Search Results - EGA European Genome-Phenome Archive

Regulatory and Effector T cells in Oral Immunotherapy for Food Allergy

This study consisted of a clinical trial for peanut oral immunotherapy (OIT) and a follow-up project (see below). Patients were included from 2013-2015, and samples from the last timepoints were collected in 2017. The study focused on peanut-specific CD4+ T cell responses before, during, and after OIT with peanut protein. We analyzed T cell gene expression, cytokine production, and T cell receptor β (TCRβ) and TCRα clonotypes, both in bulk T cell populations and single cells, and sought to correlate these data with differences in clinical sensitivity between peanut-allergic patients before OIT, and with differences in clinical outcome after OIT. The goal was to better understand the role of peanut-specific effector and regulatory T cells in peanut allergy and tolerance, which may inform more effective therapies (e.g., OIT combined with biologicals, probiotics, or adjuvants) in the future. Tolerance Following Peanut Oral Immunotherapy (PNOIT2, NCT01750879): The unifying objective of this project is to determine whether peanut oral immunotherapy (PNOIT)-induced clinical tolerance in the context of food allergy is significantly associated with the expansion of a specific regulatory T cell subset (CD45RA-, CD25++, FoxP3+ +) that is thought to be inducible in the gut-associated lymphoid compartment and associated with immunological tolerance. The hypothesis of the study is that the induction of Treg cells will be associated with clinical tolerance. The investigators will measure the change from baseline of induced Treg cells as a frequency of total CD4+ T cells during active treatment and compare that between participants who achieve significant clinical tolerance and those who do not. High Threshold Peanut Challenge Study (PAID-UP, NCT02698033): This protocol was designed to better characterize a sub-population of peanut-sensitized individuals who may be non-allergic, despite significant sensitization, or who may be allergic, but at high threshold doses. By specifically targeting participants who met the initial screening criteria of an earlier study, NCT01750879, but failed to react during the pre-treatment 443 mg challenge to peanut, the investigators anticipate that they will identify individuals who have become spontaneously tolerant, despite persistent sensitization. The investigators might also find that clinical sensitivity persists but only with higher thresholds, or that sensitivity has increased (or is variable) since the previous allergen exposure. By repeating food challenges through to a full serving dose (7.4 gram), the investigators will distinguish participants who react only at higher doses from those who were not truly peanut-allergic, address whether their sensitivity has changed, and have the opportunity to further investigate their immune response to peanut allergen. Methods: Peripheral blood mononuclear cells were isolated from patient blood samples, and stimulated with peanut protein. Peanut-activated CD4+ T cells were sorted based on the activation marker CD154. For a more recent study, the activation marker CD137 was used as well. Total RNA from peanut-activated CD154+ and resting CD154- CD69- T cells was used for cDNA synthesis and amplification (SMARTer ultra low input RNA kit for sequencing - v3; Clontech Laboratories). Libraries were prepared and sequenced on the Illumina HiSeq platform, at a read depth of approximately 30 million reads per sample. Genomic DNA from CD154+ and CD154- CD69- T cells was used to amplify and sequence the TCRβ CDR3 regions (immunoSEQ assay; Adaptive Biotechnologies). The immunoSEQ approach generates an 87 base-pair fragment capable of identifying the VDJ region spanning each unique CDR3. Amplicons were sequenced using the Illumina NextSeq platform. Using a baseline developed from a suite of synthetic templates, primer concentrations and computational corrections were used to correct for the primer bias common to multiplex PCR reactions. Raw sequence data were filtered on the basis of TCRβ V, D, and J gene definitions provided by the IMGT database (www.imgt.org) and binned using a modified nearest-neighbor algorithm to merge closely related sequences and remove both PCR and sequencing errors. For single-cell analysis, we aimed to recover TCR variable sequences from high-throughput single-cell libraries generated by popular platforms such as SeqWell and DropSeq. We paired TCR information with T cell single-cell RNA sequencing results from patients undergoing peanut OIT to show clonal expansion-related T cell phenotypes.

Study phs001897

Spit for Science

Spit for Science™ is a university-wide research opportunity with the scientific goal of understanding how genetic and environmental factors come together to influence substance use and emotional health across the college years and beyond. To address this goal, we have comprehensively and longitudinally studied eligible incoming freshmen (18 years or older) from a diverse urban university, assessing a wide range of risk and protective factors, including both biological susceptibility and environmental risk, and a variety of outcome measures, particularly alcohol use and other substances, and difficulties with emotional health. Our goal is to assess how risk and protective factors dynamically interact to contribute to behavior health outcomes over time and plan to use findings from the project to inform prevention and intervention efforts and aid in university policy and programming in ways that can support and promote student success. Methods: In the fall of their freshman year, first-time college students over the age of 18 are invited to complete an online survey containing broad questions about personality and behavior, as well as family, friends, and experiences growing up. Students can also provide a saliva sample and participate in the DNA component of the project (participation in the DNA component is not a requirement for participation in the survey). Each subsequent spring students are asked to complete a follow-up survey, enabling researchers to study patterns of substance use and emotional health across the college years.

Study phs001754

Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma

Immune checkpoint inhibitors are effective cancer treatments, but molecular determinants of clinical benefit are unknown. Ipilimumab and tremelimumab are antibodies against cytotoxic T-lymphocyte antigen 4 (CTLA-4). Anti-CTLA-4 treatment prolongs overall survival in patients with melanoma. CTLA-4 blockade activates T cells and enables them to destroy tumor cells. We obtained tumor tissue from patients with melanoma who were treated with ipilimumab or tremelimumab. Whole-exome sequencing was performed on tumors and matched blood samples. Somatic mutations and candidate neoantigens generated from these mutations were characterized. Neoantigen peptides were tested for the ability to activate lymphocytes from ipilimumab-treated patients. Malignant melanoma exomes from 64 patients treated with CTLA-4 blockade were characterized with the use of massively parallel sequencing. A discovery set consisted of 11 patients who derived a long-term clinical benefit and 14 patients who derived a minimal benefit or no benefit. Mutational load was associated with the degree of clinical benefit (P = 0.01) but alone was not sufficient to predict benefit. Using genomewide somatic neoepitope analysis and patient-specific HLA typing, we identified candidate tumor neoantigens for each patient. We elucidated a neo-antigen landscape that is specifically present in tumors with a strong response to CTLA-4 blockade. We validated this signature in a second set of 39 patients with melanoma who were treated with anti-CTLA-4 antibodies. Predicted neoantigens activated T cells from the patients treated with ipilimumab.

Study phs001041

The Genetics of Type 2 Diabetes Consortium (GoT2D): Low-Pass Sequencing and High-Density SNP Genotyping for Type 2 Diabetes

The Genetics of Type 2 Diabetes Consortium (GoT2D) is a collaboration between the University of Michigan, the Broad Institute and the Wellcome Trust Centre for Human Genetics. The overall aim is to extend upon recent efforts, such as genome-wide association studies (GWAS) and large scale meta-analyses. While they have proved successful at mapping genomic loci that influence human diseases, like type 2 diabetes, much of the heritability remains unexplained. In this study, we use next generation sequencing and genotyping technologies to query for lower frequency variants in the human genome. Thereby, allowing a deeper characterization of the spectrum of alleles associated with type 2 diabetes risk, and a better assessment of the genes that play a role in the etiology of type 2 diabetes development. We studied 1,326 T2D cases and 1,331 normoglycemic controls from Northern and Central Europe (Sweden, Finland, UK, and Germany). To efficiently characterize the entire genome sequence of each individual, we performed low-coverage (~5x) whole-genome sequencing, augmented by deep coverage (~100x) sequencing of the exome (Fuchsberger et al, 2016), and dense (2.5M) single nucleotide polymorphism (SNP) genotyping using the HumanOmni2.5 array. The data deposited in dbGaP will include all the Swedish, Finnish, and UK samples, but the German data will be deposited in the European Genome-phenome Archive (EGA), by virtue of the project specific funding requirements.

Study phs000840

Risk Factors for Asymptomatic Diverticulosis

Data for this analysis came from a prospective study of colonic diverticulosis at the University of North Carolina Hospital in Chapel Hill, North Carolina (NIH R01DK094738). This is a case-control genetic and transcriptomic study to identify the genetic and cellular determinants underlying colonic diverticulosis and the relationship with other gastrointestinal disorders. The study inclusion and exclusion are described below. DNA and RNA sequencing were performed on colonic tissue from 404 patients with (N=172) and without (N=232) diverticulosis. We assessed variation in the transcriptome associated with diverticulosis and integrated this variation with human intestine single-cell RNA-seq data. We integrated our expression quantitative trait loci with GWAS using Mendelian Randomization. A polygenic risk score analysis examined associations between severity of diverticulosis and other gastrointestinal disorders. We identified 38 genes with differential expression and 17 genes with varied transcript usage linked to diverticulosis. Our results suggest tissue remodeling as a primary mechanism for diverticula formation. The presence of diverticulosis was linked to stromal and epithelial cells in the colon including endothelial cells, myofibroblasts, fibroblasts, goblet, tuft, enterocytes, neurons, and glia. MR highlighted five genes including CCN3, CRISPLD2, ENTPD7, PHGR1, and TNFSF13. In diverticulosis cases, ENTPD7 upregulation was confirmed. A greater burden of diverticula was positively correlated with genetic predisposition to diverticulitis. The data related to the study including total RNA-Seq, SNP array and imputed genotypes will be available through dbGaP.

Study phs003556

UCSF Database for the Advancement of JMML - Integration of Metadata with Omic Data

Juvenile myelomonocytic leukemia (JMML) is a rare and frequently fatal myeloproliferative/myelodysplastic disorder of early childhood with an estimated incidence of 1.2 cases per million. It is associated with a spectrum of diverse outcomes ranging from spontaneous resolution in rare patients to transformation to acute myeloid leukemia in others. The overwhelming majority of JMML patients (~95%) will harbor mutations in canonical Ras pathway genes, including NF1, NRAS, KRAS, PTPN11, and CBL. As Ras proteins are mutated in more than 30% of human cancers, the information gleaned from the study of JMML has provided insights into Ras signaling in cancer as well as a group of congenital diseases with tumor predispositions known as the “Rasopathies”. While oncogenic Ras is one of the most common mutations in human cancer, it remains one of the most vexing targets for efficacious therapy. To better understand this disease, a JMML tissue bank was established at UCSF that allows for consenting of subjects, biobanking of tissue and collection of follow up data from patients both locally and at other institutions. Through the collection and analysis of specimens, knowledge about the genetic, epigenetic, and biochemical basis of JMML has been gained. This integrated database will enable future JMML research, and importantly, additional Ras/MAPK pathway research by depositing linked, processed data to well annotated anonymized patients in an easily accessible online database

Study phs002504

H3.3G34R/V-transformed interneuron progenitors co-opt PDGFRA for gliomagenesis

Histone H3.3 glycine 34 to arginine/valine (H3.3G34R/V) mutations occur in deadly hemispheric high-grade gliomas. These tumors show exquisite regional and temporal specificity, suggesting a developmental context permissive to the effects of G34R/V mutations. Here we present the molecular landscape of G34R/V gliomas (n=85) and show that 50% bear activating mutations in PDGFRA, with strong selection pressure for PDGFRAMUT clones at recurrence. We show that G34R/V tumors arise in interneuron progenitors of the foetal ventral forebrain expressing GSX2 and the DLX family of homeobox transcription factors, where terminal neuronal differentiation is impaired through aberrant G34R/V-mediated H3K27me3. Frequent co-occurrence of G34R/V & PDGFRAMUT is facilitated in this interneuron lineage-of-origin as PDGFRA forms an aberrant chromatin loop with the adjacent GSX2, hijacking its active chromatin conformation. At the single-cell level, G34R/V tumours entirely lack oligodendroglial transcriptional programs prominent in other glioma entities, and instead harbour dual neuronal and astroglial compartments. CRISPR-removal of H3.3G34R/V does not impact tumorigenicity suggesting this mutation becomes dispensable, while PDGFRAMUT are potently oncogenic regardless of G34 mutation. Collectively, our results suggest that G34R/V gliomas arise in foetal interneuron progenitors unable to undergo terminal differentiation, enabling co-option of PDGFRA through inappropriate expression and activating mutations to promote gliogenesis and oncogenicity. Reliance on PDGFRA for oncogenesis may be of therapeutic opportunity in G34R/V glioma.

Study EGAS00001004301

Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

Study EGAS00001002073

Ultra-long sequencing for contiguous haplotype resolution of the human immunoglobulin heavy chain locus

Genetic diversity within the human immunoglobulin heavy chain (IGH) locus influences the expressed antibody repertoire and susceptibility to infectious and autoimmune diseases. However, repetitive sequences and complex structural variation pose significant challenges for large-scale characterization. Here, we introduce a method that combines Oxford Nanopore ultra-long sequencing and adaptive sampling with a bioinformatic pipeline to produce haplotype-resolved, annotated IGH assemblies. Notably, our strategy overcomes prior limitations in phasing resolution, enabling single-contig haplotype assemblies that span the entire IGH locus. We applied this method to four individuals and validated the accuracy of the IGH assemblies using Pacific Biosciences HiFi reads, demonstrating near-complete sequence congruence, detecting only indels with a high degree of confidence. Moreover, when applied to the reference material HG002, our pipeline revealed no base differences and a limited number of indels compared with the Telomere-to-Telomere genome benchmark across the IGH region. Importantly, in the four individuals, our approach uncovered 30 novel alleles and previously uncharacterized large structural variants, including a 120 kb duplication spanning IGHE to IGHA1 and an expanded seven-copy IGHV3-23 gene haplotype. These findings underscore the power of our method to resolve the full complexity of the IGH locus and uncover previously unrecognized variants that may affect immune function and disease susceptibility. Thus, our method provides a strong basis for future immunological research and translational applications.

Study EGAS50000001042

NIPT samples for systematic evaluation of BinDel, a software tool for detecting clinically significant microdeletions in low-coverage WGS-based NIPT samples

This dataset contains three sets of samples. The first sample set contains euploid fetus pregnancies reported by NIPTIFY screening test and postnatal evaluation. Dataset was processed similarly to previously published guidelines from KU Leuven, with modifications [1]. Briefly, peripheral blood samples were collected in cell-free DNA BCT tubes (Streck, USA), and plasma was separated with standard dual centrifugation. Cell-free DNA was extracted from 3 ml plasma using MagMAX Cell-Free DNA Isolation Kit (ThermoFisher Scientific). Whole-genome libraries were prepared using the FOCUS (Fragmented DNA Compact Sequencing Assay, Competence Centre on Health Technologies, Estonia) NIPT method protocol with 12 cycles for the final PCR enrichment step. In the following quantification, equal amounts of 36 samples were pooled, and the quality and quantity of the pool were assessed on Agilent 2200 TapeStation (Agilent Technologies, USA). Whole genome sequencing was performed on the NextSeq 550 instrument (Illumina Inc.) with an average coverage of 0.32× (minimum 0.08 and maximum 0.42) and producing 85 bp single-end reads. The second sample set contains a single NIPT sample postnatally diagnosed with Prader-Willi syndrome. The sample was sequenced with Illumina NextSeq 500 platform, producing 85 bp single-end reads with an average per-sample coverage of 0.32× at the University of Tartu, Institute of Genomics Core Facility, according to the manufacturer’s standard protocols, as described previously [2]. The third sample set contains samples SC005 (SeraCare Life Sciences Inc lot #10446565), SC0042 (#10571706), and SC016 (#10560229). These are SeraCare Life Sciences Inc circulating cell-free DNA (ccfDNA) like mixture of human genomic DNA that consists of matched maternal and fetus. SC005 and SC0042 consist of matched DNA of maternal and fetus with DiGeorge Syndrome. SC016 is a custom-ordered DNA Mix with fetus DNA having a pathogenic loss of the terminal region of 20p13 and a pathogenic 3q29 duplication. SC016 was processed as the first sample set was processed, and SC0042 was processed as the second sample set was processed. Sample SC005 was processed once as was sample set 1 and once as was sample set 2 processed. This study was performed with the approval of the Research Ethics Committee of the University of Tartu (#352/M-12). 1. Bayindir B, Dehaspe L, Brison N, Brady P, Ardui S, Kammoun M, et al. Noninvasive prenatal testing using a novel analysis pipeline to screen for all autosomal fetal aneuploidies improves pregnancy management. Eur J Hum Genet. 2015;23: 1286– 1293. doi:10.1038/ejhg.2014.282 2. Žilina O, Rekker K, Kaplinski L, Sauk M, Paluoja P, Teder H, et al. Creating basis for introducing noninvasive prenatal testing in the Estonian public health setting. Prenat Diagn. 2019;39: 1262–1268. doi:10.1002/pd.5578

Dataset EGAD00001009512

Whole genome bisufite sequencing for smoking and non-smoking mother-child pairs

WGBS data of whole blood samples from smoking and non-smoking mothers and their children at gestation/birth and follow-up years.

Dataset EGAD00001000366

NanoString raw data

NanoString raw data for a noeadjuvant combination PD-L1 plus CTLA-4 blockade trial on patients with cisplatin-ineligible operable urothelial carcinoma. All samples were FFPE tumor samples. Raw probe count data (.RCC files) were generated from nCounter Digital Analyzer (4.0.0.3).

Dataset EGAD00010001852

Genotype data of human CD4 Treg cell

Genotype data obtained using the coreExome Illumina SNP chip array for all the individuals included in the study of gene expression regulation in human primary regulatory CD4+ T cells (Tregs)

Dataset EGAD00010001848

SNPArray_Viet

The compressed file contains plink format file for the Affymetrix Human Origins SNP array data of 260 individuals generated and analyzed in Liu et al 2020 study of 22 ethnolinguistic groups in Vietnam.

Dataset EGAD00010002287

AmsterdamUMC Data Access Committee for the MAPS study

The current data access committee reviews and assesses data requests of researchers that seek to gain access to data acquired from the MAping the Peritoneal immune System (MAPS) project as performed at the AmsterdamUMC, Amsterdam, Netherlands.

Dac EGAC50000000096

Dataset for WGS head and neck cancer samples

This dataset contain WGS sequencing data of head and neck cancer samples as well as blood plasma controls. Sequencing was performed on Illumina Novaseq 6000 using KAPA HyperPrep Kit. The sequencing was always paired.

Dataset EGAD50000000233

CHIC_TPO3_2023

Human engineered CRC organoids (APC KO; KRAS G12D; TP53 KO) were grown in glucose, lactate or with DCA. Samples were collected 7 hours after the treatments and processed for bulk CHIC-seq.

Dataset EGAD50000000090

RNA-seq FASTQ files studied in A first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy

This data set contains 18 paired fastq files (RNA-seq).

Dataset EGAD50000000948

The taxonomic composition of the human microbiome of healthy donors

Single homogenized human stool samples from five healthy donors and mix were analyzed by shotgun sequencing to generate a baseline for the establishment of humanized microbiome to be transferred into mice.

Dataset EGAD50000001119

NICHE - DNA-seq of MMR proficient early stage colon cancers

The dataset includes 152 FASTQ files from paired-end WXS sequencing on Illumina HiSeq2500 or Novaseq 6000 for 31 pMMR patients. This includes 31 tumor DNA and 31 blood germline samples.

Dataset EGAD50000001247

cell-free methylated DNA immunoprecipitation and high-throughput sequencing data for samples from liver transplant recpients with graft pathologies

Bam and indexed bam files after removal of duplicates and trimming of the unique molecular identifiers. Sequencing was performed on NovaSeq 6000 platform.

Dataset EGAD50000001727

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