13384 results for ""pdc"+"heritage+language"+census+study"

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• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002041

• Genome and transcriptome sequence data from an ovarian cancer patient

  Genome and transcriptome sequence data from an ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002039

• Genome and transcriptome sequence data from an adrenal cancer patient

  Genome and transcriptome sequence data from an adrenal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002037

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002036

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002035

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002034

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002033

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002031

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002030

• Genome and transcriptome sequence data from an ovarian granulosa patient

  Genome and transcriptome sequence data from an ovarian granulosa patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002029

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002028

• Genome and transcriptome sequence data from a colorectal cancer patient

  Genome and transcriptome sequence data from a colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002027

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002026

• Genome and transcriptome sequence data from a colorectal cancer patient

  Genome and transcriptome sequence data from a colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002025

• Genome and transcriptome sequence data from a lung cancer patient

  Genome and transcriptome sequence data from a lung cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002023

• Genome and transcriptome sequence data from a colorectal cancer patient

  Genome and transcriptome sequence data from a colorectal cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002022

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002021

• Genome and transcriptome sequence data from a metastatic NPC patient

  Genome and transcriptome sequence data from a metastatic NPC patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002020

• Genomic variants in 121 genes associated with ovarian cancer in cancer tissue and derived organoids

  High-grade serous ovarian cancer (HGSOC) likely originates from the fallopian tube (FT) epithelium, but advanced stages are mostly found outside the FT. We used ex-vivo cultures of HGSOC and knock-out of tumor suppressors in FT organoids to study changes in epithelial cells and niche requirements for normal and transformed FT cells. We found that transformed cells require BMP signaling and are growth arrested in Wnt rich medium. A SureSelectXT Automation Custom Capture Library (Agilent) target enrichment panel was designed. The enrichment panel comprised all coding exons of 121 genes associated with ovarian cancer. Capture was performed according to the manufacturer’s instructions using an NGS Workstation Option B (Agilent) for automated library preparation starting with 3 μg DNA per sample. Sequencing was performed on a Illumina Hiseq 2500 system gnerating 2x100bp paired end reads and a target coverage of >200 per sample. Sequence reads were mapped to the haploid human reference genome (hg19) using BWA. Variants where called with FreeBayes v1.1.

  Dataset EGAD00001005279

• Genome and transcriptome sequence data from an uveal melanoma patient

  Genome and transcriptome sequence data from an uveal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005824

• Genome and transcriptome sequence data from a colon cancer patient

  Genome and transcriptome sequence data from a colon cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005826

• Genome and transcriptome sequence data from an ovarian cancer patient

  Genome and transcriptome sequence data from an ovarian cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005829

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005852

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005838

• Genome and transcriptome sequence data from a pancreatic cancer patient

  Genome and transcriptome sequence data from a pancreatic cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005841

• Genome and transcriptome sequence data from a chondrosarcoma patient

  Genome and transcriptome sequence data from a chondrosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005848

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005849

• Genome and transcriptome sequence data from a metastatic melanoma patient

  Genome and transcriptome sequence data from a metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001005851

• FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls.

  FASTQ files of the polyA+ (oligo-dT) RNA-Seq dataset from the POPS SGA (Small for Gestational Age) samples and their matched controls. The POP study placental biopsies were collected within 30 minutes of birth and flash frozen in RNAlater (ThermoFisher). For each biopsy, total placental RNA was extracted from approximately 5 mg of tissue using the “mirVana miRNA Isolation Kit” (Ambion) followed by DNase treatment (“DNA-free DNA Removal Kit”, Ambion). RNA quality was assessed with the Agilent Bioanalyzer and all the samples with RIN values ≥ 7.0 were used in the downstream experiments. RNA-libraries were prepared from 1g of total placental RNA with the TruSeq Stranded mRNA Library Prep Kit (Illumina) which captures polyA-tailed transcripts by oligo-dT beads, then pooled and sequenced (single-end, 50bp) using a Single End V4 cluster kit and Illumina HiSeq2500

  Dataset EGAD00001006304

• Colorectal cancer cells possess an equipotent capacity to enter a developmental pausing-like state to survive chemotherapy

  Cancer cells enter a reversible drug tolerant persister (DTP) state to evade death from both chemotherapies and targeted agents. It is increasingly appreciated that the DTP state is an important driver of therapy failure and tumor relapse. We combined cellular barcoding and mathematical modeling in patient-derived colorectal cancer xenograft models to identify and characterize the cancer cells capable of generating DTPs in response to standard-of-care chemotherapy. Barcode analysis revealed no loss in clonal complexity of tumors that entered the DTP state and recurred following treatment cessation. Our data fits a mathematical model in which all cancer cells, and not a small subpopulation, possess an equipotent capacity to enter the DTP state. Mechanistically, we determined that DTPs display remarkable transcriptional and functional similarities to diapause, a reversible state of suspended embryonic development triggered by unfavorable environmental conditions. Our study provides new insights into how cancer cells use a developmentally conserved mechanism to drive the DTP state pointing to novel therapeutic opportunities to target diapause-like DTPs.

  Dataset EGAD00001006849

• The polarity and specificity of antiviral T lymphocyte responses determine susceptibility to SARS-CoV-2 infection in cancer patients and healthy individuals

  We monitored patient's anti SARS-CoV-2 immune responses using an in vitro cross presentation assay. The goal of this study was to identify immune correlates of clinical protection against SARS-CoV-2 infection. Briefly, peripheral blood mononuclear cells of patient were divided into a monocyte and lymphocyte. Monocyte were differentiated into monocyte derived dendritic (mo-DC)cells using GM-CSF and Interferon alpha. Mo-DC were then loaded with SARS-CoV-2 culture lysates , or VeroE86 lysates. SARS-CoV-2 loaded mo-DC were then used to stimulates their autologous lymphocytes and T cell cytokine secretion was monitored in the supernatant. We discriminated patients producing IL-2 and patients producing IL-5. RNA sequencing was performed for 18 patients, to identify gene profile associated with IL-2 or IL-5 production.

  Dataset EGAD00001008538

• Genomics of acral lentiginous melanoma

  Melanoma is the most aggressive type of skin cancer, causing about 75% of dermatological cancer deaths. Acral lentiginous melanoma (ALM) is the most common subtype of melanoma in admixed Latin American populations, but very few tumour genomes and exomes, all from European-descent individuals, have been analysed across several studies. Because of this, the genomic landscape of ALM is mostly unknown. Our aim in this project is to define this landscape and identify driver somatic alterations by whole-exome sequencing a collection of ALM germline/tumour paired FFPE samples from the National Cancer Institute of Mexico. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010126

• Pediatric Patient-Derived-Xenograft development in MAPPYACTS – international pediatric cancer precision medicine trial in relapsed and refractory tumors

  Pediatric patients with recurrent and refractory cancers are in most need for new treatments. This study developed patient-derived-xenograft (PDX) models within the European MAPPYACTS cancer precision medicine trial (NCT02613962). To date, 131 PDX models were established following heterotopical and/or orthotopical implantation in immunocompromised mice: 76 sarcomas, 25 other solid tumors, 12 central nervous system tumors, 15 acute leukemias, and 3 lymphomas. PDX establishment rate was 43%. Histology, whole exome and RNA sequencing revealed a high concordance with the primary patient’s tumor profile, human leukocyte-antigen characteristics and specific metabolic pathway signatures. A detailed patient molecular characterization, including specific mutations prioritized in the clinical molecular tumor boards are provided. Ninety models were shared with the IMI2 ITCC Paediatric Preclinical Proof-of-concept Platform (IMI2 ITCC-P4) for further exploitation. This new PDX biobank of unique recurrent childhood cancers provides an essential support for basic and translational research and new treatments development in advanced pediatric malignancies.

  Dataset EGAD00001011048

• RNA-seq dataset: Single-cell spatial analysis of pediatric high-grade glioma reveals a novel population of immunosuppressive and tumor-promoting SPP1+/GPNMB+ myeloid cells

  Our study utilizes two novel techniques, cyclical immunofluorescence imaging and single-cell spatial transcriptomics, to spatially map the tumor microenvironment of a large sample set of pediatric high-grade gliomas (pHGG). Using these methods, we have identified an abundant immunosuppressive myeloid cell population that has not been described in the context of pediatric high-grade gliomas. We validate our findings using an in vitro assay, spatial analysis on additional pHGG biopsies, independent spatial transcriptomic data, bulk RNA sequencing data of an expanded cohort of in-house patients, and publicly available bulk RNA sequencing data of an even larger cohort of pHGG patients.

  Dataset EGAD00001015450

• Genomic Advances in Sepsis (GAinS) genotyping

  This cohort comprises a subset of patients enrolled in the Genomic Advances in Sepsis (GAinS) study, an established biobank of adult sepsis patients. Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Patients with sepsis due to community acquired pneumonia or faecal peritonitis were recruited from 35 hospitals across the UK from 2005-2018, with samples for functional genomics and detailed clinical information collected over the first five days of ICU admission to investigate how host genetics affects the individual repsonse to sepsis. DNA was extracted from buffy coat or whole blood samples using the Qiagen DNA extraction protocol, the automated Maxwell Blood purification kit (Promega), or the QIAamp Blood Midi kit protocol (Qiagen). Genotyping data were generated using the Illumina HumanOmniExpress BeadChip (295 patients), the Infinium CoreExome BeadChip (655 patients), and the Infinium Global Screening Array BeadChip (307 patients). Genotyping QC and imputation into the Haplotype Reference Consortium was perfomed within each batch. The datasets were combined and following post-imputation filtering data were available on 1168 samples.

  Dataset EGAD00001015369

• Mapping genetic variants that underlie gene regulation in intestinal cell types to identify novel, validated, Crohn’s disease drug targets

  Biopsies from the terminal ileum and rectum of healthy individuals and terminal ileum and blood from Crohns disease patients are collected and processed single cells and processed for single-cell RNA-sequencing using 10X Genomics 3' v3 and v3.1 and Illumina sequencing. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003647

• Analyzing the expression profiles of genes in ureters with and without indwelling stents using RNAseq 

  The objective of the work is to explore the pathways and mechanisms driving inflammation and fibrosis in stented ureters. In total, 6 pigs underwent cystoscopic unilateral ureteral stent insertion for 14 days. Ureteral tissue was harvested in 3 pigs, while the remaining 3 pigs had their stents removed, and were recovered for 7 days. Three separate pigs served as controls. Stents cause significant inflammation and fibrosis of ureters. Gene set enrichment analysis confirmed fibrotic changes and tissue proliferation and suggests that epithelial-mesenchymal transition is a driver of fibrosis.

  Study EGAS00001006855

• eMERGE: Northwestern (NUgene) WGS

  The NUgene Project is a biorepository with longitudinal medical information from participating patients at Northwestern Medicine affiliated hospitals and outpatient clinics. Participants' DNA samples are coupled with data from a self-reported questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 3 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated enterprise data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. The electronic MedicalRecords and Genomics (eMERGE) Network is a consortium of 9 clinical sites with EMR linked DNA biobanks, including Northwestern University and its NUgene biobank, funded by the NHGRI (National Human Genome Research Institute) to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 100,000 individuals using EMR-derived phenotypes and DNA from linked biorepositories. Using electronic phenotyping methods, the consortium has been and is using DNA samples from all participating sites to explore the genetic determinants of approximately 80 phenotypes, including both diseases and traits, for which the electronic phenotyping algorithms have or are being published on PheKB.org. Thus, for the eMERGE network, ~900 NUgene subjects were selected, as described in the study inclusion/exclusion criteria section below, to be genotyped using whole genome sequencing (WGS), for use in the eMERGE network as eMERGE subjects. The criteria used below were selected so that these subjects will likely meet the criteria to be cases and/or controls, of diverse races and/or ethnicities, for at least 1 of the ~80 phenotypes being studied within eMERGE, and could be recontacted for future research if needed.

  Study phs001191

• Development and Validation of a Disability Severity Index for Charcot-Marie-Tooth Disease (CMT)

  In Charcot-Marie-Tooth Disease (CMT) or inherited neuropathy research studies, it is the researcher who has selected what they believe to be important markers of impairment in function in patients. For example, it has been inferred that the wearing of ankle-foot-orthosis (AFOs), the use of walking aids such as canes, or the use of wheelchairs, are appropriate markers for “mild”, “moderate” or “severe” disability, respectively. Whether patients agree with this classification is unknown. By understanding what patients classify as mild, moderate and severe disability in CMT, we will know what our treatments need to target, to have a meaningful impact on the patients' functional status. Primary objective: The purpose of this study is to compare patient and healthcare provider impressions of what constitutes mild, moderate and severe disability in CMT. Target population: 200 patients who have self-registered at the Inherited Neuropathy Consortium Contact Registry, a web-based contact registry developed and supported by the Data Management and Coordinating Center (DMCC) for the Rare Diseases Clinical Research Consortium (RDCRN), located at the University of South Florida, and 200 health care professionals attending conferences about CMT, such as the 4th International CMT Consortium to be held in Potomac, Maryland, June 29-July 1, 2011 and the MDA Clinic Directors meeting in Las Vegas, NV March 4-7, 2012. Methods: A brief, anonymous, 20-item survey, in which we measure what the physician and the patient think are important indicators of disability in CMT, will be distributed by paper to 200 health care professionals, and via an online link to 200 patients self-registered with the RDCRN contact registry. Out of the 200 patients, approximately 25 patients will be requested to take the survey twice in a 2 to 4 week period. Analysis: We will measure the agreement between items in the physician and patient groups, and use items with high agreement in a Disability Severity Index.

  Study phs001295

• NICHD Genomic and Proteomic Network for Preterm Birth Research (GPN)

  We performed genome-wide association studies (GWAS) to study the Spontaneous Preterm birth (SPTB). Maternal and neonatal DNA from 743 SPTB (20 to and less than 34 weeks), and 752 controls (39 to and less than 42 weeks) who fully consented for public research usage were collected from participants in several clinical centers in Alabama, Illinois, New York, North Carolina, Rhode Island, Texas, and Utah. Cases were 1:1-matched with controls according to race/ethnicity (White, Hispanics, African Americans, and Others), maternal age (<20, 20-29, 30-39, 40+), and parity (yes or no). To determine the case-control status for each participant, a Gestational Age (GA) was determined. DNA samples were taken from blood or saliva if blood was not available. Automated DNA extractions were performed on the Qiagen M48 robot, and samples were organized in 96-well plates with barcoding and sample tracking systems. Subsequent manipulations were performed on the Biomek FX liquid handling workstation with 96-channel pipetting. DNA quantitation was performed by dye-based assay on a Molecular Devices SpectraMax Plus plate reader. Samples were genotyped using Affymetrix Genome-Wide Human SNP Array 6.0. This work was conducted at the Microarray Facility at the University of Pennsylvania. Patient data were collected through chart reviews and patient interviews, which included Demographic information (parental age, race, ethnicity, etc.); Medical history (pre-pregnancy weight, height, medications, STD history, medical conditions, etc.); Social history (marital status, years of education, alcohol use and tobacco use); Obstetrical history including outcome of all prior pregnancies and dates of termination; History of preterm labor or premature rupture of membranes symptoms, evaluation or hospitalization for those symptoms in current pregnancy; Medications taken during current pregnancy; History of cervical evaluation (manually or ultrasonographically) or fetal fibronectin measurements; Pregnancy complications; Labor (type, indications, membrane status, and induction method); Delivery type and indications for cesarean section; Neonatal outcome (sex, weight, length, Apgar score, neonatal complications, admission to intensive care unit, etc.); and Maternal family history of SPTB.

  Study phs000714

• Hematopoietic Cell Transplant for Sickle Cell Disease (HCT for SCD)

  The Center for International Blood and Marrow Transplant Research (CIBMTR) is a hematopoietic cell transplant registry that was established in 1972 at the Medical College of Wisconsin. The overarching goal of the registry is to study trends in transplantations and to advance the understanding and application of allogeneic hematopoietic cell transplantation for malignant and non-malignant diseases. Included in this dataset are children, adolescents and young adults with severe sickle cell disease who received an allogeneic hematopoietic cell transplant in the United States and provided written informed consent for research.Hematopoietic cell transplant for sickle cell disease is curative. Offering this treatment for patients with severe disease is challenging as only about 20-25% of patients expected to benefit have an HLA-matched sibling. Consequently, several transplantations have utilized an HLA-matched or mismatched unrelated adult donor and HLA-mismatched relative. Transplantation strategies have also evolved over time that has included transplant conditioning regimens of varying intensity, grafts other than bone marrow and novel approaches to overcome the donor-recipient histocompatibility barrier and limit graft-versus-host disease. The data that is available for sickle cell disease transplants have been utilized to report on outcomes after transplantation and compare outcomes after transplantation of grafts HLA-matched related, HLA-mismatched related, HLA-matched and HLA-mismatched unrelated donors. Collectively, these data have advanced our knowledge and understanding of hematopoietic cell transplant for this disease. These data can also serve as "contemporaneous controls" for comparison with other more recent curative treatments like gene therapy and gene editing.Data available for request include allogeneic hematopoietic cell transplants for sickle cell disease (Hb SS and Hb Sβ thalassemia) in the United States from 1991 to 2019. Follow-up data through December 2020 are available.Instructions for requesting individual-level data are available on BioData Catalyst at https://biodatacatalyst.nhlbi.nih.gov/resources/data/. Apply for data access in dbGaP. Upon approval, users may begin accessing requested data in BioData Catalyst. For questions about availability, you may contact the BioData Catalyst team at https://biodatacatalyst.nhlbi.nih.gov/contact.

  Study phs002385

• National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK): Identification of VUR genes by exome sequencing

  Primary vesicoureteric reflux (PVUR), or non-syndromic VUR, is the most common type of congenital anomaly of the kidney and the urinary tract (CAKUT). PVUR is the single most important risk factor for pyelonephritis and renal parenchymal scarring in the pediatric age group. Renal parenchymal scarring due to PVUR is referred to as reflux nephropathy and is a major cause of end stage kidney disease requiring dialysis and kidney transplantation in children. PVUR shows familial aggregation; however, the specific genetic cause(s) of PVUR is unknown despite a number of linkage studies. Reasons for this include: variable expression of the disease, difficulty with case ascertainment, genetic heterogeneity and lack of large pedigrees that can facilitate locus identification. We have ascertained a large 97 member PVUR kindred spanning five generations. We performed a genome-wide linkage study (GWLS) on this family and obtained a significant genome-wide LOD score of 3.3 on chromosome 6p. We performed exome sequencing on affected individuals in the family and identified mutations in tenascin XB (TNXB) as a cause of familial VUR. The proposed studies have the following specific objectives: a) to define the role of tenascin genes in the etiology of PVUR, and b) to identify new PVUR causative genes. Our specific aims are (1) To perform mutation analysis in TNXB and other tenascins in a cohort of 200 individuals with familial and sporadic PVUR and define genotype/phenotype correlations. (2) To perform sequential genome wide linkage studies (GWLS) and whole exome/targeted sequencing in families with PVUR. Impact on public health: Identification of PVUR genes may provide a novel non-invasive diagnostic tool for a subset of children with PVUR. Furthermore, this research will provide insights into the pathogenesis of PVUR and further elucidate the pathways involved in the development of the kidney and genitourinary tract. Future studies will define the role of the genes in the etiology of other malformations of the kidney and urinary tract and also seek to unravel the mechanisms by which the identified gene causes PVUR and other malformations of the kidney and the urinary tract.

  Study phs000778

• Northwestern NUgene Project: Type 2 Diabetes

  The ability to correlate genetic variation with disease susceptibility and response to drug therapy depends on genotype or sequence analysis of large numbers of richly characterized DNA samples. Eight years agoWe are a part of NHGRI's electronic Medical Records and Genomics (eMERGE) Network, whose goal is to conduct genome-wide association studies in thousands of individuals using EMR-derived phenotypes and DNA from linked biorepositories. For eMERGE, Northwestern University (NU) is studying type 2 diabetes as a phenotype. In addition, in order to explore race differences in the prevalence of type 2 diabetes, NU collaborated with Vanderbilt University to study a mix of both Caucasian and African-Americans. Northwestern University: In 2002, Northwestern committed to the development of a DNA repository to serve as a platform for the identification and validation of genotype-phenotype associations that will impact healthcare. The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a questionnaire (2 versions were used, 1 before and 1 after February 2006, both are included) and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Vanderbilt University: BioVU, Vanderbilt's DNA databank, is an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses, and represents a key first step in moving the emerging sciences of genomics and pharmacogenomics from research tools to clinical practice. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations.

  Study phs000237

• Metagenomics-Guided Pathogen Discovery in Travelers' Diarrhea

  Traveler's diarrhea (TD) is caused by enterotoxigenic Escherichia coli (ETEC), other pathogenic gram-negative pathogens, norovirus and some parasites. Nevertheless, standard diagnostic methods fail to identify pathogens in more than 30% of TD patients, so it is predicted that new pathogens or groups of pathogens may be causative agents of disease. A comprehensive metagenomic study of the fecal microbiomes from 23 TD patients and seven healthy travelers was performed, all of which tested negative for the known etiologic agents of TD in standard tests. Metagenomic reads were assembled and the resulting contigs were subjected to semi-manual binning to assemble independent genomes from metagenomic pools. Taxonomic and functional annotations were conducted to assist identification of putative pathogens. We extracted 560 draft genomes, 320 of which were complete enough to be enough characterized as cellular genomes and 160 of which were bacteriophage genomes. We made predictions of the etiology of disease in individual subjects based on the properties and features of the recovered cellular genomes. Three subtypes of samples were observed. First were four patients with low diversity metagenomes that were predominated by one or more pathogenic E. coli strains. Annotation allowed prediction of pathogenic type in most cases. Second, five patients were co-infected with E. coli and other members of the Enterobacteriaceae, including antibiotic resistant Enterobacter, Klebsiella, and Citrobacter. Finally, several samples contained genomes that represented dark matter. In one of these samples we identified a TM7 genome that phylogenetically clustered with a strain isolated from wastewater and carries genes encoding potential virulence factors. We also observed a very high proportion of bacteriophage reads in some samples. The relative abundance of phage was significantly higher in healthy travelers when compared to TD patients. Our results highlight that assembly-based analysis revealed that diarrhea is often polymicrobial and includes members of the Enterobacteriaceae not normally associated with TD and have implicated a new member of the TM7 phylum as a potential player in diarrheal disease.

  Study phs001352

• Exome Sequencing of Statin-Induced Myopathy Cases

  Severe myopathic events occur in 0.1-0.5% of patients taking statins. Although genetic association studies have identified some possibly associated gene loci, these have not been reproducible in additional studies with independent patient cohorts. A more reasonable explanation for susceptibility to statin-induced myopathy is the presence of rare pathogenic variants in genes important for skeletal muscle structure and function. In support of this, we have previously reported an increased incidence of pathogenic variants in genes causing metabolic myopathies in patients with statin-induced myopathy (Vladutiu et al.,2006). We also reported a patient with statin myopathy who had an RYR1 variant known to be causative of malignant hyperthermia susceptibility (MHS) (Vladutiu et al., 2011). There are a number of genes associated with metabolic myopathies triggered by various factors such as extreme exercise, fasting, extremes in temperature, viral infection and exposure to volatile anesthetics. In addition, many of the genes causing congenital myopathies, myofibrillar myopathies and muscular dystrophies have overlapping phenotypes with these genes. We propose that statins act as an additional trigger inducing myopathic symptoms and many patients with severe statin-induced myopathy have causative genetic variants within similar genes associated with MHS and congenital myopathy. We have analyzed the resultant data using a disease model in which rare pathogenic variants, possibly within multiple genes, are causative of statin-induced myopathy. In this study, we have identified potentially causative genetic variants in greater than 50% of the statin-induced myopathy cases and in particular, rare and possibly pathogenic in the RYR1 and CACNA1S genes were present in 25% of the patient samples studied. Vladutiu, G. D., Simmons, Z., Isackson, P.J., Tarnopolsky, M., Peltier, W.L., Barboi, A.C., Sripathi, N., Wortmann, R.L., Phillips, P.S., (2006). "Genetic risk factors associated with lipid-lowering drug-induced myopathies." Muscle Nerve 34: 153-162. Vladutiu, G. D., Isackson, P.J., Kaufman, K., Harley, J.B., Cobb, B., Christopher-Stine, L., Wortmann, R.L, (2011). "Genetic risk for malignant hyperthermia in non-anesthesia-induced myopathies." Mol Genet Metab 104: 167-173.

  Study phs001342

• NHLBI GO-ESP: Family Studies (Mendelian Lipid Disorders)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. In this study, we seek to identify the genetic cause of two monogenic lipid disorders-severe hypercholesterolemia and familial hypoalphalipoproteinemia. Monogenic severe hypercholesterolemia is clinically characterized by elevated total and low-density lipoprotein (LDL) cholesterol levels in plasma. Elevated LDL-cholesterol levels lead to excessive deposition of cholesterol in arterial walls, which eventually results in accelerated atherosclerosis and premature cardiovascular disease (CVD). Monogenic hypercholesterolemia has a prevalence of approximately one in 500 individuals, making it one of the most common inherited disorders. To date, mutations in the LDL receptor (LDLR) ligand-binding domains of APOB and PCSK9 have been shown to cause hypercholesterolemia. While mutations in these genes can explain a large percentage of clinically diagnosed patients, the underlying molecular determinant in a substantial fraction of patients remains unknown. Familial hypoalphalipoproteinemia (low HDL-C) is defined by an HDL-C below the age- and sex- specific 10th percentile. ABCA1, LCAT, and APOA1 are known to cause familial hypoalphalipoproteinemia. We hypothesize that: (1) additional novel genes responsible for Mendelian forms of low HDL-C exist; and (2) the causal gene and mutation(s) in each family may be discovered with exome analysis of just a few affected individuals in each pedigree.

  Study phs000587

• Effect of Breast Feeding on Immunologic Priming in Young Infants

  The mechanisms generating immunoglobulin heavy chain (IgH) biodiversity result in over potentially unique immunoglobulin sequences within an individual. However, over the course of B cell development, B cell receptor (BCR) selection constrains the repertoire significantly. In newborn infants compared to adults, developmental regulation of terminal deoxynucleotidyl transferase (TdT) activity in the bone marrow, selective use of V, D and J gene segments in the IgH locus during fetal life, and immaturity of somatic hypermutation (SHM) and class switch recombination (CSR) mechanisms are likely to contribute to a less diverse IgH repertoire, although the extent of repertoire biodiversity in newborns has not been extensively examined. Furthermore, the fetal IgH repertoire is tightly controlled and for the most part independent of environmental antigenic influences. As a result, the neonatal repertoire, in contrast to older children and adults, is less impacted by the selective pressures of the microbiome, pathogen exposure, and environmental antigens. Evidence for developmental differences in TdT activity is seen in shorter CDR3 lengths and decreased junctional diversity in BCR in both term and preterm newborns. Next Generation Sequencing (NGS) is a sensitive approach to evaluate the neonatal IgH repertoire and assess the relative contribution of each aspect of IgH rearrangement and affinity maturation to overall IgH biodiversity prior to and following isotype class switch. NGS and bioinformatics accurately assess biodiversity by determining the number of unique sequences within the IgH repertoire. Combined with novel analytic tools, NGS provides an approach to compare the extent of somatic hypermutation (SHM), N insertions, V/D/J gene segment usage, and CDR3 length between newborns and adults. Taken together, these measures can be used to assess the earliest events in B cell development using the newborn Ig transcriptome to evaluate the IgM, IgG, and IgA IgH repertoires. The goal of this study was to define the extent of IgH biodiversity in newborns and examine the factors that contribute to the generation of biodiversity during early life. Establishment of the bioinformatics pipeline can be applied to examine the immune deficiency, response to vaccine and infection at molecular population level.

  Study phs002073

• Temporal Lobe Epilepsy and Retrotransposons

  Idiopathic (cryptogenic) epilepsy is a common, chronic group of brain disorders, affecting 1-2% of the US population, creating a significant public health problem because of the associated morbidity and mortality. One subtype of this complex group of brain disorders, temporal lobe epilepsy (TLE), is particularly burdensome, because a substantial fraction of patients do not respond to anticonvulsant medications. If the seizure focus can be localized by imaging and/or EEG, the TLE patient often elects to have a partial resection of the affected temporal lobe, because they have daily seizures, despite multiple pharmacotherapy regimens. Although genetic risk is thought to play a role in TLE, identification of common risk alleles has had limited success. In the past 5 years, data have accumulated to prove that neuronal embryogenesis is accompanied by activation of LINE1 (L1) retrotransposons (RTPs) to an unexpected degree, such that developing neurons may accumulate de novo L1 insertions. This results in a substantial mosaicism within populations of CNS neurons. While most of these somatic de novo L1s will have little effect on neuronal function (perhaps because they occur in gene deserts or in large introns or in genes not required for that cell's function), some may interfere with normal neuronal activity because they have inserted into a gene needed by that particular neuron for normal function. If one or more functional de novo L1s occur early in CNS development, all the daughter neurons that derive from that neuronal precursor will also carry the L1 insertion, perhaps leading to a dysfunctional population of neurons destined to become an epileptic focus. This study leveraged CNS tissue (obtained at craniotomy) from patients with intractable TLE, who have undergone a therapeutic partial resection of one temporal lobe. Using fluorescence-assisted cell sorting of temporal lobe neuronal nuclei, followed by high-throughput sequencing and alignment to the reference genome, detection of de novo L1s will be done. In this manner, it is expected that de-novo intragenic L1s, contributing to idiopathic TLE, will be discovered.

  Study phs002067

• Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

  The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

  Study phs001222

• Exploring the Genetic Variants Associated with Brain Growth in Children

  Understanding the genetic factors that control brain growth during childhood and adolescence is a priority for neuroscience. Its importance lies partly in the finding that disturbances in the course of brain development characterizes many common childhood behavioral problems. Recent advances in neuroimaging such as the use of non-invasive magnetic resonance imaging have provided a chance to define these trajectories in the living child. The intramural programs of the NIMH and NHGRI have conducted repeated neuroanatomic imaging on children along with the banking of DNA, providing a cohort which is studied for defining developmental trajectories of the brain. A central goal of this cohort is to define the disturbances in brain development that are linked with common behavioral problems, such as excessive impulsivity, hyperactivity and inattention. Studies have demonstrated that problems in these domains are distributed across the entire population and that children with Attention Deficit Hyperactivity Disorder (ADHD) lie at the extreme end of these behavioral dimensions. We found a similar dimensionality in the development of brain regions that are associated with these behavioral problems. Specifically, we showed that the rate of change in both the lateral prefrontal cortex and interconnected striatum during childhood and adolescence was linked to the severity of symptoms of hyperactivity and impulsivity. As symptoms increased, the rate of growth of both structures decreased. The lateral prefrontal cortex and striatum are core components of richly interconnected 'loops' that support a host of cognitive processes, including attention, cognitive control and motor planning. Anomalies in these structures and their connections have been implicated in many childhood behavioral problems, including ADHD. In summary, we aim to identify the common and rare genetic variants that are associated with the developmental trajectories of the lateral-prefrontal cortex and striatum. Identifying genetic variants influencing the growth of these structures may reveal the biological mechanisms underlying dysregulated control of attention, impulse and activity level, which in the extreme constitute ADHD. The study thus could inform our understanding of neurobiology underpinning one of the most common neuropsychiatric disorders of childhood.

  Study phs000962