14478 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• Medulloblastoma RNAseq

  Medulloblastoma rnaseq

  Study EGAS50000000262

• Genomic characterization of retinoblastoma

  Study EGAS00001005248

• WGS Leiomyosarcoma subtypes

  Study EGAS00001005341

• Soft tissue sarcoma sequencing data

  Study EGAS00001006356

• DAC IOR CHL study

  Dac EGAC50000000434

• Cerebrospinal fluid methylome-based liquid biopsies

  Study EGAS00001006029

• RNAseq data of phamacotyping samples

  Study EGAS00001007473

• Microarray Markers of Response

  Study EGAS00001005477

• Indonesian Genome Diversity Project 3

  Low coverage whole genome sequences (1-3x) were collected to study human genetic history across Wallacea archipelago and West Papuan Region of Indonesia . We collected 254 newly sequenced genomes mostly from previously undocumented populations including 9 communities in Wallacea and 3 in West Papuan regions. Out of 254, there are 8 high coverage whole genome sequences were produce in the study (L4).

  Dataset EGAD50000000647

• Targeted Sequencing Data for RESOLVE Clinical Trial

  This is a Phase II clinical trial. This research study is studying a combination of targeted therapies as a possible treatment for estrogen-receptor positive (ER+) endometrial cancer and low-grade serous ovarian cancer. The drugs involved in this study are: - Abemaciclib (also known as Verzenio™) - Letrozole (also known as Femara®) - Metformin (also known as Glucophage®) - Zotatifin (also known as eFT226) - Gedatolisib (also known as PF-05212384)

  Dataset EGAD50000001711

• Transcriptomic dataset from a phase II study of pembrolizumab and epigenetic modification with azacitidine in platinum-resistant epithelial ovarian cancer

  This dataset includes sequence files from bulk RNA sequencing of tissue biospecimens from a phase II study investigating epigenetic priming followed by immune checkpoint blockade in platinum-resistant epithelial ovarian cancer (NCT02900560). There are 48 bulk RNA sequencing files from 24 specimens included in this dataset.

  Dataset EGAD50000001664

• A study on personalized medicine in genitourinary cancers using genetic biomarkers

  We present a patient with MSI-high castration-resistant PC who showed a remarkable and durable response to pembrolizumab. Whole exome sequencing revealed approximate tumor mutation burden of 61 mutations/Mb as well as biallelic loss of MSH2.

  Study JGAS000510

• Study of Korean Parkinson's disease

  Single nucleotide variants (SNVs) associated with Parkinson’s disease (PD) have been investigated mainly through genome-wide association studies. Here, we conducted whole genome sequencing of 410 PD patients and 200 healthy individuals of the Korean population and identified disease-related SNVs.

  Study EGAS00001006811

• Gene_epression_regulation_in_cytokine_induced_immune_cell_states

  We isolated T cells and monocotyes from healthy platelet donors and cultured them in resting and stimulated conditions with addition of a range of cytokines. We performed RNA sequencing to assess impact of different disease-relevant cytokines upon immune cell responses.

  Study EGAS00001003823

• Summary statistics of meta-analysis using two genome-wide association study of inflammatory bowel disease in Koreans.

  We combined samples from 1,469 inflammatory bowel disease (IBD) patients consisted of 896 Crohn’s disease (CD) and 573 ulcerative colitis (UC) and 4,041 controls used in our previously published GWAS with 1,726 additional IBD patients (725 CD and 1,001 UC) and 378 additional controls genotyped using the Asian Screening Array (ASA). We uploaded summary statistics of three meta-analyses in text files.

  Dataset EGAD00001006983

• Pre-diagnostic saliva microbiota of Finnish children with autoimmune diseases

  Pre-diagnostic saliva microbiota samples of Finnish children (aged 11/12 years). This is a case-control study, where case refers to the children who developed Type 1 DM or IBD later in life and control refers to the children who were free from these diseases. The aim of the study was to find biomarkers in saliva microbiota that may help us predict DM or IBD before the onset of these diseases.

  Dataset EGAD00001009984

• Peripheral blood RNA-sequencing in 4,732 participants of the INTERVAL cohort

  We performed bulk RNA-sequencing on peripheral blood collected from 4,732 blood donors recruited as part of the INTERVAL study. Using these data, we mapped gene expression and splicing quantitative trait loci (QTLs). Then, we integrated these data with protein, metabolite and lipid QTLs in the same individuals. The study aimed to identify the shared genetic etiology across transcriptional phenotypes, molecular traits and health outcomes in humans.

  Dataset EGAD00001008015

• EORTC study on the evolution of driver mutations and MGMT promotor methylation in glioblastomas treated with standard of care: Correlation with survival and impact on trial design

  Precision medicine trials in glioblastoma should be conducted at tumor recurrence. However, second surgery for recurrent GBMs is not routinely performed and therefore molecular data is predominantly derived from primary samples. This study aims to establish the frequency of driver changes at tumor recurrence.

  Dataset EGAD00001004593

• GoDARTS T2D-GENES Exome Sequencing Study

  The GoDARTS T2D-GENES exome sequencing study includes 1924 samples, 965 T2D cases and 959 T2D controls, from European ancestry. This cohort is part of a larger exome sequencing effort from the T2D-GENES project and contains the exome sequencing vcf from the GoDARTS samples. The other data generated from the T2D-GENES project can be found in dbGAP. Samples underwent deep exome sequencing, with SNVs and INDEls called according to GATK best practices.

  Dataset EGAD00001004311

• PCGP Germline Study Whole Exome Sequencing

  PCGP Germline Study Whole Exome Sequencing

  Dataset EGAD00001001433

• The Pioneer 100 Wellness Project (P100)

  108 individuals (age 21-89+ years; 59% males, 41% females; 89% Caucasian; not recruited based on any specific phenotype) participated in an IRB-approved study from April 2014 to January 2015. Each individual had the genome sequenced in full. Blood was collected in clinics every three months. Additionally, participants completed at-home collections of saliva, stool, and first morning void urine every three months. Stool and saliva samples were shipped directly to the vendor by the participant, while urine was given back to the study coordinators for distribution to the proper sample vendor. For each successful participant in each round we carried out 218 clinical laboratory tests, measured up to 643 metabolites and 262 proteins, and measured the abundance of 4616 operational taxonomic units (OTUs) in the gut microbiome using 16S rRNA sequencing. The P100 study had four objectives: 1) Establish cost-efficient procedures for generating, storing and analyzing multiple sources of health data obtained over time from participants and analyzed in combination with genomic data; 2) Develop and deploy analytic tools for integrating these diverse datasets and deriving actionable information from their observed interrelationships; 3) Identify novel patterns within the streams of health data that indicate either wellness, or transitions between wellness and disease; 4) Learn how to best interface with and present longitudinal health information to individuals by studying the reactions and feedback from participants as they are presented actionable information.

  Study phs001363

• Rare Cancer Tumors Project

  A large proportion of common cancers affecting patients around the world have been selected for comprehensive cancer genome studies. Further efforts will be needed to tackle the remaining tumor types, including the rare forms of cancers. Although rare, these cancers tend to be more aggressive and fast growing with an early recurrence following initial chemotherapy and poor prognosis. Besides, patients diagnosed with rare cancers may have difficulty finding a physician knowledgeable in treating their type of cancer. While sample collection is a major challenge, the integrated genomic analyses would identify novel causative genes in these rare cancers, shed new light on the biology of the rare cancers, as well as guide novel targeted cancer therapies. Through efficient collaboration, the Human Genome Sequencing Center (HGSC) at Baylor College of Medicine (BCM) has collected/is expected to collect 20 different types of rare cancers, 15-30 cases each. Whole-exome sequencing and high-resolution SNP array analysis were/will be performed for all cases and whole-genome sequencing was designed for a selected subset of the cases. The Rare Cancer Tumors Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in this sub-study, please click on the following sub-study below or in the "Sub-studies" section of this top-level study page phs000725 Rare Cancer Tumors Cohort. phs000754 Intracranial Germ Cell Tumors phs000861 Craniopharyngioma Tumors phs000859 Sezary Syndrome Genomic Analysis

  Study phs000725

• Oral Immunotherapy for Induction of Tolerance and Desensitization in Peanut-Allergic Children (IMPACT)

  Brief Summary:This is a randomized, double-blind, placebo-controlled, multi-center study comparing peanut oral immunotherapy (OIT) to placebo in the induction of tolerance and desensitization in peanut-allergic children. Eligible participants with peanut allergy will be randomly assigned to receive either peanut OIT or placebo for 134 weeks followed by peanut avoidance for 26 weeks.Detailed Description:An initial oral food challenge (OFC) to 1 g of peanut flour (500 mg peanut protein) will be conducted. Participants must have a clinical reaction during this OFC to initiate study dosing. After the initial OFC, the study design includes four phases:Initial dose escalation (1 day): Peanut or placebo dosing will be given incrementally and increase every 20 minutes until a dose of 12 mg peanut flour (6 mg peanut protein) or placebo flour is given. Build-up (30 weeks): Initial observed dose administration of highest tolerated dose, followed by daily OIT at home with return visit every 2 weeks for dose escalation. Maintenance (104 weeks):The participant will continue on daily OIT with return visits every 13 weeks. At the end of this phase the participant will undergo a blinded OFC to 10 g peanut flour (5 g peanut protein). Avoidance (26 weeks): In this final phase participants will be seen every 13 weeks. At the completion of this phase participants will have a final blinded OFC to 10g peanut flour (5 g peanut protein)

  Study phs003109

• Phenotype Risk Scores Identify Patients with Unrecognized Mendelian Disease Patterns

  This study was designed to assess the phenotypic effects of rare variants. Rare variants are difficult to study in a high-throughput manner because most cohorts are underpowered to detect associations. In order to gain power to test rare variants, we use Phenotype Risk Scores (PheRS) based on features of Mendelian diseases. PheRS is calculated using claims data from an EHR that is mapped to clinical features from OMIM's clinical descriptions of Mendelian disease. We calculated PheRS for 1,204 Mendelians diseases in a cohort of 21,701 individuals genotyped on the HumanExome BeadChip. We then tested for association between these diseases and rare variants in causal genes. A phenotype risk score is calculated as the weighted sum of features for a given disease. The features are defined as a set of phecodes (consolidated ICD codes) associated with a particular Mendelian disease as described in OMIM. The weights for each phecode are calculated as the log inverse prevalence of the phecode in our cohort. For an individual, their score equals the sum of the weights for each phecode that is present in their medical record. Our study was based on a cohort of individuals with genotype data linked to de-identified electronic health records (EHR) from Vanderbilt's BioVU resource. We hope that this method will help generate phenotype-genotype correlation data on rare variants which in turn may inform rare variant interpretations use for diagnostics.

  Study phs001516

• Comprehensive Genomic Characterization of Translocation Renal Cell Carcinoma

  Xp11 translocation renal cell carcinoma (tRCC) is a rare, female-predominant cancer driven by a fusion between the TFE3 gene on chromosome Xp11.2 and a partner gene on either chrX or an autosome. It remains unknown what types of rearrangements underlie TFE3 fusions, whether fusions can arise from both the active (chrXa) and inactive X (chrXi) chromosomes, and whether TFE3 fusions from chrXi translocations account for the female predominance of tRCC. To address these questions, we performed haplotype-specific analyses of chrX rearrangements in tRCC whole genomes. We show that TFE3 fusions universally arise as reciprocal translocations and that oncogenic TFE3 fusions can arise from chrXi:autosomal translocations. Female-specific chrXi:autosomal translocations result in a 2:1 female-to-male ratio of TFE3 fusions involving autosomal partner genes and account for the female predominance of tRCC. Our results highlight how X chromosome genetics uniquely constrains somatic chrX alterations and underlies cancer sex differences.This version of the dbGaP study provides a comprehensive set of whole genome data and tables with clinical information collected for the 16 patients (15 pateints as tRCC and 1 patient as ccRCC) in the study cohort. The data also contains 12 RNA-seq samples used in the study and analyses. We anticipate that this data will considerably advance our molecular and genetic understanding of oncogenic translocations in TFE3-tRCC involving inactive chromosome X and its role in cancer sex bias.

  Study phs003008

• Diagnostic Genomic Analysis is Prognostic in AYA ALL Patients Treated on a MRD-Stratified Paediatric Protocol

  Background: Over the last decade, next generation sequencing has enabled classification of multiple new recurrent genomic drivers of acute lymphoblastic leukemia (ALL). We provide a comprehensive genomic survey of adolescent and young adult (AYA) patients treated on the Australasian Leukaemia and Lymphoma Group (ALLG) ALL06 study. ALL06 clinical trial described the efficacy and tolerability of AYA ALL patients aged 15-39 years treated on a single minimal residual disease (MRD)-stratified platform. In this study we have taken the ALL06 cohort and retrospectively performed comprehensive genomic analyses assessing response of AYA patients with various genomic subtypes treated with a paediatric approach. Methods: Genomic risk classification of B- and T-ALL patients (n=57) enrolled to the study was based on mRNA-Sequencing, MLPA, immunophenotyping and cytogenetics. Results: Using this approach, 36/40 (90%) B- and 13/17 (76.5%) T-ALL patients were classified according to genomic risk. We have linked outcome data with each patient’s genomic risk and found a strong correlation between adverse genomic risk and MRD at the end of consolidation, translating to inferior overall and relapse free survival. Patients with adverse risk genomics who achieved negative MRD status had improved responses compared to those with persistent MRD. Patients with standard risk genomics had excellent responses regardless of their MRD status. Conclusion: Our data argue strongly for incorporation of a genomic risk classification into future ALL treatment paradigms at the time of diagnosis.

  Study EGAS50000000752

• T cell receptor repertoire sequencing reveals chemotherapy-driven clonal expansion in colorectal liver metastases

  Colorectal liver metastasis (CLM) is a leading cause of colorectal cancer mortality, and the response to immune checkpoint inhibition (ICI) in microsatellite stable CRC has been disappointing. Administration of cytotoxic chemotherapy may cause increased density of tumour infiltrating T cells, which has been associated with improved response to ICI. This study aimed to quantify and characterize T cell infiltration in CLM using T cell receptor (TCR) repertoire sequencing. Eighty-five resected CLM from patients included in the Oslo CoMet study were subjected to TCR repertoire sequencing. Thirty-five and 15 patients had received neoadjuvant chemotherapy (NACT) within a short or long interval, respectively, prior to resection, while 35 patients had not been exposed to NACT. T cell fractions were calculated, repertoire clonality was analysed based on Hill evenness curves, and TCR sequential convergence was assessed using network analysis. Increased T cell fractions (10.6% vs 6.3%) were detected in CLM exposed to NACT within a short interval prior to resection, while modestly increased clonality was observed in NACT exposed tumours independently of the timing of NACT administration and surgery. While private clones made up >90% of detected clones, network connectivity analysis revealed that public clones contributed the majority of TCR sequence convergence. TCR repertoire sequencing can be used to quantify T cell infiltration and clonality in clinical samples. This study provides evidence to support chemotherapy-driven T cell clonal expansion in CLM in a clinical context.

  Study EGAS00001007136

• Predictive value of chromosome 18q11.2-q12.1 loss for benefit from bevacizumab in metastatic colorectal cancer; a post-hoc analysis of the randomized controlled trial AGITG-MAX

  Patients and methods: We analyzed tumor samples of 256 patients enrolled in the AGITG-MAX 3-arm randomized controlled trial (RCT) who were randomly assigned to receive either capecitabine, or capecitabine and bevacizumab with- or without mitomycin. Chromosome 18q11.2-q12.1 copy number status was measured and correlated with PFS according to a predefined analysis plan with marker-treatment interaction as the primary end-point.Results: Chromosome 18q11.2-q12.1 losses were detected in 71% of patients (181/256) characteristic for mCRC. Consistent with the non-randomized study, significant PFS benefit of bevacizumab was observed in chromosome 18q11.2-q12.1 loss patients (P=0.009), and not in 18q no-loss patients (P=0.67). Although significance for marker-treatment interaction was not reached (Pinteraction = 0.28), hazard ratio and 95% confidence interval (HRinteraction 0.72, CI 0.39 - 1.32) show striking overlap with the non-randomized study cohorts (HRinteraction 0.41, CI 0.32 - 0.8) supported by a non-significant Cochrane chi-squared (P=0.11) for heterogeneity. Conclusions: PFS characteristics for marker positive- and negative patients randomized for treatment with- or without bevacizumab were consistent with those of the non-randomized discovery study, though the number of AGITG-MAX samples fell short to reach significance for marker-treatment interaction. Post-hoc analysis of the AGITG-MAX RCT provides supportive evidence for chromosome 18q11.2-q12.1 as a clinically relevant predictive marker for mCRC patients.

  Study EGAS00001005453

• Low-coverage whole genome sequencing for a highly selective cohort of severe COVID-19 patients

  Background Despite advances in identification of genetic markers associated to severe COVID-19, the full genetic characterisation of the disease remains elusive. Imputation of low-coverage whole genome sequencing (lcWGS) has emerged as a competitive method to study such disease-related genetic markers as they enable genotyping of most common genetic variants used for genome wide association studies. This study aims at exploring the potential use of imputation in lcWGS for a highly selected severe COVID-19 patient cohort. Findings We generated an imputed dataset of 79 variant call format (VCF) patient files using the GLIMPSE1 tool, each containing, on average, 9.5 million single nucleotide variants. The validation assessment of imputation accuracy yielded a squared Pearson correlation of approximately 0.97 across sequencing platforms, showing that GLIMPSE1 can be used to confidently impute variants with minor allele frequency up to approximately 2% in Spanish ancestry individuals. We conducted a comprehensive analysis on the patient cohort, examining hospitalisation and intensive care utilisation, sex and age-based differences, and clinical phenotypes using a standardised set of medical terms specifically developed to characterise severe COVID-19 symptoms for this cohort. Conclusion This dataset highlights the utility and accuracy of lcWGS imputation in the study of COVID-19 severity, setting a precedent for other applications in resource-constrained environments. The methods and findings presented here may be leveraged in future genomic projects, providing vital insights for health challenges like COVID-19.

  Study EGAS00001007573

• Epigenetic age deceleration reflects fitness improvements following a six-month endurance exercise intervention

  Epigenetic clocks are emerging as promising biomarkers of biological aging, yet their sensitivity to short-term interventions remains unclear. This pilot study investigates whether the GrimAge clock can capture the effects of a six-month cycling-based endurance exercise training intervention, with cardiorespiratory fitness (VO₂ max) and body composition as primary outcomes. We enrolled 42 adults aged 35-65, of whom 38 completed the study and 33 adhered to the protocol (>66% adherence). Participants demonstrated significant improvements in VO₂ max (+20%, P < 0.001) and body composition (P < 0.001). High-quality epigenetic data preprocessing yielded highly reproducible GrimAge estimates (< 2 months measurement error), which strongly correlated with chronological age (R² = 0.86, P < 0.001). On average, GrimAge decreased by 7.44 months relative to the expected trajectory (P = 0.012), reflecting improvements in VO₂ max (R² = 0.27, P = 0.002) but not body composition changes. Notably, GrimAge changes strongly correlated with fluctuations in leukocyte composition, particularly neutrophil fraction (R² = 0.74, P < 0.001). Adjusting for leukocyte composition improved consistency in GrimAge changes, aligning them with additional intervention outcomes and explaining up to 81% of variance. These findings demonstrate that GrimAge is responsive to short-term endurance training, serving as a meaningful biomarker of improved cardiorespiratory fitness, while also capturing immune system variability. This study supports the use of GrimAge in evaluating longevity interventions and highlights the importance of accounting for leukocyte composition in epigenetic aging research.

  Study EGAS00001008221

• Krakow experiment - Northern Finland Birth Cohort 1966

  Study EGAS00000000114

• organoid data of colorectal cancers

  Study EGAS00001003360

• DAC for the cfSort study (tissue deconvolution)

  Dac EGAC00001003222

• DAC for study WES of pituitary tumors

  Dac EGAC00001000443

• Japan PBC-GWAS Haplotype Study Steering Committee

  Dac EGAC00001000872

• Lead investigator of the TONIC study

  Dac EGAC00001001150

• DAC for HSTCL study. National Cancer Centre Singapore.

  Dac EGAC00001001302

• DAC for MEITL study. National Cancer Centre Singapore.

  Dac EGAC00001001323

• NARPANord narcolepsy T cell study DAC

  Dac EGAC00001001855

• DAC for cell free DNA TAPS study

  Dac EGAC00001001903

• Liu et al 2020 Vietnamese study DAC

  Dac EGAC00001002551

• HUG-CELL Covid-19 Genomics Study Commitee

  Dac EGAC00001002916

• DAC for the study EGASXXX

  Dac EGAC00001002746

• Haplotyping project

  Haplotyping project

  Study EGAS00001007600

• DAC for the study EGAS00001007247

  Dac EGAC00001003262

• RNA sequencing of PTCL-NOS

  Study EGAS00001005015

• Genomic landscape of DS-ALL

  Study EGAS00001006600

• Tumor educated platelets for BrCA

  Study EGAS00001006821

• Genetic landscape of ENKTCL

  Study EGAS00001006906

• healthy kidney tissue from Wilms tumor patients

  Study EGAS00001008035