1,194 research outputs found

    Mapping gene associations in human mitochondria using clinical disease phenotypes

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    Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes

    Using Interpolation to Estimate System Uncertainty in Gene Expression Experiments

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    The widespread use of high-throughput experimental assays designed to measure the entire complement of a cell's genes or gene products has led to vast stores of data that are extremely plentiful in terms of the number of items they can measure in a single sample, yet often sparse in the number of samples per experiment due to their high cost. This often leads to datasets where the number of treatment levels or time points sampled is limited, or where there are very small numbers of technical and/or biological replicates. Here we introduce a novel algorithm to quantify the uncertainty in the unmeasured intervals between biological measurements taken across a set of quantitative treatments. The algorithm provides a probabilistic distribution of possible gene expression values within unmeasured intervals, based on a plausible biological constraint. We show how quantification of this uncertainty can be used to guide researchers in further data collection by identifying which samples would likely add the most information to the system under study. Although the context for developing the algorithm was gene expression measurements taken over a time series, the approach can be readily applied to any set of quantitative systems biology measurements taken following quantitative (i.e. non-categorical) treatments. In principle, the method could also be applied to combinations of treatments, in which case it could greatly simplify the task of exploring the large combinatorial space of future possible measurements

    Lipopolysaccharide O1 Antigen Contributes to the Virulence in Klebsiella pneumoniae Causing Pyogenic Liver Abscess

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    Klebsiella pneumoniae is the common cause of a global emerging infectious disease, community-acquired pyogenic liver abscess (PLA). Capsular polysaccharide (CPS) and lipopolysaccharide (LPS) are critical for this microorganism's ability to spread through the blood and to cause sepsis. While CPS type K1 is an important virulence factor in K. pneumoniae causing PLA, the role of LPS in PLA is not clear. Here, we characterize the role of LPS O antigen in the pathogenesis of K. pneumoniae causing PLA. NTUH-K2044 is a LPS O1 clinical strain; the presence of the O antigen was shown via the presence of 1,3-galactan in the LPS, and of sequences that align with the wb gene cluster, known to produce O-antigen. Serologic analysis of K. pneumoniae clinical isolates demonstrated that the O1 serotype was more prevalent in PLA strains than that in non-tissue-invasive strains (38/42 vs. 9/32, P<0.0001). O1 serotype isolates had a higher frequency of serum resistance, and mutation of the O1 antigen changed serum resistance in K. pneumoniae. A PLA-causing strain of CPS capsular type K2 and LPS serotype O1 (i.e., O1:K2 PLA strain) deleted for the O1 synthesizing genes was profoundly attenuated in virulence, as demonstrated in separate mouse models of septicemia and liver abscess. Immunization of mice with the K2044 magA-mutant (K1− O1) against LPS O1 provided protection against infection with an O1:K2 PLA strain, but not against infection with an O1:K1 PLA strain. Our findings indicate that the O1 antigen of PLA-associated K. pneumoniae contributes to virulence by conveying resistance to serum killing, promoting bacterial dissemination to and colonization of internal organs after the onset of bacteremia, and could be a useful vaccine candidate against infection by an O1:K2 PLA strain

    Gene processing control loops suggested by sequencing, splicing, and RNA folding

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    Abstract Background Small RNAs are known to regulate diverse gene expression processes including translation, transcription, and splicing. Among small RNAs, the microRNAs (miRNAs) of 17 to 27 nucleotides (nts) undergo biogeneses including primary transcription, RNA excision and folding, nuclear export, cytoplasmic processing, and then bioactivity as regulatory agents. We propose that analogous hairpins from RNA molecules that function as part of the spliceosome might also be the source of small, regulatory RNAs (somewhat smaller than miRNAs). Results Deep sequencing technology has enabled discovery of a novel 16-nt RNA sequence in total RNA from human brain that we propose is derived from RNU1, an RNA component of spliceosome assembly. Bioinformatic alignments compel inquiring whether the novel 16-nt sequence or its precursor have a regulatory function as well as determining aspects of how processing intersects with the miRNA biogenesis pathway. Specifically, our preliminary in silico investigations reveal the sequence could regulate splicing factor Arg/Ser rich 1 (SFRS1), a gene coding an essential protein component of the spliceosome. All 16-base source sequences in the UCSC Human Genome Browser are within the 14 instances of RNU1 genes listed in wgEncodeGencodeAutoV3. Furthermore, 10 of the 14 instances of the sequence are also within a common 28-nt hairpin-forming subsequence of RNU1. Conclusions An abundant 16-nt RNA sequence is sourced from a spliceosomal RNA, lies in a stem of a predicted RNA hairpin, and includes reverse complements of subsequences of the 3'UTR of a gene coding for a spliceosome protein. Thus RNU1 could function both as a component of spliceosome assembly and as inhibitor of production of the essential, spliceosome protein coded by SFRS1. Beyond this example, a general procedure is needed for systematic discovery of multiple alignments of sequencing, splicing, and RNA folding data

    Downregulated parafibromin expression is a promising marker for pathogenesis, invasion, metastasis and prognosis of gastric carcinomas

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    Parafibromin is a protein encoded by the hyperparathyroidism 2 oncosuppressor gene and its downregulated expression is involved in pathogenesis of parathyroid carcinomas. To clarify the roles of parafibromin expression in tumourigenesis and progression of gastric carcinomas, it was examined by immunohistochemistry (IHC) on tissue microarray containing gastric carcinomas (n = 508), adenomas (n = 45) and gastritis (n = 49) with a comparison of its expression with clinicopathological parametres of carcinomas. Gastric carcinoma cell lines (MKN28, AGS, MKN45, KATO-III and HGC-27) were studied for parafibromin expression by IHC and western blot. Parafibromin expression was localised in the nucleus of gastric epithelial cells, adenoma, carcinoma cells and cell lines. Its expression was gradually decreased from gastritis to gastric carcinoma, through gastric adenomas (p < 0.05) and inversely correlated with tumour size, depth of invasion, lymphatic invasion, lymph node metastasis and Union Internationale Contre le Cancer (UICC) staging (p < 0.05) but not with sex or venous invasion (p > 0.05). Parafibromin was strongly expressed in older carcinoma patients compared with younger ones (p < 0.05). There was stronger positivity of parafibromin in intestinal-type than diffuse-type carcinomas (p < 0.05). Univariate analysis indicated cumulative survival rate of patients with positive parafibromin expression to be higher than without its expression (p < 0.05). Multivariate analysis showed that age, tumour size, depth of invasion, lymphatic invasion, lymph node metastasis, UICC staging and Lauren’s classification but not sex, venous invasion or parafibromin expression were independent prognostic factors for carcinomas(p < 0.05). Downregulated parafibromin expression possibly contributed to pathogenesis, growth, invasion and metastasis of gastric carcinomas. It was considered as a promising marker to indicate the aggressive behaviours and prognosis of gastric carcinomas

    Primary gastric non-Hodgkin's lymphoma in Chinese patients: clinical characteristics and prognostic factors

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    <p>Abstract</p> <p>Background</p> <p>Optimal management and outcome of primary gastric lymphoma (PGL) have not been well defined in the rituximab era. This study aimed to analyze the clinical characteristics, prognostic factors, and roles of different treatment modalities in Chinese patients with PGL.</p> <p>Methods</p> <p>The clinicopathological features of 83 Chinese patients with PGL were retrospectively reviewed. Staging was performed according to the Lugano staging system for gastrointestinal non-Hodgkin's lymphoma.</p> <p>Results</p> <p>The predominant pathologic subtype among Chinese patients with PGL in our study was diffuse large B cell lymphoma (DLBCL), followed by mucosa-associated lymphoid tissue (MALT) lymphoma. Among the 57 patients with gastric DLBCL, 20 patients (35.1%) were classified as the germinal center B cell-like (GCB) subtype and 37 patients (64.9%) as the non-GCB subtype. The 83 patients had a five-year overall survival (OS) and event-free survival (EFS) of 52% and 59%, respectively. Cox regression analysis showed that stage-modified international prognostic index (IPI) and performance status (PS) were independent predictors of survival. In the 67 B-cell lymphoma patients who received chemotherapy, 36 patients treated with rituximab (at least 3 cycles) had a mean OS of 72 months (95% CI 62-81) versus 62 months (95% CI 47-76) for patients without rituximab treatment (P = 0.021).</p> <p>Conclusion</p> <p>The proportion of Chinese gastric DLBCL cases with non-GCB subtype was higher than the GCB subtype. Stage-modified IPI and PS were effective prognostic factors in Chinese patients with PGL. Our data suggested that primary gastric B-cell lymphoma might have an improved outcome with rituximab in addition to chemotherapy. More studies are necessary, preferentially large prospective randomized clinical trials to obtain more information on the impact of the rituximab in the primary gastric B-cell lymphoma.</p

    Population based allele frequencies of disease associated polymorphisms in the Personalized Medicine Research Project

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    <p>Abstract</p> <p>Background</p> <p>There is a lack of knowledge regarding the frequency of disease associated polymorphisms in populations and population attributable risk for many populations remains unknown. Factors that could affect the association of the allele with disease, either positively or negatively, such as race, ethnicity, and gender, may not be possible to determine without population based allele frequencies.</p> <p>Here we used a panel of 51 polymorphisms previously associated with at least one disease and determined the allele frequencies within the entire Personalized Medicine Research Project population based cohort. We compared these allele frequencies to those in dbSNP and other data sources stratified by race. Differences in allele frequencies between self reported race, region of origin, and sex were determined.</p> <p>Results</p> <p>There were 19544 individuals who self reported a single racial category, 19027 or (97.4%) self reported white Caucasian, and 11205 (57.3%) individuals were female. Of the 11,208 (57%) individuals with an identifiable region of origin 8337 or (74.4%) were German.</p> <p>41 polymorphisms were significantly different between self reported race at the 0.05 level. Stratification of our Caucasian population by self reported region of origin revealed 19 polymorphisms that were significantly different (p = 0.05) between individuals of different origins. Further stratification of the population by gender revealed few significant differences in allele frequencies between the genders.</p> <p>Conclusions</p> <p>This represents one of the largest population based allele frequency studies to date. Stratification by self reported race and region of origin revealed wide differences in allele frequencies not only by race but also by region of origin within a single racial group. We report allele frequencies for our Asian/Hmong and American Indian populations; these two minority groups are not typically selected for population allele frequency detection. Population wide allele frequencies are important for the design and implementation of studies and for determining the relevance of a disease associated polymorphism for a given population.</p

    Measurement of the cross-section of high transverse momentum vector bosons reconstructed as single jets and studies of jet substructure in pp collisions at √s = 7 TeV with the ATLAS detector

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    This paper presents a measurement of the cross-section for high transverse momentum W and Z bosons produced in pp collisions and decaying to all-hadronic final states. The data used in the analysis were recorded by the ATLAS detector at the CERN Large Hadron Collider at a centre-of-mass energy of √s = 7 TeV;{\rm Te}{\rm V}andcorrespondtoanintegratedluminosityof and correspond to an integrated luminosity of 4.6\;{\rm f}{{{\rm b}}^{-1}}.ThemeasurementisperformedbyreconstructingtheboostedWorZbosonsinsinglejets.ThereconstructedjetmassisusedtoidentifytheWandZbosons,andajetsubstructuremethodbasedonenergyclusterinformationinthejetcentreofmassframeisusedtosuppressthelargemultijetbackground.ThecrosssectionforeventswithahadronicallydecayingWorZboson,withtransversemomentum. The measurement is performed by reconstructing the boosted W or Z bosons in single jets. The reconstructed jet mass is used to identify the W and Z bosons, and a jet substructure method based on energy cluster information in the jet centre-of-mass frame is used to suppress the large multi-jet background. The cross-section for events with a hadronically decaying W or Z boson, with transverse momentum {{p}_{{\rm T}}}\gt 320\;{\rm Ge}{\rm V}andpseudorapidity and pseudorapidity |\eta |\lt 1.9,ismeasuredtobe, is measured to be {{\sigma }_{W+Z}}=8.5\pm 1.7$ pb and is compared to next-to-leading-order calculations. The selected events are further used to study jet grooming techniques

    Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

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    Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente
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