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• Functional genomics approaches to understand osteoarthritis (2019-08-01)

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). We will obtain diseased and non-diseased cartilage as well as other disease-relevant tissue following TJR, coupled with a blood sample. We will generate genotype data and will characterise the pairs of diseased and non-diseased tissue samples in terms of methylation, transcription (RNASeq) and expression (quantitative proteomics). We will apply integrative approaches to combine information across the omics levels to characterise genes, pathways, and networks that underlie osteoarthritis progression. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-08-01.

  Dataset EGAD00001005215

• PELICAN33 Phenomic Dataset

  To better understand variation in metastatic prostate cancer behaviour, we assembled and analyzed longitudinal clinical and autopsy records in 33 men. The dataset is contained in a self-explanatory Excel Workbook, with each patient identified as A1, A2, etc. as listed in the "Combined longitudinal clinical and autopsy phenomic assessment in lethal metastatic prostate cancer: recommendations for advancing precision medicine" publication in European Urology Open Science. Please see Jasu J, Tolonen T, Antonarakis ES, Beltran H, Halabi S, Eisenberger MA, Carducci MA, Loriot Y, Van der Eecken K, Lolkema M, Ryan CJ, Taavitsainen S, Gillessen S, Högnäs G, Talvitie T, Taylor RJ, Koskenalho A, Ost P, Murtola TJ, Rinta-Kiikka I, Tammela T, Auvinen A, Kujala P, Smith TJ, Kellokumpu-Lehtinen PL, Isaacs WB, Nykter M, Kesseli J, Bova GS. Combined Longitudinal Clinical and Autopsy Phenomic Assessment in Lethal Metastatic Prostate Cancer: Recommendations for Advancing Precision Medicine. Eur Urol Open Sci. 2021 Jul 2;30:47-62. doi: 10.1016/j.euros.2021.05.011. PMID: 34337548; PMCID: PMC8317817. for more details.

  Dataset EGAD00001007800

• Rare Disease Synthetic Dataset

  The purpose of this project is to provide public human datasets for the study of rare diseases. The use of public human genomic background combined with the in-silico insertion of real disease-causing variants enable to have a representative dataset for testing purposes without facing ethical and legal issues associated with the use of human sensitive data. This project aims to help development of technical implementations for rare disease data integration, analysis, discovery, and federated access.

  Dataset EGAD00001008392

• Postmortem Single Nuclei and Bulk RNA-seq data of the Motor Cortex and Spinal Cord for Healthy, C9ALS and sALS Patients

  This dataset contains both snRNA-seq and bulk RNA-seq data from 19 different patients, comprising of 9 healthy controls (4 Spinal Cord, 5 Motor Cortex) as well as 5 C9ALS patients and 5 sporadic ALS patients, each with paired data from the spinal cord and motor cortex. For the snRNA-seq data, fastq files containing the raw reads are provided, many of these samples were pooled for sequencing and subsequently require demultiplexing using SNPs using a tool such as freemuxlet. The paired bulk RNA-seq data (raw fastq files) can be used to acquire the ground truth per patient - a list of pooled samples can be found in map.txt. snRNA-seq data was produced using the 10X Genomics 3' v3 kit and bulk RNA-seq was produced using the Illumina TruSeq v2 kit.

  Dataset EGAD00001009686

• Platelets contain a repertoire of DNA fragments that map over the human nuclear genome, including tumour-derived DNA in patients with active malignancy.

  This dataset consists of WGS from six patients with a recent diagnosis of gastrointestinal adenocarcinoma. DNA-Seq libraries were prepared from platelet DNA (pDNA) and plasma cfDNA obtained from the same peripheral blood sample. pDNA was size selected into 2 groups (small, s-pDNA: less than 600 bp and long, b-pDNA: greater than 600 bp). The short fragments were further cleaned to remove <100 bp fragments and large platelet fragments were fragmented via sonication. Libraries were then prepared using the NEBNext Ultra II DNA Sample Preparation Kit for Illumina according to the manufacturer’s protocol and sequenced on an Illumina NextSeq 500 (300 cycle PE) at low-pass (0.1X) for all samples, and 10X for the cfDNA and s-pDNA, using four lanes in each sample.

  Dataset EGAD00001009856

• CCA ChIP-seq data (63 CCA, 8 normal, 19 cell-line)

  Fastq files for H3K27ac ChIP-seq (with matched input-DNA control) for 63 CCAs, 8 normal bile duct tissues, 16 CCA cell-lines (including replicates), and 3 normal cholangiocyte cell-lines (including replicates). Library prep was performed with the NEBNext ChIP-seq library preparation kit. Each library (including matching input DNA) was sequenced to an average depth of 20 to 30 million raw reads on Illumina HiSeq4000 sequencer, with paired-end sequencing (except for 3 normal bile tissues done with single-end sequencing).

  Dataset EGAD00001012103

• Metabolomic and microbiome profiling reveals personalized risk factors for coronary artery disease

  A comprehensive clinical and multi-omic profiling for 199 patients with acute coronary syndrome (ACS), an acute subcategory of CAD, that we recruited in two major Israeli hospitals. We demonstrate that ACS has distinct serum metabolome and gut microbial signatures, as compared to a control cohort. Metabolic aberrations linked with microbiome and diet show a gradual trend with significant metabolite deviations in control participants with metabolic impairment suggesting their involvement in earlier dysmetabolic phases preceding clinically overt CAD.

  Study EGAS00001005342

• Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud university medical center

  Dac EGAC00001003193

• DAC for genomic data obtained within the Micrometastasis (Oslo1) project from Oslo, Norway

  Dac EGAC00001000558

• DAC for Transcriptome analysis in very preterm infants with chronic lung disease after birth

  Dac EGAC00001000698

• DAC for Cardiac Translatomes of 80 Human Samples (65 DCM cases 15 controls)

  Dac EGAC00001001040

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation Committee

  Dac EGAC00001001226

• Genomics to select patients with metastatic breast cancer for targeted therapy DAC

  Dac EGAC00001002293

• Data Access Committee for the project: Epic arrays from human OB and their mimics

  Dac EGAC00001002482

• The Data Access Committee for Human Olfactory Mucosa Cells (DAC_HOM) at UEF

  Dac EGAC00001002527

• The EMC-NICHE DAC considers appeals for hematopoietic/niche-related data sets.

  Dac EGAC00001001897

• Translational Gastroenterology Unit, University of Oxford Data Access Committee for the EPIC-CD study

  Dac EGAC00001003481

• Cyr61-MAC DAC

  DAC for access to dataset on Cyr61-MAC and HUVEC

  Dac EGAC50000000355

• Data access committee for datasets generated by the Tampere University Computational Biology research group

  Dac EGAC50000000177

• DAC_For_MPN

  This is the DAC for the MPN data set from Milena Kalmer.

  Dac EGAC50000000531

• DAC PRECISE Bennstein

  Data access control for datasets submitted by SysMed - PRECISE

  Dac EGAC50000000476

• A genome-wide association study for nasopharyngeal carcinoma in Hong Kong population

  Study EGAS00001006102

• Exploration of neuroblastoma xenograft models for tumor extracellular RNA profiling in murine blood plasma

  Study EGAS00001007295

• Mesothelima_OSCHP_Files

  Oncoscan CHP files for the Mesothelemia Project

  Dataset EGAD00010001540

• Transcriptome sequencing in monozygotic twins discordant for Mayer-Rokitansky-Küster-Hauser syndrome

  Study EGAS00001006370

• Cancer Alliance Exome

  Exome sequencing for individualized cancer interpretation

  Dataset EGAD00001006236

• Hostage_2_phenotype_basic

  Basic phenotypes for Hostage2 cohort.

  Dataset EGAD00001007840

• BelCovid_2_phenotype_basic

  Basic phenotypes for BelCovid2 cohort.

  Dataset EGAD00001007834

• BRACOVID_phenotype_lab

  Lab values for BRACOVID cohort.

  Dataset EGAD00001007833

• BRACOVID_phenotype_basic

  Basic phenotypes for BRACOVID cohort.

  Dataset EGAD00001007832

• Hostage_3_phenotype_basic

  Basic phenotypes for Hostage3 cohort.

  Dataset EGAD00001007842

• SPGRX_phenotype_basic

  Basic phenotypes for SPGRX cohort.

  Dataset EGAD00001007848

• Hostage_1_phenotype_lab

  Lab values for Hostage1 cohort.

  Dataset EGAD00001007839

• INMUNGEN_CoV2_phenotype_lab

  Lab values for INMUNGEN_CoV2 cohort.

  Dataset EGAD00001007847

• INMUNGEN_CoV2_phenotype_basic

  Basic phenotypes for INMUNGEN_CoV2 cohort.

  Dataset EGAD00001007846

• Hostage_4_phenotype_lab

  Lab values for Hostage4 cohort.

  Dataset EGAD00001007845

• Hostage_4_phenotype_basic

  Basic phenotypes for Hostage4 cohort.

  Dataset EGAD00001007844

• Hostage_3_phenotype_lab

  Lab values for Hostage3 cohort.

  Dataset EGAD00001007843

• Hostage_1_phenotype_basic

  Basic phenotypes for Hostage1 cohort.

  Dataset EGAD00001007838

• Hostage_2_phenotype_lab

  Lab values for Hostage2 cohort.

  Dataset EGAD00001007841

• GEN_COVID_phenotype_lab

  Lab values for GEN_COVID cohort.

  Dataset EGAD00001007837

• GEN_COVID_phenotype_basic

  Basic phenotypes for GEN_COVID cohort.

  Dataset EGAD00001007836

• BelCovid_2_phenotype_lab

  Lab values for BelCovid2 cohort.

  Dataset EGAD00001007835

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Multimodal Developmental Neurogenetics of Females

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002043

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Genomics of Autism Spectrum Disorder (GASD)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002509

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Simons Searchlight

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002512

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Center of Excellence (ACE II)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002042

• Genome Wide Association for Asthma and Lung Function

  The SNP Typing for Association with Multiple Phenotypes from Existing Epidemiologic (STAMPEED) asthma project includes subjects with asthma and controls from the Chicago Asthma Genetics Study (CAG), NHLBI multicenter Severe Asthma Research Program (SARP) and NHLBI Collaborative Studies on the Genetics of Asthma CSGA (Wake Forest). All studies included European American and African American children and adults with asthma ranging from mild to severe and adult controls. CAG participants were collected at the University of Chicago. SARP participants were recruited at the NHLBI SARP sites with an emphasis on recruiting severe asthmatics (Moore et al, Am J Respir Crit Care Med, 2010, PMID: 19892860). CSGA cases and controls collected by the Wake Forest investigators were also included. Asthma status was based on both a physician's diagnosis and either bronchodilator reversibility or hyper-responsiveness to methacholine as well as less than 5 pack years of smoking. Genotyping was performed on the Illumina 1Mv1 platform, with individual genotypes called using clustering algorithms as implemented in the BeadStudio software by Illumina. The total number of markers following standard QC was 1,025,129. Imputation was performed using the HapMap phase 2, release 21 SNPs using MACH with the phased HapMap CEU and YRI haplotypes as a reference. Case/control association tests for asthma status were performed using logistic regression in R (http://CRAN.R-project.org/) on genotype dosages, and adjusting for the first principal component from EIGENSTRAT.

  Study phs000355

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Study of Autism Genetics Exploration (SAGE)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001740

• Center for Common Disease Genomics (CCDG)-Neuropsychiatric: A Study of the Genetic Causes of Complex Pediatric Disorders (CAG)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002004

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Genetic Resource Exchange

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001766

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: The Autism Simplex Collection (TASC)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001741

• Center for Sub-Cellular Genomics

  A cell is a highly complex system with distributed molecular physiologies in structured sub-cellular compartments whose interplay with the nuclear genome determine the functional characteristics of the cell. A classic example of distributed genomic processes is found in neurons. Learning and memory require modulation of individual synapses through RNA localization, localized translation, and localized metabolites, such as those from dendritic mitochondria. Dendrites of neurons integrate distributed synaptic signals into both electrical and nuclear transcriptional response. Dysfunction of these distributed genomic functions in neurons can result in a broad spectrum of neuropsychiatric diseases such as bipolar and depressive disorders, autism, among others. The Center for Sub-Cellular Genomics' (CSG) mission is to develop new technologies to enable the dissection of complex genomic interactions within a single cell. New technologies include methods to target DNA and RNA sampling at sub-cellular resolution in live cells; high-throughput isolation and microfluidics chemistry for sub-cellular fractions; sub-cellular resolution mass-spectrometry; and computational tools for analysis of sub-cellular genomics data. The new technologies developed by CSG will enable the broader genomics community to associate sub-cellular processes to cell function and dysfunction. These technologies will be utilized in the center to generate a comprehensive atlas of genomic signatures of sub-cellular compartments in the mammalian neuron system. The technologies and neuron-focused data obtained here will be relevant to neurodegenerative and neuropsychiatric diseases including schizophrenia, depression, autism spectrum disorder, traumatic brain injury, and Alzheimer's.

  Study phs002120

• Stressors and Health Study

  ObjectivesThe objectives of the Stressors and Health Study were to: (1) examine the prevalence of stressors and health outcomes and (2) assess differences in the associations between multi-level stressors and health outcomes, and (3) explore the protective and adaptive factors in the associations between multi-level stressors and health outcomes. Background Stressors have been posited to explain disparities in health. However, no surveys to our knowledge have simultaneously collected multiple stressors at various levels and the coping strategies used to deal with these stressors. Measuring these factors can provide a better understanding of the stressors experienced by specific groups and the impact that these experiences have on their health and health practices. In addition, exploring the various resilience and coping strategies employed to deal with stressors can help design appropriate interventions to reduce health disparities. Participants Participants included 1000 White, 1000 Black or African American, 1000 Latino or Hispanic, 1000 Asian, 500 American Indian or Alaska Native, 500 Native Hawaiian or Pacific Islander, and 500 mixed or multi-race adults (≥18 years) across the United States. Design The Stressors and Health Study is a cross-sectional online survey of adults across the US. A sampling frame (target population) of US residents based on the American Community Survey (ACS) was constructed using a rigorous two-step sampling matching approach to establish national representation.

  Study phs004019

• Inherited chromosomally-integrated human herpesvirus 6A/B (HHV-6A/B) genome sequences in the Japanese population

  The deposited sequences represent inherited chromosomally-integrated human herpesvirus 6 (iciHHV-6) genomes identified from 10 BioBank Japan (BBJ) subjects based on the analysis of the whole-genome sequencing (WGS) data. In brief, we re-aligned unmapped reads from the WGS to HHV-6A genome (Genbank accession number: KJ123690.1) using BWA-MEM algorithm. Ten out of 3,256 subjects were identified with high depth of coverage of HHV-6. We further distinguished subjects with integrated HHV-6A subtypes from those with integrated HHV-6B based on phylogenetic analysis of concatenated sequences of three viral genes (U27/U43/U83, which show high divergence between viral species). We reconstructed the HHV-6 viral genome of 10 subjects. First, reads that mapped to a reference HHV-6A genome (KJ123690.1) were further aligned against the integrated HHV-6A genome derived from a Japanese individual NA18999 (GenBank Accession number: KY316047.1) using BWA-MEM. Based on the alignment, variant calling was performed using freebayes (version: v1.2.0-2-g29c4002) with parameters ploidy = 1 and min-alternate-fraction = 0.8 {Garrison, 2012}. We generated subject-specific iciHHV-6 viral sequences by applying the resulting variants to the KY316047.1 reference genome using the FastaAlternateReferenceMaker function in the Genome Analysis Toolkit (GATK) v3.7. Please note that HHV-6B-specific variants are unlikely to be sensitively reconstructed using this method.

  Study JGAS000240

• A thymic ILC1-like progenitor with differentiation potential towards KIR+NKG2A- NK cells

  KIR+NKG2A- Natural Killer (NK) cells have the unique ability to detect downregulation of single HLA-I allotypes, frequently occurring in malignantly-transformed and virus-infected cells in order to escape T cell recognition. We have recently shown that circulating Innate Lymphoid Cells 1 (cILC1) have the potential to generate such KIR+NKG2A- NK cells but their developmental origin was unknown. Here we demonstrate that the development of cILC1 is thymus-dependent and identify a putative progenitor of cILC1s in the thymus, called thyILC1. Single-cell RNAseq analysis revealed a close relationship of thyILC1s to CD34+ double-negative (DN) thymocytes, but in contrast to DNs, thyILC1s had lost T cell differentiation potential. However, like cILC1s they could be efficiently differentiated into KIR+NKG2A- NK cells. thyILC1s strongly expressed RAG1/2, PTCRA (preTCR, and NOTCH1/3, but lacked expression of TCR chains, suggesting that they failed to pass the -selection checkpoint of thymocyte development. Finally, analyses of patients with FOXN1het deficiency, showing thymic hypoplasia due to lack of mature thymic epithelial cells, exhibited a profound deficiency of cILC1s but not cILC2s and cILC3s, demonstrating thymus dependency of cILC1s. Together, the data suggest that thyILC1s are the source of a novel thymus-dependent NK cell differentiation pathway that promotes generation of KIR+NKG2A- NK cells.

  Study EGAS50000000760

• A thymic ILC1-like progenitor with differentiation potential towards KIR+NKG2A- NK cells - sc

  KIR+NKG2A- Natural Killer (NK) cells have the unique ability to detect downregulation of single HLA-I allotypes, frequently occurring in malignantly-transformed and virus-infected cells in order to escape T cell recognition. We have recently shown that circulating Innate Lymphoid Cells 1 (cILC1) have the potential to generate such KIR+NKG2A- NK cells but their developmental origin was unknown. Here we demonstrate that the development of cILC1 is thymus-dependent and identify a putative progenitor of cILC1s in the thymus, called thyILC1. Single-cell RNAseq analysis revealed a close relationship of thyILC1s to CD34+ double-negative (DN) thymocytes, but in contrast to DNs, thyILC1s had lost T cell differentiation potential. However, like cILC1s they could be efficiently differentiated into KIR+NKG2A- NK cells. thyILC1s strongly expressed RAG1/2, PTCRA (preTCR, and NOTCH1/3, but lacked expression of TCR chains, suggesting that they failed to pass the -selection checkpoint of thymocyte development. Finally, analyses of patients with FOXN1het deficiency, showing thymic hypoplasia due to lack of mature thymic epithelial cells, exhibited a profound deficiency of cILC1s but not cILC2s and cILC3s, demonstrating thymus dependency of cILC1s. Together, the data suggest that thyILC1s are the source of a novel thymus-dependent NK cell differentiation pathway that promotes generation of KIR+NKG2A- NK cells.

  Study EGAS50000000790

• Genomic analysis reveals novel secondary drivers and progression pathways in skin basal cell carcinoma

  Basal cell carcinoma of the skin (BCC) is the most common malignant neoplasm in humans. BCC is primarily driven by the aberrant activation of the Sonic Hedgehog (Hh) pathway. However, its extensive phenotypical variation remains to be explained. The genetic profiling of 293 BCCs revealed the highest mutation rate observed in cancer (65 Mutations/Mb), with strong prevalence of UV-light signature mutations. 85% of BCCs harbored mutations in Hh pathway genes: mutually exclusive PTCH1 (73%) and SMO (20%) (P=6.6x10-8), SUFU (8%), and in TP53 (61%). 85% of BCCs also harbored secondary driver mutations in other genes implicated in BCC tumorigenesis. Recurrent secondary driver mutations were observed in MYCN (30%), PPP6C (15%), STK19 (10%), LATS1 (8%), ERBB2 (4%), PIK3CA (2%), RAC1 (1%) and N/K/H-RAS (2%). Loss of function (LoF) and deleterious missense mutations were observed in PTPN14 (23%), RB1 (8%) and FBXW7 (5%). In line with the mutational profiles detected by RNAseq, we observed activation of the Hh pathway as well as upregulation of target genes of the Hippo-YAP pathway and activation of MYCN target genes. The functional analysis of the novel tumorigenic driver mutations in MYCN, PTPN14 and LATS1 demonstrates their relevance in BCC tumorigenesis and provides an expanded molecular understanding of BCC.

  Study EGAS00001001540

• scRNA-seq of HGSC tumor and ascites

  Immune regulatory metabolites are key features of the tumor microenvironment (TME), yet with a few notable exceptions, their identities remain largely unknown. We uncovered the immune regulatory metabolic states and metabolomes of sorted tumor and stromal, CD4+, and CD8+ cells from the tumor and ascites of patients with high-grade serous ovarian cancer (HGSC) using high-dimensional flow cytometry and metabolomics supplemented with single cell RNA sequencing. Flow cytometry revealed that tumor cells show a consistently greater uptake of glucose than T cells, but similar mitochondrial activity. Cells within the ascites and tumor had pervasive metabolite differences, with a striking enrichment in 1-methylnicotinamide (MNA) in T cells infiltrating the tumor compared to ascites. Despite the elevated levels of MNA in T cells, the expression of nicotinamide N-methyltransferase, the gene encoding the enzyme that catalyses the transfer of a methyl group from S-adenosylmethionine to nicotinamide, was restricted to fibroblasts and tumor cells. Treatment of T cells with MNA resulted in an increase in T cell-mediated secretion of the tumor promoting cytokine tumor necrosis factor alpha. Thus, the TME-derived metabolite MNA contributes to an alternative and non-cell autonomous mechanism of immune modulation of T cells in HGSC. Collectively, uncovering the tumor-T cell metabolome may reveal metabolic vulnerabilities that can be exploited using T cell-based immunotherapies to treat human cancer.

  Study EGAS00001004829

• Spatial concordance of DNA methylation classification in diffuse glioma

  Background: Intratumoral heterogeneity is a hallmark of diffuse gliomas. DNA methylation profiling is an emerging approach in the clinical classification of brain tumors. The goal of this study is to investigate the effects of intratumoral heterogeneity on classification confidence. Methods: We used neuronavigation to acquire 133 image-guided and spatially-separated stereotactic biopsy samples from 16 adult patients with a diffuse glioma (7 IDH-wildtype and 2 IDH-mutant glioblastoma, 6 diffuse astrocytoma, IDH-mutant and 1 oligodendroglioma, IDH-mutant and 1p19q codeleted), which we characterized using DNA methylation arrays. Samples were obtained from regions with and without abnormalities on contrast enhanced T1 weighted and fluid-attenuated inversion recovery MRI. Methylation profiles were analyzed to devise a three-dimensional reconstruction of (epi)genetic heterogeneity. Tumor purity was assessed from clonal methylation sites. Results: Molecular aberrations indicated that tumor was found outside imaging abnormalities, underlining the infiltrative nature of this tumor and the limitations of current routine imaging modalities. We demonstrate that tumor purity is highly variable between samples and explains a substantial part of apparent epigenetic spatial heterogeneity. We observed that DNA methylation subtypes are often, but not always, conserved in space taking tumor purity and prediction accuracy into account. Conclusion: Our results underscore the infiltrative nature of diffuse gliomas and suggest that DNA methylation subtypes are relatively concordant in this tumor type, although some heterogeneity exists.

  Study EGAS00001005434

• National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III)

  The National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) is a nationally representative cross-sectional survey of the U.S. general population, which was sponsored by the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and conducted in 2012-2013. The NESARC-III's target population was the U.S. noninstitutionalized civilian population, 18 years and older, including residents of selected group quarters (e.g., group homes, workers' dormitories). Multistage probability sampling was used to randomly select respondents. Primary sampling units (PSUs) were individual counties or groups of contiguous counties, secondary sampling units (SSU) comprised groups of Census-defined blocks, and tertiary sampling units were households within SSUs. Finally, eligible adults within sampled households were randomly selected. Hispanics, Blacks, and Asians were oversampled and resulted in a total of 36,309 respondents. All respondents provided informed consent for survey participation. Data were adjusted for oversampling and screener - and person-level nonresponse, then weighted through post-stratification to represent the US civilian population based on the 2012 American Community Survey. These weighting adjustments were found to compensate adequately for nonresponse. Interviewer field methods involved initial structured home study, in-person training, ongoing supervision, and random respondent callbacks to verify data. The NESARC-III collected information on alcohol and drug consumption, alcohol use disorder, other substance use disorders (e.g., nicotine, cannabis and opioid), and associated physical and psychiatric adverse consequences. In addition to a full array of sociodemographic characteristics such as race/ethnicity, gender, age, risk and environmental factors including adverse childhood experiences (e.g., sexual, physical abuse and neglect) and family history for alcohol, drug use disorders and other psychiatric disorders (e.g., mood, anxiety, personality disorders and PTSD) were included (phenotypic variables=4,320). As part of the NESARC-III, 22,848 informative samples were genotyped on Affymetrix Axiom Exome Array consisting of 319,283 SNPs and 103,404 custom-selected SNPs Array (refer to the SNP annotation file). The latter array was selected based on the addiction associated genes, the results of 5 GWAS of alcohol and other psychiatric disorders, and animal models with addiction phenotypes. After filtering out poor quality SNPs using the standard Affymetrix pipeline there are 295,218 SNPs in the NESARC-III genetic data. The 22,848 subjects in this study were all deeply and consistently phenotyped via structured diagnostic interview. Controls group can be selected for specific disorders from a pool of all samples. Here are numbers of cases for major DSM-5 mental disorders in NESARC-III genetic data: Alcohol use disorder (7,075); Nicotine use disorder (6,641); Drug use disorder (2,570); Major depressive disorder (5,214); Persistent depression(1,429); Bipolar I (543); Anxiety disorders (4,226); PTSD (1,674); Personality disorders (4,014); Eating Disorders (457).

  Study phs001590

• Multi-Modal Single-Cell, Spatial, and Genomic Analyses of Human Non-Small Cell Lung Cancer Brain Metastases

  We performed single nuclei RNA-sequencing (snRNA-seq) with matched T cell receptor sequencing (TCR-seq), and pool matched low pass whole genome sequencing (WGS) of 12 treatment-naive non-small cell lung cancer (NSCLC) primary tumors (PTs) and 31 treatment-naive NSCLC brain metastases (BMs). In total, we recovered 277,206 cell transcriptomes in 43 samples. Single-nuclei suspension from frozen NSCLC metastases were generated using methods published in Slyper et al. (Nature Medicine, 2020, PMID:32405060) with modifications. The tissue was first cut in 20 µm sections using a cryostat and stored on dry ice until the next step. Then the tissue was put on wet ice and washed once with 5 ml PBS to remove OCT. After this step nuclei were extracted by vigorous pipetting in salt-tris buffer with Tween-20 (TST) followed by a high-volume wash in salt-tris buffer (ST). Nuclei were counted and 10,000-14,000 and were loaded using a Chromium controller (10X genomics) and Chromium Single Cell 5' Reagents (V1.1 and V2). Complementary DNA libraries were generated according to manufacturer's instructions, with the modification of one additional cycle of amplification. Matched single nuclei T cell receptor (snTCR) sequencing libraries were prepared from amplified cDNA libraries using either Chromium Single Cell V(D)J Enrichment Kit for human T cells Reagent Kit, v1.1, or single cell human TCR amplification kit. Final snTCR sequencing libraries were prepared using Single Index Kit T Set A for V1.1 libraries or Library construction kit and Dual Index Kit TT set A for V2 libraries. Sequencing libraries were quantified using Tapestation D5000 reagents and a 2200 TapeStation and pooled for sequencing. Pool matched low pass whole-genome sequencing (lp-WGS) was performed in addition to snRNA-seq to improve the identification of the malignant and non-malignant cell compartments. Nuclei from snRNA-seq sample preparations were collected by centrifugation (500g, 5 min), snap frozen after removing excess ST buffer, and stored at -200C until further processing. If insufficient nuclei (0C for 9 minutes. Adapters were not diluted, and the optional PCR (5 cycles) and cleanup were performed. After library cleanup with AMPure beads (Beckman Coulter, Brea, CA), libraries were quantified with Tapestation D5000 HS tapes (Agilent) and stored at -200C until sequencing.Using multiplexed immunofluorescence in an independent cohort of treatment-naïve pairs of primary tumors and brain metastases from the same patients with NSCLC, we validated genomic and tumor-microenvironmental findings and identified a cancer cell population characterized by neural features that strongly enriched in brain metastases. This comprehensive analysis provides insights into human NSCLC brain metastasis biology and serves as an important resource for additional discovery.

  Study phs003865

• Predicting Chemotherapy-Induced Mucositis with Genetic and Clinical Factors

  We hypothesized that genetic variability in the enzymes/proteins involved in drug metabolism, inflammation, and immune function is a major underlying contributor to mucositis incidence and progression and that, based on this variability we can identify variants that influence risk, and develop a mucositis progression prediction model that improves on existing models by incorporating genetic variability along with clinical factors. Using genome wide association study (GWAS) combined with a pathway candidate gene approach and a modified case-control study method, we investigated the hypothesis in a sample of 1092 patients who received a myeloablative dose of melphalan (MEL) followed by autologous hematopoietic stem cell (ASCT) transplantation as treatment for multiple myeloma and for whom banked blood stem cell samples and clinical data were available.

  Study phs000545

• SNP array analysis of spondylocostal dysostosis patient iPSCs and gene edited isogenic controls

  This study, "SNP Array Analysis of Gene Edited SDV Patient iPSCs" is part of a larger study where we applied our recently established experimental in vitro model system of the human segmentation clock, for the analysis of human segmentation defects of the vertebrae (SDV) including spondylocostal dysostosis (SCD). To this end we generated patient-derived iPSC lines, identified putative disease-causing mutations and corrected these mutations using CRISPR/Cas9-based genome editing technology. We identified in the patient-sample originally obtained from the NIGMS Human Genetic Cell Repository at the Coriell Institute for Medical Research (#: GM13539) heterozygous compound mutations in MESP2. These mutations were corrected accordingly and the resulting clones were genotyped by SNP array analysis.

  Study phs001975

• Episodic Ataxia Syndrome: Longitudinal Study

  Individuals with episodic ataxia experience recurrent attacks of dizziness and incoordination; between attacks patients are typically normal. The majority of cases are likely caused by an inherited genetic mutation. However, in some patients we are unable to identify the mutation. So far, 2 genes have been identified which cause different types of episodic ataxia. Ultimately, when the actual mutation is identified the protein product of the gene can be studied and specific medications can be designed. During this study, we will clinically evaluate patients with EA and follow them over time to help us better characterize the disease. We will also obtain blood samples to test for the known genetic mutations. In the future, we plan to coordinate trials of medications for the treatment of these disorders.

  Study phs000521

• Pharmacogenomics of Metformin Dose Response in T2DM Patients

  Type 2 Diabetes Mellitus (T2DM) is a chronic and sometimes debilitating disease that affects millions of adults in the USA. Metformin is commonly prescribed for T2DM; yet some T2DM patients do not tolerate it or respond well. This pharmacogenomics study will examine response, as both change in T2DM patients' weight and hemoglobin A1c (HbA1c) levels, to different doses of metformin, by extracting this data from the electronic health record (EHR), for T2DM subjects taking metformin found by prescription orders in the EHR, and identified as cases with the EHR phenotype algorithm published by Kho et. al. in 2012 (PMID: 22101970 as part of the eMERGE (electronic Medical Records and Genomics; dbGaP phs000237, phs000297, phs000360, phs000368, phs000888, and phs000948) project.

  Study phs000984

• Genetic Basis of Pulmonary Non-tuberculous Mycobacterial Infections

  This project aims at characterizing the human host susceptibility to pulmonary non-tuberculous mycobacterial (PNTM) infections. PNTM infections occur in patients with chronic lung disease, but also in a distinct group of elderly women without lung defects but who share a common body morphology: tall and lean with scoliosis, pectus excavatum, and mitral valve prolapse. We performed whole exome and genome sequencing in extended families of patients with active PNTM. This unique collection of familial cohorts in PNTM represents an important opportunity for a high yield search for genes that regulate mucosal immunity. We also sequenced the genome of mycobacterial isolates from PNTM patients to integrate host PNTM susceptibility with mycobacterial genotypes and gain insights into the key factors involved in this devastating disease.

  Study phs000719

• The mutational characterization of adenoid cystic carcinoma

  Adenoid cystic carcinoma (ACC) typically emanate from the major and minor salivary glands of the head and neck. ACCs have high rates of perineural invasion, locoregional recurrence, and distant metastasis. Here we report sequencing of 60 tumor/normal pairs and find substantial mutational diversity. On pathway analysis, a significant percentage of mutations involved chromatin remodeling, DNA damage, protein kinase A signaling, and FGF/IGF/PI3K signaling. Whole genome sequencing and FISH confirmed the MYB-NFIB translocation as the main structural variant in ACC. Evaluation of potential driver mutations KDM6A and PIK3CA reveal that specific, observed alterations impart functional consequences. Collectively, our data delineate the ACC mutational landscape and establish a molecular foundation for investigating new therapies for this disease.

  Study phs000612

• Identification of Genomic Markers of Cervical Dystonia and Subtypes

  As the third most common movement disorder, dystonias collectively affect more than 2 million people worldwide. Despite their high prevalence, their biological roots are largely unknown. Genetic influences are suggested in familial studies, however, no specific genetic variants are responsible for a significant proportion of identified cases. Previous genome-wide association studies of the dystonias were limited by smaller sample size and lack of coverage of rare variants. In this study, we use a high-throughput genomic approach to effectively investigate relationships between over genome-wide genetic variations and dystonias. We conduct targeted analyses of candidate genes, as well as agnostic searches for any genomic with the dystonias and subtypes in a large sample of dystonia patients available.

  Study phs001803

• Natural Genetic Variation in the Human Genome

  In this study, we used existing whole genome sequencing data from the TOPMed Amish and Jackson Heart Study, as well as the GTEx study, to identify mobile element insertions in the genomes of these individuals.  A total of 1112 TOPMed Amish, 3331 TOPMed Jackson Heart Study, and 698 GTEx individuals were examined.  We used the Mobile Element Locator Tool (MELT) developed previously by our lab, along with a Cloud-based version of MELT (CloudMELT), to discover non-reference mobile element insertions (MEIs) in these genomes.  We discovered Alu, L1, SVA, and HERV-K MEIs and produced genotypes in individual genomes.  Build hg19 bams were used for the TOPMed samples, and build GRCh37 bams were used for the GTEx samples in this study.

  Study phs002463

• Lifestyle, Infertility, Fertility, and Evaluation (LIFE) Study

  The purpose of this study is to provide a reference profile of small extracellular RNAs in body fluids. These samples were originally obtained in a study that had a different purpose. The purpose of the original study was to establish a data and biological specimen repository to advance future research into male reproductive health and urologic health. Semen from semen analyses, as part of standard of care at the Center for Reproductive Health, was collected and stored in a tissue bank for future research purposes. These samples and associated clinical data (including age, race, education level, medical history and diet, environmental exposures and laboratory values, fertility diagnosis and infertility treatments) will help researchers understand any urological disorders and male reproductive health issues.

  Study phs001692

• Drug Resistant Hypertension in African Americans' Exome

  Resistant hypertension is defined as blood pressure that remains above goal in spite of the concurrent use of 3 antihypertensive agents of different classes or the concurrent use of 4 or more antihypertensive agents regardless of control. Its diagnosis is important for the identification of patients who are at high risk of having reversible causes of hypertension and/or patients who, because of persistently high blood pressure levels, may benefit from special diagnostic and therapeutic considerations. Resistant hypertension represents an extreme phenotype, thus, it has been predicted that genetic factors could play a larger role than for the general hypertensive population. Genetic assessments of patients with resistant hypertension have been limited. The current study assayed the exome of 91 African American patients with treatment resistant hypertension.

  Study phs000442

• NPC Genome Project

  Niemann-Pick disease, type C1 (NPC1) is neurodegenerative disorder due to pathological variants of NPC1. NPC1 is predominately a pediatric/adolescent disorder, although adult onset cases have been described. The NPC1 protein functions to move unesterified cholesterol from the endolysosomal lumen to make it bioavailable for cellular function. Impaired NPC1 function results in endolysosomal accumulation of unesterified cholesterol and other lipids. The NPC1 phenotype is extremely heterogeneous, both with respect to age of onset and sign/symptom complex. Comparison of individuals homozygous for the common p.I1061T variant and affected siblings suggests that other genes can significantly modify the clinical phenotype. The goal of this project is to obtain genome sequencing on ~200 individuals with NPC1 in order to facilitate identifying potential genetic modifiers.

  Study phs003214

• DAC for Early detection of ovarian cancer using cell-free DNA fragmentomes and protein biomarkers

  Ovarian cancer is a leading cause of death from gynecological malignancies worldwide. No effective screening methods exist resulting in tumor detection at advanced stages where treatment is less effective. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome and protein biomarker (CA-125 and HE4) analyses to evaluate 591 women, mostly post-menopausal, from the European Union or the United States with ovarian cancer, benign adnexal masses, or without ovarian lesions. Using a machine learning model that incorporated multi-analyte fragmentome data and protein measurements, we evaluated the detection of ovarian cancer in two clinical settings, detection of ovarian cancers among a healthy population, and classification of adnexal masses as benign or malignant. The combined approach detected ovarian cancer with specificity >99% and sensitivity of 72%, 69%, 87%, and 100% for stages I–IV, respectively (AUC=0.96, 95% CI: 0.94-0.99), including 90% of high grade serous ovarian cancers. At the same specificity, CA-125 alone detected 34%, 62%, 63%, and 100% of ovarian cancers for stages I–IV (p=0.001, two-sided test of equal proportions). Additionally, our approach differentiated benign masses from ovarian cancers with high accuracy (AUC of 0.88, 95% CI=0.83-0.92). These results were validated in an independent population. These findings show that integrated cfDNA fragmentome and protein analyses detect ovarian cancers with high performance, enabling a new accessible approach for noninvasive ovarian cancer screening and diagnostic evaluation.

  Dac EGAC50000000332

• C-MACH reduced-representation bisulfite sequencing (RRBS)

  Umbilical cord blood (CB) has been commonly used as an epigenetic surrogate of fetuses. Here, we propose umbilical cord tissue (UC) as an alternative surrogate for epigenetic studies on fetuses. To explore the feasibility to examine UC epigenome by deep sequencing, we determined CpG methylation profiles of human postnatal UC by reduced representation bisulfite sequencing. We compared DNA methylomes between UC and CB. To investigate the effect of folate during pregnancy on fetal DNA methylation, we compared fetal UC DNA methylation between low and high levels of maternal plasma folate. Our study suggests that UC is useful as an alternative surrogate for studying environmental effects on DNA methylation in human fetuses, compensating CB by providing additional information about epigenetic regulation of genes.

  Study JGAS000171

• Germline variants in UHRF1 are associated with multi-locus imprinting disturbance in humans and mice

  Genomic imprinting provides is an epigenetic process crucial for normal development and is disrupted in congenital imprinting disorders(CIDs). There is great interest in the clinical consequences and aetiology of multilocus imprinting disturbance(MLID) which occurs in some individuals with CID, though the cause of MLID is unknown in most cases. We investigated a kindred with a CID and MLID and identified a rare genetic variant in the UHRF1 gene which has a critical role in the establishment and maintenance of DNA methylation. We generated a mouse model and found that the equivalent Uhrf1 variant was associated with prenatal lethality and disruption of normal imprinting mechanisms. These findings support UHRF1 as a novel candidate gene for CIDs with MLID.

  Study EGAS50000001179

• Ultrasensitive Detection and Monitoring of Circulating Tumor DNA using Structural Variants in Early-Stage Breast Cancer

  Circulating tumor DNA (ctDNA) detection has an emerging role in the management of breast cancer, offering a non-invasive means to monitor disease status and detect recurrence. This study demonstrates that longitudinal monitoring of tumor-specific structural variants - frequent alterations observed across many tumor types including all subtypes of breast cancer derived from Whole Genome Sequencing data - allows for ctDNA detection in nearly all participants in this cohort with untreated early breast cancer prior to starting neoadjuvant therapy. On-treatment ctDNA monitoring enabled the early identification of patients at high risk of recurrence and ctDNA was detected prior to relapse in participants across all receptor subtypes. These findings demonstrate the clinical validity of this assay approach for ultrasensitive ctDNA monitoring.

  Study EGAS50000000799

• Single cell transcriptomics to characterize the tumor microenvironment of prostate cancer fusion biopsies

  The primary objective of this study was to characterize the tumor microenvironment in fusion-guided transperineal biopsy samples from patients undergoing PC diagnosis. For each patient, one biopsy was taken from a suspected tumor region and another from a non-suspicious area, which were later classified as high- or low-tumorigenicity based on anatomopathological analysis. Using scRNA-seq data, we performed cancer-oriented cell annotation, differential expression analysis, and functional pathway enrichment studies across key cellular subpopulations. Additionally, differential abundance analysis was conducted to identify cell groups representative of different tumorigenicity levels. Finally, classification models were developed using gene expression data to differentiate high- vs. low-tumorigenicity samples, with the long-term goal of establishing a diagnostic classifier for PC stratification.

  Study EGAS50000000888

• Association studies using the Metabochip array - Samples analysed by the WTCCC (1958 British Birth Cohort (58BC), Hypertension cohort (HT), Type 2 Diabetes Cohort (T2D) and Coronary Artery Disease (CAD) cohort)

  Genomewide association studies (GWAS) have proven a powerful hypothesis-free method to identify common disease-associated variants. Even quite large GWAS, however, have only at best identified moderate proportions of the genetic variants contributing to disease heritability. To provide cost-effective genotyping of common and rare variants to map the remaining heritability and to fine-map established loci, the Metabochip Consortium has developed a 200,000 SNP chip that has been produced in very large numbers for a fraction of the cost of GWAS chips. This chip provides a powerful tool for genetic studies of metabolic, cardiovascular and anthropometric traits (Voight et al., in press PLoS Genetics).

  Study EGAS00000000115

• Genome-wide NanoRCS sequencing of cfDNA and ctDNA from liquid biopsies of healthy individuals and cancer patients

  Levels of circulating tumor DNA (ctDNA) in liquid biopsies may serve as a sensitive biomarker for real-time, minimally-invasive tumor diagnostics and monitoring. However, detecting ctDNA is challenging, as much fewer than 5% of the cell-free DNA in the blood typically originates from the tumor. To detect lowly abundant molecules, extremely sensitive sequencing methods are required. We developed a new technique, NanoRCS, which is based on Oxford Nanopore sequencing of concatenated copies of a single DNA molecule for genome-wide sequencing, and applied this to plasma of healthy individuals, Esophageal cancer patients and Granulosa cell tumor patients and ascites of Ovarian cancer patients. We also sequenced these samples on Illumina Novaseq, to compare the two techniques.

  Study EGAS50000000154

• Whole-exome sequencing identifies new pathogenic germline variants in patients with colorectal polyposis

  Adenomatous polyposis confers an increased risk of colorectal cancer development. Here, we investigated probably underlying predisposition variants in patients with suspected colorectal polyposis without variants in APC and MUTYH genes by whole exome sequencing (WES). Twenty-seven patients were included and subjected to germline WES. After filtering out variants for sequencing quality, variant allele fraction frequency, and population frequency, variants were manually prioritized by the ACMG criteria. Among the variants identified, 17 were classified as pathogenic or likely pathogenic (in 12 patients). This study gives information of probably associated polyposis variants in Brazilian patients without germline pathogenic variants in APC and MUTYH genes, supporting the utilization of next-generation sequencing for screening in these patients beyond these genes.

  Study EGAS50000000591

• RNA sequencing data from patient derived colorectal cancer organoids

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The pipeline was utilized to analyze RNA-seq data from ten patient-derived colorectal cancer (CRC) organoids, representing seven microsatellite stable (MSS) and three microsatellite instable (MSI) tumors. The goal was to explore the ncTSA landscape in CRC, particularly in MSS cases, which typically exhibit low tumor mutational burden and limited response to current immunotherapies. The study identified comparable ncTSA burdens across MSI and MSS tumors, suggesting new avenues for immunotherapy targeting non-canonical antigens in CRC. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000685

• Clinical validity of post-surgery circulating tumor DNA (ctDNA) in stage III colon cancer patients treated with adjuvant chemotherapy: the PROVENC3 study

  The PROVENC3 study aimed to determine the clinical validity of post-surgery ctDNA testing in patients with stage III colon cancer treated with adjuvant chemotherapy (ACT). Blood was collected pre-surgery, post-surgery and post-adjuvant chemotherapy. Tumor-informed plasma ctDNA detection was performed through integrated whole genome sequencing (WGS) analyses of formalin-fixed paraffin-embedded tumor tissue DNA (80x), white blood cell germline DNA (40x) and plasma cell-free DNA (30x). These raw WGS data for 209 patients are shared in .cram format in this EGA submission. For 196/209 of these patients there is overlapping FFPE tumor RNA sequencing data available, shared in .fastq format in this EGA submission.

  Study EGAS50000000804

• Cell motility and migration as determinants of stem cell efficacy

  Limited stem cell migration capacities and undirected homing hamper their therapeutic efficacy. We report here the novel technology to isolate stem cell subpopulations with high migration potential. Hereby, we identified podoplanin-dependent stem cell mobility as important mechanism for their in vivo homing capacities and therapeutic efficacy as validated in preclinical models of Alzheimer´s disease and mouse glioma. In vivo applications of highly migrating stem cells resulted in remarkable improvement of targeted homing and engraftment rates. Moreover, animals receiving highly migrating stem cells showed higher recovery rates compared to unselected stem cells. This novel technology provides useful tool to improve therapeutic efficacy of stem cells and give insights into stem cell subpopulations heterogeneity with the potential of general applicability for cellular therapies.

  Study EGAS00001002478

• Targeting PTPRK-RSPO3 colon tumours promotesdifferentiation and loss of stem-cell function

  Colorectal cancer remains a major unmet medical need, promptinglarge-scale genomics efforts in the field to identify moleculardrivers for which targeted therapies might be developed. Wepreviously reported the identification of recurrent translocationsin R-spondin proteins present in a subset of colorectal tumours.Here we show that targeting RSPO3 in PTPRK-RSPO3-fusion positivehuman tumour xenografts inhibits tumour growth andpromotes differentiation. Notably, genes expressed in the stem-cellcompartment of the intestine were among those most sensitive toanti-RSPO3 treatment. This observation, combined with functionalassays, suggests that a stem-cell compartment drives PTPRK-RSPO3colorectal tumour growth and indicates that the therapeutictargeting of stem-cell properties within tumours may be a clinicallyrelevant approach for the treatment of colorectal tumors.

  Study EGAS00001001462

• Sampling of multi-centric lower grade glioma influences management and provides insight into gliomagenesis

  Rare multicentric lower-grade gliomas (LGG) represent a unique opportunity to study the heterogeneity between distinct tumor foci in a single patient, and to infer their origins and parallel patterns of evolution. In this study, we integrate clinical features, histology and immunohistochemistry for 4 patients with multicentric LGG, arising both synchronously and metachronously. For 3 patients we analyze the phylogeny of the lesions using exome sequencing, including one case with a total of 8 samples from the two lesions. We show that each tumor in multicentric LGG cases may arise independently or may diverge very early in their development, presenting as genetically and histologically distinct tumors suggesting that comprehensive sampling of these lesions can significantly alter diagnosis and management.

  Study EGAS00001002495

• Integrative_Oncogenomics_of_multiple_myeloma

  We used targeted capture and massively parallel sequencing of exomes of CD138 purified plasma cells and matched somatic DNA from 17 patients with Multiple Myeloma. For each patient, an early tumor sample (at diagnosis) and a late one (at relapse) were available. For few of them, an additional late sample (2nd progression) was present. In total, the study has 52 samples. 1044 variants were validated by 454 sequencing. The present study will validate an additional 4630 variants by targeted pull-down and sequencing. All 52 samples will be indexed and then will be pre-pooled in groups of 5 or 6. The sequence capture will use 10 reactions. All samples will then be pooled and go thorugh one lane of HiSeq.

  Study EGAS00001000244

• Pilot_experiment_on_functional_genomics_in_osteoarthritis_RNA

  The aim of this work is to apply an integrated systems approach to understand the biological underpinnings of large joint (hip and knee) osteoarthritis which culminates in the need for total joint replacement (TJR). In this pilot we will assess the feasibility of the approach in the relevant tissue. We will obtain diseased and non-diseased tissue (cartilage and endochondral bone) following TJR, coupled with a blood sample, from 12 patients. We will characterise the 12 pairs of diseased and non-diseased tissue samples in terms of transcription (RNASeq) The pilot will help assess the feasibility of isolating sufficient levels of starting material for the different approaches, and will instigate the development of analytical approaches to synthesising the resulting data.

  Study EGAS00001001203

• WGS_of_healhy_mesothelial_cells_and_primary_mesothelima_cell_lines

  Mesothelioma is a rare and aggressive cancer associated with previous exposure to asbestos. Currently there are no effective treatments for mesothelioma and majority of patients will die within a year after diagnosis. Although a large number of preclinical and clinical trials assessed the efficacy of various therapuetic modes, none of the tested molecules entered the clinic. Thus, to better understand what drives mesothelioma carcinogenesis and to identify novel targets for therapy, here we aim at performing WGS of heathy mesothelial cells and a panel of mesothelioma cells lines. Primary mesothelial cell lines were established in prof. Marciniak lab from human pleural specimens, while primary mesothelioma cell lines were obtained from MesobanK. Both models constitute low passage cell lines and therefore should closely represent genetics of the original tissue.

  Study EGAS00001005559

• GM adipose tissue study

  The Greek Metabolic (GM) adipose study was carried out in 106 individuals living in Greece and consists of genotyping data (chip), RNA-Seq and ATAC-Seq (for a subset of individuals) data from paired biopsies of Subcutaneous and Visceral adipose tissue. eQTL mapping was performed to study gene regulation and findings compared to those from adipose tissue GTEX data. The focus of this project was to study an underexplored population living in different environmental conditions in order to reveal novel regulatory effects for genes that shape complex traits and disease risk. Our results highlight the utility of modest-sized studies in adding to our understanding of the molecular basis of complex traits and to the identification of mechanisms that drive disease in specific tissues.

  Study EGAS00001007126

• A PROSTATE TUMORGRAFT PANEL TO ACCELERATE PRECISION MEDICINE

  The management of advanced prostate cancer (PCa) has strongly evolved in the last decade with the introduction of the next generation of androgen receptor pathway inhibitors which have considerably improved patient outcomes. Most recently, the investigation of genomic landscape has provided targetable molecular alterations such as homologous gene DNA repair defects correlated with response to PARP inhibitors. Despite these significant advances, while localized PCa is generally associated with favorable outcome, metastatic PCa is currently considered incurable. For further investigations in precision treatment, the development of preclinical models representing the complex prostate tumor heterogeneity are mandatory. Accordingly, we aimed to establish a resource of patient-derived xenograft (PDX) models that exemplify each phase of this multistage disease for accurate and rapid evaluation of candidate therapies.

  Study EGAS00001007033

• NOTCH1 fusion genes in pediatric T-cell lymphoblastic lymphoma hallmark a common high-risk subgroup with blood TARC levels as possible biomarker

  T-cell lymphoblastic lymphoma (T-LBL) is a common pediatric malignancy accounting for approximately 20% of the non-Hodgkin lymphomas during childhood. Survival rates of T-LBL are ~80%, but outcome after relapse is dismal, with salvage rates reaching only ~15. Considering the extremely poor prognosis after relapse and absence of clinically relevant high-risk genetics, there is an urgent need for the identification of molecular risk factors and new prognostic biomarkers in T-LBL, as well as identification of new therapeutic strategies. In this study we present a novel entity of high-risk pediatric T-LBL patients characterized by previously unknown NOTCH1 gene fusions and highly elevated blood TARC levels

  Study EGAS00001007703

• Integrative genome profiling in AML

  AML emerges as a consequence of accumulating independent genetic aberrations that direct regulation and/or dysfunction of genes resulting in aberrant activation of signalling pathways, resistance to apoptosis and uncontrolled proliferation. Given the significant heterogeneity of AML genomes, AML patients demonstrate a highly variable response rate and poor median survival in response to current chemotherapy regimens. For the past 4 years we have conducted gene expression profiling on purified bone marrow populations equating to normal haematopoietic stem and progenitor cells from healthy subjects and patients with de novo AML in order to identify AML signatures of aberrantly expressed genes in cancer versus normal. We are now applying a series of bioinformatic methodologies combined with clinical and conventional diagnostic data to establish novel genomics strategies for improved prognostication of AML. Additionally, we use our AML signatures to unravel oncogenic signalling pathway activities in AML patients and test inhibitory drugs for these pathways inn preclinical therapeutic programmes. We consider that superimposing GEP and clinical data for our AML patient cohort with additional data on their mutational status will significantly improve the prognostic power of the study as well as unravel yet unknown mutations associated with aberrant signalling activities of oncogenic pathways.

  Dataset EGAD00001001873

• May 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  May 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001008100

• NHLBI TOPMed: Pulmonary Fibrosis Whole Genome Sequencing

  This is a set of cases diagnosed with idiopathic pulmonary fibrosis, a fatal interstitial lung disease. These cases were included in the TOPMed phase three studies. The planned study will compare these cases to within-TOPMed controls for genome-wide association studies.

  Study phs001607

• Bulk RNA Sequencing of 86 Human Donor Lungs

  The goal of this study was to characterize the effect of age on gene expression in normal human lung. We collected distal lung samples from 86 human donors distributed in age between 16 and 76 years and extracted RNA for Illumina-based sequencing.

  Study phs002484

• Whole-Genome and Exome Sequencing in clear-cell Renal Cell Carcinoma (ccRCC)

  Study to evaluate the molecular genetics of ccRCC through integrative analyses of tumors and tumorgrafts using multiple platforms in clinically annotated samples. Genome and exome data for patients giving consent to have the information available on a public, secure, database is being submitted.

  Study phs000491

• Phase 2 Study of Pembrolizumab in Combination with Gemcitabine and Cisplatin as Neoadjuvant Therapy

  The purpose of the clinical trial (NCT02690558) is to evaluate whether adding pembrolizumab (Keytruda) to the combination of gemcitabine and cisplatin will improve shrinkage of the tumor before having a cystectomy, for people with muscle-invasive bladder cancer (MIBC).

  Study phs003452

• Transplant Outcomes in Aplastic Anemia (TOAA): GWAS and Whole Exome Sequence Data

  The TOAA study is a research collaboration between the National Cancer Institute and the Center for International Blood and Marrow Transplant Research. The study aims to identify molecular predictors of outcomes after hematopoietic cell transplant in patients with severe aplastic anemia.

  Study phs001710

• COVID_Methyl_scRNA

  DAC for the study of whole-genome enzymatic DNA methylation sequencing and single-cell RNA sequencing of nasal cells from COVID-19 patients. Nasal swabs were collected from COVID-19 patients during the acute phase of infection as well as 3 and 12-months post-infection. Cells isolated from nasal swabs were subjected to whole-genome enzymatic DNA methylation sequencing (n=33) and scRNA-seq (n=24). For n=12 former COVID-19 pateints, follow-up samples were collected at 3 and 12 months post-infection and subjected to scRNA-seq.

  Dac EGAC50000000197