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• Psoriatic_arthritis

  This is a pilot single cell mRNA sequencing experiment to study immune cells in psoriatic arthritis.

  Study EGAS00001002104

• Benchmarking_CRISPR_Whole_genome_Drop_out_Screen___B_S

  This study is a benchmarking exercise to explore potential source of variation between different CRISPR drop out libraries.

  Study EGAS00001002931

• Germline sequencing

  Detection of SNVs/indels in the germline of pediatric cancer patients with a focus on CHEK2 germline variants.

  Study EGAS00001006254

• Germline sequencing

  Detection of SNVs/ indels in the germline of pediatric cancer patients with a focus on CHEK2 germline variants

  Study EGAS00001006705

• Paired diagnostic and relapse medulloblastoma sequencing

  Whole exome and targeted panel sequencing in a cohort of paired diagnostic and relapse medulloblastoma samples.

  Study EGAS00001007120

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015302

• Genome and transcriptome sequence data from a glioblastoma tumor patient

  Genome and transcriptome sequence data from a glioblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015288

• Genome and transcriptome sequence data from a glioblastoma tumor patient

  Genome and transcriptome sequence data from a glioblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015300

• Genome and transcriptome sequence data from a ependymoma tumor patient

  Genome and transcriptome sequence data from a ependymoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015287

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015294

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015296

• Genome and transcriptome sequence data from a pineoblastoma tumor patient

  Genome and transcriptome sequence data from a pineoblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015280

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015293

• Genome sequence data from a GBM patient PT-AR3050

  Genome sequence data from a GBM patient PT-AR3050

  Dataset EGAD00001004226

• WGS data from a GBM patient PT-WP9124

  WGS data from a GBM patient PT-WP9124

  Dataset EGAD00001004264

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015309

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015316

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015337

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015332

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015338

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015264

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015265

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015267

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015270

• Genome and transcriptome sequence data from a angiosarcoma tumor patient

  Genome and transcriptome sequence data from a angiosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015272

• Genome and transcriptome sequence data from a craniopharyngioma tumor patient

  Genome and transcriptome sequence data from a craniopharyngioma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015273

• Genome and transcriptome sequence data from a neuroblastoma tumor patient

  Genome and transcriptome sequence data from a neuroblastoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015277

• Genome and transcriptome sequence data from a osteosarcoma tumor patient

  Genome and transcriptome sequence data from a osteosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015278

• Genome and transcriptome sequence data from a angiosarcoma tumor patient

  Genome and transcriptome sequence data from a angiosarcoma patient, generated as part of the BC Cancer Agency's Pediatric Personalized Onco-Genomics study

  Dataset EGAD00001015290

• 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

• Prevention and Early Treatment of Acute Lung Injury Network - Reevaluation of Systemic Early Neuromuscular Blockade (PETAL ROSE-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP. Available Data: The data available for request now include Long Term Outcome data.Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from PETAL ROSE include Plasma, DNA, Whole Blood, and Urine. Please note that use of biospecimens in genetic research is subject to a tiered consent.Objectives: To determine the efficacy and safety of early neuromuscular blockade with concomitant heavy sedation as compared with a strategy of usual care with lighter sedation targets in patients with moderate-to-severe ARDS.Background: It has been well established that the approaches used for the application of mechanical ventilation in patients with acute respiratory distress syndrome (ARDS) can affect survival and outcomes after discharge from the intensive care unit (ICU). A large, multicenter trial conducted a decade before this study reported that the early administration of a 48-hour infusion of neuromuscular blockade in patients with moderate-to-severe ARDS (defined by a ratio of the partial pressure of arterial oxygen [Pao2] to the fraction of inspired oxygen [Fio2] of Participants: There were 1006 participants.Design: PETAL-ROSE was a multicenter, unblinded, randomized trial of patients with moderate-to-severe ARDS. Participants were randomly assigned in a 1:1 ratio to receive 48 hours of continuous neuromuscular blockade with concomitant deep sedation (intervention group) or to receive usual care without routine neuromuscular blockade and with lighter sedation targets (control group).Patients in the intervention group who were not under deep sedation at baseline were deeply sedated within 4 hours after randomization. Subsequently, patients in this group received an intravenous bolus of 15 mg of cisatracurium, followed by a continuous infusion of 37.5 mg per hour for 48 hours. After the 48-hour trial intervention period, decisions regarding further use of neuromuscular blockade, including the choice of agent, were left to the discretion of the treating clinician. Neuromuscular blockade could be stopped early if the patient met the criteria for freedom from mechanical ventilation (Fio2 ≤0.40 and PEEP ≤8 cm of water) for at least 12 hours. All patients were treated with a strategy of low tidal volume ventilation within 2 hours after randomization and a high PEEP strategy for up to 5 days after randomization. Assessors who were unaware of the group assignment interviewed surviving patients or their proxies at 3, 6, and 12 months after randomization. The primary end point was in-hospital death from any cause at 90 days (in-hospital was defined as the time in the trial hospital plus transfer to another hospital, including the time in long-term acute care facilities). Conclusions: After the second interim analysis, the decision to stop the trial for futility was made independently by the data and safety monitoring board.In critically ill patients identified shortly after the diagnosis of moderate-to-severe ARDS, the addition of early continuous neuromuscular blockade with concomitant deep sedation did not result in lower mortality than a usual-care approach to mechanical ventilation that included lighter sedation targets.

  Study phs003878

• Targeted_sequencing_of_genes_recurrently_mutated_in_AML

  Background Massively parallel sequencing technology has transformed cancer genomics. It is now feasible, in a clinically relevant time-frame, for a clinically manageable cost, to screen DNA from patient tumours for mutations essentially genome-wide. The challenge for personalised medicine will be to increase the sample size to thousands or tens of thousands of well-characterised cases in order to attain sufficient statistical power to stratify patients accurately across the complexity and genomic heterogeneity expected for most of the common tumour types. Currently, whole genome sequencing on this scale is not feasible, and targeted sequencing of relevant portions of the genome will be required. Pilot data We have developed protocols for large-scale, multiplexed sequencing of 100-200 genes in thousands of samples. Essentially, using robotic technology, genomic DNA from the cancer specimen is processed into sequencing libraries with unique DNA barcodes, thereby allowing sequencing reads to be attributed to the sample they derive from. Currently, these sequencing libraries can be generated in a 96-well format using fully automated protocols, and we are exploring methods to expand this to a 384-well format. The sequencing libraries are pooled and hybridized to custom sets of RNA baits representing the genomic regions of interest. Sequencing of the pulled-down libraries is done in pools of 48-96 samples per lane of an Illumina Hi-Seq. This protocol is already implemented at the Sanger Institute. We have published proof that somatic mutations in novel cancer genes can be identified from exome-wide sequencing. In unpublished pilot data, we have established the feasibility of robotic library production, custom pull-down, and multiplexed sequencing of barcoded libraries for 100 known myeloid cancer genes across 760 myelodysplasia samples. Highlights of the data thus far analysed reveal that the coverage is remarkably even between samples; when 96 samples are run, average coverage per lane of sequencing is ~250, with 90-95% of targeted exons covered by >25 reads; known mutations can be discovered in the data set; and the protocol is amenable to whole genome amplified DNA. The bioinformatic algorithms for identification of substitutions and indels in pull-down data are well-established; we have pilot data proving that copy number changes, LOH and genomic rearrangements in specific regions of interest can also be identified by tiling of baits across the relevant loci. Proposal We propose to apply this methodology to 10000 samples from patients with AML enrolled in clinical trials over the last 10-20 years. Oncogenic point mutations and potentially genomic rearrangements will be identified, and linked to clinical outcome data, with a view to undertaking the following sorts of analyses: • Identification of co-occurrence, mutual exclusivity and clusters of driver mutations. • Correlation of prognosis with driver mutations and potentially gene-gene interactions • Exploration of genomic markers of drug response Ultimately, we would like to be in a position to release the mutation data together with matched clinical outcome data to genuine medical researchers via a controlled access approach, possibly within the COSMIC framework (www.sanger.ac.uk/genetics/CGP/cosmic/). The vision here is to generate a portal whereby a clinician faced with an AML patient and his / her mutational profile can obtain a ‘personalised’ prediction of outcome, together with a fair assessment of the uncertainty of the estimate. With a sufficient sample size, there would also be the potential to develop decision support algorithms for therapeutic choices based on such data.

  Study EGAS00001000408

• Genetic Predictors of Adverse Radiotherapy Effects (Gene-PARE)

  The goal of this study was to identify SNPs and CNPs that are associated with development of normal tissue toxicities resulting from radiotherapy for prostate cancer. The study population includes approximately 1,400 men treated with brachytherapy, external beam radiation therapy, or a combination of the two treatments, and assessed for adverse effects at baseline and following radiotherapy. Three toxicity endpoints were investigated using a two-stage GWAS approach: urinary morbidity, rectal bleeding and erectile dysfunction. The study sample was split into a discovery set (N=367) and a replication set (N=417), and an additional 647 samples, which were not part of this original cohort, were also included as an independent replication set. The replication set was developed via collaboration developed under the framework of the Radiogenomics Consortium (RGC). The long-term goal of this project, and other radiogenomics projects lead by the RGC, is two-fold: 1) Develop an assay capable of predicting which cancer patients are most likely to develop radiation injuries resulting from treatment with a standard RT protocol, and 2) Obtain information to assist with the elucidation of the molecular pathways responsible for radiation-induced normal tissue toxicities. These studies focus on multiple cancer types including prostate, breast, lung, and head and neck cancers.

  Study phs000772

• The National Heart, Lung, and Blood Institute (NHLBI)-funded Next Generation Genetic Association Studies (NextGen) Consortium: Phenotyping Lipid traits in iPS derived hepatocytes Study (PhLiPS Study)

  The goal of the PhLiPS study is to create a library of induced pluripotent stem cell (iPSC) lines and iPSC-derived hepatocytes of diverse genotypes for use in metabolic profiling and interrogating lipid phenotypes. These cell lines were created as a part of the Next Generation Genetic Association Studies (Next Gen) Program, which was a five-year, $80 million program to investigate functional genetic variation in humans by assessing cellular profiles that are surrogates for disease phenotypes. To achieve this, researchers from multiple institutions across the U.S. were awarded grants to derive iPSC lines from more than 1,500 individuals representing various conditions as well as healthy controls for use in functional genomic ("disease in a dish") research. This extensive panel includes a diverse set of age, gender, and ethnic backgrounds, and therefore will be an invaluable tool for evaluations across demographics. Further enhancing the utility of these cell lines are data sets such as phenotyping, GWAS, genome sequencing, gene expression and -omics analyses (e.g., lipidomic, proteomic, methylomic) that can be matched to the cell lines. The PhLiPS Study focuses on individuals free of cardiovascular disease or with lipoprotein metabolism disorders in the community served by the Hospital of the University of Pennsylvania.

  Study phs001341

• Multicenter AIDS Cohort Study (MACS)

  The Multicenter AIDS Cohort Study (MACS) - now part of the MACS-WIHS Combined Cohort Study (MWCCS) investigates the epidemiology of human immunodeficiency virus (HIV) infection among men who have sex with men. Over 7,000 participants volunteered for semiannual interview, physical examination, and laboratory testing across the 325 years of the study, in four metropolitan areas of Los Angeles, Chicago, Baltimore/Washington (DC) and Pittsburgh. The study aimed to identify risk factors for occurrence and clinical expression of the HIV infection, and to establish a repository of biologic specimens for future study. Study visits included detailed questions covering HIV-related symptoms and utilization of health services, demographic and psychosocial characteristics, a quality of life survey, a physical examination, a detailed form on medications used as prophylaxis and/or treatment, a neuropsychological screening and examination, blood samples to do measure hematologic variables including enumeration of T-cell subsets and HIV viral load and evaluate genetic risk factors via genome wide association studies using data generated using the Infinium Multi-Ethnic Global BeadChip genotyping array in all participants. Men who have sex with men, with and without HIV infection were enrolled in the MACS. MACS data continues to be available through the merged MWCCS cohort.

  Study phs002226

• Pancreatitis after Treatment for Acute Lymphoblastic Leukemia (SJIRB XPD04-123 and XPD05-078)

  A complication of acute lymphoblastic leukemia (ALL) treatment is acute pancreatitis, which is one of the common causes of asparaginase intolerance. To determine clinical and genetic risk factors for pancreatitis, we studied a cohort of children and young adults with ALL enrolled on COG trials (9904/9905/9906, AALL0232) and on St. Jude trial Total XV. We performed a genome-wide association study using germline DNA collected from blood in patients at remission in this cohort of 5185 patients and in an independent case-control group of 213 patients on AALL0331. The frequency of pancreatitis in the cohort was 2.3% (117 of 5185). No common variants reached genome-wide significance, but a rare nonsense variant rs199695765 in CPA2, encoding carboxypeptidase A2, was highly associated with pancreatitis (odds ratio = 587, 95% confidence interval 66.8-5166, P = 9.0 x 10-9). A gene-level analysis showed an excess of additional CPA2 variants in patients who did versus those who did not develop pancreatitis (P = 0.018). Sixteen CPA2 SNPs were associated (P < 0.05) with pancreatitis, and 13 of 24 patients who carried at least one of these variants developed pancreatitis. Biological functions that were overrepresented by common variants modestly associated with pancreatitis included purine metabolism and cytoskeleton regulation.

  Study phs001350

• Whole genome sequencing of core-binding factor leukemia

  Pediatric de novo acute myeloid leukemia (AML) is a heterogeneous disease that can be divided into clinically distinct subtypes based on the presence of specific chromosomal abnormalities or gene alterations. One of the best characterized subtypes of AML involves leukemias with alterations of the core-binding factor (CBF)-complex, which comprises the FAB subtypes M2 and M4Eo and associates with a favorable outcome. Patients with the AML M2 subtype harbor a translocation between chromosomes 8 and 21 [t(8;21)] that yields the chimeric fusion gene RUNX1(AML1)-RUNX1T1(ETO), while patients with AML M4Eo express the chimeric fusion gene CBFβ-SMMHC(MYH11) as a result of an inversion/translocation event of chromosome 16 [inv(16)/t(16;16)]. In an effort to define the total complement of genetic changes in CBF-leukemia, we performed paired-end whole genome sequencing (WGS) on diagnostic leukemia blasts and matched germ line samples from 17 pediatric CBF-leukemia patients using the Illumina platform. Somatic alterations, including single nucleotide variations (SNVs) and structural variations (SVs), including insertions, deletions, inversions, and inter- and intra-chromosomal rearrangements, were detected using complementary analysis pipelines (Bambino, CREST and CONSERTING). Recurrent screening of identified mutations will be performed in a cohort of approximately 94 cases of CBF-leukemias.

  Study phs000414

• NextGen Consortium: GENESiPS Study: Identifying the Gene Networks of Insulin Resistance

  Variability in induced pluripotent stem cell (iPSC) lines remains a roadblock for disease modeling and regenerative medicine. Through linear mixed models we have described different sources of gene expression variability from RNA sequencing data in 317 human iPSC lines from 101 individuals. We found that ~50% of genome-wide expression variability is explained by variation across individuals and identified a set of expression quantitative trait loci that contribute to this variation. These analyses coupled with allele specific expression show that iPSCs retain a subject-specific gene expression pattern. Pathway enrichment and key driver analyses, based on predictive causal gene networks, found that Polycomb targets explain a significant part of the non-genetic variability present in iPSCs within and across individuals. These publically available iPSC lines and genetic datasets will be a resource to the scientific community and will open new avenues to reduce variability in iPSCs and improve their utility in disease modeling. SNP array data from individuals included in RNA-seq transcriptome profiling study of human induced pluripotent stem cells to characterize gene expression variation across individuals and within multiple iPSC lines from the same individual. Genotyping was performed on patient blood. Data availability: SNP-genotyping: dbGaP - current study RNA-seq counts: GEO - GSE79636 FASTQ files: SRA - SRP072417

  Study phs001139

• Integrated Personal omics Processing (iPoP) Longitudinal multi-omics profiling of prediabetes

  Type 2 diabetes mellitus (T2D) is a significant health problem. Close to 20 million individuals in the United States have T2D, and 79 million aged 20 years or older are clinically pre-diabetic, with a 5-year conversion rate of 10% to 23% from prediabetes to T2D. In a collaborative effort to systematically understand diabetes and its etiology, the team is comprised of leading experts in research on both the human host as well as the microbiome, as properties of both are likely relevant in T2D development. For a better elucidation of mechanisms of onset and progression of T2D disease, the group is performing a detailed analysis of the biological processes that occur in the microbiome and human host by longitudinal profiling of patients at risk for T2D. Both microbiome and host profiles are being analyzed by state-of-the-art omics platforms, and these large-scale and diverse data sets will be integrated to determine the dynamic pathways that change during the onset and progression of T2D, especially during viral infections and other stresses. This longitudinal study is expected to reveal changes in the microbiome and host at an unprecedented level of detail, and identify molecules and pathways that play important roles in diabetes onset and progression.

  Study phs001719

• Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance through Serial Biopsies and Comprehensive Analytics

  This dataset accompanies the manuscript "Characterizing Advanced Breast Cancer Heterogeneity and Treatment Resistance Through Serial Biopsies and Comprehensive Analytics". In this study we discuss the clinical implications and consequences of molecular heterogeneity in a metastatic breast cancer patient identified through serial biopsies, multi-omic analysis, and longitudinal patient monitoring, performed through the precision oncology program, Serial Measurements of Molecular and Architectural Responses to Therapy (SMMART). This case study describes a metastatic breast cancer patient with a highly heterogenous tumor that began as ER positive/HER2 negative on diagnosis, then was found to be ER negative/HER2 positive in a metastatic liver lesion (Study biopsy #1), and finally triple negative (TNBC) in another metastatic liver biopsy (Study biopsy #2). Multi-omic assays included clinical genomic panel sequencing, clinical immunohistochemistry, a clinical protein profiling assay (Intracellular Signaling Protein Profiling), RNA sequencing, and RPPA. Here we provide the expression data from RNAseq and RPPA data on Study biopsy #2 for the patient discussed in this case report. Note: The first liver biopsy did not yield sufficient material for RNAseq or RPPA.Raw RNA FASTQ files from Study biopsy #2 of the liver Gene expression (RNAseq) files from Study biopsy #2Protein expression (RPPA) files (level 2, 3, 4) for Study biopsy #2

  Study phs002321

• InTEAM Consortium - Alcoholic Hepatitis

  Alcoholic hepatitis (AH) is a life-threatening condition characterized by profound hepatocellular dysfunction for which targeted treatments are urgently needed. Identification of molecular drivers is hampered by the lack of suitable animal models. By performing RNA sequencing in livers from patients with different phenotypes of alcohol-related liver disease (ALD), we describe the transcriptional programs involved in disease progression. We uncovered that development of AH is characterized by the defective activity of liver-enriched transcription factors (LETFs). The PPARG predicted activation state was found increased in early forms of ALD, while AH was associated by a marked decrease in HNF4A-dependent gene expression along with a marked expression of the fetal HNF4A isoform (P2). TGFB1, a key upstream transcriptome regulator in AH, induced the use of HNF4a P2 promoter in hepatocytes, which resulted in abnormal bile acid synthesis and defective metabolic and synthetic functions. PPARG agonists partially prevented this effect. We conclude that targeting TGFB1 and epigenetic drivers that modulate HNF4A-dependent gene expression could be beneficial to improve hepatocellular function in patients with AH. The study was conducted thanks to a multicenter collaboration under the National Institute of Alcohol Abuse and Alcoholism (NIAAA)-funded consortium: Integrated Approaches for Identifying Molecular Targets in Alcoholic Hepatitis (InTEAM).

  Study phs001807

• Whole Genome Association Study of Visceral Adiposity in the Health Aging and Body Composition (Health ABC) Study

  The Health Aging and Body Composition (Health ABC) Study is a NIA-sponsored cohort study of the factors that contribute to incident disability and the decline in function of healthier older persons, with a particular emphasis on changes in body composition in old age. Between 4/15/97 and 6/5/98 the Health ABC study has recruited 3,075 70-79 year old community-dwelling adults (41% African-American), who were initially free of mobility and activities of daily living disability. The key components of Health ABC include a baseline exam, annual follow-up clinical exams, and phone contacts every 6 months to identify major health events and document functional status between clinic visits. The core yearly examination for HEALTH ABC includes measurement of body composition by dual energy x-ray absorptio-metry (DXA), walking ability, strength, an interview that includes self-report of limitations, and a medication survey, weight. At baseline, visceral adiposity was measured by computerized tomography (CT). Provision has been made for banking of blood specimens and extracted DNA (HealthABC repository). The overall goal of this project is to identify genetic determinants of visceral adiposity. Genetic samples from 2932 unrelated participants were evaluated with a genome-wide scan.

  Study phs000169

• Genetic Predictors of Ibrutinib-Related Cardiovascular Side Effects in Patients with Chronic Lymphocytic Leukemia

  The goal of this study was to identify genetic polymorphisms associated with ibrutinib-related cardiovascular side effects (CVSEs). This is an observational non-interventional pharmacogenomic study of 50 patients with newly diagnosed or relapsed refractory chronic lymphocytic leukemia (NDCLL or RRCLL) receiving ibrutinib 420 mg for at least six months. The ibrutinib-related CVSEs included atrial fibrillation and hypertension, which occurred in 20% of patients. DNA obtained from buccal swabs was genotyped for 40 single nucleotide polymorphisms (SNPs) in GATA4, SGK1, KCNQ1, KCNA5, NPPA, and SCN5A using a customized next generation sequencing panel. It was found that GATA4 rs804280 AA (P =.043), KCNQ1 rs163182 GG (P =.036) and KCNQ1 rs2237895 AA (P =.023) were associated with the ibrutinib-related CVSEs. Patients with a high-risk score had at least two of the three significant risk genotypes identified in univariate analysis for GATA4 rs804280 A>C, KCNQ1 rs162182 G>C and KCNQ1 rs2237895 A>C, and patients with a low-risk score had either one or none of these genotypes. In multivariate analysis, 18 patients with at least two of the three high-risk genotypes had an 11.5-fold higher odds of CVSEs (P =.019; 1.79-119.73 at 95% CI).

  Study phs003370

• Genomics and Epigenomics of the Elderly Response to Pneumococcal Vaccines

  Pneumococcal Vaccine Study: This is a study designed to develop a detailed transcriptional and cellular profile of the immune response to pneumococcal vaccination with conjugated and non-conjugated polysaccharide vaccines in the senescent immune system of older adults. In this study, 39 healthy adults ages 60 and older that have never received pneumococcal vaccination, have been randomized to receive Prevnar 13 (Pfizer), a conjugated 13-valent vaccine or Pneumovax 23 (Merck), a non-conjugated 23-valent vaccine. Four (4) study visits occurred over 70 days at Day -7 (baseline), day 1, day 10 and day 60 (± 5d) post vaccination.Bulk RNA-sequencing data are available on the 4 time points for 31 of the participants and 1 replicate. ATAC-Doublet Detector Study: We generated single nucleus ATAC-seq (snATAC-seq) data from PBMCs of 2 baseline blood samples from the pneumococcal study. Generated data was then used to benchmark a novel computational method for detecting multiplets in snATAC-seq data, namely, AMULET (https://github.com/UcarLab/AMULET). Multiplets confound downstream analyses by introducing combined epigenomic profiles from 2 or more cells/nuclei. AMULET detects multiplets by using unique snATAC-seq data features that allow it to reliably use read counts to detect multiplets for their removal from data analyses.

  Study phs002361

• Genome-Wide Association Study of the Taste and Hedonic Ratings of the Low-Calorie Sweetener Acesulfame Potassium

  Acesulfame potassium (Ace-K) is a low-calorie sweetener (LCS) widely used as an additive in foods and beverages and an excipient in pediatric medicines. Because genetic variants play a role in individual variation in the taste of Ace-K, we sought to identify genetic contributions to its taste using a genome-wide association study (GWAS). 141 adult panelists rated the taste of an aqueous solution of Ace-K using the general labelled magnitude scale (gLMS) and its palatability using the hedonic gLMS. Genotypes were assayed on the Infinium Global Screening Array. Imputation of genotypes was performed on the Michigan Imputation Server with 1000 Genomes Project phase 3 genotype data as reference. Linear regression was performed to test genetic associations between genotyped and imputed variants with three gLMS ratings (bitterness (square-root-transformed), hedonic, sweetness) of Ace-K using PLINK2, adjusting for standardized age, sex, and the first 10 principal components of genetic ancestry. We identified that a locus spanning several TAS2R (Taste receptor 2) genes was associated with bitterness ratings of Ace-K and a locus within the gene ELMO1 (Engulfment and Cell Motility Protein 1) was associated with hedonic ratings of Ace-K (p-values 40594245).

  Study phs004031

• Exome sequencing identifies mutation of the ribosome in T-cell acute lymphoblastic leukemia

  Acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy and responds well to therapy in children, but not in adults. We used exome sequencing of 67 T-cell ALL (T- ALL) samples to gain insight in the mutational spectrum and age related differences of these leukemias. We detected protein-altering mutations in 508 genes, with an average of 8.2 mutations in pediatric and 21.0 in adult T-ALL. Based on stringent filtering, we predict 15 of these genes to be drivers, including 7 genes that were not previously implicated in T-ALL. We identify CNOT3 as a new tumor suppressor, as it is mutated in 12.2 % of adult T-ALLs and its knock-down causes de novo tumors in a sensitized drosophila eye tumor model. In addition, we identify mutations in RPL5 and RPL10, proteins of the 60S ribosomal complex2, in 18.2 % of pediatric T-ALLs. Mutation of arginine 98 in the X-linked RPL10 gene was most frequent. Yeast cells expressing the Rpl10 R98S mutant showed a clear ribosome biogenesis defect, excluding that this mutation is a passenger mutation. Our data provide insights in the mutational landscape of pediatric and adult T-ALL and identify the ribosome as a potential oncogenic factor in cancer.

  Study EGAS00001000296

• Pancreatic, Small-intestinal and Pulmonary Neuroendocrine Tumors

  Purpose: The primary origin of neuroendocrine tumor metastases can be difficult to determine by histopathology alone, but is critical for therapeutic decision making. DNA methylation-based profiling is now routinely used in the diagnostic workup of brain tumors. This has been enabled by the availability of cost-efficient array-based platforms. We have extended these efforts to augment histopathological diagnosis in neuroendocrine tumors. Experimental Design and Results: We compiled data of 69 small-intestinal, pulmonary, and pancreatic neuroendocrine tumors. These data were used to build a ridge regression calibrated random forest classification algorithm (NEN-ID) that predicts the origin of tumor samples with high accuracy (> 95%). The model was validated during 3x3 nested cross validation and tested in a local (n=26) and external (n=172) cohort. In addition, we show that our diagnostic approach is robust across a range of possible confounding experimental parameters such as tumor purity and array quality. A software infrastructure and online user interface was built to make the model available to the scientific community. Conclusions: This DNA methylation-based prediction model can be used in the workup for patients with neuroendocrine tumors of unknown primary. To facilitate validation and clinical implementation, we provide a user-friendly, publicly available web-based version of NEN-ID.

  Study EGAS00001004878

• Unifying recovery dynamics in heterogeneous diseases exemplified by COVID-19

  Studying the recovery dynamics in different diseases poses many difficulties, as patients often display high heterogeneity in their recovery courses. Moreover, most attempts to study disease dynamics focus on disease progression rather than disease recovery mechanisms. To model recovery dynamics, using severe COVID-19 as the example, we align heterogeneous recovery trajectories via a novel computational scheme applied to longitudinally sampled blood transcriptomes. We thus generate pseudotime trajectories, which we then link to cellular and molecular mechanisms based on cell deconvolution analysis and molecular pathway prediction, thus presenting a unique framework for studying recovery processes over time. Specifically, mature neutrophils displayed a gradual decrease during recovery, allowing superior useability for outcome prediction compared to currently used clinical markers. Further, we discovered a recovery-related regulatory change in gene programs resulting in immune rebalancing between interferon and NFkB activity and the restoration of cell homeostasis. We thus propose regulatory mechanisms governing COVID-19 recovery and suggest mature neutrophils and additional gene markers, as novel clinical biomarkers for disease outcome. Overall, we present a novel clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.

  Study EGAS00001005735

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

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

  Study EGAS00001003027

• The Genomic Landscape of Core-Binding Factor Acute Myeloid Leukemias

  Pediatric de novo acute myeloid leukemia (AML) is a heterogeneous disease that can be divided into clinically distinct subtypes based on the presence of specific chromosomal abnormalities or gene alterations. One of the best characterized subtypes of AML involves leukemias with alterations of the core-binding factor (CBF)-complex, which comprises the FAB subtypes M2 and M4Eo and associates with a favorable outcome. Patients with the AML M2 subtype harbor a translocation between chromosomes 8 and 21 [t(8;21)] that yields the chimeric fusion gene RUNX1(AML1)-RUNX1T1(ETO), while patients with AML M4Eo express the chimeric fusion gene CBFβ-SMMHC(MYH11) as a result of an inversion/translocation event of chromosome 16 [inv(16)/t(16;16)]. In an effort to define the total complement of genetic changes in CBF-leukemia, we performed paired-end whole genome sequencing (WGS) on diagnostic leukemia blasts and matched germ line samples from 17 pediatric CBF-leukemia patients using the Illumina platform. Somatic alterations, including single nucleotide variations (SNVs) and structural variations (SVs), including insertions, deletions, inversions, and inter- and intra-chromosomal rearrangements, were detected using complementary analysis pipelines (Bambino, CREST and CONSERTING). Recurrent screening of identified mutations will be performed in a cohort of approximately 94 cases of CBF-leukemias.

  Study EGAS00001000349