord motor neurons. Pathologically, Epg5 knockout mice suffered muscle denervation, myofiber atrophy, late-onset progressive hindquarter paralysis, and dramatically reduced survival, recapitulating key features of amyotrophic lateral sclerosis (ALS). Epg5 deficiency impaired autophagic flux by blocking the maturation of autophagosomes into degradative autolysosomes, leading to accumulation of p62 aggregates and ubiquitin-positive inclusions in neurons and glial cells. Epg5 knockdown also impaired endocytic trafficking. Our study establishes Epg5-deficient mice as a model for investigating the pathogenesis of ALS and indicates that dysfunction of the autophagic-endolysosomal system causes selective damage of neurons associated with neurodegenerative diseases.
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Utilizing protein structure to identify non-random somatic mutations.
BMC Bioinformatics
PUBLISHED: 03-08-2013
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Human cancer is caused by the accumulation of somatic mutations in tumor suppressors and oncogenes within the genome. In the case of oncogenes, recent theory suggests that there are only a few key "driver" mutations responsible for tumorigenesis. As there have been significant pharmacological successes in developing drugs that treat cancers that carry these driver mutations, several methods that rely on mutational clustering have been developed to identify them. However, these methods consider proteins as a single strand without taking their spatial structures into account. We propose an extension to current methodology that incorporates protein tertiary structure in order to increase our power when identifying mutation clustering.
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Normalized modularity optimization method for community identification with degree adjustment.
Phys Rev E Stat Nonlin Soft Matter Phys
PUBLISHED: 03-03-2013
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As a fundamental problem in network study, community identification has attracted much attention from different fields. Representing a seminal work in this area, the modularity optimization method has been widely applied and studied. However, this method has issues in resolution limit and extreme degeneracy and may not perform well for networks with unbalanced structures. Although several methods have been proposed to overcome these limitations, they are all based on the original idea of defining modularity through comparing the total number of edges within the putative communities in the observed network with that in an equivalent randomly generated network. In this paper, we show that this modularity definition is not suitable to analyze some networks such as those with unbalanced structures. Instead, we propose to define modularity through the average degree within the communities and formulate modularity as comparing the sum of average degree within communities of the observed network to that of an equivalent randomly generated network. In addition, we also propose a degree-adjusted approach for further improvement when there are unbalanced structures. We analyze the theoretical properties of our degree adjusted method. Numerical experiments for both artificial networks and real networks demonstrate that average degree plays an important role in network community identification, and our proposed methods have better performance than existing ones.
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Differential expression analysis for paired RNA-Seq data.
BMC Bioinformatics
PUBLISHED: 03-01-2013
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RNA-Seq technology measures the transcript abundance by generating sequence reads and counting their frequencies across different biological conditions. To identify differentially expressed genes between two conditions, it is important to consider the experimental design as well as the distributional property of the data. In many RNA-Seq studies, the expression data are obtained as multiple pairs, e.g., pre- vs. post-treatment samples from the same individual. We seek to incorporate paired structure into analysis.
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Studying the evolution of transcription factor binding events using multi-species ChIP-Seq data.
Stat Appl Genet Mol Biol
PUBLISHED: 03-01-2013
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Recent technology advances make it possible to collect whole-genome transcription factor binding (TFB) profiles from multiple species through the ChIP-Seq data. This provides rich information to understand TFB evolution. However, few rigorous statistical models are available to infer TFB evolution from these data. We have developed a phylogenetic tree based method to model the on/off rates of TFB events. There are two unique features of our method compared to existing models. First, we mask nucleotide substitutions and focus on INDEL disruption of TFB events, which are rarer evolution events and more appropriate for divergent species and non-coding regulatory regions. Second, we correct for ascertainment bias in ChIP-Seq data by maximizing likelihood conditional on the observed (incomplete) data. Simulations show that our method works well in model selection and parameter estimation when there are sufficient aligned TFB events. When this method is applied to a ChIP-Seq data set with five vertebrates, we find that the instantaneous transition rates to INDELs are higher in TFB regions than in homologous non-binding regions. This is driven by an excess of alignment columns showing binding in one species but gaps in all other species. When we compare the inferred transition rates between the conserved and non-conserved regions, as expected, the conserved regions are estimated to have lower transition rates. The R package TFBphylo that implements the described model can be downloaded from http://bioinformatics.med.yale.edu/.
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Accounting for non-genetic factors by low-rank representation and sparse regression for eQTL mapping.
Bioinformatics
PUBLISHED: 02-17-2013
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Expression quantitative trait loci (eQTL) studies investigate how gene expression levels are affected by DNA variants. A major challenge in inferring eQTL is that a number of factors, such as unobserved covariates, experimental artifacts and unknown environmental perturbations, may confound the observed expression levels. This may both mask real associations and lead to spurious association findings.
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Statistical analysis reveals co-expression patterns of many pairs of genes in yeast are jointly regulated by interacting loci.
PLoS Genet.
PUBLISHED: 02-11-2013
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Expression quantitative trait loci (eQTL) studies have generated large amounts of data in different organisms. The analyses of these data have led to many novel findings and biological insights on expression regulations. However, the role of epistasis in the joint regulation of multiple genes has not been explored. This is largely due to the computational complexity involved when multiple traits are simultaneously considered against multiple markers if an exhaustive search strategy is adopted. In this article, we propose a computationally feasible approach to identify pairs of chromosomal regions that interact to regulate co-expression patterns of pairs of genes. Our approach is built on a bivariate model whose covariance matrix depends on the joint genotypes at the candidate loci. We also propose a filtering process to reduce the computational burden. When we applied our method to a yeast eQTL dataset profiled under both the glucose and ethanol conditions, we identified a total of 225 and 224 modules, with each module consisting of two genes and two eQTLs where the two eQTLs epistatically regulate the co-expression patterns of the two genes. We found that many of these modules have biological interpretations. Under the glucose condition, ribosome biogenesis was co-regulated with the signaling and carbohydrate catabolic processes, whereas silencing and aging related genes were co-regulated under the ethanol condition with the eQTLs containing genes involved in oxidative stress response process.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.