12277 results for ""statistically+reactive"+taxa+in+microbial+community"

in 17.62 milliseconds.

• Identifying Novel Small RNA Biomarkers Unique to Patients with Gastric Cancer

  The biomarker development study consisted of two parts: discovery and validation. The first part was the discovery and verification phase of biomarkers using two different platforms: transcriptomic and miRNA. The salivary transcriptomes of 63 GC samples and 31 non-GC controls were profiled using Affymetrix HG U133+2.0 microarrays (Affymetrix, Santa Clara, CA). The identified exRNA candidates were verified by quantitative real-time PCR (RT-qPCR) using all 94 of the original samples. In the discovery phase for the miRNA biomarkers, 10 early-stage GC samples and 10 non-GC controls were selected. The salivary miRNAs of these samples (n=20) were profiled using the TaqMan MicroRNA Array (Applied Biosystems, Foster City, CA). MicroRNA candidates were verified using TaqMan miRNA Assay (Thermo Scientific, Grand Island, NY). The second part of the study was to validate these verified exRNA biomarker candidates with exRNA samples extracted from an independent cohort of 100 GC and 100 non-GC saliva samples. The cohort was not balanced for demographics on gender and smoking history but more accurately reflected the diagnostic setting where our proposed final model could be implemented. Reprinted from "Li F, Yoshizawa MJ, Kim K, Kanjanapangka J, Grogan T, Wang X, Elashoff D, Ishikawa S, Chia D, Liao W, Akin D, Yan X, Lee M, Choi R, Kim S, Kang S, Bae J, Sohn T, Lee J, Choi M, Min B, Lee J, Kim J, Kim Y, Kim S, Wong D. (2018) Development and Validation of Salivary Extracellular RNA Biomarkers for Noninvasive Detection of Gastric Cancer. Clin Chem. PMID: 30097497 DOI: 10.1373/clinchem.2018.290569", with permission from American Association for Clinical Chemistry (United States).

  Study phs001767

• Center for Inherited Disease Research (CIDR)-National Institute on Aging (NIA) Whole Exome Analysis of Ehlers-Danlos Syndrome

  The Ehlers-Danlos syndromes (EDS) are a family of hereditary disorders of connective tissue characterized by joint hypermobility and skin involvement with soft, translucent, stretchy skin, and atrophic scarring. To date, over 12 different types of EDS are known, and the genes causing almost all of them have been found. However, the gene(s) underlying the most common of Ehlers-Danlos syndrome, known as the hypermobile type, remain elusive. The hypermobile type of Ehlers-Danlos syndrome is associated with multiple co-morbidities, including dysautonomia, chronic musculoskeletal pain, gastrointestinal dysmotility, mast cell activation and multiple neurologic complications. Affected persons often suffer from chronic fatigue and may be chronically disabled. While the precise frequency of the condition is not known, it may be as common as between 1/500 and 1/1000 persons. There is a significant overlap with the phenotype of fibromyalgia, and multiple persons diagnosed with fibromyalgia may well have the hypermobile type of Ehlers-Danlos syndrome. The phenotype of hypermobile EDS segregates as a single dominant trait with complete penetrance, variable expressivity, and a markedly evolving phenotype over time. Identification of the genetic cause of this hereditary disorder has the potential to inform rational therapy for this disabling condition. It is hoped that the insight into the pathogenesis of the hypermobile type of EDS will lead to a similar breakthrough in therapy for this disorder. Toward this end, whole exome sequencing (WES) of DNA from a total of 167 patients will be performed at the Center for Inherited Disease Research (CIDR) to identify genes underlying the hypermobile type of Ehlers-Danlos syndrome and those with EDS of an uncharacterized type.

  Study phs001779

• National Emphysema Treatment Trial (NETT-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Available Data: The current release of the NETT study dataset includes follow-up data through May of 2013.Objectives: To compare lung-volume-reduction surgery with medical therapy for severe emphysema, and to identify participant selection criteria for lung volume reduction surgery.Background: Lung-volume-reduction surgery has been proposed as a palliative treatment for severe emphysema. Effects on mortality, the magnitude and durability of benefits, and criteria for the selection of participants have not been established.Participants: A total of 1,218 participants with severe emphysema underwent pulmonary rehabilitation and were randomly assigned at 17 centers to undergo lung-volume-reduction surgery (bilateral stapled wedge resection) or to receive continued medical treatment. Participants were randomized after a 6-10 week pulmonary rehabilitation period and participants with a forced expiratory volume in one second (FEV1) that was 20 percent or less of predicted and a homogeneous distribution of emphysema or carbon monoxide diffusing capacity 20 percent or less of predicted were not eligible for randomization due to poor post-surgery prognosis for death or functional improvement.Conclusions: Overall, lung-volume-reduction surgery increases the chance of improved exercise capacity but does not confer a survival advantage over medical therapy. It does yield a survival advantage for participants with both predominantly upper-lobe emphysema and low base-line exercise capacity. Participants previously reported to be at high risk and those with non-upper-lobe emphysema and high base-line exercise capacity are poor candidates for lung-volume-reduction surgery, because of increased mortality and negligible functional gain. (NEJM 2003;348:2059-2073).

  Study phs004077

• CIDR Estrogen Receptor Negative Breast Cancer in African American Women: DNA Methylation, Reproductive Events, and Mammary Epithelial Cell Populations

  We conducted methylation profiling of breast tumor DNA from Formalin-Fixed Paraffin-Embedded (FFPE) samples for 1,550 cases from a cohort of Black women from the Black Women’s Health Study (BWHS), the Women’s Circle of Health Study (WCHS), and from the Pathways Study using the Illumina MethylationEPIC array. We will examine differentially methylated loci (DML) between ER+ and ER- tumors, and by age at onset of breast cancer. Combining these data with previously analyzed samples (n=385), we will consider associations between reproductive risk factors and top DML by age at diagnosis and ER status, examining the complex relationships between methylation, tumor and patient characteristics, and reproductive risk factors using structural equation modeling.

  Study phs002688

• Multi-omics profiling identifies two epithelioid sarcoma molecular subtypes with distinct signaling and immune characteristics

  Epithelioid sarcoma (EpS) is an aggressive sarcoma, characterized by the loss of SMARCB1 expression. EpS is traditionally classified as distal or proximal according to clinicopathological features, but its molecular characteristics remain largely unknown. To establish an EpS molecular classification and uncover determinants of inter- and intra-patient heterogeneity in EpS, we used multi-omics profiling and integrated the genomic, transcriptional and methylome landscapes with single-cell RNA sequencing on fresh samples as well as spatial transcriptomics. We identified two molecular subtypes of EpS: “distal-like” and “proximal-like”, which were distinct from the histological subtypes. Distal-like tumors include all morphological distal subtypes and a subset of proximal and hybrid EpS. They express a specific molecular single-cell derived epithelial-to-mesenchymal transition signature, which associates with improved patient survival and includes Desmoglein 2 (DSG2), which we identify as a potential routine immunohistochemical biomarker to improve diagnosis. Distal-like EpS also display increased peri-tumoral CD8+ T cell infiltrates and specific tumor-immune cell interactions. Conversely, proximal-like EpS harbor a higher inter-tumoral molecular heterogeneity with some cases resembling other SMARCB1-deficient tumors by DNA methylation profiling, and increased intra-tumoral pro-tumoral macrophage infiltrates. Our study introduces a novel molecular classification of EpS with prognostic value, associated diagnostic biomarkers and distinct tumor immune microenvironments, which extends beyond traditional clinicopathological classification. This paves the way for precision medicine-based therapeutic strategies for patients with EpS.

  Dac EGAC50000000552

• Multiplexed biomarkers dynamically detect heterogeneous residual neuroblastoma cell clone activity in the bone marrow niche

  Our objective was to develop a patient-specific, genomics-informed minimal residual disease (MRD) monitoring strategy for pediatric high-risk neuroblastoma using individualized multiplexed mediator-probe PCR (MP-PCR) assays. Tumor-specific somatic mutations or structural variants were identified through hybrid-capture panel sequencing. We examined tumor material from 8 patients, including 11 primary tumor samples, 3 of which represent spatially distinct primary tumor samples and 2 samples obtained at relapse. Provided are FASTQ data files, bam and bambai files, as well as breakpoint spanning and encompassing read (enspan) bam and bambai files. Sequencing bam data files are aligned to GRCh37.p13 reference genome (processed). Sequencing data were aligned to the GRCh37.p13 reference genome and processed using validated pipelines.

  Study EGAS50000001581

• Team

  The Team Mallory Freeberg Roderic Guigó Arcadi Navarro Helen Parkinson Jordi Rambla Ana T. Alonso Silvia Bahena Àlex Bedmar Kenneth Buckley Aldar Cabrelles Ángel Carreño Marcos Casado Giulia Cellerino Amy Curwin Teresa D'Altri Abeer Fadda Teresa Garcia Sara Gregorio Max Fischer Bela Juhasz Oriol Lopez-Doriga Mireia Marin Óscar Martínez Andrea Mero Akiris Moctezuma Aurora Moreno Liina Nagirnaja Francesc de Puig Santiago Rensonnet Gabriele Rinck Aravind Sankar Andres Silva Coline Thomas Sabela de la Torre Gemma Vicente The EGA Team at the CRG co-manages the European Genome and phenome Archive together with the EGA Team at the European Bioinformatics Institute. In addition to maintaining and distributing data, we enrich the contents of the EGA contributing with our knowledge about genomics and the relationship between genomes and phenomes. Previous Team Members Alexander Vikhorev Jeff Almeida-King Mario Alberich Sergi Aguilo Pablo Arce Minjie Ding Alfred Gil Leslie Glass Jag Kandasamy Vasudev Kumanduri llkka Lapalainen Audald Lloret i Villas Sira Martinez Anand Mohan Dietmar Orth Justin Paschall Saif Ur Rehman Gary Saunders Thomas Smith Ashutosh Shimpi Marc Sitges Dhvani Solanki Giselle Kerry Nino Spataro Dylan Spalding Matthieu Vizuete-Forster Cristina Yenyxe Gonzalez Garcia Paul Flicek Anna Foix Emilio Garcia Rios Jorge Izquierdo Roberto Ariosa Marta Ferri Peradalta Daniel Barrowdale Babita Singh Umuthan Uyan Aleix Canalda Dona Shaju Mauricio Moldes Carles Garcia Frédéric Haziza Alegria Aclan Lauren Fromont Alvis Brazma Marta Huertas Arnau Soler Gemma Milla Claudia Vasallo Aina Jené Csaba Halmagyi Raül Garcia Thomas Keane Mei Gascón

  Documentation about/team

• Targeted next-generation sequencing detects novel gene-phenotype associations and expands the mutational spectrum in cardiomyopathie

  Cardiomyopathies are a heterogeneous group of primary diseases of the myocardium,including hypertrophic cardiomyopathy (HCM), dilated cardiomyopathy (DCM), andarrhythmogenic right ventricular cardiomyopathy (ARVC), with higher morbidity andmortality. These diseases are genetically diverse and associated with rare mutations ina large number of genes, many of which overlap among the phenotypes. To betterinvestigate the genetic overlap between these three phenotypes and to identify newgenotype-phenotype correlations, we designed a custom gene panel consisting of 115genes known to be associated with cardiomyopathic phenotypes and channelopathies.A cohort of 38 unrelated patients, 16 affected by DCM, 14 by HCM and 8 by ARVC,was recruited for the study on the basis of more severe phenotypes and family historyof cardiomyopathy and/or sudden death.

  Study EGAS00001002506

• minION fastq files of 10 different tumor samples from the Master program (H021)

  Nanopore RNA Sequencing was done for 10 tumor samples. Direct cDNA sequencing was performed using the SQK-DCS109 kit (Oxford Nanopore Technologies). For analysis of a single sample on a MinION flow cell (version R9.4.1), 5 μg RNA was used as input. For multiplexing on a MinION flow cell, 2.5 μg RNA per sample was used as input, and the native barcoding expansion kit EXP-NBD104 was employed in conjunction with SQK-DCS109. After reverse transcription with Maxima H Minus Reverse Transcriptase (Thermo Scientific), second-strand synthesis was performed using the 2x LongAmp Taq Master Mix (New England Biolabs). The resulting double-stranded cDNA was subjected to end-repair and dA-tailing using the NEBNext Ultra End Repair/dA-Tailing Module (New England Biolabs). For multiplexed libraries, this step was followed by barcode ligation and library pooling. Next, libraries were quantified with a Qubit Fluorometer 3.0 (Life Technologies). Finally, sequencing adapters were added to the library preparations and ligated with Blunt/TA Ligase Master Mix (New England Biolabs), followed by further quality control using a Qubit. Samples ACC1 and ACC2 were analyzed on individual MinION flow cells, while the remaining eight samples were sequenced as multiplexed libraries on two MinION flow cells by pooling four samples for each run. Five ACC samples were also analyzed individually on Flongle flow cells

  Dataset EGAD00001008970

• Molecular profiling of tissue autopsies and ctDNA

  The dataset contains high-throughput sequencing data derived from a cancer autopsy series of 10 patients. As part of this study, whole-exome sequencing and RNA-seq were performed for spatially distinct tissue biopsies from the patients. In addition, plasma samples from the patients were sequenced using a custom panelt to profile ctDNA. There are 106 files containing whole-exome sequencing data, 107 files containing RNA-seq data, and 9 files containing plasma sequencing data.

  Dataset EGAD00001007040