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• Acral Melanoma PDXs from the admixed Brazilian Population - Tumour VCF files with somatic SNV and INDELs - Whole exome sequencing data

  Raw, flagged and annotated VCF files with somatic calls made with CavEMan and Pindel for Acral Tumours. Variant effect prediction was run with Ensembl VEP v103.Acral melanoma (AM) is an aggressive melanoma subtype with limited therapeutic options and poor outcomes. In non-European descent and admixed populations, like in Latin America, it can account for a significant proportion of cutaneous melanoma cases. Here, we performed comprehensive genomic and functional profiling of AM from a uniquely diverse Brazilian cohort. Whole-exome and transcriptome sequencing was performed on both tumours and patient-derived xenograft (PDX) samples. The PDX were obtained from a comprehensive collection of patient-derived xenograft (AM-PDX) models that we established which faithfully retained the histopathological and genomic features of the original tumours.

  Dataset EGAD00001015741

• Providing access to COVID-19 data: one year later

  response efforts On 11 March 2020 the World Health Organization declared the novel coronavirus outbreak a global pandemic. Four months later, the European Genome-phenome Archive (EGA) released its first COVID-19 dataset. This dataset – single cell RNA and VDJ sequencing of B cells from 60 COVID-19 patients – showed that neutralizing antibodies could be identified by high-throughput sequencing in response to SARS-CoV-2 infection. That was one year ago. Today, the EGA provides access to fifteen COVID-19 datasets from researchers across seven countries in Asia, Europe, and North America. These studies represent almost 17,000 individuals and have resulted in at least sixteen publications and preprints. Researchers deposit controlled access COVID-19 data at EGA The global research community has come together rapidly to investigate the SARS-CoV-2 coronavirus and better understand the related disease, COVID-19. These research efforts generate valuable genetic and phenotypic data from patients and research participants that can be shared with approved researchers. The EGA enables sharing of this research data by providing a service for archiving and controlled distribution of sensitive data. Over the past year, the EGA has worked with researchers to archive and distribute COVID-19 data from high-throughput sequencing experiments, genotyping studies, and phenotypic information. These datasets investigate the immune system, blood, and cells and tissues of the lung, which are relevant for studying a contagious respiratory illness caused by a viral infection. *Study Spotlight. In January 2021, Ancestry.com demonstrated the utility of deep phenotyping based on self-reported outcomes from a large population of mild and asymptomatic COVID-19 cases. They identified genetic associations with eight COVID-19 phenotypes and showed distinct patterns of association, most notably related to the chr3/SLC6A20/LZTFL1 and chr9/ABO regions. The supporting data is available at the EGA to approved researchers and includes both genotype and phenotype data for 15,000 individuals. EGA collaborates with global COVID-19 community Since the coronavirus outbreak, the EGA has collaborated with other life science resources to support discovery and access to COVID-19 datasets. COVID-19 Host Genetics Initiative. With the NHGRI’s Genomic Data Science Analysis, Visualization, and Informatics Lab-space (AnVIL) platform, the EGA enables sharing of individual-level genetic and phenotypic data from the COVID-19 Host Genetics Initiative (HGI). This initiative aims to generate, share, and analyze data from COVID-19 host genetics research projects to better understand the genetic determinants of COVID-19 susceptibility, severity, and outcomes. In response to COVID-19, the EGA actively supports COVID-19 data submissions and integration of data access and flow into the COVID-19-HGI analysis platform. *Study Spotlight. The COVID-19 HGI has combined individual-level data for 13,868 COVID-19 positive patients (N=7,167 hospitalized) from 17 cohorts in nine countries. The data were used to assess the association of the major common COVID-19 genetic risk factor (chromosome 3 locus tagged by rs10490770) with mortality, COVID-19-related complications, and laboratory values. The genotype and phenotype data for 10 of these cohorts is available at the EGA to approved researchers under accession EGAS00001005304. Fig 1: EGA COVID-19 studies are searchable in the European COVID-19 Data Portal alongside other COVID-19 and SARS-CoV-2 public datasets. European COVID-19 Data Portal. EGA-archived COVID-19 data are discoverable via the European COVID-19 Data Portal (Fig. 1), which brings together public and controlled access data to accelerate coronavirus research for the international community. By indexing all COVID-19-related data in one place, researchers can more easily discover relevant datasets of interest, thus increasing the “FAIRness” (Findability, Accessibility, Interoperability, Reusability) of this valuable data. Fig 2: SARS-CoV-2 viral sequences are imported from ENA and analysed in Galaxy to detect variants. Results are accessible to researchers through the COVID-19 Viral Beacon. COVID-19 Viral Beacon. The COVID-19 Viral Beacon tool was developed in collaboration with the European Nucleotide Archive and Galaxy to enable near real-time browsing of SARS-CoV-2 variability at genomic, amino acid, and motif levels (Fig. 2). The COVID-19 Viral Beacon allows researchers to (i) perform detailed searches about genomic variants, (ii) filter queries and find unique cases, (iii) filter data based on strain-specific variants, and (iv) explore associated metadata. It uses the Global Alliance for Genomics and Health (GA4GH) Beacon standard including new Beacon v2 features. With this tool, researchers can study intra-host mutations on genomic regions of interest, or trace any variant frequency over time using raw read data. More than 200,000 SARS-CoV-2 analysed genomic data files are now available to researchers for further exploration. Ongoing COVID-19 efforts at EGA Addressing the COVID-19 pandemic is a global effort. Federated resources are necessary to support transnational deposition, access, and analysis of sensitive COVID-19 host genetics and other related data. At the same time, many countries now have emerging personalized medicine programmes which are generating data from national or regional healthcare initiatives. These data are subject to more stringent information governance than research data and often must comply with national data protection legislation. To address this need, the Federated EGA was established to serve as the primary global resource for discovery and access of sensitive human omics and associated data consented for secondary use. The Federated EGA will comprise a network of national human data repositories and will implement community standards and common interfaces. Launching Federated EGA promises to accelerate not only global research efforts to understand, diagnose, and treat COVID-19, but also to foster data reuse, enable reproducibility, and accelerate biomedical and disease research to ultimately improve human health.

  Blog providing-access-to-covid-19

• CSER: Incorporating Genomics into the Clinical Care of Diverse NYC Children (NYCKidSeq)

  The NYCKidSeq program will significantly advance the implementation of genomic medicine, particularly for children, young adults and their families in Harlem and the Bronx. The study will assess the clinical utility of genomic medicine in three broad areas of pediatric disorders, while engaging a range of providers and community advisors to overcome the well-documented barriers to inclusion of underserved and underrepresented populations in genomic research. The study will also include testing, analyzing, and implementing a novel communication tool, Genomic Understanding, Information and Awareness (GUÍA), to facilitate the return of genomic test results. The use of GUÍA will enhance the understanding of these genomic testing results by families, patients, and care providers at all levels of expertise, in two health systems. Healthcare system leadership will be engaged to provide insights into their readiness for genomic implementation. Overall, the NYCKidSeq program will inform the genomics and clinical communities about how to implement genomic medicine in a diverse population in a clinically useful, technologically savvy, culturally sensitive, and ethically sound manner.

  Study phs002337

• Molecular Genetics of Schizophrenia - nonGAIN Sample (MGS_nonGAIN)

  This study is part of the Molecular Genetics of Schizophrenia (MGS) genome wide association study (GWAS) of 3,972 cases (2,686 EA and 1,286 AA) and 3,629 controls (2,656 EA and 973 AA) (analyzed sample remaining after quality control exclusions), comprised of European ancestry (EA) and African American (AA) samples. We genotyped about half of the EA sample and almost all of the AA sample under the auspices of the Genetic Association Information Network (GAIN) with the Affymetrix 6.0 platform at the Broad Institute. The remainder of the included sample was also genotyped with the Affymetrix 6.0 platform at the Broad Institute, and we refer to this component as the nonGAIN sample. Cases met criteria for schizophrenia (SCZ) or schizoaffective disorder (SA) per the Diagnostic and Statistical Manual of Mental Disorders version IV (DSM-IV) for all three collections (SGI, MGS1, and MGS2) comprising these cases. However, for the older SGI collection, codes for the secondary diagnoses refer to the older DSM-III-R version. Controls were screened briefly and excluded if they endorsed a history of these illnesses.

  Study phs000167

• Genome-wide Association Study of Adiposity in Samoans

  The research goal of this study is to identify genetic variation that increases susceptibility to obesity and cardiometabolic phenotypes among adult Samoans using genome-wide association (GWAS) methods. DNA from peripheral blood and phenotypic information were collected from 3,119 adult Samoans, 23 to 70 years of age. The participants reside throughout the independent nation of Samoa, which is experiencing economic development and the nutrition transition. Genotyping was performed with the Affymetrix Genome-Wide Human SNP 6.0 Array using a panel of approximately 900,000 SNPs. Anthropometric, fasting blood biomarkers and detailed dietary, physical activity, health and socio-demographic variables were collected. We are replicating the GWAS findings in an independent sample of 2,500 Samoans from earlier studies. After replication of genomic regions and informative SNPs in those regions, we will determine sequences of the important genes, and determine the specific genetic variants in the sequenced genes that are associated with adiposity and related cardiometabolic conditions. We will also identify gene by environment interactions, focusing on dietary intake patterns and nutrients.

  Study phs000914

• Characterization of Immune Evasion in Merkel Cell Carcinoma

  Merkel cell carcinoma (MCC) is a rare, neuroendocrine skin carcinoma that is caused by the Merkel cell polyomavirus (MCPyV) in 80% of cases and by ultraviolet (UV) damage in 20% of cases. MCC should theoretically elicit a strong cytotoxic T cell response due to the high neoantigen and viral antigen burden in MCPyV- and MCPyV+ MCC, respectively. However, MCC often escapes immune recognition and is associated with very poor prognosis at advanced stages. To systemically identify mechanisms of immune evasion in MCC, we established 11 robust MCC lines from either primary tumors or patient-derived xenografts (7 MCPyV+ and 4 MCPyV-). We then characterized these tumors and cell lines by whole exome sequencing (WES), RNA-sequencing, scRNA-sequencing, ATAC-seq, and whole genome bisulfite sequencing (WGBS). We also studied MCC transcriptional subtypes, utilizing bulk and scRNA-sequencing datasets of patient-derived tumors and cell lines to investigate profiles of neuroendocrine gene expression. The genes linked below define either a neuroendocrine or a non-neuroendocrine phenotype presence within MCC tumors.

  Study phs002260

• Epigenome Wide DNA Methylation Study for Osteoporosis Risk

  Osteoporosis is characterized by low bone mineral density (BMD). The advancement of high-throughput technologies and integrative approaches provided an opportunity for deciphering the mechanisms underlying osteoporosis. In this study, we generated genomic (from whole blood DNA), transcriptomic and methylomic (from peripheral blood monocytes, PBMs), and serum metabolomic datasets from 143 premenopausal Caucasian females aged 25-40 years, including 74 with relatively high hip BMD (Z scores ≥ 0.8) and 69 with relatively low hip BMD (Z scores ≤ -0.8). The BMD Z score was defined as the number of standard deviations a subject's BMD differed from the mean BMD of their age-, gender-, and ethnicity-matched population. We identified differentially methylated CpG sites (DMCs) in peripheral blood monocytes (PBMs) at the whole methylome level between premenopausal women with high BMD and those with low BMD and deciphered how the DMCs influence the BMD variation through affecting the expression of the relevant genes. We also performed differential gene expression and metabolic analysis to assess their biological interaction and causal mechanisms. Our study provided novel insights into the pathogenesis of osteoporosis.

  Study phs001960

• The Innate Immune Response as a Therapeutic Target for Cutaneous Leishmaniasis

  The overall goal of the proposed project is to identify innate host functions that contribute to cure or failure during antileishmanial drug therapy, and their related biomarkers. Results from this project enabled the identification of host-specific predictive and prognostic signatures of therapeutic responsiveness, and the bases for rational selection of host-targeted therapeutics that redirect inflammation and revert pathogenicity. Through sequential transcriptomic profiling of blood monocytes (Mo), neutrophils (Nφ), and eosinophils (Eφ) over the course of systemic treatment with meglumine antimoniate, we discovered that a heightened and sustained Type I interferon (IFN) response signature is a hallmark of treatment failure (TF) in Cutaneous Leishmaniasis (CL) patients. The transcriptomes of pre-treatment, mid-treatment and end-of-treatment samples were interrogated to identify predictive and prognostic biomarkers of TF. Results from this study instigate the evaluation of Type-I IFN responses as new immunological targets for host-directed therapies for treatment of CL, and highlight the feasibility of using transcriptional signatures as predictive biomarkers of outcome for therapeutic decision making.

  Study phs003545

• Ten colorectal cancer patients with locally advanced primary tumors who underwent primary tumor resection following neoadjuvant chemotherapy (NAC).

  Background We aim to investigate the utility of serial gene mutation tracking for locally advanced CRC in those who underwent curative resection following neoadjuvant chemotherapy. Methods We prospectively collected 10 locally advanced CRC cases for which curative resection was performed following preoperative neoadjuvant chemotherapy. Tissues from the primary tumour, distant metastatic tumours, and blood plasma were obtained during serial treatment. Comprehensive mutation analysis of 47 cancer-associated genes was performed using a pre-designed gene panel and next-generation sequencing. Results All cases showed a partial response to neoadjuvant chemotherapy, and pathological R0 resection was accomplished. In primary tumours, non-synonymous mutations were detected at between 1 and 14 sites before chemotherapy and at between 1 and 2 sites after. Founder mutations were precisely detected in blood plasma and metastatic tumours during longitudinal treatment. Conclusions Serial mutational analysis indicated that subclonal selection occurs during chemotherapy and that plasma can substitute for tumourous tissue in mutational analysis for drug selection and treatment decisions.

  Study JGAS000222

• Host factors dictate gut microbiome alterations in chronic kidney disease more strongly than to kidney function

  Despite recent progress, microbial markers in Chronic Kidney Disease (CKD) remain inconclusive. We combined quantitative faecal metagenomics (N=130 CKD cohort) and cross-study biomarker comparisons (Ntotal=4420) to study microbiome associations with glomerular filtration rate (eGFR; kidney function) and 4-year CKD progression. Transit time (TT) and medications primarily explained microbiome variation, trumping eGFR-related effects. Metagenome analysis showed increased p-cresol and indole synthesis potential and decreased plant-to-animal CAZyme ratios with lower eGFR, coupled to a Bact1 to Rum enterotype shift, suggesting saccharolytic-to-proteolytic microbiome transitions linked to dietary guidelines and slowed-down TT. Peritoneal dialysis patients showed increased (dysbiotic) Bact2 prevalence and linked intestinal inflammation. Only Escherichia coli, an unnamed Alistipes species and Bifidobacterium adolescentis were confounder-independent markers for eGFR, but these nor previous markers convincingly replicated across 11 studies. No predictors for CKD progression were found. Together, poor evidence for microbiome biomarkers but substantial eGFR-independent effects were found, suggesting potential for nutritional and TT interventions in CKD.

  Study EGAS50000000646