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• Molecular Biomarkers of Obesity and Metformin Response in Endometrial Cancer: Analysis of GOG-0286B

  The primary endpoint for the phase 2 study was progression free survival (PFS), and the primary endpoint for the phase 3 study was overall survival (OS). Data from phase 2 were included in the phase 3 analysis. Tissue was collected from patients with endometrial cancer who participated in the study (NCT02065687). The tissue will be analyzed for genetic data and combined with the clinical data to see if some gene variants are associated with longer PFS or OS, particularly on the metformin arm of the study.

  Study phs002934

• FLG LoF Variants are Associated with Atopic Dermatitis in an Early-Life Prospective Cohort

  We performed targeted sequencing of the FLG gene in 438 children with physician-diagnosed Atopic Dermatitis (AD), identified Loss-of-Function (LoF) variants, and tested the association of having one or more of these variants (binary composite) variants with AD-associated outcomes. We found that having a LoF variant was associated with moderate-severe AD compared to mild AD, food allergy at the first visit, and higher transepidermal water loss (TEWL) in both lesional and non-lesional skin in these children.

  Study phs003489

• Variant analysis on FFPE specimen from NSCLC patients (OCAPlus)

  This study assessed the presence of somatic variants via the Oncomine Comprehensive Panel Plus panel (ThermoFisher) for commonly mutated cancer genes and measure tumor mutational burden using next-generation sequencing. It was performed on genomic DNA from FFPE tissue of tumor resections. Mutations were used to draw OncoPrints and to assess TMB in relation with response metrics.

  Study EGAS50000001136

• Grey_Platelet_Syndrome__GPS_

  As part of the Bloodomics collaboration we have several categories of pedigrees with diseases/syndromes relevant to cardiovascular diseases (CVD). One such pedigree, Grey Platelet Syndrome (GPS) is a rare congenital bleeding disorder caused by a reduction or absence of alpha granules in platelets. Exome sequencing has been performed as part of a discovery program to ascertain potential causative variants of the clinical phenotype.

  Study EGAS00001000091

• BARIA baseline first 100 individuals transcriptomes

  Prevalence of obesity and associated diseases, including type 2 diabetes mellitus, dyslipidaemia and non-alcoholic fatty liver disease (NAFLD), are increasing. Underlying mechanisms, especially in humans, are unclear. Bariatric surgery provides the unique opportunity to obtain biopsies and portal vein blood-samples. Methods The BARIA Study aims to assess how microbiota and their metabolites affect transcription in key tissues and clinical outcome in obese subjects and how baseline anthropometric and metabolic characteristics determine weight loss and glucose homeostasis after bariatric surgery. We phenotype patients undergoing bariatric surgery (predominantly laparoscopic Roux-en-Y gastric bypass), before weight loss, with biometrics, dietary and psychological questionnaires, mixed meal test (MMT) and collect fecal-samples and intra-operative biopsies from liver, adipose tissues and jejunum. We aim to include 1500 patients. A subset (approximately 25%) will undergo intra-operative portal vein blood-sampling. Fecal-samples are analyzed with shotgun metagenomics and targeted metabolomics, fasted and postprandial plasma-samples are subjected to metabolomics, and RNA is extracted from the tissues for RNAseq-analyses. Data will be integrated using state-of-the-art neuronal networks and metabolic modeling. Patient follow-up will be ten years.

  Study EGAS00001005704

• RRBS sequencing of 7 tumour regions and a normal sample from a single TRACERx patient.

  Background: Epigenetic heterogeneity within a tumour can play an important role in tumour evolution and the emergence of resistance to treatment. It is increasingly recognised that the study of DNA methylation (DNAm) patterns along the genome - so-called `epialleles' - offers greater insight into epigenetic dynamics than conventional analyses which examine DNAm marks individually. Results: We have developed a Bayesian model to infer which epialleles are present in multiple regions of the same tumour. We apply our method to reduced representation bisulfite sequencing (RRBS) data from multiple regions of one lung cancer tumour and a matched normal sample. The model borrows information from all tumour regions to leverage greater statistical power. The total number of epialleles, the epiallele DNAm patterns, and a noise hyperparameter are all automatically inferred from the data. Uncertainty as to which epiallele an observed sequencing read originated from is explicitly incorporated by marginalising over the appropriate posterior densities. The degree to which tumour samples are contaminated with normal tissue can be estimated and corrected for. By tracing the distribution of epialleles throughout the tumour we can infer the phylogenetic history of the tumour, identify epialleles that differ between normal and cancer tissue, and define a measure of global epigenetic disorder. Conclusions: Detection and comparison of epialleles within multiple tumour regions enables phylogenetic analyses, identification of differentially expressed epialleles, and provides a measure of epigenetic heterogeneity.

  Study EGAS00001002484

• RODAM

  The RODAM study assesses the health and wellbeing of Ghanaian residents in Ghana and Europe and follows them up over time. With this unique approach the RODAM study attempts to unravel the causes of cardiovascular disease and its risk factors among African migrants in Europe and non-migrants sub-Saharan Africa. Data are available upon reasonable request. These requests can be made to de RODAM-Pros cohort coordinator (rodamcoordinator@amsterdamumc.nl) or principal investigator, Professor Charles Agyemang (c.o.agyemang@amsterdamumc.nl).

  Dac EGAC50000000474

• Cryptic Relatedness in the Singapore Living Biobank Project

  The Singapore Living Biobank is a collection of healthy population-based Chinese and Malay individuals, for the purpose of phenotype recall study of high-impact variant carriers. These individuals are sampled from two studies: Multi-Ethnic Cohort (MEC), and the Singapore Health 2012 (SH2012). The MEC is a population-based cohort initiated in 2007 to investigate the genetic and lifestyle factors that affect the risk of developing chronic diseases such as diabetes and cardiovascular outcomes in the three ethnic groups (Chinese, Malays, and Indians). The SH2012 study is a population-based cross-sectional survey conducted in Singapore between 2012 and 2013, with over-sampling of Malays and Indians. Participants in MEC and SH2012 completed a similar set of questionnaire components, health examination, and biochemisty panels. Description of the MEC and SH2012 studies can be found at http://blog.nus.edu.sg/sphs/. We generated whole-exome sequencing data and Illumina OmniExpress array genotyping data for 1,299 Chinese and 1,229 Malays from the Singapore Living Biobank. This study includes a subset of 762 individuals that were found to be closely related (≤3rd degree), including 263 Chinese and 499 Malays.

  Study EGAS00001002619

• A whole-genome sequencing study for evolutionary history of Tibetans and their genetic adaptations to high altitude

  Due to a unique adaptation to high altitude, the Tibetan Plateau population has been the subject of much research interest. In this study, we conducted whole genome sequencing of 27 Tibetan individuals. Through our analysis, we inferred a detailed history of demography and revealed the natural selection of Tibetan population. We provided evidence of genetic separation between the two subpopulations of Han and Tibetans as early as 44 to 58 thousand years ago, replicated previously reported high altitude adaptation genes, including EPAS1 and EGLN1, and reported three new candidate genes, including PTGIS, VDR, and KCTD12.

  Study phs001338

• NCI Cancer Model Development for the Human Cancer Model Initiative (HCMI)

  The Cancer Model Development Center (CMDC) project is part of the Human Cancer Model Initiative (HCMI) and is managed by the Office of Cancer Genomics within the Center for Cancer Genomics at the National Cancer Institute (NCI). The goal of the HCMI is to generate approximately 1000 novel human "next generation" tumor-derived models as a community resource. The models aim to faithfully recapitulate the cellular complexity and heterogeneity of human tumors. The CMDCs are tasked by the NCI with producing a proportion of the cancer models. Wellcome Sanger Institute (WSI) is a contributing member of the HCMI. Models developed by HCMI are being derived from a number of tumor types and subtypes (see below), including rare adult, pediatric and understudied cancers. The number of models and the clinical sites from which patient samples are acquired is increasing. Normal tissue, originating tumor, and tumor-derived models are sequenced. The next generation cancer models are associated with rich clinical and genomic data through the NCI Genomic Data Commons for all researchers to advance cancer research. The CMDC and HCMI models will serve as excellent tools in research to provide insight into the pathways that influence tumor growth and progression, how tumors respond to therapy, etc. Ultimately, the data generated using these models will support the development of personalized oncology. There is a delay between registered IDs and model availability. The current model count is found in The HCMI Searchable Catalog which is updated when new models are available for distribution to the research community.

  Study phs001486