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• Transcription Factor Analysis of SLE

  Background: Systemic lupus erythematosus (SLE) is an autoimmune disease with protean manifestations. This study identifies two histone marks of activation and the binding of p300 genome-wide in three cell types and three clinical subsets to better understand cell-specific effects and differences across clinical subsets. Results: We examined 20 patients with SLE and 8 controls and found the TNF, IL-2/STAT5, and KRAS pathways were identified across multiple cell types and ChIP data sets. Patients with cutaneous lupus and lupus nephritis generally had less dramatically altered chromatin than the general SLE group. Conclusions: NFkB and classical inflammatory pathways were strongly associated with increased peak heights across all cell types but were the highest-ranking pathway for all three antibodies in monocytes according to fgsea analysis. IL-6 Jak/STAT3 signaling was the most significant pathway association in T cells marked by H3K27ac change. Therefore, each cell type experiences the disease process distinctly although in all cases there was a strong theme of classical inflammatory pathways. These studies define important cell type differences and emphasize the breadth of the inflammatory effects in SLE.

  Study phs003713

• Characterisation of the genomic landscape of CRLF2-d ALL

  To determine the clinical and genetic landscape of CRLF2 deregulated acute lymphoblastic leukaemia (CRLF2-d ALL). We identified 172 patients with a CRLF2 rearrangement treated on either the UKALL2003 trial for children and adolescents (1-24 years) or the UKALLXII trial for adolescents and adults (15-59 years). Genomic technologies from conventional karyotyping, and FISH through to whole genome and exome sequencing were used to characterise the genomes of patients with CRLF2-d ALL. This is the largest study to date to investigate the genomic landscape of CRLF2-d ALL and define CRLF2-d as a unique subgroup of B-other ALL. We have confirmed the high incidence of CRLF2-d in Down syndrome-ALL and demonstrated the co-existence of CRLF2-d with other primary chromosomal rearrangements, suggesting that in these patients CRLF2-d can be a secondary genetic abnormality. Other defining features included enrichment of IKZF1, BTG1 and ADD3 deletions in IGH-CRLF2 patients and specific chromosomal gains seen at much higher frequencies than B-other ALL . We report recurrent established and new co-operating abnormalities and the novel involvement of USP9X and DDX3X in CRLF2-d ALL. It is clear from these data that CRLF2-d ALL is heterogenoeus, requiring a combination of genetic abnormalities in functionally relevent genes, to work alongside the deregulated expression of CRLF2 in order to initiate and drive leukaemogenesis in this subtype. Although the functional relevance of many of the abnormalities presented here are currently unknown, many are likely to activate alternate pathways or sensitize patients to current therapies.

  Dataset EGAD00001002008

• Characterisation of the genomic landscape of CRLF2-d ALL

  To determine the clinical and genetic landscape of CRLF2 deregulated acute lymphoblastic leukaemia (CRLF2-d ALL). We identified 172 patients with a CRLF2 rearrangement treated on either the UKALL2003 trial for children and adolescents (1-24 years) or the UKALLXII trial for adolescents and adults (15-59 years). Genomic technologies from conventional karyotyping, and FISH through to whole genome and exome sequencing were used to characterise the genomes of patients with CRLF2-d ALL. This is the largest study to date to investigate the genomic landscape of CRLF2-d ALL and define CRLF2-d as a unique subgroup of B-other ALL. We have confirmed the high incidence of CRLF2-d in Down syndrome-ALL and demonstrated the co-existence of CRLF2-d with other primary chromosomal rearrangements, suggesting that in these patients CRLF2-d can be a secondary genetic abnormality. Other defining features included enrichment of IKZF1, BTG1 and ADD3 deletions in IGH-CRLF2 patients and specific chromosomal gains seen at much higher frequencies than B-other ALL . We report recurrent established and new co-operating abnormalities and the novel involvement of USP9X and DDX3X in CRLF2-d ALL. It is clear from these data that CRLF2-d ALL is heterogenoeus, requiring a combination of genetic abnormalities in functionally relevent genes, to work alongside the deregulated expression of CRLF2 in order to initiate and drive leukaemogenesis in this subtype. Although the functional relevance of many of the abnormalities presented here are currently unknown, many are likely to activate alternate pathways or sensitize patients to current therapies.

  Dataset EGAD00001002007

• NHLBI TOPMed: Genetics of Cardiometabolic Health in the Amish

  The Amish Complex Disease Research Program includes a set of large community-based studies focused largely on cardiometabolic health carried out in the Old Order Amish (OOA) community of Lancaster, Pennsylvania (http://medschool.umaryland.edu/endocrinology/amish/research-program.asp). The OOA population of Lancaster County, PA immigrated to the Colonies from Western Europe in the early 1700's. There are now over 30,000 OOA individuals in the Lancaster area, nearly all of whom can trace their ancestry back 12-14 generations to approximately 700 founders. Investigators at the University of Maryland School of Medicine have been studying the genetic determinants of cardiometabolic health in this population since 1993. To date, over 7,000 Amish adults have participated in one or more of our studies. Due to their ancestral history, the OOA may be enriched for rare variants that arose in the population from a single founder (or small number of founders) and propagated through genetic drift. Many of these variants have large effect sizes and identifying them can lead to new biological insights about health and disease. The parent study for this WGS project provides one (of multiple) examples. In our parent study, we identified through a genome-wide association analysis a haplotype that was highly enriched in the OOA that is associated with very high LDL-cholesterol levels. At the present time, the identity of the causative SNP - and even the implicated gene - is not known because the associated haplotype contains numerous genes, none of which are obvious lipid candidate genes. A major goal of the WGS that will be obtained through the NHLBI TOPMed Consortium will be to identify functional variants that underlie some of the large effect associations observed in this unique population.

  Study phs000956

• Analysis of Somatic Mutations in Pediatric AML FAB-M7 Subtype by Whole Transcriptome Sequencing

  High resolution analysis of DNA copy number abnormalities and loss-of-heterozygosity on acute myeloblastic leukemia samples utilizing SNP arrays has demonstrated that in contrast to pediatric ALL, de novo AML is characterized by a very low burden of genomic alterations (Radtke, et al., PNAS, 2009). Samples for this study represented a cross-section of the different subtypes of pediatric AML. The only AML subtype that was an outlier from the above observations was acute megakaryocytic leukemia (AML FAB-M7), with the majority of these cases being characterized by complex chromosomal rearrangements and a high number of copy number alterations. To more fully define the genomic landscape of this subtype, we performed transcriptome sequence analysis on 14 pediatric FAB-M7 cases and mutation recurrence screening in a panel of 62 adult and pediatric AML FAB-M7 samples using the Illumina platform. Our results identified chromosomal rearrangements resulting in the expression of novel fusion transcripts in 11/14 cases. Remarkably, in 7/14 cases we detected an inversion on chromosome 16 that results in the juxtaposition of the CBFA2T3 gene next to the GLIS2 gene resulting in a CBFA2T3-GLIS2 chimeric gene that encoded an in frame fusion protein. This fusion led to the acquisition or preservation of self-renewal in colony forming assays, providing functional evidence for a role in leukemogenesis. In addition to novel chimeric transcripts, we found mutations in genes previously identified to play a role in megakaryoblastic leukemia that carry a proliferative advantage to the cell, such as JAK2 and MPL. These data demonstrate that AML FAB-M7 is characterized by cooperating Class I and Class II mutations leading to leukemogenesis.

  Study phs000413

• Foundation Medicine Adult Cancer Clinical Dataset (FM-AD)

  The Foundation Medicine adult cancer clinical dataset consists of 18,004 unique solid tumor samples that underwent genomic profiling on a single uniform platform as part of standard clinical care. The dataset is derived from the FoundationOne® genomic profiling assay version 2 that interrogates exonic regions of 287 cancer-related genes and selected introns from 19 genes known to undergo rearrangements in human cancer. Genomic DNA samples were sequenced to over 500x median coverage, and custom computational analyses identified all classes of genomic alterations (base substitutions, insertions and deletions, copy number alterations, and rearrangements). Since matched normal tissue was unavailable for analysis, these data underwent additional filtering to enrich for cancer-related events. The reported data includes genomic alterations that are known and suspected tumor drivers, as well as variants of unknown significance. To preserve patient anonymity, all known or suspected germline variants were removed from the data unless known to be associated with cancer development. The dataset contains genomic alteration profiles generated by FoundationOne version 2 testing for adult cancer patients (over 18 y.o.), and represents a vast diversity of tumor subtypes, including many rare diseases not profiled as part of large-scale profiling efforts. Cases are grouped into 16 broad disease categories containing tumors from 162 unique disease subtypes. Since specimens were profiled as part of clinical care, limited clinical parameters were available, including age, gender, tissue of origin, % of tumor nuclei, and diagnosis. Publication of this dataset is intended to allow the broad scientific community access to this unique cohort for use in scientific research projects of common and rare types of cancer, both for generating leads regarding causal mechanisms as well as cross-testing and confirming existing hypotheses. A pediatric cancer clinical dataset consisting of data from 1,215 patients under 18 y.o. is available separately at: FOUNDATION MEDICINE

  Study phs001179

• Glioblastoma stem cell lines RNA-seq (Guilhamon et al.)

  RNA was extracted from GSCs using the Qiagen RNeasy Plus kit. RNA sample quality was measured by Qubit (Life Technologies) for concentration and by Agilent Bioanalyzer for RNA integrity. All samples had RIN above 9. Libraries were prepared using the TruSeq Stranded mRNA kit (Illumina). Two hundred nanograms from each sample were purified for polyA tail containing mRNA molecules using poly-T oligo attached magnetic beads, then fragmented post-purification. The cleaved RNA fragments were copied into first strand cDNA using reverse transcriptase and random primers. This is followed by second strand cDNA synthesis using RNase H and DNA Polymerase I. A single “A” base was added and adapter ligated followed by purification and enrichment with PCR to create cDNA libraries. Final cDNA libraries were verified by the Agilent Bioanalyzer for size and concentration quantified by qPCR. All libraries were pooled to a final concentration of 1.8nM, clustered and sequenced on the Illumina NextSeq500 as a pair-end 75 cycle sequencing run using v2 reagents to achieve a minimum of ~40 million reads per sample.

  Dataset EGAD00001006813

• Quantification of chromosomal copy number aberrations by shallow whole-genome sequencing

  Detection of DNA copy number aberrations by shallow whole-genome sequencing (WGS) faces many challenges including lack of completion and errors in the human reference genome, repetitive sequences, polymorphisms, variable sample quality, and biases in the sequencing procedures.Formalin-fixed paraffin-embedded (FFPE) archival material, the analysis of which is important for studies of cancer, presents particular analytical difficulties due to degradation of the DNA and frequent lack of matched reference samples. We present a robust, cost-effective WGS method for DNA copy number analysis that addresses these challenges more successfully than currently available procedures. In practice very useful profiles can be obtained with 0.1 fold genome coverage. We improve on previous methods by; first, implementing a combined correction for sequence mappability and GC content, and second, applying this procedure to sequence data from the 1000 Genomes Project in order to develop a blacklist of problematic genome regions. A small subset of these blacklisted regions were previously identified by ENCODE, but the vast majority are novel unappreciated problematic regions. Our procedures are implemented in a pipeline called QDNAseq. We have analyzed over 1,000 samples, most of which were obtained from the fixed tissue archives of over 25 institutions.We demonstrate that for most samples our sequencing and analysis procedures yield genome profiles with noise levels near the statistical limit imposed by read counting. The described procedures also provide better correction of artifacts introduced by low DNA quality than prior approaches, and better copy number data than high-resolution microarrays at substantially lower cost.

  Study EGAS00001000642

• Whole Exome Sequencing of Calcitonin Producing Pancreatic Neuroendocrine Neoplasms (CT-pNENs) Indicates a Unique Molecular Signature

  Calcitonin-producing pancreatic neuroendocrine neoplasms (CT-pNENs), which can mimic clinical and laboratory features of medullary thyroid carcinoma, are an extremely rare clinical entity with approximately 60 cases reported worldwide. The molecular profile of CT-pNENs is not yet known. Whole-exome sequencing (WES) was performed on tumor and corresponding serum samples of five patients with increased calcitonin serum levels and histologically proven calcitonin-positive CT-pNENs. cBioPortal analysis and gene enrichment analysis with DAVID were performed to validate candidate genes. Immunohistochemistry was used to detect protein expression of MUC4 and MUC16 in CT-pNEN specimens. Common somatic mutations of pNENs like MEN1, ATRX and PIK3CA were identified in cases of CT-pNENs. New somatic SNVs in ATP4A, HES4, and CAV3 have not yet been described in CT-pNENs. Pathogenic germline mutations in FGFR4 and DPYD were found in three of five cases. Mutations of CALCA (calcitonin) and the corresponding receptor CALCAR were found in all five tumor samples, but none of them resulted in clinical or protein sequelae. All five tumor cases showed single nucleotide variations (SNVs) in MUC4, and four cases showed SNVs in MUC16, both of which were membrane-bound mucins. Immunohistochemistry showed protein expression of MUC4 and MUC16 in one case each, and the liver metastasis of a third case was double positive for MUC4 and MUC16. The homologous recombination deficiency (HRD) score of all tumors was low.CT-pNENs have a unique molecular signature compared to other pNEN subtypes, specifically involving the FGFR4, DPYD, MUC4, MUC16 and the KRT family genes. However, these WES data from only five cases must be interpreted with caution because causal interpretation of the mutational landscape in CT-pNENs is difficult. Further research is needed to explain differences in pathogenesis compared with other pNENs. In particular, multi-omics data such as RNASeq, methylation, and whole genome sequencing could be informative.

  Study phs003060

• Resource for Genetic Epidemiology Research on Adult Health and Aging (GERA)

  The Resource for Genetic Epidemiology Research on Aging (GERA) Cohort was created by a RC2 "Grand Opportunity" grant that was awarded to the Kaiser Permanente Research Program on Genes, Environment, and Health (RPGEH) and the UCSF Institute for Human Genetics (AG036607; Schaefer/Risch, PIs). The RC2 project enabled genome-wide SNP genotyping (GWAS) to be conducted on a cohort of over 100,000 adults who are members of the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), and participating in its RPGEH. The purpose of the RPGEH is to facilitate research on the genetic and environmental factors that affect health and disease by linking together clinical data from electronic health records, survey data on demographic and behavioral factors, and environmental data from various sources, with genetic data derived from biospecimens collected from participants. At the time of the award of the RC2 project in late 2009, the RPGEH had established a cohort of about 140,000 individuals who had answered a detailed survey, provided saliva samples for extraction of DNA, and given broad consent for the use of their data in studies of health and disease. To maximize the diversity of the resulting sample, the GERA cohort was formed by including all racial and ethnic minority participants with saliva samples (N = 20,925; 19%); the remaining participants were drawn sequentially and randomly from white non-Hispanic participants (89,341; 81%). A total of 110,266 participant samples were included to ensure that at least 100,000 were successfully assayed. The resulting GERA cohort is 42% male, 58% female, and ranges in age from 18 to over 100 years old with an average age of 63 years at the time of the RPGEH survey (2007). The sample is ethnically diverse, generally well-educated with above average income. Approximately 69% of the participants are married or living with a partner. Length of membership in KPNC averages 23.5 years. UCSF and RPGEH investigators worked with the genomics company Affymetrix to design four custom microarrays for genotyping each of the four major race-ethnicity groups included in the GERA Cohort, described in detail in Hoffmann et al., 2011a and 2011b. Following genotyping and quality control procedures, and after removal of invalid, discordant, or withdrawn samples, about 103,000 participants were successfully genotyped. The resulting genotypic data were linked to survey data and data abstracted from the electronic medical records. As described below, all RPGEH participants were mailed new consent forms with explicit discussion of the placement of data in the NIH-maintained dbGaP. About 77% of participants returned completed consent forms, resulting in a final sample size of 78,486 participants in the GERA Cohort with data for deposit into dbGaP. Origins of the RPGEH GERA Cohort The goal in creating the RPGEH GERA cohort was to create a large, multiethnic, and comprehensive population-based resource for research into the genetic and environmental basis of common age-related diseases and their treatment, and factors influencing healthy aging and longevity. The GERA Cohort consists of a diverse cohort of more than 100,000 adults who are members of the Kaiser Permanente Medical Care Plan, Northern California Region (KPNC), and participating in its Research Program on Genes, Environment and Health (RPGEH). KPNC is an integrated health care delivery system with a population of about 3.3 million people in northern California. The membership of KPNC is representative of the general population in the 14 county area in which facilities are located, although the membership is underrepresented for the extremes of income at both ends of the spectrum. The RPGEH utilizes the longitudinal electronic health records (EHR) of KPNC to obtain clinical, laboratory, imaging and pharmacy information on all cohort members, to which personal demographic, behavioral and health characteristics have been added through member surveys. The GERA Cohort comprises a subsample of the RPGEH participant cohort, and was created through the RC2 award from the NIA, NIMH, and NIH Common Fund as described above. GERA Study Design The GERA Cohort is a subsample, as described above, of the longitudinal cohort enrolled in the Kaiser Permanente RPGEH. The RPGEH cohort includes about 400,000 survey participants of whom about 200,000 have provided broad consent and a sample of saliva or blood for use in studies of genetic and environmental factors in health and disease. The GERA Cohort was developed from a mailed survey sent to all adult members of KPNC who had been members for two years or more in 2007. All survey respondents were contacted and asked to complete a consent form; those who completed consent forms were asked to provide a saliva sample. Additional male participants were added to the RPGEH through inclusion of the Northern California sample of the California Men's Health Study (CMHS) cohort of about 40,000 men from KPNC, ages 45-69 years old at the time of the CMHS survey in 2002-2003. The CMHS participants contributed about 15,400 saliva samples to the RPGEH and were eligible for inclusion in the GERA Cohort. CMHS participants were included according to the same sampling design as for the RPGEH cohort as a whole. Specifically, all minority participants were selected for inclusion in order to maximize representation of minorities in the GERA Cohort, and Non-Hispanic White participants were selected at random to complete the sample of 110,266 GERA Cohort participants. GERA Genotypic Data High-density genotyping was conducted at UCSF using custom designed Affymetrix Axiom arrays, as described in Hoffmann et al. (2011a; 2011b). To maximize genome-wide coverage of common and less common variants, four specific arrays were designed for individuals of Non-Hispanic White (EUR), East Asian (EAS), African-American (AFR), and Latino (LAT) race/ethnicity. There was broad overlap among the SNPs on the arrays, which were designed using a hybrid greedy imputation algorithm (Hoffmann et al., 2011b) applied to genotype information validated by Affymetrix from the 1000 Genomes Project. However, in order to capture low frequency variants specific to particular race-ethnicity groups, SNP content varies between arrays. A more detailed description of the process of genotyping and results is included in Genotyping of DNA Samples. Description of the analyses of population structure and development of principal components for adjustment of population structure is included in Population Structure Analysis. GERA Phenotypic Data RPGEH and CMHS Survey Data. The sources of data on demographic and behavioral factors deposited in dbGaP for the GERA Cohort are the RPGEH and CMHS surveys. Data on common demographic factors such as gender, race/ethnicity, marital status, and education and on behavioral factors such as smoking, alcohol consumption, and body mass index, have been cleaned, edited, reconciled between the two surveys, and compiled into summary indices, where appropriate, for deposition into dbGaP. A more complete description of the survey variables is included in Survey Variables Documentation. Please note that the terms of use of the GERA Cohort Data, as specified in the Data Use Certification (DUC), prohibit the use of survey variables as outcomes in analyses. For example, a genome-wide association study (GWAS) of education or smoking is not permitted as specified by the DUC. Only health conditions can be used as outcome variables in analyses. Health Conditions derived from Kaiser Permanente Electronic Medical Records. Data on the occurrence of health conditions in participants in the GERA Cohort have been derived from summarizing ICD-9 coded diagnoses in Kaiser Permanente's electronic medical records. An algorithm that aggregates specific ICD-9 codes into appropriate diagnostic groups for selected conditions is applied to outpatient and inpatient databases; see Disease and Conditions Definitions Documentation for details. The criterion for including a condition as "present" for a participant is the occurrence of two or more diagnoses within a diagnostic category occurring on separate days. Two or more is used as the criterion in order to reduce false positives due to mistakes or rule-out diagnoses. When compared with validated disease registries, the criterion of 2+ diagnoses yields high specificity and good sensitivity. ICD-9 codes in the electronic records are specified in several ways. For outpatient visits occurring during the period 1995 to 2006, diagnoses were assigned by the treating physician who endorsed specific diagnoses on an optically scanned list that varied by specialty. Beginning in 2006 with the advent of an integrated, fully electronic medical record, outpatient diagnoses are made by physicians/ providers using a pull down menu. Discharge diagnoses from inpatient stays are specified by physicians and coded by specially trained coders. Databases of ICD-9 codes for diagnoses assigned at outpatient visits, or as one of the discharge diagnoses following inpatient stays, are complete and available for all KPNC members dating back to 1995. Although the average length of KPNC membership among GERA cohort members is 23.5 years in 2007, not all have been members since 1995, so the history for some conditions, such as those that are not chronic or recurrent, may not be complete for all cohort members. The year of first membership in KPNC is included as a variable in the list of survey variables, enabling investigators to estimate the number of years of observation of each Cohort member. RPGEH Access and Collaborations Website and Procedures The RPGEH maintains a web portal for inquiries and applications for collaboration and access to data. The url is: https://rpgehportal.kaiser.org/. RPGEH has an application process and an Access Review Committee that reviews applications for collaboration and use. For more details, please contact RPGEH through the website.

  Study phs000674