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• Genomics and Epigenomics of the Elderly Response to Pneumococcal Vaccines

  Pneumococcal Vaccine Study: This is a study designed to develop a detailed transcriptional and cellular profile of the immune response to pneumococcal vaccination with conjugated and non-conjugated polysaccharide vaccines in the senescent immune system of older adults. In this study, 39 healthy adults ages 60 and older that have never received pneumococcal vaccination, have been randomized to receive Prevnar 13 (Pfizer), a conjugated 13-valent vaccine or Pneumovax 23 (Merck), a non-conjugated 23-valent vaccine. Four (4) study visits occurred over 70 days at Day -7 (baseline), day 1, day 10 and day 60 (± 5d) post vaccination.Bulk RNA-sequencing data are available on the 4 time points for 31 of the participants and 1 replicate. ATAC-Doublet Detector Study: We generated single nucleus ATAC-seq (snATAC-seq) data from PBMCs of 2 baseline blood samples from the pneumococcal study. Generated data was then used to benchmark a novel computational method for detecting multiplets in snATAC-seq data, namely, AMULET (https://github.com/UcarLab/AMULET). Multiplets confound downstream analyses by introducing combined epigenomic profiles from 2 or more cells/nuclei. AMULET detects multiplets by using unique snATAC-seq data features that allow it to reliably use read counts to detect multiplets for their removal from data analyses.

  Study phs002361

• EGA FUSE Client

  EGA FUSE Client What is EGA FUSE Client? The EGA FUSE Client is a Java Native Runtime (JNR) based Filesystem in Userspace (FUSE) client that allows users to access authorised EGA files by presenting them in a virtual directory. This means that users can use authorised EGA files like regular files without having to download them first. The EGA FUSE Client is a useful tool for researchers who need to access and work with large amounts of EGA data. Why use EGA FUSE Client? The EGA FUSE Client provides several benefits for researchers working with EGA data: Efficient use of storage space: With the EGA FUSE Client, users can access authorised EGA files without having to download them first. This means that users can save storage space on their local machines. Faster access to data: Since users can access authorised EGA files directly through the EGA FUSE Client, they can work with the data more quickly than if they had to download the files first. Simplified workflow: The EGA FUSE Client presents authorised EGA files in a virtual directory, allowing users to work with the files like regular files. This simplifies the workflow for researchers who need to access and work with large amounts of EGA data. Get started with EGA FUSE Client To get started with EGA FUSE Client visit the EGA FUSE Client GitHub repository for more information and installation instructions.

  Documentation access/download/visualisation/fuse-client

• Single cell RNA-seq of two rare cases of human glioblastoma at multiple sampling points

  Glioblastoma is characterized by large cellular diversity whose complexity and organizing principles are only starting to be uncovered. Both neurodevelopment-like and mesenchymal-like cell states have been described in glioblastoma but the nature of the mesenchymal-like cell states remains unresolved. Here, we performed deep single-cell RNA sequencing of two rare glioblastoma cases where tissue could be sampled from tumor core to macroscopically normal cortex with the aim of understanding these tumor cell states.

  Study EGAS50000001030

• Treatment-mediated selection of lethal prostate cancer clones defined by copy number architectures

  Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient relationships of metastases that evade treatment, we performed genome- wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 142 metastatic regions from 10 organs harvested post-mortem from nine men who died from prostate cancer. We identified diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number change, we confirmed a common clone of origin across metastases and diagnostic biopsies; and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. Autosome-defined clusters were characterized by cluster-specific AR gene architectures that in two index cases were topologically more congruent than by chance (p-values 0.03, 3.07x10-8). Integration with anatomical site suggested patterns of spread and points of genomic divergence. Copy number boundaries identified treatment-selected clones with putatively distinct lethal trajectories.

  Study EGAS00001006598

• dbGaP Collection: Open Translational Science in Schizophrenia (OPTICS)

  Schizophrenia is a chronic, severe, disabling brain disorder that affects approximately 1% of the population worldwide. Epidemiologic studies have clearly demonstrated that genetics play a strong role in etiology, but the inheritance is very complex. Innovative analytic approaches and creative ways of combining disparate data sets will be necessary for making breakthroughs in identifying causal pathways and ultimately new drug targets. This dbGaP Collection consists of all genetic studies of schizophrenia available in dbGaP that have been consented for general research use. The goal is to facilitate identification of datasets with related scientific content in order to expedite the application process and ascertainment of datasets of interest for increased scientific discovery. The Open Translational Science in Schizophrenia (OPTICS) Project, was launched by Janssen Research & Development, LLC, part of the Janssen Pharmaceutical Companies of Johnson & Johnson, with a group of leading research organizations including the National Institutes of Health, Yale University School of Medicine, Rutgers University and the Harvard T.H. Chan School of Public Health, to create a new forum for collaborative analysis of Janssen's schizophrenia clinical trial data and other publicly available data about schizophrenia with the goal of creating new models for conducting research. The OPTICS project is one part of a larger effort at Janssen and other Johnson & Johnson research companies to share clinical trials data to enhance public health and advance science and medicine. Qualified investigators and physicians may apply for access to anonymized clinical trials data from Janssen, for more information please visit https://sites.google.com/site/opticsschizophrenia/.

  Study phs000887

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 40 samples matched to the WGS was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001009048

• scRNAseq dataset of circulating T cells in FL patient before and after Lenalidomide treatment

  scRNAseq dataset of circulating T cells from 3 FL patients (P011, P014 and P020) included in the GALEN clinical trial. There is two time points for each patient : One before treatment (D0) and one at day 7 of Lenalidomide treatment (D7).

  Dataset EGAD50000001529

• Cord blood progenitor CITE-seq dataset

  Sequencing results of single-cell transcriptome and antibody libraries from two biological experiments of cord blood progenitor cells. Four samples from different time points were processed using 10X Genomics Chromium Next GEM Single Cell 3’ Reagent Kits v3.1. Gene expression and antibody-derived libraries were sequenced separately.

  Dataset EGAD50000000405

• A Perioperative Study of Safusidenib in Patients with IDH1-Mutated Glioma

  10 participants with a radiological or pathological diagnosis of WHO Grade 2 lower-grade glioma (LGG) were recruited at a single center starting in December, 2022. Eligibility criteria permitted participants who had undergone prior surgery for WHO Grade 2 LGG, but excluded those with a history of prior radiation or chemotherapy.In Part A of the study, participants underwent an initial craniotomy with tumor biopsy and a lumbar puncture for cerebrospinal fluid (CSF) collection at study entry. Following sample collection, participants received safusidenib at the recommended phase 2 doses of 250 mg twice daily (b.i.d.) for a period of 22–36 days. This was followed by a second craniotomy for maximal safe tumor resection and a repeat lumbar puncture within 5 hours of the final pre-resection dose of safusidenib. Tumor, blood, and CSF samples were collected at both surgical time points for comprehensive translational research.Molecular analyses were performed on samples collected at both time points. These included pharmacokinetics (PK), targeted metabolomics, whole-genome sequencing (WGS) of tumor tissue, single-nucleus RNA sequencing (snRNA-seq), and DNA methylation profiling on all patients. Targeted metabolomics was conducted on samples from 9 participants, while spatial transcriptomics and spatial metabolomics were performed on tumor tissue from 3 participants each. Histone methylation profiling was conducted on samples from 8 participants.

  Study phs003976

• Novel Strategies to Eliminate Resistance to B-cell Receptor Inhibitor Therapy in Lymphoid Malignancies

  Ibrutinib and acalabrutinib are BTK inhibitors (BTKi) used as frontline therapies for chronic lymphocytic leukemia (CLL). Clonal evolution during ibrutinib treatment has previously been studied, but limited study of clonal evolution in patients receiving acalabrutinib has been done. Our group analyzed 216 blood samples from 38 CLL patients at multiple time points during their BTKi treatment. Samples were prepared by standard protocols and sequenced using 200x Illumina sequencing. Using the longitudinal data, we reconstructed the clonal evolution of each patient using somatic mutations found within the B-cell populations. Three patterns of clonal evolution were identified: 1) new clone emergence, 2) clonal selection, and 3) clonal replacement. As previously seen in ibrutinib treatment, the evolution of subclones containing CLL-driver mutations was associated with worse clinical outcomes for patients treated with acalabrutinib (Log-rank p=0.04). Understanding clonal evolution during treatment with acalabrutinib can help determine and modify the clinical course of patients with CLL.

  Study phs003042

• Transcriptomic classes of BCR-ABL1 lymphoblastic leukemia

  In BCR-ABL1 lymphoblastic leukemia, treatment heterogeneity to tyrosine kinase inhibitors (TKIs), especially in the absence of kinase domain mutations in BCR-ABL1, is poorly understood. Through deep molecular profiling, we uncovered three transcriptomic subtypes of BCR-ABL1 lymphoblastic leukemia, each representing a maturation arrest at a stage of B-cell progenitor differentiation. An earlier arrest was associated with lineage promiscuity, treatment refractoriness, and poor patient outcomes. A later arrest was associated with lineage fidelity, deep and durable leukemia remissions, and improved patient outcomes. Each maturation arrest was marked by specific genomic events that control different transition points in B-cell development. Interestingly, these events were absent in BCR-ABL1+ pre-leukemic stem cells isolated from patients regardless of subtype, which supports that transcriptomic phenotypes are determined downstream of the leukemia-initialing event. Overall, our data indicate that treatment response and TKI-efficacy is an unexpected outcome of the differentiation stage at which this leukemia transforms.

  Study EGAS00001007167

• RNA-seq of high grade serous ovarian tumours

  Somatic RNA for 37 samples was extracted using the Qiagen Qiasymphony RNA protcol (cat no 931636). The tissue was initially homogenised using a Qiagen Bioruptor, followed by the manufacturers recommended protocol (including DNase digestion). The resulting RNA the underwent quality control as follows: firstly, A260 and A280nm were measured on a Denovix DS-11 Fx to qualitatively illustrate A260/280nm and A260/230nm ratios as measures of RNA purity. A260/280 had to be 2.0 and A260/230 had to be 2.0-2.2. Then RNA was quantified using LifeTechnologies Qubit RNA BR kit (cat no Q10210). RNAseq was carried out by the Edinburgh Clinical Research Facility on an Illumina NExtSeq500. Total RNA samples were assessed on the Agilent Bioanalyser (Agilent Technologies, #G2939AA) with the RNA 6000 Nano Kit (#5067-1512) for quality and integrity of total RNA, and then quantified using the Qubit 2.0 Fluorometer (Thermo Fisher Scientific Inc, #Q32866) and the Qubit RNA HS assay kit (#Q32855). Libraries were prepared from total-RNA sample using the NEBNext Ultra 2 Directional RNA library prep kit for Illumina (#E7760S) with the NEBNext rRNA Depletion kit (#E6310) according to the provided protocol. 400ng of totalRNA was then added to the ribosomal RNA (rRNA) depletion reaction using the NEBNext rRNA depletion kit (Human/mouse/rat) (#E6310). This step uses specific probes that bind to the rRNA in order to cleave it. rRNA-depleted RNA was then DNase treated and purified using Agencourt RNAClean XP beads (Beckman Coulter Inc, #66514). RNA was then fragmented using random primers before undergoing first strand and second strand synthesis to create cDNA. cDNA was end repaired before ligation of sequencing adapters, and libraries were enriched by PCR using the NEBNext Multiplex oligos for Illumina set 1 and 2 (#E7500). Final libraries had an average peak size of 271bp. Libraries were quantified by fluorometry using the Qubit dsDNA HS assay and assessed for quality and fragment size using the Agilent Bioanalyser with the DNA HS Kit (#5067-4626). Sequencing was performed using the NextSeq 500/550 High-Output v2 (150 cycle) Kit (# FC- 404-2002) on the NextSeq 550 platform (Illumina Inc, #SY-415-1002). Libraries were combined in an equimolar pool based on the library quantification results and run across 5 High-Output Flow Cell v2.5.

  Dataset EGAD00001010139

• 16S-based fecal microbiota composition

  The dataset reports the 16S rRNA gene sequencing of the fecal microbiota of donors from the Milieu Intérieur Cohort. The Milieu Intérieur cohort includes a total of 1,000 healthy individuals of western European ancestry, recruited in France as part of the Milieu Intérieur project. To assess their fecal microbiota composition, 16S rRNA profiles were generated from stool samples of 863 of the 1,000 donors. Human stool samples were produced at home no more than 24 hours before the scheduled medical visit and collected in a double-lined sealable bag maintaining strict anaerobic conditions. Upon reception at the clinical site, the fresh stool samples were aliquoted and stored immediately at -80°C. DNA was extracted from stool and barcoding PCR was carried out using indexed primers targeting the V3-V5 region of the 16S rRNA gene. Equal volumes of normalized PCR reaction were pooled and thoroughly mixed. The amplicon libraries were sequenced on Illumina MiSeq.

  Dataset EGAD00001004979

• Drug-perturbation-based stratification of blood cancer

  As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.

  Study EGAS00001001746

• Whole Exome Sequencing analysis of three tumor biopsies from a LUAD patient

  Whole Exome Sequencing (WES) analysis was performed on three distinct tumor biopsies collected at different time points, along with their matched germline non-tumor sample, from the same LUAD patient. DNA was extracted using the DNeasy Blood and Tissue Kit (Qiagen, Germantown, MD) according to the manufacturer’s instructions and quantified using the Qubit Fluorometer assay (Life Technologies, Carlsbad, CA). To minimize FFPE-related sequencing artifacts (e.g., C:G > T:A transitions), the extracted DNA was treated with the DNA repair enzyme Uracil-DNA-Glycosylase (UDG) following the manufacturer’s protocol (New England Biolabs, Ipswich, MA). Whole-exome capture was performed with the Twist Human Core Exome + RefSeq + Mito-Panel kit (Twist Bioscience), in accordance with the manufacturer’s guidelines. Sequencing generated paired-end 100-bp reads on the Illumina NovaSeq 6000 platform. The resulting reads were aligned to the reference human genome (GRCh38) using the Burrows-Wheeler Aligner (BWA, v0.7.12).

  Dataset EGAD50000001198

• EOSC4Cancer Longitudinal Synthetic Colorectal Cancer Genomic data developed at BSC

  The synthetic genomes have been created trying to mimic real cancer data of 4 patients (Named 185,186,187 and 188). Mutations are based on real CRC patients from the PCAWG dataset. For each patient, two tumor samples at different time points and one healthy sample have been simulated. The cancer intra-tumor heterogeneity and evolution in the patients is depicted by simulating reads from tumor subclones separately and then mixing them according to their clonal proportions in each sample. For rapid use and transfer only selected chromosomes have been generated for each patient. Chromosomes per patient: -185: chr4, chr5, chr7, chr17 -186: chr1, chr7, chr12, chr17 -187: chr1, chr2, chr5, chr12, chr17 -188: chr2, chr5, chr12, chr13, chr17 Worflows used to create BAM/BAI, VCF and MAF files from FASTQ (Alignment with GRCh38): - https://usegalaxy.eu/published/workflow?id=2c3d05023c02113e - https://usegalaxy.eu/published/workflow?id=1da86d74f8535f4e

  Dataset EGAD50000000276

• Analysis_of_genomic_integrity_of_disease_corrected_human_induced_pluripotent_stem_cells_by_exome_sequencing

  Induced pluripotent stem (iPS) cells hold great promise for autologous cell transplantation. In order to apply this therapy to monogenic disorder, disease-causing mutations must be corrected prior to transplantation. We generated iPS cells from patients with alpha-1 antitrypsin deficiency, which is caused by homozygous non-synonymous mutation in the SERPINA1 gene. In vitro differentiation of patient-derived iPS cells to hepatocytes showed recapitulation of the disease phenotype. We corrected the mutations by gene targeting using zinc finger nuclease (ZFN) and piggyBac transposon technologies. Our mutation correction is highly accurate. There is no exogenous sequence left behind at the targeted site. The corrected iPS cell-derived hepatocytes were indistinguishable from healthy hepatocyte, suggesting that the corrected gene was fully functional. The genomic integrity was also analyzed by CGH and SNP array, showing no genomic alterations. These are important points to ensure clinical safety as well as functional restoration of the corrected gene. One remaining question is if these corrected iPS cells are clinically safe at the single base-pair level. Recent publications suggested that cancer-related mutations are significantly accumulated during iPS cell propagation. We aim to assess the clinical safety of the corrected iPS cells by using exome sequencing. Outcome from this project would bring iPS cell technology one step closer to clinical applications.

  Study EGAS00001000055

• T-VEC CBCL scRNA

  We are presenting raw and processed data of our study where we analyze fine-needle aspirate (FNA) samples of primary cutaneous B-cell lymphoma patients undergoing oncolytic virotherapy (https://clinicaltrials.gov/ct2/show/NCT03458117). We are uploading single cell RNA-sequencing and immune repertoire profiling data of 29 FNA samples from four pCBCL patients. The four patients have three different subtypes of primary cutaneous B-cell lymphoma: pCDLBCL-LT, pCFCL and pCMZL. The samples are taken at different time points following T-VEC injection (from baseline up to 91 days after injection). We are uploading the sequences in BAM format and the outputs of the cellranger pipeline (count matrices and filtered VDJ contigs) in CSV format.

  Dataset EGAD00001006829

• Longitudinal RNA-seq datasets from patients after abdominal surgery

  This dataset consists of RNA-seq data of 126 whole-blood samples derived from patients after abdominal surgery. Total-RNA collected preoperatively and at 3-time points postoperatively (2-6, 24 and 48hrs) were analysed using RNA-sequencing. RNA was collected in PAXGene (Qiagen) tubes and extracted using the PAXGene RNA extraction kit, with a DNase step to remove contaminating DNA. Globin and ribosomal RNA were removed via a Ribo-zero kit (Illumina) and library preparation was carried out using the TruSeq Stranded Total RNA Library Prep Kit (Illumina). Next generation sequencing was performed on the NovaSeq sequencing platform (Illumina) at the Wellcome Centre for Human Genetics (WCHG) in Oxford.

  Dataset EGAD00001011102

• Fecal metagenomics and plasma metabolomics

  This dataset contains all fecal shotgun metagenomics and metabolomics of the study which investigated the effects of the probiotic strain Anaerobutyricum soehngenii. Shotgun data is from three different time points, baseline and two follow up. Metabolomics sets are pre and post intervention, both fasted and post prandially. Data on randomization and metformin use can be found in the analysis.

  Dataset EGAD50000000608

• Spatial multi-omic map of human myocardial infarction

  Myocardial infarction is a leading cause of mortality worldwide 1 . While advances have been made in acute treatment, an incomplete understanding of remodelling processes has limited the effectiveness of therapies to reduce late-stage mortality 2 . Here, we generate an integrative high- resolution map of human cardiac remodelling after myocardial infarction using single-cell gene expression, chromatin accessibility, and spatial transcriptomic profiling of multiple physiological zones at distinct time points in myocardium from myocardial infarction and control patients. Multimodal data integration allowed us to evaluate cardiac cell-type compositions at increased resolution, yielding insights into changes of the cardiac transcriptome and epigenome through the identification of distinct tissue structures of injury, repair and remodelling. We identified and validated disease-specific cardiac cell-states of major cell-types and analysed them in their spatial context, evaluating their dependency on other cell-types. Our data elucidates molecular principles of human myocardial tissue organisation, recapitulating a gradual cardiomyocyte and myeloid continuum following ischemic injury. In total, our study provides an integrative molecular map of human myocardial infarction and represents an essential reference for the field and paves the way for advanced mechanistic and therapeutic studies of cardiac disease.

  Study EGAS00001006330

• NHLBI TOPMed: GOLDN Epigenetic Determinants of Lipid Response to Dietary Fat and Fenofibrate

  The GOLDN study was initiated to assess how genetic factors interact with environmental (diet and drug) interventions to influence blood levels of triglycerides and other atherogenic lipid species and inflammation markers (registered at clinicaltrials.gov, number NCT00083369). The study recruited Caucasian participants primarily from three-generational pedigrees from two NHLBI Family Heart Study (FHS) field centers (Minneapolis, MN and Salt Lake City, UT). Only families with at least two siblings were recruited and only participants who did not take lipid-lowering agents (pharmaceuticals or nutraceuticals) for at least 4 weeks prior to the initial visit were included. The diet intervention followed the protocol of Patsch et al. (1992). The whipping cream (83% fat) meal had 700 Calories/m2 body surface area (2.93 mJ/m2 body surface area): 3% of calories were derived from protein (instant nonfat dry milk) and 14% from carbohydrate (sugar). The ratio of polyunsaturated to saturated fat was 0.06 and the cholesterol content of the average meal was 240 mg. The mixture was blended with ice and flavorings. Blood samples were drawn immediately before (fasting) and at 3.5 and 6 hours after consuming the high-fat meal. The diet intervention was administered at baseline as well as after a 3-week treatment with 160 mg micronized fenofibrate. Participants were given the option to complete one or both (diet and drug) interventions. Of all participants, 1079 had phenotypic data and provided appropriate consent, and underwent whole genome sequencing through the Trans-Omics for Precision Medicine (TOPMed) program. Comprehensive phenotypic and pedigree data for GOLDN study participants are available through dbGaP phs000741.

  Study phs001359

• VCRC Imaging Protocol for Magnetic Resonance and Positron Emission Tomography in Large-Vessel Vasculitis (Takayasu's Arteritis): Development as Clinical Trial Outcome Measures Vasculitis Clinical Research Consortium

  Takayasu's arteritis is a rare disease that affects the blood vessels. Takayasu's arteritis can cause swelling of large and medium-sized blood vessels. The blood vessels that are commonly affected are the branches of the aorta (the main blood vessel that leaves the heart). The purpose of this study is to help doctors learn more about this disease by using x-ray like tests to see if they are helpful in taking care of patients with Takayasu's arteritis. This is an imaging study that compares x-ray-like tests that would not be a part of your regular care (PET/CT) with x-ray-like tests that are a part of your regular care (MRI). At two visits, three months apart, patients will have a PET/CT scan performed at the same time as their MRI scan; some patients will also have a third PET/CT scan. A total of 36 people with Takayasu's arteritis at several hospitals will take part in this study. Doctors will use images from the different time points, along with information from exams and symptoms, to learn more about the disease.

  Study phs001715

• WES Elucidation of Pathogenetic Mechanisms for Immune System Disorders and NIAID Pilot of Genetic Incidental Finding Management

  Background: - There are many types of immune disorders. These range from rare immune deficiencies to allergies to autoimmune disease like rheumatoid arthritis. Genes are the instructions our body uses to work and develop. A new technology called whole exome sequencing may help find the cause of these disorders. Whole exome sequencing is a way to look at many genes at once for errors. Researchers hope to find new gene changes that lead to immune disorders. Additionally, researchers are interested in finding the best way to manage unexpected but important findings by whole exome sequencing. Objectives: - To better understand genetic causes of immune system disorders. Also, to better understand people s thoughts and feelings about immune system disorders and new genomic testing. Eligibility: - People ages 0 100 with an immune disorder or a relative with an immune disorder. People must be at least 2 to be evaluated at the NIH clinical center. People must be at least 12 to do the survey/interview portion of the study. Design: Participants will have their genes sequenced. They may be asked for a new sample of blood. If participants cannot come for a study visit, they can have a blood sample collected by their local lab or doctor and sent by mail. Researchers may or may not find the cause of the participant s immune disorder. Participants will learn that information. Some participants may be asked to return to NIH to get results and have more tests. Researchers may share information with other studies. The data will be anonymous. For the survey part of the study, participants will answer questions about their or their relative s immune disorder. They will also answer about their thoughts and feelings about genomic testing. Some participants will be asked for a brief interview to ask more about the survey topics. There may be more follow-up after several months. From clinicaltrials.gov

  Study phs001561

• Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

  Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via "mapping" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

  Study EGAS00001003452