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• Using human induced pluripotent stem cells (iPSC) and iPSC-derived neurons to explore cellular phenotypes associated with schizophrenia.

  Schizophrenia and major mental illness are common devastating conditions. Whilst partially effective treatments are available, none are disease-modifying. Notwithstanding important insights provided by animal models there is a need for novel models of mental illness to develop more effective therapies. A study of sporadic schizophrenia-derived human induced pluripotent stem cells (hiPS) has demonstrated a neuronal phenotype representing a powerful proof of concept of in vitro disease modeling, even for diseases with complex causation such as schizophrenia. These techniques have been used here to examine the behaviour of neural stem cells and neurons derived from fibroblasts from subjects carrying NDE1 copy number variations (CNVs) associated with increased risk of major mental illness. Using hiPS from individuals with and without disease-associated CNVs we have investigated how disease risk is conferred at a cellular and molecular level through detailed comparative studies of neural progenitor proliferation, neuronal morphology, physiology, cytoskeletal organization, synaptic function, glutamate (NMDA) receptor expression and also RNA sequencing and proteomic studies of these patient-derived cells.

  Study EGAS00001002895

• Molecular evolution and clinical trajectories of prostate cancer identifies novel markers for risk stratification

  Prostate cancer is a highly heterogeneous disease that is thought to develop over many years. Identifying the earliest somatic changes can give important insights into the tumour evolution and aid in stratifying high- from low-risk diseases. Here we pursued integrative whole-genome, transcriptome and methylome-based analysis of early-onset prostate cancer patients. Characterisation of genomic alterations across 270 PCa tumours revealed age-related genomic alterations and mutation signatures including BRCAness and APOBEC. We used methylation- and expression-data to identify four molecular subgroups, which included a highly aggressive tumour subgroup that frequently involved recurrent duplications and increased expression of ESRP1. Analysis of 12,000 tissue-microarray tumour samples demonstrated that ESRP1 is a candidate biomarker associated with faster proliferation rate and shorter time to relapse. We combine the patterns of molecular co-occurrence, risk-stratification and subgroup information to deconvolute tumor heterogeneity, which reveal complex but recurrent clinical trajectories of prostate cancer.

  Study EGAS00001002923

• Sequencing cancer mutations in various types of lung cancer using the long-read, portable sequencer

  In this study, we used a long-read and portable sequencer MinION to identify cancer mutations in lung adenocarcinoma cells. We performed cDNA amplicon sequencing for various types of mutations such as point mutations in EGFR and KRAS and oncogenic fusion transcripts in ALK and RET. Using the long reads of MinION, we also conducted mutation phasing of EGFR TKI-sensitive and resistant mutations, which would provide useful information to next thrapeutic approaches for cancers. We applied this method to identify mutation genotypes of eight clinical samples from Japanese lung adenocarcinomas. This method could provide new sequencing-based diagnostic approaches for lung cancers. Additinally we also performed cancer mutation identification of risk-dependent unique samples. Usual interstitial pneumonia (UIP) is a risk factor for lung carcinogenesis. This study was performed to characterize mutagenesis and mutational target genes underlying lung carcinogenesis in patients with UIP.We performed whole exome sequencing of lung adenocarcinoma with usual interstitial pneumonia.

  Study JGAS000065

• Pharmacogenomics of HIV Therapy - Atazanavir Bilirubin-related Side Effects

  This is an evaluation of genetic associations with atazanavir (ATV) discontinuation for bilirubin-related causes within 12 months of treatment. Patients were treated at an HIV primary care clinic in Nashville TN from 1998 to 2012. A previously known SNP in UGT1A1 (rs887829) was used to define metabolizer genotypes (extensive, intermediate, slow metabolizer). Over 500,000 SNPs from genome-wide genotyping were used to define MDS (Multidimensional Scaling) coordinates to account for population stratification. Patients were defined as cases if they discontinued ATV for bilirubin-related causes within 12 months of treatment, otherwise they were defined as controls if they did not stop treatment. Among 321 evaluable patients, 15 (4.6%) had bilirubin-related atazanavir discontinuation within 12 months. Homozygosity for rs887829 T/T was present in 28.1% of black, 21.4% of Hispanic, and 8.6% of white patients. Among all patients the hazard ratio (HR) for bilirubin-related discontinuation with T/T versus C/C genotype was 7.3 (95% C.I.: 1.7 to 31.5; p = 0.007). Among 152 white patients the HR was 14.4 (95% CI: 2.6 to 78.7; p = 0.002), but among 153 black patients the HR was 0.8 (95% C.I. 0.05 to 12.7; p = 0.87).

  Study phs001484

• Cancer Genomics of the Kidney

  The aim of CAGEKID is to carry out comprehensive detection of DNA markers for conventional (clear cell) renal carcinoma. The project includes complete analysis of somatic and constitutional DNA variation, methylation patterns and expression in a large number of constitutional/tumor pairs. CAGEKID is a part of the International Cancer Genome Consortium, ICGC.

  Dataset EGAD00001004018

• Whole Genome Sequencing of HCC

  The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003994

• Ensemble learning for classifying single-cell data and projection across reference atlases

  Single-cell data are being generated at an accelerating pace.How best to project data across single-cell atlases is an open problem. We developed a boosted learner that overcomes the greatest challenge with status quo classifiers: low sensitivity, especially when dealing with rare cell types.

  Study EGAS00001004283

• Search for genetic variants influencing gestational weight gain in type 1 diabetes patients by genome wide association method

  Clinical data suggest that BMI and gestational weight gain (GWG) are strongly interconnected phenotypes, however the genetic basis of the latter is rather unclear. Here we aim to investigate the genetic factors associated with GWG from the perspective of the genetics of obesity.

  Study EGAS00001004408

• Whole Exome Sequencing of 60 tumor/normal matched liver Cancers (HCC)

  The French ICGC project on liver tumors is coordinated by Pr Jessica Zucman-Rossi and funded by Inca (French Institute for Cancer). The aim of the present project is to identify the catalog of somatic and germline mutations in liver tumors using whole genome (WGS) and whole exome sequencing (WGS), integrated with DNA methylation and RNA sequencing (RNA-seq) data. The present series corresponds to 60 whole exome tumor/normal pairs with matched RNA-seq.

  Dataset EGAD00001004180

• ICU_transcriptomics__Assessing_the_role_of_the_host_immune_response_in_patients_with_ventilator_associated_pneumonia

  The aim of the proposed project is to provide transcriptomic sequencing data analysis of cells isolated from bronchioalveolar lavage and blood samples from critically ill patients with pneumonia on an intensive care unit in order to investigate the host contribution to disease. The lung microbiome of these patients will be analysed in parallel by deep sequencing and 16S sequencing. These data will provide important information to the development of strategies aimed at improving patient outcomes, reducing the development of antimicrobial resistance and facilitating infection control measures in hospital. Specifically, the proposed work will be a proof of principle study of 100 patients. We will use transcriptomic data to define the host contribution to the symptoms of these critically ill patients diagnosed with pneumonia. The data will be correlated with cytokine/chemokine concentrations, routine microbiology analysis and pathogen genomic data from the same samples to determine the ecology of the lungs of these patients. We will look for associations between clinical features, host response and pathogen genomics in order to identify new diagnostic markers. This study should provide important information to improve the speed and accuracy of diagnosis - resulting in more targeted and successful treatment of critically ill patients in the ICU. 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 (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001003074