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• EDi013-C / SAMEA4459368 WGS data

  The iPSC line EDi013-C / SAMEA4459368 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi013-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001065

• EDi012-C / SAMEA4459364 WGS data

  The iPSC line EDi012-C / SAMEA4459364 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi012-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001064

• EDi012-B / SAMEA4459363 WGS data

  The iPSC line EDi012-B / SAMEA4459363 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi012-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001063

• UKKi017-C / SAMEA17621668 WGS data

  The iPSC line UKKi017-C / SAMEA17621668 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line UKKi017-C is available for research use at www.EBiSC.org.

  Dataset EGAD50000001061

• EDi010-B / SAMEA4459356 WGS data

  The iPSC line EDi010-B / SAMEA4459356 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line EDi010-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001056

• BIONi010-B / SAMEA3158000 WGS data

  The iPSC line BIONi010-B / SAMEA3158000 has undergone whole genome sequencing. Whole genome sequencing was done using Illumina HiSeq X Five platform with a reference genome of GRCh38. Raw data as FASTQ files and analysed data as CRAM files are available for this sample, in this dataset. The iPSC line BIONi010-B is available for research use at www.EBiSC.org.

  Dataset EGAD50000001055

• Whole-Genome Sequencing in Multiplex Epilepsy Families

  Epilepsy is one of the most common neurologic disorders, affecting approximately 4% of individuals at some time in their lives. More than 30% of people with epilepsy continue to have seizures despite treatment, and improved approaches to treatment and prevention are sorely needed. In the search for new strategies to reduce the burden of disease, the discovery of specific genes that influence risk offers a novel opportunity to clarify pathogenic mechanisms, identify susceptible individuals prior to seizure onset, and treat and prevent seizures in people at risk. Despite clear evidence of the importance of genetics in susceptibility to epilepsy, only limited progress has been made in identifying the specific genes that influence risk. One of the greatest challenges for genetic research on this disorder is its extreme clinical and genetic heterogeneity. Although epilepsy is broadly defined by recurrent unprovoked seizures, it is so variable in its clinical manifestations, natural history, and treatment response that most epileptologists view it as a collection of different syndromes ("epilepsies") with distinct etiologies. The genetic effects on susceptibility are also likely to be extremely variable, ranging from rare variants with high penetrance (some of which produce Mendelian patterns of inheritance) to common variants with low penetrance. Recent findings strongly suggest that rare gene variants play a major role in the genetic architecture of the epilepsies. The purpose of this study was to discover new genetic risk factors for epilepsy. The primary approach was to use whole-genome sequencing to interrogate classes of genetic variants, including very rare variants, in multiplex families. Our main hypothesis was that, in at least some proportion of these families, a single variant would explain all instances of epilepsy. Variants identified within the families could then be tested for cosegregation within the family and also validated by seeing enrichment in sporadic epilepsy cases. Furthermore, understanding the impact of rare variation in epilepsy also has the potential to provide insight into the genetic architecture of other complex human diseases. Our analysis focused on families containing multiple individuals with non-acquired (idiopathic or unknown cause) epilepsy under the hypothesis that these would be enriched for genetic control. The families studied had been previously collected and phenotyped in detail, and contain an average of 3.8 individuals per family with a range of different types of epilepsy. We selected one or two affected individuals from each family for sequencing. This work has generated NGS data on 60 samples from 29 multiplex epilepsy families. We have established that, under a monogenic model of inheritance, sequencing pairs of distantly related relatives is an effective method for reducing the number of candidate variants. Critically, we have found that no single variant can explain a large proportion of these epilepsy families. This work emphasizes that identifying causal variants among the many genetic candidates found in this work will require very large sample sizes and gene-based analyses.

  Study phs000690

• The 3D evolution of glioma cell populations

  Study description: A detailed understanding of heterogeneity in solid tumors has been limited due to insufficient sampling and a lack of knowledge from where within the tumor the sample was taken from. We present here a novel resource - the 3D Glioma Atlas - in which we record the precise, three-dimensional (3D) coordinate for each of 8-20 spatially-distinct samples obtained from each patient tumor.By revealing how genetic alterations and tumor cell states are patterned in glioma in 3D space, our Atlas shows that genetic diversity is more regionally confined in indolent as compared to aggressive tumors, that recurrent tumors have a greater density of genetic diversity, and that more aggressive tumors have greater tumor-wide transcriptomic heterogeneity.

  Study EGAS00001003710

• 2014_Lung_sq_WES

  Purpose Lung squamous cell carcinoma (SqCC) is the second most prevalent type of lung cancer. Currently, no targeted-therapeutics are approved for treatment of this cancer, largely due to lack of systematic understanding of the molecular parthenogenesis of the disease. To identify therapeutic targets and comparatively analyze them in lung SqCC, we probed somatic alterations of Korean lung SqCC. Patients and Methods We performed massively parallel whole-exome sequencing of 104 Korean lung SqCC patients’ samples with matched normal samples. In addition, copy number analysis and transcriptome analysis were conducted for a subset of these samples. Clinical association with cancer-specific somatic alterations was investigated.

  Study EGAS00001002844

• RNAseq dataset for MALT1 in MCL

  Manuscript Title: Co-targeting of BTK and MALT1 overcomes resistance to BTK inhibitors in mantle cell lymphoma Journal: Journal of Clinical Investigation Authors Vivian Changying Jiang1, Yang Liu1, Junwei Lian1, Shengjian Huang1, Alexa Jordan1, Qingsong Cai1, Fangfang Yan3, Joseph Mitchell McIntosh1, Yijing Li1, Yuxuan Che1, Zhihong Chen1, Jovanny Vargas1, Maria Badillo1, JohnNelson Bigcal1, Heng-Huan Lee1, Wei Wang1, Yixin Yao1, Lei Nie1, Christopher Flowers1, and Michael Wang1, 2* Abstract Bruton’s tyrosine kinase (BTK) is a proven target in mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma. However, resistance to BTK inhibitors is a major clinical challenge. We here report that MALT1 is one of the top overexpressed genes in ibrutinib-resistant MCL cells, while expression of CARD11, which is upstream of MALT1, is decreased. MALT1 genetic knockout or inhibition produced dramatic defects in MCL cell growth regardless of ibrutinib sensitivity. Conversely, CARD11 knockout cells showed anti-tumor effects only in ibrutinib-sensitive cells, suggesting that MALT1 overexpression could drive ibrutinib resistance via bypassing BTK-CARD11 signaling. Additionally, BTK knockdown and MALT1 knockout markedly impaired MCL tumor migration and dissemination, and MALT1 pharmacological inhibition decreased MCL cell viability, adhesion, and migration by suppressing NF-κB, PI3K-ATK-mTOR, and integrin signaling. Importantly, co-targeting MALT1 with safimaltib and BTK with pirtobrutinib induced potent anti-MCL activity in ibrutinib-resistant MCL cell lines and patient-derived xenografts. Therefore, we conclude that MALT1 overexpression associates with resistance to BTK inhibitors in MCL, targeting abnormal MALT1 activity could be a promising therapeutic strategy to overcome BTK inhibitor resistance, and co-targeting of MALT1 and BTK should improve MCL treatment efficacy and durability as well as patient outcomes. Dataset description: The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment. sample Cell MI-2 Ibrutinib (IBN) Venetoclax (VEN) Used for IBN-R vs IBN-S comparison Used for MI-2 vs untreated (DMSO) H9 Granta519 - R S yes H21 Granta519 - R S yes H33 Granta519 - R S yes H10 Granta519-VEN-R - R R yes H22 Granta519-VEN-R - R R yes H34 Granta519-VEN-R - R R yes H3 JeKo BTK KD_1 - R R yes yes H15 JeKo BTK KD_1 - R R yes yes H27 JeKo BTK KD_1 - R R yes yes H5 JeKo BTK KD_2 - R R yes yes H17 JeKo BTK KD_2 - R R yes yes H29 JeKo BTK KD_2 - R R yes yes H1 JeKo-1 - S R yes yes H13 JeKo-1 - S R yes yes H25 JeKo-1 - S R yes yes H7 Mino - S S yes H19 Mino - S S yes H31 Mino - S S yes H8 Mino-VEN-R - S R yes H20 Mino-VEN-R - S R yes H32 Mino-VEN-R - S R yes H11 Rec-1 - S S yes H23 Rec-1 - S S yes H12 Rec-VEN-R - S S yes H24 Rec-VEN-R - S R yes H36 Rec-VEN-R - S R yes H35 Rec-1 -- S R yes H4 JeKo BTK KD_1 + MI-2 + yes H16 JeKo BTK KD_1 + MI-2 + yes H28 JeKo BTK KD_1 + MI-2 + yes H6 JeKo BTK KD_2 + MI-2 + yes H18 JeKo BTK KD_2 + MI-2 + yes H30 JeKo BTK KD_2 + MI-2 + yes H2 JeKo-1 + MI-2 + yes H14 JeKo-1 + MI-2 + yes H26 JeKo-1 + MI-2 + yes

  Dataset EGAD00001009771

• DNA methylation at HBV integrants and flanking host genomes

  Integration of DNA viruses into the human genome plays an important role in various types of tumors, including hepatitis B virus (HBV)-related hepatocellular carcinoma. However, the molecular details and clinical impact of HBV integration on either the human or HBV epigenomes are unknown. Here, we show that methylation of the integrated HBV DNA is related to the methylation status of the flanking human genome. We developed a next-generation sequencing-based method for structural methylation analysis of integrated viral genomes (denoted G-NaVI). This method is a novel approach that enables enrichment of viral fragments for sequencing using unique baits based on the sequence of the HBV genome. We detected integrated HBV sequences in the genome of the PLC/PRF/5 cell line and found variable levels of methylation within the integrated HBV genomes. Allele-specific methylation analysis revealed that the HBV genome often became significantly methylated when integrated into highly methylated host sites. After integration into unmethylated human genome regions such as promoters, however, the HBV DNA remains unmethylated and may eventually play an important role in tumorigenesis. The observed dynamic changes in DNA methylation of the host and viral genomes may functionally affect the biological behavior of HBV. These findings may impact public health given that millions of people worldwide are carriers of HBV. We also believe our assay will be a powerful tool to increase our understanding of the various types of DNA virus-associated tumorigenesis.

  Study JGAS000015

• Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets

  Untreated prostate cancers rely on androgen receptor (AR) signaling for growth and survival, forming the basis for the initial efficacy of androgen deprivation therapy (ADT). Yet, the disease can relapse and progress to a lethal stage termed castration-resistant prostate cancer (CRPC). Reactivation of AR signaling represents the most common driver of CRPC growth and next generation AR signaling inhibitors (ARSIs) are now used in combination with ADT as a first line therapy. However, ARSIs can result in selective pressure generating AR-independent tumors. The transition from AR-dependence frequently accompanies a change in phenotype resembling developmental trans-differentiation or ‘lineage plasticity’. Neuroendocrine prostate cancer, which lacks a defined pathologic classification, is the most studied type of lineage plasticity. However, most AR-null tumors do not exhibit neuroendocrine features and are classified as ‘double-negative prostate cancer’, the drivers of which are poorly defined. Lineage plasticity studies in CRPC are limited by the lack of genetically defined patient-derived models that recapitulate the disease spectrum. To address this, we developed a biobank of organoids generated from patient biopsies to study the landscape of metastatic CRPC and allow for functional validation assays. Proteins called transcription factors (TFs) are drivers of tumor lineage plasticity. To identify the key TFs that drive the growth of AR-independent tumors, we integrated epigenetic and transcriptomic data generated from CRPC models. By presenting a map of the chromatin accessibility and transcriptomic landscape of CRPC using a diverse biobank of organoids, PDXs and cell lines that recapitulate the heterogeneity of metastatic prostate cancer, we validate CRPC-AR and CRPC-NE subtypes and reveal two subtypes of AR-negative/low samples as well as their respective masterTFs. Additional analysis revealed a model in which YAP, TAZ, TEAD and AP-1 function together and drive oncogenic growth in CRPC-SCL samples. Overall, we show here how an approach to stratify CRPC patients into four subtypes using their transcriptomic signatures can potentially inform upon appropriate clinical decisions.

  Study EGAS00001006059

• Genomic Factors Involved in Chromosome Rearrangements

  Approximately 15-20% of children referred for chromosomal microarray analysis (CMA) testing have a clinically relevant CNV that in many cases explains their phenotype. The goal of this study is to discover the genomic factors that mediate chromosome rearrangements and the phenotypic effects of chromosome rearrangements. We hypothesize that particular DNA sequences are susceptible to breakage and rearrangement. To this end, we fine-map chromosome breakage sites and analyze the DNA motifs that underlie double-strand breaks (DSBs). Our studies will also capture the genomic structure of breakpoint junctions, which will allow us to determine the mechanisms of DNA repair that shape different types of chromosome rearrangements. We also correlate chromosome rearrangements with clinical features to establish genotype-phenotype correlations. Defining critical regions of deletion or duplication is the first step to identifying candidate genes responsible for particular phenotypes.

  Study phs000845

• Effects of busulfan, fludarabine and clofarabine treatment on human small intestinal organoids generated from healthy donors

  The intestine is vulnerable to chemotherapy-induced toxicity due to its high epithelial proliferative rate, making gut toxicity an off-target effect in several cancer treatments, including conditioning regimens for allogeneic hematopoietic cell transplantation (HSCT). In HSCT, intestinal damage is an important factor in the development of Graft-versus-Host Disease (GVHD), an immune complication in which donor immune cells attack the recipient's tissues. Here, we developed a novel human intestinal organoid-based 3D model system to study the effects of chemotherapy-induced intestinal epithelial damage at the RNA level. We show that chemotherapy conditioning specifically reprograms the intestinal epithelial transcriptome after treatment with either busulfan (3.5μM), fludarabine (15μM) or clofarabine (0.5μM) for 24h. This knowledge can potentially enable us to understand which changes undergo in healthy tissues upon conditioning and how those are related with immune activation typical in GVHD.

  Study EGAS00001007550

• Common Fund (CF) Genotype-Tissue Expression Project (GTEx)

  Lay Description The aim of the Genotype-Tissue Expression (GTEx) Project is to increase our understanding of how changes in our genes affect human health and disease with the ultimate goal of improving health care for future generations. GTEx will create a database that researchers can use to study how inherited changes in genes lead to common diseases. GTEx researchers are studying genes in different tissues obtained from many different people. The GTEx project also includes a study of the GTEx donor consent process - this study will help ensure that the consent process and other aspects of the project effectively address the concerns and expectations of participants in the study. GTEx is a pioneering project that uses state-of-the-art protocols for obtaining and storing a large range of organs and tissues, and for testing them in the lab. Until now, no project has analyzed genetic variation and expression in as many tissues from the same person in such a large population as planned for GTEx. Scientific Description Understanding the role of variation in the human genome is crucial to elucidating genetic contributions to human health and disease. Despite the results of genome-wide association studies (GWAS) documenting strong statistical associations between genetic variation and human traits, the functional role for most of these variants is largely unexplained. Nearly 90% of these GWAS-implicated sites lie outside of protein-coding sequences, suggesting that these variants might regulate gene expression. The goal of the Genotype-Tissue Expression (GTEx) project is to establish a resource database and tissue biobank in which to study the relationship between genetic variation and gene expression and other molecular phenotypes in reference/non-diseased tissues. The ultimate resource will include approximately 960 post-mortem donors with several dozen tissues from each, a resource large enough to study both cis- and trans- gene expression quantitative trait loci (eQTLs). Some tissue will also be banked for additional molecular analyses. To request biosamples, please see the Biobank page for more information. GTEx was initially funded as a 2-year pilot project by the NIH Common Fund (CF) in 2010, and has been scaled up after demonstration of feasibility. The project will collect and analyze RNA levels in many different human tissues and each donor will be characterized for germline genetic variation through dense genotyping arrays and sequencing of either whole exomes or whole genomes. By treating RNA expression levels as quantitative traits, eQTLs will be identified as sites containing genetic variation that correlate with changes in RNA expression. Such eQTLs have been associated with 4%-12% of expressed human genes, and with common complex human diseases, including obesity, atherosclerosis, type 2 diabetes, Crohn's disease, and asthma. Additionally, few studies have examined the tissue specificity of eQTLs. A subset of banked tissue samples will also be analyzed for other molecular phenotypes, such as DNA methylation, DNaseI hypersensitivity sites, and proteomics. The GTEx project will thus serve as a resource database and tissue bank for many future studies, especially for understanding the functional basis of inherited susceptibility to disease. All GTEx releases since Version 5 follow the NIH Genomic Data Sharing (GDS) Policy whereby there are no restrictions on use or publication after release. Additional information about the GTEx Data Release and Publication policy can be found on the GTEx Data Portal at www.gtexportal.org.

  Study phs000424

• International Consortium to Identify Genes and Interactions Controlling Oral Clefts

  Oral clefts represent the most common group of craniofacial birth defects in humans, and include cleft lip with or without cleft palate (CL/P) and cleft palate (CP). Oral clefts have a complex and heterogeneous etiology, with strong evidence for both genetic and environmental causal factors. Candidate gene studies and genome wide linkage studies have yielded compelling but inconsistent evidence that multiple genes control risk, and several studies have shown evidence for interaction between genes and environmental exposures, especially maternal smoking and nutrient intake. This consortium pulls together a very large collection of cases and their parents from multiple populations, and offers a unique opportunity to expand the search for genes controlling risk to the genome wide level. The specific aims are: To conduct a genome wide analysis on 2000+ case-parent trios ascertained through a case with isolated, non-syndromic CL/P or CP to test for linkage and disequilibrium. Initial analysis will consist of individual tests for gene effects while simultaneously testing for GxE interaction with common maternal exposures including vitamin supplementation, cigarette smoking and alcohol consumption (which have all been implicated as environmental risk factors for oral clefts). To use haplotypes in tests for GxE interaction incorporating population specific estimates. Since haplotype frequencies vary among populations, trios will be assigned haplotypes in a stratified estimation and then a pooled test statistic will be constructed. To test for interaction between SNPs in different genes showing evidence of influencing risk in a test for GxG interaction. To test for interaction between genes and maternal biomarkers using trios from Utah where measures of plasma folate, vitamin B-6, homocysteine and zinc in mothers are available. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org), which was developed through the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to oral clefts through large-scale genome-wide association studies of well-characterized cases and their parents from multiple populations. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). The study was supported by the National Institute of Dental and Craniofacial Research (NIDCR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000094

• Liquid Biopsy Detection of Tumor-specific Structural Variants in High Grade Serous Ovarian Cancer

  WGS Liquid Biopsy. Recurrence is frequent for most patients with high grade serous ovarian cancer (HGSOC), even after effective chemotherapy induced remission. However, after achievement of complete clinical response, the minimal residual disease is often insufficient for genomic analysis. Therefore, methods to interrogate the clonal composition and molecular properties of minimal residual disease are needed to better understand the mechanisms of HGSOC relapse. To address this unmet need, we developed and validated a novel cfDNA-based approach for tracking disease burden using NGS-informed tumor specific structural variants (SVs). Methods: The optimization of the methodology was first performed using synthetic cfDNA generated by ultrasonication of gDNA from ovarian cancer cell lines. Following the optimized workflow, whole genome sequencing of multisite biopsies from pre-treatment HGSOC patients were performed and high confidence SVs were called by consensus of multiple published SV callers. Real-time PCR and digital droplet PCR (ddPCR) were used for assays development.

  Study EGAS50000001044

• Genetic immune escape landscape in primary and metastatic cancer

  Immune surveillance escape is a hallmark of tumorigenesis1. Multiple studies have characterized the immune escape landscape across several untreated early-stage primary cancer types2–4. However, whether late-stage treated metastatic tumors present differences in genetic immune escape (GIE) prevalence and dynamics remains unclear. Here, we performed a pan-cancer characterization of GIE prevalence across six immune escape pathways in 6,457 uniformly processed Whole Genome Sequencing (WGS) tumor samples including 58 cancer types from 1,943 primary untreated patients and 4,514 metastatic patients. To effectively address the complexity of the Human Leukocyte Antigen (HLA-I) locus and to characterize its tumor status, we developed LILAC, an open-source integrative framework. We demonstrate that one in four tumors harbor GIE alterations, with high mechanistic and frequency variability across cancer types. GIE prevalence is highly consistent between primary and metastatic tumors for most cancer types with few exceptions such as prostate and thyroid carcinomas that have increased immune evasion frequencies in metastatic tumors. Positive selection analysis revealed that GIE alterations are frequently selected for in tumor evolution and that focal LOH of HLA-I, unlike non-focal LOH of HLA-I, tends to lose the HLA allele that presents the largest neoepitope repertoire. We also unraveled tumor genomic features contributing to immune escape incidence, including DNA repair deficiency, APOBEC activity, tobacco associated mutation load and viral DNA integration. Finally, there is a strong tendency for mid and high tumor mutation burden (TMB) tumors to preferentially select LOH of HLA-I for GIE whereas hypermutated samples favor global immune evasion strategies. Our results indicate that genetic immune escape is generally a pre-metastatic event during tumor evolution and that tumors adapt different strategies depending on their neoepitope burden.

  Study EGAS00001006123

• To profile the landscape of sebaceous tumours_RNAseq

  Sebaceous tumours are a rare cutaneous cancer with potential for aggressive behaviour. However, limited information is available on these cancers with few published cases. Here we wish to exome sequence these cancers to define the first genomic landscape for this malignancy. We will extract RNA from formalin-fixed, paraffin-embedded (FFPE) cores. Cores may be obtained from lesional and non-lesional tissues of primaries as well as matching metastases. The extracted RNA will be used for RNA sequencing.

  Dataset EGAD00001015368

• Genomic landscape and PD-1 blockade in Natural-killer/T cell lymphoma

  Natural killer/T-cell lymphoma (NKTL) is an aggressive malignancy with a predilection for Asian, Mexican and South American populations. With the exception of Japan, it is the most common mature T-cell lymphoma in Asia. NKTL presents as extranodal disease and mostly affects the upper aerodigestive tract. Neoplastic cells are invariably infected by the Epstein-Barr virus (EBV) and characterized by a cytotoxic phenotype. The genetic landscape of NKTL has been recently unraveled by discoveries describing recurring mutations altering the JAK-STAT pathway, epigenetic modifiers, the DDX3X gene and genetic predisposition in the HLA-DPB1 gene.The genomic landscape of NKTL has been interrogated by whole-exome sequencing, targeted sequencing and single nucleotide polymorphism arrays, but has yet been studied with whole-genome sequencing (WGS). In this study, we will use a combination of WGS, targeted-capture sequencing (TCS) and RNA sequencing data to explore the genetic landscape and its relevance to immunotherapy in NKTL

  Study EGAS00001003828

• Suspected Lynch syndrome dataset

  This dataset comprises a genomic and a phenotypic excel sheet displaying 137 cases classified as suspected Lynch syndrome. Included are genotypic data such as tumour mutational burden, tumour mutational signatures and germline/somatic variant calls for each colorectal, endometrial or sebaceous skin tumour screened. Genomic data is derived from targeted multigene panel sequencing including ~300 hereditary cancer genes.

  Dataset EGAD50000000031

• Impact of Respiratory Virus Infections and Bacterial Microbiome Shifts on Lymphocyte and Respiratory Function in Infants Born Prematurely or Full Term

  Public health importance: Babies born preterm, approximately 1 out of every 9 live births in the United States, have significant respiratory morbidity over the first two years of life, exacerbated by respiratory viral infections. Many (<50%) return to pediatricians, emergency rooms and pulmonologists with symptoms of respiratory dysfunction (SRD): intermittent or chronic wheezing, poor growth and an excess of upper and lower respiratory tract infections (LRTI). SRD correlate inversely with gestational age and weight at birth and is more common in those with chronic lung disease of prematurity, yet its incidence and severity varies widely among both the prematurely born and those born at term. There is evidence from clinical studies and animal models that risks of LRTI and recurrent wheezing is influenced by gut and respiratory flora and by T cell responses to infection. Information gained from this study will be used to identify characteristics, risk factors and potential mechanisms for early and persistent lung disease in children born at term and born preterm. This Clinical Research Study will investigate the relationships between sequential respiratory viral infections, patterns of intestinal and respiratory bacterial colonization, and adaptive cellular immune phenotypes which are associated with increased susceptibility to respiratory infections and long term respiratory morbidity in preterm and full term infants. We hypothesize that the timing and acquisition of specific viral infections and bacterial species are directly related to respiratory morbidity in the first year of life as defined by SRD and by measures of pulmonary function. We hypothesize that cellular and molecular immuno-maturity are altered due to factors presented by premature birth in such a way as to promote chronic inflammatory and cytotoxic damage to the lung, with subsequent enhanced, damaging responses to infectious agents and environmental irritants. Our preliminary studies demonstrate both feasibility and expertise in mutiparameter immunophenotyping of small volume peripheral blood samples obtained from premature infants including gene expression arrays of flow cytometry sorted cells. We will use new technologies for known viral identification, as well as high-throughput metagenome sequencing of RNA and DNA virus like particles (VLP) to be used for viral discovery in infant respiratory sample and use of high-throughput pyrosequencing (454T) of bacterial 16S rRNA to determine shifts in bacterial community structure, occurring in pre-term (PT) as compared to full term (FT) infants, over the first year of life. Finally, we present statistical approaches to stratify disease risk predictors using multivariate logistic regression modeling approaches. We propose to evaluate T cell phenotypic and functional profiles relative to viral and predominant bacterial exposures according to highly complementary, but independent, Specific Objectives. Objective 1: To determine if viral respiratory infections and patterns of respiratory and gut bacterial community structure (microbiome) in prematurely born babies predict the rate and degree of immunologic maturation, and pulmonary dysfunction, measured from birth to 36 weeks corrected gestational age (CGA). Objective 2: To determine the relationship between respiratory viral infections and disease severity up to one year CGA, and the lymphocyte (Lc) phenotypes documented at term gestation (birth for term infants and 36 wks/NICU discharge in preterm infants) and at one year CGA. Three secondary outcomes of this objective will be to a) relate the quantity, type and severity of viral infections with pulmonary function at one and three years of life, b) relate the viral community structure to severity of viral infections and c) to seek evidence of modulation of viral susceptibility by bacterial respiratory and gut community structure (microbiome). The relationship of colonization with known and non-identified bacterial species in both the respiratory tract and the gut will be evaluated. Flow cytometry data corresponding to this study can be found within Immport study SDY1302. Positive and negative controls for microbiome samples are uploaded under SRA bioproject PRJNA474485. Microbiome samples corresponding to PRISM2 are distinguished from PRISM1 via "_PRISM2" appended to the sample name. Within the positive and negative controls, PRISM1 controls are uploaded as bam files and PRISM2 controls are uploaded as paired fastq. Samples ending in -08 correspond to TLDA qPCR results for a given sample. There is a column for each pathogen tested and a column to indicate where that pathogen was bacteria or virus.

  Study phs001347

• GENEVA Genes and Environment Initiatives in Type 2 Diabetes (Nurses' Health Study/Health Professionals Follow-up Study)

  Type 2 diabetes mellitus (T2D) affects approximately 21 million individuals in the U.S., or almost 10% of the U.S. adult population. Because diabetes is determined by both genetic and environmental factors, a better understanding of the etiology of diabetes requires a careful investigation of gene-environment interactions. The Nurses' Health Study (NHS) and Health Professionals' Follow-up Study (HPFS) are well-characterized cohort studies of women and men for whom stored blood and DNA samples are available as well as detailed information on dietary and lifestyle variables. The major goals of the project include: 1. To conduct a GWA analysis among 3,000 cases of T2D and 3,000 healthy controls in NHS/HPFS cohorts. 2. To use information on the joint effects of genes and a list of carefully selected environmental exposures at the initial screening stage to test gene-environment interactions. This approach optimizes our power to detect variants that have a sizeable marginal effect and those with a small marginal effect but a sizeable effect in a stratum defined by an environmental exposure. For this analysis, we have developed a joint test of genetic marginal effect and gene-environment interaction. This flexible two-degree-of-freedom test generally provides greater power than standard methods and has the potential to uncover both marginal genetic effects and stratum-specific effects. The Version 1 (v1) dbGaP release of data from the GENEVA Diabetes Study (NHS/HPFS) includes data from the NHS only. The Version 2 (v2) dbGaP release includes data from both the NHS and HPFS. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to type 2 diabetes mellitus through large-scale genome-wide association studies of well-characterized cohorts of nurses and health professionals. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center. Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000091

• Genomic profiling of localized (lFL) and systemic follicular lymphoma (sFL) reveals novel insights into FL pathogenesis

  At diagnosis, the majority of FL presents with symptomatic disease in advanced/systemic stages of FL (sFL). In contrast only around 10 to 15% of cFL are diagnosed in localized stages (lFL). The biological knowledge is mainly based on data derived from global sFL analysis and only small cohorts of lFL were characterized intensively so far. It is well-known that the hallmark BCL2 translocation is less frequently observed in lFL. Furthermore, lFL differs from sFL concerning their gene expression and their N-glycosylation profiles. In consequence, comprehensive global analysis with CNA profiling and whole exome sequencing was performed in a large cohort of lFL. Additionally, the mutational profile as well as the CNA landscape of lFL and sFL, as well as for BCL2 translocation-positive and -negative was compared.

  Study EGAS00001006927

• National Institute of Dental and Craniofacial Research (NIDCR) Sjögren's International Collaborative Clinical Alliance (SICCA): Center for Inherited Disease Research (CIDR) Genome-Wide Genotyping

  The Sjögren's International Collaborative Clinical Alliance (SICCA) is a multisite observational cohort study that recruited a large cohort of geographically diverse participants. Enrollment of participants began in late 2004 at five (one domestic and four international) sites, in which all groups used the same protocol-directed methods to provide uniform evaluations; collect oral, ocular, and rheumatologic data; and collect specimens. The sites were located at the University of Buenos Aires, Argentina; Peking Union Medical College, Beijing, China; Rigshopitalet (formerly at Glostrup Hospital), Copenhagen, Denmark; Kanazawa Medical University, Ishikawa, Japan; King's College, London, UK (joined in 2007); and the University of California, San Francisco (UCSF). In 2009, Aravind Eye Hospital, Madurai, India; Johns Hopkins University, Baltimore, MD; and University of Pennsylvania, Philadelphia, PA were added as additional SICCA sites. UCSF is the coordinating center for SICCA. All specimens and data collected for SICCA are housed at UCSF. To facilitate the research focused on understanding the genetics of Sjögren'sSjögren's syndrome, high-density SNP genotype data and SICCA clinical information are being made available to the research community. This includes participants recruited from all SICCA research groups (RG). These participants (3,382), blood relatives (439), and unrelated healthy controls (25) had their whole blood or saliva sample (Oragene) extracted for DNA for the GWAS at the UCSF DNA Bank. Eighty eight percent of the participants are women, most are of European or Asian ancestry and the median age is 55. To assess potential batch effects when doing case-control comparisons using planned external controls, 30 DNA samples from each of three studies were genotyped with SICCA DNA samples: The Genetic Architecture of Smoking and Smoking Cessation - Collaborative Genetic Study of Nicotine Dependence (COGEND) - PI: Laura Bierut. NEI-Age-related disease study (AREDS) - Genetic Variation in Refractive Error Substudy - PI: Dwight Stambolian. Controls from the National Institute of Mental Health's (NIMH's) Human Genetics Initiative. Genome-Wide Association Study of Schizophrenia - PI: Pablo V. Gejman. Molecular Genetics of Schizophrenia - nonGAIN Sample (MGS_nonGAIN) - PI: Pablo V. Gejman. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data quality control, dbGaP preparation and posting, and imputation to 1000 Genomes to increase SNP density was performed by the Center for Biomedical Statistics at the University of Washington. Data analysis was performed at UCSF using software PLINK, EIGENSOFT, and SNPTEST.

  Study phs000672