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• Type 1 Diabetes Genetics Consortium (T1DGC): Genome-Wide Association Study in Type 1 Diabetes, 2008

  Cases with Type 1 Diabetes (T1D) in the UK, were part of the Wellcome Trust Case Control Consortium (WTCCC) - http://www.wtccc.org.uk - that first reported in 2007: Wellcome Trust Case Control Consortium (2007) Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447, 661-678. [PubMed: 17554300] In this genome-wide association study (GWAS), funded by the NIH and JDRF, and sponsored by the Type 1 Diabetes Genetics Consortium (T1DGC), we were able to extend the case and control groups used in the WTCCC, with the intention of performing a well-powered meta-analysis. The study is written up as: Barrett, J.C., Clayton, D.G., Concannon, P., Akolkar, B., Cooper, J.D., Erlich, H.A., Julier, C., Morahan, G., Nerup, J., Nierras, C., Plagnol, V., Pociot, F., Schuilenburg, H., Smyth, D.J., Stevens, H., Todd, J.A., Walker, N.M., Rich, S.S. and The Type 1 Diabetes Genetics Consortium Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nature Genetics, PMID: 19430480. Resources - data: * Case data from this study is deposited here (i.e. in dbGaP) * Control data from this experiment - with subjects from the 1958 British Birth Cohort - is deposited with the European Genotype Archive (EGA): http://www.ebi.ac.uk/ega/ from where the WTCCC data is also available. * A complete description of how to request all components of the meta-analysis is available at: http://www.t1dbase.org/page/PosterView/display/poster_id/324 * Additional genetic data on the same case subjects, including some HLA types, are available from the Juvenile Diabetes Research Foundation/Wellcome Trust Diabetes and Inflammation Laboratory (JDRF/WT-DIL): http://www-gene.cimr.cam.ac.uk/todd/ Resources - samples: Case and control DNA samples are also available: * Case DNA samples are available from the JDRF/WT-DIL, as above, and will be available from the NIDDK Genetics Repository at Rutgers: https://www.niddkrepository.org * Control DNA samples are available from the 1958 British Birth Cohort (aka National Child Development Study): http://www.cls.ioe.ac.uk/studies.asp?section=000100020003 Use restrictions: There are access limitations to both data and samples, in order to keep their use in line with subjects' consent.

  Study phs000180

• Copy-Number Analysis of Understudied Black Women Ovarian Cancers

  Two general types of genetic alterations drive cancer progression: mutations and copy number alterations (CNAs). With the exception of p53, single nucleotide variant mutations (here, simply "mutations") are not drivers of 80% of tumors within the most frequent and deadly histotype of ovarian cancer: serous ovarian cancer (SOC). Rather, CNAs are more prevalent in SOC than any other cancer type studied by phs000178 The Cancer Genome Atlas (TCGA). Fully two-thirds of genes are altered by CNAs in the average SOC. Bioinformatic methods have shown that these CNAs modulate specific molecular pathways, such as autophagy, and this finding enabled effective pathway-targeted therapies1. Unfortunately, TCGA ovarian cancer data lacks racial diversity. Only 6% of SOC tumors (n=32) studied are from African origin. Black women diagnosed with ovarian cancer are more likely to die from their disease than white women. Five-year survival after diagnosis is 31% among blacks versus 42% among whites, and this disparity is seen in every age group and tumor stage distribution. Dr. Kelemen examined data from 365 white and 95 black ovarian cancer patients from the Hollings Cancer Center (HCC) Cancer Registry between 2000 and 2015 and found that black women had an 81% higher risk of death after diagnosis compared to white women (HR 1.81, 95% CI 1.35-2.43), independent of diagnosis center (98% were treated at HCC but half were diagnosed elsewhere), tumor stage, histology, extent of residual tumor remaining following surgery, insurance status, smoking, type of treatment for ovarian cancer, and age-adjusted Charlson comorbidity index. This disparity remained even when restricted to women who received the standard of care, surgery-chemotherapy sequence (HR 1.79, 95% CI 1.10-2.89). Despite receiving the same treatment, black race was still associated with inferior survival. A similar disparity has been reported by others, indicating that the HCC experience is representative of national data. Here, an additional set of high-grade serous ovarian cancer primary tumors were acquired from biorepositories with a focus on expanding data originating from African American women. Data were analyzed for copy-number alterations using exome sequencing and control-FREEC software.

  Study phs002313

• RNA-Seq of Whole Blood from Patients with Intracranial Aneurysms

  Rupture of intracranial aneurysms (IAs) causes intracranial hemorrhaging that leads to high rates of neurological deficits and death. Although rupture rates are low, clinicians must decide whether to treat or monitor these potentially dangerous lesions. In the current clinical practice, the most common metric to measure risk of rupture is aneurysm size. However, clinical data show that small aneurysms can also rupture. As a result, alternative clinical stratification scores have been proposed, including the PHASES (Population, Hypertension, Age, Size, Earlier subarachnoid hemorrhage, and Site) score based on patient demographics and IA characteristics to stratify ruptured and unruptured IAs, and the Rupture Resemblance Score (RRS) that stratifies ruptured and unruptured IAs based on hemodynamic and morphological properties. However, all metrics require imaging on digital subtraction angiography (DSA), which is invasive, expensive, requires the use of X-rays, and is associated with transient or permanent neurological and non-neurological complications. We hypothesize that individuals with dangerous IAs have detectable gene expression differences in their blood that could be used as biomarkers to determine rupture risk. We propose to use whole blood transcriptomes to develop a "one-stop" diagnostic test that can detect the presence of IAs and determine the risk of rupture based on circulating RNA expression biomarkers using our prototype AneuScreenTM platform. We aim to develop and validate biomarkers to predict risk, as calculated by the currently-used metric of aneurysm size, the clinical PHASES score, and the RRS. Here, we collected blood samples from consented individuals who were receiving cerebral imaging at the Gates Vascular Institute (Buffalo, NY) for intracranial aneurysm. RNA extracted from blood samples (n=43) was subjected to RNA-sequencing and added to our existing database (n=44). When combined with our previous data, we had transcriptome data from 68 aneurysms (after additional sample filtering). This dataset was stratified into low- and high-risk according to IA size, PHASES score, and RRS score. Differentially expressed genes were identified and used to construct predictive models. Fastq files and basic demographic information for the 43 newly-sequenced intracranial aneurysm samples on this project will be available through dbGaP.

  Study phs003072

• NHLBI GO-ESP: Early-Onset Myocardial Infarction (Broad EOMI)

  The NHLBI "Grand Opportunity" Exome Sequencing Project (GO-ESP), a signature project of the NHLBI Recovery Act investment, was designed to identify genetic variants in coding regions (exons) of the human genome (the "exome") that are associated with heart, lung and blood diseases. These and related diseases that are of high impact to public health and individuals from diverse racial and ethnic groups will be studied. These data may help researchers understand the causes of disease, contributing to better ways to prevent, diagnose, and treat diseases, as well as determine whether to tailor prevention and treatments to specific populations. This could lead to more effective treatments and reduce the likelihood of side effects. GO-ESP is comprised of five collaborative components: 3 cohort consortia - HeartGO, LungGO, and WHISP - and 2 sequencing centers - BroadGO and SeattleGO. In the Grand Opportunities Exome Sequencing Program Early MI Project (GO ESP - EOMI), we are sequencing cases with extremely early-onset MI drawn from 8 cohorts. These cohorts include five hospital or community-based studies that ascertained individuals based on MI status. These include PennCATH, Cleveland Clinic Genebank, Massachusetts General Hospital Premature Coronary Artery Disease Study (MGH-PCAD), Heart Attack Risk in Puget Sound (HARPS), and Translational Research Investigating Underlying Disparities in Myocardial Infarction Patients' Health Status (TRIUMPH). Cases were selected based on MI occurring in men aged ≤50 years and women aged ≤60 years. In addition, early-MI cases are being drawn from three population-cohort studies including the Framingham Heart Study, the Women's Health Initiative, and the Atherosclerosis Risk in Communities Study. MI-free controls are being drawn from five population-based cohort studies including the Framingham Heart Study, the Women's Health Initiative, Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, and the Jackson Heart Study. Controls were selected based on two factors: (1) highest predicted risk for MI based on Framingham risk score; and (2) absence of prevalent or incident MI despite a high predicted risk.

  Study phs000279

• Centers for Common Disease Genomics (CCDG) - Whole Genome Sequencing in Type 1 Diabetes (T1DGC)

  The Type 1 Diabetes Genetics Consortium (T1DGC) was established to collect resources (biological samples and data) and conduct research to better understand the genetic basis of type 1 diabetes (T1D). Collection was initiated by ascertaining affected sib-pair families (both parents, two affected siblings and, when available, an unaffected sibling), collected from five geographic regions through four recruitment networks (Asia-Pacific, Europe, North America, United Kingdom). In addition, the T1DGC collected trio families (both parents and affected child) and cases and controls from low-prevalence populations (African-American, with four grandparents self-reporting as African ancestry; Mexican-American, with four grandparents self-reporting as ancestry from Mexico). The T1DGC also served as a repository for contributed collections from other studies, all meeting the broad data-sharing policy of the T1DGC, for inclusion in the genetic studies. These collections include T1D case samples ascertained from the UK Genetic Resource Investigating Diabetes (UK GRID) cohort, SEARCH for Diabetes in Youth (SEARCH), The Genetics of Kidneys in Diabetes (GoKinD), and control samples obtained from the British 1958 Birth Cohort, the UK National Blood Services collection, CLEAR (Consortium for the Longitudinal Evaluation of African-Americans with Early Rheumatoid Arthritis), the New York Cancer Project (NYCP), and other cohorts. For the NHGRI-funded Centers for Common Disease Genomics (CCDG) project, participants with T1D and ancestry-matched controls were identified through the T1DGC, either through direct ascertainment or by contribution from other sources to the T1DGC. As the CCDG has focused initially on non-Caucasian populations for whole genome sequencing, T1DGC participants of African, Mexican and Asian ancestry (targeting ~1200 cases and ~1200 controls in each ancestral group) and a small group of participants of Northern European ancestry (~100 cases, ~100 controls) were to be contributed to the study. Whole genome sequencing of T1DGC samples would be conducted at Washington University McDonnell Genome Institute and based upon matching case-control status within an ancestry group and prioritization by the CCDG.

  Study phs001222

• NIDDK IBD Genetics Consortium Ulcerative Colitis Genome-Wide Association Study

  This dataset contains data for 1,028 white, non-Hispanic, European ancestry individuals with ulcerative colitis who were included in a genome-wide association study published by Silverberg et al. (2009). These individuals were ascertained in North America and selected to have either left-sided or extensive disease (i.e., individuals with proctitis only were excluded). Genotyping was performed using the Illumina HumanHap300v2 (n = 540) and HumanHap550v3 (n = 488) Genotyping BeadChips at the Feinstein Institute for Medical Research. Control data (not included) were obtained from the NIDDK IBD Genetics Consortium's Crohn's Disease GWAS (available from dbGaP) and from studies 64 and 65 deposited in the Illumina iControlDB. Seven hundred eighty individuals in this dataset were taken from the NIDDK IBD Genetics Consortium cell line repository (http://www.niddkrepository.org). These individuals are identified in the file dbGaP_SubjectDS.txt. The subject IDs for these individuals may be used to request corresponding samples for follow-up research through the repository. In addition, complete phenotype data for these individuals are included, collected using the Consortium's forms and phenotyping manual (both included). The remaining 248 individuals were identified from pre-existing collections ascertained by members of the Consortium or their collaborators. For these samples, several of the items in the phenotype file are incomplete. Those who wish to replicate the results in Silverberg et al. should note that 6 individuals with missing genotype rates > 0.07 were excluded from that analysis (leaving 1,022 affected samples total). In addition, the minor allele frequencies (MAFs) reported in the publication were calculated using only those individuals who were included in the allelic association tests (n = 977 for SNPs included in the HumanHap300 and n = 476 for SNPs included only in the HumanHap550). These tests were performed using conditional logistic regression on gender-ancestry strata; individuals who were not placed in a stratum (using the procedure described in the supplementary information for Silverberg et al.) were excluded. The indicator variables hh300 and hh550 in the file dbGaP_PhenotypeDS.txt identify the samples included in the allelic association tests, and may be used to replicate the published MAFs among affected individuals.

  Study phs000345

• Genome-Wide Pleiotropy Scan Across Multiple Cancers

  A whole-exome sequencing (WES) study was conducted in 3,233 cases diagnosed with multiple primary cancers and 3,229 matched cancer-free controls (90% non-Hispanic white, 3% African-American, 3% East Asian, and 4% Latino) selected from individuals in the Kaiser Permanente Research Bank (KPRB) who were members of the Kaiser Permanente Northern California (KPNC) health plan. Cancer-free controls were matched to cases on age at specimen collection (within 2 years), sex, genotyping array (which matched on self-reported race/ethnicity), closest distance using the first two principal components for genetic ancestry, and reagent kit. Cases and controls were drawn from two prospective KPRB cohorts: the Research Program on Genes, Environment and Health (RPGEH) and the ProHealth study. Participants were sequenced by the Regeneron Genetics Center using the Illumina NovaSeq 6000 platform, and sample preparation and quality control were performed using a high-throughput, fully-automated system [PMID: 33087929]. Reads were aligned to the GRCh38 reference genome, and variants were called using WeCall [PMID: 33087929]. Participants with sex discordance, 20x coverage at less than 80% of targeted sites, and/or contamination greater than 5% were excluded. After quality control, we retained n = 6,247 (3,111 cases, 3,136 controls) individuals for downstream analyses. Among participants selected for this WES study, n = 5,432 (2,299 cases; 3,133 controls) consented to deposition of data to the National Institutes of Health (NIH).Further quality control was applied to filter low quality variants. Genotype calls with low depth of coverage (DP) were updated to missing (DP < 7 for SNPs and DP < 10 for indels), after which sites with low allele balance (AB) - variants without at least one sample having AB ≥ 15% for SNPs or AB ≥ 20% for indels - were removed. Lastly, variants with missingness > 10% and Hardy-Weinberg equilibrium p-value < 10-15 were excluded. Further description of quality control and downstream single-variant and gene-based analyses is available in Cavazos et al, 2022 [medRxiv].

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• B cell receptor silencing reveals origin and dependencies of high-grade B cell lymphomas with MYC and BCL2 rearrangements

  High-grade B cell lymphomas with MYC and BCL2 rearrangements (HGBCL-DH-BCL2) represent highly aggressive Germinal center (GC) derived B cell malignancies with dismal prognosis and limited therapeutic options. In the present study, we investigated the expression of BCR complex components, including immunoglobulin (IG) heavy (H) and light (L) chains, and CD79A and CD79B signaling subunits in HGBCL-DH-BCL2, scoring 65% of cases with undetectable IGH immunoreactivity (IGHUND). Transcriptomics (bulk RNA-seq) and genetic (whole exome/genome sequencing) analyses indicated that IGHUND and IGH+ HGBCL-DH-BCL2 lymphomas represent distinct biological entities. Specifically, IGHUND HGBCL-DH-BCL2 exhibit a GC DZ-like molecular program, and select subset-specific gene mutations pointing to distinct evolutionary trajectories respect to the IGH+ counterparts. IG profiling revealed that IGHUND HGBCL-DH-BCL2 preserved potentially productive, hypermutated IGH variable (V) gene rearrangements, indicating a selective advantage conferred to the malignant B cells by residual IGH molecules. Accordingly, disruption of the productively rearranged IGHG1 gene in BCRnull HGBCL-DH-BCL2 cell line model confirmed the dependency on IGH expression for optimal fitness. Using transcriptomics and in situ RNA-scope analysis, we reported that IGHUND HGBCL-DH-BCL2 originated from IG-class switched GC B cells, while IGH-expressing tumors were selected for continuous IGM expression. Moreover, while IGH+ HGBCL-DH-BCL2 favor IGM/IG-Kappa expression, IGHUND counterparts complete IG-Lambda light chain rearrangements. Notably, BCR silencing, caused by accelerated IGH turnover and reduced IGH expression, precedes HGBCL-DH-BCL2 onset, inducing RAG1/2-dependent IG light chain editing and eventually facilitating t(8;22)/IGL::MYC translocations. Finally, IGH silencing observed in HGBCL-DH-BCL2 cell models, which leads to intracellular retention/silencing of CD79B, results in reduced sensitivity to the CD79B-targeting antibody-drug conjugate Polatuzumab-vedotin. Collectively, HGBCL-DH-BCL2 originates from isotype-switched t(14;18)+ GC B cells that undergo IG light chain editing fuelling intra-clonal diversification, BCR silencing, and the acquisition of t(8;22) translocation, while preserving IGH dependency.

  Study EGAS50000001047

• Analysis of chromosomal background of cancerous mutations using a long-read sequencer

  In our previous study detecting cancerous complex SVs, we performed whole-genome sequencing of lung cancer clinical samples using PromethION. In this study, its depth and quality was substantially enriched and we conducted the phasing analysis in human lung cancer genomes. In addition, long read and short read RNA-seq was performed for transcriptome analysis.

  Study JGAS000349

• Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution

  We have used next generation sequencing to sequence genomes (>43-fold coverage) and transcriptomes of an oestrogen-receptor-alpha-positive metastatic lobular breast cancer at depth. We found 32 somatic non-synonymous coding mutations present in the metastasis, and measured the frequency of these somatic mutations in DNA from the primary tumour of the same patient.

  Study EGAS00000000054