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• Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) tumor patient

  Genome and transcriptome sequence data from a pre-B all (2nd relapse in CNS) patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015291

• Utility of ctDNA to support patient selection for early phase clinical trials: The TARGET Study

  The TARGET Study consists of 200 BAM files, for the 100 patients discussed in the publication. Each patient has a normal control BAM file and a ctDNA BAM file.

  Dataset EGAD00001004796

• Whole exome sequencing of a sinonasal glomangiopericytoma case

  The is dataset includes the whole exome sequencing of the tumor from a sinonasal glomangiopericytoma case together with the matching blood. The whole exome sequencing revealed somatic PIK3CA and CTNNB1 mutations.

  Dataset EGAD00001008291

• WGS and RNA-Seq data from a GBM patient PT-CM1209

  WGS and RNA-Seq data from a GBM patient PT-CM1209

  Dataset EGAD00001004231

• Next Generation Sequencing in an IBD Pedigree Exome Data

  We perform whole exome sequencing on samples from a large IBD pedigree. The selected samples are from more distantly related family members (healthy and with IBD) and a set of matched population (Ashkenazy Jewish ancestry) samples.

  Dataset EGAD00001000422

• RNA-seq

  Stranded RNA-seq libraries were performed for 150 ng of mRNA using the TruSeq library kit (Illumina, San Diego, CA, USA). Libraries were sequenced on a NextSeq 2000 (Illumina) in a 2x50bp length.

  Dataset EGAD00001010841

• Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Evaluation of somatic mutations in cervicovaginal samples as a non-invasive method for the detection and molecular classification of endometrial cancer

  Dataset EGAD00001011123

• Segmental Cherry Angioma case

  Cherry angiomas are common benign blood vessel growths on the skin. In this study we characterise mutational profile of a cherry angioma and adjacent skin biopsied from a patient with multiple lesions with segmental presentation.

  Dataset EGAD00001015641

• DNA Double Strand Breaks in KMT2A-Rearranged AML patients

  DNA breakage at specific rearrangement-participating genes, which are more sensitive to a range of environmental and chemotherapeutic agents than other regions of the human genome, contributes to the generation of leukemia-causing rearrangements, and can be used as a predictor of susceptibility to cancer caused by gene rearrangements. As a direct proof-of-principle regarding the feasibility of employing fragile site breakage to identify and monitor high-risk populations to allow personalized treatments, genome-wide DNA break mapping/sequencing was used to determine whether preferential DNA breaks are generated at the major breakpoint regions of KMT2A in AML remission patients with previously diagnosed KMT2A rearrangement. We are submitting break mapping data from three patients with KMT2A rearrangements and three non-fusion patients, with and without etoposide treatments.

  Study phs002804

• Genome wide association study for early onset coronary disease and related phenotypes (ADVANCE)

  ADVANCE (Atherosclerotic Disease, VAscular functioN, and genetiC Epidemiology) is a large epidemiological study of genetic and non-genetic determinants of coronary artery disease (CAD) that started in 2000 as a collaborative effort between researchers at Stanford University and Kaiser Permanente of Northern California. The overarching goal of the study is to improve our ability to prevent, diagnose and treat CAD. The initial study included recruitment of over 3600 subjects (including 1873 subjects with incident clinically significant coronary disease and 1745 control subjects) from multiple race/ethnic backgrounds. A subset of ~ 500 subjects with very early onset coronary disease (men < 45 and women < 55) and ~ 500 similar aged controls were genotyped using the Illumina 550K platform as part of an NIH funded effort within the STAMPEED consortium.

  Study phs000423

• Rapid Acceleration of Diagnostics - Digital Health Technologies (RADx-DHT): Large Scale Flu Surveillance Study (LSFS)

  The purpose of this study was to better understand behavioral and physiological functioning in relation to recent self-reported influenza and influenza-like-illness (ILI), including coronavirus disease (COVID-19). Over 65,000 Achievement members responded to a weekly one-click survey asking if they had experienced ILI within the previous 7-day period. If they responded no, they were given the option to complete a survey about their risk factors and behavior. If they responded yes, they were given the option to complete a survey asking about the specifics of the incident. Participants were also asked to sync their wearable activity trackers and health apps in order for researchers to better understand changes in behavioral and physiological outcomes related to self-reported ILI experiences.DOI: https://rapids.ll.mit.edu/10.57895/fkth-d352

  Study phs002539

• Genetic Epidemiology of Chronic Lymphocytic Leukemia

  Chronic lymphocytic leukemia (CLL) is a subtype of B-cell lymphoproliferative disorders (LPD), and is the most common form of adult leukemia in Caucasians in the United States. Small lymphocytic lymphoma (SLL) is also a B-cell LPD and is typically considered to be the same disease as CLL, based on pathology. We consider CLL and SLL as the same disease entity, and hereafter refer to both simply as "CLL". Using genealogical databases and cancer records, the familial clustering for CLL is one of the strongest for all cancer sites, strongly implicating germline genetic risk. We ascertained CLL cases and controls for a genomewide association study (GWAS) that was undertaken as part of the International Lymphoma Epidemiology (InterLymph) consortium GWAS. Some CLL cases are also part of extended high-risk CLLpedigrees.

  Study phs001568

• HNPCC-Sys: Molecular Characterization of Lynch Syndromes

  Lynch Syndrome (LS) tumors are characterized by constitutional mutations in DNA mismatch-repair genes. Colorectal cancers (CRCs) are the predominant tumor type in patients with LS. Here, we have used whole-genome and transcriptome sequencing of LS- CRC to find similarities and differences of mutation and gene expression characteristics between LS-CRC and sporadic CRC (data provided by TCGA via dbGaP). Furthermore, we were interested in the molecular heterogeneity of LS-CRC. We have performed a molecular characterization of LS-tumors and of matched tumor-distant reference colonic mucosa based on whole-genome DNA- and RNA-sequencing analyses. Our data indicates the existence of two subgroups of LS-CRCs, G1 and G2, where G1 tumors show a higher number of somatic mutations, higher microsatellite slippage and a different mutation spectrum.

  Study phs001407

• HuBMAP: Single-Cell Data from Human Tissues

  The small bowel and colon are organs critical for maintaining homeostasis of the human body by mediating nutritional absorption upon the ingestion of food. Though both organs are extensive in length, there are known differences in function and cellular heterogeneity within different portions of each. Also, a cross section anywhere in the bowel reveals a complex layering of components involved in absorption and secretion, motility of gut contents, circulation, and immunity. We are mapping the complexity of the the small bowel and colon with cell-to-cell resolution in histologic sections, both along their lengths and across multiple individuals. Our molecular data consist of single cell ATAC-seq and RNA-seq. These profiles are spatially mapped to histologic sections using CO-Detection by indEXing (CODEX), a highly multiplexed system of antibody-tagged target epitopes.

  Study phs002272

• Evolution of Resistance in ER+ Breast Cancer

  While the combination of endocrine therapy and CDK4/CDK6 inhibitors has been shown to be effective in the metastatic ER+ breast cancer setting, to test whether it is effective in an earlier stage neoadjuvant setting, the FELINE trial (NCT02712723) was established to test the efficacy of letrozole and ribociclib in a ER-positive, HER2-negative patients in a randomized, placebo-controlled, multicenter trial. Patients were randomized to one of three arms: those in Arm A received letrozole and placebo, Arm B letrozole and intermittent ribociclib, and Arm C letrozole and continuous ribociclib. Samples were collected at screening (Day 0), Cycle 1 (Day 14), and end of trial (Day 180). Samples from 24 patients, where cancer cells were present at Day 0 and one additional time point, were subjected to whole-exome sequencing profiling.

  Study phs002287

• Transcriptomic and Clonal Characterization of T Cells in the Human Central Nervous System

  The cerebrospinal fluid (CSF) is thought to be a main route for immune surveillance in the central nervous system (CNS). Understanding the composition and state of CSF in healthy individuals may provide insight into perturbations present during neuroinflammation. Here, we have used single-cell RNA and TCR sequencing to profile CSF and peripheral blood mononuclear cells (PBMCs) from healthy individuals and patients with relapsing-remitting multiple sclerosis (MS), a chronic autoimmmune disease. In addition, with the goal of understanding how transcriptional artefacts are introduced in transcriptomics experiments, we have performed single-cell and TCR sequencing to profile PBMCs from a healthy individual that were processed with the same enzymatic digestion used for tissues (such as the brain) in the presence or absence of transcription inhibitors. 

  Study phs002222

• Hereditary Cancer Predisposition Syndromes and Uveal Melanoma

  Uveal melanoma (UM) is a subtype of melanoma characterized by the strong contribution of genetic rather than environmental factors in the pathogenesis of the disease, making it an ideal model disease to study the genetic basis of cancer. The long-term goal of our laboratory is to determine the genes and mechanisms responsible for hereditary cancer predisposition associated with UM. BAP1 has been identified as a candidate gene with definitive association with predisposition to UM. However, pathogenic variants in BAP1 are detected in only a small subset of UM patients even those with strong personal and family history of cancer suggesting the existence of other candidate genes. The goal of this project is to identify novel candidate genes contributing to hereditary predisposition to UM in patients with no detectable germline pathogenic variant in BAP1.

  Study phs001943

• Somatic Mutations in Epilepsy: Whole Genome Sequence Analysis of Single Neurons

  Low-coverage whole-genome sequencing was performed on single-cells from resected brain tissues obtained from an individual with hemimegalencephaly (HMG) along with a somatic copy number variant (sCNV) of chromosome 1q in order to characterize the sCNV at the single cell level. Single neuronal nuclei and non-neuronal nuclei were isolated by fluorescence-activated cell sorting (FACS) using NeuN immunoreactivity to identify neurons. 46 neurons and 30 non-neuronal cells, as well as a batch of 10 and a batch of 100 cells from each group, were genome amplified using multiple displacement amplification (MDA) and sequenced on an Illumina HiSeq 2000 sequencer. Thirty-two samples were multiplexed into each HiSeq lane for single-end 50 bp runs, obtaining ~5 million pass-filter reads per sample.

  Study phs002615

• Clinical relevance of TCGA subtypes for gastric cancer patients

  There is a clinical need for the availability of molecular biomarkers in the tratment of gastric cancer (GC), since survival rates remain poor with a 5-year survival rate of only ~`40% for patients with resectable disease. These markers will elad to a more tailored approach in the treatment of GC, which enhances efficacy and reduces toxicity. Recently, The Cancer Genome Atlas (TCGA) classified GC patients into four molecular subgroups: Epstein Barr Virus positive (EBV+), genomically stable (GS), microsatellite instable (MSI), and chromosomal instable (CIN). For this purpose we aim to collect tumor tissue blocks from patients who participated in the Dutch D1/D2 or the CRITICS trial and who gave informed consent for translational studies. Associations between TCGA subtypes and outcomes to these different therapeutic options will be analyzed.

  Study EGAS50000000779

• 10x genomics single cell RNA-seq and ATAC-seq from 10 pre-menopausal patients fimbriae and ampullary part of the fallopian tube

  The fallopian tube, connecting the uterus with the ovary, is a dynamic organ that undergoes cyclical changes and is the site of several diseases, including serous cancer. Here, we use single-cell technologies to construct a comprehensive cell map of healthy pre-menopausal fallopian tubes, capturing the impact of the menstrual cycle and menopause on different fallopian tube cells at the molecular level. The comparative analysis between pre- and post-menopausal fallopian tubes reveals substantial shifts in cellular abundance and gene expression patterns, highlighting the physiological changes associated with menopause. Further investigations into menstrual cycle phases illuminate distinct molecular states in secretory epithelial cells caused by hormonal fluctuations. The markers we identified characterizing secretory epithelial cells provide a valuable tool for classifying ovarian cancer subtypes.

  Study EGAS50000000628

• Transcriptomic profiling of circulating regulatory T cells from follicular lymphoma patients before and after Lenalidomide treatment

  Lenalidomide has demonstrated a favorable efficacy profile in follicular lymphoma (FL) in combination with anti-CD20 antibodies. However, in vivo administration of Lenalidomide in FL patients triggers a proliferation of functional regulatory T cells (Tregs), and a high percentage of Tregs before and along the course of treatment with Lenalidomide/anti-CD20 combination is of poor prognosis. In this study, we evaluated the impact of Lenalidomide on circulating Treg in 3 FL patients using single cell RNA sequencing (scRNAseq). For this purpose, we took advantage of the GALEN clinical trial (NCT01582776), where Lenalidomide was initiated one week before starting the anti-CD20 antibody Obinutuzumab, allowing us to compare the transcriptomic profile of immune cells before (D0) and at day 7 (D7) of treatment by Lenalidomide alone.

  Study EGAS50000001048

• The Oral Microbiome and Head and Neck Cancer

  Oral microbiota may influence head and neck squamous cell carcinoma (HNSCC) development, potentially related to carcinogen metabolism. The human oral cavity hosts a diverse microbiota, including bacteria and fungi. We performed shotgun sequencing and ITS1 sequencing on 236 HNSCC case participants who developed HNSCC during a mean follow-up of 5.1 years and 458 matched controls who remained HNSCC-free. Oral samples were obtained from a prospective nested case-control study within three epidemiological cohorts: the American Cancer Society Cancer Prevention Study II Nutrition Cohort (ACS CPS-II), the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), and the Southern Community Cohort Study (SCCS). Control participants were selected using 2:1 frequency matching based on cohort, age, sex, race and ethnicity, and time since oral sample collection.

  Study phs004018

• Single-Cell Atlas of Human Liver and Blood Immune Cells Across Fatty Liver Disease Stages

  The goal of the study was to investigate immunological correlates of human fatty liver disease progression. We generated a single-cell RNA-seq (scRNA-seq) atlas of immune cells from liver fine needle aspirates (FNAs) and paired peripheral blood mononuclear cells (PBMCs) from a full-spectrum Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD)/Metabolic Dysfunction-Associated Steatohepatitis (MASH) human cohort, using the 3' 10X Genomics platform. Using computational analyses to assess changes in cellular frequencies and function, we found heightened immunoregulatory programs with profibrotic potential alongside a shift from antigen-specific to natural killer cytotoxic functions in the liver with MASH progression. Available data include raw single-cell transcriptomic data (FASTQ files) for each sample type (PBMC, FNA) per patient alongside clinical and histological measurements of fatty liver disease.

  Study phs004044

• Smoking-dependent expression alterations in nasal epithelium reveal immune impairment linked to germline variation and lung cancer risk.

  Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to lifestyle risk in the form of cigarette smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, often many years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk are unclear. CT screening of current and former smokers has been shown to reduce lung cancer mortality by up to 26%. To examine whether clinical risk stratification can be improved upon by the addition of genetic data, and to explore the mechanisms of the persisting risk in former smokers, we have analyzed transcriptomic data from accessible airway tissues of 487 subjects. We developed a model to assess smoking associated gene expression changes and their reversibility after smoking is stopped, in both healthy subjects and clinic patients. We find persistent smoking associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune and interferon related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalised smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.

  Dac EGAC50000000169

• exploration of biomarkers discriminating squamous cell carcinoma from other lung cancers

  Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. The most effective regimen in lung cancers is different between squamous cell carcinoma (SCC) and adenocarcinoma (AD). Therefore a precise diagnosis is crucial, but this has been difficult, particularly for poorly differentiated SCC (PDSCC) and AD without a lepidic growth component (non-lepidic AD). Biomarkers enabling a precise diagnosis are therefore urgently needed. To achieve this goal, we initially performed CAGE (Cap Analysis of Gene Expression) to quantify promoter activities on 97 frozen tissues from surgically resected lung cancers (22 SCC and 75 AD). We furhter expanded the transcriptome profiling to cover additional 48 malignant neoplasm of bronchus and lung, including mesothelioma and metastatic lung cancers derived from other tissues.

  Study JGAS000488

• ECM-free patient-derived organoids preserve diverse prostate cancer lineages and uncover in vitro-enriched cell types

  Patient-derived organoids (PDOs) hold promise for modeling various cancers, yet their application in prostate cancer (PCa) has been limited due to low culture success and the predominance of non-tumor-like cells. Using 164 PCa samples and optimizing culture conditions, we demonstrate that an extracellular matrix (ECM)-free culture method improves PDO take-rates, fostering cell populations with luminal and PCa-specific characteristics. Single-cell RNA sequencing (scRNA-seq) reveals that these ECM-free PDOs closely mirror their original tumors at the transcriptomic level and maintain a diverse array of tumor cell types, unlike traditional Matrigel-based cultures which predominantly yield benign-like cells. This study introduces a PCa PDO single-cell atlas, providing a valuable resource for advancing prostate cancer research.

  Study EGAS50000000807

• Germline Aberrations of PAX5 Cause Susceptibility to pre-B cell Acute Lymphoblastic Leukemia

  A novel heterozygous germline variant, c.547G>A (p.Gly183Ser), in the paired box protein encoding gene, PAX5, was found to segregate with disease in two unrelated kindreds with autosomal dominant pre-B cell acute lymphoblastic leukemia (ALL). Leukemic cells from both families exhibited 9p deletion, with loss-of-heterozygosity and retention of the mutant PAX5 allele at 9p13 . Two additional sporadic ALL cases with 9p loss demonstrated PAX5 Gly183 substitution in the leukemic cells. Functional analysis of the PAX5 germline variants demonstrated reduced transcriptional activity, as well as decreased interaction with Groucho-4. These data extend the role of PAX5 alterations in the pathogenesis of pre-B ALL, and implicate PAX5 in a novel syndrome of germline susceptibility to pre-B cell neoplasia.

  Study EGAS00001000447

• Whole-exome sequencing of breast cancer metastasis and corresponding blood samples

  This study included samples from metastatic breast cancer patients who underwent a biopsy in the context of SAFIR01 (NCT01414933), SAFIR02 (NCT02299999), SHIVA (NCT01771458) and MOSCATO (NCT01566019) prospective trials. These French multicentre trials used high throughput genome analysis on fresh frozen tumor biopsies as a therapeutic decision tool for metastatic cancer patients, with solid cancers (SHIVA, MOSCATO) or specifically with breast cancer (SAFIR01, SAFIR02). All patients gave their informed consent for translational research and genetic analyses of their somatic DNA. Overall, whole-exome sequencing for a total of 216 pairs of metastatic tumor and unmutated DNA derived from corresponding blood samples was performed using Illumina technology. The results of the analysis of the mutational profile of metastatic breast cancer was reported in Lefebvre et al. (PMID:28027327).

  Study EGAS00001001695

• Tumor-associated preferred end coordinates and somatic variants as signatures of circulating tumor DNA

  Cell-free DNA fragmentation is a nonrandom process. We showed that cell-free DNA fragments with ends at certain genomic coordinates had higher likelihoods of being derived from hepatocellular carcinoma. Other coordinates were associated with cell-free DNA molecules originating from the liver. Quantitative assessment of cell-free DNA molecules bearing these respective groups of end signatures correlated with the amounts of tumor-derived or liver-derived DNA in plasma. There were millions of tumor-associated plasma DNA end coordinates across the genome. Due to their high prevalence, they were more readily detectable than somatic mutations as a cancer signature in plasma. Hence, detection of tumor-associated plasma DNA ends may offer a cost-effective means of capturing evidence for the presence of cancer through liquid biopsy assessment.

  Study EGAS00001003160

• Pediatric Low-Grade Glioma RNA and Targeted Sequencing

  Pediatric low-grade gliomas (pLGG) are frequently driven by genetic alterations in the RAS/MAPK pathway yet show unexplained variability in their clinical outcome. To address this, we characterized a cohort of >1,000 clinically annotated pLGG. 84% of cases harbored a driver alteration, while those without an identified alteration also often exhibited up-regulation of the RAS/MAPK pathway. pLGG could be broadly classified based on their alteration type. Rearrangement-driven tumors were diagnosed at a younger age, enriched for WHO grade I histology, infrequently progressed, and rarely resulted in death as compared to SNV-driven tumors. Further sub-classification of clinical-molecular correlates stratified pLGG into risk categories. These data highlight the biological and clinical differences between pLGG subtypes and opens avenues for future treatment refinement.

  Study EGAS00001004242

• Loss-of-activity-mutation in the cardiac chloride-bicarbonate exchanger AE3 causes short QT syndrome

  Patients with short QT syndrome (SQTS) may present with syncope, ventricular fibrillation or sudden cardiac death. Six SQTS susceptibility genes, encoding cation channels, explain less than 25% of SQTS cases. Here we identify a missense mutation in the anion exchanger (AE3)-encoding SLC4A3 gene in two unrelated families with SQTS. The mutation causes reduced surface expression of AE3 and reduced membrane bicarbonate transport. Slc4a3 knockdown in zebrafish causes increased cardiac pHi, short QTc, and reduced systolic duration, which is rescued by wildtype but not mutated SLC4A3. Mechanistic analyses suggest that an increase in pHi and decrease in [Cl-]i shortened the action potential duration. However, other mechanisms may also play a role. Altered anion transport represents a mechanism for development of arrhythmia and may provide new therapeutic possibilities.

  Study EGAS00001002632

• Multiple migrations to the Philippines during the last 50,000 years

  A key link to understand human history in Island Southeast Asia is the Philippine archipelago and its poorly investigated genetic diversity. We collected and analyzed the most comprehensive set of population-genomic data for the Philippines, 1028 individuals covering 115 indigenous communities. We demonstrate that the Philippines were populated by at least five waves of human migration. The Cordillerans migrated into the Philippines prior to the arrival of rice agriculture, where some remain to be the least admixed East Asians carrying an ancestry shared by all Austronesian-speaking populations; thereby challenging an exclusive Out-of-Taiwan model of joint farming-language-people dispersal. Altogether, our findings portray Philippines as a crucial gateway, with a multilayered history, that ultimately changed the genetic landscape of the Asia-Pacific region.

  Study EGAS00001005083

• Germline SDHB-inactivating mutation in gastric spindle cell sarcoma (HIPO-021)

  Gastrointestinal stromal tumors (GISTs) are the most frequent mesenchymal tumors of the gastrointestinal tract. Inactivating mutations or epigenetic deregulation of succinate dehydrogenase complex (SDH) genes are considered defining features of a subset of GIST occurring in the stomach. Based on comprehensive molecular profiling and biochemical analysis within a precision oncology program, we identified hallmarks of SDH deficiency (germline SDHB-inactivating mutation accompanied by somatic loss of heterozygosity, lack of SDHB expression, global DNA hypermethylation, and elevated succinate/fumarate ratio) in a 40-year-old woman with undifferentiated gastric spindle cell sarcoma that did not meet the diagnostic criteria for other mesenchymal tumors of the stomach, including GIST. These data reveal that the loss of SDH function can be involved in the pathogenesis of non-GIST sarcoma of the gastrointestinal tract.

  Study EGAS00001004277

• Persistent Mutation Burden Drives Sustained Anti-Tumor Immune Responses

  Tumor mutation burden is an imperfect proxy of tumor foreignness and has therefore failed to consistently demonstrate clinical utility in predicting responses in the context of immunotherapy. We evaluated mutations in regions of the genome that are unlikely to undergo loss and discovered that clonal mutations in single-copy regions and those present in multiple copies per cell constitute a persistent tumor mutation burden (pTMB) that is linked with therapeutic response to immune checkpoint blockade. Persistent mutations were retained in the context of tumor evolution under selective pressure of immunotherapy and tumors with a high pTMB content were characterized by a more inflamed tumor microenvironment. pTMB imposes an evolutionary bottleneck that cancer cells cannot overcome and may thus drive sustained immunologic tumor control in the context of immunotherapy.

  Study EGAS00001006660

• The Iberian Roma genetic variant server

  The Roma are the most numerous ethnic minority in Europe. The Iberian Roma arrived in the Iberian Peninsula five centuries ago and still today, they keep a strong group identity. Demographic and cultural reasons lie behind a high rate of Mendelian disease often related to founder variants. We have analysed exome data from 119 Iberian Roma individuals collected from 2018 to 2020. A database of variant frequency has been implemented (IRPVS) and made available online. We have analysed the carrier rate of founder private alleles as well as pathogenic variants present in the general population. Significant enrichment in structural variants involving gene clusters related to keratinization and epidermal growth suggest that evolutive mechanisms have developed towards climate and environmental adaptation. IRPVS can be accessed at http://irpvs.clinbioinfosspa.es/

  Study EGAS00001006758

• GCparagon: Evaluation and correction of GC biases in cell-free DNA at the fragment level

  We present GCparagon, a two-stage algorithm for computing and correcting GC biases in cell-free DNA (cfDNA) samples. The length of the highly fragmented cfDNAs and the number of GC bases are essential parameters in the calculations. Regions of low mappability, known reference genome assembly errors and regions surrounding assembly gaps are excluded from the bias computation. GCparagon outputs a bias matrix and an optional tagged BAM file with GC bias balance weights as alignment tags. Parallelization allows calculation of a GC bias estimate in less than 2 minutes per sample with between 99.0% and 99.9% of fragments already corrected. We propose that GCparagon can help standardize cfDNA applications and evaluate the impact of GC bias on algorithms used in the analysis of liquid biopsy data.

  Study EGAS00001006963

• The earliest stages of neoplastic transformation in Familial Adenomatous Polyposis

  The succession of somatic genetic events associated with the conversion of a normal colorectal epithelial cell into a colorectal carcinoma constitutes a paradigmatic model of cancer development. Familial Adenomatous Polyposis (FAP) is caused by constitutional inactivating mutations in APC, the central gatekeeper gene of colorectal cancer, and is associated with a substantially increased lifetime-risk of colorectal cancer. To investigate the earliest stages of neoplastic change due to APC inactivation, we microdissected and individually whole genome sequenced 279 histologically normal and abnormal colorectal crypts from 15 individuals with FAP. Histologically normal crypts generally exhibited similar mutation burdens and mutational signatures to normal crypts from wild-type individuals of the same age, with 1/110 carrying a somatic inactivating APC mutation. By contrast, 9/18 aberrant crypt foci carried somatic APC mutations and exhibited modestly increased burdens of some mutational signatures found in normal crypts. 12/13 diminutive adenomatous polyps (less than 5mm diameter) showed somatic APC mutations and carried substantially increased mutation loads of most mutational signatures present in normal crypts. Phylogenetic trees of crypts from aberrant crypt foci and adenomatous polyps revealed that some had acquired their initiating somatic APC mutations decades previously during the first few years of life. The results catalogue the changes in somatic mutation rates, mutational processes and “driver” mutations in cancer genes during the earliest stages of colorectal neoplastic transformation initiated by APC inactivation and highlight the long periods of clonal evolution required for a cancer to develop.

  Dataset EGAD00001015477

• Transcriptome human nasal epithelium

  1. Odors are detected, firstly, by olfactory sensory neurons (OSNs) in the olfactory epithelium of the nose. This neurons then project directly to the olfactory bulb in the brain. Olfaction depends on cellular regeneration of the OE, olfactory bulb and hippocampus, and on their continual re-wiring. The olfactory neural pathway includes regions of the frontal, temporal and limbic brain, which in turn overlap with brain areas involved in brain disorders. OSNs are the only aspect of the human brain exposed to the external environment. This not only makes them vulnerable to environmental changes, but also accessible for biomedical studies. We have already sequenced and developed a protocol for analyzing the transcriptome of mouse main olfactory epithelium and single OSNs. We propose here to perform a similar study for samples from the human olfactory epithelium. We have developed a minimally invasive method for obtaining human OSNs, among other cells from the nasal epithelium. In this experiment, we have obtained cell samples from the olfactory epithelium, including OSN, from healthy volunteers. We would like to further characterize them by RNA sequencing. This will give us valuable insight into human olfaction. It will also provide a first step into a new avenue to study, and find biomarkers for, brain diseases though the analysis of these easily available neurons. 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/

  Dataset EGAD00001002226

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Dataset EGAD00001005448

• The earliest stages of neoplastic transformation in Familial Adenomatous Polyposis

  The succession of somatic genetic events associated with the conversion of a normal colorectal epithelial cell into a colorectal carcinoma constitutes a paradigmatic model of cancer development. Familial Adenomatous Polyposis (FAP) is caused by constitutional inactivating mutations in APC, the central gatekeeper gene of colorectal cancer, and is associated with a substantially increased lifetime-risk of colorectal cancer. To investigate the earliest stages of neoplastic change due to APC inactivation, we microdissected and individually whole genome sequenced 279 histologically normal and abnormal colorectal crypts from 15 individuals with FAP. Histologically normal crypts generally exhibited similar mutation burdens and mutational signatures to normal crypts from wild-type individuals of the same age, with 1/110 carrying a somatic inactivating APC mutation. By contrast, 9/18 aberrant crypt foci carried somatic APC mutations and exhibited modestly increased burdens of some mutational signatures found in normal crypts. 12/13 diminutive adenomatous polyps (less than 5mm diameter) showed somatic APC mutations and carried substantially increased mutation loads of most mutational signatures present in normal crypts. Phylogenetic trees of crypts from aberrant crypt foci and adenomatous polyps revealed that some had acquired their initiating somatic APC mutations decades previously during the first few years of life. The results catalogue the changes in somatic mutation rates, mutational processes and “driver” mutations in cancer genes during the earliest stages of colorectal neoplastic transformation initiated by APC inactivation and highlight the long periods of clonal evolution required for a cancer to develop.

  Dataset EGAD00001015471

• Evolutionary landscape of clonal hematopoiesis in 3359 individuals from the general population

  This project contains longitudinal data for processed somatic variant calls and data on core phenotypic variables for 3359 community-based individuals ≥60 years, a sub-cohort of the population-based Lifelines cohort (167,729 participants). Cases with peripheral blood count abnormalities and population-based controls were included. Next-generation sequencing data were generated with a median time period of 43 months between baseline and follow-up visit. For 327 individuals a third visit sample was included. Error-corrected sequencing was performed using single-molecule tagged molecular inversion probes targeting 27 myeloid and lymphoid driver genes. The threshold for variant calling was set at ≥1% VAF and ≥10 consensus variant reads. Details on sample selection, sequencing technique, variant calling procedures and data curation are described (van Zeventer et al. 2023).

  Study EGAS00001007087

• eMERGE Network Genome-Wide Association Study of Red Cell Indices, White Blood Count (WBC) Differential, Diabetic Retinopathy, Height, Serum Lipid Levels, Specifically Total Cholesterol, HDL (High Density Lipoprotein), LDL (Low Density Lipoprotein), and Triglycerides, and Autoimmune Hypothyroidism.

  The electronic Medical Records and Genomics (eMERGE) Network is a consortium of five participating sites (Group Health Seattle, Marshfield Clinic, Mayo Clinic, Northwestern University, and Vanderbilt University) funded by the NHGRI to investigate the use of electronic medical record systems for genomic research. The goal of eMERGE is to conduct genome-wide association studies in approximately 19,000 individuals using EMR-derived phenotypes and DNA from linked Biorepositories. Using electronic phenotyping methods, the consortium used DNA samples from all participating sites to explore the genetic determinants of red cell indices, white blood count (WBC) differential, diabetic retinopathy, height, serum lipid levels, specifically total cholesterol, HDL (high density lipoprotein), LDL (low density lipoprotein), and triglycerides, and autoimmune hypothyroidism as well as using the phenome-wide association study (PheWAS) paradigm to replicate and discover relationships between targeted genotypes with multiple phenotypes. eMERGE led studies for which original genotyping was performed and are included in this merged set: Genome-Wide Association Study on Cataract and HDL in the Personalized Medicine Research Project Cohort, phs000170 Development and Use of Network Infrastructure for High-Throughput GWA Studies, phs000234 Vanderbilt Genome-Electronic Records (VGER) Project: QRS Duration, phs000188 Northwestern NUgene Project: Type 2 Diabetes, phs000237 A Genome-Wide Association Study of Peripheral Arterial Disease, phs000203 Sites and participants include: Vanderbilt University: BioVU, Vanderbilt's DNA databank, is an enabling resource for exploration of the relationships among genetic variation, disease susceptibility, and variable drug responses, and represents a key first step in moving the emerging sciences of genomics and pharmacogenomics from research tools to clinical practice. BioVU acquires DNA from discarded blood samples collected from routine patient care. The biobank is linked to de-identified clinical data extracted from Vanderbilt's EMR, which forms the basis for phenotype definitions used in genotype-phenotype correlations. Marshfield Clinic: The Marshfield Clinic Personalized Medicine Research Project is a population-based biobank in central Wisconsin with more than 20,000 adult subjects who provided written, informed consent to access their medical records and provided a blood sample from which DNA was extracted and plasma and serum stored. In addition to an average of 30 years of medical history data, a questionnaire about environmental exposures, including a detailed food frequency questionnaire, is available to facilitate gene/environment studies. Northwestern University: The NUgene Project is a repository with longitudinal medical information from participating patients at affiliated hospitals and outpatient clinics from the Northwestern University Medical Center. Participants' DNA samples are coupled with data from a self-reported questionnaire and continuously updated data from our Electronic Medical Record (EMR) representing actual clinical care events. Northwestern has a state-of-the art, comprehensive inpatient and outpatient EMR system of over 2 million patients. NUgene has broad access to participant data for all outpatient visits as well as inpatient data via a consolidated data warehouse. NUgene participants consent to distribution and use of their coded DNA samples and data for a broad range of genetic research by third-party investigators. Group Health(GH)/University of Washington (UW): Aging and Dementia eMERGE study biorepository leverages rich population-based longitudinal data from both electronic medical records and in-depth research data to explore genome wide associations. Participants include Seattle-area members of GH (a large integrated health care system in Washington State) consented and enrolled in 1) the UW Alzheimer's Disease Patient Registry (ADPR) and 2) the Adult Changes in Thought (ACT) study. The ADPR (PI: Eric B. Larson; NIH/NIA U01 AG 006781) is a population-based registry of incident dementia cases designed to identify all new Alzheimer's Disease cases within GH from 1987 to 1996. Medical history, physical, laboratory testing, and neuropsychological testing were performed on all consenting potential cases for determination of dementia status by a consensus conference. The study base of the ADPR population was stable with an attrition rate of less than 1%/year. The ACT study (PI: Eric B. Larson; NIH/NIA U01 AG 006781) is an ongoing community-based cohort study of aging and dementia. The original cohort of 2,581 randomly selected dementia-free members age 65 and older was enrolled in 1994-1996 and expanded by 811 in 2000-2002. Continuous enrollment to maintain a cohort of 2,000 dementia free persons began in 2005. Participants receive biennial assessment including cognitive status determination. The ACT sub-sample is stable; for the original cohort, median enrollment in GH was 19 years prior to joining the ACT study, and 85% of the cohort has ≥10 years of GH enrollment. DNA for the ADPR participants were obtained through a companion study, Genetic Differences in Cases and Controls (PI: Walter Kukull; NIH/NIA R01 AG007584). DNA obtained through both studies were extracted from blood using Gentra Systems Puregene methods. DNA concentration is determined by UV optical density. All samples are checked for quality by 260/280 ratio. For long-term storage, samples are aliquoted and stored at -70°C. Mayo Clinic: The Mayo biobank is a disease-specific biobank for vascular diseases including peripheral arterial disease (PAD). PAD patients were identified from individuals referred to the non-invasive vascular laboratory for lower extremity arterial evaluation. Since 1997, laboratory findings have been recorded into an electronic database employing an in-house software package for data archiving and retrieval; this data becomes part of the Mayo EMR. Patients referred to the center with suspected PAD undergo a comprehensive non-invasive evaluation including the ankle-brachial index (ABI) - the ratio of blood pressure measured in the upper arms divided by blood pressure measured at the ankles. Controls subjects are identified from patients referred to the Cardiovascular Health Clinic for stress ECG. The prevalence of PAD in patients with normal exercise capacity who do not have inducible ischemia on the stress ECG, was <1%. Data regarding risk factors for atherosclerosis such as diabetes, dyslipidemia, hypertension, and smoking are ascertained from the EMR.

  Study phs000360

• Genetic Analysis of Normal Human Facial Variation

  The purpose of this project is to identify genes associated with normal human quantitative facial variation. The motivation for this project stems from the fact that very little is known about how variation in specific genes relates to the diversity of facial forms commonly observed in humans. Viable candidates for these morphogenes originate from a number of sources: tissue expression studies, animal models with targeted or spontaneous mutations, and genetic syndromes with craniofacial manifestations. Importantly, understanding the genetic basis for normal facial variation also has important implications for health-related research. For example, this work has the potential to shed light on the factors influencing liability to common craniofacial anomalies such as orofacial clefts. There is now ample evidence that certain facial features (e.g., increased midfacial retrusion) characterize individuals genetically at-risk for orofacial clefts (e.g., biological relatives of affected cases). While these predisposing facial features are statistically over-represented in at-risk groups, they are also common in the general population. Since many of the current candidate genes for clefting are thought to play a critical role in facial morphogenesis, variation in these genes may also underlie normal variation in these facial features. These candidate genes, however, probably represent only a small fraction of the total number of loci influencing normal human facial variation. Phenotypes for this project were obtained from over 3000 healthy Caucasian subjects recruited through three separate studies. The majority of the subjects were recruited as part of the 3D Facial Norms Project, which is described in extensive detail here: (https://www.facebase.org/facial_norms/notes). The provided dbGaP phenotypes include a series of anthropometric craniofacial measurements (linear distances) primarily derived from 3D photographic facial surface scans (see previous hyperlink). The specific genotyping requested is described elsewhere in this document. Our analysis team is pursuing a variety of different analytic approaches to derive genetically informative phenotypes, including various shape-based morphometric methods. For those interested in pursuing more advanced phenotypic approaches, the original 3D surface scans and additional phenotypic traits are available to researchers through the FaceBase Consortium. This dataset has the potential to facilitate the discovery of new genetic loci with an important role in both normal and abnormal facial development. It may also serve as a dataset to test hypotheses regarding specific SNP associations (e.g. as a replication dataset) or as part of a larger meta-analysis.

  Study phs000949

• NHLBI TOPMed: The Cleveland Family Study (CFS)

  The Cleveland Family Study (CFS) is one cohort involved in the WGS project. The CFS was designed to provide fundamental epidemiological data on genetic and non-genetic risk factors for sleep disordered breathing (SDB). In brief, the CFS is a family-based study that enrolled a total of 2284 individuals from 361 families between 1990 and 2006. The sample was selected by identifying affected probands who had laboratory diagnosed obstructive sleep apnea. All first degree relatives, spouses and available second degree relatives of affected probands were studied. In addition, during the first 5 study years, neighborhood control families were identified through a neighborhood proband, and his/her spouses and first degree relatives. Each exam, occurring at approximately 4 year intervals, included new enrollment as well as follow up exams for previously enrolled subjects. For the first three visits, data, including an overnight sleep study, were collected in the participants' homes while the last visit occurred in a general clinical research center (GCRC). Phenotypic characterization of the entire cohort included overnight sleep apnea studies, blood pressure, spirometry, anthropometry and questionnaires. The GCRC exam (n=735 selected individuals) included more comprehensive phenotype data on a focused subsample of the larger cohort, to permit linking SDB phenotypes with cardio-metabolic phenotypes, with an interest in identifying genetic loci that are associated with these related phenotypes. In this last round of data collection, a subset of 735 individuals was selected based on expected genetic informativity by choosing pedigrees where siblings had extremes of the apnea hypopnea index (AHI). Participants underwent detailed phenotyping including laboratory polysomnography (PSG), ECG, spirometry, nasal and oral acoustic reflectometry, vigilance testing, and blood and urine collection before and after sleep and after an oral glucose tolerance test. A wide range of biochemical measures of inflammation and metabolism were assayed by a Core Laboratory at the University of Vermont. 994 individuals were sequenced as part of TOPMed Phase 1, including 507 African-Americans and 487 European-Americans. Among the sequenced individuals, 156 were probands with diagnosed sleep apnea, an additional 706 were members of families with probands, and 132 were from neighborhood control families. 298 individuals were sequenced as part of TOPMed Phase 3.5, including 169 African-Americans and 129 European-Americans. Among the newly sequenced individuals, 33 were probands with diagnosed sleep apnea, an additional 214 were members of families with probands, and 51 were from neighborhood control families. Please note: Phenotype and pedigree data are available through "NHLBI Cleveland Family Study (CFS) Candidate Gene Association Resource (CARe)", phs000284.

  Study phs000954

• GA4GH

  Standards The EGA is a long-standing supporter of the Global Alliance for Genomics & Health (GA4GH) to enhance responsible sharing of human genetic data through the development of interoperable global standards for human data access. The EGA is one of the founding GA4GH Driver Projects and has contributed to the development and implementation of several GA4GH standards and APIs. Below is a list of the GA4GH standards and APIs that are currently available or planned for implementation at EGA. TechnicalStandards Purpose SpecificationVersion SupportedVersion Implementation Large Scale Genomics htsget A protocol for secure, efficient, and reliable access to sequencing read and variation data. V1.3.0 V1.0.0 Specification Documentation Endpoint Read File Formats (SAM/BAM/CRAM) Specifications for storing next-generation sequencing read data. V3.0.0 V3.0.0 Implementation Example of Usage Variation File Formats (VCF/BCF) The specifications for Variant Call Format Files (VCF) and its binary counterpart BCF. V4.0.0 V2.0.0 V4.0.0 V2.0.0 Implementation Example of Usage Crypt4GH v1.0 Enables direct byte-level compatible random access to encrypted genetic data stored in community standards (e.g. CRAM, VCF) V1.0 V1.0 Specification Documentation Endpoint refget API Enables access to reference sequences using an identifier derived from the sequence itself. V1.2.6 NA Specification RNAget API v1 Provides a means of retrieving data from several types of RNA experiments including (i) feature-level expression data from RNA-seq type measurements and (ii) coordinate-based signal/intensity data similar to a bigwig representation via a client/server model. V1.0.0 NA Documentation Discovery Beacon v2 Supports discovery of genomic variants, phenotypes, and individuals V1.0.1 V0.3 Web UI API Source Code Service Info API v1 The Service Info API is an endpoint for describing GA4GH service metadata, designed for extension and inclusion in other APIs. Service info is used to describe a single service, while Service Registry is used to describe multiple services. V1.0.0 NA Documentation Service Registry API v1 provides information about other GA4GH services, primarily for the purpose of organizing services into networks or groups and service discovery across organizational boundaries. V1.0.0 NA Documentation Data Use Researcher Identities Data Use Ontology (DUO) Allow users to semantically tag genomic datasets with usage restrictions, allowing them to become automatically discoverable based on a health, clinical, or biomedical researcher’s authorisation level or intended use. 2021-02-23 2021-02-23 Specification Documentation Endpoint Authentication & Authorization Infrastructure (AAI) The GA4GH AAI specification leverages OpenID Connect (OIDC) Servers for use in authenticating the identity of researchers desiring to access clinical and genomic resources from data holders adhering to GA4GH standards, and to enable data holders to obtain security-related attributes of those researchers. V1.2.0 V1.2.0 API URI: ega.ebi.ac.uk:8443 Documentation Repository Researcher IDs (passport, visa) Specify the collection of researchers that may access a dataset at any given time, and the credentials they must supply. V1.0.1 V1.0.1 Specification Documentation Endpoint Cloud Tool Registry Service API TRS is a standard API for exchanging tools and workflows to analyze, read, and manipulate genomic data. V2.0.1 NA Documentation Repostiory Data Repository Service API ​DRS API is a standard for building data repositories and adapting access tools to work with those repositories, works with other approved APIs from the GA4GH Cloud Work Stream to allow researchers to discover algorithms across different cloud environments and send them to datasets they wish to analyse. V1.0.3 NA Documentation Repostiory Workflow Execution Service API This API lets users run a single workflow (defined using CWL or WDL) on multiple different platforms, clouds, and environments, and be confident that it will work the same way. The API provides methods to request that a workflow be run, pass parameters to that workflow, get information about running workflows, and cancel a running workflow. V1.0.1 NA Documentation Repostiory Genomic Knowledge Standards Variation Representation v1 Provides a flexible framework of computational models, schemas, and algorithms to precisely and consistently exchange genetic variation data across communities. V1.3.0 EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Clin/ Pheno Data Capture Phenopackets Provides information models with different levels of complexity to enable high level clinical phenotype information as well as deep clinical phenotype information to be exchanged. V2.0.0 Included in Ongoing Submissions EGA team is contributing to including it in in Beacon v2 Specification and Elixir Reference Implementation Documentation Repostiory Driver Project The EGA, jointly coordinated by the EBI and the CRG, was announced, in 2017, to be one of the 15 Driver Projects for GA4GH. Driver Projects are international genomic data initiatives, focussed on real projects and challenges that will guide the development efforts in order to accelerate and enable completely responsible and standarised data sharing by 2022. All chosen Driver Projects make a cross-sectional effort by playing an important role across the different workstreams. Thomas Keane, Jordi Rambla, Mallory Freeberg, and Aina Jené have been named Driver Project Champions for the EGA. All Driver Project Champions will be leading this ambitious initiative for the following years.

  Documentation about/projects-and-funders/ga4gh

• Action to Control Cardiovascular Risk in Diabetes (ACCORD-BioLINCC)

  Related StudiesWhole genome and whole exome data is available on a subset of participants with phs001411. ECG signal data is available with phs003562.ObjectivesThe purpose of this study was to determine if intensive glycemic control, multiple lipid management and intensive blood pressure control could prevent major cardiovascular events (myocardial infarction, stroke or cardiovascular death) in adults with type 2 diabetes mellitus. Secondary hypotheses included treatment differences in other cardiovascular outcomes, total mortality, microvascular outcomes, health-related quality of life and cost-effectiveness. BackgroundGlycemia Trial:Patients with type 2 diabetes mellitus die of cardiovascular disease (CVD) at rates two to four times higher than non-diabetic populations of similar demographic characteristics. They also experience increased rates of nonfatal myocardial infarction and stroke. With the growing prevalence of obesity in the United States, CVD associated with type 2 diabetes is expected to become an even greater public health challenge in the coming decades than it is now. Expected increases in event rates will be associated with a concomitant rise in suffering and resource utilization.The ACCORD study investigated whether intensive therapy to target normal glycated hemoglobin (HbA1c) levels would reduce cardiovascular events in patients with type 2 diabetes who had either established cardiovascular disease or additional cardiovascular risk factors when compared to standard therapy (HbA1c between 7.0% and 7.9%). A separate analysis investigated whether reduction of blood glucose concentration decreases the rate of microvascular complications in these patients. Lipid Therapy Trial: Patients with type 2 diabetes mellitus have an increased incidence of atherosclerotic cardiovascular disease attributable, in part, to associated risk factors such as dyslipidemia. This is characterized by elevated plasma triglyceride levels, low levels of high-density lipoprotein (HDL) cholesterol and small, dense low-density lipoprotein (LDL) particles. The ACCORD Lipid Therapy trial was designed to test the effect of a therapeutic strategy that uses a fibrate to raise HDL-C and lower triglyceride levels and uses a statin for treatment of LDL-C reduce the rate of CVD events compared to a strategy that only uses a statin for treatment of LDL-C on cardiovascular outcomes in patients with type 2 diabetes that were at high risk for cardiovascular disease. Blood Pressure Trial: Diabetes mellitus increases the risk of cardiovascular disease at every level of systolic blood pressure. Because cardiovascular risk in patients with diabetes is graded and continuous across the entire range of levels of systolic blood pressure, even at prehypertensive levels, the Seventh Report of the Joint National Committee on Prevention, Detection, Evaluation, and Treatment of High Blood Pressure (JNC 7) recommended beginning drug treatment in patients with diabetes who have systolic blood pressures of 130 mm Hg or higher, with a treatment goal of reducing systolic blood pressure to below 130 mm Hg. There is, however, a paucity of evidence from randomized clinical trials to support these recommendations. The ACCORD Blood Pressure trial tested the effect of a target systolic blood pressure below 120 mm Hg on major cardiovascular events among high-risk persons with type 2 diabetes compared to a strategy that targeted a SBP of EYE Substudy: Diabetic retinopathy, an important microvascular complication of diabetes, is a leading cause of blindness in the United States. Randomized, controlled clinical trials in cohorts of patients with type 1 diabetes and those with type 2 diabetes have shown the beneficial effects of intensive glycemic control and intensive treatment of elevated blood pressure on the progression of diabetic retinopathy. Elevated serum cholesterol and triglyceride levels have been implicated, in observational studies and small trials, as additional risk factors for the development of diabetic retinopathy and visual loss. The ACCORD EYE Substudy evaluated the effects of the ACCORD medical strategies on the progression of diabetic retinopathy in a subgroup of trial patients. MIND Substudy: Studies suggest that older persons with type 2 diabetes have at least twice the likelihood of developing late-life cognitive impairment or dementia compared to those without. The mechanisms underlying these cognitive disorders are increasingly thought to reflect a mixed pathology pattern with contributions from vascular, neurodegenerative and neurovascular processes. Pathophysiological mechanisms that have been described include inflammation, oxidative stress, energy imbalance, protein misfolding, glucocorticoid-mediated effects and differences in genetic susceptibilities. The ACCORD MIND substudy took as a premise that early intervention with the ACCORD therapeutic strategies to improve glycemic control could mitigate the adverse effects of type 2 diabetes on the brain. Participants10,251 participants with type 2 diabetes and HbA1c concentrations of 7.5% or more participated in the trial. Of these patients, 5518 were assigned to the lipid therapy arm and 4733 to the blood pressure arm. EYE Substudy: A subgroup of 2856 participants was evaluated for the effects of the ACCORD interventions at 4 years on the progression of diabetic retinopathy. Participants who, at baseline, had a history of proliferative diabetic retinopathy that had been treated with laser photocoagulation or vitrectomy were excluded. MIND Substudy: A subgroup of 2977 participants was evaluated for cognitive function and brain volume. The ACCORD MIND substudy excluded participants aged Design Participants were randomly assigned to undergo either intensive glycemic control (targeting a glycated hemoglobin level EYE Substudy: EYE Substudy participants were evaluated at two standardized and comprehensive eye examinations for the effects of the ACCORD interventions at 4 years on the progression of diabetic retinopathy by 3 or more steps on the Early Treatment Diabetic Retinopathy Study Severity Scale (as assessed from seven-field stereoscopic fundus photographs, with 17 possible steps and a higher number of steps indicating greater severity) or the development of diabetic retinopathy necessitating laser photocoagulation or vitrectomy. MIND Substudy: The cognitive primary outcome, the Digit Symbol Substitution Test (DSST) score, was assessed at baseline, 20 and 40 months. Total brain volume (TBV), the primary brain structure outcome, was assessed with MRI at baseline and 40 months in a sub-set of 632 patients. All patients with follow-up data were included in the primary analyses. Conclusions Glycemia Trial: As compared with standard therapy, the use of intensive therapy to target normal glycated hemoglobin levels for 3.5 years increased mortality and did not significantly reduce major cardiovascular events. (Action to Control Cardiovascular Risk in Diabetes Study Group, et al.,2008, PMID:18539917). Microvascular Outcomes of the Glycemia Trial: Intensive therapy did not reduce the risk of advanced measures of microvascular outcomes, but delayed the onset of albuminuria and some measures of eye complications and neuropathy. Microvascular benefits of intensive therapy should be weighed against the risk of increased total and cardiovascular disease-related mortality, increased weight gain, and higher risk for severe hypoglycemia. (Ismail-Beigi et al., 2010, PMID: 20594588) Lipid Therapy Trial: The combination of fenofibrate and simvastatin did not reduce the rate of fatal cardiovascular events, nonfatal myocardial infarction or nonfatal stroke, as compared with simvastatin alone. These results do not support the routine use of combination therapy with fenofibrate and simvastatin to reduce cardiovascular risk in the majority of high-risk patients with type 2 diabetes (ACCORD Study Group, et al., 2010, PMID: 20228404). Blood Pressure Trial: In patients with type 2 diabetes at high risk for cardiovascular events, targeting a systolic blood pressure of less than 120 mm Hg, as compared with less than 140 mm Hg, did not reduce the rate of a composite outcome of fatal and nonfatal major cardiovascular events (ACCORD Study Group, et al., 2010, PMID: 20228401). EYE Substudy: Intensive glycemic control and intensive combination treatment of dyslipidemia, but not intensive blood-pressure control, reduced the rate of progression of diabetic retinopathy (ACCORD Study Group, et al., 2010, PMID: 20587587). MIND Substudy: Although significant differences in TBV favored the intensive therapy, cognitive outcomes were not different. Combined with the unfavorable effects on other ACCORD outcomes, MIND findings do not support using intensive therapy to reduce the adverse effects of diabetes on the brain in patients similar to MIND patients (Launer et al., 2011, PMID: 21958949).

  Study phs003551

• Programmatic submission based on XML

  Programmatic submissions (XML based) For further information please check our Submission FAQs, submission quickguide as well as submission terms! Introduction Besides the Submitter Portal tool, EGA supports programmatic sequence and clinical data metadata submissions. If you are not sure what this means, you may want to explore our brief metadata introduction. Programmatic submissions are recommended for array-based submission. Moreove, it may be of help if your submission is recurrent or it is difficult to manage manually due to its sheer size. Otherwise, we highly recommend using the Submitter Portal to perform submissions. In this page we will guide you through the required steps to programmatically submit data to the EGA. Programmatic submissions require your metadata to be structured for an easy and straightforward validation and archival. It basically consists in formatting your metadata as Extensible markup language (XML) files and submitting them to the EGA using the WEBIN Before submitting metadata to the EGA, it is important to ensure that the information in your XML files is compliant with our standards. You can see further details on how these standards are maintained at EGA at our EGA Schemas documentation page. Using WEBIN, you can validate your XML files against EGA's schemas to ensure that your metadata is compliant before submission. WEBIN services WEBIN production service WEBIN test service We advise you to submit your metadata to the test service when submitting to the production service for the first time. The test service is identical to the production service except that all submissions will be discarded in the following 24 hours. This allows you to learn about the submission process without having to worry about data being submitted. Authentication Authentication is required each time a submission is made. The submission service uses HTTPS protocol for metadata encryption and identification to provide a secure submission environment. Data file upload Both Runs and Analyses reference files (e.g. FASTQ need to be uploaded to the EGA before these metadata objects are submitted. In other words, if you submit a Run that references a file that we cannot find associated with your account, the metadata submission will fail. See further details on how to upload your files in our File Upload documentation. Metadata model of the EGA Our metadata model is formed by multiple metadata objects. Check further details in our documentation at our EGA Schema documentation page. Working with EGA XMLs files Now that the basic concepts of the EGA metadata have been described, you can start preparing your programmatic submission through XML. Here you will find the guidance on how to prepare the XML files. Programmatic Submission Tutorial Video Take a look at the Programmatic Submission Tutorial Video, which explains the workflow of a programmatic submission and goes over an example metadata submission. Programmatic Submission Tutorial Video. When building your XML files, we recommend using text editors (e.g.Sublime Text or VisualStudio) that allow you to visualise the structure of the XML with ease. Furthermore, these editors constantly check the consistency of the XML structure. Alternatively, and if the submission consists of a big number of objects (specially analyses), you may find the tool star2xml handy. This tool allows for a direct conversion between metadata in a tabular format (e.g. a spreadsheet) into XMLs. Identifying objects: Aliases and center names Every EGA object must be uniquely identified within the submission account using their alias attribute. The aliases can be used in submissions to make references between EGA objects. Let us dig into EGA's use of aliases and center names: alias: every object should have a name that is unique within your submission account. Once submitted successfully, every alias will be assigned a unique and permanent accession (EGA ID). refname: when an object references another by its alias, the alias of the referenced object goes into the "refname" attribute of the referencing object. For example, if a sample has the alias "sample1", and an experiment uses this sample, then the experiment's "EXPERIMENT/SAMPLE/refname" attribute should be "sample1". center_name: The "center_name" attribute is required within the submission XML and, if not provided when the object is submitted, it will be automatically filled using your default EGA account center_name. This element is the "controlled vocabulary acronym or abbreviation that is provided to the account holder when the account is first generated". If the submitter is brokering a submission for another institute, the submitter should use their special broker account name in broker_name while the data centre acronym remains in center_name. Log-in details should have been provided when you requested a submission account. Please contact our Helpdesk team if you have any questions. run_center: Many submitting centers contract out the actual sample sequencing to another center. In these cases, the sequencing center should be acknowledged in the run_center attribute. Again, this is controlled vocabulary and the acronym should be sought from EGA helpdesk before submitting. Please contact our Helpdesk team if you have any questions. Prepare your XMLs The goal of this section is to provide sufficient information to be able to create the metadata XML documents required for programmatic submissions. Please note, the EGA utilises the XML schemas maintained at the European Nucleotide Archive (ENA). It is important due to the fact that by using a similar system, some pieces of documentation from the ENA's programmatic submission can also help you with your programmatic submission to the EGA. For example, you can submit programmatically without using a Submission XML by following the steps at Submission actions without submission XML. A submission does not have to contain all different types of XMLs. For example, it is possible to submit only a few samples; or a study that is later to be referenced. You can submit each object one by one, or submit all in a batch: you choose what method of submission works best for you. We do recommend, nevertheless, that you submit the objects to be referenced (e.g. samples or studies) first, and the objects that reference these (e.g. experiments or datasets) afterwards. You can see a graphical view of these objects and their relationships at our EGA Schemas page. Independently of the submission scenario, you will always require a Dataset XML. The entity of a dataset is what is used to control access to the given data, in the form of runs or analyses. In other words, when a requester is granted access, it is through the dataset and the objects (e.g. runs or analyses) that the dataset contains, granting access to them in one go. Given the nature of the EGA, a dataset XML will always be required for the data access. First, we will differentiate between submissions of "raw" and "processed" data: Runs and Analyses, respectively. Run data submissions Raw data derives from instruments "as is". For example, a plain sequence file (e.g. FASTQ or unaligned BAM files) would be considered raw data. A typical raw (unaligned) sequence read submission consists of 8 XMLs: Submission Study Sample Experiment Run DAC Policy Dataset When technical reads (e.g. barcodes, adaptors or linkers) are included in the submitted raw sequences, a spot descriptor must be submitted to describe the position of the technical reads so that they can be removed. The following data files can be submitted without providing spot descriptor information in the experiment/run XML: BAM files (single reads) SFF files (single reads without barcodes) FastQ files (single reads without any technical reads) Complete Genomics files Analysis data submissions Processed data is, in some way, refined raw data. This includes raw data that has been processed by some form of analysis method (e.g. alignment, noise reduction, etc.). For example, an aligned sequence (e.g. BAM file), that was created using raw FASTQ files, would be a processed file. This category includes most types of data: sequence alignment files (e.g. BAM or CRAM), clinical data (e.g. phenopackets), sequence variation files (e.g. VCF), sequence annotation, etc. A typical EGA analysis data submission consists of 7 EGA XML: Submission Study Sample Analysis DAC Policy Dataset We accept three different types of analysis data submissions: BAM files (for multiple read alignments) VCF files (for sequence variations) Phenotype files (in any format) In anycase, keep in mind that samples must be created in order to be referenced in the analyses. In other words, the provenance of the information within the BAM, VCF and phenotype files Example XMLs Below you can find a non-extensive list of example XMLs with descriptive fields (i.e. explaining what to provide in each field). Furthermore, you can also find real examples (i.e. the true value of the provided fields) in our GitHub repository. Submission XML The submission XML is used to validate, submit or update any number of other objects. The submission XML refers to other XMLs. New submissions use the ADD action to submit new objects. Object updates are done using the MODIFY action and objects can be validated using the VERIFY action. Descriptive submission XML example True values submission XML example Study XML The study XML is used to describe the study containing a title, a study type and abstract as it would appear in a publication. Descriptive study XML example True values study XML example Please use the following notation within the property "STUDY_LINKS" when including PubMed citations in the Study XML: <STUDY_LINKS> <STUDY_LINK> <XREF_LINK> <DB>PUBMED</DB> <ID>18987735</ID> </XREF_LINK> </STUDY_LINK> </STUDY_LINKS> Sample XML The sample XML is used to describe the samples used to obtain the data, whether they were sequenced, measured in any other way, or have an associated phenotype. The mandatory fields include information about the taxonomy of the sample, sex, subject ID and phenotype. For example, the mandatory attribute fields for each sample would look like these, within the array of "SAMPLE_ATTRIBUTES": <SAMPLE_ATTRIBUTES> <SAMPLE_ATTRIBUTE> <TAG>subject_id</TAG> <VALUE>free text!</VALUE> </SAMPLE_ATTRIBUTE> <SAMPLE_ATTRIBUTE> <TAG>sex</TAG> <VALUE>female/male/unknown</VALUE> </SAMPLE_ATTRIBUTE> <SAMPLE_ATTRIBUTE> <TAG>phenotype</TAG> <VALUE>Free text, EFO terms (e.g. EFO:0000574) are recommended</VALUE> </SAMPLE_ATTRIBUTE> </SAMPLE_ATTRIBUTES> Sample is one of the most important objects to be described biologically, it is highly recommended that “TAG-VALUE” pairs are generated as SAMPLE_ATTRIBUTES to describe the sample in as much detail as possible. For example, were we to give the population ancestry of the sample, we could add a new attribute to the array, in which, for example, we would indicate that the sample derives from an individual of "Mende in Sierra Leone" (MSL), with an african ancestry: <SAMPLE_ATTRIBUTE> <TAG>Population</TAG> <VALUE>MSL</VALUE> </SAMPLE_ATTRIBUTE> Given that VALUE and TAG are free text, the combinations are limitless in order to give you full flexibility on the information you want to provide. We recommend you use the Experimental Factor Ontology (EFO) to describe the phenotypes of your samples. You can provide more than one phenotype by adding more items to the array of SAMPLE_ATTRIBUTES. Phenotypes considered essential for understanding the data submission should be provided. Each phenotype described should be listed as a separate sample attribute <SAMPLE_ATTRIBUTE> </SAMPLE_ATTRIBUTE>. There is no limit to the number of phenotypes that can be submitted. If a suitable EFO accession cannot be found for your phenotype attribute, please consider using another controlled ontology database (e.g. HPO, MONDO, etc.) before using free text. Descriptive sample XML example True values sample XML example Experiment XML The experiment XML is used to describe the experimental setup, including instrument platform and model details, library preparation details, and any additional information required to correctly interpret the submitted data. Where any of these values differ between runs, a new experiment object must exist, since runs are grouped by experiments. Each experiment references a study and a sample by alias, or if previously-submitted, by accession. Pooled data must be demultiplexed by barcode for submission. Descriptive experiment ( Illumina paired read ) XML example True values experiment ( Illumina paired read ) XML example Run XML The run XML is used to associate data files with experiments and typically comprises a single data file (e.g. a FASTQ file). Please note that pooled samples should be de-multiplexed prior submission and submitted as different runs. Descriptive run XML example True values run XML example Analysis XML Given that an analysis can be used to submit any type of processed data to the EGA, we will list below an example of each of the three most common types of analysis XMLs submitted to the EGA: sequence alignments (e.g. BAM files); sequence variation (e.g. VCF files); and clinical metadata or phenotypes (e.g. phenopackets). Regardless of the type of processed data submitted in the analysis, the analysis must be associated with a Study and can reference multiple types of other objects, from samples to experiments, if they are available at the EGA. Just like with Runs, whenever a file is submitted to the EGA through an analysis object, the file MD5 checksums must be present, in order for the EGA to validate file integrity upon transfer. This also includes index files when applicable (e.g. .bai.md5 files). Ideally, any analysis that uses a reference sequence for some kind of alignment (e.g. BAM, CRAM or VCF files), would contain metadata about the alignment, such as INSDC reference assemblies and sequences, by either using accessions (e.g. CM000663.1) or common labels (e.g. GRCh37). Read alignment (BAM) Analysis XML The Analysis can be used to submit BAM alignments to EGA. Only one BAM file can be submitted in each analysis and the samples used within the BAM read groups must be associated with Samples. Descriptive bam alignments XML example True values bam alignments XML example Sequence variation (VCF) Analysis XML The Analysis can be used to submit VCF files to EGA. Only one VCF file can be submitted in each analysis and the samples used within the VCF files must be associated with Samples. Download analysis XML (VCF) Phenotype files The Analysis XML can be used to submit phenotype files to the EGA. Only one phenotype file can be submitted in each analysis and the samples used within the phenotype files must be associated with EGA Samples. Download analysis XML (Phenotype) DAC XML The DAC XML describes the Data Access Committee (DAC) affiliated to the data submission. The DAC may consist of a group or a single individual and is responsible for the data access decisions based on the application procedure described in the POLICY.XML. As with any other object, if it was already submitted to the EGA, there is no need to submit it again: you can reference an existing object within the EGA. Hence, A DAC XML does not need to be provided if your submission is affiliated to an existing EGA DAC.. Further information on DACs can be found here, and you can always contact our Helpdesk team if you have further inquiries. Descriptive dac XML example True values dac XML example Policy XML The Policy XML describes the Data Access Agreement (DAA) to be affiliated to the named Data Access Committee. Descriptive policy XML example True values study XML example Dataset XML The dataset XML describes the data files, defined by the Run.XML and Analysis.XML, that make up the dataset and links the collection of data files to a specified Policy. The dataset xml is commonly the last metadata object to be submitted, since it references multiple other entities. Please consider the number of datasets that your submission consists of. For example, a case-control study is likely to consist of at least two datasets. In addition, we suggest that multiple datasets should be described for studies using the same samples but different sequence technologies. Descriptive dataset XML example True values dataset XML example Validating and submitting your EGA Validating EGA's XMLs through Webin After you have ensured that the XMLs are properly formatted and contain all the required information. You can proceed to validate and submit your data. Use the curl command to validate your XML file: Once you have prepared your XML file and asserted you have access to Webin, you can validate your XML file programmatically against EGA's schemas using the curl command. There are multiple ways in which you can validate your XMLs. This variety has to do with the fact that: (1) there are 2 instances of Webin (test and production); and (2) that validation is a default step during submission. In other words, any time that you submit your data through Webin, it will be validated automatically before being accepted. This allows for 4 possible routes of validation, all having the same validation result: validating or submitting to either the production service or the test service of Webin. For example, directly validating a "study" object XML in the testing service (wwwdev…) would look like the following: curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" In this command, you would need to replace <USERNAME> and <PASSWORD> with your EGA account username and password, respectively. You would also replace <INPUT_FILE> with the path to your XML file. A mock example would look like the following: curl -u ega-test-data@ebi.ac.uk:egarocks -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" The validation attempt can have different results depending on the given arguments: If your XML file is valid according to EGA's schemas, you will see a message indicating that your XML file is compliant. For example, see below for our mock example, where the "success" was "true" (i.e. no validation errors found). Nevertheless, notice how the "<STUDY accession=" is empty: it is because we were simply validating, so the study did not get an accession or ID. <?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="receipt.xsl"?> <RECEIPT receiptDate="2023-04-11T15:19:28.850+01:00" submissionFile="submission-EBI-TEST_1681222768850.xml" success="true"> <STUDY accession="" alias="Mock example" status="PRIVATE"/> <SUBMISSION accession="" alias="SUBMISSION-11-04-2023-15:19:28:840"/> <MESSAGES> <INFO>VALIDATE action has been specified.</INFO> <INFO>Submission has been rolled back.</INFO> <INFO>This submission is a TEST submission and will be discarded within 24 hours</INFO> </MESSAGES> <ACTIONS>VALIDATE</ACTIONS> <ACTIONS>PROTECT</ACTIONS> If there are any errors or warnings, the tool will display them, allowing you to correct them before submitting your data to EGA. For example, in the following response, it is said that the object we were trying to submit was already existing, and therefore the "success" was "false". <?xml version="1.0" encoding="UTF-8"?> <?xml-stylesheet type="text/xsl" href="receipt.xsl"?> <RECEIPT receiptDate="2023-04-11T15:12:35.609+01:00" submissionFile="submission-EBI-TEST_1681222355609.xml" success="false"> <STUDY alias="Example!_Human Microbiome Project SP56J" status="PRIVATE" holdUntilDate="2023-03-11Z"/> <SUBMISSION alias="SUBMISSION-11-04-2023-15:12:35:576"/> <MESSAGES> <ERROR>In study, alias: "Example!_Human Microbiome Project SP56J". The object being added already exists in the submission account with accession: "ERP127584".</ERROR> <INFO>VALIDATE action has been specified.</INFO> <INFO>Submission has been rolled back.</INFO> <INFO>This submission is a TEST submission and will be discarded within 24 hours</INFO> </MESSAGES> <ACTIONS>VALIDATE</ACTIONS> <ACTIONS>PROTECT</ACTIONS> If the curl command retrieves no response at all, please double check if your username and password are correctly provided. Also notice the "ACTION=..." argument passed to the Curl command. This specifies the action to take during the call to Webin, so we do not need a "Submission" XML just for a validation attempt. See more at submission actions without submission XML. Furthermore, validation of multiple files or objects (e.g. sample, experiment, study…) can be done in a single command by adding more arguments (i.e. '-F'). For example: curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" -F "SAMPLE=@sample.xml" -F "DATASET=@dataset.xml" As mentioned above, beside "validate" action in the test environment, you can also validate your metadata by three other methods: "Validate" in the production server. From our example above, you simply need to take the "dev" away from the URL. curl -u <USERNAME>:<PASSWORD> -F "ACTION=VALIDATE" "https://www.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" "Add" in the development server. From our example above, you would simply need to replace the action: from "validate" to "add". Whatever is submitted to this service will be discarded in 24h, so whether something gets submitted or not would not matter in the long run. curl -u <USERNAME>:<PASSWORD> -F "ACTION=ADD" "https://wwwdev.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" "Add" in the productionserver. A combination of the previous two methods, which would render this attempt into a submission. This path is just to be taken when you are sure your metadata is compliant and what you want to submit. curl -u <USERNAME>:<PASSWORD> -F "ACTION=ADD" "https://www.ebi.ac.uk/ena/submit/drop-box/submit/" -F "STUDY=@study.xml" What happens after the submission of a dataset XML? Once you have completed the registration of your dataset/s please contact our Helpdesk Team to provide a release date for your study. Please note that all datasets affiliated to unreleased studies are automatically placed on hold until the authorised submitter or DAC contact contact the EGA Helpdesk for the study to be released. We strongly advise you not to delete your data until EGA Helpdesk confirms that your data has been successfully archived.

  Documentation submission/metadata/submission/programmatic-submission-xml

• GEDI: A Developmental Model of Gene-Environment Interplay in SUDs: Combined Genotype Dataset from the "Great Smoky Mountains Study" and the "Caring for Children in the Community Study".

  1. Great Smoky Mountains Study (GSMS; Costello et al. 1996, 1997) Three cohorts of boys and girls, aged 9, 11, and 13 years at intake in 1993, were selected from a rural population of some 20,000 children using a household equal probability design. A two-phase procedure was used for White and African-American youth to increase power by oversampling children at risk for psychiatric and SUDs. Parents (usually mothers) of the first stage random population sample completed a questionnaire about their child&#39;s behavioral problems. Of 4,195 subjects selected, 95% (N=3,896) of parents completed the screen. All children scoring above a predetermined threshold (the top 25% of the total scores), plus a 10% random sample of the remaining 75%, were recruited for detailed interviews. Results can be back-weighted to population levels for analyses. Half of the sample consists of females, and 6% are African Americans, reflecting the population of the study area. The interviewed sample of white and African-American subjects was 1,070 (80% of those recruited). American Indian youth were oversampled (100%) because they are an understudied group known to be at high risk for stressful events, substance disorders, and mood disorders. Of 431 age-eligible children, 350 (81% boys, 49% girls) participated. Thus, the size of total GSMS sample is 1,070 + 350 = 1,420. Data collection is complete for ages 9-26, and age 30 interviews are in progress. By age 26 a total of 9,858 interviews had been completed; the average number of interviews per subject was seven, and by age 26, 97.3% completed two or more interviews. 2. The Caring for Children in the Community Study (CCC; Angold et al., 2002) This representative study of psychiatric illness and service use in African-American and White youth took place in four rural counties in the southeastern USA. The two-stage sampling design and methods are similar to those used in the GSMS. Of 4,500 youth randomly selected from the 17,117 9- to 17-year-olds in the public school&#39;s database, 3,613 (80.0%) were successfully contacted and agreed to complete the behavioral screen. Of the 1,302 selected to participate in the study, 920 (70.7%) interviews were completed. Because CCC was also the only study in GEDI to contain more than a very few African-American participants, these were omitted from the multi-site analyses. Reprinted with permission from Cambridge University Press from Costello et al., 2013: PMID: 23461817 References: Costello et al., 1996: PMID: 8956679 Costello et al., 1997: PMID: 9184514 Angold et al., 2002: PMID: 12365876

  Study phs000852

• Bladder Cancer Organoids as a Functional System to Model Different Disease Stages and Therapy Response

  The study 'Bladder Cancer Organoids as a Functional System to Model Different Disease Stages and Therapy Response' reports the genomic characterization at the single allele level upon Whole Exome Sequencing of Bladder Cancer (BLCa) Patient Tumor (PT) samples obtained from 18 patients and corresponding Patient Derived Organoids (PDOs), implementing the SPICE pipeline (Ciani Y et al). Our cohort included 21 PTs and 22 PDOs. In this study, we generated a unique biobank resource of BLCa organoids that encompasses a broad spectrum of disease stages. We demonstrated that PDOs retain cancer heterogeneity and mutational burden. Furthermore, we observed that BLCa PDO can have different morphologies which may reflect tumor-specific features. Indeed, a solid morphology may be associated with more advanced tumors, as supported by the high PDO genomic burden and high primary tumor stage. Moreover, with our drug screening pipeline, we demonstrated the clinical relevance and feasibility of using a BLCa PDO-based drug assay for comparing the standard of care (SOC) drugs with compounds not currently in use for BLCa. Response to SOC was highly heterogeneous with approximately 50% of non-muscle invasive bladder cancer and 33% of muscle invasive bladder cancer PDOs showing no or minimal response. The most effective targeted therapy was lapatinib. We used an integrative analysis of drug response profiles with matched PDO genomic analysis to determine enrichment thresholds for candidate markers of therapy resistance and sensitivity. Importantly, by assessing the clinical history of longitudinally sampled cases, the clonal evolution of the disease could be determined and matched with PDO drug response profiles.

  Study phs003149

• Genomic Studies of Bipolar Disorder in a Large Cohort from The Netherlands

  The transcriptomes of whole blood samples of a large cohort of individuals from the Netherlands were assayed using RNA-seq. These whole blood samples included patients diagnosed with schizophrenia or bipolar disorder, family members of patients, and healthy controls. Within the whole blood dataset, about 600 of the samples were sequenced to an average of 13.9 million mapped reads per sample, while about 2,000 were sequenced to an average of 5.9 million mapped reads per sample, in order to assess changes in power to detect eQTLs based on sample size. We find that expression, defined as the log transcripts per million reads (TPMs), is highly correlated when comparing the moderate (13.9M) and lower (5.9M) coverage datasets.&nbsp;Additionally, a subset of about 150 individuals provided fibroblast cell lines which were assessed for the levels of gene expression using RNA-seq at an average of 50 million mapped reads per sample. We use downsampling techniques to generate synthetic datasets derived from this real fibroblast RNA-Seq data to explore the relationship between coverage and number individuals in an eQTL analysis.&nbsp;Corresponding individual-level genotypes for the samples included in the expression matrix are also made available. The genotypes were derived from multiple other project cohorts, each using different genotyping platforms including OmniExpress Exome, Global Screening Array, Illumina550, and PsychChip. A Plink file set of these cohorts is provided here after merging the separate project file sets and extracting only the individuals who have expression data also provided here; quality control for SNP-missingness is recommended.&nbsp;We demonstrate in this study that given a fixed budget, eQTL discovery power can be increased by lowering the sequencing depth per sample to allow for an a greater number of individuals sequenced.&nbsp;

  Study phs002856