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• 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

• Addictions: Genotypes, Polymorphisms, and Function/Human Genetic Correlates of Addictive Diseases

  Drug addiction continues to be a major medical and social problem. It is estimated that one million or more persons in the United States are currently addicted to heroin or prescription opioids, with millions more worldwide. Cocaine addiction and alcohol dependence are frequent comorbid conditions in persons with heroin/opioid dependence in addition to being major primary addictions. Many studies over the past thirty years have shown that these drugs disrupt physiologic systems, and that these disruptions may contribute to drug addiction and alcohol dependence and to relapse to drug or alcohol abuse following withdrawal and abstinence. Clinical observations suggest that individuals differ in their response to heroin, cocaine, and alcohol; however, little is known about specific underlying hereditary genetic factors which might influence individual susceptibility to the addictive properties of these substances. Studies also suggest that both common and distinct heritable factors account for the genetic variance in the susceptibility to the separate addictive diseases. We hypothesize that there is a heritable as well as environmental basis for the acquisition and persistence of, and relapse to, specific addictive diseases. Using samples from individuals without and with opioid and other specific drug dependence diagnoses and psychiatric comorbidities, genetic analyses will be used to determine association and linkage. All study subjects will be extensively characterized with respect to the addictive diseases, medical history, family medical addictive disease history; psychiatric comorbidity, and psychological profile, as well as ethnic/cultural background. A better understanding of the consequences of genetic contributions with respect to protection from, or susceptibility to, heroin/opioid addiction and related codependencies and comorbid conditions, could have enormous importance in both prevention and treatment of this problem.

  Study phs001109

• Health and Retirement Study (HRS)

  Introduction to V2: This data release comprises data from the V1 release combined with approximately 3,000 additional samples, collected during the HRS 2010 field period. The 2010 data include samples from a random half of the new cohort enrolled in 2010 along with a significant expansion of the minority sample. Description: The University of Michigan Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of approximately 20,000 people in America over the age of 50 every two years. Supported by the National Institute on Aging (NIA U01AG009740) and the Social Security Administration, the HRS explores the changes in labor force participation and the health transitions that individuals undergo toward the end of their work lives and in the years that follow. The study collects information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, and health care expenditures. Through its unique and in-depth interviews, the HRS provides an invaluable and growing body of multidisciplinary data that researchers can use to address important questions about the challenges and opportunities of aging. Because of its innovation and importance, the HRS has become the model and hub for a growing network of harmonized longitudinal aging studies around the world. Origins of the HRS. As the population ages it is increasingly important to obtain reliable data about aging and topics that are relevant to a range of policy issues in aging. To address this need, the National Institutes on Aging (NIA) established a cooperative agreement with the University of Michigan Institute for Social Research to collect such data. The HRS launched data collection in 1992 and has re-interviewed the original sample of respondents every two years since then. By adding new cohorts and refreshing the sample, the HRS has grown to become the largest, most representative longitudinal panel study of Americans 50 years and older. HRS Study Design. The target population for the original HRS cohort includes all adults in the contiguous United States born during the years 1931-1941 who reside in households, with a 2:1 oversample of African-American and Hispanic populations. The original sample is refreshed with new birth cohorts (51-56 years of age) every six years. The sample has been expanded over the years to include a broader range of birth cohorts as well. The target population for the AHEAD survey consists of United States household residents who were born in 1923 or earlier. Children of the Depression (CODA) recruits households born 1924-1930, War Babies 1942-47, Early Boomers 1948-53, and Mid-Boomers 1954-59. Data collection includes a mixed mode design combining in-person, telephone, mail, and Internet. For consenting respondents, HRS data are linked at the individual level to administrative records from Social Security and Medicare claims. Genetic Research in the HRS. The HRS has genotyped 2.5 million single nucleotide polymorphisms (SNPs) on respondents using Illumina's Human Omni2.5-Quad (Omni2.5) BeadChip. The genotyping was performed by the NIH Center for Inherited Disease Research (CIDR). Saliva was collected on half of the HRS sample each wave starting in 2006. In 2006, saliva was collected using a mouthwash collection method. From 2008 onward, the data collection method switched to the Oragene kit. Saliva completion rates were 83% in 2006, 84% in 2008, and 80% in 2010 among new cohort enrollees. HRS Phenotypic data. Phenotypic data are available on a variety of dimensions. Health measures include physical/psychological self-report, various health conditions, disabilities, cognitive performance, health behaviors (smoking, drinking, exercise), physical performance and anthropomorphic measures, and biomarkers (HbA1c, Total Cholesterol, HDL, CRP, Cystatin-C). Data are also available on health services including utilization, insurance and out-of-pocket spending with linkage to Medicare records. Economic measures include employment status/history, earnings, disability, retirement, type of work, income by source, wealth by asset type, capital gains/debt, consumption, linkage to pensions, Social Security earnings/benefit histories. There is also extensive information on family structure, proximity, transfers to/from of money, time, social and psychological characteristics, as well as a wide range of demographics. Performance on a cognitive test combining immediate and delayed word recall was selected as an example trait for the dbGaP data release. In the immediate word recall task the interviewer reads a list of 10 nouns to the respondent and asks the respondent to recall as many words as possible from the list in any order. After approximately five minutes of asking other survey questions, the respondent is asked to recall the nouns previously presented as part of the immediate recall task. The total recall score is the sum of the correct answers to these two tasks, with a range of 0 to 20. Researchers who wish to link to other HRS measures not in dbGaP will be able to apply for access from HRS. A separate Data Use Agreement (DUA) will be required for linkage to the HRS data. See the HRS website (http://hrsonline.isr.umich.edu/gwas) for details.

  Study phs000428

• DNA methylation-based classification of sinonasal tumors [DNA sequencing]

  This dataset contains raw exome sequencing data from nine sinonasal undifferentiated carcinoma FFPE samples and matched normal tissue that were assigned to a shared epigenetic class using DNA methylation-based classification. They were analyzed using the Twist Human Core Exome Plus Kit (Twist Bioscience) on a NovaSeq 6000 sequencer.

  Dataset EGAD00001009668

• NHLBI TOPMed: Outcome Modifying Genes in Sickle Cell Disease (OMG)

  Sickle cell disease (SCD) is caused by homozygosity for a single mutation of the beta hemoglobin gene. Despite the constancy of this genetic abnormality, the clinical course of patients with SCD is remarkably variable. SCD can affect the function and cause the failure of multiple organ systems through the pathophysiologic processes of vaso-occlusion and hemolysis. These pathophysiological processes are complex and expected to impact multiple organ systems in a variety of ways. This study, therefore, was designed to identify genetic factors that predispose SCD patients to develop specific end-organ complications and to experience more or less severe clinical courses. We enrolled > 700 patients with Hb SS, Hb S-beta0 thalassemia and HbSC being followed primarily at three southeastern U.S. regional institutions (Duke University Medical Center, University of North Carolina Medical Center, and Emory University Medical Center). Medical information obtained included the presence or absence of specific targeted outcomes (overall disease severity as well as specific types of end organ damage). Clinical data include medical status (history, physical, examination, and laboratory results) and information regarding potentially confounding environmental factors. Limited plasma samples are available for correlative studies (e.g. of cytokine levels, coagulation activation). Targeted SNP for candidate gene analysis as well as GWAS has been performed on most samples. Whole genome sequencing has been conducted through the TOPMed Consortium. The subjects in this analysis were collected as part of a larger study, "Outcome Modifying Genes in Sickle Cell Disease" (OMG-SCD) aimed at identifying genetic modifiers for sickle cell disease. More information about the study can be found in Elmariah et al. (2014), PMID: 24478166. Clinical and genetic data have been used to identify genetic characteristics predisposing patients with SCD to a more or less severe overall clinical course as well as to individual organ-specific complications. It is anticipated that identification of such genetic factors will reveal new therapeutic targets individualized to specific complications of SCD, leading to improved outcomes and increased life expectancy for patients with SCD.

  Study phs001608

• 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

• 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

• A super-enhancer associated with CD47 links pro-inflammatory signaling to CD47 upregulation in breast cancer

  CD47 is a cell surface molecule that inhibits phagocytosis of cells that express it by binding to its receptor, SIRPα, on macrophages and other immune cells. CD47 is expressed at different levels in normal cells, however, in cancer cells, CD47 transcript and protein expression is aberrantly increased. Here we sought to uncover the regulators of CD47 transcription, including active enhancers that increase its aberrant expression in cancer cells, in order to reveal mechanisms by which different neoplastic cells generate this dominant 'don't eat me' signal. Enhancers are genomic regions, often referred to as "switches", that can turn on or off the transcription of target genes. Recently the discovery of super-enhancers (SEs) has given more insight into the regulatory architecture of key genes that are highly expressed in a specific cell type, during a particular developmental stage or in disease. By analyzing the CD47 regulatory genomic landscape, we discovered: i) A distinct super-enhancer (SE) is associated with CD47 upregulation in breast cancer cells ii) Disruption of CD47 SEs by using the BRD4 inhibitor JQ1 robustly reduces CD47 gene expression; and iii) The TNF-NFKB1 signaling pathway is directly involved in the regulation of CD47 by interacting with a distal downstream constituent enhancer located within a CD47-associated SE specific to breast cancer. Our results describe a novel mechanism that cancer cells have evolved to drive CD47 overexpression to escape immune surveillance.

  Study phs001264

• 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

• Etiological Investigation of Cancer Susceptibility in Inherited Bone Marrow Failure Syndromes: A Natural History Study

  Background: A prospective cohort of Inherited Bone Marrow Failure Syndrome (IBMFS) will provide new information regarding cancer rates and types in these disorders. Mutations in IBMFS genes are relevant to carcinogenesis in sporadic cancers. Patients with IBMFS who develop cancer differ in their genetic and/or environmental features from patients with IBMFS who do not develop cancer. These cancer-prone families are well suited for cancer screening and prevention trials targeting those at increased genetic risk of cancer. Carriers of IBMFS gene mutations are at increased risk of cancer. The prototype disorder is Fanconi Anemia (FA); other IBMFS will also be studied. Objectives: To determine the types and incidence of specific cancers in patients with an IBMFS. To investigate the relevance of IBMFS gene mutations in the carcinogenesis pathway of the sporadic counterparts of IBMFS-associated cancers. To identify risk factors for IBMFS-related cancers in addition to the primary germline mutations. To determine the risk of cancer in IBMFS carriers. Design: Natural history study, with questionnaires, clinical evaluations, clinical and research laboratory tests, review of medical records, cancer surveillance. Primary endpoints are all cancers, solid tumors, and cancers specific to each type of IBMFS. Secondary endpoints are markers of pre-malignant conditions, such as leukoplakia, serum or tissue evidence of carcinogenic viruses, and bone marrow morphologic myelodyplastic syndrome or cytogenetic clones.

  Study phs001481