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• GAW16 Framingham and Simulated Data

  Important links to apply for individual-level data Genetic Analysis Workshop Instructions to Request Authorized Access Data Use Certification Requirements (DUC) Apply here for controlled access to individual level data Research Use Statement Questions regarding GAW16 should be directed to Vanessa Olmo at vanessa@business-endeavors.com. Problem 2: Description of the Framingham Heart Study In GAW16, we use data drawn from the Framingham Heart Study. The Framingham Heart Study — under the direction of National Heart, Lung, and Blood Institute; NHLBI — began in 1948 with the recruitment of adults from the town of Framingham, Massachusetts. At the time, little was known about the general causes of heart disease and stroke, but the death rates for cardiovascular disease (CVD) had been increasing steadily since the beginning of the 20th century and had become an American epidemic. The Framingham Heart Study is now conducted in collaboration with Boston University. The objective of the Framingham Heart Study was to identify the common factors or characteristics that contribute to CVD by following its development over a long period of time in a large group of participants who had not yet developed overt symptoms of CVD or suffered a heart attack or stroke. Between 1948 and 1953 the researchers recruited 5,209 subjects (2,336 men and 2,873 women) between the ages of 29 and 62 from the town of Framingham, Massachusetts and began the first round of extensive physical examinations and lifestyle interviews that they would later analyze for common patterns related to CVD development. Subjects were recruited from lists of addresses recorded for the town. Two out of every three households were approached for participation in the study. While there was no intention to recruit families for family studies, the plan was to recruit all household members in the ages 30-60 within each house that was selected for study. Hence, many biologically related individuals were recruited, including 1644 spouse pairs. Since 1948, these participants have returned to the study every two years for a detailed medical history, physical examination, and laboratory tests. Now in 2008 at 60 years of follow up, there remain about 500 participants from this cohort. Between 1971 and 1975 the study enrolled a second-generation group — 5,124 of the original participants' children and the spouses of these children — to participate in similar examinations. 2,616 subjects are offspring of the original spouse pairs and 34 are stepchildren. A total of 898 offspring are children of cohort members where only one parent was a study participant and 1,576 are spouses of the offspring. The Offspring Cohort has been followed every four years through 2001 (except between Exams 1 and 2 with an intervening 8 years) using protocols similar to those used for study of the Original Cohort. Between 2002 and 2005 the study enrolled the third generation (Gen3) of the Framingham Heart Study - 4095 offspring of the second generation. None of their spouses were recruited. An additional 103 parents of this third generation, who were not recruited between 1971 and 1975, were also recruited at this time. The latter group is not included in the GAW16 data. With the recruitment of this third generation, the study has increasingly focused on genetic factors associated with the development of cardiovascular disease and its associated risk factors. To date, there is only one examination of this generation of participants. A description of the recruitment of this third generation and comparison with the earlier generations at their initial recruitment is presented in Splansky GL et al., 2007. Further information on the Study can be found at http://www.nhlbi.nih.gov/about/framingham/index.html. Genome-wide Dense SNP Scan in Framingham Heart Study Genetic studies did not begin in the FHS until the 1990s. In the late 1980s and through the 1990s DNA was extracted from blood samples of surviving FHS participants. In 2007, the FHS entered a new phase with the conduct of genotyping for the FHS SHARe (SNP Health Association Resource) project, for which dense SNP genotyping was performed using approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel) in 10,775 samples (some duplicates) from the three generations of subjects (including over 900 pedigrees). Affymetrix conducted all genotyping for the FHS SHARe project, using the 250K Sty, 250K Nsp, and the supplemental 50K platforms. Eighty-nine percent of the DNA samples were collected during the 1990s. To maximize the power of the study, we also extracted DNA from 1133 blood samples, drawn from subjects who had no DNA, to include in the SHARe project. These samples had been sitting in our refrigerators for some time, a few as far back as the 1970s. We refer to these DNA samples as the legacy samples. These samples had a higher failure rate in the genotyping process (40%) than the other eighty-nine percent (3%). Affymetrix invoked its own criteria for a sample to succeed in genotyping. All non-legacy samples must succeed on all three platforms, while legacy samples needed to pass on at least one platform. When a sample failed, additional attempts were made. Samples that repeatedly failed 2-4 times were called failures. Other samples failed due to issues of genotyped sex identification not matching our records or low SNP concordance among SNPs common across arrays or contamination. Eighty-nine percent of the legacy samples for which genotyping results are available passed all three platforms. The genotyping data from the 10,043 samples from 9354 subjects that passed the Affymetrix criteria were additionally checked for gender consistency and consistency with family structure, resulting in genotyping data for 9,274 participants in FHS SHARe. Genotype calls were made with the BRLMM algorithm. The SHARe database is housed at the National Center for Biotechnology Information database of genotypes and phenotypes (NCBI dbGaP) and contains all ~550,000 SNPs. This genome-wide dense SNP scan and a subset of phenotypes from the Framingham Heart Study are the focus of the Genetic Analysis Workshop 16. Further information on the specific variables in the Problem 2 dataset can be found by clicking on the Documents tab at the top of the page. Problem 3: Description of the Simulated Data Set The focus of this simulation is gene discovery in genome-wide association scans (GWAS). The Framingham Heart Study data set (distributed as "Problem 2") is the basis for the FHS* simulated data. The pedigree structures are derived from the data distributed for Problem 2, and we distribute an accompanying triplet file (triplet_sim) containing person ID, father ID, mother ID, to ensure the identical subjects, pedigrees, and singletons are used in the simulated data analysis. Consistent with standard practice, founders and singletons are designated as subjects with both fshare and mshare equal to zero (missing). The simulated data includes a total of 6,479 subjects with both phenotype and genotype data, in 942 pedigrees distributed among 3 generations and 188 singletons. Data inclusion is consistent with the subjects' consent for use by both for-profit and not-for-profit researchers. The genotypes for all Problem 3 replicates are fixed as measured and distributed for Problem 2 for both the genomewide scan and the additional candidate gene SNPs, for a total of approximately 550,000 SNPs (GeneChip® Human Mapping 500K Array Set and the 50K Human Gene Focused Panel). Thus, to analyze the Problem 3 simulated data you also will need to download the Problem 2 genotypes. Note that there are slight discrepancies in counts between Problems 2 and 3 due to a change in consents between the two datasets. Several phenotypes that contribute to coronary heart disease (CHD) were simulated for all individuals with genotypes across three different time points, 10 years apart. All genotyped individuals have complete data; the effects of missing values can be investigated by user-specified missing value patterns. There are 200 longitudinal datasets created, based on the generating model, and each replication is found in a separate dataset. We suggest that if only one replication is to be analyzed, that it be replication 1 to enable more precise comparisons among analytical approaches. The 'shareid' will allow you to merge the simulated phenotype data with the Problem 2 genotype data, and reconstruction of the pedigrees using the distributed 'triplet_sim' file or for larger families' relationships with the triplet distributed with the Problem 2. The simulated data problem is further described in the associated readme file, and a data dictionary is provided defining all the variables. For disclosure of the generating model for these data, please contact Jean MacCluer at jean@sfbrgenetics.org.

  Study phs000128

• Effect of Breast Feeding on Immunologic Priming in Young Infants

  The mechanisms generating immunoglobulin heavy chain (IgH) biodiversity result in over potentially unique immunoglobulin sequences within an individual. However, over the course of B cell development, B cell receptor (BCR) selection constrains the repertoire significantly. In newborn infants compared to adults, developmental regulation of terminal deoxynucleotidyl transferase (TdT) activity in the bone marrow, selective use of V, D and J gene segments in the IgH locus during fetal life, and immaturity of somatic hypermutation (SHM) and class switch recombination (CSR) mechanisms are likely to contribute to a less diverse IgH repertoire, although the extent of repertoire biodiversity in newborns has not been extensively examined. Furthermore, the fetal IgH repertoire is tightly controlled and for the most part independent of environmental antigenic influences. As a result, the neonatal repertoire, in contrast to older children and adults, is less impacted by the selective pressures of the microbiome, pathogen exposure, and environmental antigens. Evidence for developmental differences in TdT activity is seen in shorter CDR3 lengths and decreased junctional diversity in BCR in both term and preterm newborns. Next Generation Sequencing (NGS) is a sensitive approach to evaluate the neonatal IgH repertoire and assess the relative contribution of each aspect of IgH rearrangement and affinity maturation to overall IgH biodiversity prior to and following isotype class switch. NGS and bioinformatics accurately assess biodiversity by determining the number of unique sequences within the IgH repertoire. Combined with novel analytic tools, NGS provides an approach to compare the extent of somatic hypermutation (SHM), N insertions, V/D/J gene segment usage, and CDR3 length between newborns and adults. Taken together, these measures can be used to assess the earliest events in B cell development using the newborn Ig transcriptome to evaluate the IgM, IgG, and IgA IgH repertoires. The goal of this study was to define the extent of IgH biodiversity in newborns and examine the factors that contribute to the generation of biodiversity during early life. Establishment of the bioinformatics pipeline can be applied to examine the immune deficiency, response to vaccine and infection at molecular population level.

  Study phs002073

• Investigation of BK Polyomavirus (BKPyV) and Molecular Signatures in UC specimens from Taiwan

  Urothelial carcinoma (UC) is the most prevalent cancer of kidney transplant recipients in some regions. The integration of BK polyomavirus (BKPyV) genome into the human genome is observed in some cases of UC. The prevalence of aristolochic acid (AA) mutational signatures in urothelial carcinoma is high in the general population of Taiwan. To better understand the mechanisms of UC carcinogenesis in kidney transplant recipients, 19 UC specimens were analyzed by whole genome sequencing (WGS) and Hybrid Sequencing.

  Study EGAS50000001063

• Histone chaperone CHAF1A promotes proliferation and tumorigenicity in gastric cancer and impacts prognosis via context-depedent regulation of gene expression

  The histone chaperone CHAF1A is associated with some tumors, but its mechanisms in tumor biology remain elusive. Gastric cancer (GC) has significant heterogeneity among patients, and novel prognostic markers and therapeutic targets may improve its outcomes. The role of CHAF1A in GC is unknown. In this study, we demonstrated that CHAF1A was overexpressed in GC tissues accompanied by low expression of wild-type P53 and high expression of the proliferation marker MKI67. In vitro, CHAF1A knockdown inhibited cell proliferation, induced cell cycle arrest and promoted apoptosis, while CHAF1A overexpression had contrary effects. In vivo, CHAF1A knockdown inhibited tumorigenicity of GC cells. A microarray assay with CHAF1A inhibition and a PathScan signaling antibody array with CHAF1A overexpression showed that CHAF1A inhibited the P53 pathway, activated stress response and induced glycolytic metabolism. In 665 patients, the expression level of CHAF1A protein was an independent predictor for overall survival and disease-free survival in non-cardia GC and also had survival associations in patients with small or perineural invasion-negative tumors. Tumor mRNA analyses based on next-generation sequencing in patients indicated that CHAF1A promoted the Warburg effect by depressing oxidative phosphorylation and increasing glycolysis. Furthermore, the heterogeneous clinical significance of CHAF1A among patient subgroups was associated with its differential regulation of gene expression involved with glycolysis and cell proliferation and survival, indicating that the role of CHAF1A is depended on patient characteristics. These results reveal critical roles and clinical values for CHAF1A in GC. CHAF1A may have context-dependent effects in GC, which increases understandings for GC heterogeneity.

  Study EGAS00001003064

• PD-1 Instructs a Tumor Suppressive Metabolic Program to Restrain AP-1 Activity in T Cell Lymphoma

  T cell non-Hodgkin lymphomas (T-NHLs) represent a heterogeneous group of aggressive cancers of mature CD4+ T cells, for which therapeutic options are limited. Recent work uncovered that the PDCD1 encoded immune checkpoint receptor PD-1 is a key tumor suppressor in T cells. PD-1 is recurrently inactivated in T-NHL and the highest frequencies of PDCD1 deletions are detected in advanced disease, predicting worse prognosis. The tumor-suppressive mechanisms of PD-1 signaling remain unknown. In the present study, we identify transcriptional and epigenetic mechanisms underlying PD-1 tumor suppression in T-NHL.Some subjects included in this study overlap with the subjects from phs002456. To establish the link between the overlapping subjects, the Subject Consent datasets will be utilized.

  Study phs003312

• DIPG RNA and exome sequencing

  DIPG is a paediatric high-grade glioma that diffusely infiltrates the brainstem and is the leading cause of paediatric brain tumour death. Here we performed RNA and whole exome sequencing on DIPG and control samples to analyse transcriptomic and genetic alterations associated with this devastating disease, and to understand the relationship between them.

  Study EGAS00001004749

• A proteogenomic atlas of the human neural retina

  The human neural retina is enriched for alternative splicing, and it is estimated that more than 10% of variants associated with inherited retinal diseases (IRDs) alter splicing. Previous research mainly used short-read RNA-sequencing techniques to investigate retina-specific splicing and splicing factors. However, this technique provides limited information about transcript isoforms. To gain a deeper understanding of the human neural retina and its isoforms, we generated a proteogenomic atlas that combines PacBio long-read RNA-sequencing data with mass-spectrometry and whole-genome sequencing data from three healthy human neural retina samples. About one third of the nearly 60,000 transcript isoforms were novel, and ten novel peptides that confirmed novel isoforms were detected. This study highlights the importance of studying tissue-specific transcriptomes in greater detail to better understand tissue-specific regulation and to identify disease-causing variants.

  Study EGAS50000000070

• Lenalidomide Resistance in del(5q) Myelodysplastic Syndrome Follows Loss of RUNX1/TP53-mediated Megakaryocytic Differentiation

  Interstitial deletion of the long arm of chromosome 5 (del(5q)) is the commonest structural genomic variant in myelodysplastic syndromes (MDS). Lenalidomide (LEN) is the treatment of choice for patients with del(5q) MDS, but half of the responding patients become resistant within two years. TP53 mutations are detected in ~20% of patients who become resistant to LEN. Our data show that patients who become resistant to LEN harbor either TP53 or RUNX1 mutations or loss of RUNX1 expression. Here we show that LEN-induced degradation of IKZF1 permits a RUNX1/GATA2 complex to drive megakaryocytic differentiation and consequent del(5q) MDS progenitor cell death via CRBN-mediated CSNK1A1 degradation. Overexpression of GATA2 is able to restore LEN sensitivity in the context of RUNX1 or TP53 mutations by enhancing LEN-induced megakaryocytic differentiation. Screening for TP53 and RUNX1 mutations or downregulation should identify patients resistant to LEN, and strategies to activate GATA2 may resensitize del(5q) MDS cells to LEN.

  Dataset EGAD00001005769

• ICGC Oesophageal adenocarcinoma - lymph-node samples

  The oesophageal project will focus on adenocarcinoma which is increasing in incidence in the UK and other developed countries and has a very poor outcome. The primary aims of this project are to deeply sequence tumour and normal genomic DNA (including the precursor condition Barrett’s oesophagus when material is available) to provide a comprehensive catalogue of somatic mutations. This will be achieved through a UK-wide network of hospitals involved in a research collaboration called the OCCAMS consortium. The goal of this project is to use high quality clinical material with accurately annotated clinic-pathological, treatment and outcome data.

  Study EGAS00001000727

• Understanding the Progression of Metastatic Colorectal Cancer

  This study is to understand (1) the clonal evolution of metastatic colorectal cancer using DNA sequencing and (2) long non-coding RNAs associated with metastatic colon cancer using RNA sequencing. Our goal is to better understand the progression of aggressive colorectal cancer.

  Study phs001722