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• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_agilent)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005587

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_oncoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005586

• GUARDIAN: The Insulin Resistance Atherosclerosis Family Study (IRASFS)

  TThe IRAS Family Study was a family study designed to examine the genetic and epidemiologic basis of glucose homeostasis traits and abdominal adiposity. Briefly, self-reported Mexican pedigrees were recruited in San Antonio, TX and San Luis Valley, CO. Probands with large families were recruited from the initial non-family-based IRAS Study, which was modestly enriched for impaired glucose tolerance and T2D. GUARDIAN includes 1,024 individuals in 88 pedigrees from the IRAS Family Study. Insulin sensitivity was obtained by FSIGT.

  Study phs001008

• The Chromatin Landscape of Pathogenic Transcriptional Cell States in Rheumatoid Arthritis

  In this study, we characterized 24 rheumatoid arthritis (RA) synovial tissue chromatin classes (i.e., cell states defined by chromatin accessibility) across 5 cell types (T, B/plasma, myeloid, stromal, and endothelial). We also investigated the transcription factors that may regulate these chromatin classes, their connections to transcriptional cell states in a proposed superstate model, and their interplay with RA pathology through associations with histological parameters and risk variants.As part of the Accelerating Medicines Partnership (AMP) network, we obtained 18 synovial tissue samples from 14 RA and 4 osteoarthritis (OA) patients for this study. Samples were collected from 7 clinical sites. We performed a 10x single cell ATAC-seq experiment on each sample.We further collected synovial tissue samples from 11 RA patients and 1 OA patient from 2 clinical sites; each sample was used for a 10x single cell multimodal ATAC and Gene Expression experiment.For additional support of the proposed superstate model, we also collected peripheral blood mononuclear cells (PBMCs) from 4 RA patients, sorted for 4 populations (CD4+CD127-CD25hi Tregs, CD4+CD127-CD25int Tregs, CD4+CD25-PD1+CXCR5- TPH, CD4+CD25-PD1+CXCR5+ TFH), tagged each population with a hashing antibody, and pooled populations for one multimodal sequencing run.The FASTQ files are available for controlled access via dbGaP. Additional data can be found on Synapse.The presence of pooled subjects inflates the automatically-generated subject count; the actual consented subject count for this data is 34.

  Study phs003417

• Integrated copy number and expression analysis identifies profiles of whole-arm chromosomal alterations and subgroups with favorable outcome in ovarian clear cell carcinomas

  Ovarian clear cell carcinoma (CCC) is generally associated with chemoresistance and poor clinical outcome, even with early diagnosis; whereas high-grade serous carcinomas (SCs) and endometrioid carcinomas (ECs) are commonly chemosensitive at advanced stages. Although an integrated genomic analysis of SC has been performed, conclusive views on copy number and expression profiles for CCC are still limited. In this study, we performed single nucleotide polymorphism arrays in 57 (31 CCCs, 14 SCs, and 12 ECs) and expression microarrays in 55 epithelial ovarian cancers (25 CCCs, 16 SCs, and 14 ECs), and then evaluated PIK3CA mutations and ARID1A expression in CCCs. SNP array analysis classified 13% of CCCs into a cluster with high frequency and focal range of copy number alterations (CNAs), significantly lower than for SCs (93%, P < 0.01) and ECs (50%, P = 0.017). The ratio of whole-arm to all CNAs was higher in CCCs (46.9%) than SCs (21.7%) (P < 0.0001). SCs with loss of heterozygosity (LOH) of BRCA1 (85%) also had LOH of NF1 and TP53, and LOH of BRCA2 (62%) coexisted with LOH of RB1 and TP53. Microarray analysis classified CCCs into three clusters. One cluster (CCC-2, n = 10) showed more favorable prognosis than the others (CCC-1and CCC-3) (P = 0.041). Coexistent alterations of PIK3CA and ARID1A were more common in CCC-1 and CCC-3 (7/11, 64%) than in CCC-2 (0/10, 0%) (P < 0.01). Being in cluster CCC-2 was an independent favorable prognostic factor in CCC. In conclusion, CCC was characterized by a high ratio of whole-arm CNAs; whereas CNAs in SC were mainly focal, but preferentially caused LOH of well-known tumor suppressor genes. As such, expression profiles might be useful for sub-classification of CCC, and might provide useful information on prognosis.

  Study JGAS000022

• Genotyping microarray data of molecular tumorboard patients in the context of the HRD-manuscript published in IJC

  Intensity files (.idat) derived from the Infinium CytoSNP-850K BeadChip microarray (Illumina) were used to analzye a possible Homologous-Recombination-Repair Deficiency (Molecular Rationale for a PARP-Inhibitor therapy) of n= 39 tumor patients (each n= 39 .idat files of the green and red chanel respectively) presented in the Molecular Tumorboard at the University Hospital Erlangen. Using these files a Genomic Instability Score was bioinformatically deducted (R-based scripts, e.g. ASCAT, scarHRD) based upon the presence of three parameteres "Loss of Heterozygosity, LOH", "Large Scale Transitions, LST" and "Telomeric Allelic Imbalances, TAIs". The associated manuscript is published in International Journal of Cancer, IJC.

  Dataset EGAD00010002736

• Identification of Host Genetic Factors That Are Determinant for the Development of Severe Forms of COVID-19

  We conducted whole exome sequencing (WXS) on 21 cases of Multisystem Inflammatory Syndrome in Children (MIS-C) related to COVID-19 from Brazil. All patients who were hospitalized underwent serum (ELISA) and molecular (RT-PCR) testing for SARS-CoV-2, and the main clinical symptoms associated with SARS-CoV-2 infection were collected. During hospitalization, data on complications, medical interventions, and laboratory findings were also collected. Our results revealed in an unprecedented way the occurrence of several rare loss-of-function variants in the NLRP12 gene among the affected children, and three other SNVs, predicted to be highly pathogenic, were identified in the IL17RC gene. An additional nonsense variant, in the IFNA10 gene, was identified in a single patient. Through in vitro functional analysis, we unequivocally demonstrated that these mutations impact NF-kB activation. These findings are similar to those observed in NLRP12-associated systemic autoinflammatory disorders, characterized by altered innate immune response, with increased NF-&#954;B activation and excessive production of inflammatory cytokines. To our knowledge, our study is the first to provide a plausible molecular mechanism for MIS-C involving inborn errors in NLRP12. We suggest that some patients with MIS-C may benefit from Interleukin (IL)-1 pathway blockade treatments.

  Study phs003512

• Analysis of a cohort of familial ademomatous polyposis patients bearing APC gene mutation

  large number of colorectal adenomas with high risk of evolving into colorectal tumors. Mutations of the Adenomatous polyposis coli (APC) gene is often at the origin of this disease, as well as of a high percentage of spontaneous colorectal tumors. APC is therefore considered a tumor suppressor gene. While the role of APC in intestinal epithelium homeostasis is well characterized, its importance in immune responses remains ill defined. We investigated an array of immune cell features in FAP subjects carrying APC mutations. A group of 12 FAP subjects and age and sex-matched healthy controls were studied. In particular, the expression of 579 immune response genes was analyzed in whole blood cells using the Nanostring nCounter Human Immunology kit v2. (Cuche C. et al. Frontiers in Immunology, 2023, in press)

  Study EGAS00001007237

• The University of Hong Kong Colon Cancer GCV Study

  Background: Ganciclovir (GCV) is widely used in solid organ and hematopoietic stem cell transplant patients for prophylaxis and treatment of cytomegalovirus. It has long been considered a mutagen and carcinogen. However, the contribution of GCV to cancer incidence and other factors that influence its mutagenicity remains unknown. Methods: This retrospective cohort study analysed genomics data for 121,771 patients who had undergone targeted sequencing compiled by the Genomics Evidence Neoplasia Information Exchange (GENIE) or Foundation Medicine (FM). A statistical approach was developed to identify patients with GCV-associated mutational signature (GCVsig) from targeted sequenced data of tumour samples. Cell line exposure models were further used to quantify mutation burden and DNA damage caused by GCV and other antiviral and immunosuppressive drugs. Results: Mutational profiles from 22 of 121,771 patient samples in the GENIE and FM cohorts showed evidence of GCVsig. A diverse range of cancers was represented. All patients with detailed clinical history available had previously undergone solid organ transplantation and received GCV and mycophenolate treatment. RAS hotspot mutations associated with GCVsig¬¬ were present in 9 of the 22 samples, with all samples harbouring multiple GCV-associated protein-altering mutations in cancer driver genes. In vitro testing in cell lines showed that elevated DNA damage response and GCV¬sig are uniquely associated with GCV but not acyclovir, a structurally similar antiviral. Combination treatment of GCV with the immunosuppressant, mycophenolate mofetil (MMF), increased the misincorporation of GCV in genomic DNA and mutations attributed to GCVsig in cell lines and organoids. Conclusions: In summary, GCV can cause a diverse range of cancers. Its mutagenicity may be potentiated by other therapies, such as mycophenolate, commonly co-prescribed with GCV for post-transplant patients. Further investigation of the optimal use of these drugs could help reduce GCV-associated mutagenesis in post-transplant patients.

  Study EGAS00001006707

• Carbamazepine-induced hypersensitivity reactions in Europeans

  An antiepileptic drug carbamazepine is well tolerated by the majority of patients, but can cause severe and potentialy fatal hypersensitivity reactions in a small number of individuals. The aim of this study was to identify genetic predictors of hypersensitivity reactions to carbamazepine. We undertook a genome-wide association study (GWAS) in 22 patients of European ancestry with carbamazepine-induced hypersensitivity syndrome (HSS) and compared our data with genotypes from a healthy population within the WTCCC. We performed imputation of classical HLA alleles according to a recently described method (Science. 2010 Dec 10;330(6010):1551-7. Epub 2010 Nov 4). GWAS statistical analysis was performed using logistic regression with an additive model of inheritance.

  Study EGAS00000000037

• Long-term organoid culture of a small intestinal neuroendocrine tumor rna-seq

  Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare and highly heterogeneous neoplasms whose incidence has markedly increased over the last decades. A grading system based on the tumor cells' proliferation index predicts high-risk for G3 NETs. However, low-to-intermediate grade (G1/G2) NETs have an unpredictable clinical course that varies from indolent to highly malignant. Cultures of human cancer cells enable to perform functional perturbation analyses that are instrumental to enhance our understanding of cancer biology. To date, no tractable and reliable long-term culture of G1/G2 NET has been reported to permit disease modeling and pharmacological screens. Here, we report of the first long-term culture of a G2 metastatic small intestinal NET that preserves the main genetic drivers of the tumor and retains expression patterns of the endocrine cell lineage. Replicating the tissue, this long-term culture showed a low proliferation index, and yet it could be propagated continuously without dramatic changes in the karyotype. The model was readily available for pharmacological screens using targeted agents and as expected, showed low tumorigenic capacity in vivo. Overall, this is the first long-term culture of NETs to faithfully recapitulate many aspects of the original neuroendocrine tumor.

  Study EGAS00001007108

• Long-term organoid culture of a small intestinal neuroendocrine tumor

  Gastroenteropancreatic neuroendocrine tumors (GEP-NETs) are rare and highly heterogeneous neoplasms whose incidence has markedly increased over the last decades. A grading system based on the tumor cells' proliferation index predicts high-risk for G3 NETs. However, low-to-intermediate grade (G1/G2) NETs have an unpredictable clinical course that varies from indolent to highly malignant. Cultures of human cancer cells enable to perform functional perturbation analyses that are instrumental to enhance our understanding of cancer biology. To date, no tractable and reliable long-term culture of G1/G2 NET has been reported to permit disease modeling and pharmacological screens. Here, we report of the first long-term culture of a G2 metastatic small intestinal NET that preserves the main genetic drivers of the tumor and retains expression patterns of the endocrine cell lineage. Replicating the tissue, this long-term culture showed a low proliferation index, and yet it could be propagated continuously without dramatic changes in the karyotype. The model was readily available for pharmacological screens using targeted agents and as expected, showed low tumorigenic capacity in vivo. Overall, this is the first long-term culture of NETs to faithfully recapitulate many aspects of the original neuroendocrine tumor.

  Study EGAS00001007093

• Identification of RNA biomarkers in Parkinson's disease iPSC-derived neuronal cells

  Parkinson?s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons and subsequent motor symptoms. These overt motor symptoms are often preceded by prodromal non-motor symptoms. Though a number of genetic and environmental factors have been identified to play a role in PD, more exact methods for both diagnosing and assessing prognosis are yet to be discovered. Probing the transcriptomes of control and PD cells can give some interesting insight into changes caused by the disease (in both coding and non-coding gene expression), highlighting potential RNA biomarkers that may be used for PD diagnosis and as new drug targets. The study consists of two main sources of data: matched neural stem cell (NSC) and fully differentiated dopaminergic neurons derived from iPS cells. Both sets of data are made up of three samples from a control cell line, and five samples carrying a mutation in one of several genes known to be linked to heritable PD: PARK2, PARK22 or PARK9. All transcriptome libraries were synthesized and sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) on the Illumina HiSeq 2500 platform. Resulting data was mapped to the human genome annotation (hg38) and processed CAGE tags were clustered ready for differential expression analyses. The 16 samples here described were sequenced across two lanes.

  Study JGAS000142

• Identification of RNA biomarkers in Parkinson's disease iPSC-derived neuronal cells

  Parkinson���s disease (PD) is an age-related, chronic and progressive neurodegenerative disorder characterized by a loss of multifocal neurons and subsequent motor symptoms. These overt motor symptoms are often preceded by prodromal non-motor symptoms. Though a number of genetic and environmental factors have been identified to play a role in PD, more exact methods for both diagnosing and assessing prognosis are yet to be discovered. Probing the transcriptomes of control and PD cells can give some interesting insight into changes caused by the disease (in both coding and non-coding gene expression), highlighting potential RNA biomarkers that may be used for PD diagnosis and as new drug targets. The study consists of two main sources of data: matched neural stem cell (NSC) and fully differentiated dopaminergic neurons derived from iPS cells. Both sets of data are made up of three samples from a control cell line, and five samples carrying a mutation in one of several genes known to be linked to heritable PD: PARK2, PARK22 or PARK9. All transcriptome libraries were synthesized and sequenced using no-amplification non-tagging cap analysis of gene expression (nAnT-iCAGE) on the Illumina HiSeq 2500 platform. Resulting data was mapped to the human genome annotation (hg38) and processed CAGE tags were clustered ready for differential expression analyses. The 16 samples here described were sequenced across two lanes.

  Study JGAS000318

• Efficacy and safety of entrectinib in patients with ROS1-positive advanced/metastatic non-small cell lung cancer (NSCLC) from the Blood First Assay Screening Trial (BFAST)

  BFAST is a global, open-label, multicohort trial that evaluates the efficacy and safety of multiple therapies in patients with advanced/metastatic NSCLC and targetable alterations, identified by blood-based molecular testing. We present data from Cohort D (ROS1-positive). Patients ≥18 years old with stage IIIB/IV, ROS1-positive NSCLC detected by blood-based testing, received entrectinib 600 mg daily. At data cut-off (November 2021), 55 patients were enrolled and 54 had measurable disease. Cohort D met its primary endpoint; the confirmed objective response rate (ORR) by investigator was 81.5% which was consistent with the ORR from the integrated analysis of entrectinib (investigator-assessed ORR: 73.4%, data cut-off May 2019, ≥12 months follow-up). The safety profile of entrectinib was consistent with prior reports. These results demonstrate consistency with those from the integrated analysis of entrectinib in patients with ROS1-positive NSCLC identified by tissue-based testing and support the clinical value of blood-based testing to inform clinical decision-making.

  Study EGAS50000000105

• Targeted sequencing of Burkitt lymphoma tumour samples from the UK's Haematological Malignancy Research Network

  The UK’s Haematological Malignancy Research Network (www.HMRN.org) was established in 2004 to provide robust generalizable data to inform clinical practice and research. HMRN is a collaboration between researchers in the Epidemiology &amp;amp; Statistics Group (ECSG) at the University of York, a unified Clinical Network operating across 14 hospitals, and an integrated Haematological Malignancy Diagnostic Service (HMDS) in Leeds. Covering a population of around 4 million, HMRN collects detailed information about all patients diagnosed with a haematological malignancy within the HMRN region, accruing around 2,400 new diagnoses each year. The population has a similar socio-demographic profile to the country as a whole, and HMRN’s maturing data present an increasingly valuable resource to address real questions of concern to haematologists, commissioners and health service researchers – locally, nationally and internationally. This study forms part of a larger project employing targeted exome sequencing on tumour samples from patients diagnosed with a variety of both lymphoid and myeloid malignancies. The results for samples collected from 39 Burkitt lymphoma patients, diagnosed within HMRN from 2005 to 2012, are provided.

  Study EGAS00001004649

• Homozygous Duplication Identified by Whole Genome Sequencing Causes LRBA Deficiency

  In more than one third of primary immunodeficiency (PID) patients, extensive genetic analysis including whole exome sequencing (WES) fails to identify the genetic defect. Whole genome sequencing (WGS) is able to detect variants missed by other genomics platforms, enabling the molecular diagnosis of otherwise unresolved cases. Here, we report two siblings, offspring of consanguineous parents, who experienced similar severe events encompassing early onset of colitis, lymphoproliferation and hypogammaglobulinemia, typical of lipopolysaccharide (LPS)-responsive and beige-like anchor protein (LRBA) or cytotoxic T-lymphocyte-associated protein 4 (CTLA4) deficiencies. WGS of these patients detected a 12.3 kb homozygous tandem duplication that was absent in control cohorts and is predicted to disrupt the reading frame of the LRBA gene.

  Study phs002557

• Action to Control Cardiovascular Risk in Diabetes (ACCORD) Clinical Trial

  The Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial was a randomized, multicenter, double 2 x 2 factorial design study involving 10,251 middle-aged and older participants with type-2 diabetes who are at high risk for CVD events because of existing CVD or additional risk factors. The purpose of ACCORD was to determine if intensive glycemic control, intensive lipid management and intensive blood pressure control could prevent major cardiovascular events (myocardial infarction, stroke or cardiovascular death) in adults with type 2 diabetes mellitus. Secondary hypotheses included treatment differences in other cardiovascular outcomes, total mortality, microvascular outcomes, health-related quality of life and cost-effectiveness. The ACCORD trial failed to show a beneficial effect of intensive blood pressure or lipid therapy on the primary outcome, and intensive glycemia management actually increased mortality. The hypothesis underlying this ancillary study is that the failure of ACCORD to achieve its goal of reducing cardiovascular risk in diabetic patients through intensive management of hyperglycemia, dyslipidemia, and hypertension may be the result of variation in drug response due to genetic variation between individual participants. Benefits of intensive therapy may accrue to subsets of subjects with specific genetic variants predisposing to efficacious responses to particular therapeutic regimens, and harms may accrue to those with other variants predisposing to poor efficacy or adverse events. Identifying these variants could lead to a precision medicine approach to treating diabetes where each patient&#39;s genetic profile could identify the most efficacious treatment regimen with the lowest likelihood of adverse events. To test this hypothesis, a genome-wide genetic analysis was undertaken, incorporating both common variants distributed across the genome and rare variants targeted to exonic regions. Associations of genetic variants with short term responses to individual medicines as well as long term outcomes were investigated. The dataset is composed of genetic data from the ~6100 participants who agreed to participate in the ACCORD optional genetic studies and who allowed broad investigator access to their samples and the data derived from those samples, and from whom a DNA sample of sufficient quality was obtained. While a total of 8514 participants consented to the optional genetics studies, not all consented to broad investigator access, and those who did not are not included in this dataset, although they were also genotyped. Access to these additional genotypes can only be obtained by direct collaboration with the investigators of this study. Phenotype data used in the association analyses are derived from the ACCORD public release clinical data set, which has been made available through BioLINCC.

  Study phs001411

• Leucocyte eQTLs in autoimmune disease and health

  Peripheral blood was taken from healthy controls and patients with active autoimmune disease. CD4 T cells, CD8 T cells, monocytes, neutrophils, and B cells were separated using magnetic-activated cell sorting. RNA and genomic DNA was extracted from cell lysates using Qiagen Allprep kits. Genotyping of healthy controls and patients with inflammatory bowel disease was performed using the Illumina Human OmniExpress12v1.0 BeadChip at the Wellcome Trust Sanger Institute. 200 ng RNA was processed for hybridization onto Affymetrix Human Gene ST 1.1 microarrays. Gene expression and genotyping data was used to perform eQTL mapping.

  Study EGAS00001001251

• Center for Common Disease Genomics (CCDG)-Neuropsychiatric: A Study of the Genetic Causes of Complex Pediatric Disorders (CAG)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002004

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: The Autism Simplex Collection (TASC)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001741

• Proteomic Biomarkers of Progressive Fibrosing Interstitial Lung Disease: a Multicentre Cohort Analysis (PF-ILD Proteomics-BioLINCC)

  Data Access NOTE: Please refer to the &#8220;Authorized Access&#8221; section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives: To identify novel plasma biomarkers of progressive fibrosing interstitial lung disease and develop a proteomic signature to predict this phenotype. Background: Progressive fibrosing interstitial lung disease (ILD) is a devastating condition characterized by parenchymal scar formation, leading to deteriorating lung function and early death. Whereas almost all patients with idiopathic pulmonary fibrosis (IPF) progress, a variable proportion of patients with other common ILDs, including connective tissue disease associated ILD, chronic hypersensitivity pneumonitis, and unclassifiable ILD, develop progressive fibrosing ILD. There are criteria that effectively identify those experiencing ILD progression. However, the criteria do not allow patients who are at risk to be identified before progression occurs. Several blood-based biomarkers have been linked to differential progression in patients with IPF and other fibrosing ILDs. Inflammatory signaling also appears to have a prominent role in fibrotic-predominant ILDs. As such, cytokines, interleukins, and other immune mediators might serve as useful biomarkers of progressive fibrosing ILD. The PF-ILD Proteomics study was a targeted investigation of inflammation-related proteins to identify and validate novel biomarkers of progressive fibrosing ILD in patients with fibrotic connective tissue disease-associated ILD, chronic hypersensitivity pneumonitis, and unclassifiable ILD. Participants: There were 589 participants. The discovery cohort comprised 385 participants and the validation cohort comprised 204 participants. Design: PF-ILD Proteomics was a multicenter cohort analysis study. Peripheral blood was collected from consenting patients and plasma was isolated according to center-specific protocols. Relative plasma concentrations for 368 biomarkers were determined with use of a semi-quantitative, targeted proteomic platform. Patients from UC Davis and UCSF comprised the discovery cohort and those from UTSW comprised the validation cohort. Participants who were alive with less than 10% relative decline in forced vital capacity (FVC) at 12 months-after blood draw were considered to have non-progressive ILD. Participants who died of any cause, underwent lung transplant, or experienced 10% or greater relative FVC decline within 12 months of blood draw were deemed to have progressive fibrosing ILD. Conclusions: 17 plasma biomarkers of progressive fibrosing interstitial lung disease were identified and showed consistent associations across ILD subtypes.

  Study phs003954

• Impact of Genetic Polymorphisms on Human Immune Cell Gene Expression

  While many genetic variants have been associated with risk for human diseases, how these variants affect gene expression in various cell types remains largely unknown. To address this gap, the DICE [Database of Immune Cell Expression, Expression quantitative trait loci (eQTLs) and Epigenomics] project was established. Considering all human immune cell types and conditions studied, we identified cis-eQTLs for a total of 12,254 unique genes, which represent 61% of all protein-coding genes expressed in these cell types. Strikingly, a large fraction (41%) of these genes showed a strong cis-association with genotype only in a single cell type. We also found that biological sex is associated with major differences in immune cell gene expression in a highly cell-specific manner. These datasets will help reveal the effects of disease risk-associated genetic polymorphisms on specific immune cell types, providing mechanistic insights into how they might influence pathogenesis.

  Study phs001703

• Gut microbiome profiles according to sex, body mass index and dietary fiber intake

  Findings from recent studies suggest that the community of microbes residing in the human body is important in disease etiology; however, it remains unclear whether personal factors modulate human microbial composition. Studies based on animal models indicate that differences in composition might be attributed to sex-mediated effects. We analyzed the relationship of sex, adiposity, and dietary fiber intake with gut microbial composition using fecal samples from human subjects. We explored the associations of these factors with metrics of community composition and specific taxon abundances. We found that men and women had significantly different microbial community composition and that women had reduced abundance of a major phylum. Adiposity was associated with gut microbiome composition and specifically in women but not in men. Fiber from fruits and vegetables and fiber from beans were each associated with increased abundance of specific bacterial taxa. These findings provide initial indications that sex, adiposity, and dietary fiber might play important roles in influencing the human gut microbiome. Better understanding of these factors may have significant implications for gastrointestinal health and disease prevention.

  Study phs000884

• Ghana Breast Health Study

  The Ghana Breast Health Study (GBHS) was a multi-disciplinary, population-based case-control study conducted in Accra and Kumasi, Ghana that was designed to investigate breast cancer etiology in the West Africa region. The study enrolled 1,126 invasive breast cancer cases and 2,106 frequency matched population-based controls using census-based sampling. GHBS participants were between the ages of 18 to 74 years of age. Breast cancer cases were recruited at the time they presented with lesions suspicious of breast cancer at three hospitals: Korle Bu Teaching Hospital (Accra), Komfo Anoyke Teaching Hospital (Kumasi) and Peace and Love Hospital (Kumasi). These hospitals are the primary providers of treatment for breast cancer in Ghana, allowing for cases in our study to represent most breast cancers diagnosed in these areas during the study period. The following publications describe the GBHS in detail: 1) Brinton LA et al. Design considerations for identifying breast cancer risk factors in a population-based study in Africa. Int J Cancer 2017;140:2667-2677 (PMID:28295287). 2) Nyante SJ et al. Recruiting population controls for case-control studies in sub-Saharan Africa: The Ghana Breast Health Study. PloS one 2019;14:e0215347 (PMID:30990841)Among subjects with an available source of germline DNA genotyping was performed using the Infinium Global Screening Array-24 per the manufacturer&#8217;s guidelines using the Infinium automated protocol. We excluded probable duplicates and close relatives, and samples with a call rate &lt; 95% or samples with extreme heterozygosity. Female sex was verified by Identifiler using X chromosome heterozygosity and the X chromosome inbreeding coefficient F statistics. The GLU genetics&#8217; ld.tagzilla module was used to confirm African ancestry. To resolve more detailed population substructure, principal components analysis was conducted among all unrelated subjects using the EIGENSOFT v7.2.1. Imputation was performed using the Michigan imputation server Minimac3 with 1K genomes phase3 as reference panel.

  Study phs002387

• Rare occurrence of Aristolochic Acid Mutational Signatures in Oro-Gastrointestinal Tract Cancers

  Aristolochic Acids (AAs) are a family of carcinogenic phytochemical compounds commonly found in plants of Aristolochia and Asarum genus. Comprehensive genomic profiling of genitourinary and hepatobiliary cancers has highlighted the widespread prevalence of Aristolochic Acid (AA) signatures in cancer patients across parts of Asia, particularly in Taiwan. The aim of our study was to determine in Oro-Gastrointestinal Tract (OGITC) cancers, the prevalence, role and significance that AA plays as a driver of tumorigenesis as AA containing products are commonly administered orally. This would suggest a possible etiological relationship between cancers of OGITC. However, in this study the rarity of AA mutational signatures in OGITC suggests that AA is unlikely to drive carcinogenesis in OGITC through direct exposure. Our study is valuable to show that AA exposure is not an equal driver of tumorigenesis in different organs and represents an important piece of information in the field.

  Study EGAS00001005909

• A Clone's Genomic Stability as a Biomarker of Its DNA-Damage Resilience

  A main problem in the treatment of advanced cancers, including gastric cancers and glioblastoma, is the incertitude at which we predict how individual patients will respond to DNA-damaging agents, especially on the long run. Knowing the mechanism behind a patient's response, or the lack thereof, will help us depart from the oversimplified &#8220;more-is-better&#8221; and &#8220;one-size-fits-all&#8221; principles according to which DNA-damaging agents are administered. This will improve clinical outcome by allowing us to pinpoint those who would respond better and longer to lower doses than to higher doses of DNA-damaging agents. Under the assumption that the success of DNA-damaging therapy increases with the proliferation rate of a relatively homogeneous tumor population, there was little reason to assume anything other than monotonic dose-response relations. With the recent paradigm shift that most cancers are in fact DNA mosaic products of ongoing evolution, comes the urgency to reconsider these fundamental principles behind DNA-damaging therapy administration. As the developers of one of the first DNA deconvolution methods and with access to technologies to profile the transcriptomes of up to 10,000 cells simultaneously, we are equipped to embark on first personalized dose-finding strategies for DNA-damaging therapies. We will test the potential of the very long-term legacy that DNA-damage entails on a cell &#8220;genomic instability&#8221; as new biomarker of DNA-damage response. Our preliminary studies showed that, for most cancer types, DNA-damaging agents change a clone's genomic instability and that clones succumb to a limit in the amount of genomic instability they can tolerate. In particular, our results showed that patients with intermediate genomic instability have a very poor outcome and that this relation is only evident among treatment-naive patients, but not among patients treated with DNA-damaging agents. Further they show that we can measure genomic instability per clone and that clones with extreme genomic instability typically don't grow large. Our hypothesis that genomic instability, rather than proliferation rate, determines how sensitive a tumor is to DNA-damaging agents on the long-term, is founded on two unexpected findings. Patients with extremely high genomic instability per tumor clone have an exceptionally good outcome. Aim 1 will integrate exome- and single cell RNA-Seq (scRNA-Seq) data to characterize clones and to measure how much genomic instability they can tolerate. Low genomic instability is associated with reduced benefit from DNA-damaging agents. Aim 2 will use comet assays and treatment history to quantify DNA damage per clone, relating it to the clones' ability to tolerate DNA damage and to changes in the genomic instability of therapy-surviving clones.

  Study phs003762

• M116 Proteome Extracellular Vesicle Profiling

  For extracellular vesicles (ECV) extraction from plasma, 1M ammonium acetate was added to precipitate ECVs on ice for 45 min. Then, 100 mM ammonium acetate was added to the mixture, and ECVs were precipitated by centrifugation at 20,000g for 30 min. ECVs were washed with 50 mM ammonium bicarbonate (Sigma-Aldrich, Cat. 1066-33-7). Then, 600 µl of 1% ammonium deoxycholate (Sigma Aldrich, Cat. K2755-1MG) were added. The concentration of protein in each sample was measured using a bicinchoninic acid assay (BCA assay). Ammonium bicarbonate was used to dilute 500 µg of protein into a final volume of 500 µl. Next, dithiothreitol (Sigma-Aldrich, Cat. D9779) was added to obtain a final concentration of 20 mM, followed by iodoacetamide (Sigma-Aldrich, Cat. I6125) to a final concentration of 40 mM. Next, trypsin (Roche, Cat. RTRYP-RO) was added to the sample in a 1:25 protein ratio and incubated at 37°C overnight. Next day, formic acid (ThermoFisher Scientific, Cat. 28905) in a final concentration of 0.1% was added and extraction of proteins was done using Empore™ Solid Phase Extraction Cartridges (3M), following manufacturer’s instructions. The eluted samples were then centrifuged for 90 min. using a speed vacuum centrifuge (Thermo, RC1010), followed by snap freezing in liquid nitrogen. Then, the samples were kept in a freeze dryer (LyoDry Compact Benchtop, MechaTech) overnight. Next, the samples were reconstituted in 30 µl of 0.1% formic acid (FA) and an o-Phthaladehyde (Oparil) assay was performed to determine the concentration of each sample. After that, the sample was prepared in a concentration of 0.5 µg/µl using 0.1% FA and alcohol dehydrogenase (ADH). The samples were prepared in glass mass spectrometry vials for proteomic analysis using a Waters Synapt G2Si High-Definition Mass Spectrometry (Waters Corporation) operated by the MassLynx 4.1., 110 min. running time with 2 µl of an injection containing 1 µg of peptide. Quality controls were also run along with samples to guarantee consistency. Pooled quality controls were made from all samples, in which the samples were run at the beginning, middle and end of the mass spectrometry run. Samples were randomized before running the experiment. The proteomic data was then imported into Progenesis software 4.2 (Nonlinear Dynamic, UK) to identify and quantify peptides and proteins.

  Dataset EGAD50000001679

• Targeting the p53 pathway to treat Malignant Rhabdoid and High-Risk Atypical Teratoid Rhabdoid Tumors

  Rhabdoid tumors (RTs) predominantly affect young children and are among the deadliest pediatric solid tumors. Despite multimodal therapy consisting of surgery, radiation, and chemotherapy, children with these tumors have median survival of less than one year. RTs can arise throughout the body, including the central nervous system (CNS) where they are called atypical teratoid rhabdoid tumors (AT/RTs), and in extra-CNS locations such as the kidneys and other soft tissues where they are designated malignant RTs (MRTs). We previously identified MDM2 and MDM4 as therapeutic vulnerabilities in RTs and showed that treatment with the MDM2 inhibitor idasanutlin increased survival in mice bearing MRT xenografts. However, the therapeutic potential of idasanutlin in CNS RT tumors is unknown. Single agent therapies are prone to resistance and show limited clinical benefit on their own. Therefore, we sought to identify combination strategies incorporating idasanutlin that would be effective in both CNS and extra-CNS RTs. Here, we show that the XPO1 inhibitor selinexor increased nuclear retention of p53 and potentiated idasanutlin-induced p53 pathway activation and cytotoxicity in AT/RT and MRT cell lines in vitro. Importantly, combination therapy limited acquired resistance through TP53 mutation. In vivo, combination therapy was well-tolerated, reduced tumor burden, and increased survival in orthotopic models of both AT/RT and MRT. Our results demonstrate that combining idasanutlin with selinexor is a promising therapeutic strategy for children with rhabdoid tumors.

  Study EGAS00001007680

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Multimodal Developmental Neurogenetics of Females

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002043

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Genomics of Autism Spectrum Disorder (GASD)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002509

• Center for Common Disease Genomics [CCDG] - Neuropsychiatric: Simons Searchlight

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of New York Genome Center (NYGC). WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal.An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002512

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Center of Excellence (ACE II)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants, both in coding and noncoding regions, will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases, pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs002042

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Study of Autism Genetics Exploration (SAGE)

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001740

• Center for Common Disease Genomics (CCDG) Neuropsychiatric: Autism Genetic Resource Exchange

  In this study, we address the enormous challenges common complex diseases pose for genomic analysis and the enormous opportunities surmounting them offers for advancing healthcare. The common genetic disorders proposed for study here are believed to have extreme locus heterogeneity, requiring the analysis of large numbers of samples to comprehensively identify the genomic variants underlying them. We propose that a combination of deep population studies and joint analysis of SNPs, indels, and structural variants both in coding and noncoding regions will provide the next level of understanding of common genetic disorders. Whole genome sequencing (WGS) will be critical to this next-generation approach to the genomics of complex disease. WGS will need to be accompanied by the technical ability to generate and handle very large data sets, a particular focus and strength of NYGC. WGS will also need to be accompanied by new statistical tools and algorithms, which will be developed by the strong core group committed to this proposal. An overarching goal of this proposal, one that capitalizes on the power of WGS, is to identify disease-associated variants at the individual nucleotide level. In many cases pathogenic mutations fall in noncoding regions of the genome, which can only be fruitfully explored with WGS. A major effort was put into building new computational strategies to functionally annotate noncoding transcribed sequences, and to build new datasets to enable such strategies, opening new frontiers of understanding of disease-related regulatory variants.

  Study phs001766

• A New CA19-9 Cut-Off Value Identifies Lewis Antigen Status and Refines Prognostic Stratification in PDAC

  This study investigates the clinical utility of serum CA19-9 levels in pancreatic ductal adenocarcinoma (PDAC), with a focus on identifying patients with Lewis antigen–negative status due to germline FUT3 variants. Using data from multicenter prospective cohorts in Taiwan, we analyzed CA19-9 classification, FUT2/FUT3 genotypes, and clinicopathological annotations. The goal of this study is to refine prognostic stratification and reduce false-negative interpretation of CA19-9 in PDAC patients. All participants provided informed consent, and the study was approved by the relevant institutional review boards.

  Study EGAS50000001575

• RNA-Sequencing of cervical cancers

  Question: Can we identify cervical cancer patients who are at risk for distant metastatic (DM) recurrence following treatment with radiotherapy, concurrent weekly cisplatin and brachytherapy (RTCT). Findings: An immune-based 55 gene risk score was developed using a cohort of 81 patients treated with RTCT that was strongly predictive of DM and cause-specific survival (CSS). The risk score was validated in two independent patient cohorts. A high immune metastatic risk score was associated with a high tumor mutational burden and a ‘cold’, immune-excluded tumor microenvironment at diagnosis. Meaning: The immune gene expression risk score may help to identify patients at risk of DM and potential targets for mitigating this risk.

  Study EGAS50000000087

• Single Cell Transcriptomic Data from CD4+ T Cells from Children with MIS-C

  Multisystem inflammatory syndrome in children (MIS-C) is a severe complication of SARS-CoV-2 infections in the pediatric population characterized by fever, multi-organ involvement and systemic inflammation. Single-cell RNA sequencing was used to evaluate the transcriptomic signature of CD4+ T cells obtained from the peripheral blood of patients with MIS-C before (n=3) and after (n=5) immunomodulatory treatment, along with pediatric controls (n=4). Compared to controls and treated children with MIS-C, T cells obtained from pre-treatment MIS-C patients upregulated genes associated with activation, such as NF-kB signaling. This single-cell transcriptomic data was used in the context of a larger study entitled, "Notch1-CD22-Dependent Immune Dysregulation in the SARSCoV2-Associated Multisystem Inflammatory Syndrome in Children."

  Study phs003086

• Misoprostol-induced high fever GWAS study

  Genome-wide association (GWAS) meta-analysis study of misoprostol-induced fever was conducted on two South American cohorts (Argentina and Ecuador). DNA was collected from blood of women who were screened for postpartum haemorrhage (PPH) and administered misoprostol were included in the study. Genotypes were acquired from the Global Screening Array (Illumina). Meta-analysis of these cohorts was completed using METAL software.

  Study EGAS00001005455

• The T cell receptor repertoire of tumor infiltrating T cells is predictive and prognostic for cancer survival

  Tumor infiltration by T cells is paramount for effective anti-cancer immune responses. We hypothesized that the T cell receptor (TCR) repertoire of tumor infiltrating T lymphocytes (TIL/Tc) could determine disease course at different stages in cancer progression. We show that the diversity of the TIL/Tc TCR at baseline is prognostic in various cancers, whereas in metastatic melanoma TIL/Tc TCR clonality at baseline is predictive for activity and efficacy of PD1 blockade immunotherapy.

  Study EGAS00001005201

• Effect of ETS2 modulation on chromatin accessibility and enhancer activity in inflammatory (TPP) macrophages

  This dataset consists of H3K27ac ChIP-seq and ATAC-seq in primary human macrophages following modulation of ETS2 expression. There are three datasets: H3K27ac ChIP-seq in ETS2-edited and unedited inflammatory (TPP) macrophages, H3K27ac ChIP-seq in ETS2-overexpressing and control M0 macrophages, and ATAC-seq in ETS2-edited and unedited inflammatory macrophages. For editing experiments, monocytes were transfected with CRISPR-Cas9 ribonucleoproteins containing a gRNA that was validated to edit ETS2, or a non-targeting control gRNA. Inflammatory macrophage differentiation was performed using conditions that model chronic inflammation (TPP): 3 days GM-CSF (50ng/mL) followed by 3 days GM-CSF, TNFa (50ng/mL), PGE2 (1mg/mL), and Pam3CSK4 (1mg/mL). For overexpression experiments, controlled overexpression of ETS2 mRNA or control mRNA (an equivalent amount of mRNA encoding the reverse complement of ETS2 – thereby controlling for the quantity, length and purine/pyrimidine composition of the transfected RNA but with a transcript that would not be translated) was induced in resting, non-activated (M0) macrophages by transfecting 500ng mRNA. To minimise non-specific activation due to the transfected RNA, in vitro transcription was performed using co-transcriptional capping (to minimise uncapped products), and incorporating modified, minimally immunogenic nucleotides (replacing uridine with N1-methyl-pseudouridine and cytidine with methylcytidine). After 18 hours, transfected cells were were activated with low dose LPS and harvested 6 hours later. For H3K27ac ChIP-seq, cells were harvested, cross-linked, quenched, lysed, and sheared. Immunoprecipitation of histone-DNA complexes was performed overnight at 4C with rotation using an anti-H3K27ac antibody and the SimpleChIP Plus Sonication ChIP kit (Cell Signaling Technology). Following reverse cross-linking, 50ng of immunoprecipitated DNA or input DNA were used to prepare sequencing libraries using the iDeal Library Preparation kit (Diagenode), according to manufacturer instructions. 10 PCR cycles were used for the amplification step and size selection was not performed. The quality and molarity of all libraries was assessed using a BioAnalyzer 2100 (Agilent) and the libraries were sequenced on an Illumina NovaSeq 6000. Raw data are provided as raw and aligned sequencing reads from H3K27ac-bound DNA and the input chromatin. ATAC-seq in TPP macrophages was performed using the Omni-ATAC protocol (Corces et al 2017) with the following modifications: cell number was increased to 75,000 cells, cell lysis time was increased to 5 minutes; volume of Tn5 transposase in the transposition mixture was doubled; duration of the transposition step was extended to 40 minutes. Sequencing libraries were prepared by PCR with the NEBNext Ultra II Q5Master Mix (NEB) as described previously (Corces et al 2017). Amplified libraries were cleaned using AMPure XP beads (Beckman Coulter). Sequencing reads were trimmed using TrimGalore! (Phred score 24), filtered to remove reads < 20 bp and aligned to the human genome (hg19) using Burrows-Wheeler Aligner (BWA). Aligned reads were converted to BAM files, sorted and indexed using SAMtools (Li et al, 2009). PCR duplicates and unmapped reads were removed, and the resulting BAM files were re-sorted and indexed. Raw data are provided as 100 bp paired-end Illumina reads from n = 3 donors for each experiment. BAM files are also provided.

  Study EGAS50000000109

• Illumina HumanOmniExpress genotyping data from the TEENAGE (TEENs of Attica: Genes and Environment) study.

  The TEENAGE study is a cross-sectional study comprising healthy Greek adolescents. The study was conducted according to the guidelines specified in the Declaration of Helsinki and all procedures involving human subjects were approved by the Institutional Review Board of Harokopio University and the Greek Ministry of Education, Lifelong Learning and Religious Affairs. The TEENAGE study target population comprised adolescent students aged 13 to 15 years attending the first three classes of public secondary schools located in the wider Athens area of Attica. The regions across Attica from which students were recruited were physically similar and all urban in nature. Sampling of regions and schools selected to participate was random. Students were enrolled from the wider urban region to ensure that they were coming from families with varying educational background and socio-economic status. Moreover, in order to exclude any vast economic disparities, all participating schools were exclusively public schools, which are free of charge. A total of twenty-four schools participated in the study out of 285 junior secondary public schools in Attica. Anthropometric, medical and dietary information was obtained. DNA samples were genotyped using Illumina HumanOmniExpress BeadChips (Illumina, San Diego, CA, USA) at the Wellcome Trust Sanger Institute, Hinxton, UK. Genotype calling algorithm used was Illuminus (Teo et al., 2007).

  Study EGAS00001000996

• Center Common Disease Genomics [CCDG] - Cardiovascular: Partners Biobank

  This study is a part of NHGRI&#39;s Center for Common Disease Genomics, a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will perform whole genome sequencing of 140K individuals and whole exome sequencing of 225K individuals over the course of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. CAD is the leading cause of death in the world and common variant association studies show that our understanding of the underlying molecular mechanisms is incomplete (e.g, &gt;2/3 of the 63 common variants previously mapped for CAD do not directly relate to known risk factors). CAD is representative of a class of common diseases with onset at middle age. When CAD occurs early in life, there is a stronger inherited component. In addition, there is empirical evidence that a burden of rare coding alleles in individual genes contribute to risk for CAD. Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOCAD_STROKE_FINAL.pdf For this study, The Broad Institute of MIT and Harvard generated genetic data for ~13,500 individuals from the Partners Biobank, including using whole exome sequencing and whole genome genotyping (Infinium Global Screening Array), with 550 samples from patients with myocardial infarction, a type of EOCAD. Partners Biobank, launched in 2010, is a biobank composed of samples from Partners hospitals, including Massachusetts General Hospital and Brigham and Women&#39;s Hospital. The Biobank has enrolled &gt;100K individuals to study how genes, lifestyle, and other factors affect people&#39;s health and contribute to disease.

  Study phs002018

• Personalized Medicine Strategy for MPNSTs: Using Precision Oncology on PDOX Models to Inform Tumor Boards

  Background: Malignant peripheral nerve sheath tumors (MPNSTs) are a heterogeneous group of aggressive soft tissue sarcomas with poor prognosis. Currently there is a lack of effective treatments for MPNSTs. Here, we propose a personalized medicine approach that integrates a precision oncology strategy guided by MPNST genomic analysis, with a functional validation of treatment response in an orthotopic xenograft model (PDOX) derived from the same MPNST. Methods: Comprehensive whole genome sequencing analysis was performed in primary MPNSTs, relapses and (in one case) metastases, following disease progression in two independent individuals. Matched MPNST PDOX models were generated by orthotopically implanting tumor fragments near the sciatic nerve of immunodeficient mice. Candidate targeted combination therapies were prioritized based on genomic alterations and tested in vivo in the PDOX models. Results: The feasibility of the developed strategy is illustrated for two MPNST patients, one Neurofibromatosis type 1 (NF1) individual that developed two independent MPNSTs and another sporadic MPNST case with multiple metastatic relapses. Genomic analysis revealed a remarkable degree of genomic stability across primary MPNSTs and their successive relapses in each patient, and even metastases in one individual. While based on a small number of cases requiringing additional analyses, this finding aligns with previous evidence suggesting a fair genomic conservation throughout tumor evolution. This stability supports the identification of consistent therapeutic vulnerabilities throughout disease progression. Among the therapies tested, co-treatment of MEK inhibitor (MEKi) plus bromodomain inhibitor (BETi) elicited the highest antitumor activity, resulting in approximately 60% tumor volume reduction in the sporadic MPNST PDOX model, whose patient has been receiving this therapy for eight months with sustained remission. Conclusions: This study demonstrates the feasibility and clinical utility of integrating genomic-driven precision oncology with PDOX-based functional testing for MPNSTs. This strategy may support molecular tumor boards (MTBs) in their treatment decisions. The observed genomic stability supports the use of longitudinal tumor profiling to guide treatment, and the success of MEKi+BETi highlights its potential as a combination therapy for MPNSTs.

  Study EGAS50000001502

• Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure (InterGEN Study)

  This research study focuses on the genomic and psychological environmental effects on blood pressure among mothers and their children. The study includes 250 mothers who self-identify as AA/black, and 250 children between the ages of 3 and 5 years old at the time of enrollment. The study is longitudinal and data collection interviews are scheduled every six months for two years after enrollment, for a total of four participant interviews. Assessment is as follows: genetic (time 1 only) and psychological factors (every six months for two years).

  Study phs001792

• Clonally resolved single-cell multi-omics identifies routes of cellular differentiation in acute myeloid leukemia

  In this study we generated single-cell whole transcriptome and surface marker expression data for 24 samples of 19 AML patients as well as one healthy donor. We followed the CITEseq protocol with the 3' 10x Genomics scRNAseq kit version 3.1 To increase the coverage of the mitochondrial genome we generated mitochondrial libraries following a protocol termed Optimized 10x. Based on TAPseq, we generated libraries to increase the coverage of selected nuclear SNVs. Exome sequencing was generated for 15 patients to identify nuclear variants. Bulk ATAC was obtained for 9 samples to facilitate the discovery of mitochondrial SNVs. MutaSeq (modified version of SmartsSeq2) was performed on cells from 3 patients. Targeted DNAseq from single-cell derived colonies was generated for 1 patient.

  Study EGAS00001007078

• We screened 2.5 million SNPs in 161 individuals from 13 Sahelian populations from Western, Central and Eastern parts of the belt, and including both nomadic and sedentary groups

  We confirmed the role of the Sahel belt as a main corridor for human migrations across the African continent. Strong admixture was observed in both Central and Eastern Sahelian populations, with North Africans and Near Eastern/Arabians respectively, but it was inexistent in Western Sahelian populations. Genome-wide local ancestry inference in admixed Sahelian populations revealed several candidate regions that were significantly enriched for non-autochthonous haplotypes, and many showed to be under positive selection.

  Study EGAS00001001610

• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Dataset EGAD50000000226

• Osteosarcoma mate-pair and RNA-sequencing

  DNA mate pair and RNA sequencing data of conventional osteosarcomas. Mate pair libraries, with average insert sizes of 2-4 kb, were prepared for sequencing using the Nextera Mate Pair Library Preparation Kit. Paired-end 76 base pair reads were generated using an Illumina NextSeq 500 sequencing instrument. Total RNA was enriched for polyadenylated RNA using magnetic oligo(dT) beads. Enriched RNA was prepared for sequencing using the TruSeq RNA Sample Preparation Kit v2 and paired-end 151 base pair reads were generated from the cDNA libraries using an Illumina NextSeq 500 instrument.

  Study EGAS00001003842

• Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer

  The goal of the sequencing study was to determine the neoantigen profile of melanoma patients. We performed whole exome sequening of the tumor and respective patien matched PBMC samples (2x50nt) and RNA-sqeuencing of the tumor samples. The was analyzed for somatic point mutaions, using the RNA-Seq data to determine mutation expression. This study contains the exome seq data.

  Study EGAS00001003306

• Personalized RNA mutanome vaccines mobilize poly-specific therapeutic immunity against cancer RNA-Seq

  The goal of the sequencing study was to determine the neoantigen profile of melanoma patients. We performed whole exome sequening of the tumor and respective patien matched PBMC samples (2x50nt) and RNA-sqeuencing of the tumor samples. The was analyzed for somatic point mutaions, using the RNA-Seq data to determine mutation expression. This study contains the patient matched RNA-Sequencing data.

  Study EGAS00001003307

• Drug screening and whole genome sequencing of primary cells and cell lines from ovarian cancer patients to associate genomic aberrations with in vitro drug sensitivities

  Identifying drugs for cancers with poor prognosis like ovarian cancer (OC) is hindered by inappropriate cell models and the limitations of current viability assays. We developed an automated confocal microscopy-based live cell assay (DeathPro) that robustly de-convolves cell death and proliferation over time by employing a specific image processing strategy. Using DeathPro, we screened nine OC patient-derived cell lines and one normal cell line (HOSEpiC) with 22 drugs or combinations. Whole genome was performed to analyze if the cell lines harbor OC-typical genomic aberrations and to relate genomic features to drug sensitivities. Commonly observed alterations in OC patients like TP53 mutations and MYC or PI3KCA amplifications were absent in the normal cell line but frequently detected in the OC cell lines. Moreover, genome-derived homologous recombination deficiency (HRD) scores of the OC cell lines correlated with their responses to carboplatin, olaparib and DNA demethylation drugs. Overall, we propose an imaging-based platform to guide drug development and genome-drug sensitivity analysis.

  Study EGAS00001002239

• Jackson Heart Study (JHS-BioLINCC)

  Accessing Data: Please refer to &#8220;Authorized Access&#8221; below regarding accessing data through the BioData Catalyst ecosystem. The data from this accession is not available for download through dbGaP.Related Studies: Other Jackson Heart Study data available include: Imaging studies (JHS-Imaging), Genetics and genomics (The Jackson Heart Study, phs000286.v7.p2), and Collaborative Cohort of Cohorts for COVID-19 Research (C4R-JHS, phs002907.v1.p1): Jackson Heart Study (phs002907.v1.p1).Available Data: Data available for request include Jackson Heart Study visit 1-3 examination cycles, collated annual follow-up communication data through 2016, and follow-up for mortality, heart disease, and stroke events through 2014.Objectives: The objectives of the Jackson Heart Study are to: 1) investigate the associations of biological, psychosocial, and behavioral factors with the incidence atherosclerotic events and health outcomes in an African American cohort; and 2) increase access to and the participation of African American populations and scientists in biomedical research and professions.Background: It has long been recognized that African Americans share a disproportionate burden of deleterious health outcomes including diabetes, hypertension, kidney disease and early onset of cardiovascular disease. The Jackson Heart Study was initiated in 2000 to explore potential mechanisms and mediators of health outcomes in a large African American cohort. In addition, the JHS conducts a variety of community education and outreach activities to promote healthy lifestyles to reduce disease risk burden and student training programs to promote and support public health research.Participants: African American men and women, age 35-84 at entry. Of the 5306 cohort members enrolled in the study, the data repository contains data from 3,883 that provided informed consent to share their data with investigators not affiliated with the study.Design: Participants were enrolled in the study from 2000-2004 from urban and rural areas of three counties (Hinds, Madison and Rankin) in the Jackson, MS metropolitan statistical area. Participants were enrolled from each of 4 recruitment pools: a random sample component (17%), volunteer component (30%), currently enrolled in the Atherosclerosis Risk in Communities (ARIC) Study (31%), and secondary family members (22%). Recruitment was limited to non-institutionalized adult African Americans age 35-84 years, except in the family cohort where those age &#8805;21 years were eligible. The final cohort of 5,306 participants includes 6.59% of all African American residents aged 35-84 (N=76,426, US Census 2000). Data collection at the baseline exam included a medical history, physical examination, blood/urine analytes and interview questions on areas such as: physical activity; stress, coping and spirituality; racism and discrimination; socioeconomic status; and health care access.The current release of the Jackson Heart Study includes data collected at baseline, exam 2 (2005-2008), and exam 3 (2009-2013). Annual follow-up and surveillance of clinical cardiovascular events is ongoing.

  Study phs003740

• Whole exome sequencing of ATCWGS42 primary tumour and PDX

  Genomic DNA was isolated from snap-frozen tissue and subjected to whole genome sequencing at The Center for Applied Genomics (Hospital for Sick Children, Toronto, ON) or at Beijing Genomic Institute (BGI). High-coverage whole exome-sequencing was performed at GeneSeeq Inc. (Toronto, Ontario, Canada) using IDT xGen exome panel.

  Study EGAS50000001490

• Massachusetts General Hospital (MGH) Atrial Fibrillation Study

  The Massachusetts General Hospital (MGH) Atrial Fibrillation Study was initiated in 2001. The study has enrolled serial probands, unaffected and affected family members with atrial fibrillation. At enrollment participants undergo a structured interview to systematically capture their past medical history, AF treatments, and family history. An electrocardiogram is performed; the results of an echocardiogram are obtained; and blood samples are obtained. The Massachusetts General Hospital (MGH) Atrial Fibrillation Study is utilized in the following dbGaP substudies. To view genotypes, analysis, other molecular data, and derived variables collected in these substudies, please click on the following substudies below or in the "Substudies" box located on the right hand side of this top-level study page phs001001 Massachusetts General Hospital (MGH) Atrial Fibrillation Study. phs001116 MGH AF CHARGE-S phs001117 MGH AF Exome Sequencing phs001118 MGH AF Medical Resequencing

  Study phs001001

• Development and Validation of Patient-Derived Xenografts from Fibrolamellar Carcinoma Human Tissue

  We developed and validated Patient-Derived Xenografts (PDX) of Fibrolamellar Carcinoma human tissue from surgical resections. Human tissues from primary liver tumor, recurrent liver, and liver metastases were implanted into NOD-SCID-Gamma (NSG) mice (Jackson laboratories) and monitored for tumor growth. Some of the original tissues were frozen for further analysis including RNA sequencing. Tumors that grew were then harvested and passaged into additional mice. Some tumor tissues from the PDX samples were frozen for RNA-Seq analysis. The PDX was validated by histologic, transcriptomic and proteomic analysis. The RNA-Seq analysis was performed on original tissue samples including primary liver tumor, recurrent liver, liver metastases, normal liver, and the derived PDX.

  Study phs002435

• Reading about genomic analysis of pan-neuroblastoma

  There are virtually no research fields that do not benefit from the large-scale genomic analysis that are so popular nowadays. For research into diseases with highly diverse clinical behavior like pediatric neuroblastoma, nevertheless, this type of approach has been a game-changer. Samuel W. Brady and colleagues, from St. Jude Children’s Research Hospital in Memphis, have gathered data from 702 neuroblastomas which were profiled by whole genome sequencing (WGS, n = 205), whole exome sequencing (WES, n = 539), and/or RNA-Seq. Less than half of the samples were generated during this study, while the others were obtained from previous work. Part of the WES data was indeed deposited in EGA in 2012 (EGA study EGAS00001000213). A scratchy summary about the huge work from Samuel W. Brady and colleagues, published in Nature Communications this October 2020 “These findings suggest that the sympathetic nervous system, the tissue from which neuroblastoma arises, is susceptible to different oncogenic insults at different times during development, which could be explored in future investigations using animal models.” Conclude the authors, highlighting the importance of their findings. Pediatric neuroblastomas are classified according to clinical and molecular features into low, intermediate, and high risk. Age plays a critical role in the classification, with younger children having an overall better prognosis. The samples included in this study belonged to all ages and risk-groups: the aim of such set up is the identification of age-associated molecular aberrations. The authors defined a mutational landscape of pediatric neuroblastoma including rare driver events, impossible to pick with a smaller data set. Interestingly, most driver mutations' frequency was found to be age-related. Those include alterations on MYCN, TERT, PTPRD, and Ras pathway, in addition to the previously reported ATRX. In addition, the large data set allowed the authors to define co-existence relations between the mutations (mutual exclusion or co-occurrence) which is a crucial puzzle piece to unravel the mechanisms driving the pathogenesis. Enjoy this really interesting article, open source on Pubmed.

  Blog genomic-analysis-of-pan-neuroblastoma

• Dataset for Fragle Software Development and Evaluation

  Fragle is a deep learning based two stage model that quantifies ctDNA from blood plasma derived cfDNA bam files. Fragle was developed using some previously published datasets and some newly generated data. Fragle was evaluated using some validation cohorts and some unseen cohorts. Some of these cohorts are newly created consisting of total 365 low pass (2-3X) whole genome sequencing bam files mapped to hg19/GRCh37. This dataset contains these newly generated bam files.

  Dataset EGAD50000000167

• Genomic Characterization CS-MATCH-0007 Arm Z1D

  The CS-MATCH-0007 protocol is a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and posttreatment tumor biopsy specimens from all patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to their corresponding genomic alterations. Arm Z1D is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with MMR deficiency are treated with nivolumab. This subprotocol is one of the treatment arms in the EAY-131 trial included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood and RNA from tumor tissue. A fuller genomic landscape of tumors from these patients will enable discovery of potential molecular features correlated to clinical outcomes or lay the foundation for future studies leading to new and more effective treatments.

  Study phs001859

• Genomic Characterization CS-MATCH-0007 Arm Y

  The CS-MATCH-0007 protocol is a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing, RNA sequencing and if possible, whole-genome, methylation and miRNA sequencing using pre-and post-treatment tumor biopsy specimens from all patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to their corresponding genomic alterations. Arm Y is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with AKT mutations are treated with AZD5363. This subprotocol is one of the treatment arms in the EAY-131 trial included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood and RNA from tumor tissue. A fuller genomic landscape of tumors from these patients will enable discovery of potential molecular features correlated to clinical outcomes or lay the foundation for future studies leading to new and more effective treatments.

  Study phs001904

• Genomic Characterization CS-MATCH-0007 Arm H

  The CS-MATCH-0007 protocol is a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from all patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to their corresponding genomic alterations. Arm H is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with BRAF V600K/V600E mutations are treated with Dabrafenib and Trametinib. This subprotocol is one of the treatment arms in the EAY-131 trial included in the CS-MATCH-0007 protocol and will provide specimens for the program including DNA from tumor tissue and whole blood and RNA from tumor tissue. A fuller genomic landscape of tumors from these patients will enable discovery of potential molecular features correlated to clinical outcomes or lay the foundation for future studies leading to new and more effective treatments.

  Study phs001888

• DAC Portal documentation

  DAC Portal Welcome to the DAC Portal documentation! If you are involved in governance or legal aspects, technical or operational aspects, or serving as a data steward, this page will be helpful for you. By exploring these materials, you can define your own Data Access Committee (DAC) and policies, understand the minimal requirements for a DAC and a policy object, and comprehend how the EGA data access requests are managed. DAC Portal Index Setting up your account DACs and Policies Pending Request table Manage Data Requests History page Audit your DACs, policies, and datasets Deprecation User Preferences DAC API - A programmatic approach Setting up your account Register yourself as an EGA user. The Helpdesk team will validate your account (this could take up to 48 hours). After validation, you will receive an email with a link to verify your email - Make sure you click on the link to verify your account! If you don’t receive the email, please check your spam folder. Once your account is active you can login to the DAC Portal. We recommend you to check out the Take The Tour! DACs and Policies Create a DAC Click on Create a DAC Add the title and description to your DAC. Once ready, click on the ‘Create’ button. You will have to wait until the Helpdesk Team validates the creation of your DAC. Once approved by Helpdesk, your DAC will be assigned with a persistent identifier (EGAC). Edit a DAC Once your DAC is registered and approved, you can edit it and add contacts. Remember, you can add as many contacts as needed. And, you can also remove/add contacts anytime. To add a contact, you must write the username or email of a registered EGA user in the Members field. Once you have typed the whole username or email, a drop-down menu will appear where you can select the contact. Select a contact from the drop-down menu. Make sure you write the full username or email of the contact so it appears as an option. Make sure that you select one main contact. Set up the role you want to grant to the new contact of the DAC. We recommend you to check out the FAQ to learn more about the different roles! After adding all the necessary contacts and assigning roles, click on Update. This will send an email notification to the new DAC member, letting them know about the invitation to managing the DAC. Once they log into the DAC Portal, they will be able to either accept or turn down the invitation. Create a policy First, please note that all information registered in a policy metadata object will be publicly available on the EGA website. For each released dataset, all users will be able to read the policy under the “Data Access” tab. Select Create a Policy from the Policies tab. Select the DAC that you want your policy to depend on. Add the title and terms and conditions for accessing and using your data. If you already have an external website for data access requests, you can add the URL directly here (see example here). You can find a template of a Data Access Agreement (DAA) document in our Policy documentation page. The DAA template is provided for guidance only and should be adapted to suit your own purpose depending on the security policies, terms for publication or embargoes, and restrictions on data use or sharing. You can also add Data Use Ontologies (DUO) to your policy. These DUO codes are used to semantically tag the terms and conditions of using the data linked to the policy (example). For more information, you can refer to the Data Uso Ontology documentation. Once completed, make sure to click the Create button in order to register your policy. A persistent identifier (EGAP) will be assigned automatically. Edit a policy Please, note that you will not be able to edit the policy if it shows in orange. Meaning that you are a member of the DAC linked to that policy. Members don’t have edit rights. Only admins can edit objects. You can check your registered policies on My policies, available at the menu in the top-right corner. Select your policy. It will then display the information of that policy, allowing you to edit the information. Once you are done with the modifications, click Update. Pending Requests Table Table Settings Upon selecting a specific DAC, you will be presented with a customisable table showcasing all pending data access requests. This table allows you to tailor the displayed information according to your preferences by selecting desired columns. Available Columns (Displayed with the Eye Icon): Date: The date when the data access request was submitted. Full Name: Name and surname of the user submitting the request. Email: Email address associated with the user's request. Username: The username linked to the EGA account of the user submitting the request. Organisation: Affiliated organisation of the user submitting the request. Dataset: EGA accession ID for the requested EGA dataset. Dataset Title: Title of the requested dataset. DAC Comment: Space provided for internal comments related to the request. Expiration: Option to specify an expiration date for granted permissions. Check more information on the pending request table here! Table Filters By default, all data access requests are displayed. However, you have the option to apply filters to refine your view. Follow these steps to apply filters: Click on the More button. This action will reveal the different columns available for applying filters. As you select columns, the checked fields will be displayed at the top of the request table. Choose the specific values within the selected columns that you want to filter for. Click the Search button to apply the selected filters. Do you find yourself frequently applying the same filters? You can save multiple combinations of filters for easy access at any time! Here's how: Click the Save button. Provide a descriptive name for the filter combination. Click Save to confirm. To load saved filters, simply select the saved filter from the dropdown menu to apply it automatically. Check more information on filters here! Advanced Search For users requiring more granular control over their data access requests, the DAC Portal offers an Advanced Search feature using JIRA Query Language (JQL). With JQL, you can craft precise and complex queries to filter and retrieve specific data access requests based on various criteria such as date, user details, dataset attributes, and more. Using JQL's flexibility, you can create custom queries to meet your specific needs, allowing for advanced filtering options beyond the standard filters provided. You can find the Advanced Search feature following these steps: Click the … button Select Advanced To view the allowed fields for filtering and explore all available options, simply click on the info icon. Once you have written the filtering values, click the Search button to apply. Check more information on filters here! Manage Data Requests Upon logging into the DAC Portal, you'll notice a sand clock icon next to the DAC ID, indicating the number of pending requests. Click on the DAC to review these requests. Accept requests Click on the right side of the toggle button to grant access to the user. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with granting permissions. Deny requests Click on the left side of the toggle button to deny access to the user. Provide a reason for the denial. Note that the user will receive an email with this reason. Click on the Done button. You can manage other requests before proceeding to the next step. After managing the requests, click on the Apply button. A confirmation box will appear summarising the options to be applied. Click on Yes, Confirm to proceed with denying permissions. Tips! Apply a filter to view all requests to be managed at once. Use the toggle in the row with column names to grant or deny permissions for multiple requests simultaneously. You can grant and deny permissions in the same action, simplifying the process. The confirmation box will provide a summary of all actions, including grants, denials, DAC comments, and expiration dates. History Page The History page serves as a dedicated space to view information regarding all requests managed by all DAC members. Here, you can review active permissions and revoke them as needed. Go to the History page by clicking on the "HISTORY" button from a DAC page in the DAC Portal. Here are the different row types you may find: Current permissions: row in green with a toggle button to revoke permissions on the right. Approved requests: row in green, with no toggle button. Request denied: row in red with “request denied” on the right. Permission revoked: row in red with “permission revoked” on the right. Distinctions to Note! Between Request Denied and Permission Revoked: Request Denied: Refers to requests that were rejected from the outset, indicating that access to the dataset was never granted. Permission Revoked: Indicates that permissions were previously granted but have since been revoked. Users with permissions revoked have previously accessed the dataset. Between Approved Request and Current Permissions: Approved Request: Represents an entry when a data access request has been approved in the past. Current Permissions: Denotes ongoing permissions where a user has present access to the dataset. An approved request may now appear as Permission Revoked in the present. By observing these different rows, users can gain insight into the complete history of a user's interactions and permissions regarding a dataset over time. To revoke access to a specific user for a dataset, follow these steps: Go to History page Look for the row with the specific permissions. You can use the filters! Click on the toggle button to revoke access. Add a denial reason. Bear in mind that the requester will receive the denial reason! Click on the Apply button. Check more information on the Hisotry page here! Audit your metadata objects In the DAC Portal, you can efficiently manage and audit various metadata objects pertinent to your role as a Data Controller. Upon accessing the DAC Portal, you will encounter three primary tabs on the homepage: DAC: Contains information about Data Access Committees (DACs). Policies: Provides insights into linked policies. Datasets: Displays datasets and relevant details. Within each tab, you'll find a comprehensive list of the objects you manage, these being grouped by type (DAC, Policies, Datasets), as well as by your role (member/admin). Whilst the lists give you a quick look, to check how things are connected, we've added a table at the bottom DACs and policies. DACs Let’s check which policies are linked to a specific DAC: Go to "My DACs." Select a DAC. Click on "EDIT" to see more details. You are now on this page: Scroll down to see the linked policies. Click on “List of linked policies of this DAC” and you will see a list of all policies linked to your selected DAC. Policies Do you want to view a list of datasets connected to a particular policy? Follow the same steps mentioned earlier, but head to the policy tab this time. In the policy tab, you'll find a list of all your policies. Here, you may notice two different icons next to the policy ID (EGAP): DAC Icon (): This represents the DAC. Hover your mouse over the icon to see the DAC ID. Dataset icon (): This indicates datasets falling under that policy. The number next to the icon tells you how many datasets are linked to the policy. For example, if you see "2" next to the icon, it means there are two datasets linked to that policy. If you want to check the linked datasets and their relevant information, simply click on a specific policy. You'll then find the "List of linked datasets of this policy" at the bottom of the page. Datasets Finally, in the dataset tab, by default you will see a list of all the datasets you can manage with all your DACs and policies. Yet, we've included two handy ways to organise them: DAC vs. policy: You can group by datasets, either by DAC or policy. Released vs. unreleased: You can sort out datasets based on their release status. Feel free to experiment with both options! For instance, if you want to see which DACs have unreleased datasets, simply select DAC and unreleased, and you'll get the details you need! Deprecation Do you have a bunch of metadata objects like DACs and policies that you don’t need anymore? This section shows you how to get rid of them! But what does "deprecation" mean for EGA? It's basically changing the status of a metadata object to "deprecated," which means we won't be using it in the future. In simple terms, it's like saying these objects are no longer useful. However, because we believe in making metadata FAIR, once an object has a persistent identifier, we can't just delete it. So, instead of deleting, we deprecate it. Here's a helpful tip! If you want to make a metadata object disappear from the DAC Portal, deprecate it. You won’t see it in the portal anymore! Let’s say you want to deprecate a DAC. Let’s do it! Go to "My DACs." Select a DAC. Click "EDIT" to see more details. You are now in this page: Click on the Deprecate button It will then appear a message. There are two options here: Your DAC is not linked to any policy, hence it’s ready to be deprecated. Click on “Yes. Confirm” to deprecate your DAC object! Your DAC is linked to at least one policy, and you need to either: Deprecate the linked policy first, or Link the policy to a different DAC Now, let’s say you don’t want to get rid of the policy altogether, but you want to change the DAC it’s linked to. Here's how: Go to the policy tab. Find the policy you want to change (for example, EGAP50000000019). Choose a new DAC to link it to. Click on Update. See the Edit Policy section for more details. After ensuring that the DAC we want to deprecate isn’t linked to any policy, return to the "My DACs" section and follow the steps outlined previously. This will lead you to a confirmation message. You can only deprecate DACs and Policies. To deprecate a dataset, please contact our Helpdesk team. Check more information on how deprecation works here! User Preferences We have implemented email notifications in the DAC Portal. Here’s the complete list: DACs: Pending requests Approved by Helpdesk Rejected by Helpdesk DAC Invitation Requesters: Data access request approved Data access request denied Permissions revoked Upcoming expiration date As a DAC member, you will be able to decide whether you want to receive the DAC notifications or not. For that, go to the top-right corner menu, select User Preference. You will be able to decide whether you want to receive notifications for: Approved by Helpdesk Rejected by Helpdesk DAC Invitation For pending requests, you will be able to select how often do you want to receive the notification: Daily Weekly Fortnightly As a DAC member, you are responsible for managing data access requests. Consequently, you will receive notifications for pending requests. If you prefer not to manage these requests, please arrange to be removed as a contact for your DAC. Here's a tip! Do you have a pending request that you don’t want to receive a notification? Add a DAC comment! The EGA understands that a request resolution can take some time, for this reason, if you add a comment (make sure you save it by clicking the APPLY button!) we will filter those requests at the time of sending the notification! DAC API - A programmatic approach In addition to the new DAC Portal, we are excited to announce the release of the DAC API. This enables users to programmatically manage permissions. If you are interested in learning more about the technical specifications, you can click the button below. Check out the DAC API specification!

  Documentation access/data-access-committee/dac-portal

• Panel sequencing of endocrine-resistant breast cancer

  Patients with endocrine-resistant breast cancer in Stockholm Sweden. DNA obtained from patients primary and relapse tumors, and tumor-free lymph nodes used as germline control. DNA was extracted from formalin-fixed paraffin-embedded tissue and sequenced by 370-gene panel-based sequencing with Kapa HyperPlus library preparation and Twist Bioscience hybrid capture. Custom bait sets (panels) from Twist Bioscience. Paired end 2x150 bp using NovaSeq X. The data is presented as fastq-files.

  Study EGAS50000000236

• WES Breast Patient-derived Tumor Organoid

  This dataset includes 18 Whole Exome Sequencing (WES) samples from 5 subjects. WES is performed on a matched pair of case/control samples, e.g., tumor/control or organoid/control. For each patient, the same control sample is used for the analysis of tumor and organoid samples. The sample name structure identifies the type of sample: <subjectId>_[TON][12]_[Case|Ctrl]_EX2; where T, O, and N refer to Tumor tissue, Organoid, and control sample, respectively. The number 1 or 2 refers to the specific tissue, and Case and Ctrl indicate a tumor tissue (or organoid) and a control sample, respectively. For example, ICSBCS007_T1_Case_EX2 is the first tumor tissue of subject ICSBCS007; ICSBCS007_O1_Case_EX2 is the tumor organoid derived from that tumor sample, and ICSBCS007_N1_Ctrl_EX2 is the matching control sample. More information can be found in the sample information table.

  Dataset EGAD50000000961

• Targeting FGFR1 for treatment of soft-tissue sarcoma (H021)

  Purpose: Altered FGFR1 signaling has emerged as therapeutic target in various epithelial malignancies. In contrast, the role of FGFR1 in soft-tissue sarcoma (STS) has not been established. Prompted by the detection and subsequent therapeutic inhibition of amplified FGFR1 in a patient with metastatic leiomyosarcoma, we investigated the oncogenic properties and potential as drug target of FGFR1 in STS.Experimental Design: The frequency of FGFR1 amplification and overexpression, as assessed by fluorescence in situ hybridization, microarray-based comparative genomic hybridization and mRNA expression profiling, SNP array profiling, and RNA sequencing, was determined in three independent patient cohorts. The sensitivity of STS cell lines with or without FGFR1 alterations to genetic and pharmacologic FGFR1 inhibition and the signaling pathways engaged by FGFR1 were investigated using short-term viability assays, long-term colony formation assays, and biochemical analysis.Results: Increased FGFR1 copy number was detected in 74 of 190 (38.9%; Cohort 1), 13 of 79 (16.5%; Cohort 2), and 80 of 254 (31.5%; Cohort 3) patients. FGFR1 overexpression occurred in 16 of 79 (20.2%, Cohort 2) and 39 of 254 (15.4%; Cohort 3) patients. Targeting of FGFR1 by short hairpin RNA-mediated knockdown and different small-molecule inhibitors (PD173074, AZD4547, BGJ398) revealed that the requirement for FGFR1 signaling in STS cells is primarily dictated by FGFR1 expression levels, and identified the MAPK-ERK1/2 axis as critical FGFR1 effector pathway.Conclusion: These data identify FGFR1 as driver gene in multiple STS subtypes and support FGFR1 inhibition, guided by patient selection according to FGFR1 expression and monitoring of MAPK-ERK1/2 signaling, as therapeutic option in this challenging group of diseases.H021

  Study EGAS00001001844

• Neuroblastoma patient WGS data

  Paired tumor and normal WGS of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

  Dataset EGAD00001008123

• Clinical outcomes and immune correlates of response to nivolumab plus chemoradiotherapy in women with locally-advanced cervical cancer – NiCOL study

  Concurrent chemoradiotherapy (CRT) with blockade of the PD-1 pathway may enhance immune-mediated tumor control through increased phagocytosis, cell death, and antigen presentation. The NiCOL phase 1 trial was designed to determine safety, tolerance, and immune correlates of response to the PD-1 blocking antibody, nivolumab, with and following concurrent CRT in 16 women with locally advanced cervical cancer (LACC). Three patients experienced grade 3 dose-limiting toxicities. The overall response rate was 93.8% [95%CI: 69.8%-99.8%] with a 2-year PFS of 75% [95% CI: 56.5%-99.5%]. Compared to patients with progressive disease (PD), progression-free (PF) subjects showed a brisker stromal immune infiltrate, higher proximity of tumor-infiltrating CD3+ T cells to PD-L1+ tumor cells and of Foxp3+ T cells to proliferating CD11c+ myeloid cells. PF had higher baseline levels of PD-1 on EMRA CD4+ T cells and ICOS-L on tumor-associated macrophages (TAMs) vs PD, which instead displayed enhanced PD-L1 expression on TAMs and higher, circulating frequencies of proliferating Tregs at baseline. Concomitant nivolumab plus definitive CRT is safe and associated with encouraging PFS rates. Further validation in the subset of LACC displaying pre-existing, adaptive immune activation is warranted.

  Study EGAS00001007297

• Genetics and therapeutic responses to TIL therapy of pancreatic cancer PDX models

  Pancreatic cancer is the 7th leading cause of cancer-related deaths worldwide. Checkpoint immunotherapy has not yet showed encouraging results in pancreatic cancer possibly owing to a poor immunogenicity and/or an immune suppressive microenvironment. The aim of this study was to develop patient-derived xenografts (PDX) models and to assess if autologous tumor-infiltrating lymphocytes (TILs) would have anti-tumoral activity in pancreatic cancer. Tumor biopsies from 29 patients were subcutaneously transplanted into NOG mice. Tumor growths were confirmed in 11 out of 29 transplantations. The PDX tumors histologically resembled their original biopsies, but since stromal cells in the PDX model tumors were from mouse, their gene expression differed from the original biopsies. Immune checkpoint ligands other than PD-L1 were expressed in pancreatic cancers but PD-L1 was rarely expressed. One of the three tumors that did express PD-L1 was an adenosquamous cancer and another had a mismatch repair deficiency. TILs were expanded from six tumors and were injected into NOG or human interleukin-2 transgenic-NOG (hIL2-NOG) mice carrying PDX tumors. Regression of tumors could be verified in hIL2-NOG mice in 3 of the 6 PDX models treated with autologous TILs, including the adenosquamous PDX model. In conclusion, PDX models of pancreatic cancer can be used to learn more about tumor characteristics and biomarkers, and to evaluate responses to ACT and combination therapies. The major benefit of the model is that modifications of T cells can be tested in an autologous humanized mouse model to gain preclinical data to support the initiation of a clinical trial.

  Study EGAS00001005596

• Interferon lambda 4 impairs viral antigen presentation and attenuates T cell responses

  Genetic variants of the interferon lambda (IFNL) gene locus are strongly associated with spontaneous and IFN treatment induced clearance of hepatitis C virus (HCV) infections. Individuals with the ancestral IFNL4-dG allele are not able to clear HCV in the acute phase and develop chronic hepatitis C (CHC) with more than 90% probability. Paradoxically, the IFNL4-dG allele encodes a fully functional IFNλ4 protein with antiviral activity against HCV and coronavirus. Here we describe a hitherto unknown effect of IFNλ4 on HCV antigen presentation. Only minor amounts of IFNλ4 are secreted, because the protein is largely retained in the endoplasmic reticulum (ER) where it induces ER stress. Stressed cells were significantly weaker activators of HCV specific CD8+ T cells. This was not due to reduced MHC I surface presentation or extracellular IFNλ4 effects, since T cell responses could be restored by exogenous loading of MHC with HCV antigens. Rather, IFNλ4 induced ER stress impaired HCV antigen processing and/or loading onto the MHC I complex. Our results provide a potential explanation for the IFNλ4 – HCV paradox.

  Study EGAS00001005396

• NHGRI GREGoR Consortium: Genomics Research to Elucidate the Genetics of Rare Disease

  The NHGRI GREGoR (Genomics Research to Elucidate the Genetics of Rare Disease) Consortium was established in June 2021 with the goal of developing novel tools and approaches to advance the discovery of the genetic basis of rare conditions. Numerous types of molecular data are generated in GREGoR and available on the AnVIL cloud platform via dbGaP application, including short- and long-read genome and exome sequencing, transcriptomics, metabolomics, methylomics, and proteomics. De-identified clinical and demographic data is obtained, with a focus on standardized ontologies.Visit the GREGoR Consortium data webpage for summary information about the GREGoR Dataset, including numbers of participants and data types, methods documentation, and Release Notes. The Consortium comprises five Research Centers (RCs - see below), a Data Coordinating Center (DCC), and various partner members and external collaborators.Baylor College of Medicine Research Center (BCM-GREGoR) The Baylor College of Medicine GREGoR program, which is part of the GREGoR consortium, enrolls individuals, families, and cohorts with suspected rare disease across a range of syndromic and non-syndromic phenotypes. Subjects are enrolled from national and international collaborating physician referrals. Subjects provide written informed consent for future re-contact. Data generated and shared include family structure, detailed phenotypes, exome or short-read genome data, and in some cases long-read genome or RNA-sequencing, and these are shared upon completion of standard quality control checks and annotation. Broad Institute (Broad) The Broad Center for Mendelian Genomics, part of the GREGoR consortium uses next-generation sequencing (exome, genome, transcriptome, and long read sequencing), computational approaches, and functional studies to discover the variants and genes that underlie Mendelian conditions with a particularly focus on neuromuscular, neurodevelopmental, and syndromic phenotypes. Samples come from collaborators and direct enrollment through the Rare Genomes Project and we are committed to rapid data sharing without an embargo period. University of California, Irvine (UCI-GREGoR) To accelerate the pace of Mendelian disease gene discovery and clinical implementation, we propose a Mendelian Genomics Research Center, part of the GREGoR Consortium, leveraging the broad pediatric and adult clinical and research expertise at Children's National Hospital and University of California, Irvine. Our goal is to develop best practices to increase the diagnostic yield of rare diseases, engage the community to reduce health disparities for complex diagnoses, while creating a dataset accessible to all. Our Center will unite world class experts combining basic and translational research with innovative approaches to phenotyping, variant identification and functional investigation of both coding and non-coding sequence changes with the goals of discovering novel Mendelian gene variations and identifying variants not detected on current sequencing pipelines, disambiguating uncertain variants into disease-causing versus benign categorizations, and sharing information by working collaboratively with the GREGoR community.GREGoR Stanford Site (GSS) The goal of the GREGoR Stanford Site (GSS) is to provide a platform for functional genomics research and validation to improve diagnosis in Mendelian disease. Participants included individuals with undiagnosed suspected Mendelian disease who had non-diagnostic exome sequencing and their immediate family members. Participants and their family members provided written, informed consent and biological samples from which DNA, RNA, plasma, fibroblasts, PBMCs and other cell types were generated and stored. Samples from research participants and their immediate family members may have undergone short and long-read genome sequencing, transcriptome sequencing, metabolomics and/or lipidomics profiling, methyl-capture-sequencing and ATAC-sequencing. De-identified clinical data extracted from participant medical records are linked to the samples. University of Washington Center for Rare Disease Research (UW-CRDR) The goals of the University of Washington Center for Rare Disease Research are to: (1) maximize novel gene discovery for Mendelian conditions by recruitment, short- and long-read whole genome sequencing, transcriptome sequencing and analysis of families with rare conditions for which the gene is either unknown or the gene is known but no pathogenic variant can be identified via clinical testing; (2) develop new strategies for gene discovery for Mendelian conditions caused by variants that are difficult to detect using conventional testing strategies, variants of unknown function effect (e.g., regulatory, structural variants) or have unusual modes of inheritance; and (3) implement high-throughput screening and targeted follow-up functional studies to prioritize and validate candidate non-coding variants. De-identified data and phenotypic information are shared via MyGene2, ClinVar, and AnVIL.

  Study phs003047

• The brain neurovascular epigenome and its association with dementia

  Cerebral small vessel disease (SVD) is frequently comorbid with Alzheimer’s disease (AD) and vascular brain endothelial cells (BECs) are enriched for the expression of genes associated with AD genetic risk. However, the gene regulatory landscapes of neurovascular cells and their intersection with genetic risk for disease remains unexplored. Here we have generated gene regulomes for human BECs, mural cells and other brain cell types to show that AD heritability is primarily immune-related and that it shows modest enrichment in BECs. By contrast, genetic risk for SVD is enriched across cells of the neurovascular unit, including astrocytes. Enhancer-to-gene interactomes implicate amyloid processes in both AD and SVD, though the risk genes are mostly distinct for the two disorders. Motifs for putative partners of lineage transcription factors in microglia and BECs were enriched for AD and SVD variants at genes linked to disease pathways. Gene prioritization and enrichment analyses further identified potential repurposable drugs for AD. Our findings highlight novel regulatory mechanisms and therapeutic targets within the neurovascular system.

  Study EGAS50000001160

• Framingham Heart Study-Cohort (FHS-Cohort) - 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. Related Studies Other Framingham data available include: Imaging studies (Framingham Heart Study-Cohort (FHS-Cohort)-Imaging, phs003593), Genetics and genomics (Framingham Cohort, phs000007), Collaborative Cohort of Cohorts for COVID-19 Research (C4R): (Framingham Heart Study, phs002911), and as a component of the Sleep Heart Health Study (SHHS-BioLINCC, phs003637). Available Data Original cohort: data now include examination data from the first 32 clinical exams, selected ancillary data, and event follow-up through 2018. Offspring/Omni1 cohort: Data available include Framingham Offspring examination data from the first 9 clinical exams and selected ancillary data and event follow-up through 2019. Also included are the first 4 exams from the OMNI 1 cohort. Third Generation/Omni2/New Offspring Cohort: Data available include Framingham Generation 3 examination data from the first 3 clinical exams, selected ancillary data and event follow-up through 2019. Also included are the OMNI 2 and New Offspring (NOS) cohorts. A genetic pedigree is not provided for the Framingham phenotype only data. Objectives The objectives of the Framingham Study are to study the incidence and prevalence of cardiovascular disease (CVD) and its risk factors, trends in CVD incidence and its risk factors over time, and familial patterns of CVD and risk factors. Other important objectives include the estimation of incidence rates of disease and description of the natural history of cardiovascular disease, including the sequence of clinical signs and systems that precede the clinically recognizable syndrome and the consequences and course of clinically manifest disease. Background Original cohort: The original cohort of the Framingham Study began in 1948 under the U.S. Public Health Service and was transferred under the direct operations of the new National Heart Institute, NIH, in 1949. Participants were sampled from Framingham, Massachusetts, including both men and women. This was the first prospective study of cardiovascular disease and identified the concept of risk factors and their joint effects. Offspring/Omni1 cohort: With the aging of the Framingham cohort and with interest in familiar aggregation and heritability, a new cohort consisting of the offspring of the original cohort was sampled. Spouses of offspring were also included. This new sample, began enrollment in 1971 and constituted a second generation of participants, permitting new assessment of risk factors and outcomes, and provided a resource for the genetic analyses which were yet to come. The Offspring participants have had repeated examinations, though at typically longer intervals than the original cohort. Third Generation/Omni2/New Offspring Cohort: Thirty-one years after enrollment began for the second generation of the Framingham Heart Study (Framingham Offspring Study), Framingham investigators began enrolling adults with at least one parent enrolled in the Offspring study into the Framingham Generation 3 cohort. The addition of the third generation was expected to facilitate investigation of secular trends in risk factors and indicators of health and disease within families, to enhance statistical power to detect genetic and environmental determinants of complex diseases, and to clarify how subclinical cardiovascular disease predicts occurrence of overt clinical events. Participants Original cohort: At entry to the study in 1948-1952, the study recruited 5,209 men and women, ages 28-62 years, living in Framingham, MA. Offspring/Omni1 cohort: 5,124 men and women, ages 5-70 years at entry consisting of offspring of the original Framingham cohort (and spouses of the offspring). In 1994, the Omni Cohort 1 enrolled 507 men and women of African-American, Hispanic, Asian, Indian, Pacific Islander and Native American origins, who at the time of enrollment were residents of Framingham and the surrounding towns. Third Generation/Omni2/New Offspring Cohort: 4095 men and women, almost all who self reported their ethnicity as white, ages 19+ years at entry, with at least one parent in the Framingham Offspring study, participated in the Gen III cohort. The New Offspring Cohort enrolled spouses of Offspring participants that were not otherwise enrolled and had at least two biological children participating in Gen III. 103 New Offspring Spouses (47 men and 56 women) participated. The OMNI 2 cohort enrolled additional ethnically diverse participants, including many individuals related to the participants of Omni Cohort 1 and also individuals unrelated to Omni Cohort 1 members for a total of 410 new participants. Design The cardiovascular disease conditions under investigation include coronary heart disease (angina pectoris, myocardial infarction, coronary insufficiency and sudden and non-sudden death), stroke, hypertension, peripheral arterial disease and congestive heart failure. Original cohort: The Framingham Study is a longitudinal investigation of constitutional and environmental factors influencing the development of CVD in men and women. Examination of participants has taken place every two years and the cohort has been followed for morbidity and mortality over that time period. Offspring/Omni1 cohort: By 1975, a sample of 5,124 men and women, consisting of offspring of the original Framingham cohort (and spouses of the offspring) had participated in the study. Additional studies of these subjects have continued under research contracts. Third Generation/Omni2/New Offspring Cohort: The children of Offspring Cohort participants were initially identified who would be 20 years of age or older by the end of the enrollment period. A higher priority for recruitment was assigned to individuals who belonged to large extended families, in order to complement phenotypic and genotypic information already obtained from prior generations. The baseline examination was begun in 2002 and completed in 2005.

  Study phs003594

• The Two Sister Study: A Family-Based Study of Genes and Environment in Young-Onset Breast Cancer

  To study environmental and genetic causes of young onset breast cancer, we recruited women who had been young when recently diagnosed (under age 50 and within 4 years of enrollment), and had been identified as potentially eligible by a sister who was already participating in the ongoing Sister Study. The unaffected sister had already provided consent, questionnaire-based information and DNA (blood-based) when she enrolled in the Sister Study. Her case sister then provided comparable questionnaire-based information and DNA via a mail-back saliva collection kit. To enable family-based analyses, parents were also asked to (only) provide consent and a saliva sample. Because the cases were young-onset, most parents were alive, but unavailability of the parents was not a basis for exclusion. The study was funded in part by Susan G. Komen for the Cure.

  Study phs000678

• Genomic Analysis of Mycosis Fungoides and Sézary Syndrome Identifies Recurrent Alterations in TNFR2

  Mycosis Fungoides (MF) and S&#233;zary Syndrome (Sz) comprise the majority of Cutaneous T-Cell Lymphoma (CTCL) cases and are characterized by clinical heterogeneity. This array of symptoms includes skin patches, plaques and tumors as well as blood involvement and erythroderma. Because the genetic basis of CTCL is still poorly understood, we performed whole-exome sequencing on 11 MF/Sz samples and their matched, normal control DNA. Upon analyzing this data, we distilled a list of an additional 494 genes to be sequenced at depth. The majority of these 494 genes were sequenced in the exons alone, however, for a small subset of these genes we sequenced the entire genomic locus in search of structural variation events. This 494 gene targeted resequencing effort was performed upon 72 patients with MF/Sz and their matched, normal control DNA. An additional 5 MF/Sz and matched, normal DNA samples underwent whole genome amplification (WGA) prior to library preparation, which appears to have introduced mutations into these samples, however we also include them here. We additionally include 10 MF/Sz samples without a matched, normal control samples, 1 of which underwent WGA. In addition to primary disease samples, we also performed targeted resequencing on 4 CTCL cell lines (HH, MyLa, SeAx and Hut78) as well as on H9 cells (a subclone of Hut78 cells) and Jurkat cells, a T-ALL derived cell line that was used as an experimental system for our work. In sum, this data deposition includes exome and/or targeted resequencing from 92 individuals with 192 samples submitted.

  Study phs000913

• RNA-sequencing from duodenal bipsies of Celiac disease patients

  Samples, in a form of PAXgene fixed and paraffin-embedded biopsies, were collected from the multi-site, double-blind, randomized, placebo-controlled trial, aimed at dose-finding and assessing the efficacy and tolerability of a 6-week treatment with ZED1227 capsules vs. placebo in subjects with well-controlled celiac disease undergoing gluten challenge. Total RNA was extracted from the PaxFPE biopsy specimens (n = 116) using additional cuttings from the samples on which histomorphometry was previously assessed. For the extraction, an RNeasy Kit (Qiagen, Hilden, Germany) was used according to the manufacturer’s instructions. Library preparation and next-generation sequencing (NGS) were performed by the Qiagen NGS Service. A total of 10 ng of purified RNA was converted into cDNA NGS libraries. Library preparation was quality controlled using capillary electrophoresis. Based on the quality of the inserts and the concentration measurements, the libraries were pooled in equimolar ratios and then sequenced on a NextSeq (Illumina Inc., San Diego, USA) sequencing instrument according to the manufacturer’s instructions, with 100 bp read length for read 1 and 27bp for read 2. The raw data were de-multiplexed, and FASTQ files for each sample were generated using bcl2fastq2 software (Illumina Inc., San Diego, USA).

  Dataset EGAD50000000491

• PETAL trial Whole Exome Sequencing (WES) from Normal Samples

  Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 55 Normal Samples. WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

  Dataset EGAD50000002507

• PETAL trial Whole Exome Sequencing (WES) from Tumor Samples

  Associated with Molecular profiling of DLBCL patients treated in the PETAL trial. Whole Exome Sequencing (WES) of 224 Tumor Samples. WES was used for Molecular Profiling by simultaneous screening of mutations. Data is Complementary to sWGS.

  Dataset EGAD50000001172

• Whole Exome sequencing of colorectal cancer patients (SG-BULK)

  The study was approved by the institutional review board of Singhealth (2018-2795). Ten 5-µm tissue sections were cut using standard microtomy techniques. Each collected cell population was then extracted using the allprep kit. Extracted material was then quantified using a Qubit fluorometer. DNA-seq libraries were captured to exome regions using xGen Exome Research Panel v1.0 (IDT), and libraries were prepared using the KAPA Hyper prep kit. DNA libraries were sequenced to a target depth of ×200 for tumor sample, ×100 for normal samples on the Illumina HiSeq platform.

  Study EGAS00001006006

• NHLBI TOPMed: Genetics of Cardiometabolic Health in the Amish

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

  Study phs000956

• The role of MALT1 in driving IBN resistance in MCL

  The bulk RNA-seq dataset was generated for the cell lines below and used for two major purposes: 1. DEG analysis and GSEA analysis comparing IBN-R and IBN-S cells 2. DEG analysis and GSEA analysis comparing MCL cells with/without MI-2 treatment.

  Study EGAS00001006832

• Next Generation Mendelian Genetics: Malignant Hyperthermia

  Malignant hyperthermia (MH) is a genetic disorder that causes a profound metabolic derangement following exposure to certain anesthetics. While approximately half of all cases are associated with ryanodine receptor-1 gene (RYR1) mutations, many cases have an unknown genetic cause. We sought to identify rare variants in novel MH candidate genes by sequencing the protein-coding regions of the genomes of individuals whose disease was either ruled in or out by the gold-standard diagnostic test. We also carefully selected individuals from well-characterized families to use gene-sharing information and maximize efficiency in the study design. Exome sequencing has helped identify the causes of over a dozen Mendelian disorders, has high power at low sample sizes, and is cost-efficient compared to whole-genome sequencing.

  Study phs000405

• The Haemgen RBC study

  Anaemia is a major determinant of global ill-health. To refine our understanding of the genetic factors influencing red blood cell formation and function, we carried out a meta-analysis of genome-wide association studies (GWAS) for six red blood cell traits: haemoglobin (HB), mean cell haemoglobin (MCH), mean cell haemoglobin concentration (MCHC), mean cell volume (MCV), packed cell volume (PCV) and red blood cell count (RBC). We provide genome-wide association results for 62,553 people of European ancestry using up to 2,644,161 autosomal SNPs. Participants with extreme measurements (>+/-3SD from mean) were excluded on a per phenotype basis. Imputation was done using haplotypes from HapMap Phase 2. SNP associations with each phenotype were tested by linear regression using an additive genetic model. Associations were tested separately in each cohort, with principal components and other study specific factors as covariates to account of population substructure. We then carried out meta-analysis of results from the individual cohorts using z-scores weighted by square root of sample size. SNPs with MAF<1% (weighted average across cohorts) were removed, as were SNPs with weight <50% of phenotype sample size. Anaemia is a major determinant of global ill-health. To refine our understanding of the genetic factors influencing red blood cell formation and function, we carried out a meta-analysis of genome-wide association studies (GWAS) for six red blood cell traits: haemoglobin (HB), mean cell haemoglobin (MCH), mean cell haemoglobin concentration (MCHC), mean cell volume (MCV), packed cell volume (PCV) and red blood cell count (RBC). We provide genome-wide association results for 62,553 people of European ancestry using up to 2,644,161 autosomal SNPs. Participants with extreme measurements (>+/-3SD from mean) were excluded on a per phenotype basis. Imputation was done using haplotypes from HapMap Phase 2. SNP associations with each phenotype were tested by linear regression using an additive genetic model. Associations were tested separately in each cohort, with principal components and other study specific factors as covariates to account of population substructure. We then carried out meta-analysis of results from the individual cohorts using z-scores weighted by square root of sample size. SNPs with MAF<1% (weighted average across cohorts) were removed, as were SNPs with weight <50% of phenotype sample size.

  Study EGAS00000000132

• Shanghai Breast Cancer Genetics Study (SBCGS)

  The Shanghai Breast Cancer Genetics Study (SBCGS) includes data from four population-based studies conducted among Chinese women in urban Shanghai: the Shanghai Breast Cancer Study (SBCS), the Shanghai Breast Cancer Survival Study (SBCSS), the Shanghai Women&#39;s Health Study (SWHS), and the Shanghai Endometrial Cancer Study (SECS, contributing controls only). Shanghai Breast Cancer Study (SBCS): The SBCS is a population-based, case-control study conducted in urban Shanghai. Subject recruitment in the initial phase of the SBCS (SBCS-I) was conducted between August 1996 and March 1998. The second phase (SBCS-II) of recruitment occurred between April 2002 and February 2005. Breast cancer cases were identified through the population-based Shanghai Cancer Registry and supplemented by a rapid case-ascertainment system. Controls were randomly selected using the Shanghai Resident Registry. Approximately 3500 cases and 3500 controls were recruited in the study. Shanghai Breast Cancer Survival Study (SBCSS) and Shanghai Endometrial Cancer Study (SECS): The SBCSS also used the population-based Shanghai Cancer Registry to identify newly diagnosed breast cancer cases. A total of 5,046 breast cancer patients were recruited. In-person interviews were conducted to collect information on known breast cancer risk factors and anthropometrics by using protocols and questionnaires similar to those used in the SBCS. For genetic studies, controls for the SBCSS cases came from the SECS, which recruited healthy women between January 1997 and December 2003. With the exception of a few questions related specifically to breast or endometrial cancer risk, the questionnaires used in the SECS and the SBCS were very similar. Shanghai Women&#39;s Health Study (SWHS): The SWHS is a population-based prospective cohort study of approximately 75,000 adult women who were recruited between 1997 and 2000. The cohort has been followed by a combination of record linkage and active follow-ups. Breast cancer patients identified in the SWHS and non-cases were included in the current study.

  Study phs001088

• Shanghai Breast Cancer Genetics Study (SBCGS)

  The Shanghai Breast Cancer Genetics Study (SBCGS) includes data from four population-based studies conducted among Chinese women in urban Shanghai: the Shanghai Breast Cancer Study (SBCS), the Shanghai Breast Cancer Survival Study (SBCSS), the Shanghai Women&#39;s Health Study (SWHS), and the Shanghai Endometrial Cancer Study (SECS, contributing controls only). Shanghai Breast Cancer Study (SBCS): The SBCS is a population-based, case-control study conducted in urban Shanghai. Subject recruitment in the initial phase of the SBCS (SBCS-I) was conducted between August 1996 and March 1998. The second phase (SBCS-II) of recruitment occurred between April 2002 and February 2005. Breast cancer cases were identified through the population-based Shanghai Cancer Registry and supplemented by a rapid case-ascertainment system. Controls were randomly selected using the Shanghai Resident Registry. Approximately 3500 cases and 3500 controls were recruited in the study. Shanghai Breast Cancer Survival Study (SBCSS) and Shanghai Endometrial Cancer Study (SECS): The SBCSS also used the population-based Shanghai Cancer Registry to identify newly diagnosed breast cancer cases. A total of 5,046 breast cancer patients were recruited. In-person interviews were conducted to collect information on known breast cancer risk factors and anthropometrics by using a protocol and questionnaire similar to those used in the SBCS. For genetic studies, controls for the SBCSS cases came from the SECS, which recruited healthy women between January 1997 and December 2003. With the exception of a few questions related specifically to breast or endometrial cancer risk, the questionnaires used in the SECS and the SBCS were very similar. Shanghai Women&#39;s Health Study (SWHS): The SWHS is a population-based prospective cohort study of approximately 75,000 adult women who were recruited between 1997 and 2000. The cohort has been followed by a combination of record linkage and active follow-ups. Breast cancer patients identified in the SWHS and non-cases were included in the current study.

  Study phs000799

• Genomic DNA analysis for malignant mesothelioma from the patients of Japan and USA.

  Malignant mesotheliomas (MMs) are highly aggressive adult malignancies and exposure to asbestos is the major factor involved in MM pathogenesis. It is desirable for a better understanding of the molecular pathogenesis of MM will lead to more specific and effective targeted therapies. In addition it is reported that germline mutation in a specific gene (ex. BAP1) associates familial MMs, and new candidate markers to determine a subject?s predisposition to MM and for early detection need to be identified. Analysis of genomic DNA from MM tumors and reference peripheral blood from Japan and USA are ongoing to find the common genomic characters beyond race.

  Study JGAS000108

• Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial

  Summary of the Design and Aims: The Coagulation and Fibrinolysis in a Pediatric Insulin Titration Trial (CAF-PINT) is an ancillary study to the HALF PINT (NCT01565941) randomized, controlled trial that was originally designed to study changes in inflammatory and thrombosis pathways in the setting of an interventional trial. The parent HALF PINT study was designed to study the impact of tight glycemic control (TGC) using an explicit insulin titration algorithm to safely achieve a normal glucose in target range of 80-110 mg/dL versus 150-180mg/dL on clinical outcomes among critically ill hyperglycemic children with Heart and Lung Failure. The CAF PINT study collected blood samples pre randomization and at 2 and 4 days after randomization. Blood samples collected in EDTA tubes were centrifuged at local sites to separate the plasma from cell pellets and frozen prior to shipment. In addition, 0.5 mL of whole blood collected in PAXgene tubes modified for use in pediatrics frozen 24 hours after collection prior to shipment.Population Information: Setting: Twenty-one academic children's hospitals (HALF-PINT) and 1 academic children's hospital (IIT-SBPP). Participants: Critically ill hyperglycemic children requiring mechanical ventilation/vasoactive support (n=293).Interventions and Exposures: Patients in HALF PINT were randomized to achieve a low target glucose (80-110 mg/dL) vs. a higher target (150-180 mg/dL). The primary trial was stopped early due to low likelihood of achieving a statistically significant difference in the primary outcomes. Molecular Technologies Employed: Plasma biomarkers were assayed on thawed plasma using a Luminex panel. RNA was extracted from PAXgene Blood RNA Kits modified for pediatric use. Extracted RNA was sequenced with the Novaseq S4 system (Illumina) to generate 2 x 150 base paired end reads to a target depth of 50 million read-pairs per sample.Principal Findings of the Study: We tested for heterogeneity of treatment effects according to baseline blood inflammatory proteins using logistic regression with individual biomarkers as interaction terms and Cox regression analysis using biomarker-derived latent classes. Children with higher inflammatory proteins including TNFR-1, IL-6, IL-8, and IL-10 had lower mortality when treated with insulin to a target glucose of 80-110 mg/dL as compared to 150-180 mg/dL (interaction p&lt;0.05). Causal forest estimates ranged from a 40% mortality reduction to a 15% mortality increase with TGC, depending on each patient&#8217;s individual biomarker profile. Latent class categorization strongly interacted with TGC with respect to mortality (Cox regression interaction p=0.005). Specifically, patients with higher inflammation benefited from TGC (6% mortality with TGC vs. 48% mortality, p=0.004) whereas hypoinflamed patients showed a trend towards harm (14% mortality with TGC vs. 7% mortality, p=0.055).Data available through dbGaP: Transcriptomic (Gene Counts) and phenotype data

  Study phs003016

• Targeted-capture sequencing (bam files) of 81 samples of myxofibrosarcoma and 44 matched pairs

  Myxofibrosarcoma (MFS) is a rare subtype of sarcomas in the elderly, whose genetic basis is poorly understood. To elucidate it, the Targeted-capture sequencing was performed.

  Dataset EGAD00001007826

• Genomics Analysis Reveals Molecular Patterns of Tumorigenesis in HPV-Associated and HPV-Independent Sinonasal Squamous Cell Carcinoma

  The goal of this study was to identify molecular mechanisms of tumorigenesis in HPV-associated and HPV-independent sinonasal carcinoma using high-throughput sequencing approaches. Whole genome sequencing was performed for HPV-associated samples and whole exome sequencing for HPV-independent samples. Ultimately, we identified distinct molecular patterns of tumorigenesis between HPV-associated and HPV-independent disease. Data from patients for which informed consent allowed public sharing are included here.

  Study phs003591

• 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 (&#946;=0.95, SE=0.16, pTRPS1 and rs4147536 at ADH1B) was associated with 40.62 mg/dL higher total cholesterol (&#946;=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 (&#946;= -0.87, SE =0.14, pThe phenotypic and genotypic data will be made available on the dbGaP portal for access.

  Study phs003469

• International Genetics of Parkinson Disease Progression (IGPP) Consortium: EPIPARK and HBS2 Cohorts

  EPIPARK and HBS2 cohorts were analyzed as part of the International Genetics of Parkinson Disease Progression (IGPP) Consortium. EPIPARK is a population-based cohort to study non-motor symptoms in parkinsonism in the city of L&#252;beck, Germany led by Drs. Meike Kasten and Christine Klein. HBS2 is a recently enrolled subset of participants in the Harvard Biomarkers Study led by Dr. Clemens Scherzer (www.bwhparkinsoncenter.org/biobank) of 89 participants with a diagnosis of Parkinson Disease (PD). Genotyping with Illumina Infinium Multi-Ethnic Genotyping Arrays (MEGA chip) was performed by Dr. Scherzer, Harvard Medical School and Brigham and Women&#8217;s Hospital. 179 participants with a diagnosis of PD from EPIPARK and 89 participants with a diagnosis of PD from HBS2 met Q/C criteria were analyzed.

  Study phs002328

• Integrated clinical, whole genome, and transcriptome analysis of multisampled lethal metastatic prostate cancer

  We report the first combined analysis of whole genome sequence, detailed clinical history, and transcriptome sequence of multiple prostate cancer metastases in a single patient (A21). Whole genome and transcriptome sequence was obtained from 9 anatomically separate metastases, and targeted DNA sequencing was performed in cancerous and noncancerous foci within the primary tumor specimen removed 5 years prior to death. Transcriptome analysis revealed increased expression of AR-regulated genes in liver metastases that harbored an AR p.L702H mutation, suggesting a dominant effect by the mutation despite being present in only 1 of an estimated 16 copies per cell. The metastases harbored several alterations to the PI3K/AKT pathway, including a clonal truncal mutation in PIK3CG and present in all metastatic sites studied. The list of truncal genomic alterations shared by all metastases included homozygous deletion of TP53, hemizygous deletion of RB1 and CHD1, and amplification of FGFR1. If the patient were treated today given this knowledge, use of second-generation androgen-directed therapies, cessation of glucocorticoid administration, and therapeutic inhibition of the PI3K/AKT pathway or FGFR1 receptor could provide personalized benefit. Three previously unreported truncal clonal missense mutations (ABCC4 p.R891L, ALDH9A1 p.W89R, and ASNA1 p.P75R) were expressed at the RNA level and assessed as druggable. The truncal status of mutations is critical for actionability, and can only be determined through analysis of multiple sites of metastasis. Our findings suggest that a large set of deeply analyzed cases could serve as powerful guide to more effective prostate cancer basic science and personalized cancer medicine clinical trials.

  Study EGAS00001001659

• Open_Targets_020_Epigenomes_of_Cell_Lines

  There is currently a drive to establish cell based assay systems of greater human biological and disease relevance through the use of well characterised transformed cell lines, primary cells and complex cellular models (e.g. co-culture, 3D models). However, although the field is gaining valuable experience in running more non-standard &amp; complex cell assays for target validation and compound pharmacology studies, there is the lack of a systematic approach to determine if this expansion in cell assay models is reflected in increased human biological and disease relevance. The increasing wealth of publically available transcriptomic, and epigenome (ENCODE and Epigenome Roadmap) data represents an ideal reference mechanism for determining the relationship between cell types used for target &amp; compound studies to primary human cells and tissues from both healthy volunteers &amp; patients. The CTTV020 epigenomes of cell line project aims to generate epigenetic and transcriptomic profiles of cell lines and compare these with existing and newly generated reference data sets from human tissue and cell types. The aim is to identify assay systems which will provide greater confidence in translating target biology and compound pharmacology to patients. Multiple cell types commonly used within research have been grouped according to biology. Examples include erythroid, lung epithelial, hepatocyte cell types and immortalised models of monocyte / macrophage biology. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003138

• Alveolar Rhabdomyosarcoma case report

  Rhabdomyosarcoma (RMS) is a mesenchymal malignancy phenocopying muscle and is among the leading causes of death from childhood cancer. Metastatic alveolar rhabdomyosarcoma is the most aggressive subtype with an 8% five-year disease-free survival rate when a chromosomal fusion is present, and 40% five-year disease-free survival rate when negative for a fusion event. The underlying biology of PAX-fusion negative alveolar rhabdomyosarcoma remains largely unexplored and is exceedingly rare in Li-Fraumeni syndrome patients. Here, we present the case of an 11-year old male with fusion-negative alveolar rhabdomyosarcoma studied at end of life with a comprehensive functional genomics characterization, resulting in identification of potential therapeutic targets for broader investigation.

  Study EGAS00001004828

• National Institute of Environmental Health (NIEHS) Sciences Study of Somatic Mutation Load in Clones of Single Human Cells

  Accumulation of genetic changes with time and proliferation of cells is inevitable. We report here the genome-wide magnitude and spectra of mutations accrued in skin fibroblasts over the lifetime of healthy humans. We found that every cell contains at least one somatic chromosomal rearrangement and 600 - 13,000 base substitutions, similar to the median mutation load in human cancers. The mutation spectra and correlation of changes with epigenomic features also resemble many human cancers. Interestingly, the magnitude of ultraviolet light-characteristic mutations, representative of environmental mutagenesis, in sun-exposed skin was comparable to the number of mutations attributed to endogenous DNA damage estimated in unexposed cells. Our methodology allows delineating the precise contributions of environmental and endogenous factors to the accrual of genetic changes in the human body. This is fundamental to understanding the etiology, and improving the prognosis and prevention of cancers and other genetic diseases.

  Study phs001182

• Whole-genome sequencing of normal Singaporean volunteers

  Sleep is associated with various health outcomes. Despite their growing adoption, the potential for consumer wearables to contribute sleep metrics to sleep-related biomedical research remains largely uncharacterized. Here we analyzed sleep tracking data, along with questionnaire responses and multi-modal phenotypic data generated from 482 normal volunteers. First, we compared wearable-derived and self-reported sleep metrics, particularly total sleep time (TST) and sleep efficiency (SE). We then identified demographic, socioeconomic and lifestyle factors associated with wearable-derived TST. Among others, male gender (β = -15.539, 95% confidence interval [CI] = -26.245 - -4.832, p = 0.005), older age (β = -0.493, CI = -0.941 - -0.044, p = 0.032) and manual labor (β = -26.856, CI = -49.715 - -3.997, p = 0.022) were associated with reduced TST, whereas alcohol consumption (β = 19.247, CI = 8.008 - 30.486, p = 8.54x10-04) was associated with increased TST. Multi-modal phenotypic data analysis showed that wearable-derived TST and SE were associated with various cardiovascular disease risk markers such as body mass index (β = -0.006, CI = -0.00 - -0.000, p = 0.040) and waist circumference (β = 0.001, CI = -0.015-0.017, p = 0.893), whereas self-reported measures were not. We then showed that insufficient sleep was associated with premature telomere attrition, using telomere length estimated using whole-genome sequencing (β = 1.275, CI = 0.187 - 2.363, p = 0.023) and quantitative PCR (β = 0.001, CI = 8.318x10-05 - 0.001, p = 0.028). Our study highlights the potential for sleep metrics from consumer wearables to provide novel insights into data generated from population cohort studies.

  Study EGAS00001004007

• Contribution of specific cell types to the development of Barrett’s esophagus and carcinoma via germline genetic risk

  This study was designed to elucidate how individual cell types in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) contribute to disease development via germline genetic risk. We performed single cell RNA-sequencing (scRNA-seq) of BE, EAC and paired normal esophagus and gastric fundus tissue samples. After analyzing individual cell types, we integrated the scRNA-seq data and data of a genome-wide association study (GWAS) on BE/EAC to determine cell type-specific genetic risk. Raw data from the RNA-sequencing is provided here.

  Study EGAS50000000530

• Natural Killer Cell Therapies for Hematologic Malignancies

  The "Natural Killer Cell Therapies for Hematologic Malignancies" study is an umbrella repository for data pertaining to multiple related clinical trials that aim to assess NK cell therapies as part of treatment strategies for a range of hematologic malignancies. Here, data from two trials, NCT03068819 and NCT02782546, are presented.Cytokine Induced Memory-like NK Cell Adoptive Therapy for Relapsed AML after Allogeneic Hematopoietic Cell Transplant in Children and Adults (NCT03068819)Pediatric and young adult (YA) patients with acute myeloid leukemia (AML) who relapse after allogeneic hematopoietic cell transplantation (HCT) have extremely poor prognosis. Standard salvage chemotherapy and donor lymphocyte infusions (DLI) have little curative potential. Previous studies showed that natural killer (NK) cells can be stimulated ex vivo with interleukin-12 (IL-12), IL-15, and IL-18 to generate memory-like (ML) NK cells with enhanced anti-leukemia responses. We treated nine pediatric/YA patients with post-HCT relapsed AML with donor ML NK cells on a phase I trial. Patients received fludarabine, cytarabine, and filgrastim followed two weeks later by infusion of DLI and ML NK cells from the original HCT donor. ML NK cells were successfully generated from haploidentical, matched-related and matched-unrelated donors. Following infusion, donor-derived ML NK cells expanded and maintained ML multidimensional mass cytometry phenotype for over 3 months. Furthermore, ML NK cells exhibited persistent functional responses as evidenced by leukemia-triggered IFN-gamma production. Following DLI and ML NK cell adoptive transfer, 4 of 8 evaluable patients achieved complete remission at day 28. Two patients maintained a durable remission for over 3 months with one patient in remission for greater than two years. No significant toxicity was experienced. This study demonstrates that in a compatible immune environment post-HCT, donor ML NK cells robustly expand and persist with potent anti-leukemic activity in the absence of exogenous cytokines. ML NK cells in combination with DLI present a novel immunotherapy platform for AML that has relapsed after allogeneic HCT. This trial was registered at https://www.clinicaltrials.gov/study/NCT03068819.A Phase II Study of Cytokine Induced Memory-like NK Cell Adoptive Therapy after Haploidentical Donor Hematopoietic Cell Transplantation (NCT02782546)Natural killer (NK) cells are innate lymphoid cells that eliminate cancer cells, produce cytokines, and are being investigated as a nascent cellular immunotherapy. Impaired NK cell function, expansion, and persistence remain key challenges for optimal clinical translation. One promising strategy to overcome these challenges is cytokine-induced memory-like (ML) differentiation, whereby NK cells acquire enhanced anti-tumor function following stimulation with IL-12, IL-15, and IL-18. Here, reduced-intensity conditioning (RIC) for HLA-haploidentical hematopoietic cell transplantation (HCT) was augmented with same-donor ML NK cells on Day 7 and 3 weeks of N-803 (IL-15 superagonist) to treat patients with relapsed/refractory acute myeloid leukemia (AML) in the clinical trial (NCT02782546). In 15 patients, donor ML NK cells were well-tolerated and 87% of patients achieved a composite complete response at Day 28, which corresponded with clearing high-risk mutations, including TP53 variants. NK cells were the major blood lymphocytes for two months post-HCT with prolific expansion (1104-fold) over 1-2 weeks. Multidimensional mass cytometry and CITE-seq identified donor ML NK cells as distinct from conventional NK cells and persisting for over two months. ML NK cells expressed CD16, CD57, and high granzyme B and perforin, along with a unique transcription factor profile. ML NK cells differentiated in patients had enhanced ex vivo function compared to conventional NK cells from both patient and healthy donors. Overall, same-donor ML NK cell therapy with 3 weeks of N-803 support safely augmented RIC haplo-HCT for AML, with ML NK cells demonstrating enhanced in vivo persistence and functionality, overcoming barriers in the field.

  Study phs002681

• Tissue-specificity and co-expression analyses identify human long non-coding RNAs related to inherited retinal disease genes

  The role of long non-coding RNAs (lncRNAs) in biological and pathological processes is still poorly understood. In this study, we aimed to identify lncRNAs that potentially contribute to retinal biology and Inherited Retinal Disease (IRD) by using two complementary strategies, tissue-specificity and location in topologically associating domains (TADs) containing IRD genes on one hand, and co-expression analyses on the other, applied to human retinal omics datasets. This combined approach resulted in the selection of 11 Retina Enriched IRD-gene Related (REIR) lncRNAs, one of which is novel. In-depth in silico and experimental characterization of REIRs identified novel REIR isoforms and confirmed retina-predominant (often photoreceptor-specific) expression as well as predicted functional association with visual function. Long-read direct cDNA sequencing (ONT) of three post-mortem human retina samples was used to delineate the novel REIR isoforms.

  Study EGAS50000000963

• Idiopathic Multicentric Castleman Disease Whole Genome Sequencing Project

  Multicentric Castleman disease (MCD) is a rare lymphoproliferative disorder driven by excessive production of inflammatory cytokines. Patients can exhibit a wide range of clinical features from mild flu-like symptoms to multiple organ failure and death. Human herpesvirus-8 (HHV-8) is a well-established cause of MCD in individuals who are immunosuppressed due to human immunodeficiency virus infection or other causes. On the other hand, it is not known what causes MCD in otherwise healthy individuals with no evidence of exposure to HHV-8 (idiopathic MCD or iMCD). Although iMCD is most common in 40-60 years old adults, it affects people of all ages and early-onset (childhood or young adulthood) cases have been reported. Germline mutations may underlie iMCD in such cases. Patients with early-onset iMCD and their family members were enrolled in the study. To identify germline mutations that may underlie iMCD, whole-genome sequencing was performed in patients and their biological parents from whom DNA samples were available.

  Study phs001706

• Histological Transformation and Progression in Follicular Lymphoma: a Clonal Evolution Study

  Background: Follicular lymphoma (FL) is an indolent, yet incurable B-cell malignancy. A subset of patients experience increased mortality rate driven by two distinct clinical end points: histological transformation and early progression after immuno-chemotherapy. The nature of tumor clonal dynamics leading to these clinical endpoints is poorly understood and previously determined genetic alterations do not explain the majority of transformed cases or accurately predict early progressive disease. We contend that detailed knowledge of the expansion patterns of specific cell populations plus their associated mutations would provide insight into therapeutic strategies and disease biology over the timecourse of FL clinical histories. Methods and Findings: Using a combination of whole genome sequencing, targeted deep sequencing and digital droplet PCR on matched diagnostic and relapse specimens, we deciphered the constituent clonal populations in n=15 transformation patients and n=6 progressors, and measured their change in abundance over time. We observed widely divergent patterns of clonal dynamics in transformed cases relative to progressed cases. Transformation specimens were generally composed of clones that were rare or absent in diagnostic specimens, consistent with dramatic clonal expansions that came to dominate the transformation specimen. This pattern was independent of time to transformation and treatment modality. By contrast, progression specimens were composed of clones that were already present in the diagnostic specimens and exhibited only moderate clonal dynamics, even in the presence of immuno-chemotherapy. Analysis of somatic mutations impacting 94 genes was undertaken in a validation cohort consisting of 395 samples from 277 patients in order to decipher disrupted biology in the two clinical endpoints. We found 12 genes were more commonly mutated in transformed samples than in preceding FL, including TP53, B2M, CCND3, GNA13, S1PR2 and P2RY8. Moreover, 10 genes were more commonly mutated in diagnostic specimens of early progressors including TP53, BTG1, MKI67 and XBP1. Conclusions: Our results illuminate contrasting modes of evolution shaping the clinical histories of transformation and progression. They have implication for interpretation of evolutionary dynamics in the context of treatment-induced selective pressures, and indicate that transformation and progression will require different clinical management strategies.

  Study EGAS00001001709