13380 results for ""60+mice"+"6+weeks"+diet+study+2014+2017+DOI"

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• Drug Signatures for Prediction and Mitigation of Toxicity

  The overall goal of the drug signatures for prediction and mitigation of toxicity study is to use genomic and proteomic high-throughput measurements as the basis for computational analysis that integrates network analyses with structural constraints and dynamical models in multiple cell types to identify signatures that predict toxicity induced by 55 FDA-approved chemotherapeutic drugs and potential mitigation of this toxicity. Specifically, we have recruited and pre-screened healthy individuals to be included in our study. Ninety six male and female individuals that satisfied the initial pre-screening for the study and their sex, age, race/ethnicity recorded through an enrollment questionnaire were consented. Eighty five underwent a formal and thorough medical health screening. The evaluation involved assessment of all inclusion and exclusion criteria, a full medical history, measurement of weight, height, waist and hip circumference, heart rate, blood pressure, respiratory rate, and oxygen saturation, a physical exam and an electrocardiograph (ECG). Blood was drawn for analysis of clinical relevant parameters. A pregnancy test was included for female participants. All blood draws and pregnancy tests were sent to a certified clinical laboratory for clinical analysis. Of the 85 subjects that were screened 42 (48.3%) were deemed eligible for final inclusion. Of these 42, one declined to undergo skin biopsy and/or venesection and one subject didn’t show up for the scheduled biopsy, leaving 40 clinically healthy subjects on which a skin biopsy and venesection was performed. Fibroblast lines were established from the skin biopsies. Induced pluripotent cells (iPSC) were generated from the established fibroblast lines of these 40 clinically healthy racially diverse male and female study participants who ranged in age from 22 and 61 years through reprogramming using either the mRNA or Sendai-virus methods. One clone from each of the 40 iPSC line was fully characterized for normal karyotype, short-tandem repeat matching to the original fibroblast line (authentication), pluripotency by select pluripotent marker expression via immunocytochemistry and by mRNAseq-based PluriTest analysis, and whole-genome sequencing.

  Study phs002088

• Center for Common Disease Genomics [CCDG] - Cardiovascular: TexGen

  Cardiovascular disease (CVD), especially coronary heart disease, heart failure and cerebrovascular disease remain the leading causes of death in men and women across all race groups in the United States. Substantial evidence exists for genetic factors underlying CVD risk, and their discovery offers an opportunity to enhance understanding of disease mechanisms, to provide specific diagnostic and prognostic indicators, and to identify novel therapeutic targets. The Centers for Common Disease Genomics (CCDG) are a large-scale genome sequencing effort undertaken as a collaboration to identify rare risk and protective alleles for common chronic diseases, with a current focus on early onset heart disease, hemorrhagic stroke, and autism. In this study, whole genome sequencing (WGS) was performed in 6,146 individuals with any personal or family history of CVD from the TexGen study who were recruited from several institutions in the Texas Medical Center located in Houston, Texas. The participants included patients who were admitted with a variety of diagnoses including acute coronary syndromes, strokes, and transient ischemic attacks, or who underwent percutaneous coronary interventions or coronary artery bypass grafting (CABG) (Virani SS et al. Am J Cardiology 107:1504-1509, 2011). Patients in the TexGen cohort with a confirmed diagnosis of acute coronary syndrome (ACS) or CABG when discharged from the hospital between 2001-2008 were eligible for a follow-up study of recurrent myocardial infarction (Virani SS et al. Circulation J 76:950-956, 2012), while those presenting with ACS beginning in 2007 were recruited for an investigation of the role of depressive symptoms in the risk of major adverse coronary events (Sanner J et al. Biol Res Nurs 20:168-176, 2018). In addition, the initial criterion for enrollment in a third TexGen sub-study undertaken between 2007 and 2013 was the occurrence of premature acute myocardial infarction in men ≤ 50 years and women ≤ 55 years in order to establish a blood sample collection resource with the intention of localizing genes that contribute to disease risk. This definition was later expanded to include individuals with a clinical history of premature coronary heart disease such as CABG or percutaneous coronary interventions.

  Study phs003010

• Investigation of Brain Nitrogen Metabolism in Partial Ornithine Transcarbamylase Deficiency (OTCD) Using 1H MRS, DTI, and fMRI

  This is a case controlled, observational study. This project studies cognitive and motor dysfunction in adult and pediatric patients who are female carriers of ornithine transcarbamylase deficiency (OTCD) or are males with late onset presentation (outside of the newborn period) of OTCD, utilizing state of the art MRI (magnetic resonance imaging), a non-invasive technique. This project seeks to improve our understanding of the underlying neural mechanisms that contribute to metabolic, cognitive, sensory and motor abnormalities in urea cycle disorders, which although individually rare, collectively constitute a major cause of neonatal encephalopathy, leading to significant morbidity and mortality. As a result of this study, a greater understanding of the anatomic, cognitive, motor, and biochemical underpinnings of neurologic damage attributable to this metabolic disorder will be gained. Experimental approaches will combine sensory, cognitive and motor testing with structural, functional and molecular magnetic resonance imaging to study symptomatic and asymptomatic heterozygous female carriers of X-linked ornithine transcarbamylase deficiency (OTCD), and late onset hemizygous males. Participants to be included in the studies ranged from ages 7-60 years and were compared to an age-matched typically developed (TD) comparison group. For our research, we use anatomic MRI, functional Magnetic Resonance Imaging (fMRI), and magnetic resonance spectroscopy (MRS) to monitor brain activity. The technique of fMRI provides detailed maps of the brain areas underlying human mental activities. By using fMRI, we are able to observe how the brain is functioning while a person is performing a specific task, such as reading. We can not only observe differences in the structure of the brain, but can also measure differences in brain function and activity as well. This information will ultimately be used to provide a basis for designing more effective interventions and methods for early identification of learning disabilities in patients with OTCD and related disorders. We will also use MRS to study various brain chemicals such as glutamine using the non-invasive MRI imaging techniques.

  Study phs001296

• National Institutes of Health The Cancer Genome Atlas (TCGA)

  The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. TCGA is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), which are both part of the National Institutes of Health, U.S. Department of Health and Human Services. TCGA projects are organized by cancer type or subtype. Click here for a current list of cancer types selected for study in TCGA. Data from TCGA (e.g., gene expression, copy number variation and clinical information), are available via the Genomic Data Commons (GDC). Data from TCGA projects are organized into two tiers: Open Access and Controlled Access. Open Access data tier contains data that cannot be attributed to an individual research participant. The Open Access data tier does not require user certification. Data in Open Access tier are available in the TCGA Data Portal. Controlled Access data tier contains individual-level genotype data that are unique to an individual. Access to data in the Controlled Access data tier requires user certification through dbGaP Authorized Access. Controlled Access data types consist of the following: Individual germline variant data (SNP .cel files) Primary sequence data (.bam files), which are available at GDC Clinical free text fields Exon Array files (for Glioblastoma and Ovarian projects only) NOTE: TCGA strives to release most data in the open access tier. Individual genotype or sequence files are prominent exceptions. Commonly requested files such as descriptions of somatic mutations or clinical data are open access. Please go to this page: https://tcga-data.nci.nih.gov/docs/publications/ to access all data associated with TCGA tumor specific publications. The TCGA study is utilized in the following dbGaP substudies. To view genotypes and other molecular data collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000178 TCGA study. phs000854 Genome-wide Analysis of Noncoding Regulatory Mutations in Cancer

  Study phs000178

• Identification of Somatic Changes in Tumors from Fanconi Anemia Patients

  This study focused on the identification of genomic signatures present in tumors from Fanconi anemia patients. Fanconi anemia is a rare hereditary disease caused by defects in DNA interstrand crosslink repair. The primary patient phenotypes are bone marrow failure and cancer predisposition. We concentrated on squamous cell carcinomas and used whole genome Illumina sequencing (22 tumor samples and 12 normal samples) , whole exome sequencing (37 tumor samples and 33 normal samples), PacBio long-read whole-genome (nine tumor and four normal samples),10X linked-read whole-genome sequencing, 10x single-cell/nuclei 3’ RNA sequencing (three tumor samples), 10x Visium spatial transcriptomics (one tumor sample), EPIC 850K methylation array (six samples), and bulk RNAseq (six tumor samples) to identify somatic changes present in tumors. The study aimed to identify changes that drive tumorigenesis in Fanconi anemia, give insight into the early development and aggressive nature of these tumors, and suggest therapeutic avenues for these patients. Another goal was to compare the genomic changes identified in tumors from Fanconi anemia patients with sporadic head and neck cancers. This study demonstrated that the tumors from Fanconi anemia individuals are generally not driven by HPV. Instead, they acquire mutations in the p53 tumor suppressor. The main characteristic of the tumors is the presence of a high number of structural variants in the form of small deletions, unbalanced translocations, and fold-back inversions, which often form complex rearrangements. These rearrangements result in amplifications and deletions of a multitude of oncogenes and tumor suppressors, respectively. The study also shows that lack of the Fanconi anemia DNA repair pathway leads to an epithelial-to-mesenchymal transition in a mouse model and in human samples that may influence the behavior of tumors in Fanconi anemia. Finally, comparing genomic changes in Fanconi anemia and sporadic tumors of the head and neck, we propose that the structural variants present in sporadic cancer result in a functional deficiency of the Fanconi anemia DNA repair pathway.

  Study phs002652

• Myeloproliferative Neoplasms (MPN) Exome Validation Study

  Experiments using targeted pulldown methods will be sequenced to validate findings in the exomes of patients with Myeloproliferative Neoplasms (MPN).

  Dataset EGAD00001000619

• BMI EWAS summary stats

  Summary statistics for a multi-cohort epigenome-wide association study. This includes summary statistics (effect-size, standard error, p-value) for 470,000 methylation markers.

  Dataset EGAD00010001029

• Gene Expression Profiling for study EGAS00001004165

  Gene Expression Profiling from 44 Mantle Cell Lymphoma cases

  Dataset EGAD00010001842

• Illumina BeadArray SNP arrays

  SNP measurement. Illumina BeadArray SNP arrays for the study "Molecular characteristics in Burkitt lymphoma over age groups"

  Dataset EGAD00010002137

• Thoracic Patient-Derived Xenografts

  Targeted capture sequencing of 341 cancer associated genes in thoracic patient-derived xenografts.

  Study phs001192

• USH genes sequencing

  Sequencing of a panel including the whole genomic sequence of Usher genes.

  Study EGAS50000000476

• Aggressive PDACs show hypomethylation of repetitive elements and the execution of an intrinsic IFN program linked to a ductal cell-of-origin

  Study EGAS00001004660

• TOPARP-B patient cell-free DNA WGS

  Sequencing files for TOPARP-B patients as described in manuscript

  Study EGAS50000000280

• COVID_19_Challenge_2_WOOE_RNA_Managed_Access

  Single-cell profiling of healthy adult volunteers that were inoculated with SARS-CoV-2.

  Study EGAS00001007636

• BLUEPRINT EpiVar Whole Genome Sequencing

  BLUEPRINT EpiVar Whole Genome Sequencing

  Study EGAS00001000689

• FFPE_normals_v2_gbm_wtsi_panel

  Targeted pulldown of approx 60 ffpe normal samples to use as normal controls

  Study EGAS00001002124

• Whole exome sequencing of 103 pairs BLCA-CN

  We sequenced 50M exomes of 103 pairs bladder cancer of chinese

  Study EGAS00001000677

• BLUEPRINT EpiVar ChIP-seq for naive CD4+ T-cells

  BLUEPRINT EpiVar ChIP-seq for naive CD4+ T-cells

  Study EGAS00001000753

• Exome_sequencing_Parkinson_s_disease_patients

  In this project we will sequence the exomes of 250 patients with Parkinson's disease

  Study EGAS00001000151

• Enrichment of homologous recombination repair alteration in prostate cancer brain metastases

  Whole-exome sequencing profiling of prostate cancer brain metastases

  Study EGAS00001005091

• RNA-sequencing of HCC patients undergoing sorafenib treatment

  RNA-sequencing of hepatocellular carcinomas at various stages of sorafenib treatment

  Study EGAS00001005662

• Brain_Disease_Wellcome_Leap_Delta_Tissue_RNA

  Utilising Single-Nucleus sequencing to investigate how the tumour microenvironment regulates glioblastoma cell states.

  Study EGAS00001005800

• Effects of nucleases on cell-free extrachromosomal circular DNA

  Effects of nucleases on cell-free extrachromosomal circular DNA

  Study EGAS00001005873

• Exome_NanoSeq__Thyroid_

  Exome NanoSeq in thyroid from a number of donors, both healthy and with pathology.

  Study EGAS00001007175

• Targeted_NanoSeq___Thyroid

  Targeted NanoSeq in thyroid from a number of donors, both healthy and with pathology.

  Study EGAS00001007647

• Reference epigenome IPS01_N_Fibroblast_smRNA-Seq data generated from KEP study

  A IPS01_N_Fibroblast_smRNA-Seq single end data for iPSC(Oct4)

  Dataset EGAD00001003501

• Reference epigenome CKD25_C_Podo_WGBS data generated from KEP study

  A CKD25_C_Podo_WGBS paired end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003470

• Reference epigenome CKD24_C_Podo_WGBS data generated from KEP study

  A CKD24_C_Podo_WGBS paired end data for Podocytes(CD90(-) Podocalyxin(+), kidney)

  Dataset EGAD00001003469

• Reference epigenome IPS04_X_Fibroblast_mRNA-Seq data generated from KEP study

  A IPS04_X_Fibroblast_mRNA-Seq paired end data for iPSC(Oct4)

  Dataset EGAD00001003491

• HCC.GNE exome dataset

  Exome read sequences for 30 tumor-normal pairs for the study "Diverse modes of genomic alterations in Hepatocellular Carcinoma".

  Dataset EGAD00001000885

• Reference epigenome OB57_D_PreA_WGBS data generated from KEP study

  A OB57_D_PreA_WGBS paired end data for Preadipocyte(fat)

  Dataset EGAD00001003480

• Reference epigenome IPS01_N_Fibroblast_mRNA-Seq data generated from KEP study

  A IPS01_N_Fibroblast_mRNA-Seq paired end data for iPSC(Oct4)

  Dataset EGAD00001003488

• Reference epigenome IPS04_X_Fibroblast_smRNA-Seq data generated from KEP study

  A IPS04_X_Fibroblast_smRNA-Seq single end data for iPSC(Oct4)

  Dataset EGAD00001003504

• BASIS Genome Validation Study

  Bespoke validation experiments will be performed on ER+ Breast Cancer cases to confirm the presence of mutations found in whole genome sequencing.

  Dataset EGAD00001000661

• BGI study for primary and metastatic Chinese lung adenocarcinomas

  We sequenced 205 patients who were suffering NSCLC with Exome sequencing method.

  Dataset EGAD00001001398

• Reference epigenome SMC07 mRNA-Seq data generated from KEP study

  SMC07 mRNA-Seq paired end data

  Dataset EGAD00001007174

• Reference epigenome Pancreas-Islet07 WGBS data generated from KEP study

  Pancreas-Islet07 WGBS paired end data

  Dataset EGAD00001007146

• Reference epigenome Fat-adipocyte03 WGBS data generated from KEP study

  Fat-adipocyte03 WGBS paired end data

  Dataset EGAD00001007147

• Reference epigenome Fat-adipocyte04 WGBS data generated from KEP study

  Fat-adipocyte04 WGBS paired end data

  Dataset EGAD00001007148

• Reference epigenome SMC05 mRNA-Seq data generated from KEP study

  SMC05 mRNA-Seq paired end data

  Dataset EGAD00001007173

• Reference epigenome SMC08 mRNA-Seq data generated from KEP study

  SMC08 mRNA-Seq paired end data

  Dataset EGAD00001007175

• Reference epigenome SMC09 mRNA-Seq data generated from KEP study

  SMC09 mRNA-Seq paired end data

  Dataset EGAD00001007176

• Reference epigenome Fat-adipocyte05 WGBS data generated from KEP study

  Fat-adipocyte05 WGBS paired end data

  Dataset EGAD00001007149

• Reference epigenome Islet-derived-iPSC04 WGBS data generated from KEP study

  Islet-derived_iPSC04 WGBS paired end data

  Dataset EGAD00001007877

• Reference epigenome Islet-derived-MSC08 WGBS data generated from KEP study

  Islet-derived_MSC08 WGBS paired end data

  Dataset EGAD00001007876

• Reference epigenome ADMSC08 mRNA-Seq data generated from KEP study

  ADMSC08 mRNA-Seq paired end data

  Dataset EGAD00001007156

• Reference epigenome ADMSC05 mRNA-Seq data generated from KEP study

  ADMSC05 mRNA-Seq paired end data

  Dataset EGAD00001007153

• Reference epigenome ADMSC06 mRNA-Seq data generated from KEP study

  ADMSC06 mRNA-Seq paired end data

  Dataset EGAD00001007154

• Reference epigenome ADMSC07 mRNA-Seq data generated from KEP study

  ADMSC07 mRNA-Seq paired end data

  Dataset EGAD00001007155

• Reference epigenome SMC01 mRNA-Seq data generated from KEP study

  SMC01 mRNA-Seq paired end data

  Dataset EGAD00001007169