12393 results for ""statistically+reactive"+taxa+in+microbial+community"

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• CIP: Obesity-Diabetes Familial Risk, Viva La Familia Study

  The VIVA LA FAMILIA Study was designed to identify genetic variants influencing childhood obesity and its comorbidities in the Hispanic population. Family recruitment and phenotyping were conducted in 2000-2005 in Houston, TX. All enrolled children (n=1030) and parents gave written informed consent or assent. The protocol was approved by the Institutional Review Boards for Human Subject Research for Baylor College of Medicine and Affiliated Hospitals and for Texas Biomedical Research Institute. The VIVA LA FAMILIA study design and methodology have been described in detail (Butte NF, 2006). Each family was ascertained on an obese proband, defined as a BMI > 95th percentile, between the ages 4-19 y. The cross-sectional, longitudinal study design consisted of baseline measurements, with a one-year. GWAS was performed using the Illumina HumanOmni1 v1.0 BeadChips on 815 children from 263 Hispanic families and HumanOmni 2.5-8v1 on an additional 43 children. Exome sequencing is being performed on 822 children using NimbleGen capture, followed by Illumina DNA sequencing. Butte NF, Cai G, Cole SA, Comuzzie AG. Viva la Familia Study: genetic and environmental contributions to childhood obesity and its comorbidities in Hispanic population. Am J Clin Nutr 2006;84(3):646-54. PMID: 16960181

  Study phs000616

• Study of Women's Health Across the Nation (SWAN) Repository

  The Study of Womens Health Across the Nation (SWAN) is an active multi-site, multi-disciplinary, longitudinal study of women's health. Initially funded in 1994 by the National Institute on Aging (NIA), the National Institute of Nursing Research (NINR), and the Office of Research on Women's Health (ORWH), the overall goal of SWAN is to describe the natural history of the menopausal transition and the post menopause including biological, behavioral, and psychosocial characteristics. SWAN focuses on the impact of menopause on age-related chronic diseases, such as diabetes, cardiovascular disease, depression, bone loss and osteoporosis, as well as physical and cognitive functioning. SWAN has seven clinical study sites located in six states, two in California, and one each in Chicago, Boston, Detroit area, northern New Jersey and Pittsburgh. The SWAN cohort was recruited from these areas and consists of 3,302 African American, Caucasian, Chinese American, Hispanic and Japanese American women. SWAN participants were enrolled in 1996-1997 and have been seen annually or bi-annually for clinic visits, which include interviews, measurements, and the collection of blood and urine samples. SWAN participants have now been seen for the baseline and 15 follow-up visits.

  Study phs001470

• Genetic Epidemiology of Lung Cancer Consortium GWAS of Familial Lung Cancer

  Familial lung cancer cases were collected by the Genetic Epidemiology of Lung Cancer Consortium (GELCC) recruitment sites: University of Cincinnati, Karmanos Cancer Institute at Wayne State University, Louisiana State University Health Sciences Center-New Orleans, Mayo Clinic, and Medical College of Ohio. Familial cases for this study came from three sources: 1) one case each from families (at least 3 affected lung cancer cases in the family) included in the linkage analysis; 2) one case from linkage-eligible families (at least 3 affected lung cancer cases in the family) but where there were insufficient biospecimens available to make them informative for linkage analysis; and 3) one case from families not eligible for the linkage study with a family history of at least one first or second degree relative affected with lung cancer. Unrelated controls were selected from 1) among the spouses of family members, thus matching on socio-economic status (SES) and ethnicity (typically) of the cases or 2) from case-control studies of lung cancer conducted in the same location in which the linkage families were collected and matched on age, sex, and race. All cases and controls self-reported as European American. Biospecimens used for normal DNA extraction included blood, saliva or mouthwash. Some samples underwent whole genome amplication.

  Study phs000629

• Genome-Wide Analysis for Addiction Susceptibility Genes

  Genome wide analysis for addiction susceptibility genes is an affected sibling pair linkage study using subjects who were patients in methadone replacement treatment programs (MMTP). Such patients are highly addicted to opioids and usually to other addicting substances as well. For entry into the programs, patients had to be at least 18 years of age and had to satisfy DSM-IV criteria for opioid dependence. Despite their common substance use disorder diagnosis, patients enrolled in MMTPs generally have a heterogeneous mix of co-morbid psychiatric disorders including anti-social personality disorder, major depression and anxiety disorders, and often satisfy DSM-IV criteria of substance use disorders other than opioid dependence. Genetic analysis was carried out using genotyping data obtained from a 10K SNP array, and non-parametric linkage was assessed using MERLIN. This resulted in the identification of a linkage peak on 14q that overlapped the NRXN3 gene (neurexin 3), which was previously identified as a potential candidate gene for addiction, and subsequently identified as a target gene in other addiction studies and autism. In version 2 of this study, a text file containing 7704 SNPs with large allele frequency discrepancy as compared to 1000 Genomes is included. Users have the option to exlude these 7704 SNPs.

  Study phs001266

• Cross-Species Single-Cell Analysis of Pancreatic Ductal Adenocarcinoma Reveals Antigen-Presenting Cancer-Associated Fibroblasts

  Cancer-associated fibroblasts (CAFs) are major players in the progression and drug resistance of pancreatic ductal adenocarcinoma (PDAC). CAFs constitute a diverse cell population consisting of several recently described subtypes, although the extent of CAF heterogeneity has remained undefined. Here we employ single-cell RNA-sequencing to thoroughly characterize the neoplastic and tumor microenvironment content of human PDAC tumors. Six human PDAC tumor specimens from six patients were collected, and processed for single-cell RNA-sequencing analysis. Adjacent-normal pancreas tissue was also collected from two of the patients. Tumor samples were digested, and fluorescence-activated cell sorting was used to isolate viable cells. For one tumor sample, viable, CD45-negative, CD31-negative, and EpCAM-negative cells were also isolated to enrich for CAFs. The 10X Chromium platform was then used to isolate single cells for RNA-sequencing analysis. This work has demonstrated the differences in immune cell populations between adjacent-normal and tumor tissues, and identified subpopulations of epithelial cells and CAFs present in PDAC tumors. This high-throughput analysis is a resource to better understand the cell populations present in PDAC, and may ultimately aid in the development of more effective therapies for this deadly malignancy.

  Study phs001840

• Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

  This dataset accompanies the manuscript "Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance Through Serial Biopsies and Comprehensive Analytics". In this study we discuss the clinical implications and consequences of molecular heterogeneity in a metastatic breast cancer patient identified through serial biopsies, multi-omic analysis, and longitudinal patient monitoring, performed through the precision oncology program, Serial Measurements of Molecular and Architectural Responses to Therapy (SMMART). This case study describes a metastatic breast cancer patient with a highly heterogenous tumor that began as ER positive/HER2 negative on diagnosis, then was found to be ER negative/HER2 positive in a metastatic liver lesion (Study biopsy #1), and finally triple negative (TNBC) in another metastatic liver biopsy (Study biopsy #2). Multi-omic assays included clinical genomic panel sequencing, clinical immunohistochemistry, a clinical protein profiling assay (Intracellular Signaling Protein Profiling), RNA sequencing, and RPPA. Here we provide the expression data from RNAseq and RPPA data on Study biopsy #2 for the patient discussed in this case report. Note: The first liver biopsy did not yield sufficient material for RNAseq or RPPA.Raw RNA FASTQ files from Study biopsy #2 of the liver Gene expression (RNAseq) files from Study biopsy #2Protein expression (RPPA) files (level 2, 3, 4) for Study biopsy #2

  Study phs002321

• Comparison Between qPCR and RNA-Seq Reveals Challenges of Quantifying HLA Expression

  Human leukocyte antigen (HLA) class I and HLA class II loci are essential elements of innate and acquired immunity. Their exceptional influence on disease outcome is well documented by GWAS and candidate gene studies. The impact of HLA allelic variation on human disease through allele-specific presentation of antigenic peptides to T cells has been the main focus to determine HLA effects on disease susceptibility/pathogenesis. However, HLA expression levels have also been implicated in disease, adding another dimension to the extreme diversity of HLA that impacts variability in immune responses across individuals. HLA expression levels routinely rely on quantitative PCR (qPCR). An alternative is adoption of high throughput technologies such as RNA-Seq. This provides the opportunity to quantify HLA expression in large datasets, but also allows comparison between RNA-Seq and qPCR. In this study, we analyze expression data for HLA Class I genes for a matched set of individuals (N = 96) by RNA-Seq, qPCR and cell surface expression. Samples were obtained from the Research Donor Program (NCI-Frederick). We observed a moderate correlation between RNA-Seq and qPCR. We suggest technical and biological factors that might contribute to differences in the techniques.

  Study phs003177

• Exploring the Microbiome-Gut-Brain Axis with Respect to Psychoneurological Symptoms for Children with Solid Tumors

  The human body hosts tens of trillions of microbes, a number 10 times greater than the number of human body cells. The collection of these human-associated microbes and their genomes is called the “human microbiome”. More than 90% of these microbes live in the gastrointestinal (GI) tract, representing 500 species on average. With the development of high-throughput sequencing technology and bioinformatics tools (e.g., 16S ribosomal RNA or 16S rRNA sequencing and shotgun metagenomics analysis), recent progress has been made to elaborate the critical role that the gut microbiome plays in human health and disease. A significant disruption (dysbiosis) of the composition and function of the gut microbiome is associated with carcinogenesis, chemotherapeutic metabolism, and treatment-related symptom toxicities. The current state of science on the gut microbiome in cancer has only recently started in animal models and adults, and has not been well investigated in children diagnosed and treated for cancer, nor with respect to associations with cancer treatment-related toxicities. This proposed study will explore the hypothesis that dysbiosis of the gut microbiome is associated with cancer treatment-related GI and psychoneurological symptoms. We will collect both stool samples (for the gut microbiome) and patient-reported outcomes across chemotherapy.

  Study phs002960

• A Chromatin Accessibility Atlas of the Developing Human Telencephalon

  Gene expression differs between cell types and regions within complex tissues such as the developing brain. To discover regulatory elements underlying this specificity, we generated genome-wide maps of chromatin accessibility in nine anatomically-defined regions of the developing human telencephalon. Additionally, we defined the histone modification landscape of the prefrontal cortex and generated chromatin accessibility maps of its upper and deep layers. We predicted a subset of open chromatin regions (18%) that are most likely to be active enhancers, many of which are dynamic with 26% differing between early and late mid-gestation and 28% present in only one brain region. These predicted regulatory elements (pREs) are enriched proximal to genes with expression differences across developmental stages, regions, and cortical laminae; they harbor distinct sequence motifs that suggest potential upstream regulators. We leveraged this atlas to predict and validate novel regulatory elements of genes that control cortex laminar identity and genes associated with autism spectrum disorder (ASD). These include enhancers proximal to FEZF2 and BCL11A that were validated in mouse, and an enhancer of ASD gene SLC6A1 containing two functional de novo mutations in individuals with ASD whose enhancer function we validated via CRISPRa. We also include data for transcription factor binding in mid-fetal cortex tissues, using CUT&RUN methods.

  Study phs002033

• Integrative Gene Regulatory Network Analysis Discloses Key Driver Genes of Fibromuscular Dysplasia

  Fibromuscular dysplasia (FMD) is a poorly understood vascular disease that can lead to hypertension, stroke, myocardial infarction and even death. In 2013 we initiated the DEFINE study (ClinicalTrials.gov Identifier: NCT01967511), which has now recruited > 440 subjects and which aims to unravel the pathobiological mechanisms of this disease. Here, by integrating DNA genotype and RNA sequence data from primary fibroblasts of 83 FMD patients and 71 matched healthy controls from the DEFINE study, and its precursor the CAUSE study, we inferred 18 gene regulatory co-expression networks, four of which were found to act together as an FMD-associated super network in the arterial wall. Molecular studies indicated that this super network, termed SN-A and with the top key driver gene UBR4, governs multiple aspects of vascular cell physiology and functionality, including collagen/matrix production. The effects of UBR4 knockdown were also investigated in commercially available aortic smooth muscle and fibroblast cell lines by RNA sequencing, and these results are included in these datasets.Note, that of the 154 subjects in this analysis, 62 did not provide consent to have their genomic data made publicly available. Therefore the human subject data available here is from the 92 study participants who provided written informed consent to share their deidentified genomic data publicly.

  Study phs003674