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• A New CA19-9 Cut-Off Value Identifies Lewis Antigen Status and Refines Prognostic Stratification in PDAC

  This study investigates the clinical utility of serum CA19-9 levels in pancreatic ductal adenocarcinoma (PDAC), with a focus on identifying patients with Lewis antigen–negative status due to germline FUT3 variants. Using data from multicenter prospective cohorts in Taiwan, we analyzed CA19-9 classification, FUT2/FUT3 genotypes, and clinicopathological annotations. The goal of this study is to refine prognostic stratification and reduce false-negative interpretation of CA19-9 in PDAC patients. All participants provided informed consent, and the study was approved by the relevant institutional review boards.

  Study EGAS50000001575

• Transcriptomic Profiling of Oropharyngeal Squamous Cell Carcinoma

  The study is a retrospective transcriptomic profiling of oropharyngeal squamous cell carcinoma. The pathologic database was queried for squamous cell carcinoma tumors originating from the anatomic oropharynx (tonsil or tongue base) with available samples from surgical archives. This retrospective RNA sequencing cohort included cases dating prior to the routine implementation of p16 immunohistochemistry (IHC) testing at our institution, therefore, p16 status was not required for inclusion in this study. Formalin-fixed paraffin-embedded (FFPE) tissue samples were sent to the UNC Lineberger Comprehensive Cancer Center (LCCC) Translational Genomics Lab (TGL) for RNA isolation using the Maxwell 16 MDx Instrument (Promega AS3000) and the Maxwell 16 LEV RNA FFPE Kit (Promega AS1260) following the manufacturer's protocol (Promega 9FB167). After a pathology review of a hematoxylin and eosin (H&E) stained slides to identify tumor area, RNA was extracted from unstained slides using macrodissection. Total RNA quality was measured using a NanoDrop spectrophotometer (Thermo Scientific ND-2000C) and a TapeStation 4200 (Agilent G2991AA). Total RNA concentration was quantified using a Qubit 3.0 fluorometer (Life Technologies Q33216). Libraries were prepared with Illumina TruSeq Stranded Total RNA with Ribo-Zero protocol. Libraries were sequenced on an Illumina HiSeq2500 sequencer. Paired end read data, with read lengths of 75 were collected.

  Study phs002935

• Use of new methodologies to achieve a thorough molecular characterization in pediatric acute leukemia

  In childhood leukemia, a better genetic characterization is needed to define new clinic-biological entities, refine the risk-stratification of patients and help to reduce the toxicity by applying a risk-directed therapy. This project aims to obtain information that will allow us to personalize the management of pediatric patients with leukemia as much as possible, so that we can offer a complete diagnosis, a sensitive follow-up and a more targeted treatment to the real risk of each case. The use of massive genome analysis technologies such as transcriptome sequencing (RNA-Sequencing) will allow a comprehensive biological characterization of pediatric leukemia patients, especially those cases that we have not been able to characterize by conventional diagnostic techniques. We believe that the RNA-Seq technique will allow us to identify new biomarkers that will be useful for: 1) defining new biological entities with their own clinical behavior; 2) refining the stratification of patients into risk groups; 3) finding targets for a better follow-up of MRD and 4) identifying therapeutic targets for the application of targeted therapies to reduce toxicity. PI: Camós-Guijosa, Mireia; Vega-García, Nerea Funding: PI21/00213 Instituto de Salud Carlos III (ISCIII)

  Study EGAS50000000701

• Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy

  Anti-PD-(L)1 therapy is routinely used in metastatic NSCLC. However, response rates vary and biomarkers predicting treatment efficacy are lacking. Liquid biopsies allow monitoring of residual disease during therapy. Residual circulating tumor DNA (ctDNA) after therapy represents a predictive marker for adverse outcome. Here, we assessed copy number variations (CNVs) in serial plasma samples of NSCLC patients receiving PD-(L)1 blockade. We profiled CNV and fragmentation features in 118 plasma samples of advanced NSCLC patients by low-coverage whole genome sequencing taken at baseline, after four therapy cycles and at disease progression. CNVs and fragment features (i.e., fragment length, end motifs, position) were significantly altered in patients compared to healthy donors. Furthermore, fragment length changes at baseline and residual CNVs after four therapy cycles correlated with short progression-free survival. Our results highlight the suitability of plasma-based CNV and fragment analysis for disease monitoring and as a predictive marker for response duration in NSCLC patients under anti-PD-(L)1 therapy.

  Study EGAS50000000441

• RNA Transcriptomic and DNA Methylation Landscape in FTLD-TDP and Controls

  Frontotemporal lobar degeneration (FTLD) is one of the leading causes of dementia in individuals younger than 65 years, with the aggregation of TDP-43 as one of the most common forms of FTLD. FTLD-TDP is clinically, genetically and pathologically heterogeneous, with GRN and C9orf72 as the most common genetic forms (although more than 50% of the cases are genetically unexplained), and A, B and C as the most common pathological subtypes. To investigate the molecular differences between the different forms of FTLD-TDP, we performed bulk RNA sequencing (RNAseq) and reduced representation bisulfite sequencing (RRBS) from different brain regions of FTLD-TDP patients and controls. The RNAseq dataset includes samples from the frontal cortex of 149 individuals, comprising 127 FTLD-TDP cases (genetically unexplained types A (27), B (20) and C (22), 24 GRN mutation carriers, and 34 C9orf72 expansion carriers) and 22 controls. The RRBS dataset includes samples from the frontal cortex of 158 individuals —119 FTLD-TDP cases (genetically unexplained types A (25), B (24), and C (25), 20 GRN mutation carriers, and 25 C9orf72 expansion carriers) and 39 controls; and from the cerebellum of 151 individuals —113 FTLD-TDP cases (genetically unexplained types A (24), B (21), and C (23), 20 GRN mutation carriers, and 25 C9orf72 expansion carriers) and 38 controls. In total, the study consists of data from 183 unique individuals, with some overlap across the different datasets.

  Study phs004075

• Small cell carcinoma of the ovary, hypercalcemic type, displays frequent inactivating germline and somatic mutations in SMARCA4

  Small cell carcinoma of the ovary of hypercalcemic type (SCCOHT) is an extremely rare, aggressive cancer affecting children and young women. We identified germline and somatic inactivating mutations in the SWI/SNF chromatin-remodeling gene SMARCA4 in 75% (9/12) of SCCOHT patients in addition to SMARCA4 protein loss in 82% (14/17) of SCCOHT tumors, but in only 0.4% (2/485) of other primary ovarian tumors. These data implicate SMARCA4 in SCCOHT oncogenesis.

  Study EGAS00001000714

• danMAC5

  Three whole genome sequecing of three independent cohorts. The three cohorts derives from projects including samples of inviduals with Danish origin. Data is deviden into males and female and compiled.

  Dataset EGAD00001009756

• Circulating RNAs in Acute Heart Failure (CRUCIAL)

  The purpose of this American Heart Association-funded and NIH-funded study is to examine circulating RNAs in the acute congestive heart failure (CHF) setting, and how they change with decongestive therapy, and their function in vitro and in vivo. The investigators are testing the hypothesis that ex-RNA levels change significantly during decongestion therapy and can be used as a marker of those individuals who respond to CHF therapy (in terms of cardiac structure or outcome). Additionally, the translational research design allows the investigators to assay the effects of these RNAs on tissue phenotypes in vitro.

  Study phs003403

• Patient Registry for Primary Pulmonary Hypertension (PPH Registry-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives Establish a patient registry to evaluate the natural history, etiology, pathogenesis and treatment of primary pulmonary hypertension. Specific aims included the characterization of the demographic, medical history, family history, physical and laboratory findings of patients at time of diagnosis, and to characterize the survival duration of patients by traits evaluated at diagnosis and by medical interventions. Background There are several known causes of pulmonary hypertension: chronic obstructive pulmonary disease, congenital heart disease, mitral stenosis, left ventricular dysfunction and recurrent pulmonary emboli. Primary Pulmonary Hypertension is a disorder of unknown etiology which is diagnosed only after the known causes of pulmonary hypertension have been eliminated. Prior to the PPH registry, little was known regarding the epidemiology, etiology, natural history or ultimate survival among patients with PPH. In 1973, the WHO met to review the current state of knowledge on PPH and proposed the establishment of a multicenter collaborative study. The NHLBI PPH registry enrolled patients in the registry from 1981 to 1985. Participants Participants were enrolled into the registry from 32 medical centers throughout the US. Pulmonary hypertension was defined as a mean pulmonary arterial pressure of >25 mmHg at rest or 30 mmHg with exercise at catheterization. The diagnosis of primary pulmonary hypertension was only accepted after the following secondary causes of pulmonary hypertension had been excluded: pulmonary hypertension within the first year of life, congenital abnormalities of the heart, lungs, or diaphragm, pulmonary thromboembolic disease, diagnosis of sickle cell anemia, history of intravenous drug abuse, obstructive lung disease, interstitial lung disease, arterial hypoxemia, collagen vascular disease, parasitic disease affecting the lungs, pulmonary artery or valve stenosis, or pulmonary venous hypertension. Baseline and follow-up data collected on participants include demographic characteristics, chest radiograph, pulmonary function tests, lung perfusion scan or pulmonary angiogram, intracardiac left-to-right shunt, pulmonary hemodynamics, as well as a history, physical findings and other laboratory measurements. Participants were followed for approximately 5 years. Conclusions There were 1.7 females for each male in the registry, and females tended to present with more severe symptoms. The mean time from onset of symptoms to diagnosis was 2 years. Right ventricular hypertrophy was found in 87% of participants and right atrial pressure was elevated in 72% of participants. The estimated median survival was 2.8 years with single year survival rates of: 1 year, 68%; 3 years, 48%; and 5 years, 34%. (Ann Intern Med, 1987; 107:216-23, Ann Intern Med, 1991; 115:343-49).

  Study phs004275

• The Molecular Landscape of Asian Breast Cancers Reveals Clinically Relevant Population-Specific Differences

  Molecular profiles of breast cancer have contributed to an improved understanding of the disease, enabled development of molecular prognostic signatures to guide treatment decisions and unveiled new or more accurate therapeutic options for breast cancer patients. However, the extent to which differences in genetic, environmental and lifestyle factors influence molecular profiles in different populations remains poorly characterised, as relatively few large-scale molecular studies of breast tumours in non-Caucasian populations have hitherto been reported. Here, we present the molecular profiles of 560 Asian breast tumours and a comparative analysis of breast cancers arising in Asian and Caucasian women. Compared to the breast tumours in predominantly Caucasian women reported in TCGA and METABRIC, we show an increased prevalence of Her2-enriched molecular subtypes and higher prevalence of TP53 somatic mutations in ER+ Asian breast tumours. Using gene expression and immunohistochemistry, we observed elevated immune scores in Asian breast tumours, suggesting potential clinical response to immune checkpoint inhibitors. Whilst Her2-subtype and enriched immune score are associated with improved survival, presence of TP53 somatic mutations is associated with poorer survival in ER+ tumours. Taken together, these population differences unveil new opportunities to improve the understanding of this disease and lay the foundation for precision medicine in different populations.

  Study EGAS00001004518

• The Haemgen RBC study

  Anaemia is a major determinant of global ill-health. To refine our understanding of the genetic factors influencing red blood cell formation and function, we carried out a meta-analysis of genome-wide association studies (GWAS) for six red blood cell traits: haemoglobin (HB), mean cell haemoglobin (MCH), mean cell haemoglobin concentration (MCHC), mean cell volume (MCV), packed cell volume (PCV) and red blood cell count (RBC). We provide genome-wide association results for 62,553 people of European ancestry using up to 2,644,161 autosomal SNPs. Participants with extreme measurements (>+/-3SD from mean) were excluded on a per phenotype basis. Imputation was done using haplotypes from HapMap Phase 2. SNP associations with each phenotype were tested by linear regression using an additive genetic model. Associations were tested separately in each cohort, with principal components and other study specific factors as covariates to account of population substructure. We then carried out meta-analysis of results from the individual cohorts using z-scores weighted by square root of sample size. SNPs with MAF<1% (weighted average across cohorts) were removed, as were SNPs with weight <50% of phenotype sample size. Anaemia is a major determinant of global ill-health. To refine our understanding of the genetic factors influencing red blood cell formation and function, we carried out a meta-analysis of genome-wide association studies (GWAS) for six red blood cell traits: haemoglobin (HB), mean cell haemoglobin (MCH), mean cell haemoglobin concentration (MCHC), mean cell volume (MCV), packed cell volume (PCV) and red blood cell count (RBC). We provide genome-wide association results for 62,553 people of European ancestry using up to 2,644,161 autosomal SNPs. Participants with extreme measurements (>+/-3SD from mean) were excluded on a per phenotype basis. Imputation was done using haplotypes from HapMap Phase 2. SNP associations with each phenotype were tested by linear regression using an additive genetic model. Associations were tested separately in each cohort, with principal components and other study specific factors as covariates to account of population substructure. We then carried out meta-analysis of results from the individual cohorts using z-scores weighted by square root of sample size. SNPs with MAF<1% (weighted average across cohorts) were removed, as were SNPs with weight <50% of phenotype sample size.

  Study EGAS00000000132

• Early progression to active tuberculosis is a highly heritable trait driven by 3q23 in Peruvians

  In a genome-wide genetic study of early progression to active tuberculosis (TB), we genotyped 4,002 active TB cases and their household contacts in Lima, Peru. We first established TB progression has a strong genetic basis, and is comparable to traits with well-established genetic bases (h2g=0.212). We identified a novel association between early TB progression and variants located in a putative enhancer region on chromosome 3q23 (rs73226617, OR = 1.18; P = 3.93 x 10-8). With in silico and in vitro analyses we identified genetic variant rs73226617 or rs148722713 as the likely functional variant and ATP1B3 as a potential causal target gene with monocyte specific function.

  Study phs002025

• International Cancer Proteogenomics Consortium (ICPC): Proteogenomics of East-Asian Breast Cancer

  The incidence of invasive breast cancer is rapidly increasing in East Asia, enriching in younger patients and luminal disease. We presented a deep proteogenomic landscape of a prospectively enrolled early-stage cohort in Taiwan to uncover the etiology, age-related subtype and oncogenic vulnerabilities underlying the heterogeneous disease. Multilayer proteogenomic architecture revealed distinct endogenous and environmental carcinogen-associated mutagenesis, linking APOBEC (apolipoprotein-B mRNA editing enzyme, catalytic polypeptide-like) cytidine deaminase and DBAC (dibenz[a,j] acridine) signatures to significantly elevated hormone biosynthesis and chemical carcinogenesis in younger patients, and identifying a novel subset of high mutation burden and immune escape potentially beneficial from combined epigenetic therapy and immunotherapy. A proteomics-informed classification resolves luminal heterogeneity, defines high-risk recurrent luminal disease and nominates biomarkers and actionable druggable pathways. Furthermore, proteogenomics profile distinguished a young luminal population susceptible to exogenous carcinogen and having DNA repair deficiency. This study illuminates the age-related molecular subtypes and oncogenic vulnerabilities, providing a proteogenomics-transformative guide for patient stratification and precision therapeutics beyond clinical staging.

  Study phs003150

• UK10K NEURO ASD GALLAGHER

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. This is an Irish sample set of individuals with ASD (approximately 50% with comorbid intellectual disability). Individuals have been diagnosed with ADI/ ADOS, measures of cognition/ adaptive function. They represent a more severe, narrowly defined cohort of ASD subjects. Family histories are available for some with measures of broader phenotype. For further information on this cohort please contact Nadia Bolshakova (bolshakn@tcd.ie).

  Study EGAS00001000112

• The NIHR BioResource Rare Diseases BRIDGE consortium sequencing projects

  The NIHR BioResource Rare Diseases BRIDGE consortium is a collaboration between 13 Rare Disease projects that aim to discover the genetic sequence variants underlying unresolved inherited disorders and to improve identification of already identified high penetrance variants. BRIDGE projects cover a variety of rare disease research areas including Cardiovascular, Infection and Immunity and Neuroscience. The consortium aims to sequence 8,000 samples across the different projects by 2017.

  Study EGAS00001001012

• 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: 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

• Drug screening and whole genome sequencing of primary cells and cell lines from ovarian cancer patients to associate genomic aberrations with in vitro drug sensitivities

  Identifying drugs for cancers with poor prognosis like ovarian cancer (OC) is hindered by inappropriate cell models and the limitations of current viability assays. We developed an automated confocal microscopy-based live cell assay (DeathPro) that robustly de-convolves cell death and proliferation over time by employing a specific image processing strategy. Using DeathPro, we screened nine OC patient-derived cell lines and one normal cell line (HOSEpiC) with 22 drugs or combinations. Whole genome was performed to analyze if the cell lines harbor OC-typical genomic aberrations and to relate genomic features to drug sensitivities. Commonly observed alterations in OC patients like TP53 mutations and MYC or PI3KCA amplifications were absent in the normal cell line but frequently detected in the OC cell lines. Moreover, genome-derived homologous recombination deficiency (HRD) scores of the OC cell lines correlated with their responses to carboplatin, olaparib and DNA demethylation drugs. Overall, we propose an imaging-based platform to guide drug development and genome-drug sensitivity analysis.

  Study EGAS00001002239

• Early evolutionary branching across spatial domains predisposes to clonal replacement under chemotherapy in neuroblastoma

  Neuroblastoma (NB) is one of the most lethal childhood cancers due its propensity to treatment resistance. By spatial mapping of subclone geographies before and after chemotherapy across 89 tumor regions from 12 NBs, we find that densely packed territories of closely related subclones present at diagnosis are replaced under effective treatment by islands of distantly related survivor subclones, originating from a different most recent ancestor compared to lineages dominating before treatment. Conversely, in tumors that progressed under treatment, ancestors of subclones dominating later in disease are present already at diagnosis. Chemotherapy treated xenografts and cell culture models replicates these two contrasting scenarios and shows branching evolution to be a constant feature of proliferating NB cells. Phylogenies based on whole genome sequencing of 505 individual NB cells indicate that a rich repertoire of parallel subclones, emerges already with the first oncogenic mutations and lays the foundation for clonal replacement under treatment.

  Study EGAS00001007650

• Clinical outcomes and immune correlates of response to nivolumab plus chemoradiotherapy in women with locally-advanced cervical cancer – NiCOL study

  Concurrent chemoradiotherapy (CRT) with blockade of the PD-1 pathway may enhance immune-mediated tumor control through increased phagocytosis, cell death, and antigen presentation. The NiCOL phase 1 trial was designed to determine safety, tolerance, and immune correlates of response to the PD-1 blocking antibody, nivolumab, with and following concurrent CRT in 16 women with locally advanced cervical cancer (LACC). Three patients experienced grade 3 dose-limiting toxicities. The overall response rate was 93.8% [95%CI: 69.8%-99.8%] with a 2-year PFS of 75% [95% CI: 56.5%-99.5%]. Compared to patients with progressive disease (PD), progression-free (PF) subjects showed a brisker stromal immune infiltrate, higher proximity of tumor-infiltrating CD3+ T cells to PD-L1+ tumor cells and of Foxp3+ T cells to proliferating CD11c+ myeloid cells. PF had higher baseline levels of PD-1 on EMRA CD4+ T cells and ICOS-L on tumor-associated macrophages (TAMs) vs PD, which instead displayed enhanced PD-L1 expression on TAMs and higher, circulating frequencies of proliferating Tregs at baseline. Concomitant nivolumab plus definitive CRT is safe and associated with encouraging PFS rates. Further validation in the subset of LACC displaying pre-existing, adaptive immune activation is warranted.

  Study EGAS00001007297

• Population Genetics Analysis Program: Immunity to Vaccines/Infections - Smallpox Vaccination (NIAID/NIH)

  The study examines the role of candidate human immune response gene polymorphisms (and their receptors, expression and function) and variations in immune response, among 1,000 active duty members of the military who were recently vaccinated with ACAM2000 or Dryvax Smallpox vaccine. In addition to the phenotype and genotype data available through dbGaP, extensive clinical data are available through NIAID&#39;s ImmPort data portal; information to map the the data available in dbGaP to the data available in ImmPort is provided in the dataset pht005302.v1.p1 of the current study, dbGaP phs001057.v1.p1.

  Study phs001057

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

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

  Study EGAS50000001030

• Chromosome contacts in activated T cells identify autoimmune disease-candidate genes

  Autoimmune disease-associated DNA variants are preferentially found in regions with putative regulatory function in immune cells, particularly CD4+ T cells. Linking such regulatory elements to gene promoters in disease-relevant cells and contexts is essential to identify disease candidate genes. Here we show that the activation of CD4+ T cells invokes changes in the activity of regulatory elements and transcription of RNAs that correspond to changes in the expression of their interacting genes identified by promoter capture Hi-C (PCHi-C).

  Study EGAS00001001961

• Transcriptomic profiling of skin biopsies from psoriasis patients following treatment with Zasocitinib

  The objective of this study is the exploratory analysis and characterization of psoriasis using RNA-seq-based profiling. Specifically, the cutaneous and serum biomarker profiles associated with the molecular, histological and clinical effects of Zasocitinib treatment in patients with moderate-to-severe plaque psoriasis were characterized. To evaluate differences between the transcriptomic profiles of Zasocitinib- and placebo-treated patients, exploratory biomarker endpoints included quantification of skin biomarkers, such as immune cell infiltration and mRNA expression levels in lesional and non-lesional skin, as well as quantification of circulating cytokines and other inflammatory biomarkers.

  Study EGAS50000001548

• Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss

  The Demographically Diverse Substance Use Disorder Cohorts of Dr. Stanley H. Weiss, which constitute the Epidemiology of the Weiss Cohort Projects, consist of a series of inter-connected projects, building upon a set of cohort projects of various groups, mainly drug users from medication-assisted treatment programs, that Dr. Stanley H. Weiss first developed in the 1980&#8217;s plus several newer initiatives, each with an array of collaborators. Beginning in the 1980&#8217;s, Dr. Stanley H. Weiss started several long-term studies of persons who inject drugs (PWID) across the United States, ultimately enrolling over 10,000 participants through the early 1990&#8217;s with an average age then in their 30&#8217;s. About a quarter were enrolled from sites in New Jersey (NJ). These studies included the first testing of PWID for the human immunodeficiency virus (HIV) and the human T-cell lymphotropic viruses (HTLV I and HTLV II). Cumulative past support (initiation thru ~ 1999) for these cohort studies included ~ $20 million from intramural resources from the National Cancer Institute (NCI) and the National Institute on Drug Abuse (NIDA), plus multiple grants and in-kind support from the New Jersey Department of Health (NJDOH) totaling ~ $1 million. The Weiss Cohort Projects include the first large AIDS-era cohorts to include women at high risk for HIV. A high percentage of subjects in these studies are black or Latino. Thus, this is an ethnically diverse US cohort, with a high proportion of women included. These subjects are at high risk of parenteral and sexual infection from both drug use and sexual practices. Samples from other studies conducted by Dr. Weiss, in which detailed interviews were conducted, are included as controls (persons documented by us not to have a history of opioid drug use). As one of our groups of subjects have many persons of Haitian ancestry, we specifically included some Haitians who had never used opioids as controls. Our documentation includes such ancestry. These cohorts demonstrated high rates of HIV and HTLV-II infection in PWIDs, including one study initiated in 1981 with confirmation in the later cohorts. In the first two decades of these studies, among numerous publications was the first study showing a very high rate of hepatitis C infection among PWIDs. An example of how the studies&#8217; long-time horizon proved essential was that it first became possible to test whether a person had ever been infected with hepatitis C virus (HCV), as well as how much HCV was in each person&#8217;s blood, many years after the specimens were collected. This allowed HCV amounts in blood to be compared for subjects who had died of liver disease early in the study versus those who survived. Then a sequence of published papers culminated in demonstrating, using a nested case-control design, that a high baseline HCV titer was predictive of early progression to death from end-stage liver failure. Outcomes related to HCV (end stage liver disease and hepatocellular carcinoma) remain under study. In the original cohort studies, the mean age at enrollment was ~ 33 years old, so that those still alive in 2022 are mainly now ~ 60 - 75 years old. Many participants have already died. The tincture of time has led to subjects reaching ages when many more are dying from a wide array of outcomes, including from many chronic diseases (including cancer) as well as from infectious agents (especially HIV, HCV) or drug overdose. Renewed collaboration with local drug treatment programs has led to new field-based studies, including examination of some currently evolving problems among drug users. Dr. Weiss joined the National Institute on Drug Abuse (NIDA) Genetics Consortium (NGC) in 2017, and through the NIDA project officer has had access to NGC contract resources (see below). NIH Certificate of Confidentiality, CC-DA-16-214 (attached) protects these studies. Past arrangements related to data on our subjects leads to restrictions on the use of data emanating from our study, such as potential commercialization and restrictions on whom may access and use these data. NIDA Genetics Consortium (NGC) resources further support these endeavors and will be used as part of the NGC analyses studying the genetics of substance use. Study participants signed informed consent for the information collected from them to be used with no time limit and for biologic specimens collected from them to be used without restriction in future research. Serum samples were collected from participants, and from many also plasma, white blood cells and/or urine samples. About 100,000 vials were stored. All specimens have been continuously preserved at sufficiently cold temperatures to prevent deterioration, and many subjects separated white blood cells were processed and frozen in such a way as to maintain viability. Detailed data from the participants has been accumulated over time, and in general, linkage has been retained in each sub-study in accordance with the consent forms and protocols. For some participants, specimens were collected at multiple times (that is, sequential specimens). Multiple specimens from a single person exist in this database, and efforts at de-duplication remain ongoing. Dr. Weiss should be contacted if an investigator requires unique individuals since: &#8226; Multiple phases of enrollment occurred, and as our prospective follow-up continues; Dr. Weiss may identify new instances of multiple enrollment. &#8226; Some persons are related to each other. &#8226; In general, in this dataset for dbGaP, only a single specimen/record form a given person is included. Advances in laboratory testing techniques now permit innovative new uses for our linked research biospecimen repository. The ongoing focus of an interdisciplinary research program based on these cohorts relates subjects&#8217; diseases, behaviors, medical history, and outcomes with biological and exposure markers. Participants&#8217; use of various substances was ascertained on study enrollments, many serially over time. Quantitative frequency of use data, also sometimes sequential over time, were ascertained. Active ascertainment of outcomes is being conducted, including matching to mortality and cancer databases. Investigators interested in collaborations on specific outcomes (which is not part of this dbGaP dataset) or in the use of our stored specimens are encouraged to contact the principal investigator, Dr. Weiss. The processing of the genomic data was done in conjunction with NIDA, and in accordance with some longstanding data cleaning steps used by NIDA in the NIDA Genetics Consortium (NGC), a group to which we shall be contributing these data for collaborative analyses. Since there is the potential for these steps to introduce certain types of potential biases, we summarize these here. Under contract from NIDA, cryopreserved sera or plasma (-80 C) or cells (in liquid nitrogen) were used, with most stored having been stored for 30 to 40 years in our biorepository. In the case of serum or plasma, in which only (largely) cell-free DNA fragments were available, DNA was extracted and restored prior to amplification. Industry standard DNA amplification techniques were done on all samples prior to genotyping in accord with established protocols of the NIDA Genetics Consortium. Our genotype data were run and processed on the Illumina Infinium OmniExpress_v_1.3 array. This array has 714,238 SNPs, and was designed many years ago. There were 628 SNPs on the array that do not correspond to any chromosome position, and these were removed. Genotype data were submitted by NIDA&#8217;s contracted genotyping laboratory in six batches over time to NIDA&#8217;s contracted dbGaP data management group, which conducted quality control (QC) analyses. QC analysis included an assessment of batch effects on for five of the six batches. (One of the batches, with only 12 samples, was too small for QC analysis of batch effects.) Standard NIDA Genetic Consortium cleaning was performed. Samples with a call rate &lt;.85 were removed. Only one sample per person was retained. When more than one specimen was genotyped from one subject, only the sample with the higher call rate was retained (provided, of course, that that call rate was &#8805; 0.85). We have retained some people we know are related, including some found to have been related through genotyping; the pedigree file describes those relationships. In summary, key cleaning steps include: 1. Using PLINK to check gender discrepancy. 2. Using PREST-PLUS and KING (Kinship-based Inference for GWAS) to check relatedness. 3. Using PEDCHECK and PLINK to check/zero-out Mendelian error. 4. Using PLINK to perform sample QC, SNP QC, along with KING to perform chromosome X and chromosome Y QC. 5. SNP-QC: Batch-effect: 5 Batches were compared (one batch, with few samples, was not). These five batches were compared to each other in all ten possible pairs, one batch vs. another batch, examining SNP allele frequency discrepancies by population (from GRAF), Fisher Exact Allelic test, with the criterion of p&lt;5e-8 for removal. 6. SNP-QC: discordant SNPs in QC duplicates. Compared 25 QC duplicated samples with call rate &gt; 0.95, removed SNPs with 3+ discordance. 7. There were 1,056 SNPs that were monomorphic; these have been retained so they can be included in analyses in which our dbGaP data are combined with those from other cohorts (in the latter of which those SNPs may not be monomorphic). The final cleaned dataset submitted has 8,898 samples and 606,793 SNPs.

  Study phs002140

• Sexual dimorphism in human immune system aging

  We isolated peripheral blood mononuclear cells (PBMCs) from 172 community-dwelling healthy volunteers (91 women, 81 men) ages spanning adult lifespan: 54 young (ages 22-40: 23 men, 31 women), 59 middle-aged (ages 41-64: 31 men, 28 women), and 59 older subjects (65+: 27 men, 32 women). PBMCs were profiled using ATAC-seq (54 men, 66 women), RNA-seq (41 men, 34 women), and flow cytometry (62 men, 67 women). Flow cytometry data is publicly available, genomic data for 121 individuals are provided here. These datasets revealed immune system aging signatures in men and women and showed in which ways aging differentially affects the immune systems of men and women. A subset of these samples have been generated and analyzed previously and can be found at EGA (EGAS00001002605). This dataset on dbGaP include EGA samples as well.

  Study phs001934

• NCI COVID-19 in Cancer Patients Study (NCCAPS): A Longitudinal Natural History Study

  NCCAPS is a longitudinal prospective cohort study designed to assess patient, disease and treatment factors associated with short- and long-term outcomes in patients with cancer who develop COVID-19. We also aimed to describe COVID-19 symptoms and treatments, and to describe disruptions in cancer treatment due to COVID-19. The study enrolled patients with cancer on active treatment or with a history of stem cell transplant or CAR-T cell therapy with new, active COVID-19, defined as being within 14 days of their first positive SARS-CoV-2 test. The study found that receipt of chemotherapy and baseline history of stroke, atrial fibrillation or pulmonary embolism were associated with a higher risk of hospitalization for COVID-19. Vaccination for SARS-CoV-2 was associated with a lower risk of hospitalization. Death due to COVID-19 was highest in patients with lymphoma, intermediate in those with acute leukemia and lung cancer, and lowest in those with other solid tumors and other hematologic cancers. Disruptions of cancer treatment were frequent in the first 30 days after SARS-CoV-2 infection.

  Study phs004178

• 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

• 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: 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

• Single-Cell Analysis of Somatic Mutations in Human Bronchial Epithelial Cells in Relation to Aging and Smoking

  While lung cancer risk among smokers is dependent on smoking dose, it remains unknown if this increased risk reflects an increased rate of somatic mutation accumulation in normal lung cells. Here we applied single-cell whole genome sequencing of proximal bronchial basal cells from 33 subjects, aged between 11 and 86 years, with smoking histories varying from never smoking to 116 pack years. We found an increase in the frequency of single-nucleotide variants and small insertions and deletions with chronological age in never-smokers, with mutation frequencies significantly elevated among smokers. However, when plotted against smoking pack-years, mutations were found to follow the linear increase in cancer risk only until about 23 pack years, after which no further increase in mutation frequency was observed, pointing towards individual selection for mutation avoidance. Known lung cancer-defined global mutation signatures tracked with both age and smoking. Within study power limits, no significant enrichment for somatic mutations in lung cancer driver genes was observed.

  Study phs002758

• CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Summary Results from Genomic Studies

  GWAS have successfully identified genetic loci associated with a variety of conditions such as type 2 diabetes and coronary disease. The large number of statistical tests required in GWAS has posed a special challenge because few studies that have DNA and high-quality phenotype data are sufficiently large to provide adequate statistical power for detecting small to modest effect sizes. Even before the era of GWAS, the requirement for large sample sizes and the importance of replication have served as powerful incentives for collaboration. Meta-analyses combining summary data from multiple sources have improved the ability to detect new loci. The Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium was formed to facilitate GWAS meta-analyses and replication among multiple large and well-phenotyped cohort studies. The design of the CHARGE Consortium was formed initially from 5 prospective cohort studies from the United States and Europe: the Age, Gene/Environment Susceptibility (AGES) - Reykjavik Study, the Atherosclerosis Risk in Communities (ARIC) Study, the Cardiovascular Health Study (CHS), the Framingham Heart Study (FHS), and the Rotterdam Study (RS). Additional studies have expanded the CHARGE consortium based upon the phenotypes and willingness to share information across the research community. In order to facilitate investigators across the world to examine relationships between phenotypes and genetic markers within CHARGE published reports, an open site is made available on dbGaP that provides the rsID and the p-value for inspection. Access to detailed summary statistics (including minor allele frequency, odds ratio/effect size) requires approval of a Data Access Request (DAR).

  Study phs000930

• Functionally Active Copy Number Variants Associated with Prostate Cancer Risk

  Prostate cancer is a leading cause of cancer death in males throughout the world and has the largest estimated effect of heritability among the most common tumor types. Copy Number Variants (CNVs) are a recently recognized class of human germline polymorphisms (Iafrate AJ, et al. (2004) Nat Genet 36, 949-951; Sebat J, et al. (2004) Science 305, 525-528.) and are associated with a variety of human diseases, including cancer. This study characterized 1,903 individuals from the Tyrol Early Prostate Cancer Detection Program (Bartsch G, et al. (2008) BJU Int 101, 809-816) using a computational framework (Banerjee S, et al. (2011) PLoS One 29;6(3)). The study results establish non-coding and coding germline CNVs as significant risk factors for prostate cancer susceptibility and implicate their role in disease development and progression. The study "Identification of functionally active, low frequency copy number variants at 15q21.3 and 12q21.31 associated with prostate cancer risk," Demichelis F, Setlur SR, Proc Natl Acad Sci U S A. 2012 Apr 24;109(17):6686-91.

  Study phs000487

• Allele Balance Bias Identifies Systematic Genotyping Errors and False Disease Associations

  In recent years, Next Generation Sequencing (NGS) has become a cornerstone of clinical genetics and diagnostics. Many clinical applications require high precision, especially if rare events such as somatic mutations in cancer or genetic variants causing rare diseases need to be identified. Although random sequencing errors can be modeled statistically and deep sequencing minimizes their impact, systematic errors remain a problem even at high depth of coverage. Understanding their source is crucial to increase precision of clinical NGS applications. In this work, we studied the relation between recurrent biases in allele balance (AB), systematic errors and false positive variant calls across a large cohort of human samples analyzed by whole exome sequencing (WES). We have modeled the allele balance distribution for biallelic genotypes in 987 WES samples in order to identify positions recurrently deviating significantly from the expectation, a phenomenon we termed allele balance bias (ABB). Furthermore, we have developed a genotype callability score based on ABB for all positions of the human exome, which detects false positive variant calls that passed state-of-the-art filters. Finally, we demonstrate the use of ABB for detection of false associations proposed by rare variant association studies (RVAS).

  Study EGAS00001003027

• 16S rRNA Rectal Mucus

  16S rRNA sequencing of rectal mucus samples from patients suspected to have colorectal cancer. This is 1 of 4 sequencing experiments on the same sample type.

  Study EGAS50000001262

• Enzymatic Methyl-Seq Rectal Mucus

  Enzymatic methyl sequencing of rectal mucus samples from patients suspected to have colorectal cancer. This is 1 of 4 sequencing experiments on the same sample type.

  Study EGAS50000001314

• Interferon lambda 4 impairs viral antigen presentation and attenuates T cell responses

  Genetic variants of the interferon lambda (IFNL) gene locus are strongly associated with spontaneous and IFN treatment induced clearance of hepatitis C virus (HCV) infections. Individuals with the ancestral IFNL4-dG allele are not able to clear HCV in the acute phase and develop chronic hepatitis C (CHC) with more than 90% probability. Paradoxically, the IFNL4-dG allele encodes a fully functional IFNλ4 protein with antiviral activity against HCV and coronavirus. Here we describe a hitherto unknown effect of IFNλ4 on HCV antigen presentation. Only minor amounts of IFNλ4 are secreted, because the protein is largely retained in the endoplasmic reticulum (ER) where it induces ER stress. Stressed cells were significantly weaker activators of HCV specific CD8+ T cells. This was not due to reduced MHC I surface presentation or extracellular IFNλ4 effects, since T cell responses could be restored by exogenous loading of MHC with HCV antigens. Rather, IFNλ4 induced ER stress impaired HCV antigen processing and/or loading onto the MHC I complex. Our results provide a potential explanation for the IFNλ4 – HCV paradox.

  Study EGAS00001005396

• Clinical and Genetic Analysis of Costa Rican Patients with Parkinson's Disease

  This study is a pilot study designed to describe the clinical and genetic landscape of Parkinson's disease in Costa Rica. While most genetic studies have been conducted on Europeans, few have examined Parkinson's disease in Costa Ricans. 118 patients and 97 controls were recruited at the Movement Disorders Unit of the Department of Neurology, Hospital San Juan de Dios, Caja Costarricense de Seguro Social, Costa Rica. Familial Parkinson's disease genes were sequenced using Next-Generation Sequencing. We also measured and obtained different sociodemographic and clinical information.

  Study phs002495

• Genomic and Genetic Analysis of Brain Tumors and Analysis of Their Clinicopathological Significance

  The treatment outcome of glioma patients remains disappointing, and more studies are needed to improve therapeutic strategies. In particular, it is crucial to understand the mechanisms underlying resistance to treatment and malignant transformation, as well as the intratumoral heterogeneity and interaction of tumor cells and host immunity. Recent advances in omics analysis techniques, such as next-generation sequencing (NGS), have enabled us to obtain omics data more easily and accelerated our ability to integrate this information and precisely characterize cases. In our project, we have already collected more than 100 pairs of human glioma/normal tissue samples, of which some are multiple specimens collected from initial and recurrent tumors, and some include multiple specimens collected from different regions within a single tumor. We used our in-house algorithms, composed of alignment and variant calling programs, to analyze omics data from multiple platforms, such as whole-exome sequencing (WES), RNA sequencing (RNA-seq), and methylation array, with our original cohort of glioma patients. Using several informatics tools, the information about genetic and epigenetic status and expression signatures were analyzed. Those data are expected to provide key information for investigating the mechanisms discussed above. Through this project, we hope to improve strategies for personalized therapy based on comprehensive omics data.

  Study JGAS000004

• The landscape of chromothripsis across adult cancer types

  Chromothripsis is a recently identified mutational phenomenon, by which a presumably single catastrophic event generates extensive genomic rearrangements of one or a few chromosome(s). Considered as an early event in tumour development, this form of genome instability plays a prominent role in tumour onset. Chromothripsis prevalence might have been underestimated when using low-resolution methods, and pan-cancer studies based on sequencing are rare. We analysed chromothripsis in 28 tumour types covering all major adult cancers (634 tumours, 316 whole-genome and 318 whole-exome sequences). We show that chromothripsis affects a substantial proportion of human cancers, with a prevalence of 49% across all cases. Chromothripsis generates entity-specific genomic alterations driving tumour development, including clinically relevant druggable fusions. Chromothripsis is linked with specific telomere patterns and univocal mutational signatures in distinct tumour entities. Longitudinal analysis of chromothriptic patterns in 24 matched tumour pairs reveals novel insights in the clonal evolution of tumours with chromothripsis. (H021)

  Study EGAS00001004250

• Jackson Heart Study (JHS-BioLINCC)

  Accessing Data: Please refer to &#8220;Authorized Access&#8221; below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Related Studies: Other Jackson Heart Study data available include: Imaging studies (JHS-Imaging), Genetics and genomics (The Jackson Heart Study, phs000286.v7.p2), and Collaborative Cohort of Cohorts for COVID-19 Research (C4R-JHS, phs002907.v1.p1): Jackson Heart Study (phs002907.v1.p1).Available Data: Data available for request include Jackson Heart Study visit 1-3 examination cycles, collated annual follow-up communication data through 2016, and follow-up for mortality, heart disease, and stroke events through 2014.Objectives: The objectives of the Jackson Heart Study are to: 1) investigate the associations of biological, psychosocial, and behavioral factors with the incidence atherosclerotic events and health outcomes in an African American cohort; and 2) increase access to and the participation of African American populations and scientists in biomedical research and professions.Background: It has long been recognized that African Americans share a disproportionate burden of deleterious health outcomes including diabetes, hypertension, kidney disease and early onset of cardiovascular disease. The Jackson Heart Study was initiated in 2000 to explore potential mechanisms and mediators of health outcomes in a large African American cohort. In addition, the JHS conducts a variety of community education and outreach activities to promote healthy lifestyles to reduce disease risk burden and student training programs to promote and support public health research.Participants: African American men and women, age 35-84 at entry. Of the 5306 cohort members enrolled in the study, the data repository contains data from 3,883 that provided informed consent to share their data with investigators not affiliated with the study.Design: Participants were enrolled in the study from 2000-2004 from urban and rural areas of three counties (Hinds, Madison and Rankin) in the Jackson, MS metropolitan statistical area. Participants were enrolled from each of 4 recruitment pools: a random sample component (17%), volunteer component (30%), currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study (31%), and secondary family members (22%). Recruitment was limited to non-institutionalized adult African Americans age 35-84 years, except in the family cohort where those age &#8805;21 years were eligible. The final cohort of 5,306 participants includes 6.59% of all African American residents aged 35-84 (N=76,426, US Census 2000). Data collection at the baseline exam included a medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic status; and health care access.The current release of the Jackson Heart Study includes data collected at baseline, exam 2 (2005-2008), and exam 3 (2009-2013). Annual follow-up and surveillance of clinical cardiovascular events is ongoing.

  Study phs003740

• Whole genome sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia

  TCF3::PBX1 leukemia is a rare subtype of B-cell acute lymphoblastic leukemia (B-ALL), occurring in approximately 3–5% of pediatric cases. It results from a chromosomal translocation t(1;19)(q23;p13), generating the TCF3::PBX1 fusion gene, which disrupts normal transcriptional regulation and contributes to leukemogenesis. Although historically associated with poor prognosis, contemporary risk stratification and intensified therapy have significantly improved outcomes, and both 5-years DFS and OS are nowadays ≥ 0.96.

  Study EGAS50000001257

• Panel sequencing of endocrine-resistant breast cancer

  Patients with endocrine-resistant breast cancer in Stockholm Sweden. DNA obtained from patients primary and relapse tumors, and tumor-free lymph nodes used as germline control. DNA was extracted from formalin-fixed paraffin-embedded tissue and sequenced by 370-gene panel-based sequencing with Kapa HyperPlus library preparation and Twist Bioscience hybrid capture. Custom bait sets (panels) from Twist Bioscience. Paired end 2x150 bp using NovaSeq X. The data is presented as fastq-files.

  Study EGAS50000000236

• RNA sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia

  TCF3::PBX1 leukemia is a rare subtype of B-cell acute lymphoblastic leukemia (B-ALL), occurring in approximately 3–5% of pediatric cases. It results from a chromosomal translocation t(1;19)(q23;p13), generating the TCF3::PBX1 fusion gene, which disrupts normal transcriptional regulation and contributes to leukemogenesis. Although historically associated with poor prognosis, contemporary risk stratification and intensified therapy have significantly improved outcomes, and both 5-years DFS and OS are nowadays ≥ 0.96.

  Study EGAS50000001797

• Nivolumab and Tumor Infiltrating Lymphocytes (TIL) in Advanced Non-Small Cell Lung Cancer

  We performed a trial of adoptive cell therapy using tumor infiltrating lymphocytes (TIL) in metastatic non-small cell lung cancer (NSCLC). We conducted a single-arm open- label phase 1 trial (NCT03215810) of TIL administered with nivolumab in 20 patients with advanced NSCLC. Patients had tumor metastases resected for TIL, and the sequencing data from these tumors is included herein. The primary endpoint was safety, and secondary endpoints included objective response rate, duration of response, and T-cell persistence. Autologous TIL was expanded ex vivo from minced tumors cultured with IL-2. Patients received initial nivolumab for 4 cycles. If they had subsequent evidence of progression, then they proceeded to receive cyclophosphamide and fludarabine lymphodepletion, TIL infusion, and interleukin-2, followed by maintenance nivolumab. The endpoint of safety was met according to pre-specified criteria. Of 13 evaluable patients, 3 had confirmed responses and 11 had reduction in tumor burden, with a median best change of 35%. Two patients achieved complete responses ongoing 1.5 years later. In exploratory analyses, we found T cells recognizing multiple types of cancer mutations were detected after TIL treatment, and were enriched in responding patients.

  Study phs002486

• A GWAS meta-analysis on severe acne on a European population of 26,722 individuals

  Acne vulgaris is a highly heritable common, chronic inflammatory disease of the skin. We performed a genome-wide association study of 3,823 cases and 16,144 controls followed by meta-analysis with summary statistics from a previous study, with a total sample size of 26,722. We identified 20 independent association signals at 15 risk loci, 12 of which have not been previously implicated in the disease.

  Study EGAS00001003278

• Somatic L1 retrotranspositions in normal human cells

  Genomic mutations accumulate in normal cells during lifetime; however, somatic mosaicism generated by mobilization of transposable elements is not well understood. Here, we explored whole-genome sequences of single-cell expanded clones to illustrate the mutational landscape produced by L1. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 and read-through RNA expression profiles to investigate the epigenetic regulation of L1 activity.

  Study EGAS00001006213

• Neuroblastoma patient WGS data

  Paired tumor and normal WGS of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

  Dataset EGAD00001008123

• GEOCODE data access policy

  The GEOCODE Data Access Policy ensures the responsible use, security, and compliance of GEOCODE data. Access to GEOCODE data is restricted to authorized users based on role-based permissions, ensuring compliance with data protection regulations.

  Dac EGAC50000000574

• Distinct genomic profiles and clinical outcomes in constitutional mismatch repair deficiency-associated high-grade gliomas: insights into mutational signatures and clonal evolution

  Constitutional mismatch repair deficiency (CMMRD) is a rare cancer-predisposition syndrome, yet the mutational processes and clonal evolution of CMMRD-associated high-grade gliomas (HGGs) remain incompletely understood. In this study, mutational signatures and tumor evolution were analyzed in 25 CMMRD-associated HGGs. Germline biallelic mutations were most frequently identified in MSH6 (56.0%), followed by PMS2 (36.0%) and MLH1 (8.0%). Affected patients showed very early disease onset (mean 5.8 years) and poor clinical outcomes, with a mean progression-free survival of 16 months. Distinct genomic and clinical differences were observed between MSH6- and PMS2-associated tumors. MSH6-deficient HGGs were enriched for SBS6, whereas PMS2-deficient tumors showed predominance of SBS21, and these mutational signatures were correlated with prognosis. Clonal evolution analyses revealed early involvement of POLE/POLD1 mutations and persistence of the founding clone at recurrence. Overall, the study highlights the importance of mutational signatures and clonal evolution in shaping tumor behavior and clinical outcomes in CMMRD-associated HGGs.

  Study EGAS50000001506

• Atypical teratoid/rhabdoid tumors (ATRT) are comprised of three epigenetic subgroups with distinct enhancer landscapes

  Atypical teratoid/rhabdoid tumor (ATRT) is one of the most common brain tumors in infants and young children. Although the prognosis of ATRT patients is poor, some patients respond very well to current treatments, suggesting inter-tumor molecular heterogeneity. To investigate this further, we genetically and epigenetically analyzed a large cohort of ATRTs (n = 170). Three distinct molecular subgroups of ATRTs, associated with differences in demographics, tumor location and type of SMARCB1 alterations, were identified using DNA-methylation or gene expression analyses. Whole genome DNA- and RNA-sequencing found no other recurrent mutations explaining the differences between subgroups. However, whole genome bisulfite-sequencing and H3K27Ac ChIP-sequencing of primary tumors revealed clear differences in methylation patterns and enhancer landscapes, leading to the identification of subgroup-specific regulatory networks.

  Dataset EGAD00001001444

• Kidney_tumour_DNA

  This is a bulk DNA and RNA sequencing study of human renal tumours

  Study EGAS00001002486

• PETAL trial Whole Exome Sequencing (WES) from Normal Samples

  Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 55 Normal Samples. WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

  Dataset EGAD50000002507

• PETAL trial Whole Exome Sequencing (WES) from Tumor Samples

  Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 224 Tumor Samples. WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

  Dataset EGAD50000001172

• METABRIC: Data from Pereira et al (2016), The somatic mutation profiles of 2433 breast cancers refine their genomic and transcriptomic landscapes. Nat Comms 7.

  The genomic landscape of breast cancer is complex, and inter- and intra-tumour heterogeneity are important challenges in treating the disease. In this study, we sequence 173 genes in 2433 primary breast tumours that have copy number aberration (CNA), gene expression, and long-term clinical follow-up data. We identify 40 mutation-driver (Mut-driver) genes, and determine associations between mutations, driver CNA profiles, clinical-pathological parameters, and survival. We assess the clonal states of Mut-driver mutations, and estimate levels of intratumour heterogeneity using mutant allele fractions. Associations between PIK3CA mutations and reduced survival are identified in three subgroups of ER-positive cancer (defined by amplification of 17q23, 11q13-14 or 8q24). High levels of intratumour heterogeneity are in general associated with worse outcome, but highly aggressive tumours with 11q13-14 amplification have low levels of intratumour heterogeneity. These results emphasise the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies.

  Study EGAS00001001753

• Impact of DIS3 Aso on BCR repertoir in human buffy coat purified B-Cells

  The aim is to identify difference in the BCR of Aso DIS3 treated cells compared to Control Aso. Using extracted DNA from human B-cells

  Study EGAS50000001107

• Whole genome sequencing of multiple myeloma identifies novel structural and non-coding mutations.

  The coding region of the myeloma genome is well understood with key mutations having been identified. However, the non-coding regions of the myeloma genome are yet to be analyzed. Here we have performed whole genome sequencing of myeloma patient samples to identify structural abnormalities including chromothripsis and chromoplexy, as well as gene dysregulation through super-enhancer juxtaposition with key oncogenes. We have also identified non-coding region hotspots of mutation, especially in promoter regions, that affect gene expression.

  Study EGAS00001003164

• Sporadic Parathyroid Carcinoma

  This dataset is compromised of 5 sequencing experiments from a single patient with sporadic and recurring parathyroid carcinoma. The samples include whole genome sequence of the primary tumor, the first recurrent tumor and peripheral blood. Whole transcriptome sequence of the first and second recurrent tumors are also included.

  Dataset EGAD00001000370

• Investigating the impact of MBD4 on the mutability of the germline (2020-01-15)

  We will be testing the hypothesis that MBD4 PTV germline carriers also show an increased number of C toT germline mutations in their offspring. 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 2020-01-15.

  Dataset EGAD00001005788

• The UCSD / O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension

  Study Design: The UCSD / O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension contains N=797 participants. At the time of recruitment individuals ranged from 15-84 years of age and had varying ethnic backgrounds (Whites, African-Americans and Hispanics). The cohort was developed to study the genetic basis of autonomic dysfunction in human essential hypertension (reviewed in Zhang et al. Curr Hypertens Rep. 2011 13: 36-45. PMID: 21104344) and contains cross-sectionally collected phenotypes related to blood pressure regulation.&nbsp; Phenotypes: Phenotype data specifically focuses on the sympathetic branch of the autonomic system, which is a key regulator of blood pressure. Data includes circulating concentrations of the secretory "quantum" (catecholamines, neuropeptides, chromogranins) which influence vascular responses to sympatho-adrenal activation resulting in blood pressure. Other measures on the twins and a subset of family members include a standard urine panel with absolute concentrations of potassium, sodium, uric acid, phosphorous; DynaPulse acquired heart rate and blood pressure measures including systolic and diastolic blood pressure, mean arterial pressure, heart rate, Left Ventricular (LV) ejection time, LV contractility, cardiac output, stroke volume data including; and absolute concentrations of plasma aldosterone, endothelin, leptin, and insulin. Phenotype data is included for the 697 individuals sequenced here and 100 family members.&nbsp; Whole Genome Sequence Data Generation: Whole genome sequencing (20X coverage) was conducted on plasma-derived DNA. The WGS was generated using the Illumina HiSeq X Ten sequencing platform with variants called by Human Longevity, Inc (HLI; Ref 1). Preparation of sample libraries was conducted by mechanical shearing of gDNA (100-800 bp), isolation of DNA fragments 300-500bp in size, followed by library PCR amplification employing high-fidelity, low-bias PCR to amplify library fragments consisting of appropriate adapter sequences on both ends. BAM files were created by alignment of sequence reads to the reference genome (GRCh38) using iSAAC-01.14.02.06 (Python2.7). Note: The user may want to realign the sequence data and recall variants. In total, the WGS dataset contains 30 monozygotic twin pairs represented by one member of the twin pair, 133 monozygotic twin pairs with both individuals sequenced, 7 dizygotic twin pairs represented by one member of the twin pair, 67 dizygotic twin pairs with both individuals sequenced, 8 twin pairs with undetermined zygosity (both individuals sequenced) and 1 triplet with mother (all individuals sequenced). The dataset also contains sequences of 260 family members of twins including their mother, father, non-twin sibling, and offspring. Table 1 describes the composition of families ("sibling" refers to a non-twin sibling in the cohort). Note: We suggest users check gender and family relatedness. Table 1: Description of the families with sequence data &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp;Units with:Twin PairsTwin (no pairs)No twinSibshipsMother and Father511Mother only1222Father only113One or more siblings22133Mother and siblings132Father and siblings(s)211Offspring of twins11Non twin siblings2Sib with unknown relative1Only one member of8The UCSD/O'Connor "TSP" (Twin/Sibling/Pedigree) Resource in Hypertension is now being managed at the UCSD School of Medicine's Institute for Genomic Medicine (IGM). The TSP Resource has collected a wide range of information (phenotypic, genotypic, demographic, metabolomic) and reagents (blood, plasma, urine, DNA, human induced pluripotent stem cells). For additional information about the resource, including other data types available as well as references and links to data from studies with previous collaborators, please go to the resource website at IGM [http://igm.ucsd.edu/research/twins-resource.shtml] or contact Dr. Brinda Rana at UCSD [bkrana@ucsd.edu].&nbsp;

  Study phs002230

• Whole Genome Sequencing of 317 individuals from the Pacific region

  Although genetic studies of modern Oceanians have revealed varying levels of admixture with populations of East Asian ancestry, attributed to the Austronesian expansion, the early peopling history of Oceania remains poorly characterized. Additionally, it is currently unknown whether and how the settlement of the Pacific was accompanied by genetic adaptation to island environments, and if archaic introgression facilitated this process in Oceanians, who present the highest worldwide levels of combined Neanderthal and Denisovan ancestry. This study reports the first whole genome-based survey that addresses a wide range of questions related to the demographic and adaptive history of Pacific populations.

  Study EGAS00001004540

• Whole Genome Profiling to Detect Schizophrenia Methylation Markers

  Schizophrenia (SCZ) is a devastating psychiatric disorder. The aim of this study was to detect DNA methylation (5meC) profiles in whole blood associated with SCZ. The sample consisted of schizophrenia cases and controls selected from national population registers in Sweden. We employed MBD protein-based enrichment of the methylated DNA fraction, followed by single end sequencing (50 bp reads) on the SOLiD platform. To improve methylome-wide coverage we used an existing protocol variant, which increases the relative number of fragments from CpG poor regions. To analyze the data, we used an analysis pipeline described elsewhere7, that was designed specifically for MBD-seq and included alignment, quality control (QC) of reads and samples, coverage calculations for the 26,752,702 autosomal CpGs in the reference genome using a non-parametric estimate of the fragment size distribution, an in silico experiment to identify CpGs in loci with alignment problems, a 2-stage adaptive algorithm to combine data from correlated adjacent CpG sites in "blocks", principal component analysis (PCA), association testing, bioinformatics annotation and network analysis. After QC, 1459 subjects with on average 32.4 million high quality reads remained. Association testing was performed on 4.3 million high quality blocks after regressing out possible assay related technical artifacts, sex/age, and unmeasured confounders through the PCA components.

  Study phs000608

• Comprehensive Genomic Characterization of Refractory Multiple Myeloma Reveals a Complex Mutational and Structural Landscape Associated with Drug Resistance (H067)

  Outcome of patients with multiple myeloma (MM) refractory to immunomodulatory agents (IMiDs) and proteasome inhibitors (PIs) is still very poor. To elucidate the genetic landscape of relapsed/refractory MM (RRMM) we performed whole genome and transcriptome sequencing of 39 heavily pretreated RRMM patients with at least double refractoriness revealing complex structural changes and a high mutational load (H067/K08K). We found a median of 67 structural variants and 116 nonsynonymous exonic mutations per patient. Assessment of oncogenic drivers showed NRAS, BRAF, TP53, KRAS, SLC4A7, FAM46C, DIS3, RB1, KMT2C, MLLT4, EWSR1, HCFC2, and COPS3 as significantly mutated. We found multiple genomic regions with bi-allelic events affecting known tumor suppressor genes, most frequently TP53, RB1, and TRAF3. Supervised analysis of mutational signatures showed a major contribution of Cosmic signature 6 associated with deficiency in DNA mismatch repair and the ‘BRCAness’ signature which coincided with mutations in genes known to confer PARP inhibitor sensitivity. Recurrently mutated gene networks included genes with relevance for PI and IMiD activity, the latter including in particular members of the Cereblon and the COP9 signalosome complex. In conclusion, this comprehensive genomic characterization revealed a complex mutational and structural landscape in RRMM and highlights potential implications for therapeutic strategies.

  Study EGAS00001004363

• Epigenetic Profiling of Human Colorectal Cancer

  DNA methylation, together with chromatin modifications, constitute the epigenome that functions to regulate gene expression and genome integrity. DNA methylation alterations are ubiquitous in human cancers, as many genes acquire DNA methylation in a cancer-specific manner. DNA methylation at these sites in the genome of cancer cells not only serves as a marker for tumor identification, but together with gene mutation and gene expression data, can also be used to describe subsets of tumors of the same organ source. We have previously shown distinct human colorectal cancer subtypes based on DNA methylation differences. Correlating these DNA methylation differences with clinical co-variates will serve to further understand how these distinct subtypes are generated. We have collected 100 colorectal tumor tissues (for which clinical information is known) and have obtained (unprotected) genome-wide DNA methylation and chromatin modification information for each sample for the purposes of identifying and classifying unique tumor subtypes of colorectal cancers. In addition, we have determined mutations of key genes relevant to colorectal cancer as well as gene expression profiles. We will use the clinical data for each de-identified sample to correlate with the DNA methylation, mutation and gene expression information so as to understand the driving forces behind these distinct colorectal subtypes. We have selected the most promising tumors for whole-genome bisulfite sequencing using next-generation sequencing technology to obtain complete maps of colon cancer methylomes. Researchers will be unable to identify the subjects because the samples and associated information have been de-identified and anonymized by the tissue source site. In addition, upon receipt by the USC Epigenome Center, we have assigned new random identifiers for each sample. The data generated using these new codes are not traceable to the patient identity.

  Study phs000385

• DAC Portal documentation

  DAC Portal Welcome to the DAC Portal documentation! If you are involved in governance or legal aspects, technical or operational aspects, or serving as a data steward, this page will be helpful for you. By exploring these materials, you can define your own Data Access Committee (DAC) and policies, understand the minimal requirements for a DAC and a policy object, and comprehend how the EGA data access requests are managed. DAC Portal Index Setting up your account DACs and Policies Pending Request table Manage Data Requests History page Audit your DACs, policies, and datasets Deprecation User Preferences DAC API - A programmatic approach Setting up your account Register yourself as an EGA user. The Helpdesk team will validate your account (this could take up to 48 hours). After validation, you will receive an email with a link to verify your email - Make sure you click on the link to verify your account! If you don’t receive the email, please check your spam folder. Once your account is active you can login to the DAC Portal. We recommend you to check out the Take The Tour! DACs and Policies Create a DAC Click on Create a DAC Add the title and description to your DAC. Once ready, click on the ‘Create’ button. You will have to wait until the Helpdesk Team validates the creation of your DAC. Once approved by Helpdesk, your DAC will be assigned with a persistent identifier (EGAC). Edit a DAC Once your DAC is registered and approved, you can edit it and add contacts. Remember, you can add as many contacts as needed. And, you can also remove/add contacts anytime. To add a contact, you must write the username or email of a registered EGA user in the Members field. Once you have typed the whole username or email, a drop-down menu will appear where you can select the contact. Select a contact from the drop-down menu. Make sure you write the full username or email of the contact so it appears as an option. Make sure that you select one main contact. Set up the role you want to grant to the new contact of the DAC. We recommend you to check out the FAQ to learn more about the different roles! After adding all the necessary contacts and assigning roles, click on Update. This will send an email notification to the new DAC member, letting them know about the invitation to managing the DAC. Once they log into the DAC Portal, they will be able to either accept or turn down the invitation. Create a policy First, please note that all information registered in a policy metadata object will be publicly available on the EGA website. For each released dataset, all users will be able to read the policy under the “Data Access” tab. Select Create a Policy from the Policies tab. Select the DAC that you want your policy to depend on. Add the title and terms and conditions for accessing and using your data. If you already have an external website for data access requests, you can add the URL directly here (see example here). You can find a template of a Data Access Agreement (DAA) document in our Policy documentation page. The DAA template is provided for guidance only and should be adapted to suit your own purpose depending on the security policies, terms for publication or embargoes, and restrictions on data use or sharing. You can also add Data Use Ontologies (DUO) to your policy. These DUO codes are used to semantically tag the terms and conditions of using the data linked to the policy (example). For more information, you can refer to the Data Uso Ontology documentation. Once completed, make sure to click the Create button in order to register your policy. A persistent identifier (EGAP) will be assigned automatically. Edit a policy Please, note that you will not be able to edit the policy if it shows in orange. Meaning that you are a member of the DAC linked to that policy. Members don’t have edit rights. Only admins can edit objects. You can check your registered policies on My policies, available at the menu in the top-right corner. Select your policy. It will then display the information of that policy, allowing you to edit the information. Once you are done with the modifications, click Update. Pending Requests Table Table Settings Upon selecting a specific DAC, you will be presented with a customisable table showcasing all pending data access requests. This table allows you to tailor the displayed information according to your preferences by selecting desired columns. Available Columns (Displayed with the Eye Icon): Date: The date when the data access request was submitted. Full Name: Name and surname of the user submitting the request. Email: Email address associated with the user's request. Username: The username linked to the EGA account of the user submitting the request. Organisation: Affiliated organisation of the user submitting the request. Dataset: EGA accession ID for the requested EGA dataset. Dataset Title: Title of the requested dataset. DAC Comment: Space provided for internal comments related to the request. Expiration: Option to specify an expiration date for granted permissions. Check more information on the pending request table here! Table Filters By default, all data access requests are displayed. However, you have the option to apply filters to refine your view. Follow these steps to apply filters: Click on the More button. This action will reveal the different columns available for applying filters. As you select columns, the checked fields will be displayed at the top of the request table. Choose the specific values within the selected columns that you want to filter for. Click the Search button to apply the selected filters. Do you find yourself frequently applying the same filters? You can save multiple combinations of filters for easy access at any time! Here's how: Click the Save button. Provide a descriptive name for the filter combination. Click Save to confirm. To load saved filters, simply select the saved filter from the dropdown menu to apply it automatically. Check more information on filters here! Advanced Search For users requiring more granular control over their data access requests, the DAC Portal offers an Advanced Search feature using JIRA Query Language (JQL). With JQL, you can craft precise and complex queries to filter and retrieve specific data access requests based on various criteria such as date, user details, dataset attributes, and more. Using JQL's flexibility, you can create custom queries to meet your specific needs, allowing for advanced filtering options beyond the standard filters provided. You can find the Advanced Search feature following these steps: Click the … button Select Advanced To view the allowed fields for filtering and explore all available options, simply click on the info icon. Once you have written the filtering values, click the Search button to apply. Check more information on filters here! Manage Data Requests Upon logging into the DAC Portal, you'll notice a sand clock icon next to the DAC ID, indicating the number of pending requests. Click on the DAC to review these requests. Accept requests Click on the right side of the toggle button to grant access to the user. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with granting permissions. Deny requests Click on the left side of the toggle button to deny access to the user. Provide a reason for the denial. Note that the user will receive an email with this reason. Click on the Done button. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with denying permissions. Tips! Apply a filter to view all requests to be managed at once. Use the toggle in the row with column names to grant or deny permissions for multiple requests simultaneously. You can grant and deny permissions in the same action, simplifying the process. The confirmation box will provide a summary of all actions, including grants, denials, DAC comments, and expiration dates. History Page The History page serves as a dedicated space to view information regarding all requests managed by all DAC members. Here, you can review active permissions and revoke them as needed. Go to the History page by clicking on the "HISTORY" button from a DAC page in the DAC Portal. Here are the different row types you may find: Current permissions: row in green with a toggle button to revoke permissions on the right. Approved requests: row in green, with no toggle button. Request denied: row in red with “request denied” on the right. Permission revoked: row in red with “permission revoked” on the right. Distinctions to Note! Between Request Denied and Permission Revoked: Request Denied: Refers to requests that were rejected from the outset, indicating that access to the dataset was never granted. Permission Revoked: Indicates that permissions were previously granted but have since been revoked. Users with permissions revoked have previously accessed the dataset. Between Approved Request and Current Permissions: Approved Request: Represents an entry when a data access request has been approved in the past. Current Permissions: Denotes ongoing permissions where a user has present access to the dataset. An approved request may now appear as Permission Revoked in the present. By observing these different rows, users can gain insight into the complete history of a user's interactions and permissions regarding a dataset over time. To revoke access to a specific user for a dataset, follow these steps: Go to History page Look for the row with the specific permissions. You can use the filters! Click on the toggle button to revoke access. Add a denial reason. Bear in mind that the requester will receive the denial reason! Click on the Apply button. Check more information on the Hisotry page here! Audit your metadata objects In the DAC Portal, you can efficiently manage and audit various metadata objects pertinent to your role as a Data Controller. Upon accessing the DAC Portal, you will encounter three primary tabs on the homepage: DAC: Contains information about Data Access Committees (DACs). Policies: Provides insights into linked policies. Datasets: Displays datasets and relevant details. Within each tab, you'll find a comprehensive list of the objects you manage, these being grouped by type (DAC, Policies, Datasets), as well as by your role (member/admin). Whilst the lists give you a quick look, to check how things are connected, we've added a table at the bottom DACs and policies. DACs Let’s check which policies are linked to a specific DAC: Go to "My DACs." Select a DAC. Click on "EDIT" to see more details. You are now on this page: Scroll down to see the linked policies. Click on “List of linked policies of this DAC” and you will see a list of all policies linked to your selected DAC. Policies Do you want to view a list of datasets connected to a particular policy? Follow the same steps mentioned earlier, but head to the policy tab this time. In the policy tab, you'll find a list of all your policies. Here, you may notice two different icons next to the policy ID (EGAP): DAC Icon (): This represents the DAC. Hover your mouse over the icon to see the DAC ID. Dataset icon (): This indicates datasets falling under that policy. The number next to the icon tells you how many datasets are linked to the policy. For example, if you see "2" next to the icon, it means there are two datasets linked to that policy. If you want to check the linked datasets and their relevant information, simply click on a specific policy. You'll then find the "List of linked datasets of this policy" at the bottom of the page. Datasets Finally, in the dataset tab, by default you will see a list of all the datasets you can manage with all your DACs and policies. Yet, we've included two handy ways to organise them: DAC vs. policy: You can group by datasets, either by DAC or policy. Released vs. unreleased: You can sort out datasets based on their release status. Feel free to experiment with both options! For instance, if you want to see which DACs have unreleased datasets, simply select DAC and unreleased, and you'll get the details you need! Deprecation Do you have a bunch of metadata objects like DACs and policies that you don’t need anymore? This section shows you how to get rid of them! But what does "deprecation" mean for EGA? It's basically changing the status of a metadata object to "deprecated," which means we won't be using it in the future. In simple terms, it's like saying these objects are no longer useful. However, because we believe in making metadata FAIR, once an object has a persistent identifier, we can't just delete it. So, instead of deleting, we deprecate it. Here's a helpful tip! If you want to make a metadata object disappear from the DAC Portal, deprecate it. You won’t see it in the portal anymore! Let’s say you want to deprecate a DAC. Let’s do it! Go to "My DACs." Select a DAC. Click "EDIT" to see more details. You are now in this page: Click on the Deprecate button It will then appear a message. There are two options here: Your DAC is not linked to any policy, hence it’s ready to be deprecated. Click on “Yes. Confirm” to deprecate your DAC object! Your DAC is linked to at least one policy, and you need to either: Deprecate the linked policy first, or Link the policy to a different DAC Now, let’s say you don’t want to get rid of the policy altogether, but you want to change the DAC it’s linked to. Here's how: Go to the policy tab. Find the policy you want to change (for example, EGAP50000000019). Choose a new DAC to link it to. Click on Update. See the Edit Policy section for more details. After ensuring that the DAC we want to deprecate isn’t linked to any policy, return to the "My DACs" section and follow the steps outlined previously. This will lead you to a confirmation message. You can only deprecate DACs and Policies. To deprecate a dataset, please contact our Helpdesk team. Check more information on how deprecation works here! User Preferences We have implemented email notifications in the DAC Portal. Here’s the complete list: DACs: Pending requests Approved by Helpdesk Rejected by Helpdesk DAC Invitation Requesters: Data access request approved Data access request denied Permissions revoked Upcoming expiration date As a DAC member, you will be able to decide whether you want to receive the DAC notifications or not. For that, go to the top-right corner menu, select User Preference. You will be able to decide whether you want to receive notifications for: Approved by Helpdesk Rejected by Helpdesk DAC Invitation For pending requests, you will be able to select how often do you want to receive the notification: Daily Weekly Fortnightly As a DAC member, you are responsible for managing data access requests. Consequently, you will receive notifications for pending requests. If you prefer not to manage these requests, please arrange to be removed as a contact for your DAC. Here's a tip! Do you have a pending request that you don’t want to receive a notification? Add a DAC comment! The EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! DAC API - A programmatic approach In addition to the new DAC Portal, we are excited to announce the release of the DAC API. This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can click the button below. Check out the DAC API specification!

  Documentation access/data-access-committee/dac-portal

• Multi-Omics Study of Lung Cancer in Smokers From EAGLE

  EAGLE (Environment And Genetics in Lung cancer Etiology) is a population-based case-control study examining the full spectrum of lung cancer etiology from smoking initiation, smoking dependency to lung cancer development and outcome. It combines a traditional molecular epidemiology design with more integrative approaches by examining epidemiological, molecular, and clinical data together. To comprehensively investigate the effect of tobacco smoking behaviors on genomic or epigenomic alterations, we performed a multi-omics study including whole-genomic, transcriptomic, and epigenomic profiles in a total of 221 individuals from the EAGLE study.

  Study phs002992

• Genetic Neuroscience: How Human Genes and Alleles Shape Neuronal Phenotypes

  The goal of this collaborative, interdisciplinary project is to develop powerful, generalizable approaches for discovering how risk variants for psychiatric disorders shape neurobiological processes at multiple levels of analysis, and to identify the processes whose dysregulation underlies disease.Induced pluripotent stem cells (iPSCs) were used towards the development of these new experimental and inferential systems bridging gaps between human genetics and experimental biology. The largest publicly available collection of iPSCs (2607 lines) has been generated from 2184 donors by the California Institute for Regenerative Medicine (CIRM). To expand our donor collection, an additional 44 iPSC donors from the McLean_Levy cohort were identified. We wish to share the available SNP data for 2167 CIRM lines and whole genome sequence data generated at the Broad Institute for 473 of the CIRM and 44 McLean_Levy iPSC donors. These data can be used to identify (for experiments) lines with specific genotypes of interest and lines from donors with high or low polygenic risk scores for phenotypes of interest. The data can also be used to identify acquired mutations in the iPSC lines. The CIRM iPSC lines are available through Fujifilm Cellular Dynamics iPSC Repository (https://www.fujifilmcdi.com/cirm-ipsc-products/). The McLean_Levy lines are available through the NIMH Repository &#38; Genomics Resource (https://www.nimhgenetics.org/).Additional project data registered with the study includes data from an iPSC line derived from an SMA patient (n=1), as well as single-cell RNA sequence data and supplemental processed genomic datasets in support of project publications.Molecular DatasetsSingle-cell RNA-seq: 10X Genomics, Illumina NovaSeqSupplemental "cell village" pooled genomic sequence data: Illumina NextSeqWhole Genome Genotyping: Infinium Global Screening Array-24 Kit, Illumina HumanCore chipWhole Genome Sequencing: Illumina NovaSeq

  Study phs002032

• Genetics of Disorders Affecting Tooth Structure, Number, Morphology and Eruption

  The long-term objective of this research project is to discover the complete spectrum of genes that contribute to the etiologies of genetic disorders of dentition. Inherited tooth defects can be isolated (the only symptom) or syndromic (having additional symptoms), and can be caused by mutations in many different genes. Clinically, it can be difficult to distinguish among the diverse forms. Making an accurate diagnosis would be greatly improved if reliable tests could identify the specific genetic defect that causes the disease in each case. Current technology can identify the numerous sequence variations throughout a patient's exome, but the disease-causing variation among them cannot be identified unless it is already on the list of genes that potentially cause the disease. A diagnosis based upon the genetic defect that causes the disorder distinguishes between isolated and syndromic tooth defects. A precise diagnosis permits formulation of a more accurate prognosis, which informs treatment decisions. The benefits of accomplishing our aims are to 1) enable genetic testing to achieve a precise and accurate diagnosis, and thereby optimize treatment, and 2) improve our understanding of normal and pathological tooth formation, leading to future improvements in treatment and eventually cures. Our short-term objectives are to 1) recruit kindreds with inherited disorders affecting their dentition, characterize their dental phenotype (and non-dental phenotypes when applicable) and the distribution of the disorder throughout the family, and 2) determine the genetic etiology of their disorders.

  Study phs001491

• Carolina Breast Cancer Study (CBCS)

  The Carolina Breast Cancer Study (CBCS), phase III, is a population-based study aiming to understand the social and molecular correlates of breast cancer outcomes, particularly among Black and young women. CBCS recruited first primary breast cancer cases from 44 North Carolina counties between 2008-2013. All cases were between age 20 and 74 and self-identified as female. Black women and young women were systematically oversampled by randomized recruitment such that the study includes approximately 50% Black women and approximately 50% women diagnosed before age 50. A total of 2,998 participants were enrolled. In the ten years following diagnosis, women completed surveys approximately every 1-2 years and diagnoses of subsequent distant local recurrence and second primary tumors were ascertained via linked medical records. We identified records of women who developed secondary breast tumors (including second primary tumors, contralateral breast cancers, and locoregional recurrences), and these participants were oversampled for targeted DNA sequencing using the UNCseq panel (~1200 genes).CBCS germline pathogenic mutations cannot be investigated because participants were consented between 2008 and 2013 with specific language prohibiting this. However, germline data can be used to call somatic mutations or to standardize somatic genomic data.For sharing of study data not included here, please visit unclineberger.org for instructions on submitting a data use agreement.

  Study phs003725

• Epigenetic characterization of glioblastoma stem cells

  Chromatin accessibility discriminates stem from mature cell populations, enabling the identification of primitive stem-like cells in primary tumors, such as glioblastoma (GBM) where self-renewing cells driving cancer progression and recurrence are prime targets for therapeutic intervention. We show, using single-cell chromatin accessibility, that primary human GBMs harbor a heterogeneous self-renewing population whose diversity is captured in patient-derived glioblastoma stem cells (GSCs). In-depth characterization of chromatin accessibility in GSCs identifies three GSC states: Reactive, Constructive, and Invasive, each governed by uniquely essential transcription factors and present within GBMs in varying proportions. Orthotopic xenografts reveal that GSC states associate with survival, and identify an invasive GSC signature predictive of low patient survival, in line with the higher invasive properties of Invasive state GSCs compared to Reactive and Constructive GSCs as shown by in vitro and in vivo assays. Our chromatin-driven characterization of GSC states improves prognostic precision and identifies dependencies to guide combination therapies.

  Study EGAS50000001804

• Induction Failure in Childhood and Young Adult T-cell Acute Lymphoblastic Leukemia

  We carried out WGS and RNAseq on a cohort of 48 children and young adults with induction failure in T-cell Acute Lymphoblastic Leukemia (T-ALL) to identify genomic drivers of treatment resistance. The study includes WGS for 33 tumour/normal pairs and 15 tumour-only samples. In addition, there is RNAseq data for 37 cases.

  Dataset EGAD00001009058

• Genomics of Substance Use Disorders in Latin American Populations

  This is a subsample of the National Survey of Drug, Alcohol, and Tobacco Use, administered in 2016 between August and October to participants aged 12-65 in urban and rural Mexican households, named Mexican Genomic Database for Addiction Research (MxGDAR). The objective of the survey was to evaluate the patterns of use of different psychoactive substances and mental health problems in Mexico. The sample universe was made up of primary sampling units (PSUs) that were the sum of basic statistical geographic areas, stratified by state and urban-rural communities. An adult aged 18-65 was chosen randomly from each household, and an adolescent aged 12-17 was also chosen randomly from the household which has at least one member under 18. The second administration of the survey included a subsample of 13,130 respondents who agreed to give a saliva sample for DNA analysis, to be used in analyzing the relationship of mental health, addiction, and genetics. This sample was weighted according to selection probability to be representative on the national level. Mental health symptomatology for these individuals was evaluated using the Diagnostic Interview for Psychosis and Affective Disorders (DI-PAD) using the operational criteria for psychotic disorders (OPCRIT v.4.0), administered by interviewers trained in its use. It includes the evaluation of symptomatology of psychosis, depression, anxiety, obsession/compulsion, mania/hypomania, and post-traumatic stress. The study seeks to replicate genetic associations with substance use (LINC01622), psychiatric disorders (PTPRM), or comorbidity between both (MGMT) reported in following paper: https://pubmed.ncbi.nlm.nih.gov/33762635/. Funding for genotyping was provided by the National Institute on Drug Abuse (NIDA), one of the National Institutes of Health (NIH).

  Study phs003558

• Multi-omics profiling of paired primary and recurrent glioblastoma patient tissues

  Despite maximal therapy with surgery, chemotherapy and radiotherapy, glioblastoma multiforme (GBM) patients have a median survival of only 15 months. Almost all patients inevitably experience symptomatic tumor recurrence. A hallmark of this tumor type is the large heterogeneity between patients and within tumors itself which relate to failure of standardized tumor treatment. In this study, tissue samples of paired primary and recurrent GBM tumors were investigated to identify individual factors related to tumor progression.

  Study EGAS00001004345

• Integration of genomics and metabolomics in acute myeloid leukemia

  Although targeting of cell metabolism is a promising therapeutic strategy in acute myeloid leukemia (AML), metabolic dependencies are largely unexplored. We aimed to classify AML patients based on their metabolic landscape and map connections between metabolic and genomic profiles. The intracellular metabolome distinguished three AML clusters, correlating with distinct genomic profiles: NPM1-mutated(mut), chromatin/spliceosome-mut and TP53-mut/aneuploid AML that were confirmed by biofluid analysis.

  Study EGAS00001005422

• Loss of SDHB promotes dysregulated iron homeostasis, oxidative stress and sensitivity to ascorbate

  Succinate dehydrogenase is a key enzyme in the tricarboxylic acid cycle and the electron transport chain. All four subunits of succinate dehydrogenase are tumor suppressor genes predisposing to paraganglioma, but only mutations in the SDHB subunit are associated with increased risk of metastasis. Here we generated an Sdhd knockout chromaffin cell line and compared it to Sdhb-deficient cells. Both cell types exhibited similar SDH loss of function, metabolic adaptation, and succinate accumulation. In contrast, Sdhb-/- cells showed hallmarks of mesenchymal transition associated with increased DNA hypermethylation and a stronger pseudo-hypoxic phenotype compared to Sdhd-/- cells. Loss of SDHB specifically led to increased oxidative stress associated with dysregulated iron and copper homeostasis in the absence of NRF2 activation. High-dose ascorbate exacerbated the increase in mitochondrial reactive oxygen species, leading to cell death in Sdhb-/- cells. These data establish a mechanism linking oxidative stress to iron homeostasis that specifically occurs in SDHB deficient cells and may promote metastasis. They also highlight high-dose ascorbate as a promising therapeutic strategy for SDHB-related cancers.

  Study EGAS00001005279

• Long-read-transcriptome-sequencing of CLL and MDS patients uncovers common molecular effects of SF3B1 mutations

  Mutations in SF3B1 occur frequently in patients with chronic lymphocytic leukemia (CLL) and myelodysplastic syndromes (MDS), and a full-length transcriptome approach can expand our current knowledge on SF3B1 mutation effects on RNA splicing. We applied long-read-transcriptome-sequencing (LRTS) to 44 MDS and CLL patients with and without SF3B1 mutations and found a large fraction (>60%) of novel isoforms. Furthermore, we revealed that mutation effects on alternative splicing were largely common in both cancer types and specifically altered the usage of introns as well as 3’-splice-sites. We combined the LRTS with genome-wide SF3B1-RNA binding maps and show multimodal binding at 3’-splice-sites highlighting a window of 12-21nt upstream of the canonical 3’-splice-site in which a dynamic switch in splice site usage is observable in patients carrying SF3B1 mutations. Our work presents the hitherto most complete LRTS study in CLL and MDS and provides a resource for further research on aberrant splicing in cancer.

  Study EGAS50000000053

• T cell responses of ALS patients

  In this project, we aimed to understand how T cell responses contribute to the disease progression of amyotrophic lateral sclerosis (ALS). The present data is on single-cell sequencing isolated from human cerebrospinal fluid (CSF) cells from both ALS patients (n=5) and controls (n=4). This analysis was conducted as part of a bigger project which is summarized in the section below. We used flow cytometry to define T cell subsets and phenotypes in blood and CSF samples collected at the time of diagnosis on a cohort of 89 newly diagnosed ALS patients in Stockholm, Sweden. High frequency of CD4+FOXP3- effector T cells in blood and CSF was associated with poor survival whereas high frequency of activated regulatory T (Treg) cells and high ratio between activated and resting Treg cells in blood was associated with better survival. T cell profiles also predicted disease progression rate. On an independent cohort of cases and controls, we used single cell transcriptomics data to demonstrate that ALS patients had altered T cell gene expression patterns and clonally expanded CD4+ and CD8+ T cells in CSF. In summary, T cell responses contribute to disease progression of ALS, supporting modulation of adaptive immunity as a viable therapeutic option.

  Study EGAS00001006675

• Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study

  Background: Follicular lymphoma (FL) is an indolent, yet incurable B-cell malignancy. A subset of patients experience increased mortality rate driven by two distinct clinical end points: histological transformation and early progression after immuno-chemotherapy. The nature of tumor clonal dynamics leading to these clinical endpoints is poorly understood and previously determined genetic alterations do not explain the majority of transformed cases or accurately predict early progressive disease. We contend that detailed knowledge of the expansion patterns of specific cell populations plus their associated mutations would provide insight into therapeutic strategies and disease biology over the timecourse of FL clinical histories. Methods and Findings: Using a combination of whole genome sequencing, targeted deep sequencing and digital droplet PCR on matched diagnostic and relapse specimens, we deciphered the constituent clonal populations in n=15 transformation patients and n=6 progressors, and measured their change in abundance over time. We observed widely divergent patterns of clonal dynamics in transformed cases relative to progressed cases. Transformation specimens were generally composed of clones that were rare or absent in diagnostic specimens, consistent with dramatic clonal expansions that came to dominate the transformation specimen. This pattern was independent of time to transformation and treatment modality. By contrast, progression specimens were composed of clones that were already present in the diagnostic specimens and exhibited only moderate clonal dynamics, even in the presence of immuno-chemotherapy. Analysis of somatic mutations impacting 94 genes was undertaken in a validation cohort consisting of 395 samples from 277 patients in order to decipher disrupted biology in the two clinical endpoints. We found 12 genes were more commonly mutated in transformed samples than in preceding FL, including TP53, B2M, CCND3, GNA13, S1PR2 and P2RY8. Moreover, 10 genes were more commonly mutated in diagnostic specimens of early progressors including TP53, BTG1, MKI67 and XBP1. Conclusions: Our results illuminate contrasting modes of evolution shaping the clinical histories of transformation and progression. They have implication for interpretation of evolutionary dynamics in the context of treatment-induced selective pressures, and indicate that transformation and progression will require different clinical management strategies.

  Study EGAS00001001709

• Single Cell RNASeq for ARMS tumors

  6 samples from 3 mice related to Alveolar Rhabdomysarcoma. In this study, we employ scRNA-seq to analyze ARMS tumors from a conditional mouse model of ARMS. The conditional knock-in mouse model of ARMS, in which the Pax3-Foxo1 allele is activated in the skeletal muscle cell lineage via Myf6Cre (Myf6CrePax3P3Fm/P3FmTrp53F2-10/F2-10; referred to hereafter as GEMM-ARMS) has been described previously23,24. These mice also carry Cre-activated reporters, eYFP to label Pax3::Foxo1-expressing cells and dsRED2 to labels Myh2-expressing cells. Some tumors are derived from GEMM-ARMS mice, and some are allografts of GEMM-ARMS tumors into immunodeficient mice

  Dataset EGAD50000002241

• Prime editing for functional repair in patient-derived disease models

  Prime editing is a novel genome editing technology using fusion proteins of Cas9-nickase and reverse transcriptase, that holds promise to correct a wide variety of genetic defects. We succeeded in efficient prime editing and functional recovery of disease-causing mutations in patient-derived liver and intestinal stem cell organoids. Whole genome sequencing of did not detect off-target mutations or a mutational signature induced by prime editing.

  Study EGAS00001004611

• Germline Genomic Analyses of Breast Cancer in Latinas

  In this case-control study of breast cancer among Hispanic/Latina (H/L) women, the goals were to identify breast cancer susceptibility genes and genetic variants for risk of developing breast cancer in H/L women. There were two phases with whole exome sequencing (WES) done in a discovery phase and targeted sequencing of candidate genes in the replication phase. The candidate genes selected for replication came from the first phase and from genes known to affect breast cancer risk in prior studies. Cases and controls were drawn from several studies. Breast cancer cases for discovery phase included women from the City of Hope (COH) Clinical Cancer Genomics Community Research Network (CCGCRN), UCSF Cancer Genetics Clinic and USC Cancer Genetics clinic. Controls for discovery phase included women who did not have breast and were recruited through City of Hope community fairs. A separate group of controls included women from the California Teachers Study. Additional controls for discovery were obtained from WES already generated by the Multi-ethnic cohort (MEC) study. The discovery/WES results of known breast cancer genes were published (PMID 31206626). In the replication phase, we included cases and controls from the Cancer de Mama (CAMA) study which is a case-control study of breast cancer in Mexico, MEC for those not included in the discovery dataset, the San Francisco Bay Area Cancer study (phs000912), the Northern California Breast Cancer Registry, and the California Pacific Medical Center Research Institute Women's Cohort (phs000395). Cases from the PATHWAYS study who were recruited from Northern California Kaiser Permanente were also included. Results from the combined discovery and replication analyses are reported in PMID 36747679.

  Study phs003144

• Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) - OncoArray Genotypes

  The data come from 40 studies participating in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). CIMBA recruits individuals with pathogenic mutations in BRCA1 or BRCA2. The majority of carriers were recruited through cancer genetics clinics offering genetic testing, and were enrolled into national or regional studies. The remainder were identified by population-based sampling of cases, or community recruitment. Eligibility to participate is restricted to carriers of pathogenic BRCA1/2 mutations who were 18 years or older at recruitment. Information collected included amongst other variables: age at recruitment; ages at breast and ovarian cancer diagnosis; and estrogen receptor (ER) status. Samples were genotyped using the Illumina OncoArray beadchip 500K SNP custom array. Details of the genotyping process and sample selection are included in Phelan et al, Identification of twelve new susceptibility loci for different histotypes of epithelial ovarian cancer, Nat Genet. 2017 May;49(5):680-691 (PMID:28346442), and Milne et al, Identification of ten variants associated with risk of estrogen receptor negative breast cancer, Nat Genet (in press).

  Study phs001321

• Single-cell RNA-seq of cervix and placenta

  Placental trophoblasts have been detected in cervical smears early in gestation, creating opportunities for non-invasive prenatal diagnosis. However, trophoblast isolation is limited by the lack of a cell catalogue and molecular profile of cervical smears. To establish an atlas and to explore the potential of single-cell RNA-sequencing to detect cervical trophoblasts, 10,539 single-cell transcriptomes from 12 non-invasive exocervical smears from pregnant women were profiled. In addition, we characterized 34,565 cells from six placental biopsies. We uncovered a novel extravillous trophoblast cell subtype characterized by epithelial marker genes and reduced HLA-G expression. Integration of both cell atlases demonstrated surprisingly similar expression profiles between maternal epithelial cells and placental extravillous trophoblasts, indicating that these trophoblasts retained epithelial properties without an invasive mesenchymal phenotype. Additionally, differential expression analysis identified novel markers discriminating cervical and placental cell types. Those analyses may contribute to trophoblast discovery and isolation from cervical smears.

  Study EGAS00001007044

• Genomic abnormalities of TP53 define distinct risk groups of paediatric B-cell non-Hodgkin lymphoma

  TP53 alterations are associated with adverse outcome in many malignancies; however, whilst common in paediatric B-NHL, their utility as a risk classifier in this setting is unknown. We evaluated the clinical significance of TP53 abnormalities (mutations, deletion and/or copy number neutral loss of heterozygosity) in a large UK paediatric B-NHL cohort (n=95) and determined their impact on survival.

  Study EGAS00001005617

• GOSH_Childhood_Leukemia_Behjati_WellcomeCore_RNA

  Paediatric single-cell archival project This project is taking sequential samples of children with B-cell acute lymphoblastic leukaemia (B-ALL) treated at Great Ormond Street Hospital (GOSH) between 2011 and the present day. Patients selected, are those that have done badly (e.g. had to escalate treatment, relapsed or died) despite having apparently ""good"" or ""intermediate"" risk cytogenetics, and often also had immunotherapy (e.g., the bi-specific T-cell engager blinatumomab) because of this. Using samples from key treatment-points, we hope to better characterise their disease and treatment response, to re-define understandings of risk for patients who did unexpectedly poorly. Additionally, we hope to define the disease/immunological factors that determine response to increasingly used immunotherapies within the field of paediatric B-ALL. Each of the samples will be viably frozen bone marrow-derived mononuclear cells. They will come in Eppendorf's, frozen and de-anonymised, from GOSH. We plan to primarily do single cell analysis (GEX, BCR +/-TCR), and then tumour-only WGS and bulk-RNA expression on left-over

  Study EGAS00001007616

• Genetic Legacy of Punan Hunter-Gatherer Groups in Indonesian Borneo

  Punan Batu (the “Cave Punan”), the last living nomadic hunter-gatherer (HG) group who still literally live under karst rock shelters in Borneo, is the least-known hunter-gatherer society in Asia. To provide insights on the origin and adaptation of the Cave Punan, here we present the autosomal genome-wide SNPs study of the Cave Punan, including other Punan groups who speak different language from the Cave Punan, which are transitioning into a more sedentary lifestyle.

  Study EGAS00001004471

• Multimodal Analysis for Human Ex Vivo Studies Shows Extensive Molecular Changes from Delays in Blood Processing

  Multi-omic profiling of human peripheral blood is increasingly utilized to identify biomarkers and pathophysiologic mechanisms of disease. The importance of these platforms in clinical and translational studies led us to investigate the impact of delayed blood processing on the numbers and state of peripheral blood mononuclear cells (PBMC) and on the plasma proteome. Similar to previous studies, we show minimal effects of delayed processing on the numbers and general phenotype of PBMCs up to 18 hours. In contrast, profound changes in the single-cell transcriptome and composition of the plasma proteome become evident as early as 6 hours after blood draw. These reflect patterns of cellular activation across diverse cell types that lead to progressive distancing of the gene expression state and plasma proteome from native in vivo biology. Differences accumulating during an overnight rest (18 hours) could confound relevant biologic variance related to many underlying disease states.

  Study phs002280

• pediatric AML genomic sequences

  This dataset contains whole sequencing data from 30 patients with pediatric AML. For each patient, there is one dataset derived from tumor cells and one dataset derived from a matched non-malignant control.

  Dataset EGAD50000001572

• Comparison of structural variations from 10X Genomics linked-reads and conventional Illumina short-reads sequencing

  Structural variations (SVs) are large genomic rearrangements that can drive many diseases. Conventional short-reads whole genome sequencing (cWGS) allows their identification with base-pair resolution, but suffers from high false discovery rate. cWGS taps in short-range information from short-reads while linked-reads sequencing (10XWGS) utilizes long-range information. 10XWGS allows linkage of short-reads originating from the same large DNA molecule with a unique barcode captured in a gel bead in emulsion. This mitigates alignment-based artefacts from cWGS especially in repetitive regions. However, the false discovery rate of this technology is unclear. In this study, we performed a comprehensive analysis of different type and size of SVs predicted from these two technologies. The SVs common between both technologies were found to be highly specific by PCR and Sanger sequencing while validation rate dropped for uncommon events. Further, we propose a novel enrichment approach for filtering out false positive calls from both the technologies independently. To this end, we trained a machine learning model for respective technologies and used it to characterise SVs from MCF7 cell line and a primary breast cancer tumor with high precision. This approach would be valuable in understanding true mechanisms driven by SVs in various diseases.

  Study EGAS00001004093

• Kids First: Pediatric Research Project on the Genomic Analysis of Congenital Diaphragmatic Hernia

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). Both, childhood cancers and structural birth defects are critical and costly conditions associated with substantial morbidity and mortality. Elucidating the underlying genetic etiology of these diseases has the potential to profoundly improve preventative measures, diagnostics, and therapeutic interventions. WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. In collaboration with the University of Utah, DNA from four families were selected for high-depth WGS (60X) including diaphragm and skin tissue to identify mosaicism. In collaboration with the Broad Institute, DNA from four families underwent linked long read sequencing using 10X Genomics technology. Probands with congenital diaphragmatic hernia/defects and both biological parents enrolled as part of the DHREAMS study.

  Study phs001110

• Genetic and epigenetic characterization of adenoid cystic carcinoma

  Whole genome sequences of ACC primagrafts, Histone modification maps and transcription factor binding maps for ACC primagrafts and primary tumors. Processed ChIP-seq data is available on GEO under accession number GSE76465.

  Dataset EGAD00001001662

• Human induced pluripotent stem cells display a similar mutation burden as embryonic pluripotent cells in vivo

  Induced pluripotent stem cells (iPSCs) hold great promise for regenerative medicine, but genetic instability is a major concern. Embryonic pluripotent cells also accumulate mutations during early development, but how this relates to the mutation burden in iPSCs remains unknown. Here, we directly compared the mutation burden of cultured iPSCs with their isogenic embryonic cells during human embryogenesis. We generated developmental lineage trees of human fetuses by phylogenetic inference from somatic mutations in the genomes of multiple stem cells, which were derived from different germ layers. Using this approach, we characterized the mutations acquired pre-gastrulation and found a rate of 1.65 mutations per cell division. When cultured in hypoxic conditions, iPSCs generated from fetal stem cells of the assessed fetuses displayed a similar mutation rate and spectrum. Our results show that iPSCs maintain a genomic integrity during culture at a similar degree as their pluripotent counterparts do in vivo.

  Study EGAS00001005939

• Single-cell transcriptomic data from tumor samples

  Extramedullary multiple myeloma is an aggressive form of multiple myeloma where the myeloma cells escape BM microenvironment and infiltrate distant tissues.We analyse using single cell techniques, the composition and functional state of major immune cells in EMM tumor microenvironment, T and NK cells. This dataset contains the singlecell RNAseq data used in the publication. It includes scRNAseq data from tumor samples across extramedullary multiple myeloma soft tissue (EMM) (n=5; 3 additional samples in the study are under accession numbers mentioned in the publication), EMM bone marrow (EMM_BM) (n=5), and relapsed/refractory multiple myeloma (RRMM_BM) BM (n=6).

  Study EGAS50000001038

• Integrated Transcriptomic and Regulatory RNA Profiling Reflects Complex Pathophysiology and Uncovers a Conserved Gene Signature in End Stage Heart Failure RNA-Seq data

  Heart failure (HF) is a complex syndrome. Despite availability of multiple treatment options, the mortality remains high and the quality of life poor. Better understanding of the underlying pathophysiological processes can lead to development of novel therapies. Multiple comparative transcriptomics studies, which revealed gene level changes in the key pathophysiological pathways in failing hearts, point towards heterogeneity from interplay of disease stage, etiologies and ethnicity. Transcriptomic characterization of HF in patients from different ethnicities can potentially help in understanding the heterogeneity imparted by various factors and the core elements in heart failure.

  Study EGAS50000000810

• A multicenter study of susceptibility genes to type 1 diabetes

  The first genome-wide association study of fulminant type 1 diabetes mellitus was performed in Japanese individuals. As previously reported using a candidate gene approach, a strong association was observed with multiple SNPs in the HLA region, and the strongest association was seen for rs9268853 in the class II DR region (P=1.56 x 10-23, odds ratio [OR] 3.18). In addition, rs11170445 in CSAD/lnc-ITGB7-1 on chromosome 12q13.13 showed an association at a genome-wide significance level (P=7.58 x 10-9, OR 1.96). Fine mapping of the region revealed that rs3782151 in CSAD/lnc-ITGB7-1 showed the lowest P value (P=4.60 x 10-9, OR 1.97 [95% CI 1.57-2.48]). The risk allele of rs3782151 is a cis-expression quantitative trait locus (eQTL) for ITGB7 that significantly increases the expression of this gene. CSAD/lnc-ITGB7-1 was strongly associated with the susceptibility to fulminant, but not classical autoimmune, type 1 diabetes, implicating this locus in the distinct phenotype of fulminant type 1 diabetes.

  Study JGAS000144

• Deep whole genome sequencing identifies recurrent genomic alterations in breast cancer cell lines and patient derived xenograft models

  Breast cancer cell lines (BCCLs) and patient-derived xenografts (PDX) are the most frequently used models in breast cancer research. Despite their widespread usage, genome sequencing of these models is incomplete, with previous studies only focusing on targeted gene panels, whole exome or shallow whole genome sequencing. Here we describe deep whole genome sequencing (WGS) of commonly used BCCL and PDX models using the Illumina X10 platform with an average ~ 60x coverage.

  Study EGAS00001006285

• Contribution of specific cell types to the development of Barrett’s esophagus and carcinoma via germline genetic risk

  This study was designed to elucidate how individual cell types in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) contribute to disease development via germline genetic risk. We performed single cell RNA-sequencing (scRNA-seq) of BE, EAC and paired normal esophagus and gastric fundus tissue samples. After analyzing individual cell types, we integrated the scRNA-seq data and data of a genome-wide association study (GWAS) on BE/EAC to determine cell type-specific genetic risk. Raw data from the RNA-sequencing is provided here.

  Study EGAS50000000530