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• 10x Multiome from Human Fetal Heart

  We hope to uncover the genetic basis of congenital heart disease by examining how genetic variants, especially those in non-coding regions, influence heart development. To achieve this goal, our research team created a single-cell atlas of human fetal heart development. The study population consists of 41 structurally normal fetal hearts spanning 6 to 22 weeks post-conception. We profiled close to 750,000 using single-cell RNA sequencing and ATAC sequencing technologies via the 10x Genomics Multiome platform.The molecular technologies employed allowed for simultaneous analysis of gene expression and chromatin accessibility at the single-cell level. This approach identified numerous distinct cell types and states within the developing heart, offering detailed insights into gene activity and enhancer usage during critical stages of heart development.Principal findings include the characterization of diverse cell populations and the identification of specific gene expression patterns and regulatory elements active during heart formation. This high-resolution atlas provides valuable insights into how genetic variants may disrupt normal heart development, particularly those in non-coding regions that affect gene regulation.

  Study phs003778

• Phase I Study and Cell-Free DNA Analysis of T-DM1 and Metronomic Temozolomide for Secondary Prevention of HER2-Positive Breast Cancer Brain Metastases

  This study is a phase I trial combining ado-trastuzumab emtansine (T-DM1) with Temozolomide (TMZ) for the prevention of additional brain metastases after previous occurrence and local treatment in HER2+ breast cancer patients. Twelve patients were enrolled in this study. Data includes whole exome sequencing (WES) from patients' cerebrospinal fluid (CSF) and plasma samples. The CSF was collected from each patient at trial entry and after the initial two treatment cycles of TMZ and T-DM1 treatment. Blood was collected through a standard peripheral venipuncture at the following four time points: 1) upon trial entry, 2) after two treatment cycles, 3) the treatment cycle prior to the last follow-up, and 4) most recent follow-up. Whole exome libraries were captured by the SureSelect Human All Exon V8 Kit (Agilent, Santa Clara, CA, USA) and sequenced by NovaSeq 6000 S2 Sequencer in paired-end sequencing mode (Illumina, San Diego, CA, USA). Gene mutations in DNMT3A, ELP1, NOTCH4, KMT2B, CRLF2, and KCNJ18 were observed in patients' CSF.

  Study phs003165

• Analysis of mechanisms of CD19- relapse following novel low affinity CD19 Chimeric Antigen Receptor (CAR) T-cells (CD19 CAR T-cells) in a Phase I clinical study in paediatric ALL: CARPALL

  Phase I clinical study (CARPALL, NCT02443831) utilizing a novel low affinity CD19CAR CAR in patients age <25 with high risk CD19+ ALL. Seventeen patients were enrolled and 14 received an infusion of CAR T cells. Among those achieving complete remission, 6 subsequently relapsed, 5 with CD19- disease, 1 with CD19+ disease. Whole exome sequencing of bone marrow DNA from patients with CD19- relapse showed mutations in the CD19 gene predicted to result in loss of surface expression in 4/5 patients. These mutations were not detectable prior to CAR T cell therapy. With a median follow-up of 14 months, 5/14 patients (36%) are alive and disease-free. Overall survival was 84% at 6 months and 63% at 12 months and by the criteria used in the ELIANA study, event-free survival was 67% and 46%. Using more stringent criteria where an event is defined as molecular relapse, molecular EFS was 55% and 29 %. The median duration of remission in responding patients was 7.4 months.

  Study EGAS00001003733

• HSC_population_dynamics___KX004_samples___WGS

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001003768

• HSC_population_dynamics___CB002_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001003743

• HSC_population_dynamics___KX007_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001004193

• HSC_population_dynamics___KX008_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001004490

• HSC_population_dynamics_KSP_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001002762

• HSC_population_dynamics_CBD_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001003091

• HSC_population_dynamics___KX003_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001003550

• HSC_population_dynamics___TG001_2_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001003688

• HSC_population_dynamics___PX001_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001004146

• HSC_population_dynamics___KX009_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001004580

• HSC_population_dynamics___KX010_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001004581

• HSC_population_dynamics___LEUK4_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001004247

• HSC_population_dynamics___CB001_samples

  My research project aims to use the clonal dynamics of spontaneously occurring somatic mutations to answer fundamental questions about human haematopoietic stem cell (HSC) biology. The four major questions I will address are: 1. How do age and aging affect normal human HSC dynamics in vivo? 2. How do in vivo perturbations, particularly chemotherapy and increased levels of reactive oxygen species, affect HSC population dynamics? 3. Is response to in vitro perturbation heritable and/or correlated with other features such as age of individual and contribution of the lineage to peripheral blood? 4. How are HSC dynamics altered in people with early driver mutations (clonal haematopoiesis)?

  Study EGAS00001003397

• 86 paired-end MiSeq 16S rRNA sequencing samples

  We compared bacterial communities in breast milk from teen (≤19 yr, n = 26) vs. adult (>19 yr, n = 56) mothers, normal weight (BMI 18.5-24.9, n = 63) vs. overweight (BMI ≥ 25, n = 19) mothers, primiparous (parity = 1, n = 41) vs. multiparous (parity > 1, n = 44), early (5-46d postpartum, n = 39) vs. established lactation (4-6 mo postpartum, n = 45), breastfeeding (EBF: PBF, n = 72) vs. mixed feeding (n = 11) and mothers with (Na/K ratio < 0.6, n = 75) and without SCM (Na/K ration ≥ 0.6, n = 10).

  Dataset EGAD00001004160

• Sequencing of pancreatic cancer primary tumors and metastases

  The extent of heterogeneity of driver gene mutations present in naturally occurring metastases is largely unknown, i.e. treatment-naïve metastatic disease. To address this issue, 60x whole genome sequencing of 26 metastases from 4 patients was carried out. We found that the identical driver gene mutations were present in every metastatic lesion of each patient studied. Passenger gene mutations not known or predicted to have functional consequences accounted for all intratumoral heterogeneity. Even with respect to these passenger gene mutations, the genetic similarity among the founding cells of metastases was markedly higher than that expected for any two cells randomly taken from a normal tissue. The uniformity of driver gene mutations among metastases in the same patient has critical, encouraging implications for the success of future targeted therapies in advanced stage disease.

  Study EGAS00001002186

• Germline RUNX1 Variation and Predisposition to Childhood Acute Lymphoblastic

  Somatic mutations of RUNX1, which encodes the myeloid and lymphoid transcriptional factor RUNX1, are common in both B- and T- acute lymphoid leukemia (ALL) and are associated with poor prognosis of T-ALL. However, there has been no comprehensive investigation of the pattern or prevalence of RUNX1 germline mutation in both B- and T-ALL. Here we report germline RUNX1 variants in 1.23% of B-ALL and 2.11% of T-ALL, identifying 31 unique variants in 62 B-ALL and 18 unique variants in 26 T-ALL children. The majority of frameshift and nonsense variants affected RUNX1 function in transcriptional regulation, hematopoiesis, and cellular proliferation. We identified JAK3 as the most frequent somatic mutation in T-ALL with RUNX1 variants. These results not only identify RUNX1 as a leukemia predisposition gene but also further underline the importance of germline genetic variants to the development of ALL

  Study EGAS00001005403

• Test Study for EGA using data from 1000 Genomes Project - Phase 3

  The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies...

  Study EGAS00001005042

• Transcriptome profiling of human lung fibroblasts in COPD

  Primary lung fibroblast were isolated from well-matched control donors (no COPD, n=3) and patients with COPD (GOLD stage I-IV, n=8). Total RNA of cultured human lung fibroblast were isolated at passage 3 and rRNA was depleted. 75 bp single-end reads were generated from RNA libraries on Illumina NextSeq 500.

  Dataset EGAD00001009405

• Transcriptional_reprogramming_from_innate_immune_functions_to_a_pro_thrombotic_signature_upon_SARS_CoV_2_sensing_by_monocytes_in_COVID_19

  Alterations in the myeloid immune compartment have been observed in COVID-19, but the specific mechanisms underlying these impairments are not completely understood. Here we examined the functionality of classical CD14+ monocytes as a main myeloid cell component in well-defined cohorts of patients with mild and moderate COVID-19 during the acute phase of infection and compared them to that of healthy individuals. We found that ex vivo isolated CD14+ monocytes from mild and moderate COVID-19 patients display specific expression patterns of costimulatory and inhibitory receptors that clearly distinguish them from healthy monocytes, as well as an altered metabolic profile. In addition, decreased NFB activation in COVID-19 monocytes ex vivo is accompanied by an intact type I IFN antiviral response. Secondary pathogen sensing ex vivo led to a state of functional unresponsiveness characterized by a defect in pro-inflammatory cytokine expression, NFB-driven cytokine responses and defective type I IFN response in moderate COVID-19 monocytes, together with defects in the metabolic reprogramming that innate immune cells usually undergo upon pathogen sensing. Transcriptionally and functionally, COVID-19 monocytes switched their gene expression signature from canonical innate immune functions to a pro-thrombotic phenotype characterized by enrichment of pathways involved in hemostasis, immunothrombosis, platelet aggregation and other accessory pathways to platelet activation, accumulation and clot formation, including extracellular matrix reorganization, integrin cell surface interactions and signaling by PDGF. These results provide a potential mechanism by which innate immune dysfunction in COVID-19 may contribute to disease pathology

  Study EGAS00001006788

• Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study

  Study population The WECARE Study is an international multicenter population-based case-control study of cases with asynchronous contralateral breast cancer (CBC) and individually matched controls with unilateral breast cancer (UBC). Recruitment and data collection for the WECARE Study were conducted in two phases, herein referred to as WECARE I (2001–2004) and WECARE II (2009–2012). The study design of the first phase (WECARE I) has been described in detail elsewhere [Bernstein JL, et al 2004, PMID: 15084244]; the second phase (WECARE II) employed a nearly identical approach [Langballe R, et al 2016, PMID: 27400983]. Participants in each phase were identified through eight population-based cancer registries, including six in the United States that contribute to the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program: Los Angeles County Cancer Surveillance Program; Cancer Surveillance System of the Fred Hutchinson Cancer Center (Seattle region, WA); State Health Registry of Iowa; Cancer Surveillance Program of Orange County/San Diego-Imperial Organization for Cancer Control (Orange County/San Diego, CA); the Greater Bay Area Cancer Registry (San Francisco Bay Area region and Santa Clara region, CA); and the Sacramento and Sierra Center Registry (Sacramento region, CA). Participants were additionally identified using the Ontario Cancer Registry (Canada) and the Danish Breast Cancer Cooperative Group Registry, supplemented by data from the Danish Cancer Registry. The study protocol was approved by the institutional review or regulatory ethics boards at each study site. Data collection Study participants were interviewed by telephone using a structured questionnaire aimed at evaluating known or suspected breast cancer risk factors, including personal demographics, medical history, menstrual and reproductive history, family history of cancer, use of hormones, smoking, and alcohol intake. Risk factor status was assessed during the period prior to first diagnosis, as well as between first diagnosis and reference date (i.e., the at-risk period for CBC). Detailed data on treatment and tumor characteristics were obtained directly from cancer registry records or by abstracting medical records, including pathology and surgical reports, radiation oncology clinic notes, and systemic adjuvant treatment data. Complete medical treatment history information was collected, and for all women who received radiotherapy, the radiation dose to the contralateral breast was reconstructed using radiotherapy records and radiation measurements. Biospecimens were collected from study participants for genotyping: blood collected from WECARE I women; and saliva collected from WECARE II women.

  Study phs003945

• WES and RNAseq dataset

  This dataset includes WES and RNAseq for 7 patients with metastatic melanoma (4), non-small cell lung adenocarcnioma (1), cervix adenocarcinoma (1), and Epidermoid nasophaeyngeal carcinoma (1), enrolled in phase I clinical trials (NCT03475134m NCT04643574 and NCT05195619). WES was performed on matched cancer and healthy tissues, whereas RNAseq was performed on cancer tissues, using Illumina HiSeq 4000/6000 and Illumina NextSeq 500/550 systems.

  Dataset EGAD50000000337

• HIPO016 - glioblastoma tumour methylation microarray profiling

  Methylation microarray profiling (Illumina Human Methylation 450k and EPIC platforms) of 60 adult glioblastomas. Tumours were subtyped using the approach from Sturm et al. (https://doi.org/10.1016/j.ccr.2012.08.024): 12 IDH, 18 MES, 12 RTK I, 18 RTK II. DNA was prepared, assayed on the microarrays, and raw data computationally processed as described in Capper et al., "DNA methylation-based classification of central nervous system tumours": https://www.nature.com/articles/nature26000

  Dataset EGAD00010001797