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• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-Up Study: Research Studies in Hong Kong

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Hong Kong cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGaP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGaP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 500 526 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 530 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 352 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Risk of Myocardial Infarction Study (PROMIS) Pakistan 914 932 The research studies in Hong Kong contributed 493 cases and 485 controls to T2D-GENES Follow-Up study.

  Study phs001504

• Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow-Up Study: BioMe Biobank Program

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the BioMe Biobank cohort was part of the T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1294 1254 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 914 932 The BioMe Biobank study contributed 1294 cases and 1254 controls to T2D-GENES Follow-Up Study.

  Study phs001490

• Type 2 Diabetes Genetic Exploration by Next-generation Sequencing in Multi-Ethnic Samples (T2D-GENES) Follow up Study: Pakistan Genomic Resource (PGR)

  The ~52,000 sample Type 2 Diabetes Exome Sequencing project is a collaboration of six consortia with various funding mechanisms that have joined together to investigate genetic variants for type 2 diabetes (T2D) using the largest T2D case/control sample set compiled to date. This includes samples from: Type 2 Diabetes Genetic Exploration by Next-generation sequencing in Multi-Ethnic Samples (T2D-GENES) Genetics of Type 2 Diabetes (GoT2D) Exome Sequencing Project (ESP) Slim Initiative in Genomic Medicine for the Americas (SIGMA) Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCAMP) Progress in Diabetes Genetics in Youth (ProDIGY) This data generated from the Pakistan Genomic Resource (PGR) cohort was part of the T2-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) consortium, which is a NIDDK-funded international research consortium that seeks to identify genetic variants for type 2 diabetes (T2D) through multiethnic sequencing studies. The T2D-GENES Project is a multi-ethnic sequencing study designed to assess whether less common variants play a role in T2D risk and to assess similarities and differences in the distribution of T2D risk variants across ancestry groups. The individuals were obtained from over 20 cohorts across the 6 consortia that are listed in Table 1. The strategy was to perform deep exome sequencing of individuals, 24,991 with T2D and 24,953 controls, divided among five ancestry groups: Europeans, East Asians, South Asians, American Hispanics, and African Americans. The T2D-GENES, ProDIGY and SIGMA studies, sequencing was performed at the Broad Institute using the Agilent v2 capture reagent or Illumina Rapid Capture on Illumina HiSeq machines. Please note that while we summarize the full sample list in publications and below, two of the cohorts below are not in dbGAP, due to the samples not being consented for deposition. This includes the Kooperative Gesundheitsforschung in der Region Augsburg (KORA) study and Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) study. The Exome Sequencing Project (ESP) was deposited in dbGAP as part of their initial study and the phs numbers for that project can be found here: https://esp.gs.washington.edu/drupal/dbGaP_Releases. Table 1. 52,000 sample T2D Case/Control Whole Exome Sequencing Studies Ancestry Consortia Study Countries of Origin # Cases # Controls African American T2D-GENES Project 1 Jackson Heart Study US 502 527 African American T2D-GENES Project 1 Wake Forest School of Medicine Study US 518 532 African American ESP Exome Sequencing Project (ESP) US 467 1374 African American T2D-GENES Follow-Up Study BioMe Biobank Program (BioMe) US 1297 1256 East Asian T2D-GENES Project 1 Korea Association Research Project Korea 526 561 East Asian T2D-GENES Project 1 and Follow-Up Study Singapore Diabetes Cohort Study; Singapore Prospective Study Program Singapore (Chinese) 1486 1568 East Asian T2D-GENES Follow-Up Study Korea SNUH South Korea 450 475 East Asian T2D-GENES Follow-Up Study Research Studies in Hong Kong (Hong Kong) Hong Kong 493 485 European T2D-GENES Project 1 Ashkenazi US, Israel 506 355 European T2D-GENES Project 1 Metabolic Syndrome in Men Study (METSIM) Finland 484 498 European GoT2D Finland-United States Investigation of NIDDM Genetics (FUSION) Study Finland 472 476 European GoT2D Kooperative Gesundheitsforschung in der Region Augsburg (KORA) Germany 97 90 European GoT2D UK Type 2 Diabetes Genetics Consortium (UKT2D) UK 322 320 European GoT2D Malmö-Botnia Study Finland, Sweden 478 443 European LuCamp Lundbeck Foundation Centre for Applied Medical Genomics in Personalised Disease Prediction, Prevention, and Care (LuCamp) Denmark 997 997 European ESP Exome Sequencing Project (ESP) US 390 2843 European T2D-GENES Follow-Up Study Genetics of Diabetes and Audit Research Tayside Study (GoDARTS) Scotland, UK 960 966 European T2D-GENES Follow-Up Study Framingham Heart Study (FHS) US 396 596 Hispanic T2D-GENES Project 1 San Antonio Family Heart Study, San Antonio Family Diabetes/ Gallbladder Study, Veterans Administration Genetic Epidemiology Study, and the Investigation of Nephropathy and Diabetes Study Family Component US 272 218 Hispanic T2D-GENES Project 1 and SIGMA v2 Starr County, Texas US 1762 1738 Hispanic SIGMA v1 Mexico City Diabetes Study Mexico 281 549 Hispanic SIGMA v1 and SIGMA v2 Multiethnic Cohort (MEC) US 1476 1443 Hispanic SIGMA v1 and SIGMA v2 UNAM/INCMNSZ Diabetes Study (UIDS) Mexico 1998 1977 Hispanic SIGMA v1 and SIGMA v2 Diabetes in Mexico Study (DMS) Mexico 1522 1546 Multiethnic ProDIGY Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) US 3097 0 Multiethnic ProDIGY SEARCH for Diabetes in Youth (SEARCH) US 553 0 South Asian T2D-GENES Project 1 London Life Sciences Population Study (LOLIPOP) UK (Indian Asian) 531 538 South Asian T2D-GENES Project 1 and Follow-Up Study Singapore Indian Eye Study Singapore (Indian Asian) 1640 1478 South Asian T2D-GENES Follow-Up Study Pakistan Genomic Resource (PGR) Pakistan 903 930 The PGR study contributed 903 cases and 930 controls to T2D-GENES Follow-Up Study.

  Study phs001552

• Plasma MicroRNA Signatures of Aging

  Background. MicroRNAs are small non-coding RNAs that regulate gene expression post-transcriptionally and show differential expression in various tissues with aging phenotypes. Detectable in circulation, extracellular microRNAs reflect (patho)physiological processes and hold promise as biomarkers for healthy aging and age-related diseases. This study aimed to explore plasma extracellular microRNAs as biological aging indicator and their associations with health outcomes using population-level data. Methods. We quantified plasma expression levels of 2,083 extracellular microRNAs using targeted RNA-sequencing in 2,684 participants from the population-based Rotterdam Study cohort. The training and test sets included 1,930 participants from the advanced-aged initial and second subcohort (RS-I/RS-II; median age: 70.6), while the validation set comprised 754 participants from the middle-aged fourth subcohort (RS-IV; median age: 53.5). Based on 591 microRNAs well-expressed in plasma, we examined differential expression of microRNAs with chronological age, PhenoAge –a composite score of age and nine multi-system blood biomarkers–, the frailty index, and mortality. Next, elastic net models were employed to construct composite microRNA-based aging biomarkers predicting chronological age (mirAge), PhenoAge (mirPA), frailty index (mirFI), and mortality (mirMort). The association of these aging biomarkers with different age-related health outcomes was assessed using Cox Proportional Hazard, linear regression, and logistic regression models in the test and validation sets. Results. We identified 188 microRNAs differentially expressed with chronological age within the RS-I/RS-II advanced-aged population (ntraining=1158, ntest=772), of which 177 microRNAs (94.1%) were replicated in the middle-aged RS-IV subcohort (nvalidation=754). Moreover, 227 miRNAs showed robust associations with PhenoAge, 61 with FI, and 16 with ten-year mortality independent of chronological age. Subsequently, we constructed four plasma microRNA-based aging biomarkers: mirAge with 108, mirPA with 153, mirFI with 81, and mirMort with 50 miRNAs. Elevated scores on these microRNA-based aging biomarkers were associated with unfavorable health outcomes, including lower subjective physical functioning and self-reported health and increased mortality and frailty risk, but not with first- or multi-morbidity. Overall, larger effect estimates were observed for mirPA, mirFI, and mirMort compared to mirAge. Conclusions. This study describes distinct plasma microRNA-aging signatures and introduces four microRNA-based aging biomarkers with potential to identify accelerated aging and age-related decline, providing insights into the intricate process of human aging.

  Study EGAS00001008117

• Evolutionary trajectories and clonal migration underlying tumor progression and lymph node metastasis in resectable lung cancer

  In this prospective study, targeted deep sequencing was performed on a total of 160 primary tumors (474 regions) and 112 lymph nodes from 125 patients with stage I-III lung cancer (LuCaTH). Progressive evolution at clonal divergence scale was observed while specific driver events were positively selected for clonal sweeps during tumor development. Between-region genetic divergence (BRGD) of tumors were assessed and positively correlated with tumor differentiation. A machine learning algorithm was employed to evaluate clinicopathological and molecular parameters of primary tumors underlying lymph node metastasis. By analyzing clonal lineages and metastatic trajectories across multiple nodal stations, we unraveled a common sequential LNM seeding pattern but with divergent modes of clonal spread.

  Dataset EGAD00001007587

• Sequence data from stage I of the CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer

  The dataset for the study "Early ctDNA molecular response captures therapeutic response in the first stage of CCTG BR.36 ctDNA-directed, multi-center phase II study of molecular response adaptive immunotherapy in non-small cell lung cancer", includes 134 bam files from hybrid capture targeted error-correction next-generation sequencing (PGDx Elio plasma resolve) from plasma cell-free DNA and matched white blood cell DNA from 35 individuals with non-small cell lung cancer on the BR.36 trial, alongside 11 bam files from targeted next generation sequencing (PGDx Elio tissue complete) of tumor DNA from 11 individuals with non-small cell lung cancer on the BR.36 trial.

  Dataset EGAD00001011359

• A thymic ILC1-like progenitor with differentiation potential towards KIR+NKG2A- NK cells

  KIR+NKG2A- Natural Killer (NK) cells have the unique ability to detect downregulation of single HLA-I allotypes, frequently occurring in malignantly-transformed and virus-infected cells in order to escape T cell recognition. We have recently shown that circulating Innate Lymphoid Cells 1 (cILC1) have the potential to generate such KIR+NKG2A- NK cells but their developmental origin was unknown. Here we demonstrate that the development of cILC1 is thymus-dependent and identify a putative progenitor of cILC1s in the thymus, called thyILC1. Single-cell RNAseq analysis revealed a close relationship of thyILC1s to CD34+ double-negative (DN) thymocytes, but in contrast to DNs, thyILC1s had lost T cell differentiation potential. However, like cILC1s they could be efficiently differentiated into KIR+NKG2A- NK cells. thyILC1s strongly expressed RAG1/2, PTCRA (preTCR, and NOTCH1/3, but lacked expression of TCR chains, suggesting that they failed to pass the -selection checkpoint of thymocyte development. Finally, analyses of patients with FOXN1het deficiency, showing thymic hypoplasia due to lack of mature thymic epithelial cells, exhibited a profound deficiency of cILC1s but not cILC2s and cILC3s, demonstrating thymus dependency of cILC1s. Together, the data suggest that thyILC1s are the source of a novel thymus-dependent NK cell differentiation pathway that promotes generation of KIR+NKG2A- NK cells.

  Study EGAS50000000760

• A thymic ILC1-like progenitor with differentiation potential towards KIR+NKG2A- NK cells - sc

  KIR+NKG2A- Natural Killer (NK) cells have the unique ability to detect downregulation of single HLA-I allotypes, frequently occurring in malignantly-transformed and virus-infected cells in order to escape T cell recognition. We have recently shown that circulating Innate Lymphoid Cells 1 (cILC1) have the potential to generate such KIR+NKG2A- NK cells but their developmental origin was unknown. Here we demonstrate that the development of cILC1 is thymus-dependent and identify a putative progenitor of cILC1s in the thymus, called thyILC1. Single-cell RNAseq analysis revealed a close relationship of thyILC1s to CD34+ double-negative (DN) thymocytes, but in contrast to DNs, thyILC1s had lost T cell differentiation potential. However, like cILC1s they could be efficiently differentiated into KIR+NKG2A- NK cells. thyILC1s strongly expressed RAG1/2, PTCRA (preTCR, and NOTCH1/3, but lacked expression of TCR chains, suggesting that they failed to pass the -selection checkpoint of thymocyte development. Finally, analyses of patients with FOXN1het deficiency, showing thymic hypoplasia due to lack of mature thymic epithelial cells, exhibited a profound deficiency of cILC1s but not cILC2s and cILC3s, demonstrating thymus dependency of cILC1s. Together, the data suggest that thyILC1s are the source of a novel thymus-dependent NK cell differentiation pathway that promotes generation of KIR+NKG2A- NK cells.

  Study EGAS50000000790

• Sleep Abnormalities in Rare Genetic Disorders: Angelman Syndrome, Rett Syndrome, and Prader-Willi Syndrome

  This research study will investigate sleep behavior in the rare neurological disorders Angelman Syndrome (AS), Rett Syndrome (RTT), Prader-Willi Syndrome (PWS) and Early-onset Morbid Obesity (EMO). Sleep is very important to proper health and plays a critical role in learning, memory, brain development and brain function. Sleep disturbances can have negative effects on health and the quality of life of children and their families. Sleep disorders are common in individuals with AS, RTT, PWS and EMO. As a result, individuals with AS, RTT, PWS and EMO are at risk for sleep-related health problems that can worsen existing daytime behaviors and lead to additional problems with learning and memory. The principal objectives of the study are to: Characterize sleep behavior in individuals with Angelman Syndrome, Rett Syndrome, Prader-Willi Syndrome and Early-onset Morbid Obesity. Compare sleep behavior in these individuals with sleep behavior in normal controls Assess the natural history of sleep behavior in individuals with Angelman Syndrome, Rett Syndrome, Prader-Willi Syndrome and Early-onset Morbid Obesity About this Study This is a questionnaire study that will evaluate the sleep behavior of individuals with AS, RTT or PWS (participants), or unaffected siblings of individuals with AS, RTT or PWS (controls). Those participating in the study will already be registered with the Rare Disease Clinical Research Network (RDCRN) and have a confirmed diagnosis of AS, RTT or PWS or be an unaffected sibling. We will look at the medical records on file with the RDCRN to confirm diagnosis of AS, RTT or PWS. Study participants will participate in the study at their regularly scheduled RDCRN clinic visits. Participants will be asked to complete questionnaires at the study visits that will document their sleep behaviors. The questionnaires are not difficult and participants should be able to complete them in approximately 15-30 minutes. Parents and legal guardians are allowed to assist participants or answer on their behalf. Questionnaires will be administered at the initial study visit and at a 12 month follow-up visit to document any changes in sleep behavior. We hope to enroll approximately 1400 individuals with either AS, RTT or PWS or their unaffected siblings.

  Study phs001292

• Heart Failure: A Controlled Trial Investigating Outcomes of Exercise Training (HF-ACTION-BioLINCC)

  Accessing Data Please refer to “Authorized Access” below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.ObjectivesThe HF-ACTION study examined whether exercise training reduces a composite endpoint of all-cause mortality or all-cause hospitalization for patients with left ventricular systolic dysfunction and heart failure symptoms. Background Heart failure (HF) is a major and growing cardiovascular syndrome that is the end result of many cardiovascular disorders. Although evidence-based drug and device therapies decrease mortality, hospitalizations, and HF symptoms and improve quality of life, many patients treated with these regimens often remain burdened by dyspnea and fatigue, diminished exercise tolerance, reduced quality of life, recurrent hospitalizations, and early mortality. Whereas rest was traditionally recommended for HF patients, there has been evidence that physical deconditioning may play a key role in the progression of symptoms and poor outcomes. Previous studies have shown positive effects of exercise training on exercise capacity, quality of life, and biomarkers and suggest that exercise training might improve survival and decrease HF hospitalizations. Nonetheless, there remains a safety concern regarding exercise training in HF and a large scale, multicenter, controlled clinical trial was needed to provide definitive clinical outcome data. Participants A total of 2,331 participants were randomized. 2,130 consented to share data with non-commercial entities, and 1,753 consented to share for commercial purposes. Design All participants underwent baseline cardiopulmonary exercise testing. Test results were reviewed by investigators to identify significant arrhythmias or ischemia that would prevent safe exercise training, to determine appropriate levels of exercise training, and to establish training heart rate ranges. Demographics, socioeconomic status, past medical history, current medications, physical exam, and the most recent laboratory tests were obtained prior to randomization. All participants received detailed self-management educational materials which included information on medications, fluid management, symptom exacerbation, sodium intake, and physical activity. Participants randomized to the exercise training arm first participated in a structured, group-based, supervised exercise program, with a goal of 3 sessions per week for a total of 36 sessions in 3 months. The primary exercises were walking, treadmill, or stationary cycling. Exercise was initiated at 15 to 30 minutes per session at a heart rate corresponding to 60% of heart rate reserve, and was increased after 6 sessions to 30 to 35 minutes duration and 70% of heart rate reserve. Participants began home-based exercise after completing 18 supervised sessions and were to fully transition to home exercise after 36 supervised sessions. The target training regimen for home exercise was 5 times per week for 40 minutes at a heart rate of 60% to 70% of heart rate reserve. Participants randomized to the usual care group were not provided with a formal exercise prescription. To provide comparable levels of attention from study personnel, all participants were called every 2 weeks for the first 9 months, monthly until 24 months of follow-up, and quarterly thereafter. Participants returned for clinic visits every 3 months for the first 2 years of participation and yearly thereafter for up to 4 years. Follow-up assessments included cardiopulmonary exercise testing, a 6-minute walk test, and a physical activity questionnaire. The primary end point was a composite of all-cause mortality or all-cause hospitalization. Secondary end points included all-cause mortality, the composite of cardiovascular mortality or cardiovascular hospitalization, and the composite of cardiovascular mortality or HF hospitalization. Conclusions After adjustment for highly prognostic predictors of the primary end point, exercise training was associated with modestly significant reductions for both all-cause mortality or hospitalization and cardiovascular mortality or heart failure hospitalization.

  Study phs003599

• Exome-wide mutation analysis of cell-free DNA to simultaneously monitor the full spectrum of cancer treatment outcomes

  Purpose: Cell-free DNA (cfDNA) offers a non-invasive approach to monitor cancer. Here we develop a method using whole-exome sequencing (WES) of cfDNA for simultaneously monitoring the full spectrum of cancer treatment outcomes, including MRD, recurrence, evolution, and second primary cancers. Experimental Design: Three simulation datasets were generated from 26 cancer patients to benchmark the detection performance of MRD/recurrence and second primary cancers. For further validation, cfDNA samples (n=76) from cancer patients (n=35) with six different cancer types were used for performance validation during various treatments.Results: We present a cfDNA-based cancer monitoring method, named cfTrack. Taking advantage of the broad genome coverage of WES data, cfTrack can sensitively detect MRD and cancer recurrence by integrating signals across known clonal tumor mutations of a patient. In addition, cfTrack detects tumor evolution and second primary cancers by de novo identifying emerging tumor mutations. A series of machine learning and statistical denoising techniques are applied to enhance the detection power. On the simulation data, cfTrack achieved an average AUC of 99% on the validation dataset and 100% on the independent dataset in detecting recurrence in samples with tumor fraction ≥0.05%. In addition, cfTrack yielded an average AUC of 88% in detecting second primary cancers in samples with tumor fraction ≥0.2%. On real data, cfTrack accurately monitors tumor evolution during treatment, which cannot be accomplished by previous methods.Conclusion: Our results demonstrated that cfTrack can sensitively and specifically monitor the full spectrum of cancer treatment outcomes using exome-wide mutation analysis of cfDNA.

  Study EGAS00001005906

• Adenoma development in familial adenomatous polyposis and MUTYH‐associated polyposis: somatic landscape and driver genes

  Familial adenomatous polyposis (FAP) and MUTYH‐associated polyposis (MAP) are inherited disorders associated with multiple colorectal adenomas that lead to a very high risk of colorectal cancer. The somatic mutations that drive adenoma development in these conditions have not been investigated comprehensively. In this study we performed analysis of paired colorectal adenoma and normal tissue DNA from individuals with FAP or MAP, sequencing 14 adenoma whole exomes (eight MAP, six FAP), 55 adenoma targeted exomes (33 MAP, 22 FAP) and germline DNA from each patient.

  Dataset EGAD00001004332

• ELLIPSE Prostate Cancer Meta-Analysis and Genotyping

  The ELLIPSE Consortium is an international effort to discover risk loci for prostate cancer. It includes the meta-analysis of existing GWAS data as well as novel GWAS, exome, and iCOGS genotyping. The GWAS meta-analysis includes the following cases and controls from studies of European ancestry: UK GWAS stage 1 (Illumina Infinium HumanHap 550 Array: 1854 cases and 1894 controls), UK GWAS stage 2 (Illumina iSELECT: 3706 cases and 3884 controls), CAPS1 (Affymetrix GeneChip 500K: 474 cases and 482 controls), CAPS2 (Affymetrix GeneChip 5.0K: 1458 cases and 512 controls), BPC3 (Illumina Human610 Illumina: 2068 cases and 3011 controls), PEGASUS (HumanOmni2.5: 4600 cases and 2941 controls). The OMNI 2.5M genotyping was conducted for 977 prostate cancer cases from UKGPCS. The Exome SNP array genotyping was conducted for 4741 subjects from UKGPCS. The iCOGs genotyping was conducted for 10366 subjects which includes the Multiethnic Cohort (n=1648) and UKGPCS (n=8718). Below is a description of each study that contributed to the meta-analysis of men of European ancestry. Information about the studies that contributed to the multiethnic meta-analysis can be found on the associated study page and also in Conti et al (Nature Genetics, PMID:33398198).   UK GWAS Stage 1 (UK1) and Stage 2 (UK2): The UK Genetic Prostate Cancer Study (UKGPCS) was first established in 1993 and is the largest prostate cancer study of its kind in the UK, involving nearly 189 hospitals. We are based at The Institute of Cancer Research in Sutton, Surrey, and collaborate with the Royal Marsden NHS Foundation Trust. Our aim is to find genetic changes which are associated with prostate cancer risk. Our target is to recruit 26,000 gentlemen into the UKGPCS by 2017. Men are eligible to take part if they fit into at least one of the following groups: They have been diagnosed with prostate cancer at 60 years of age or under (up to their 61st birthday). They have been diagnosed with prostate cancer and a first, second or third degree relative where at least one of these men were diagnosed with prostate cancer at 65 years of age or under. They are affected and have 3 or more cases of prostate cancer on one side of their family. They are a prostate cancer patient at the Royal Marsden NHS Foundation Trust. We have to date recruited around 16,000 men on whom we have germline DNA and clinical data at diagnosis. The UK GWAS is based on genotyping of 541,129 SNPs in 1,854 individuals with clinically detected (non-PSA-screened) prostate cancer (cases) and 1,894 controls. 43,671 SNPs showing strong evidence of association in stage 1 were followed up by genotyping a further 3,268 cases and 3,366 controls from UK and Melbourne in stage2. CAPS1 and CAPS2: The CAPS (Cancer of the Prostate in Sweden) study represents a large Swedish population-based cancer study, comprising 3,161 cases and 2,149 controls, recruited between 2001 and 2003. Biopsy confirmed prostate cancer cases were identified and recruited from four out of six regional cancer registries in Sweden, diagnosed between July 2001 and October 2003. Clinical data including TNM stage, Gleason grade and PSA levels at time for diagnosis were retrieved through record linkage to the National Prostate Cancer Registry. Control subjects, who were recruited concurrently with case subjects, were randomly selected from the Swedish Population Registry and matched according to the expected age distribution of cases (groups of 5-year intervals) and geographic region. Whole blood was collected from all individuals for extraction of genomic DNA. A GWAS was conducted in two parts. In the first phase (CAPS1) 498 cases and 502 controls were genotyped, in the second phase 1,483 cases and 519 controls were genotyped. Genotyping was performed using the GeneChip Human Mapping 500K (CAPS1) and 5.0K (CAPS2) Array Set from Affymetrix (Santa Clara, CA). The National Cancer Institute Breast and Prostate Cancer Cohort Consortium, BPC3: BPC3 was a consortium of prospective cohort studies investigating genetic and gene-environmental risk factors for breast and prostate cancer. Each study selected cases and controls for this study as described below. The clinical criteria defining advanced prostate cancer (Gleason = 8 or stage C/D) were either obtained from medical records or cancer registries. The Gleason score source was either surgical specimens (radical prostatectomy or autopsy) or the diagnostic biopsy (needle biopsy or TURP). When multiple Gleason scores were available the surgical value was used. PLCO was removed from the analysis as the samples were included in the Pegasus GWAS described below. In total 2,473 advanced prostate cancer cases and 3,534 controls were included in the analysis following QC. ATBC, Alpha-Tocopherol, Beta-Carotene Cancer Prevention Study: ATBC was a randomized, placebo-controlled primary prevention trial to investigate whether α-tocopherol or ß-carotene supplementation reduced the incidence of lung or other cancers in male smokers. Between 1985 and 1988, 29,133 men ages 50 to 69 years were enrolled in the trial from Finland and randomized to supplementation (50 mg α-tocopherol, 20mg ß-carotene, or both) or placebo. Men with a prior history of cancer, other than non-melanoma skin cancer or carcinoma in situ, were excluded from participating. Incident cancer cases are identified through linkage with the Finnish Cancer Registry, which has ~100% ascertainment of cancer cases nationwide. Cases included 249 men diagnosed with advanced prostate cancer (Gleason = 8 or stage C/D) from 1985 to 2003 with DNA available. Controls were 1,271 men selected previously for a GWAS of lung cancer in ATBC without a diagnosis of prostate cancer. CPSII, Cancer Prevention Study II: CPSII is a cohort study started in 1982 to investigate the relationship between dietary, lifestyle and other etiologic factors and cancer mortality. Approximately 1.2 million men and women enrolled in the study from 50 states in the U.S. In 1992, a subset of these participants (n= ~184,000) were enrolled in the CPSII Nutrition Cohort to examine the relationship between dietary and other exposures and cancer incidence. Blood samples were drawn from approximately 39,376 members of the Nutritional Cohort from 1998 to 2001, and buccal cells were collected from 69,467 members from 2001 to 2002. Cancer cases are identified by self-report through follow-up questionnaires followed by verification through medical records and/or linkage to state cancer registries as well as death certificates. A total of 660 advanced prostate cancer cases (Gleason = 8 or stage III/IV) with a source of DNA were identified for this study. Controls were 660 men matched on ethnicity, date of birth, sample collection date and DNA type. EPIC, European Prospective Investigation into Cancer and Nutrition: EPIC is a prospective study designed to investigate both genetic and non-genetic risk factors for different forms of cancer. Study participants were almost all white Europeans. Approximately 500,000 individuals (150,000 men) in EPIC were recruited between 1992 and 2000, from 23 centers in 10 European countries. Overall approximately 400,000 subjects also provided a blood sample at recruitment. The methods of recruitment and details of the study design are described in detail elsewhere. In brief, study participants completed an extensive questionnaire on both dietary and nondietary data at recruitment. The present study includes subjects from advanced prostate cancer cases (Gleason = 8 or stage III/IV) matched to controls based on study center, length of follow-up, age at enrollment (± 6 months), fasting and time of day of blood collection (± 1 hour). The advanced prostate cancer subjects were from 8 of the 10 participating countries: Denmark, Germany, Greece, Italy, the Netherlands, Spain, Sweden and the United Kingdom (UK). France and Norway were not included in the current study because these cohorts only included female subjects. All participants gave written consent for the research and approval for the study was obtained from the ethical review board from all local institutions in the regions where participants had been recruited for the EPIC study. HPFS, Health Professionals Follow-up Study: HPFS began in 1986 and is an ongoing prospective cohort study of 51,529 United States male dentists, optometrists, osteopaths, podiatrists, pharmacists, and veterinarians 40 to 75 years of age. The baseline questionnaire provided information on age, marital status, height and weight, ancestry, medications, smoking history, disease history, physical activity, and diet. At baseline the cohort was 97% white, 2% Asian American, and 1% African American. The median follow-up through 2005 was 10.5 years (range 2-19 years). Self-reported prostate cancer diagnoses were confirmed by obtaining medical and/or pathology records. Prostate cancer deaths are either reported by family members in response to follow-up questionnaires, discovered by the postal system, or the National Death Index. Questionnaires are sent every two years to surviving men to update exposure and medical history. In 1993 and 1994, a blood specimen was collected from 18,018 men without a prior diagnosis of cancer. Prostate cancer cases are matched to controls on birth year (+/-1) and ethnicity. Controls are selected from those who are cancer-free at the time of the case’s diagnosis, and had a prostate-specific antigen test after the date of blood draw.   MEC, Multiethnic Cohort: The Multiethnic Cohort Study is a population-based prospective cohort study that was initiated between 1993 and 1996 and includes subjects from various ethnic groups - African Americans and Latinos primarily from Californian (great Los Angeles area) and Native Hawaiians, Japanese-Americans, and European Americans primarily from Hawaii. State drivers’ license files were the primary sources used to identify study subjects in Hawaii and California. Additionally, in Hawaii, state voter’s registration files were used, and, in California, Health Care Financing Administration (HCFA) files were used to identify additional African American men. All participants (n=215,251) returned a 26-page self-administered baseline questionnaire that obtained general demographic, medical and risk factor information. In the cohort, incident cancer cases are identified annually through cohort linkage to population-based cancer Surveillance, Epidemiology, and End Results (SEER) registries in Hawaii and Los Angeles County as well as to the California State cancer registry. Information on stage and grade of disease are also obtained through the SEER registries. Blood sample collection in the MEC began in 1994 and targeted incident prostate cancer cases and a random sample of study participants to serve as controls for genetic analyses. PHS, Physicians Health Study:PHS was a randomized trial of aspirin and ß carotene for cardiovascular disease and cancer among 22,071 U.S. male physicians ages 40-84 years at randomization; none had a cancer diagnosis at baseline. The original trial ended, but the men are followed. From 1982 to 1984, blood samples were collected from 14,916 physicians before randomization. Participants are sent yearly questionnaires to ascertain endpoints. Whenever a physician reports cancer, we request permission to obtain the medical records, and cancers are confirmed by pathology report. We obtain death certificates and pertinent medical records for all deaths. Follow-up for nonfatal outcomes in PHS is over 97% complete, and for mortality, over 99%. PLCO, Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial:PLCO is a multicenter, randomized trial to evaluate screening methods for the early detection of prostate, lung, colorectal and ovarian cancer. Between 1993 and 2001, over 150,000 men and women ages 55-74 years were recruited from ten centers in the United States (Birmingham, AL; Denver, CO; Detroit, MI; Honolulu, HI; Marshfield, WI; Minneapolis, MN; Pittsburgh, PA; Salt Lake City, UT; St. Louis, MO; and Washington, D.C.). Men randomized to the screening arm underwent prostate cancer screening with prostate-specific antigen (PSA) annually for six years and digital rectal exam annually for four years. Blood specimens were collected from participants randomized to the screening arm of the trial, and buccal cell specimens were obtained from participants randomized to the control arm. Cases included 754 men diagnosed with advanced prostate cancer (Gleason = 8 or stage III/IV) from either arm of the trial. Of these cases, 317 were genotyped previously as part of Cancer Genetic Markers of Susceptibility (CGEMS), a GWAS for prostate cancer. Controls included 1,491 men without a diagnosis of prostate cancer from the screening arm of the PLCO trial. All subjects provided informed consent to participate in genetic etiology studies of cancer and other traits. This study was approved by the institutional review boards at the ten centers and the National Cancer Institute. PLCO was removed from the meta-analysis of the BPC3 studies as a consequence of PEGASUS below. PEGASUS, Prostate cancer Genome-wide Association Study of Uncommon Susceptibility loci: Pegasus is a genome-wide association nested within the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial. PLCO is a multicenter, randomized trial to evaluate screening methods for the early detection of prostate, lung, colorectal and ovarian cancer. Between 1993 and 2001, over 150,000 men and women ages 55-74 years were recruited from ten centers in the United States (Birmingham, AL; Denver, CO; Detroit, MI; Honolulu, HI; Marshfield, WI; Minneapolis, MN; Pittsburgh, PA; Salt Lake City, UT; St. Louis, MO; and Washington, D.C.). Men randomized to the screening arm underwent prostate cancer screening with prostate-specific antigen annually for six years and digital rectal exam annually for four years. Blood specimens were collected from participants randomized to the screening arm of the trial, and buccal cell specimens were obtained from participants randomized to the control arm. Cases included 4,598 men of European ancestry diagnosed with prostate cancer from either arm of the trial and controls included 2,941 men of European ancestry without a diagnosis of cancer from the screening arm, matched on age and year of randomization. All subjects provided informed consent, and the study approved by the institutional review board at the National Cancer Institute. Funding:This work was supported by the GAME-ON U19 initiative for prostate cancer (ELLIPSE): U19 CA148537. The BPC3 was supported by the U.S. National Institutes of Health, National Cancer Institute (cooperative agreements U01-CA98233, U01-CA98710, U01-CA98216, and U01-CA98758, and Intramural Research Program of NIH/National Cancer Institute, Division of Cancer Epidemiology and Genetics). The ATBC study and PEGASUS was supported in part by the Intramural Research Program of the NIH and the National Cancer Institute. Additionally, this research was supported by U.S. Public Health Service contracts N01-CN-45165, N01-RC-45035, N01-RC-37004 and HHSN261201000006C from the National Cancer Institute, Department of Health and Human Services. CAPS: The Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden was supported by the Cancer Risk Prediction Center (CRisP; www.crispcenter.org), a Linneus Centre (Contract ID 70867902) financed by the Swedish Research Council, Swedish Research Council (grant: K2010-70X-20430-04-3), the Swedish Cancer Foundation (grant: 09-0677), the Hedlund Foundation, the Söderberg Foundation, the Enqvist Foundation, ALF funds from the Stockholm County Council. Stiftelsen Johanna Hagstrand och Sigfrid Linnér’s Minne, Karlsson’s Fund for urological and surgical research. We thank and acknowledge all of the participants in the Stockholm-1 study. We thank Carin Cavalli-Björkman and Ami Rönnberg Karlsson for their dedicated work in the collection of data. Michael Broms is acknowledged for his skillful work with the databases. KI Biobank is acknowledged for handling the samples and for DNA extraction. Hans Wallinder at Aleris Medilab and Sven Gustafsson at Karolinska University Laboratory are thanked for their good cooperation in providing historical laboratory results. UKGPCS would like to acknowledge the NCRN nurses and Consultants for their work in the UKGPCS study. We thank all the patients who took part in this study. This work was supported by Cancer Research UK (grants: C5047/A7357, C1287/A10118, C1287/A5260, C5047/A3354, C5047/A10692, C16913/A6135 and C16913/A6835). We would also like to thank the following for funding support: Prostate Research Campaign UK (now Prostate Cancer UK), The Institute of Cancer Research and The Everyman Campaign, The National Cancer Research Network UK, The National Cancer Research Institute (NCRI) UK. We are grateful for support of NIHR funding to the NIHR Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. The MEC was supported by NIH grants CA63464, CA54281 and CA098758. 

  Study phs001120

• A Genome-Wide Association Study in Patients Experiencing Breast Events While Receiving Adjuvant Aromatase Inhibitors for Early Breast Cancer on NCIC CTG Trial MA.27

  Source of patients:The source of the patients for this genome-wide case-control study was MA.27, which was conducted as a multi-cooperative group effort under the auspices of the NCI Breast Cancer Intergroup of North America. The NCIC Clinical Trials Group (CTG) serves as the coordinating group, with participation by the NCI-sponsored North Central Cancer Treatment Group, Eastern Cooperative Oncology Group (ECOG), Southwest Oncology Group, and Cancer and Leukemia Group B (CALGB). MA.27 involved postmenopausal women with histologically confirmed and completely resected invasive breast cancer with surgical margins clear of invasive carcinoma in the following TMN categories (AJCC Version 6): pT1, pT2, pT3; pNx, pN0, pN1, pN2, pN3 (only when the sole basis is presence of 10 or more involved axillary nodes); MO. The primary tumor must have been estrogen receptor (ER) and/or progesterone receptor positive. Patients were stratified by lymph node status at diagnosis, prior adjuvant chemotherapy, and trastuzumab use and were randomized to 5 years of adjuvant therapy with anastrozole or exemestane. The trial was activated on May 26, 2003, and reached its accrual objectives on July 31, 2008, after the randomization of 6827 North American patients, with the majority (79%) providing DNA and consent for genetic testing. Non-North American patients were also entered by the International Breast Cancer Study Group but they did not contribute DNA. From 2003 to December 21, 2004, patients also underwent a second randomization to celecoxib 400 mg twice daily or placebo but, after the entry of 1,622 patients, this treatment was discontinued because of reports of increased cardiovascular risk associated with celecoxib. The final results of this study have been published, see Goss et al., 2013 (23358971). The patients in this analysis came from three cohorts: Cohort 1 consisted of 870 patients genotyped on the Illumina Human610-Quad BeadChip studied in a GWAS with the phenotype of musculoskeletal adverse event, see Ingle et al., 2010 (20876420), Cohort 2 consisted of 882 patients genotyped on the Illumina OmniExpress platform studied in a GWAS with the phenotype of fragility fractures, see Liu et al., 2014 (25148458), and the remaining 2913 patients were genotyped with the Illumina OmniExpressExome platform.

  Study phs001043

• Study of Melanoma Risk in Australia and the United Kingdom

  The results from a small number of melanoma GWAS have been published. Initial studies identified several pigmentation- and nevus-associated loci that mediate an effect on melanoma risk, however, these studies were somewhat limited in that sample number (hence power) was low, they used first-generation low density SNP arrays, or used pools of DNA samples. Subsequently, additional melanoma GWAS have been completed, including a "Phase 2" study by the International Melanoma Genetics Consortium (GenoMEL), a full GWAS of the Australian sample resource previously used in a pooled-DNA GWAS, and study conducted through the MD Anderson Cancer Center and the Brigham and Women's Hospital. The groups who performed these studies have recently shared data and replicated a number of new melanoma susceptibility loci. Aside from the identification of novel loci, there are two additional notable outcomes of these studies. Firstly, an examination of the observed versus expected test statistics (Q-Q plot) from the Australian study, even after removing data from SNPs within known replicated susceptibility loci, reveals that there remains an excess of positive results. Similarly, the latest GenoMEL study finds almost three times as many SNPs reaching p-values between 10-4 and 10-5 as would be expected by chance. In the light of other studies of complex traits [1], these data suggest that studies based on additional melanoma samples from the same population are likely to identify an even larger "polygenic tail" and should prove invaluable in identifying and characterizing the underlying loci. A second observation, is that the effect size for replicated associations differs very little between GWAS. Given the strong effect of ultraviolet radiation (UVR) on risk of melanoma this might be expected to affect penetrance, particularly in the Australian and English samples, which are ethnically similar, but have very different sun exposures. We hypothesize that those SNPs whose effects are strongly mediated by UVR exposure may have smaller marginal effects on risk and are therefore harder to detect initially, suggesting a whole category of genetic effects that are unexplored.Indeed, most melanoma GWAS performed to date used samples from both European and Australian populations in discovery and or replication, and thus, existing studies have been poorly powered to detect associations with a wide difference in effect between these low- and high-UVR populations. Here, we wish to pursue this hypothesis further and plan to genotype additional cases drawn from the English and Australian populations. This will serve two complementary objectives: firstly, it will greatly increase our collective power to detect additional new melanoma risk alleles; secondly, it will highlight associations that are stronger specifically within the context of either low-UVR or high-UVR exposure environments. We posit that these data will be invaluable, not just for identifying novel melanoma-associated loci, but also for addressing gene-environment interactions. We have available a collection of valuable resources to help fulfill our aims. These include a considerable number of well-characterized and ungenotyped Australian and UK melanoma cases, as well as existing genotype data from sets of Australian and UK cases and population-based controls. We propose the following Specific Aims: To extend our current collective melanoma GWAS by genotyping a large number of additional UK and Australian cases. To jointly analyze these data and identify new melanoma risk loci. To determine whether pre-existing and new melanoma risk alleles show different degrees of association between the English and Australian populations, and assess whether these differences might be due to differences in sunlight exposure.

  Study phs000519

• SNP array files, IDAT files, from 34 members of a Family with a high prevalence of psychosis

  We investigated the genetic causes of major mental disorders (MMDs) including schizophrenia, bipolar disorder I, major depressive disorder, and attention deficit hyperactive disorder, in a large family pedigree from Alpujarras, South of Spain, a region with a high prevalence of psychotic disorders. We applied a systematic genomic approach based on karyotyping (N=4), genotyping by genome-wide SNP array (N=33), whole-exome sequencing (N=4), and whole-genome sequencing (N=12). We performed genome-wide linkage analysis, family-based association analysis, and polygenic risk score estimates. Significant linkage was obtained at chromosome 9 (9q33.1-33.2, LOD score= 4.11), a suggestive region that contains five candidate genes ASTN2, BRINP1, C5, TLR4, and TRIM32, previously associated to MMDs. Comprehensive analysis associated the MMD phenotype with genes of the immune system with dual brain functions. Moreover, the psychotic phenotype was enriched for genes involved in synapsis. These results should be considered once studying the genetics of psychiatric disorders in other families, especially the ones from the same region, since founder effects may be related to the high prevalence.

  Study EGAS00001004592

• ATAC-seq of a selected group of AML cases

  ATAC-seq data were generated for a number of selected patients to investigate changes in enhancer and promoter regions. ATAC-seq was essentially carried out as described in31. Briefly, prior to transposition the viability of the cells was assessed and 1 × 106 cells were treated in culture medium with DNase I (Sigma) at a final concentration of 200 U ml−1 for 30 minutes at 37 °C. After Dnase I treatment, cells were washed twice with ice-cold PBS, and cell viability and the corresponding cell count were assessed. 5 × 104 cells were aliquoted into a new tube and spun down at 500 × g for 5 minutes at 4 °C, before the supernatant was discarded completely. The cell pellet was resuspended in 50 µl of ATAC-RSB buffer (10 mM Tris-HCl pH 7.4, 10 mM NaCl, 3 mM MgCl2) containing 0.1% NP-40, 0.1% Tween-20, and 1% Digitonin (Promega), and was incubated on ice for 3 minutes to lyse the cells. Lysis was washed out with 1 ml of ATAC-RSB buffer containing 0.1% Tween-20. Nuclei were pelleted at 500 × g for 10 minutes at 4 °C. The supernatant was discarded carefully and the cell pellet was resuspended in 50 µl of transposition mixture (25 µl 2× tagment DNA buffer, 2.5 µl transposase (100 nM final; Illumina), 16.5 µl PBS, 0.5 µl 1% digitonin, 0.5 µl 10% Tween-20, 5 µl H2O) by pipetting up and down six times. The reaction was incubated at 37 °C for 30 minutes with mixing before the DNA was purified using the Monarch PCR & DNA Cleanup Kit (NEB) according to the manufacturer’s instructions. Purified DNA was eluted in 20 µl elution buffer (EB) and 10 µl purified sample was objected to a ten-cycle PCR amplification using Nextera i7- and i5-index primers (Illumina). Purification and size selection of the amplified DNA were carried out with Agencourt AMPure XP beads. For purification the ratio of sample to beads was set to 1:1.8, whereas for size selection the ratio was set to 1:0.55. Purified samples were eluted in 15 µl of EB. Quality and concentration of the generated ATAC libraries were analyzed using the High Sensitivity D1000 ScreenTape Kit (Agilent) and libraries were sequenced paired-end on a NovaSeq (Illumina). ATAC-seq reads were aligned to the human reference genome build hg19 with bowtie2

  Dataset EGAD00001007583

• HIPO016 - glioblastoma tumour methylation microarray profiling

  Methylation microarray profiling (Illumina Human Methylation 450k and EPIC platforms) of 60 adult glioblastomas. Tumours were subtyped using the approach from Sturm et al. (https://doi.org/10.1016/j.ccr.2012.08.024): 12 IDH, 18 MES, 12 RTK I, 18 RTK II. DNA was prepared, assayed on the microarrays, and raw data computationally processed as described in Capper et al., "DNA methylation-based classification of central nervous system tumours": https://www.nature.com/articles/nature26000

  Dataset EGAD00010001797

• Acute Respiratory Distress Network Early Versus Delayed Enteral Feeding to Treat People with Acute Lung Injury or Acute Respiratory Distress Syndrome (ARDSNet EDEN-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Biospecimens: Access to Biospecimens is through the NHLBI Biologic Specimen and Data Repository Information Coordinating Center (BioLINCC). Biospecimens from ARDSNet-EDEN include bronchial lavage, plasma, DNA, and urine. Please note that use of biospecimens in genetic and non-genetic research is subject to a tiered consent. Objectives: To determine if initial lower-volume trophic enteral feeding would increase ventilator-free days (VFDs) and decrease gastrointestinal intolerances compared with initial full enteral feeding. Background: Mechanically ventilated patients cannot eat normally and if not fed for long periods become malnourished. Because malnutrition is associated with poor outcomes in critically ill patients, artificial nutrition is often provided, especially in those with acute lung injury (ALI) and with expected longer duration of mechanical ventilation. When feasible, enteral nutrition targeting full caloric needs has been advocated over parenteral nutrition. However, feeding intolerance and common care practices often serve as practical barriers to reaching recommended goals. Although confounded by indication and severity of illness, several observational studies have shown improved clinical outcomes, including fewer infections, shorter duration of mechanical ventilation, and lower mortality for patients receiving a higher percentage of calculated caloric needs. Nonetheless, the best timing, formulation, and amount of enteral nutrition remain unknown. Participants: A total of 1,000 participants were enrolled. Design: Participants were randomized, stratified by site and presence of shock at enrollment, to receive either trophic or full enteral feeding for the first 6 days of mechanical ventilation. The initial 272 patients were also simultaneously randomized to a separate trial (the OMEGA study) comparing a nutritional supplement containing omega-3 fatty acids and antioxidants with an isocaloric, isovolemic control in a 2 × 2 factorial design.The designated feeding strategy was initiated within 6 hours of randomization and continued until death, extubation, or day 6. The care of mechanically ventilated patients still receiving enteral feedings after day 6 was managed according to the full feeding strategy in both groups. In extubated patients who then required reintubation, enteral nutrition was restarted and managed according to the study protocol.In the full-feeding group, enteral nutrition was initiated at 25 mL/h and advanced to goal rates as quickly as possible. Gastric residual volumes were checked every 6 hours while enteral feeding was increased. Patients randomized to the initial trophic-feeding group had enteral nutrition initiated at 10 mL/h (10-20 kcal/h) for the first 272 patients who also received the omega-3 or control supplement (240 mL volume per day). After the data and safety monitoring board stopped the OMEGA portion of the factorial design, the initial trophic feeding rate was changed to 20 kcal/h to approximate the calories that had been delivered in the OMEGA study. Gastric Residual Volumes (GRVs) were checked every 12 hours during trophic feeding. In patients randomized to trophic feeding, enteral nutrition was advanced to full-energy feeding rates following the same protocol used for the full-feeding group if they were still receiving mechanical ventilation at 144 hours. Conclusions: There was no difference between groups with regard to the primary end point, VFDs to day 28. There also were no differences in 60-day mortality, organ failure−free days, ICU-free days, or the incidence of infection between groups. Similarly, there were no differences between groups in VFDs or survival when analyzed by body mass index category or when subsets of patients with shock or more severe lung injury (acute respiratory distress syndrome) were examined.JAMA. 2012 Feb 22;307(8):795-803

  Study phs004168

• Genetic Markers of Lipids in Indians: A Validation Study of Most Relevant Findings of Genome-Wide Association Studies

  We aimed to validate the GWAS loci (identified in European populations) related to serum lipid levels (total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and very low-density lipoprotein cholesterol (VLDL-C)) in the Indian population originally recruited to examine the 20-year trend of cardiometabolic risk factors in rural and urban areas around National Capital region in India. Isolated DNA was processed for genotyping of 12 established GWAS variants using multiplex Sequenom Mass ARRAY technology. We examined the association of these genetic variants with different lipid levels and found association of eight variants for lipid levels. We also derived weighted genetic risk scores (wGRAS) using the validated variants. The wGRS for triglycerides and VLDL-C was derived based on four associated variants (rs174546 at FADS1, rs17482753 at LPL, rs2293889 at TRPS1, rs4148005 at ABCA8, rs4420638 at APOC1) which was associated with 36.31 mg/dL elevated triglycerides and VLDL-C (β=0.95, SE=0.16, pTRPS1 and rs4147536 at ADH1B) was associated with 40.62 mg/dL higher total cholesterol (β=1.01, SE=0.23, pTRPS1, rs4147536 at ADH1B, rs4420638 at APOC1 and rs660240 at CELSR2). The wGRS derived from five associated variants (rs174546 and FADS1, rs17482753 at LPL, rs4148005 at ABCA8, rs4420638 at APOC1 and rs7832643 at PLEC) was associated with 10.64 mg/dL lower HDL-C (β= -0.87, SE =0.14, pThe phenotypic and genotypic data will be made available on the dbGaP portal for access.

  Study phs003469

• Cell-free DNA Methylome Analysis Enables Early Preeclampsia Prediction

  This dataset contains in solution target-enrichment bisulfite sequencing of placental tissue, buffy coat and plasma DNA from pregnant women. Blood samples were taken for cell-free DNA (cfDNA) DNA extraction from 64 women at the time of early-onset preeclampsia (PE) diagnosis, or from 38 controls (uncomplicated pregnancies) at a similar gestational age that did not develop preeclampsia subsequently. Among these subjects, plasma samples from 7 PE patients and 6 controls were also subjected to oxidative bisulfite sequencing. Placental tissues from 11 PE and 26 control subjects after delivery, and buffy coat from 16 PE and 16 control subjects at the same time of cfDNA sampling were profiled. A discovery cohort for early PE assessment in the first trimester was collected. In this cohort, cfDNA from 75 pregnancies that went on to develop early-onset PE and from 124 matched controls were collected and methylome sequencing were carried out. An independent validation cohort to validate early PE assessment with methylome profiling was collected as well. This validation cohort includes cfDNA samples from 61 PE and 136 control pregnancies.

  Dataset EGAD00001010159

• California Pacific Medical Center Research Breast Health Cohort

  Description of Cohort: The California Pacific Medical Center (CPMC) Breast Health Cohort is a cohort study based at CPMC and is linked to the San Francisco Mammography Registry, one of the sites of the NCI-funded Breast Cancer Screening Consortium (U01CA063740). CPMC is a community hospital in San Francisco, which has one of the highest volumes for mammography in San Francisco. Between September 2004 and June 2007, >90,000 mammograms were performed at CPMC. The CPMC breast health cohort collects demographic and risk factor data on women receiving mammography through participation in the San Francisco Mammography Registry, as part of the Breast Cancer Screening Consortium (U01CA063740). The SFMR database collects information from all sources, including a questionnaire on demographic and risk factor information, the clinical results of the breast examination, the measures of breast density by Dr. John Shepherd and the women who agreed to donate a blood sample. By merging these various sources of information we have very efficiently developed a large sample of women who have donated blood and have had a measure of mamographic density. Blood Collection: Dr. Steve Cummings is leading an effort to collect and archive blood samples from women who are receiving mammography screening. All women who are sent for a screening mammogram at CPMC are considered eligible. Since the cohort began collecting blood samples in July 2004 until June 2007, samples have been collected from over 11,000 women. Measurement of Breast Density: Dr. John Shepherd is currently measuring breast density in a large fraction of the cohort using an automated approach with single X-ray absorptiometry. Dr. Shepherd has established a link with the CPMC mammography center that allows him to collect routine digital mammography information. Using the data from the mammogram, Dr. Shepherd and his group have developed the single X-ray absorptiometry (SXA) technique for measuring density which is described in more detail below. The table demonstrates the distribution of demographic variables and some breast cancer risk factors of women who donated blood and had a breast density measurement in the CPMC breast health cohort. Nearly 80% of the participants are Caucasian and most of the women are post-menopausal with a median age of ~52. Since it will be difficult to accrue a large enough sample from each ethnic group, our study will focus only on Caucasian women. Table: Demographic variables, reproductive history and family history of breast cancer among 2962 women participating in the CPMC cohort study who contributed blood samples between 1994-1997. Variable Median/Percentage Age (Median/IQR) 52 (46-59) Ethnicity Caucasian/White 0.76 Asian/Pacific Islander 0.141 Hispanic 0.029 Mixed Race/Ethnicity 0.039 African American/Black 0.022 American Indian 0.001 Other 0.009 First degree relative with breast cancer 0.17 Age at first birth Nulliparous 0.39 Age<20 0.043 Age>40 0.032 Age<30, ≥20 0.251 Age>30, ≤40 0.282 Measurement of Breast Density in Cohort: Measurement of breast density is accomplished using an automated technique for all mammograms obtained by Dr. Shepherd using Single X-Ray absorptiometry (SXA). SXA measurement of breast density is done on approximately 30% of all screening mammograms. Below we describe the method for measurement of breast density by SXA by Dr. Shepherd's group and its validation and association with breast cancer. As we demonstrate below, breast density, as measured by SXA, is an automated, highly reproducible measure of the density of breast tissue and is associated with breast cancer risk. SXA for Quantifying Breast Density: Single x-ray absorptiometry (SXA) was initially developed for measuring bone density. SXA can determine the fraction of each of two densities simultaneously using the fact the sample is a constant thickness, the thickness in known, and the total attenuation is known. In applying this technique to breast density, we assume a two compartment model: fat and non-fatty (fibroglandular tissue). We use a reference material composed of various concentrations of two materials: one which is the same density as fat and another which is the same density as fibroglandular tissue. The reference material (phantom) is placed in the X-ray field with each mammogram. We have been able to implement this in a way that is unintrusive to the patient and technologist at CPMC. Assuming this two-compartment model and a constant known breast thickness, we can then calculate the percent density at any region of the breast based on the assumption that % pixel grey-scale is proportion to the mass fractions of breast fat and lean tissue. If reference materials (a phantom) of fat and fibroglandular tissue are imaged with the patient's breast and the reference materials have the same thickness as the patient's breast, then the breast's grey-scale values can be converted to fat/fibroglandular mass fractions by interpolating between those two references. The total percent density is found by averaging the volume fraction over all breast pixels. The phantom being used for breast density assessment at CPMC began to be used in September 2004. The phantom does not have to be manipulated by the technologist and stays attached on the mammography device during standard craniocaudal (CC) views. Thus it creates minimal to no interference with the clinical mammogram. Reproducibility of breast density measures: Traditional measures of mammographic density require some human interpretation. A human reader outlines the area perceived to be dense and a computer then calculates the percent area outlined as a percent of the entire image. Thus, while traditional mammographic density is associated with breast cancer risk, it has some limitations. In a study by Drs. Shepherd, Kerlikowske, et al., the correlation coefficient (Pearson's R) between different readers was 0.8-0.9. In contrast to the traditional mammographic density measurement, the SXA measurement is fully automated and, therefore, the reproducibility of the measurement is higher. Dr. Shepherd and colleagues have performed a replication study of SXA as a measurement of breast density. They have estimated the correlation coefficient of the SXA measurement of breast density to be >0.98. Thus, as expected for an automated measure, SXA is a highly reproducible measure of mammographic breast density. Drs. Shepherd and Kerlikowske have recently analyzed the association between breast cancer risk and breast density as measured by SXA (Shepherd et al., Cancer Epi Biomarkers and Prev, 2011, PMID: 21610220). They found that women in the highest quintile of % volumetric density had an odds ratio of 4.1 (95% CI: 2.3 - 7.2) for breast cancer risk compared to women in the lowest quintile of volumetric density. Thus volumetric density appears to be a highly reproducible, automated measure of breast cancer.

  Study phs000395

• Innate Immune Anti-Viral Deaminase Deregulation Fuels Pre-Leukemia Stem Cell Evolution

  This study evaluates the effect of Rebecsinib treatment on gene expression, isoform splicing, and ADAR1 mediated RNA editing in cells from an in vivo humanized mouse model which have been engrafted with human secondary AML cells. For analysis of cells from Rebesinib-treated animals, CD34+ cells were obtained from bone marrow and spleens of sAML-engrafted mice following once weekly treatment with 0 (Vehicle) or 5 or 10 mg/kg Rebecsinib. For analysis of cells from serial transplant recipients of cells harvested from Rebecsinib-treated mice, CD34+ cells were obtained from bone marrow and spleens of sAML-engrafted mice that were transplanted with cells from animals that received twice weekly treatment with 0 (Vehicle) or 10 mg/kg Rebecsinib. No further treatment was given to serial transplant recipients, thus allowing the analysis of molecular changes that are sustained following serial transplantation. Whole transcriptome sequencing was performed at The Scripps Research Institute Next Generation Sequencing Core on Illumina NextSeq 500 sequencers with 150bp paired-end reads.These data revealed a uniquely expressed ADAR1 splice isoform (with a retrained intronic region), global downregulation of normalized RNA editing events, and isoform switching from MCL1-L to MCL1-S in Rebecsinib-treated sAML-engrafted mice. These results demonstrate the anti-survival and anti-self-renewal effects of Rebecsinib treatment on the leukemia stem cell (LSC) population in sAML-engrafted mice as well as the reduction in the inflammation-induced, hyper-editing p150 isoform of ADAR1. Thus, Rebecsinib treatment has promise for reducing the LSC population in myeloproliferative disorders and associated cancers.

  Study phs002228

• Cellular Indexing of Transcriptomes and Epitopes Sequencing (CITE-Seq) Analysis to Investigate the Impact of Granulocyte-Colony Stimulating Factor on CRISPR/Cas9 Gene Edited Human Hematopoietic Stem Cell Function

  Our research using in-vivo preclinical xenograft mouse models demonstrated that G-CSF impedes engraftment of CRISPR-Cas9 gene edited human hematopoietic stem cells (HSCs). In this CITE-seq study, we sought to investigate the mechanisms by which G-CSF negatively impacts long-term repopulating functions of CRISPR-Cas9 gene edited human HSCs. Accordingly, human CD34+ cells were obtained from a healthy volunteer and edited with Cas9 alone (Cas9 group), Cas9+AAVS1-targeting gRNA (RNP group), or Cas9+AAVS1-targeting gRNA+GSE56 (RNP/GSE56 group). Then, these edited cells were transplanted into busulfan-conditioned NSG mice, and these mice subsequently received 3 days of phosphate buffered saline (PBS) or G-CSF. Each mouse was subsequently euthanized and harvested for bone marrow cells and human CD34+cells were isolated using immunomagnetic beads. Isolated CD34+ cells from a total of 6 mice were individually stained with Total seq B CITE-seq antibodies (CD38, CD45RA, CD90, CD49f) + hashtag oligo antibodies 1, 2, 3, 4, 5 and 6. Fluorescence activated cell sorting (FACS) was used to purify ~2,500 cells from each group that were subsequently pooled for CITE-seq library preparation and sequencing. Seurat was used to demultiplex data into 6 individual groups and differential gene expression analysis was performed to evaluate the impact of G-CSF within Cas9, RNP and RNP/GSE56 groups.

  Study phs003277

• Discovering the Genetic Basis of Human Neuroblastoma: A Gabriella Miller Kids First Pediatric Research Program (Kids First) Project

  The Gabriella Miller Kids First Pediatric Research Program (Kids First) is a trans-NIH effort initiated in response to the 2014 Gabriella Miller Kids First Research Act and supported by the NIH Common Fund. This program focuses on gene discovery in pediatric cancers and structural birth defects and the development of the Gabriella Miller Kids First Pediatric Data Resource (Kids First Data Resource). All of the WGS and phenotypic data from this study are accessible through dbGaP and kidsfirstdrc.org, where other Kids First datasets can also be accessed. Children with disseminated neuroblastoma have a very high risk of treatment failure and death despite receiving intensified chemotherapy, radiation therapy and immunotherapy. The long-term goal of our research program is to ultimately improve neuroblastoma cure rates by first comprehensively defining the genetic basis of the disease. The central hypothesis to be tested here is that neuroblastoma arises largely due to the epistatic interaction of common and rare heritable DNA variation. Here we will perform a comprehensive whole genome sequencing of 563 quartets of neuroblastoma patient germline and diagnostic tumor DNAs and germline DNAs from both parents. The case series was recently collected through a Children's Oncology Group epidemiology clinical trial and is robustly annotated with complete demographic (age, sex, race, ethnicity), clinical (e.g. age at diagnosis, stage, risk group), epidemiologic (parental dietary and exposure questionnaire) and biological (e.g. tumor MYCN status and multiple other tumor genomic measures) co-variates. Subjects were consented for genetic research and DNA is immediately available for shipment for sequencing. We propose Illumina-based whole genome sequencing in the 593 "trio" germline samples (Aim 1; due to missing parent: 487 full neuroblastoma triads, 106 child-single parent dyads = 1673 whole genome sequences) and matched diagnostic tumor DNA (Aim 2; N=366) at 30x sequencing depth (N=2039 whole genome sequences). Also in Aim 2 we will perform whole exome (100x) and RNA sequencing on the 366 tumor DNA and 228 tumor RNA samples from this cohort. Finally, we propose a pilot study of structural variation using long-range sequencing in 10 non-overlapping tumor samples chosen based on potentially relevant chromosomal alterations discovered with conventional NGS. Thus, a total of 2277 individual samples and 2655 sequences will be generated. We will use our established analytic pipeline that is currently being used to study the germline genomes of all cases sequenced through the NCI supported Therapeutically Applicable Research to Generate Effective Treatments program. We plan a three-stage analytic approach, first focusing on classic de novo and inherited Mendelian damaging alterations. We will next integrate our extensive epigenomic data from human neuroblastoma cell lines and genome-wide association study data (N=5,703 neuroblastoma cases to date) to guide a comprehensive assessment of noncoding variants that influence tumor initiation with a recently established analytic pipeline. Finally, we will utilize the tumor DNA analyses to inform relevance via somatic gain or loss of function effects at the sequence and/or copy number levels. All data generated in this project will be immediately placed into the Genomic Data Commons (GDC) and we will compute within this environment by importing our analytic pipelines into the GDC. These data will be fully integrated into the Kids First Data Resource and freely shared with all academically qualified petitioners. This comprehensive data set derived from a large and richly phenotyped series of neuroblastoma DNA quartets will be integrated with existing germline and/or tumor genomic data from over 6,000 neuroblastoma subjects (but none with matched patient-parent germline sequencing data) to provide an unparalleled opportunity to comprehensively discover the genetic basis of neuroblastoma.

  Study phs001436

• A Dormant TIL Phenotype Defines Non-Small Cell Lung Carcinomas Sensitive to Immune Checkpoint Blockers

  The biological determinants of sensitivity and resistance to immune checkpoint inhibitors are not completely understood. To elucidate the role of intratumoral T-cells and its association with the tumor genomic landscape, we perform paired whole exome DNA sequencing and multiplexed quantitative immunofluorescence (QIF) in pre-treatment samples from non-small cell lung carcinoma patients treated with PD-1 axis blockers. QIF was used to simultaneously measure the level of CD3+ tumor infiltrating lymphocytes (TILs), in situ T-cell proliferation (Ki-67 in CD3) and effector capacity (Granzyme-B in CD3). Whole exome sequencing reported in the number/type of mutations and predicted class I and class II mutant neoantigens.

  Study phs001618

• The genetic footprint of the European Roma diaspora: Evidence from the Balkans to the Iberian Peninsula

  Our genomic approach focuses on: (i) the internal genetic structure of Roma and its correlation with geography; (ii) the relationships between Iberian Roma and other non-Roma populations to explore possible contacts during the period of population upheaval following the Roma’s arrival on the Iberian Peninsula; (iii) estimation of the admixture events in the Iberian Roma before and after their arrival to the Iberian Peninsula; and (iv) the assessment of endogamy patterns and assortative mating of the European Roma. Our study provides a detailed analysis of the intricate population history of the Iberian Roma, offering insights from both micro-geographical and large-scale perspectives on the population history of European Roma.

  Study EGAS50000000746

• BLUEPRINT Gene expression analysis during human B-cell differentiation using the Affymetrix Human Genome U219 Array

  We performed gene expression analysis using the Affymetrix Human Genome U219 Array of 9 subpopulations covering the complete B-cell maturation program: hematopoietic progenitor cells (HPC); pre-B-I cells (preB1C); pre-B-II cells (preB2C); naive B cells from peripheral blood (naiBC); naive B cells from tonsil (t-naiBC); germinal center B cells (gcBC); plasma cells from tonsil (t-PC); memory B cells from peripheral blood (memBC) and plasma cells from bone marrow (bm-PC). All the samples were isolated from healthy donors and, with the exception of bm-PC (only 1 replicate), we used 3 to 11 biological replicates of each subtype.

  Study EGAS00001001197

• Response to tumor-infiltrating lymphocyte adoptive therapy is associated with preexisting CD8+ T-myeloid cell networks in melanoma

  Adoptive cell therapy (ACT) using ex vivo–expanded tumor-infiltrating lymphocytes (TILs) can eliminate or shrink metastatic melanoma, but its long-term efficacy remains limited to a fraction of patients. Using longitudinal samples from 13 patients with metastatic melanoma treated with TIL-ACT in a phase 1 clinical study, we interrogated cellular states within the tumor microenvironment (TME) and their interactions. We performed bulk and single-cell RNA sequencing, whole-exome sequencing, and spatial proteomic analyses in pre- and post-ACT tumor tissues, finding that ACT responders exhibited higher basal tumor cell–intrinsic immunogenicity and mutational burden. Compared with nonresponders, CD8+ TILs exhibited increased cytotoxicity, exhaustion, and costimulation, whereas myeloid cells had increased type I interferon signaling in responders. Cell-cell interaction prediction analyses corroborated by spatial neighborhood analyses revealed that responders had rich baseline intratumoral and stromal tumor–reactive T cell networks with activated myeloid populations. Successful TIL-ACT therapy further reprogrammed the myeloid compartment and increased TIL-myeloid networks. Our systematic target discovery study identifies potential T-myeloid cell network–based biomarkers that could improve patient selection and guide the design of ACT clinical trials.

  Study EGAS50000001217

• Predicting the Prevalence of Complex Genetic Diseases from Individual Genotype Profiles Using Capsule Networks

  Diseases with a complex genetic architecture, such as amyotrophic lateral sclerosis (ALS) as a most prominent example, are hard to disentangle. "Human mind-friendly" methods, such as linear approaches used in genome wide association studies (GWAS), remain blind to many genetic variants that matter. On the other hand, methods that are sufficiently sophisticated to entirely capture the characteristic interplay of genetic variants remain black boxes for the human mind. Here, we give this a decided, and as we argue, a very promising try. We present DiseaseCapsule, a capsule network-based approach that enables us to predict prevalence/occurrence of a genetically complex disease from individual genotype profiles. Importantly, capsule networks are considerably easier to decompose into their components than ordinary deep neural networks, which promotes the interpretability of their results. The data we used are from Project MinE, a large-scale study that aims to reveal the genetic and epigenetic mechanisms that underlie ALS in the framework of a globally concerted collaboration. Specifically, we used data from the Dutch cohort of the project, which contains 7213 healthy ('control') individuals and 3192 individuals affected with ALS. The cohort includes 5208 females and 5197 males. All participants of the study were genotyped using an Illumina 2.5M SNP array.

  Study phs003146

• The Genomic Landscape of Childhood and Adolescent Melanoma

  Despite remarkable advances in the genomic characterization of adult melanoma, the molecular pathogenesis of pediatric melanoma remains largely unknown. We analyzed 15 conventional melanomas (CM), 3 melanomas arising in congenital nevi (CNM), and 5 spitzoid melanomas (SM), using various platforms, including whole genome or exome sequencing, molecular inversion probe assay, and/or targeted sequencing. CM demonstrated a high burden of somatic single nucleotide variations (SNV), with each case containing a TERT promoter (TERT-p) mutation, 13/15 containing an activating BRAF V600 mutation, and >80% of the identified SNV consistent with UV damage. By contrast, the 3 CNM contained an activating NRAS Q61 mutation and no TERT-p mutations. SM were characterized by chromosomal rearrangements resulting in activated kinase signaling in 40%, and an absence of TERT-p mutations except for the one SM that succumbed to hematogenous metastasis. We conclude that pediatric CM has a very similar UV-induced mutational spectrum to that found in the adult counterpart, emphasizing the need to promote sun protection practices in early life and to improve access to therapeutic agents being explored in adults in young patients. By contrast, the pathogenesis of CNM appears to be distinct. TERT-p mutations may identify the rare subset of spitzoid melanocytic lesions prone to disseminate.

  Study EGAS00001000901

• T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS)

  The Type 2 Diabetes (T2D) Genetic Exploration by Next-generation sequencing in Ethnic Samples (T2D-GENES) Consortium is a collaborative international effort to identify genes influencing susceptibility to type 2 diabetes in multiple ethnic groups using next generation sequencing. To fulfill this objective, T2D-GENES Consortium undertook two large sequencing studies, called T2D-GENES Projects 1 and 2. Project 1 has carried out whole exome sequencing of 12,940 individuals, 6,504 with T2D and 6,436 non-diabetic controls, equally divided among five continental ancestry groups: Europeans, East Asians, South Asians, Hispanic Americans, and African Americans. The goal of Project 1 is to identify all genetic variants in the complete coding regions of the genomes (i.e., whole exome) by sequencing, including rare variants. Project 2 (i.e., SAMAFS substudy 2) is a pedigree-based study designed to identify low frequency or rare variants influencing susceptibility to T2D, using whole genome sequence information from approximately 600 individuals in 20 Mexican American T2D-enriched pedigrees from San Antonio, Texas, augmented with family-based imputation into approximately 440 additional family members. The major objectives of Project 2 are to identify low frequency or rare variants in and around known common variant signals for T2D, as well as to find novel low frequency or rare variants influencing susceptibility to T2D. Both T2D-GENES Projects 1 and 2 involve the San Antonio Mexican American Family Studies (SAMAFS), which are composed of four San Antonio, Texas-based family studies: the San Antonio Family Heart Study (SAFHS), San Antonio Family Diabetes/Gallbladder Study (SAFDGS), Veterans Administration Genetic Epidemiology Study (VAGES), and Family Investigation of Nephropathy and Diabetes - San Antonio (FIND-SA) Component and its extension called the Extended FIND [E-FIND]. The SAFHS and SAFDGS began in 1991 and have followed participants with extensive clinical phenotyping related to T2D for over 20 years. The VAGES was initiated in 1994 and a large battery of T2D-related phenotypic data has been obtained from its participants. The FIND-SA began in 2000, a part of the multicenter FIND study which was designed to identify genetic determinants of diabetic kidney disease; data from its participants related to T2D were used for this project. Non-overlapping subsets of SAMAFS participants are part of the T2D-GENES Projects 1 and 2, henceforth referred to as SAMAFS substudies 1 and 2, respectively. The SAMAFS substudies 1 and 2 are part of one of the five awards funded by NIDDK under a cooperative agreement award mechanism, which is governed by the Steering Committee of the T2D-GENES Consortium. Since Project 1 relies on population based subsets of cases and controls, 491 unrelated participants are drawn from the four SAMAFS as part of the T2D-GENES Project 1 Mexican American sample (i.e., SAMAFS substudy 1). The whole exome sequencing was performed at the Broad Institute. For Project 2, 1048 individuals are drawn from two SAMAFS (SAFHS and SAFDGS), representing 20 large families for substudy 2. The substudy 2 strategy is to sequence approximately 600 individuals at an average of 50x coverage across the entire genome, then impute genome wide genotypes for about 440 additional family members. The 600 sequenced individuals are specifically chosen for their value in imputing sequence information into other family members. By studying large pedigrees, we expect to find multiple individuals carrying each genetic variant, even if this variant is very rare in the population at large. Thus, a pedigree-based approach provides an excellent opportunity for identifying rare novel variants influencing risk of T2D and quantitative variation in T2D-related phenotypes. The whole genome sequencing has been done commercially by Complete Genomics, Inc. (CGI). The available sample of 1,048 includes 5 sequenced individuals who do not belong to any of the 20 large pedigrees. The final family data of 1,043 individuals includes whole genome sequence data for 607 individuals. After quality control, 590 sequenced individuals provide data for family based imputation using Merlin linkage analysis software into approximately 440 additional family members for whom chip based genotypes are available to indicate which parental haplotype is transmitted. The complete SAMAFS data including phenotype, genotype, sequence, other T2D-related trait data utilized for Projects 1 and 2 are available. These data can readily be viewed by clicking on the substudy title shown below or in the box: "Substudies", located on the right hand side of this parent or top study page phs000847.v1.p1, titled T2D-GENES Consortium: San Antonio Mexican American Family Studies (SAMAFS). phs000849 T2D-GENES Project 1: San Antonio Mexican American Family Studies (SAMAFS), Substudy 1: Whole Exome Sequencing phs000462 T2D-GENES Project 2: San Antonio Mexican American Family Studies (SAMAFS), Substudy 2: Whole Genome Sequencing in Pedigrees

  Study phs000847

• Bulk-tissue RNA-sequencing of anterior cingulate cortex samples derived from Lewy body disease patients

  Parkinson’s disease (PD), Parkinson’s disease with dementia (PDD) and dementia with Lewy bodies (DLB) are three clinically, genetically and neuropathologically overlapping neurodegenerative diseases collectively known as the Lewy body diseases (LBDs). A variety of molecular mechanisms have been implicated in PD pathogenesis, but the mechanisms underlying PDD and DLB remain largely unknown, a knowledge gap that presents an impediment to the discovery of disease-modifying therapies. Transcriptomic profiling can contribute to addressing this gap, but remains limited in the LBDs. Here, we applied paired bulk-tissue and single-nucleus RNA-sequencing to anterior cingulate cortex samples derived from 28 individuals, including healthy controls, PD, PDD and DLB cases (n = 7 per group), to transcriptomically profile the LBDs. Using this approach, we (i) found transcriptional alterations in multiple cell types across the LBDs; (ii) discovered evidence for widespread dysregulation of RNA splicing, particularly in PDD and DLB; (iii) identified potential splicing factors, with links to other dementia-related neurodegenerative diseases, coordinating this dysregulation; and (iv) identified transcriptomic commonalities and distinctions between the LBDs that inform understanding of the relationships between these three clinical disorders. Together, these findings have important implications for the design of RNA-targeted therapies for these diseases and highlight a potential molecular “window” of therapeutic opportunity between the initial onset of PD and subsequent development of Lewy body dementia.

  Study EGAS00001005305

• Single-nucleus RNA-sequencing data of kidney biopsies from patients with primary FSGS, maladaptive FSGS, proteinuric controls and healthy controls

  This dataset includes FASTQ files of single-nucleus RNA sequencing of cryopreserved kidney biopsy cores from adult patients with diagnosed primary FSGS (n = 9, all nephrotic), maladaptive FSGS (n = 9, not nephrotic), proteinuric controls (PLA2R-positive membranous nephropathy, n = 3), and healthy controls (n = 4). A total of 120,751 high-quality nuclei were identified, including 2,471 podocytes and 1,574 parietal epithelial cells (PECs). In addition to the raw FASTQ files, the dataset includes processed data files from all 25 samples, generated using Seurat in R: barcode files, features, count matrices, and associated metadata. Details regarding the bioinformatics pipeline can be found at https://github.com/lambrechtslab/FSGS_Deleersnijder_et_al

  Dataset EGAD50000001557

• GCAT | Genomes for life: cohort study of the genomes of Catalonia

  The GCAT Study have recruited 20 000 participants aged 40–65 years. Participants who agreed to take part in the study completed a self-administered computer-driven questionnaire, and underwent blood pressure, cardiac frequency and anthropometry measurements. For each participant, blood plasma, blood serum and white blood cells are collected at baseline. A total of 5459 genomic profiles have been characterised by comprehensive genotyping. Genome-wide genotypes have been generated using Illumina Infinium SNP-bead array technology. We chose the Multi-Ethnic Global (MEGAEX, V.2) consortium array, a multipurpose, multiethnic genotyping array with two million selected markers (including previously described germline mutations, insertions-deletions (InDels) and SNPs).We have strictly followed the standard manufacturer recommended automated protocol for the Infinium HTS Assay scanned with a HiScan confocal scanner (Illumina, San Diego, California, USA). Genome Studio V.2011.1 has been used for raw data analysis. Genotyping was performed at the Genomics and Bioinformatics Unit of the PMPPC Institute for Health Science Research Germans Trias i Pujol, in Badalona, Spain. Future plans The first follow-up study started in December 2017 and will end by March 2018. Residences of all subjects will be geocoded during the following year. Several genomic analyses are ongoing, and metabolomic and genomic integrations will be performed to identify underlying genetic variants, as well as environmental factors that influence metabolites. http://dx.doi.org/10.1136/bmjopen-2017-018324

  Study EGAS00001003018

• Genetic Analysis of the Chiari I Malformation

  This study used whole exome sequencing (WES) on families affected with Chiari I Malformation (CM1). Individuals were recruited from the Republic of Tartarstan in the Russian Federation, where CM1 has a high prevalence (approximately 413 out of 100,000). At least one-third of these affected individuals have an affected relative. In collaboration with Dr. Enver Bogdanov of Kazan State Medical University, seven extended families affected with CM1 were identified. Eligible participants for this study were required to 1) have CM1 and a family member with syringomyelia or CM1, or 2) be a family member of a patient with CM1 and have at least two immediate family members diagnosed with CM1. Adults and minors were eligible for this study and recruitment was through self and physician referral. Patients were excluded if they had a contraindication to MRI scanning, were unable to understand the risks of testing, were under one year of age, or could not undergo MRI scanning without sedation. Study participants underwent SPGR (Spoiled Gradient Recalled) and T1-weighted MR-imaging of the brain and cervical spinal cord to assess the volume of the posterior fossa, as well as the presence of CM1. Individuals were defined as having CM1 if the inferior aspect of the cerebellar tonsils were lying ≥=2 mm caudal to the foramen magnum. Individuals were defined as having a small posterior fossa volume if the ratio of the posterior fossa volume to the supratentorial volume was < 0.15. Sixty-two patients (both cases and controls) from the seven extended families had DNA extracted from blood lymphocytes contained in 10 milliliters of stored blood. Whole exome sequencing (WES) was performed by the National Intramural Sequencing Center (NISC). These genotype data, as well as the case-control phenotype data on CM1 diagnosis and small posterior fossa diagnosis, were made available to dbGaP.

  Study phs001795

• RNA sequencing of periprostatic fat after a 6 month deep androgen deprivation therapy

  Androgen deprivation therapy treated patients (n=11) were recruited from an open label neoadjuvant phase II study in which patients with high-risk disease received a ‘supercastration’ regimen consisting of degarelix 240/80 mg subcutaneously every four weeks; abiraterone acetate 500 mg orally daily titrating upwards every two weeks by 250 mg to a final dose of 1000 mg daily; bicalutamide 50 mg orally daily; and prednisolone 5 mg orally twice daily for a total of 6 months (Australian New Zealand Clinical Trials Registry 12612000772842). Untreated patients with similar pre-treatment characteristics were obtained from a prospective prostatectomy biorepository22,23. Prior to ligation of the dorsal venous complex and prostate pedicles, the anterior prostate was defatted and the specimen was removed immediately, placed in a sterile container and transferred on ice for long-term storage in the vapour phase of liquid nitrogen. A total of 50–100 µg of adipose tissue was separated from fresh frozen samples stored at −160°C. RNA was isolated using the Qiagen RNeasy Lipid Tissue Mini Kit and eluted in 35 µL nuclease-free water. 0.5–1 µg of total RNA was used as the input for cDNA library synthesis using TruSeq RNA Sample Prep Kit v2 (Illumina), and libraries were constructed according to manufacturer’s instructions. Samples were sequenced on a HiSeq 2500 (Illumina) using 101 base paired-end chemistry, aiming for 50 million mapped paired-end reads per sample.

  Dataset EGAD00001004971

• Machine learning to detect the SINEs of cancer

  We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA (cfDNA) through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a novel machine-learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to samples from 5108 individuals, 2037 with cancer and the remainder without cancer. Samples from cancer patients and controls were pre-specified into four cohorts used for: 1) model training, 2) analyte integration and threshold determination, 3) validation, and 4) reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the Validation Cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and 8 common protein biomarkers detected 51% of 1167 cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature – the global reduction of AluS sub-family elements in the circulating DNA of cancer patients. We confirmed this reduction through the analysis of another independent dataset obtained with a very different approach (whole genome sequencing). The evaluation of Alu elements therefore has the potential to enhance the performance of several methods designed for the earlier detection of cancer.

  Study EGAS00001007169

• Therapy-related myeloid neoplasms and HSPCs from the International-Berlin-Frankfurt-Münster (I-BFM) Study group

  Dataset contains WGS sequencing data from bulk sorted therapy-related myeloid neoplasms (t-MN) and reference cells (MSCs/B cells/T cells). In addition, from 4 patients, also WGS data from single hematopoietic stem and progenitor cells, obtained from samples of t-MN diagnosis, are included. These are either clonally expanded before WGS, or DNA was directly amplified via the primary template-directed amplification (PTA) protocol (mentioned in the sample name).

  Dataset EGAD00001011256

• Colorectal cancer samples WES

  The whole exome was sequenced in two cancer-affected members (II:1 and III:1) of the family. The family subject of this study showed an autosomal dominant mode of CRC inheritance, fulfilling the Amsterdam I clinical criteria with three CRCs in two consecutive generations. The exome capture was performed using SureSelectXT Human All Exon V3 (51Mb, Agilent Technologies), and the library was sequenced on an Illumina HiSeq 2000 platform with paired-end reads of 101bp and a 50x average coverage depth.

  Dataset EGAD00001009170

• Methylation profiling of human lung fibroblasts in COPD

  Primary lung fibroblast were isolated from well-matched control donors (no COPD, n=3) and patients with COPD (GOLD stage I-IV, n=8). Genomic DNA of cultured human lung fibroblast was isolated at passage 3, fragmented by tagmentation, and subjected to bisulfite treatment. 100 bp paired-end reads were generated from DNA libraries on Illumina HiSeq2500 platform.

  Dataset EGAD00001009406

• Exome sequencing of uterine leiomyosarcomas

  Uterine leiomyosarcomas (ULMSs) are aggressive smooth muscle tumors associated with poor clinical outcome. Despite previous cytogenetic and molecular studies, their molecular background has remained elusive. To examine somatic variation in ULMS, we performed exome sequencing on 19 tumors. Altogether 43 genes were mutated in at least two ULMSs. Most frequently mutated genes included tumor protein P53 (TP53; 6/19; 33%), alpha thalassemia/mental retardation syndrome X-linked (ATRX; 5/19; 26%), and mediator complex subunit 12 (MED12; 4/19; 21%). Unlike ATRX mutations, both TP53 and MED12 alterations have repeatedly been associated with ULMSs. All the observed ATRX alterations were either nonsense or frameshift mutations. ATRX protein levels were reliably analyzed by immunohistochemistry in altogether 44 ULMSs, and the majority of tumors (23/44; 52%) showed clearly reduced expression. Loss of ATRX expression has been associated with alternative lengthening of telomeres (ALT), and thus the telomere length was analyzed with telomere-specific fluorescence in situ hybridization. The ALT phenotype was confirmed in all ULMSs showing diminished ATRX expression. Exome data also revealed one nonsense mutation in death-domain associated protein (DAXX), another gene previously associated with ALT, and the tumor showed ALT positivity. Aberrant expression of both TP53 and ATRX were associated with poor overall survival. In conclusion, exome sequencing revealed that TP53, ATRX, and MED12 are frequently mutated in ULMSs. ALT phenotype was commonly seen in tumors, indicating that ATR inhibitors, which were recently suggested as possible new drugs for ATRX-deficient tumors, could provide a potential novel therapeutic option for ULMS.

  Study EGAS00001001612

• National Institute of Arthritis and Musculoskeletal and Skin Diseases and Istanbul Faculty of Medicine Genome-wide Association Study of Behçet's Disease (Turkish)

  IntroductionBehçet's disease (BD) is a genetically complex multisystem disease of unknown etiology, characterized by recurrent inflammatory attacks affecting orogenital mucosa, eyes, skin, joints, blood vessels, and less frequently, the central nervous system and gastrointestinal tract. Family studies suggest a genetically complex contribution to BD. With the exception of HLA-B51, which explains less than 20% of the genetic risk, the identities of alleles that are responsible for the complex inheritance of this disease have remained unclear. AimTo identify genes that contribute to BD susceptibility. MethodsA genome-wide association study was undertaken with 311,459 informative and high quality SNPs in a collection of 1215 BD patients and 1278 healthy controls from Turkey using a beadchip microarray assay (Infinium SNP genotype assay, Illumina). HLA-B types were determined with a reverse sequence-specific oligonucleotide method (One Lambda). Regions with evidence for association were fine-mapped using Sequenom iPLEX gold assays. Disease-associated SNPs were genotyped in additional ethnically matched case/control collections from diverse genetic backgrounds, including a total of 2430 cases and 2660 controls, using TaqMan SNP genotype assays. Association data were combined in a meta-analysis of all the collections. ResultsWe confirmed the known association with HLA-B51 and found evidence for a second, independent susceptibility locus in the Class I region of the MHC. In addition, we identified one SNP with genome-wide evidence for disease association (P < 5.0 x 10-8) within the gene encoding the immunoregulatory cytokine, interleukin-10 (IL10). A meta-analysis of the data from all the collections established associations with the IL10 variant (rs1518111, P = 3.54 x 10-18, odds ratio 1.45 with 95% confidence interval 1.34 to 1.58) and with a variant located between the interleukin-23 receptor (IL23R) and interleukin 12 receptor β2 (IL12RB2) genes (rs924080, P = 6.69 x 10-9, odds ratio 1.28 with 95% confidence interval 1.18 to 1.39). The disease-associated IL10 variant was associated with diminished mRNA expression and low protein production by cells obtained from healthy blood donors. ConclusionsThese data suggest that genetically encoded low production of IL-10 increases risk of BD and suggest novel interventional targets in the IL-10 and IL-23 pathways. Note: The submitted data are the genotypes of the 311,459 SNPs in 1215 cases and 1278 controls.

  Study phs000272

• RNAseq of circulating monocytes of familial hypercholesterolaemia (FH) patients before and after treatment, and healthy controls.

  RNAseq of circulating monocytes of familial hypercholesterolaemia (FH) patients before and after treatment, and healthy controls. Please cite original paper: Monocyte and macrophage lipid accumulation results in downregulated type-I interferon responses. Willemsen et al. Frontiers in Cardiovascular Medicine (2022) Familial hypercholesterolemic patients (n=10) and healthy subjects (n=9): the study population, design, and further processing of these human study subjects and their samples have been extensively described (Stiekema et al., 2021). Briefly, untreated FH patients who indicated to start lipid-lowering therapy (statin, PCSK9 antibody, and/or ezetimibe) according to their treating physician were included. The healthy controls were age, sex, and body mass index (BMI) matched with the FH patients. After inclusion, FH patients fasted for at least 9 hours before blood samples were drawn for lipid measurements and monocyte isolation. This was repeated after 12 weeks of lipid-lowering therapy. RNA-seq was performed on circulating monocytes. V1 = visit 1. V2 = visit 2.

  Dataset EGAD00001008967

• CRU-Ukrainian National Research Center for Radiation Medicine Trio Study

  Data on transgenerational effects following nuclear accidents are important for understanding fully the consequences of parental exposure to ionizing radiation. Few studies to date have had adequate statistical power to detect effects of the magnitude expected based on animal data, and most have not been of low-dose, protracted exposures associated with nuclear accidents and their aftermath. Although, to date, scant use has been made of the new genomic technologies, in Chernobyl-exposed areas of Ukraine and Belarus, excess minisatellite mutations have been seen in children born after the accident. We propose a study of parent-child trios in which at least one parent was exposed to Chernobyl radiation as a clean-up worker (mean dose>=100 mGy) and/or evacuee from a contaminated area (mean >=50 mGy). The specific aims are to investigate the transgenerational and de novo mutation rates of the spectrum of genetic variants in trios, in particular looking at effects in children and mapping them to possible parental origin of the chromsoome. Together with long-term collaborators at the Research Center for Radiation Medicine (RCRM) in Kiev, epidemiologic data will be collected for up to 450 trios of parents with preconceptional doses and their unexposed offspring. We will use state-of-the-art genomic technologies to characterize the landscape of the genomes of the trios to determine whether parental radiation exposure is associated with genetic mutations transmitted to the offspring, by examining de novo mutation rates, minisatellite mutations, copy number alterations, and variations in telomere length. The analysis will be conducted in peripheral blood and/or buccal samples (when blood is not available) from complete father-mother-child trios. Doses to the gonads from the time of the accident to the time of conception will be reconstructed for all parents using existing records supplemented by interview data. Trio subjects will be selected from representative populations exposed to radiation from Chernobyl who are under active follow-up in the Clinico-Epidemiologic Registry at RCRM. To help identify specific effects of paternal and maternal radiation exposure, we will initially select sets of trio subjects in five categories: (1) exposed father, unexposed mother; (2) unexposed father, exposed mother; (3) both parents exposed; (4) both parents unexposed; and (5) a group of high dose "emergency workers" with acute radiation syndrome. All trio members will be invited to the RCRM outpatient clinic for collection of a 20 ml blood sample (or buccal cells for those who refuse phlebotomy). Both parents will be asked to complete a general questionnaire to obtain demographic and lifestyle data. Then one or both will complete detailed dosimetry questionnaires, based on forms used in previous collaborations with RCRM and administered by specially trained interviewers. Once 50 trios have been recruited (10 from each of the 5 exposure categories), we will conduct an interim evaluation of participation rates, sample collection and quality, and dose reconstruction in order to modify the protocol as needed. The analytical approach will be to correlate the extent, especially for de novo events of genetic alterations in the offspring with parental pre-conceptional radiation dose overall and by parental origin. The statistical power in relation to de novo mutations is very high, in excess of 90%, but somewhat lower for trends in minisatellite mutations. Study findings will contribute importantly to knowledge of the heritable effects of moderate- and low-dose radiation exposure in humans and to radiation risk projection. Eventually data from the Trio Study may be shared with the international community through dbGap.

  Study phs001163

• Submitter Portal API

  Submitter Portal API The metadata submission process can be difficult and time-consuming. For this reason, the EGA has developed the Submitter Portal, a tool that was created to offer a simplified and user-friendly method of registering metadata. Our portal provides features that are intended to make the input of metadata easier, ensuring that your data is registered correctly and effectively. Our page is divided into logical sections and includes a helpful video instruction to further assist you as you complete the submission process. With the Submitter Portal, you can rest assured that the submission of your data is in good hands. For those that want a more flexible and automated approach, we also provide a programmatic approach using the Submitter Portal AP in addition to the user interface of the Submitter Portal. With the help of our API, you can quickly include the submission of metadata into your own workflow for a more effective and individualised experience. Previous steps Create your EGA account To submit data you first need to create your EGA user. Then, once your account has been verified, you will have to request a submitter role and sign the EGA Data Processing Agreement (DPA). When the DPA is signed, you must send it to EGA Helpdesk for further validation. Please, note that if you already have an EGA account, or you have an ega-box (submission account), you can skip this step.  Upload your files Please note that all your files must be encrypted using the Crypt4GH tool before upload them.As soon as you are assigned with a submitter role, you will be able to connect to the EGA inbox and upload your files. Understand the EGA metadata schema It's crucial to comprehend the EGA metadata schema, a set of rules that specify how data is organised, described, and shared inside the EGA, in order to get the most out of this resource. Learn all about EGA metadata schema! Register your DAC and policy There are two objects in the EGA metadata schema that are registered in a separate portal. All DACs and policy objects are registered using the DAC Portal, a tool developed by EGA to help data controllers manage their data stored at the EGA. You can find the relevant information in the DAC Portal Guide. Programmatic submission All the calls to the API need to be Authenticated. We use the OpenID Connect protocol. API Usage Flow: Click here to check the API usage flow schema Obtain Access and Refresh Token: The first step to using the API is to obtain an access and refresh token. These tokens are required for authentication and authorisation of API requests. To obtain these tokens, you need to log in using your EGA credentials. Example: curl "https://idp.ega-archive.org/realms/EGA/protocol/openid-connect/token" \ -d "grant_type=password" \ -d "client_id=sp-api" \ -d "username=your-username" \ --data-urlencode "password=your-password" Use Access Token in API Calls: Once you have obtained the access token, you must use it in all the calls to the API. The access token is valid for a limited time period. When it expires, you will need to use the refresh token to obtain a new access token. Create Submission Object: After authentication, you can start creating a submission object. This object will be used to store all the metadata objects and files related to the submission. Example: curl "https://submission.ega-archive.org/api/submissions" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" \ -d "{ \"title\":\"My submission title\", \"description\":\"My submission description\" }" Create EGA Metadata Objects: Within the submission object, you can create other metadata objects required for the submission. These objects may include information about the submitter, study, sample, experiment, and run. Example of study creation: curl "https://submission.ega-archive.org/api/submissions/{submisison-id}/studies" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" \ -d "{ \"title\":\"My study title\", \"description\":\"My study description\", \"study_type\":\"Metagenomics\" }" If you would like to reuse already registered objects in new submissions, bear in mind that they must have an accession which you must use to reference them. You cannot reuse objects that have not been finalised and accepted yet.For example, when creating a new run which is reusing a previously submitted experiment, instead of using experiment_provisional_id, you must use experiment_accession_id. Enums There are some fields that only accept specific values, i.e. study_type. The API provides several enumerations to list these values. You can list all the enumerations, or a specific one, for example, study_types. Obtain IDs of files You can list the files available in your inbox and filter by a prefix by adding the prefix param, i.e. &prefix=/my_folder/abc Example: curl "https://submission.ega-archive.org/api/files?status=inbox&prefix=/my_folder/abc" \ -H "Authorization: Bearer your-access-token" \ -H "Content-Type: application/json" To improve performance and manageability, we have limited the number of files that the Submitter Portal API can return in a response. If a given call exceeds this limit, user will be asked to narrow down the search by using the query parameters already available in this endpoint. Finalise Submission: Once all the metadata objects are created and linked to the submission, you can finalise the submission. Finalising the submission sends it to the Helpdesk team for review. Please, note that all files linked to the submission must be ingested, and all objects created in a submission must be linked before you can finalise the submission. API Reference: For a full API reference, please check our specification documentation.

  Documentation submission/metadata/submission/sequencing-phenotype/submitter-portal-api

• Ongoing Replication Stress Tolerance and Clonal T Cell Responses Distinguish Liver and Lung Recurrence and Patient Outcomes in Pancreatic Ductal Adenocarcinoma

  Patients with metastatic pancreatic ductal adenocarcinoma (PDAC) survive longer when disease spreads to the lung but not to the liver. We generated overlapping, multi-omic datasets to identify molecular and cellular features that distinguish patients whose disease develops liver metastasis (liver cohort) from those whose disease progression results in lung metastasis without liver metastases (lung cohort). Lung cohort patients generally survived longer than liver cohort patients, independent of tumor subtype. We developed a pORG gene signature that distinguishes primary tumors in the liver and lung cohorts. We identified ongoing replication stress (RS) response pathways in high pORG/liver cohort tumors, while low pORG/lung cohort tumors had greater densities of lymphocytes and shared T cell clonal responses. Our study demonstrates that liver-avid PDAC is associated with tolerance to ongoing RS, limited tumor immunity, and less favorable outcomes; whereas low RS, lung-avid/liver-averse tumors are associated with active tumor immunity that may account for favorable outcomes. As expected, we found high frequencies of KRAS, TP53, CDKN2A, and SMAD4 gene alterations in our tumor samples. High pORG activity (GSVA scores) in our primary tumors appear to be positively correlated with alteration frequencies in both TP53 and CDKN2A. We did not see a correlation with alterations in KRAS as almost all the tumor samples have KRAS alterations. From a de-identified dataset of 1,873 patients diagnosed with and/or treated for PDAC at our institution between 2004 and 2020, we identified 422 patients for which we had specimens with sequencing data (N=374) and/or specific evidence of disease metastasis site(s) from the OHSU cancer registry or disease-relevant computed tomography (CT) scans to allow cohort classification. Note that our study includes RNA-Seq, DNA-Seq panel, and TCR-Seq (T-cell Receptor Sequencing) data, but that this dbGaP submission just includes the patients/samples with RNA-Seq and/or DNA-Seq panel data. Therefore, this submission includes 290 samples from 278 patients. TCR sequence data is available on the Adaptive Biotechnologies platform. Clinical course timepoints, patient demographics, stage, grade, nodal involvement, resection margins, and angiolymphatic invasion were provided as deidentified data by the OHSU cancer registry with quality control data verification in a subset by pathologists (BB and TM). We reviewed all available computed tomography (CT) scans for all patients with primary tumor resection dates recorded by the cancer registrar, with tumor samples analyzed by RNA-seq, DNA-seq, or TCR-seq, and/or with additional information indicating metastatic spread (e.g., metastatic samples received for related studies). We abstracted the site of all lesions proven to be metastatic by biopsy and/or that clearly increased in size during progression or decreased in size during treatment as long as a radiologist described the lesion as “likely”, “suspicious for”, “concerning for”, or “favor” metastasis. Clinical imaging was reviewed by a radiologist (AG) to validate patient assignments to the liver, lung, and neither liver nor lung (other recurrence site) cohorts. Time to recurrence was calculated from the earliest of either the recurrence date provided by the OHSU cancer registry, or the date of earliest lesion abstracted from CT reports. The subject attributes reported in this submission were up to date at the time of our data freeze, which occurred July 2021.

  Study phs003597

• Characterization_of_individual_foci_of_multicentric_multifocal_breast_cancer_using_targeted_next_generation_sequencing

  Multifocality or multicentricity in breast cancer may be defined as the presence of two or more tumor foci within a single quadrant of the breast or within different quadrants of the same breast, respectively. This original classification of the breast cancer as multicentric or multifocal was based on the assumption that cancers arising in the same quadrant were more likely to arise from the same ductal structures than those occurring in separate areas of the breast. The problem with these definitions is that the “quadrants” of the breast are arbitrary external designations, as no internal boundaries do exist. This project will therefore focus both on synchronous multifocal and multicentric tumors. The incidence of multifocal and multicentric breast cancers was reported to be between 13 and 75% depending on the definition used, the extent of the pathologic sampling of the breast and whether in situ disease is considered evidence of multicentricity (1). Although this incidence is variable, those figures show that it is a frequent phenomenon. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic management of the cancer. Multifocality or multicentricity has been associated with a number of more aggressive features including an increased rate of regional lymph node metastases and adverse patient outcome when compared with unifocal tumors (2-3), and a possible increased risk of local recurrence following breast conserving surgery (4). For the moment, the literature is divided on whether there is a corresponding impact on survival outcomes. Today, the current convention to stage and to treat multifocal and multicentric tumors is the classical tumor-node-metastasis (TNM) staging guidelines with which tumor size is assessed by the largest tumor focus without taking other foci of disease into consideration. If some papers, as the recent one from Lynch and colleagues, support the current staging convention (3), others, however, as Boyages et al. suggested that aggregate size and not the size of the largest lesion should be considered in order to refine the prognostic assessment of those tumors (5). On the top of that, the question whether multifocal/multicentric carcinomas are due to the spread of a single carcinoma throughout the breast or is due to multiple carcinomas arising simultaneously has been a matter of debate. Some studies suggested that multifocal breast cancer may result from either intramammary spread from a single primary tumor or multiple synchronous primary tumors; whereas others suggest that multiple breast carcinomas always arise from the same clone (6-8). Recently, Pietri and colleagues analyzed the biological characterization of a series of 113 multifocal/multicentric breast cancers (8) which were diagnosed over a 5-year period. The expression of estrogen (ER) and progesterone (PgR) receptors, Ki-67 proliferative index, expression of HER2 and tumor grading were prospectively determined in each tumor focus, and mismatches among foci were recorded. Mismatches in ER status were present in 5 (4.4%) cases and PgR in 18 (15.9%) cases. Mismatches in tumor grading were present in 21 cases (18.6%), proliferative index (Ki-67) in 17 (15%) cases and HER2 status in 11 (9.7%) cases. Interestingly, this heterogeneity among foci has led to 14 (12.4%) patients receiving different adjuvant treatments compared with what would have been indicated if we had only taken into account the biologic status of the primary tumor. This study therefore showed that differences in biological characteristics of multifocal/multicentric lesions play a crucial role in the adjuvant treatment decision making process. In this study, we will concentrate on a larger series of patients with multifocal invasive ductal breast cancer lesions. We aim at: 1. Evaluating the incidence of multifocality according to the different breast cancer molecular subtypes (ER-/HER2-, HER2+, ER+/HER2-). 2. Evaluating the incidence of multifocality in patients with hereditary breast cancer disease (presence of germline BRCA1 or BRCA2 mutations). Moreover, we would like to investigate if multifocal lesions with BRCA1 or BRCA2 mutations exhibit a characteristic combination of substitution mutation signatures and a distinctive profile of deletions as demonstrated recently by Nik-Zainal and colleagues (9). 3. Correlating multifocality with clinical information in order to define its influence on patients’ survival (DFS and OS). 4. Carrying high coverage targeted gene sequencing of driver cancer genes and genes whose mutation is of therapeutic importance in order to compare clinically-relevant genetic differences between several multifocal breast cancer lesions. 5. Evaluating the impact of the distance between the different lesions on the clinical outcome but also on the genetic differences. 6. Comparing gene expression patterns between several multifocal breast cancer lesions and correlate them with the results of the targeted genes screen. 7. Characterizing the genomic and transcriptomic status of cancer related genes in metastatic lesions (local recurrence, positive lymph node or distant metastatic sites) from the same multifocal invasive ductal breast cancer patients in order to evaluate the consequence of genomic and transcriptomic heterogeneity of multifocal lesions on metastatic lesions. Multiple (multifocal/multicentric) breast carcinomas, especially when occurring in the same breast, represent a real challenge for both pathologists and clinicians in terms of identifying the cellular origin and the best therapeutic choice. This project has the potential to identify genetic/transcriptomic differences existing between several lesions constituting multifocal breast cancers, which in the routine clinical practice are usually considered to be homogeneous among them. We foresee validating significant results in a larger series of patients and this, in turn, could have a remarkable impact on the treatment and clinical management of multifocal breast cancers. Indeed, we hope to provide some evidence whether or not each focus matters in multifocal and multicentric breast cancer to define the adequate therapeutic approach, especially in the context of targeted therapies. The work to be done at Sanger will be target gene screen pooling of 1400 samples.

  Study EGAS00001000407

• Clonal selection after gene therapy in sickle cell disease

  While gene therapy (GT) provides a potentially curative treatment option for patients with sickle cell disease (SCD), the occurrence of myeloid malignancies in clinical trials has prompted concern. To interrogate potential mechanisms underlying increased cancer risk, we used hematopoietic stem cell (HSC) clonal tracking by whole genome sequencing (WGS) to map the somatic mutation and clonal landscape of 2,592 gene modified as well as unmodified single stem and progenitor cells from six SCD patients undergoing gene therapy (7-26 years old, average 12.7× depth). Pre-GT phylogenetic trees in SCD were highly polyclonal and mutation burdens per cell were elevated in some, but not all, patients. Post-GT, no clonal expansions were identified. However, an increased frequency of driver mutations associated with myeloid neoplasms or clonal hematopoiesis (DNMT3A- and EZH2-mutated clones in particular) were seen in both genetically modified and unmodified cells suggested positive selection of mutant clones during gene therapy. This work sheds light on the mutation landscape and HSC clonal dynamics in gene therapy for SCD and highlights enhanced fitness of some HSCs harboring pre-existing driver mutations following gene therapy. Future studies should define the long-term fate of mutant clones including any contribution to expansions associated with myeloid neoplasms.

  Dataset EGAD00001010914