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• 16S-based fecal microbiota composition

  The dataset reports the 16S rRNA gene sequencing of the fecal microbiota of donors from the Milieu Intérieur Cohort. The Milieu Intérieur cohort includes a total of 1,000 healthy individuals of western European ancestry, recruited in France as part of the Milieu Intérieur project. To assess their fecal microbiota composition, 16S rRNA profiles were generated from stool samples of 863 of the 1,000 donors. Human stool samples were produced at home no more than 24 hours before the scheduled medical visit and collected in a double-lined sealable bag maintaining strict anaerobic conditions. Upon reception at the clinical site, the fresh stool samples were aliquoted and stored immediately at -80°C. DNA was extracted from stool and barcoding PCR was carried out using indexed primers targeting the V3-V5 region of the 16S rRNA gene. Equal volumes of normalized PCR reaction were pooled and thoroughly mixed. The amplicon libraries were sequenced on Illumina MiSeq.

  Dataset EGAD00001004979

• Cell and Circuit-Specific Exploration of HIV Neurogenomics in Context of Opiate and Cocaine Misuse

  Utilizing frozen postmortem brain tissue from the Manhattan HIV Brain Bank, we performed cell-type-specific, genome-wide sequencing of three different types: 1) single-nucleus RNA-sequencing (snRNA-seq), 2) in situ Hi-C, and 3) HIV integration site sequencing (IS-seq). We assayed tissue from three different donor types: 1) HIV-uninfected control (HIV-), HIV-infected (HIV+), and HIV-infected with HIV encephalitis (HIVE), who served as a positive control for active CNS viral infection. The diagnosis of HIVE was made by a board-certified neuropathologist on routine histopathology, based on the presence of a microglial nodule encephalitis with characteristic multinucleated syncytial cells and staining for HIV p24 antigen. Other HIV-infected individuals (the HIV+ group) did not have this histologic evidence of active HIV brain replication, and were variable with regard to cART status and virologic control prior to death. Donor characteristics, including ante-mortem plasma HIV loads, CD4 counts, and cART status, were documented. Quality controls were used for each assay: For snRNA-seq we applied filters to remove low quality nuclei from analysis and performed experiments in which mouse tissue was mixed with human tissue to determine a reliable HIV read count threshold. For Hi-C, we used paired HIV- and HIVE samples and processed all samples in parallel, at the same time. Correlation analysis was used to ensure biological replicates were aligned. For IS-seq, each time the assay was run, a positive and negative control were included. This allowed us to ensure a lack of contamination in IS-seq libraries and that, when a particular sample failed to yield library, this was due to low levels of HIV rather than a failure of the assay. Altogether, we built an integrative dataset from 79 sequencing files, including snRNA-seq, and cell type specific Hi-C, IS-seq, and ChIP-seq datasets. Human autopsy brain samples were collected by the Manhattan HIV Brain Bank (MHBB, U24MH100931), using protocols under the supervision of the Icahn School of Medicine at Mount Sinai (ISMMS) Institutional Review Board. Written informed consent was obtained either from decedents or their primary next of kin. Major Findings: Reorganization of open/repressive (A/B) compartment structures in HIVE microglia encompassing 6.4% of the genome was linked to transcriptional activation of interferon (IFN) signaling and cell migratory pathways and was partially recapitulated by IFN-gamma stimulation of cultured microglia. In contrast, decreased expression and repressive compartmentalization of genes regulating neuronal health and signaling was seen in both HIVE and HIV+ microglia. IS-seq recovered 1,221 integration sites in the brain that displayed distinct genomic patterns as compared to peripheral lymphocyte integration and were enriched for chromosomal domains newly mobilized into a permissive chromatin environment in HIVE microglia. Viral transcription occurred in a subset of highly activated microglia comprising 0.003% of all nuclei in HIVE brain. Our findings point to a disruption of microglia-neuronal interactions in the HIV infected brain and an interrelation of retroviral integration and expression with interferon-associated remodeling of the microglial 3D genome during progression to HIVE. Search terms: HIV, postmortem brain, microglia, substance abuse, viral integration, chromosomal conformation capture, Hi-C, chromatin, single nuclei RNA-seq, Irf8, NeuN, HIV encephalitis, neuron-microglia interaction, cytokine

  Study phs003080

• Defining Cutaneous Gene Expression Signatures in Juvenile Dermatomyositis

  Skin inflammation in juvenile dermatomyositis (JDM) can signal disease onset or flare up and prevent complete disease remission. Our objective was to evaluate JDM cutaneous expression signatures through tape stripping in both lesional and non-lesional skin and as compared to paired blood. A total of 28 JDM and 20 control (CTL) patients participated in the study. All patients had tape strip sampling of non-lesional (NL) skin at enrollment visit. Within our JDM cohort, paired lesional (L) skin was additionally sampled if rash was present. 16/28 of JDM patients had at least one additional skin sample associated with a follow-up (FU) visit (total number of follow-up samples included = 26 NL and 4 L). We identified a common innate immune signature in both lesional and non-lesional JDM skin. Using unsupervised hierarchical clustering of skin expression data, we distinguished a JDM molecular subgroup characterized by a mitochondrial dysfunction signature. In comparison to blood expression data, we determined that skin may more effectively highlight the JDM subgroup characterized by a mitochondrial dysfunction expression signature. Data available include bulk RNA-sequencing data from tape strips and blood of the JDM and control patients from this study.

  Study phs003884

• National Cancer Institute (NCI) Genome Wide Association Study (GWAS) of Lung Cancer in Never Smokers

  A genomewide study of lung cancer in never smokers Abstract and specific aims In the United States, lung cancer incidence and mortality rates have been steadily declining over the past decade, following decline in the prevalence of tobacco smoking. However, lung cancer remains the leading cause of cancer death, killing more patients than breast, colon, and prostate cancers combined. Although tobacco smoke is the predominant risk factor for development of lung cancer, some patients develop the disease without a history of tobacco smoking. About 10 - 15% of all lung cancers occur in lilfetime never smokers. This figure will increase as the proportion of never smokers increases in the population. Even at present rates, lung cancer in never smokers, if considered a separate disease, is 6th to 8th top cause of cancer death. The growing number of never smokers in the USA and other countries emphasizes the importance of understanding the epidemiology and biology underlying lung cancer in this group. Genetic polymorphisms associated with the risk of lung cancer in never smokers are expected to overlap with those associated with the risk of lung cancer in ever smokers only partially. Epidemiological, molecular and clinical data suggest that molecular mechanisms of LC may differ in smokers and non-smokers, implying that lung cancer in never smokers is a different disease compared to the lung cancer in smokers. One can expect that there should be stronger genetic component in the control lung cancer in never smokers because effects of the genetic factors in never smokers are unmasked by the lack of tobacco smoke exposure. The genetic epidemiology of lung cancer in never smokers has not been well explored, largely because of difficulties in accruing the needed sample size for association studies. We propose a multicenter (total 14 sites from the US and Europe) genomewide association study of lung cancer in never smokers with the following specific aims: Aim 1: To identify candidate SNPs influencing risk for lung cancer in never smokers using Discovery sample. In the Discovery phase we will genotype 1256 Caucasian cases and 1365 age- and gender-matched never smoker controls using the Illumina Human660W-Quad platform. In addition, we will include in the analysis 284 cases and 175 matched controls already genotyped on the 610Quad platform. In this phase we will only include the study sites that have collected blood specimens (MDACC, Mayo Clinic, Karmanos Cancer Institute, The University of Liverpool Cancer research Centre, Institute of Cancer Research in Sutton, and Lunenfeld Research Institute in Toronto, Canada). All the samples will be sent to the independent lab for genotyping, to reduce site-specific technical artifacts. The final sample will consist of 1540 cases and 1540 controls matched by study site. Aim 2: To perform the second phase (validation) analysis of significant SNPs identified in aim 1 using an independent set of cases and controls. SNPs associated with risk at the significance level of 0.01 or below in the discovery set will be included in the replication phase. The proposed threshold guarantees an adequate power to retain SNPs with the typical effect size of 1.3. We plan to carry 6000-7000 SNPs for validation. The independent replication set will include 800 cases and 800 controls, mostly from sites that collected tissue (Mayo Clinic, Karmanos Cancer Institute, UT Southwestern) or buccal specimens (UCLA), but also blood samples (Imperial College London, University of Pennsylvana, German Cancer Research Center, Heidelberg, National Research Center for Environment and Health, Neuherberg, Carmel Medical Center, Haifa). We will then perform a joint analysis to test the significance of the SNPs identified in the first stage using a stringent critical p-value of 10-7. There will be 2340 cases and 2340 controls in the joint set. Based on our experience with GWAS in smokers and assuming that genetic component in lung cancer risk in never smokers can be higher than genetic component in smokers, we expect to identify about 5-10 candidate regions associated with lung cancer risk in never smokers. Aim 3: To identify and explore pathways associated with the risk of lung cancer in never smokers. Results of the number of studies on the molecular mechanisms and drug response suggest that lung cancer in never smokers is a different disease and different pathways will be associated with lung cancer risk in non-smokers and smokers. To identify pathways and molecular functions associated with lung cancer risk in never smokers we will apply Ingenuity and DAVID bioinformatics tools. We will use at least 300 top candidate genes identified in joint and discovery analysis. The reason why we select rather large number of candidate genes for functional annotation is two-fold: 1. Both algorithms are looking for enrichment of pathways and function by most significant genes and they produce statistically robust results only when number of genes is relatively high. 2. Despite the fact that this study will be largest possible for never smokers we still are underpowered to detect SNPs with relatively small effect size. But though those SNPs will not reach genome wide level of significance they will tend to be on the top of the list. In other words genes from the gray zone (significant on individual level and non-significant for genome wide level) are expected to be enriched by true discoveries. True discoveries are likely to be associated with limited number of pathways / functions while false positives are expected to be uniformly distributed across functions and pathways. Therefore significant clustering of the gene to a given function will suggest that that those genes are true discoveries. This is the first GWAS aiming at identifying the genetic control of susceptibility to lung cancer in Caucasian never smokers. We will combine the available resources from the multiple sites to achieve the sample size sufficient for this study. The study will identify genetic architecture of the predisposition to the lung cancer in never smokers.

  Study phs000634

• T2D-GENES Project 2: San Antonio Mexican American Family Studies

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to T2D in multiple ethnic groups using next generation sequencing. T2D-GENES Project 2 is a complex pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence (WGS) information from 1,043 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas. The major objectives of this study are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. The sampled individuals are obtained from two studies: the San Antonio Family Heart Study (SAFHS) and the San Antonio Family Diabetes/Gallbladder Study (SAFDGS), collectively referred to as the San Antonio Mexican American Family Studies (SAMAFS). The strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The final data set includes whole genome sequence data for 607 individuals. After quality control, 585 sequenced individuals provide data for family based imputation, using Merlin linkage analysis software, into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. Extensive phenotype data is provided for 1048 individuals. These include 5 sequenced individuals who do not belong to any of the 20 large pedigrees. Phenotype information was collected between 1991 and 2011 in the two contributing longitudinal studies. SAFHS participants may have information from up to 5 visits, and SAFDGS participants may have up to 4 visits. The clinical variables reported are coordinated with T2D-GENES Project 1 (multi-ethnic exome sequencing) and include T2D status and age at diagnosis, glycemic traits (fasting and 2 hour glucose and insulin), blood pressure, blood lipids (total cholesterol, HDL cholesterol, calculated LDL cholesterol and triglycerides), clinical chemistry (cystatin c, glutamic acid decarboxylase antibody titer (GadAb), creatinine, adiponectin and leptin). Glycated hemoglobin (HbA1c) was not measured for these individuals and insulin C-peptide is not included in this data set. Additional phenotype data include the medication status at each visit, classified in four categories as any current use of diabetes, hypertension or lipid-lowering medications, and, for females, current use of female hormones. Anthropometric measurements include age, sex, height, weight, hip circumference, waist circumference and derived ratios. Each phenotype variable has an initial summary column containing the most recent non-missing measurement for each individual, followed by the five potential time points for each individual, the number of non-missing measurements, and the age and year for the most recent non-missing measurement. For historical reasons, the order in which variables are presented on the dbGaP web site differs from their order in the data download file. When reading the comment fields for each variable, please note that commas are omitted to support data exchange in .csv format.

  Study phs000462

• Heart Failure Network: Diuretic Optimization Strategies Evaluation in Acute Heart Failure (HFN DOSE-BioLINCC)

  ObjectivesThe DOSE study sought to evaluate the most effective dosing (high vs. low) and administration (continuous infusion vs. intermittent boluses) combination of the diuretic Furosemide in the treatment of patients with acute decompensated heart failure.BackgroundAcute decompensated heart failure is the most common cause of hospital admissions among patients older than 65 years of age and is responsible for more than 1 million hospitalizations annually in the United States. Intravenous loop diuretics are an essential component of current treatment and are administered to approximately 90% of patients who are hospitalized with heart failure. Despite decades of clinical experience with these agents, prospective data to guide the use of loop diuretics are sparse, and current guidelines are based primarily on expert opinion. As a result, clinical practice varies widely with regard to both the mode of administration and the dosing.SubjectsA total of 308 patients were enrolled between March 2008 and November 2009 at 26 clinical sites in the United States and Canada. DesignThe DOSE study was a prospective, randomized, double-blind, controlled trial with a 2-by-2 factorial design. Patients were randomly assigned to either a low-dose strategy (total intravenous furosemide dose equal to their total daily oral loop diuretic dose in furosemide equivalents) or a high-dose strategy (total daily intravenous furosemide dose 2.5 times their total daily oral loop diuretic dose in furosemide equivalents) and to administration of furosemide either by intravenous bolus every 12 hours or by continuous intravenous infusion.The study treatment, with group assignments concealed, was continued for up to 72 hours. At 48 hours, the treating physician had the option of adjusting the diuretic strategy on the basis of the clinical response. An assessment of biomarkers, including creatinine, cystatin C, and N-terminal pro-brain natriuretic peptide, was performed at a central core laboratory at baseline, 72 hours, and 60 days. Patients were followed for clinical events to day 60. The coprimary end points were patients' global assessment of symptoms, quantified as the area under the curve (AUC) of the score on a visual-analogue scale over the course of 72 hours, and the change in the serum creatinine level from baseline to 72 hours.ConclusionsAmong patients with acute decompensated heart failure, there were no significant differences in patients' global assessment of symptoms or in the change in renal function when diuretic therapy was administered by bolus as compared with continuous infusion or at a high dose as compared with a low dose. (Felker et. al., 2011, PMID: 21366472)

  Study phs003524

• NHLBI TOPMed: The Genetic Epidemiology of Asthma in Costa Rica

  This administrative supplement to the project, "The Genetic Epidemiology of Asthma in Costa Rica" (R37 HL066289) is in response to NOT-HL-14-029 to perform whole genome sequencing (WGS) on existing NHLBI populations. We focus on asthma because of its public health significance. Asthma affects 26 million U.S. children and adults, remains a major cause of morbidity (one-half million hospitalizations a year) and is the most common cause of school and work days lost. Asthma-related costs are estimated to be over $12.7 billion annually. The Asthma Probands for both the extended pedigrees and the trios utilized in this study were selected on the basis of a physician diagnosis of asthma; a history of recurrent asthma attacks or at least 2 respiratory symptoms; and either airway hyperresponsiveness to methacholine or significant response to bronchodilator (Albuterol) administration. These criteria are identical to the criteria used in the Childhood Asthma Management Program (CAMP). The three primary goals of this project are to: (1) identify common and rare genetic variants that determine asthma and its associated phenotypes (height, weight, IgE level, lung function, bronchodilator response, steroid treatment response) through whole genome sequencing (WGS); (2) perform novel family based association analysis of our WGS data to identify novel genes for asthma; and (3) integrate epigenomic and transcriptomic data with our WGS data and determine the epistatic interactions present using systems genomics approaches. Identification of the molecular determinants of asthma remains an important priority in translational science. Genome-wide association studies (GWAS) have been successful in this regard, identifying at least 10 novel susceptibility genes for asthma. However, as with most complex traits, the variants identified by GWAS explain only a fraction of the estimated heritability of this disorder. Herein, we propose a novel family-based study design and state-of-the-art genome sequencing techniques to map a set of sequence variants for asthma and its associated phenotypes and assess the interrelationships of the identified genes and variants using systems genomics methods. We have assembled a team of investigators highly-skilled and expert in whole genome sequencing (Drs. Michael Cho and Benjamin Raby), genetic association analysis (Drs. Scott T. Weiss, Jessica Lasky-Su and Christoph Lange), integrative genomics (Drs. Raby, Kelan Tantisira, Augusto Litonjua and Dawn DeMeo), and systems genomics (Drs. Weiss, Amitabh Sharma, Lange and Raby) to address this important problem with both a novel study design and data set.

  Study phs000988

• fragmentomic features of individuals with different cfDNA concentrations

  The uploaded data includes sequencing data of 862 individuals from the nasopharyngeal carcinoma (NPC) screening study. Samples from this cohort were sequenced using targeted sequencing methods for the Epstein Barr Virus (EBV) and selected autosomal DNA, but only ‘off-target’ reads were used for fragmentomic analyses. We have also performed genome-wide (non-targeted sequencing) for 1) Individuals with the highest and lowest cell-free DNA concentration (40 individuals); 2) A subsequent collection of the subjects with the highest and lowest DNA concentrations after six years (26 individuals); 3) 30 cases of pregnancy and 4) 20 patients with hepatocellular carcinoma. All sequencing data are of extracted plasma cfDNA from human subjects. The targeted sequencing samples from 862 individuals were sequenced on the NextSeq500 System (Illumina) and aligned to the EBV genome (AJ507799.2) and the human genome (hg19). The alignments were provided in bam format. The original fastq files of the remaining non-target sequencing samples were provided.

  Dataset EGAD50000000970

• Single cell targeted DNA-sequencing (and antibody sequencing) of high hyperdiploid B-ALL

  This dataset contains all sequencing data of the publication "Single-cell DNA and Surface Protein Characterization of High Hyperdiploid Acute Lymphoblastic Leukemia at Diagnosis and During Treatment". We provide both the raw fastq-files as well as the processed data in the form of .h5 files. There are 13 patients: XJ176, XH135, XJ180, XI145, XI148, XI167, XI150, XJ175, XJ178, XI162, XF98, XG111 and XG115. Of 9 patients, also follow-up samples during/after treatment were sequenced: XJ180, XI145, XI148, XI167, XI150, XJ175, XJ178, XI162 and XG111. To identify the cell types and distinguish between normal and leukemic cells, cell surface proteins were also captured for 6 samples: XF98, XG111 (at diagnosis and during treatment), XG115, XI162 (after treatment) and XJ175 (after treatment). All samples were processed on the MissionBio platform with a custom amplicon panel, and DaB-seq for the combined targeted DNA and protein sequencing.

  Dataset EGAD50000000829

• IMCISION RNAseq

  RNA sequencing of 32 primary head and neck squamous cell carcinoma (HNSCC) samples prior to treatment with neoadjuvant anti-PD-1 (n=6) or anti-PD-1 + anti-CTLA-4 (n=26) immunotherapy, and 30 paired on-treatment HNSCC samples (i.e. after neoadjuvant immunotherapy). RNA quantity used: 10ng. Library Preparation Kit: SMART Stranded Total RNA Seq Kit (Takara). Sequencing parameters: NovaSeq 6000, 2x 100 bp. File type: fastQ

  Dataset EGAD00001008127