15120 results for "cancer studies using rna-seq"

in 25.33 milliseconds.

• Hospital for Sick Children Infant Glioma RNA Sequencing

  Whole transcriptome (n=4) and targetted RNA sequencing (n=15) .bam files of infantile glioma samples reported on at the Hospital for Sick Children

  Dataset EGAD00001005092

• RNA-Sequencing data of Human Acute Myleloid Leukemia Stem Cells

  RNA-Sequencing of 27 functionally validated LSC and blast fractions from 9 AML patients. Three healthy hematopoietic stem and progenitor cells from age-matched controls.

  Dataset EGAD00001006112

• RNA sequencing data of pretreatment tumor biopsies of patients treated in the OpACIN-neo trial

  The dataset includes RNA sequencing on pre-treatment tumor biopsies of lymph node metastases (n=65)

  Dataset EGAD00001006731

• 5 scRNA-seq with TCR Enrichment of Tumour-Involved Lymph Nodes, Malignant Seromas and Patient-Derived Xenografts from 18 T-Cell Lymphoma Patients

  This raw data contains 5' scRNA-seq with TCR enrichment data from 18 individual patients analysing cells taken from tumour-involved lymph nodes (LN), malignant seromas and patient-derived xenografts (PDX) including systemic/nodal ALK+ ALCL (n=3 PDX), BIA-ALCL (n=2 seromas), PTCL-NOS (n=5 nodal tumours), nodal T follicular helper lymphoma - angioimmunoblastic type (nTFHL-AI) (n=1), nTFHL, not otherwise specified (nTFHL, NOS, n=1), TLBL (n=5) and 1 case of Sezary Syndrome (SS, cutaneous tumour). Droplet-based 5’ scRNA-seq with TCR enrichment (10x Chromium platform) was performed for all live cells, or the viable CD45+CD3- and CD45+CD3+ fractions following cell sorting by flow cytometry.

  Dataset EGAD00001015703

• Asian Indian Diabetic Heart Study (AIDHS) /Sikh Diabetes Study (SDS)

  The Punjabi Sikh population is a well-defined, carefully collected homogeneous sample from northern India and the US. It has unique characteristics, which are ideal for genetic studies. Sikhs are strictly a non-smoking population and about 50% of participants are life-long vegetarians. All subjects included in the genome-wide association studies (GWAS) were recruited from one geographical location. Our population demonstrates a strong familial clustering of type 2 diabetes and related cardio-metabolic disorders that may be genetic and we believe that the contribution of alleles at specific loci are likely to be unique to Punjabi Asians compared to Europeans. Our group first showed that the association of a common variant at rs9939609 in the FTO (fat mass and obesity) gene in South Asians was independent of BMI (PMID:18598350) in contrast to Europeans where the association of same variant with T2D is mediated through obesity (PMID:17434869). These findings were later confirmed in an independent sample of South Indians (PMID:19005641), Pakistanis (PMID:21294771), and even East and South Asians in a large meta-analyses study comprising 96,551 individuals (PMID: 22109280). Earlier reported association of MTNR1B with fasting glucose concentrations and type 2 diabetes in European GWAS could not be confirmed in our Sikh cohort. On the other hand, our study revealed, for the first time, a significant protective association of another less common variant in MTNR1B with fasting glucose levels that was modulated by obesity. Ours was the first report that suggested that the low CETP activity was associated with higher CAD risk (PMID:22143414) in South Asians and that the genetic effects are significantly modulated by environmental factors (alcohol consumption). Our recent GWAS on type 2 diabetes has identified a novel locus at chromosome 13q12 in the SGCG gene (p=1.82x10-8) associated with type 2 diabetes (PMID:23300278) in Punjabi Sikhs. From these findings, we are optimistic that our resource will provide new insights to gene functions in the diabetic pathway and better help researchers to understand and translate these insights to novel therapeutic treatment and early prevention to T2D that may be important beyond Indians.

  Study phs000583

• Ulcerative Colitis Human Microbiome Project (UCHMP)

  The aims of the multi-center Ulcerative Colitis Human Microbiome Project (UCHMP) are to examine the role of the enteric microbiome in causing human ulcerative colitis, specifically the development of pouchitis. Pouchitis is an inflammatory condition of the surgically-created ileoanal pouch that serves as a pseudo-rectum in patients with ulcerative colitis who have undergone a total colectomy. It is a condition unique to ulcerative colitis (UC), as it rarely occurs in non-UC patients who have the same procedure. Within one year, about 50% of patients will develop pouchitis. The condition is almost certainly due to aspects of the pouch microbiota on a background of genetic susceptibility, as most patients respond to treatment with antibiotics. While there have been reports on the microbiota in pouchitis patients, all have been performed after the inflammatory process is initiated, rendering interpretation of the results difficult, as the inflammatory process itself will change the microbiota. Our project is therefore unique and possibly the only opportunity in the role of the enteric microbiome in IBD in a prospective manner, thereby establishing potentially important causal relationships between microbiota structure or function and development of UC.The studies also offer two additional advantages. First, the development of the pouch microbiota can be observed prospectively. Second, the cause of antibiotic treatment failure in some patients with pouchitis may be revealed. The two aims are (1) to identify causal factors in the structure and/or function of the enteric microbiota in the development of pouchitis, and (2) to determine the basis of treatment failure in UC pouchitis patients. Our analyses will include serial measurements of enteric microbial structure (16S rRNA gene-based), function (metagenomics and functional candidate genes), and cultivation, the latter to enhance interpretation of gene sequences derived from metagenomes and targeted gene surveys (either functional or 16S genes). The insights gained from these studies will help us understand the fundamental and causative roles of the enteric microbiome in human inflammatory bowel diseases (IBD). This information will be the basis for developing strategies to restore host-microbial relationships to prevent and treat IBD.

  Study phs000262

• METABRIC

  The elucidation of breast cancer subgroups and their molecular drivers requires integrated views of the genome and transcriptome from representative numbers of patients. We present an integrated analysis of copy number and gene expression in a discovery and validation set of 997 and 995 primary breast tumours, respectively, with long-term clinical follow-up. Inherited variants (CNVs, SNPs) and acquired somatic copy number aberrations (CNAs) were associated with expression in 40% of genes, although the landscape was dominated by cis and trans-acting CNAs. By delineating expression outlier genes driven in cis by CNAs, we identified putative cancer genes, including deletions in PPP2R2A, MTAP, and MAP2K4. Unsupervised analysis of paired DNA/RNA profiles revealed novel subgroups with distinct clinical outcomes, which reproduced in the validation cohort. These include a high-risk, ER-positive 11q13/14 cis-acting subgroup and a favourable prognosis subgroup devoid of CNAs. Trans-acting aberration 0152hotspots were found to modulate subgroup-specific gene networks, including a TCR deletion-mediated adaptive immune response in the 0152CNA-devoid sub-group and a Basal-specific chromosome 5 deletion-driven mitotic network. Our results provide a novel molecular stratification of the breast cancer population, derived from the impact of somatic copy number aberrations on the transcriptome.

  Study EGAS00000000083

• Somatic L1 retrotransposition in normal colorectal epthelium

  Throughout an individual’s lifetime, genomic alterations accumulate in somatic cells. However, the mutational landscape induced by retrotransposition of long interspersed nuclear element-1 (L1), a widespread mobile element in the human genome, is poorly understood in normal cells. Here, we explored the whole-genome sequences of 406 normal colorectal clones, 12 MUTYH-associated adenomatous clones, and 19 matched colorectal cancer tissues. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 (in 139 clones) and read-through RNA expression profiles (in 116 clones) to investigate the epigenetic regulation of L1 activity.

  Dataset EGAD00001010183

• ChIP seq samples

  Dataset contains 12 ChIP-Seq samples sequenced on the Illumina NextSeq500 sequencer. 3 samples are control samples (HcAct-Chip 1,HcAct-Chip 2,HcAct-Imput 2) 9 samples are case samples (HcAct2DG-Chip 1,HcAct2DG-Chip 2,HcAct2DG-Imput 1,JIAAct-Chip1,JIAAct-Chip2,JIAAct-Imput2,JIAAct2DG-Chip1,JIAAct2DG-Chip2,JIAAct2DG-Imput2)

  Dataset EGAD50000001188

• Whole genome sequencing of adult glioblastoma nuclei

  Three primary adult glioblastoma specimens were dissociated and nuclei were extracted. A portion of the nuclei was used for single-cell ATAC seq and the remainder were submitted for whole genome sequencing, to provide orthogonal validation of copy number variations in the samples compared to single-cell ATAC seq. Samples were sequenced on the Illumina NovaSeq 6000 in paired-end mode.

  Dataset EGAD00001007651

• BLUEPRINT release August 2014, Bisulfite-Seq for macrophage

  Bisulfite-Seq data for 1 macrophage sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000923

• BLUEPRINT release January 2015, Bisulfite-Seq for erythroblast

  Bisulfite-Seq data for 2 erythroblast sample(s). 35 run(s), 2 experiment(s), 2 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001133

• BLUEPRINT release August 2014, Bisulfite-Seq for erythroblast

  Bisulfite-Seq data for 1 erythroblast sample(s). 14 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000909

• BLUEPRINT release January 2015, Bisulfite-Seq for macrophage

  Bisulfite-Seq data for 5 macrophage sample(s). 72 run(s), 5 experiment(s), 5 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001192

• BLUEPRINT release August 2014, Bisulfite-Seq for inflammatory macrophage

  Bisulfite-Seq data for 3 inflammatory macrophage sample(s). 38 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000914

• BLUEPRINT release January 2015, Bisulfite-Seq for inflammatory macrophage

  Bisulfite-Seq data for 3 inflammatory macrophage sample(s). 38 run(s), 3 experiment(s), 3 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001139

• BLUEPRINT release August 2014, Bisulfite-Seq for Plasma cell

  Bisulfite-Seq data for 1 Plasma cell sample(s). 11 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release August 2014. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001000927

• BLUEPRINT release January 2015, Bisulfite-Seq for plasma cell

  Bisulfite-Seq data for 1 plasma cell sample(s). 11 run(s), 1 experiment(s), 1 alignment(s). Part of BLUEPRINT release January 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20140811/homo_sapiens/README_bisulphite_analysis_CNAG_20140811

  Dataset EGAD00001001160

• Multi-omics characterization of KMT2A-rearranged infant acute lymphoblastic leukemia

  KMT2A gene rearranged (KMT2A-r) infant acute lymphoblastic leukemia (ALL) is the most refractory subgroup of childhood leukemia, whose molecular heterogeneity remains largely unknown. To better understand the molecular pathogenesis of KMT2A-r infant ALL, we comprehensively analyzed the RNA sequencing, methylation array, whole exome sequencing, single-cell RNA sequencing data of diagnostic samples of KMT2A-r infant ALL. We also performed ChIP sequencing of infant ALL-derived cell lines.

  Study JGAS000385

• Effect of inflammation on human hematopoietic stem cells in a xenograft model

  Transcriptional heterogeneity in cord blood HSCs was investigated by 10X single-cell Multiome (RNA+ATAC). To investigate the effect of inflammatory stress on human HSC, 10X single-cell Multiome profiling of cells from xenografted mice recovered from repeated inflammatory challenge was performed. To investigate transmission of inflammatory stress-related molecular programs from HSC to their progeny, 10X single-cell RNA sequencing was performed on committed progenitor and myeloid cells from the same mice.

  Study EGAS50000001624

• Data Access Commitee - Peripheral Blood Leukocytes 10x Genomics scRNA-seq

  Dac EGAC00001002550

• Peripheral clonal expansion of T cells (scTCR-seq)

  Study EGAS00001003994

• WGBS and oxBS-seq for APL

  Study EGAS00001005610

• Single Cell ATAC-Seq on human cord-blood derived HSPC.

  Study EGAS00001004740

• 16SV4 ribosomal RNA gene sequencing data

  16SV4 ribosomal RNA gene sequencing data of GI samples and associated mixed community cultures collected from pediatric patients at risk for IBD.

  Dataset EGAD50000000485

• RNA sequencing of pediatric BCP ALL

  RNA sequencing data of 33 B-cell precursor (BCP) acute lymphoblastic leukemia (ALL) cases were constructed on an Illumina nextseq 2000 Sequencing System.

  Dataset EGAD50000001125

• Multi-omics characterisation of immune cells in Long Covid

  We generated 10X Multiomics (paired RNA+ATAC) for Long Covid patients with up to 14 months follow-up.

  Study EGAS50000000142

• RNA sequencing of AML with 3q26 rearrangements

  RNA sequencing of 44 AML cases with diverse 3q26 rearrangements. This dataset is complementary to EGAD00001000726 (which only contains t(3;3)/inv(3)) and to EGAD00001006123.

  Dataset EGAD00001015629

• The Extracellular RNA Quality Control (exRNAQC) study (phase 2)

  mRNA capture sequencing and small RNA sequencing data (FASTQ files) of the exRNAQC study phase 2 (interaction study)

  Dataset EGAD00001009724

• Whole exome and RNA sequencing of 5 samples of patient-derived xenograft (PDX).

  Whole exome and RNA sequencing of 5 samples of patient-derived xenograft (PDX). Available files are raw sequencing fastq files.

  Dataset EGAD00001010102

• Human serum small non-coding RNA sequencing

  Human small non-coding RNA sequencing of serum from sons of PCOS mothers (n=9) and sons of control mothers (n=9), see publication for details.

  Dataset EGAD00001010165

• Strand-specific RNA Sequencing of initial and recurrent gliomas

  Four RNA-sequencing datasets from two patients with initial low-grade glioma and copy number alteration at IDH1 upon recurrence. Data is provided as bam files.

  Dataset EGAD00001003764

• Poikiloderma syndrome RNAseq

  We will sequence the RNA of lymphoblast samples, transformed with EBV, which have poikiloderma syndrome with mutations in c16orf57. The aim of the experiment is to characterise RNA structural effects in this disease.

  Dataset EGAD00001000324

• Strand-specific RNA sequencing of 16 pairs of primary and relapsed IDH-wt glioblastomas

  This dataset contains strand-specific RNA sequencing data from 16 primary/relapsed sample pairs of IDH-wt glioblastomas

  Dataset EGAD00001004564

• RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

  RNA sequencing of paediatric glioblastoma in the ICGC PedBrain project

  Dataset EGAD00001001944

• Rheumatoid Arthritis Finger Stick RNA Sequence Data

  This is a longitudinal study of 355 blood samples collected weekly from 5 patients with Rheumatoid Arthritis with varying disease activity over the course of one to five years. Blood samples were self collected from finger sticks and mailed from home. RNA was extracted, purified and sequenced.

  Study phs003179

• Single-cell bam files and RNA sequencing of viral RNA stocks

  244 infected single-cell alveolar bam files, 48 empty well bam files, and 52 RNA sequencing of amplicons (4 SARS-CoV-2 variants with 12 batches and 4 viral variants pool samples). 244 alveolar single cells were captured over 12 experimental batches and experimental condition is written in metadata uploaded as "infected_cells_final_revision.csv". on github (https://github.com/twkim-0510/SARS-CoV-2_viral_competition). Each bam file name corresponds to the sample_name column of the metadata.

  Dataset EGAD00001009711

• Targeted sequencing

  Paired-end BAM files with associated index files of 15 AML samples were generated using Agilent SureSelect XT library capture system using a custom panel as described before Takahashi et al Blood 2018. Libraries were sequenced using Illumina HiSeq 2500.

  Dataset EGAD00001007671

• GenomeDenmark Phase 2 - variants called on chrY for 62 males.

  Variants on the Y chromosome for 62 danish males in VCF format from the GenomeDenmark Phase 2 cohort. Variants were called using reference based approaches such as the haplotype-caller module from GATK and using alignment of denovo assemblies to the reference using ASMvar.

  Dataset EGAD00001003186

• DAC for TCR-seq analysis of human intestinal Trm cells

  Dac EGAC00001001219

• scBCR-seq data from human donors

  Dataset EGAD00001005057

• How to use EGA Webin?

  EGA Webin EGA Webin serves as a platform for registering metadata for array based submissions, large scale sequence submission as well as for legacy EGA submission accounts (ega-box-XXXX). For large scale submitters of sequence data you have also the option to submit metadata via XMLS programmatic submission, while new submitters are advised to utilise the Submitter Portal for their submissions. You can request a legacy EGA submission account (ega-box-XXXX) by populating this form. Please, allow two business days for our Helpdesk team to contact you after populating this form. WEBIN actions: Register metadata for a sequence submission Register study, samples, experiments, runs, DAC, policy and dataset/s after file upload. Register components for your array-based metadata submission Register study, samples, DAC or policy before uploading files. Edit existing submission metadata Change or update previously submitted metadata. Register metadata for a sequence submission Ensure that all sequence files have been encrypted before uploading them to your submission account using the EgaCryptor. Go to the EGA Webin and log in using your submission account name (ega-box-XXX) and password. Register components of your metadata submission Study Samples Data Access Committee (DAC) Data access policy Dataset For array-base submissions: Study, Samples, Data Access Committee (DAC) and Data access policy may all be registered BEFORE file upload and dataset registration through the array-base template. Register your Study Go to the “Studies (Projects)” box Click on “Register Study” and fill in the information related to your study. Click on “Submit”, this will save the information and generate an EGA study ID. To use the study accession number in a publication, the study has to be previously released on the EGA website, we suggest the following format: "Sequence data has been deposited at the European Genome-phenome Archive (EGA), which is hosted by the EBI and the CRG, under accession number EGASXXXXXXXXXXX.Further information about EGA can be found on https://ega-archive.org and “The European Genome-phenome Archive in 202 "(10.1093/nar/gkab1059)" Register your Samples Go to the “Samples” box Click on “Register Samples” Select “Download spreadsheet to register samples” and customise your template, there is a default EGA template (EGA default checklist) but more attributes can be added if required. For the EGA default checklist, there are mandatory,recommended and optional attributes. As well custom fields which can be added if required. Mandatory attributes Field Name Description tax_id Taxonomy ID of the organism as in the NCBI Taxonomy database. Entries in the NCBI Taxonomy database have integer taxon IDs. See our tips for sample taxonomy here scientific_name Scientific name of the organism as in the NCBI Taxonomy database. Scientific names typically follow the binomial nomenclature. For example, the scientific name for humans is Homo sapiens. sample_alias Unique name of the sample. If not selected system will auto generate an unique alias sample_title Title of the sample sample_description Description of the sample phenotype *** Where possible, please use the Experimental Factor Ontology (EFO) to describe your phenotypes. Recommended attributes Field Name Description subject_id Identifier for the subject where the sample has been derived from gender * Sex Optional attributes Field Name Description sex sex of the organism from which the sample was obtained disease_site Affected organ sample type Affected organ donor_id ** Identifier of the donor where the sample has been derived from *Gender should be described as 'male', 'female' or 'unknown'. If 'unknown' due to a known sex chromosome aneuploidy, please create a user defined attribute called 'Sex chromosome karyotype' and add the appropriate value, for example, 'XXY'. **Donor id (Subject id) should be a de-identified subject handle. If unknown, please add 'unknown' to the field. ***Phenotypes should, where possible, be an Experimental Factor Ontology accession. If a term cannot be found to describe your phenotype please use free text. All sample phenotypes considered important for further analysis of the data should be provided (for example, tumour type), additional phenotype attributes can be created by defining your own attributes; use the notion 'phenotype2', 'phenotype3', etc. After you have customised the fields for the sample submission, download the template and fill in the information. Example of the sample template: Finally upload the sample template to get the EGA accession IDs for the samples. Register your Data Access Committee (DAC) Further information on the role of your DAC Go to the “Data Access” box Click on “Register Dacs” Input the information about the DAC and register at least one main DAC contact. Register your Data Access Policy Your Data Access Policy provides the terms and conditions of data use, this is also referred to as the Data Access Agreement (DAA). Completion of a DAA by the applicant/s should form part of the application process to the Data Access Committee (DAC). Go to the “Data Access” box Click on “Register Policies” Select the DAC to which this policy will be linked to and fill in the policy information. Submitting your Runs and Analyses This section is only for sequence data submission, for array-based submission it can be skipped. Please refer to our Submitting array based metadata Runs Registration Go to the “Raw Reads (Experiments and Runs)” box Click on “Submit Reads” Select “Download spreadsheet template for Read submission” Select the template corresponding to your submission type For the templates you have the option to customise the optional fields. To check their description click on “Show Description “ Download the template and fill in the required information. Example of the runs template: We recommend that Fastq, BAM, and CRAM read files are submitted using Webin-CLI When using this interface instead of Webin-CLI, raw sequences must be uploaded in one of the supported data formats before they can be submitted. The files can be uploaded using FTP or Aspera. The study and the sequenced samples must be pre-registered before the raw reads are submitted. Please note that each individual study and sample should be registered only once. You will be asked to provide information about the sequencing libraries and instruments. Submitting your Dataset This section is only for sequence data submissions, for array based submissions it can be skipped. Please refer to our Submitting array based metadata The dataset describes the data files, defined by the run (EGARXXXXXXXXXXX) and analysis (EGAZXXXXXXXXXXX) accessions that make up the dataset and links the collection of data files to a specified Data Access Committee and Data Access Policy. As a result, you must have registered your Reads and experiments, Data Access Committee (DAC) and Data access policy before submitting your Dataset. Please consider the number of datasets that your submission consists of, for example, a case control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Please contact EGA Helpdesk for further assistance. Go to the “Data Access” box Click on “Register Dataset” Select the Data Access Committee (DAC) and Data access policy Register your dataset After submitting your dataset you should contact the EGA Helpdesk to provide a release date for your dataset. Datasets are automatically held (i.e. not released) unless they are affiliated to a study that has already been released. Edit/update existing submission metadata Go to the “Report” section of the object you would like to edit. Locate the object and click on the arrow under action. An option menu will be displayed. Objects can be edited through their XML or with the WEBIN menu. After an object has been edited, changes would be available on the website until the submission is released again. Please contact the EGA Helpdesk if you require further assistance.

  Documentation submission/metadata/submission/EGA_webin

• Whole genome sequencing of breast cancer and related clones

  Paired WGA (whole-genome amplificated) samples from 65 single cell-derived organoids and six fresh single cell-derived organoid samples both of which were established from normal mammary epithelial cells, 84 FFPE LCM (laser-capture microdissection) samples of breast cancer and related clones, 79 fresh-frozen LCM samples of non-cancer lobules of breast cancer patients, and 36 matched germline controls were subjected to whole genome sequencing using NovaSeq 6000 system (Illumina) or DNBSEQ-G400RS (MGI Tech).

  Dataset EGAD00001010833

• Geographical structure and differential natural selection among North European populations

  European populations and epidemiological cohorts are of special significance in the current era of genomic research aiming to characterize the background of common human diseases. The genome sequence, detailed information of genetic variations between individuals, high-throughput molecular technologies and novel statistical strategies create new possibilities to define genetic and life-style risk factors behind common health problems. Studies of large population cohorts are needed to transform the genetic information to detailed understanding of the predisposing factors in diseases affecting most human populations. European twin cohorts provide a unique competitive advantage for investigations of the role of genetics and environment or life style in the etiology of common diseases. This project will apply and develop new molecular and statistical strategies to analyze unique European twin and other population cohorts to define and characterise the genetic, environmental and life-style components in the background of health problems like obesity, migraine, coronary heart disease and stroke, representing major health care problems worldwide.

  Study EGAS00000000033

• Reproductive Health in Men and Women with Vasculitis

  The purpose of this study is to learn about reproductive health, including fertility and pregnancies, in people with vasculitis. All patients enrolled in the Vasculitis Clinical Research Consortium's Contact Registry will be invited via email to participate in this study. The Contact Registry includes people who self-identify as having one of 11 vasculities: Behçet's disease, central nervous system vasculitis, drug-induced vasculitis, eosinophilic granulomatosis with polyangiitis (Churg-Strauss), giant cell arteritis, granulomatosis with polyangiitis (Wegener's), Henoch-Schoenlein purpura, Kawasaki disease, microscopic polyangiitis, polyarteritis nodosa, or Takayasu arteritis. People voluntarily enroll in this Registry with the understanding that they will receive information about clinical studies for which they might be eligible. The introductory email included basic information about the study and all of the required elements for informed consent in a brief format. Once participants agreed to participate in the study, they were directed to an online questionnaire.

  Study phs001382

• The Etiological Bases of Giftedness: Epidemiological Study of Cognitive Ability in Children in Saudi Arabia

  Recent studies of genetic foundations of cognitive ability rely on large samples (hundreds of thousands) of individuals from relatively outbred populations of mostly European ancestry. Hypothesizing that the genetic foundation of cognitive ability depends on the broader population-specific genetic context, we performed a genome-wide association study and homozygosity mapping of cognitive ability estimates obtained through latent variable modeling in a sample of 354 children from the consanguineous population of Saudi Arabia. Approximately half of the sample demonstrated significantly elevated homozygosity levels indicative of inbreeding, and among those with elevated homozygosity, it was negatively associated with cognitive ability. Further homozygosity mapping identified a specific run, inclusive of the GRIA4 gene, that survived corrections for multiple testing for association with cognitive ability. The results suggest that in a consanguineous population, a notable proportion of the variance in cognitive ability in the normal range in children might be regulated by population-specific mechanisms such as patterns of elevated autozygosity.

  Study phs001884

• Intervention with Micronutrients and Long-Term Impact in Brazil-RECODISA

  Intervention with Micronutrients and Long-Term Impact in Brazil, a partnership between the Federal University of Ceará, Brazil and the University of Virginia, USA, enrolled infants in the age group of 2-36 months to investigate trends in gastrointestinal infections and their effects on growth and development and to identify genetic factors contributing to these diseases.A total of 1044 children from six urban communities in Brazil's semiarid region, were enrolled during active surveillance; those with diarrhea (three or more liquid stools in the last 24 hours at enrollment) were defined as a cases and matched with controls having no diarrhea during the past two weeks (at enrollment) to evaluate their growth and development. A subset of 664 children with their genetic and associated phenotypic data is included in this submission. More information on this project and its related projects can be found here: Studies of diarrheal susceptibility, growth, and development, in pediatric populations in Northeastern Brazil

  Study phs003174

• Genome-Wide Association Study of Parkinson Disease: Genes and Environment

  This is a gene-environment study of Parkinson's disease. PD is a common, progressive, age-related, movement disorder that affects 1-2% of the people over the age of 65. The NeuroGenetics Research Consortium (NGRC) is the infrastructure of the study. Protocols and methods are standardized across NGRC clinics and labs as much as possible. The 2000 patients and 2000 control subjects selected for this GWAS were recruited at the NGRC-affiliated movement disorder clinics in Oregon, Washington, Georgia and New York. All 4000 subjects were white and all DNA samples were extracted from whole blood and unamplified. Seventy-five percent of subjects have data on cigarette smoking and caffeinated coffee consumption, which are inversely associated with PD risk. This study population represents the norm for clinical genetic studies of PD; i.e., NGRC estimates of risk to relatives, heritability, genotype frequencies, and exposure frequencies (see references) are very close to estimates from meta-analyses.

  Study phs000196

• Structurally Complex Osteosarcoma Genomes Exhibit Limited Heterogeneity within Individual Tumors and across Evolutionary Time

  A key characteristic of osteosarcoma is extensive and complex genomic rearrangements. However, published models explaining how these genomic rearrangements occur disagree about if these rearrangements occur early in tumor progression and then are stable afterwards, or if there is ongoing genomic instability. Previous studies have employed bulk sequencing technologies to characterize genomic alterations. A limitation of this approach is that it averages all changes within the bulk sample, essentially masking intra-sample heterogeneity and making evaluation of ongoing genomic instability difficult. To overcome this limitation and compliment previous work, we utilized single-cell whole genome sequencing to quantify somatic copy number alterations (SCNA). By interrogating individual cells within a sample, we were able to examine intra-sample heterogeneity. We found that the SCNA patterns between cells within a single sample were remarkably consistent, which supports the concept that the genomes of osteosarcoma tumors are relatively stable after early genome fragmentation events.

  Study phs003209

• NHLBI TOPMed: MWCCS: Sex Differences in the Role of Multi-Omics in HIV-Associated Carotid Artery Atherosclerosis

  The MACS-WIHS Combined Cohort Study (MWCCS) is a multicenter prospective cohort study of men and women in the U.S. that aims to understand and reduce the impact of chronic health conditions, including heart, lung, blood, and sleep (HLBS) disorders that affect people living with HIV. MWCCS, which currently has over 5000 active study participants, is designed to investigate a spectrum of questions relating to the basic science, clinical science, and epidemiology of HIV infection in the U.S., with a focus on comorbidities among men and women living with HIV. The current substudy, nested within the MWCCS, integrates detailed metabolomics and proteomics data, among other "omics" measures, to improve the understanding of the etiology of atherosclerosis and cardiovascular disease in women and men with HIV, guide mechanistic studies, and provide insights to more efficient intervention strategies. Data on 374 men are included in the current substudy.

  Study phs003651