1217 results for ""initial+cohort"+"mid-2020s"+"consortium"+"scholarly+exchange"+"university""

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• Whole Genome Association Study of Systemic Lupus Erythematosus

  The goal of this collaborative study was to identify new genetic risk factors for Systemic Lupus Erythematosus (SLE). To do this we conducted a genome-wide scan by combining the resources and expertise from a number of SLE researchers to establish a large sample set comprising 1311 SLE cases and 3340 controls. The SLE case samples were genotyped from the following collections: 338 subjects from the Autoimmune Biomarkers Collaborative Network (ABCoN), an NIH/NIAMS funded repository, 141 subjects from the Multiple Autoimmune Disease Genetics Consortium (MADGC), 613 subjects from the University of California San Francisco (UCSF) Lupus Genetics, and 335 subjects from the University of Pittsburgh Medical Center (UPMC), plus 8 samples collected at The Feinstein Institute for Medical Research. A total of 3583 control samples were examined in the association analyses. As part of this project, 1861 control samples were selected and then genotyped from the New York Cancer Project (NYCP), based on self-described ethnicity, gender and age. In addition, genotype data from 1722 control samples (all self-described North Americans of European descent) were obtained from the publicly available iControlDB database (http://www.illumina.com/pages.ilmn?ID=231).

  Study phs000122

• Genome wide association study for early onset coronary disease and related phenotypes (ADVANCE)

  ADVANCE (Atherosclerotic Disease, VAscular functioN, and genetiC Epidemiology) is a large epidemiological study of genetic and non-genetic determinants of coronary artery disease (CAD) that started in 2000 as a collaborative effort between researchers at Stanford University and Kaiser Permanente of Northern California. The overarching goal of the study is to improve our ability to prevent, diagnose and treat CAD. The initial study included recruitment of over 3600 subjects (including 1873 subjects with incident clinically significant coronary disease and 1745 control subjects) from multiple race/ethnic backgrounds. A subset of ~ 500 subjects with very early onset coronary disease (men < 45 and women < 55) and ~ 500 similar aged controls were genotyped using the Illumina 550K platform as part of an NIH funded effort within the STAMPEED consortium.

  Study phs000423

• Multi-Omic Microbiome Study-Pregnancy Initiative (MOMS-PI)

  The Vaginal Microbiome Consortium team at Virginia Commonwealth University has conducted the Multi-Omic Microbiome Study: Pregnancy Initiative (MOMS-PI) in collaboration with the Global Alliance to Prevent Prematurity and Stillbirth (GAPPS) to better understand how microbiome and host profiles change throughout pregnancy and influence the establishment of the nascent microbiome in neonates. The team particularly focused on elucidation of the role of the microbiome and its components in the etiology of preterm birth, which occurs in over 10% of pregnancies and which is the leading cause of death in neonates. Samples from 1594 women and their neonates were collected throughout pregnancy, at delivery and postpartum. The group has generated a comprehensive dataset of multiple omics technologies. This longitudinal, large-scale effort was designed to provide a large-scale resource for the scientific community. The study also permits characterization of temporal dynamics of the microbiome in pregnancy and factors associated with preterm birth.

  Study phs001523

• Proteogenomic Characterization Unveils Biomarkers Associated With Chemoresistance in Muscle Invasive Bladder Cancer

  Cisplatin-based neoadjuvant chemotherapy (NAC) combined with radical cystectomy has been used as a standard of care for patients with clinically non-metastatic muscle invasive urothelial bladder cancer, but 40-50% patients will benefit from the treatment. Molecular subtypes of muscle invasive bladder cancer (MIBC) provide a possible biomarker roadmap that may help identify patients who may or may not respond to NAC. Recently, by integrating Mass Spectrometry-based proteomics, proteogenomic studies from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) have demonstrated the potential of this approach in prioritizing candidate driver genes and facilitating understanding of the chemotherapy resistance mechanisms. To demonstrate the proteogenomic workflow for investigating the mechanisms underlying chemotherapy resistance in MIBC, we conducted proteogenomic characterization of 46 pre- and 14 post- treatment tumors, including whole exome sequencing (WES), mRNA sequencing, Tandem Mass Tag (TMT)-proteomics, or TMT-phosphoproteomic. These samples were selected from an initial cohort of 143 MIBC tissues and filtered by tumor purity, clinical history, pathological response, and proteomic quality control metrics. The final cohort comprised samples from 53 patients, including 45 with both genomic and proteomic data and 8 with genomic data only.Our multi-omics-based clustering reveals subtypes associated with chemotherapy sensitivity. Protein abundance of a short isoform of ATAD1 and RAF family proteins were identified as biomarkers of chemosensitivity which highlights the importance of proteomics data. Integration of proteomic and phosphoproteomic data reveals Wnt signaling via GSK3B-S9 phosphorylation and the JAK/STAT pathway as potential targets to overcome chemoresistance. Correlations between PD-L1 and TROP-2/NECTIN-4 indicate an additive benefit of combination therapy targeting these proteins. Our data analysis clearly demonstrates that proteogenomic plays an important role in uncovering potential resistance mechanisms that operate only at protein and Post-Translational Modification (PTM) levels. Proteomics data can be accessed through PRIDE with ID PXD060290. RNA-seq and whole-exome sequencing (WES) FASTQ files are archived in the dbGaP database.

  Study phs004049

• Myocardial Infarction Genetics Exome Sequencing Consortium: University of Lubeck

  MI cases were recruited from the German MI Family Study and the Angio-Lub study. Controls were recruited from the German MI Family Study and the Angio-Lub study. All exome sequencing was performed at the Broad Institute of Harvard and MIT; samples sequence capture was performed using Illumina's ICE Capture reagent and sequencing was performed on an Illumina HiSeq 2000 or 2500.

  Study phs000990

• eMERGE: Genetics of Complex Pediatric Disorders from the Center for Applied Genomics

  The Center for Applied Genomics (CAG) is a specialized Center of Emphasis at the Children's Hospital of Philadelphia (CHOP) with the primary goal of translating basic research findings to medical innovations. The mission of CAG is to develop new and better ways to diagnose and treat children affected by rare and complex medical disorders. We aim to discover genetic causes for the most prevalent diseases of childhood including asthma, autism, diabetes, epilepsy, obesity, schizophrenia, pediatric cancer, and a range of rare diseases. Ultimately, our objective is to generate new diagnostic tests and to guide physicians to the most appropriate therapies. The CAG is one of the world's largest genetics research programs in pediatrics, and the only center at a pediatric hospital to have established a large-scale biobank of genotyped samples. The electronic Medical Records 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.

  Study phs001165

• Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC)

  In 2016 we established the Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC) funded by the Ice Bucket Challenge Grant administered by the Motor Neurone Disease Research Institute of Australia. The goals of the SALSA-SGC are to collect biological samples from clinics across Australia with matched in depth clinical and self-report phenotypes and to generate multiple levels of genetic and genomic data. In this first data generation exercise of the SALSA-SGC the majority of the samples were collected prior to the formal establishment of SALSA-SGC from clinics across Australia.Briefly, the cohort includes the University of Sydney’s Australian Motor Neuron Disease DNA Bank (MND Bank) cohort recruited April 2000 to June 2011), with study protocol approved by the Sydney South West Area Health Service Human Research Ethics Committee (HREC). Cases were recruited from around Australia via state-based MND associations with diagnosis verified by a neurologist. The remainder of the cases were recruited from clinics across Australia between 2015 and 2017 under HREC approvals from Royal Brisbane and Women’s Hospital, Macquarie University Multidisciplinary Motor Neurone Disease Clinic,  Calvary Health Care Bethlehem in Melbourne , Fiona Stanley Hospital in Perth, and from 2016 under HREC approvals at each site for the sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC). The ALS cases were diagnosed with definite or probable ALS according to the revised El Escorial criteria. Some controls were recruited as either partners or friends of patients, healthy individuals free of neuromuscular diseases. We are providing GWAS and MWAS data in this dataset. Individual level GWAS data were generated using Illumina Infinium CoreExome-24 version 1.1 chips for N= 846 cases and N=665 controls. Individual MWAS data was generated using the Illumina Human methylation 450K array for N=782 cases and N=613 controls. There 1315 individuals where GWAS and MWAS data has been generated and is available. Further information on these data sets can be found: Paper 1: Restuadi, R, Garton, FC, Benyamin, B, Lin, T, et al. Amyotrophic Lateral Sclerosis Genetic Correlation with Cognitive Performance, educational attainment and schizophrenia: evidence from polygenic risk score analysis. (submitted) Paper 2: Nabais, MF, Lin, T, Benyamin, B et al. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. 2020. NPJ genomic medicine. 5(10). Files provided in this submission include: GWAS: This folder contains QCed genotype for the Australian ALS case-control cohort. Contains PLINK files for genotyping data (not imputed yet). The individuals selected here have: good consistency on phenotype data ethics approval registered as part of sporadic ALS studies unrelated by GRM cut-off 0.05 No ancestry QC yet MWAS: This folder contains the IDAT and post-QC normalized DNAm (beta) for the Australian ALS case-control cohort. 2019_AUS_ALS_PCTG_DNAm.tar.gz - IDATS for 1315 individuals analyzed in the MWAS study normalized_beta_values - Binary files (created with the OSCA software) containing information on the individuals, probes and the DNAm (beta) values obtained after QC phenotype_file - contains all the covariates analysed in the MWAS including: case-control status, coded 0 = Control and 1 = ALS, predicted age, predicted cell-type proportions, predicted smoking scores, slide and chip position and sex Important Notes: The DNAm data were normalized together with samples that were not part of this ALS case/control study and thus, the normalization procedure may not be 100% reproducible using only the IDAT files uploaded here. Summary data has been made publicly available and can be accessed directly: Data collection and sample processing were performed at several clinics across Australia. Genotyping and DNA methylation arrays were performed by the Human Studies Unit, at the Institute for Molecular Bioscience (University of Queensland). Quality control of the genotypic, phenotypic and DNA methylation data was done by the Program of Complex Traits Genomics, at the Institute for Molecular Bioscience (University of Queensland).

  Study phs002068

• Sequencing data for the manuscript "Resolving spatial subclonal genomic heterogeneity of loss of heterozygosity and extrachromosomal DNA in gliomas"

  Mapping the spatial organization of DNA-level somatic copy number changes in tumors can provide insight to understanding higher-level molecular and cellular processes that drive pathogenesis. We describe an integrated framework of spatial transcriptomics, tumor/normal DNA sequencing, and bulk RNA sequencing to identify shared and distinct characteristics of an initial cohort of eleven gliomas of varied pathology and a replication cohort of six high-grade glioblastomas.

  Dataset EGAD50000001394

• DAC Wachten Laboratory and Toma Laboratory, University of Bonn/University Hospital Bonn

  DAC for collaborative projects of the Wachten Laboratory (Institute of Innate Immunity, University of Bonn, University Hospital Bonn) and the Toma Laboratory (Institute of Pathology, University Hospital Bonn). Contact: Prof. Dr. Dagmar Wachten dwachten@uni-bonn.de Institute of Innate Immunity, University Hospital Bonn, University of Bonn, Germany Prof. Dr. Marieta I. Toma Marieta.Toma@ukbonn.de Institute of Pathology, University Hospital Bonn, Germany

  Dac EGAC50000000916

• International Consortium for Blood Pressure (ICBP)

  The ICBP consortium is an international effort to investigate blood-pressure genetics. The consortium was formed by two parent consortia, the CHARGE-BP consortium (Cohorts for Heart and Aging Research in Genomic Epidemiology - blood pressure) and the GBPGEN consortium (Global Blood Pressure Genetics Consortium). In 2011 we performed genome-wide association analyses based on genome-wide SNPs imputed to HapMap for systolic and diastolic blood pressure (SBP and DBP) and mean arterial pressure and pulse pressure (MAP and PP). In 2016 we performed an analysis based on the Cardio-MetaboChip for SBP and DBP. All these datasets are available here, however, full association statistics including effect size directions, only under controlled access by dbGaP.

  Study phs000585