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• Consanguinity and rare mutations outside of MCCC genes underlie non-specific phenotypes of MCC Deficiency

  3-Methylcrotonyl-CoA Carboxylase Deficiency (MCCD) is an autosomal recessive disorder of leucine catabolism, which has a highly variable clinical phenotype, ranging from acute metabolic acidosis to non-specific symptoms such as developmental delay, failure to thrive, hemiparesis, muscular hypotonia, and multiple sclerosis. Implementation of newborn screening for MCCD has resulted in broadening the range of phenotypic expression to include asymptomatic adults. The purpose of this study was to identify factors underlying the varying phenotypes of MCCD. We performed exome sequencing on DNA from 107 healthy controls and 33 cases. We examined these data for associations between either MCC mutational status, genetic ancestry or consanguinity and the absence or presence/specificity of clinical symptoms in MCCD cases. We determined that individuals with non-specific clinical phenotypes are highly inbred compared to cases that are asymptomatic and healthy controls. For five of these individuals we discovered a homozygous damaging mutation in a disease gene that is likely to underlie their non-specific clinical phenotypes previously attributed to MCCD.

  Study phs000776

• Plasma cell‐Free transcriptome profiling in chronic liver disease

  Chronic liver disease (CLD) encompasses a wide range of hepatic disorders that progressively compromise liver function. In order to support the development of non-invasive diagnostic tools and improve patient stratification, we generated a high-throughput extracellular RNA sequencing dataset from blood plasma samples collected from patients at various stages of liver disease. Samples were obtained from two independent cohorts of 112 (cohort 1) and 489 (cohort 2) patients using standardized collection and processing protocols, and profiled using total RNA sequencing (SMARTer Stranded Total RNA-Seq Kit v3 - Pico Input Mammalian), resulting in 112 and 820 extracellular transcriptomic profiles for cohort 1 and 2, respectively. This dataset is provided with full documentation of the preprocessing analysis pipeline and accompanying metadata, enabling its use as an independent validation cohort for biomarker discovery and as a complementary resource for integrative multi-omics studies, even in cases with incomplete data modalities. The publicly available resource is intended to facilitate reproducibility and foster further research in the field of liver disease diagnostics

  Study EGAS50000000545

• Genes-Environments and Admixture in Latino Asthmatics (GALA II) Study

  A case-control pharmacogenetic study of bronchodilator drug response among racially admixed Latino children with asthma. Each participant had two spirometry measurements using the KoKo PFT System. With the first spirometry test, participant was administered with 4 puffs of HFA Albuterol. The second albuterol measurement was based on age, for participants under 16 years of age, additional 2 puffs were administered and for those over 16 years of age, additional 4 puffs were administered. The overall goal is to identify genetic factors which are predictive of drug response in children with asthma. The principal tools include a questionnaire and biological specimen collection. Participants are 8-21 years old at time of recruitment. Children with asthma have physician-diagnosed asthma, symptoms and medications. The GALAII 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 phs001180 GALAII Study. phs001274phs001274 GALAII GWAS

  Study phs001180

• Network-based systems pharmacology identifies heterogeneity in LCK and BCL2 signaling and differential vulnerability of T-cell acute lymphoblastic leukemia to targeted therapy

  T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy, and novel therapeutics are much needed. Profiling patient leukemia’ drug sensitivities ex vivo, we discovered striking inter-patient variability in T-ALL response to a panel of targeted agents. Applying network-based systems pharmacology analyses, by integrating ex vivo pharmacotyping, bulk and single-cell RNA-seq, genomics, phospho-proteomics, and genome-wide CRISPR screening data, to examine signal circuitry, we identified the pharmacogenomic basis of T-ALL drug response and revealed a therapeutic vulnerability that is directly related to the developmental stage of leukemia cells. In conclusion, our results indicate that heterogeneity in the differentiation of T-ALL drives activation of key signaling pathways in this leukemia, providing unique opportunities for targeted therapy.

  Study EGAS00001004700

• The EGA joins EUCAIM, the European project powering AI and imaging in cancer research

  EUCAIM (EUropean Federation for CAncer IMages) is the cornerstone of the European Cancer Imaging Initiative, one of the flagships of the Europe’s Beating Cancer Plan (EBCP). The European Genome-Phenome Archive (EGA), as member of the EUCAIM consortium, attended the kick-off meeting organized this week in Brussels for the launch of the Initiative. The EGA will contribute to the project with the experience gained in the deployment of our federated network, the Federated EGA (FEGA), and the experience gained as partners of EuCanImage (AI4HI initiative) contributing to the definition of common data models, ontologies and data standards. The ultimate goal of the project is to unlock the power of imaging and Artificial Intelligence for the benefit of cancer patients, clinicians and researchers. The consortium will deploy a pan-European digital federated infrastructure hosting cancer-related images, and associated pathology, molecular and laboratory data from Real-World. This endeavour will provide a comprehensive dashboard for imaging data discovery, federated search, metadata harvesting, annotation and distributed data processing. EUCAIM joins 76 partners, gathering the experience and previous effort made by the different repositories of the AI4HI initiative, European Research Infrastructures and national/regional repositories. Find out more information about the EUCAIM launch here

  Blog the-ega-joins-eucaim

• This DAC is to control access to data contained within dataset EGAS00001001147, for Myeloma XI clinical trial patients.

  Dac EGAC00001000307

• Structurally Complex Osteosarcoma Genomes Exhibit Limited Heterogeneity within Individual Tumors and across Evolutionary Time

  A key characteristic of osteosarcoma is extensive and complex genomic rearrangements. However, published models explaining how these genomic rearrangements occur disagree about if these rearrangements occur early in tumor progression and then are stable afterwards, or if there is ongoing genomic instability. Previous studies have employed bulk sequencing technologies to characterize genomic alterations. A limitation of this approach is that it averages all changes within the bulk sample, essentially masking intra-sample heterogeneity and making evaluation of ongoing genomic instability difficult. To overcome this limitation and compliment previous work, we utilized single-cell whole genome sequencing to quantify somatic copy number alterations (SCNA). By interrogating individual cells within a sample, we were able to examine intra-sample heterogeneity. We found that the SCNA patterns between cells within a single sample were remarkably consistent, which supports the concept that the genomes of osteosarcoma tumors are relatively stable after early genome fragmentation events.

  Study phs003209

• H3Africa - An integrated approach to the identification of genetic determinants of susceptibility to trypanosomiasis

  The over-arching aim of this network is to improve the health of people living in some of the poorest countries in the world that carry a disproportionate burden of infectious diseases. Despite their importance, the study of many tropical diseases has lagged behind that of diseases of developed countries. This network will redress the balance by performing high quality research into two neglected tropical diseases, human African Trypanosomiasis (HAT) and schistosomiasis. Our aim is to investigate the genetic determinants of the human reservoirs of HAT and schistosomiasis, filling an important knowledge gap, while extending and strengthening the underpinning infrastructure to deliver these scientific objectives in particular by developing the next generation of African geneticists.

  Study EGAS00001007173

• Comparison Between qPCR and RNA-Seq Reveals Challenges of Quantifying HLA Expression

  Human leukocyte antigen (HLA) class I and HLA class II loci are essential elements of innate and acquired immunity. Their exceptional influence on disease outcome is well documented by GWAS and candidate gene studies. The impact of HLA allelic variation on human disease through allele-specific presentation of antigenic peptides to T cells has been the main focus to determine HLA effects on disease susceptibility/pathogenesis. However, HLA expression levels have also been implicated in disease, adding another dimension to the extreme diversity of HLA that impacts variability in immune responses across individuals. HLA expression levels routinely rely on quantitative PCR (qPCR). An alternative is adoption of high throughput technologies such as RNA-Seq. This provides the opportunity to quantify HLA expression in large datasets, but also allows comparison between RNA-Seq and qPCR. In this study, we analyze expression data for HLA Class I genes for a matched set of individuals (N = 96) by RNA-Seq, qPCR and cell surface expression. Samples were obtained from the Research Donor Program (NCI-Frederick). We observed a moderate correlation between RNA-Seq and qPCR. We suggest technical and biological factors that might contribute to differences in the techniques.

  Study phs003177

• Integrated genomic analysis for HCC

  Liver cancer is a common malignancy and is the third cause of cancer-related death in the world and hepatocellular carcinoma (HCC) is the major type of liver cancer, accounting for ~90% of cases. Only 20 ~ 30% of patients can benefit from combined immunotherapy and targeted therapy due to the high inter-tumor heterogeneity of HCC. This work aims to identify homogeneous and robust molecular subtypes in HCC based on a large, homogenous and well-annotated cohort. We performed whole genome/exome sequencing (WGS/WES) and/or RNA sequencing (RNA-seq) on 529 HCC from 461 patients collected mainly in France. Based on the great consistence between genomic and transcriptomic data, we identified 9 robust HCC subtypes mainly based on driver mutations. And we further characterized HCC subtypes using genomic, transcriptomic and clinicopathological features. Among 9 subtypes, 5 subtypes belonged to chromosome instable tumors, while 3 subtypes belonged to chromosome stable tumors. In addition, our subtypes were associated with prognosis and we also found different distributions of subtypes across various features, such as etiology and gender. Our study provided a robust molecular classification based on a large HCC dataset from Western country, it improves our understanding of the mechanisms of carcinogenesis and will facilitate development of genome-based precision medicine in HCC.

  Study EGAS00001007957