Search Results - EGA European Genome-Phenome Archive

INCLUDE: The Epidemiology of Transient Leukemia in Newborns with Down Syndrome

The INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project is an NIH-wide collaboration that seeks to improve health and quality-of-life for people with Down syndrome. The INCLUDE Project Data Coordinating Center and partners created the INCLUDE Data Hub, a centralized data resource that allows access to large-scale clinical and multi-omics datasets specific to Down syndrome and supports collaborative, cloud-based analysis to accelerate scientific discoveries related to Down syndrome and its co-occurring conditions.Down syndrome (DS) is associated with a remarkably high risk of childhood acute myeloid leukemia (AML), with an approximately 500-fold increased risk of the rare subtype acute megakaryoblastic leukemia. Though largely treatable, a proportion of myeloid leukemia in DS (ML-DS) patients relapse with dismal survival. ML-DS is preceded by a preleukemia, transient abnormal myelopoiesis (TAM), which presents clinically at birth and is driven by somatic truncating mutations in the erythro-megakaryocytic transcription factor gene GATA1. Up to 15% of DS newborns have TAM, and this can be fatal in up to 20% of cases. A further 10-15% of newborns with DS harbor subclonal GATA1 mutations with clinically silent disease (i.e., Silent TAM). Of the DS newborns with either TAM or Silent TAM (i.e., transient leukemia), up to 15% will acquire additional somatic mutations and progress to ML-DS. We predict that germline variation modifies the risk of developing somatic truncating GATA1 mutations, the first step towards ML-DS, however this has yet to be examined. To address this, the main aim of this X01 study is to perform the first genetic association study of GATA1 mutations in DS, through whole-genome sequencing (WGS) of 470 DS newborns in the Oxford Down Syndrome Cohort Study (ODSCS). Targeted sequencing of GATA1 has already been performed in the 470 DS newborns in the ODSCS, with 130 (28%) confirmed to harbor a somatic truncating GATA1 mutation. We will perform a genome-wide association study (GWAS) of GATA1 mutations to assess genetic variation genome-wide, in particular focusing on variants in candidate genes on the trisomic chromosome 21, RUNX1, ERG, ETS2, and DYRK1A, which have previously been associated with upregulation of GATA1. We will also carry out a chromosome X-wide association study (XWAS) to investigate genetic variation at the GATA1 gene, which resides on chromosome X. WGS data will also enable us to assess the potential role of copy number variation in the risk of transient leukemia in DS. Discovering genetic risk factors for GATA1 mutations in DS may reveal targets for new targeted therapies for TAM, and also inform the etiology of ML-DS as well as AML in the non-DS population. Finally, the ODSCS includes rich phenotypic data for the 470 DS newborns, including clinical diagnosis of TAM and other hematologic complications, complete blood counts, maternal pregnancy complications, and information on congenital heart disease and other birth defects. Thus, whole genome sequencing data in DS newborns from the ODSCS will provide a rich resource for the DS research community.

Study phs002982

RNAseq data to study PRPF6 regulated splice forms in colon cancer cell lines

Alternative splicing plays critical roles in differentiation, development, and cancer (Pettigrew et al., 2008; Chen and Manley, 2009). The recent identification of specific spliceosome inhibitors has generated interest in the therapeutic potential of targeting this cellular process (van Alphen et al., 2009). Using an integrated genomic approach, we have identified PRPF6, an RNA binding component of the pre-mRNA spliceosome, as an essential driver of oncogenesis in colon cancer. Importantly, PRPF6 is both amplified and overexpressed in colon cancer, and only colon cancer cells with high PRPF6 levels are sensitive to its loss. Our data clearly point to an important role for PRPF6 in colon cancer growth and suggest that a better understanding of its role in alternative splicing in colon cancer is warranted. To determine the specific alternative splice forms that PRPF6 regulates in colon cancer, we plan three experiments: 1. The first involves knocking down expression of PRPF6 in two different cancer cell lines with 3 different siRNAs, and then completing RNA-seq to determine the gene expression changes that occur relative to a non-targeting control siRNA. Because of the role for PRPF6 in pre-mRNA splicing, we especially want to quantify the changes in splice-specific forms of all genes genome-wide to identify genes whose splicing is altered upon PRPF6 knockdown. 2. The second involves immunoprecipitating PRPF6 from two different cancer cell lines and isolating any RNA that is bound to PRPF6, since PRPF6 is an RNA-binding protein. We then want to carry out RNA-seq to identify which RNA molecules co-immunoprecipitated with PRPF6. This will help us determine possible functions for PRPF6 in regulating colon cancer growth. 3. The third involves overexpressing PRPF6 in cell lines and then carrying out RNA-seq to identify any changes in splice-specific gene expression. This will allow us to determine whether increased PRPF6 expression is sufficient to drive alternative splicing changes.

Study EGAS00001000761

Providing safe access to sensitive human data across borders: Federated EGA becomes a reality

Enabling discovery and access to sensitive data across national boundaries is vital for improving human health. It enables more powerful and efficient research by increasing the volume and diversity of data available for analysis. It allows us to better understand the causes of diseases – cancer, rare diseases, infectious diseases like COVID-19 – and develop new medicines and treatments. Sensitive human omics data are typically generated by research initiatives and shared using specialist repositories which provide services for data submission, discovery, and access. The EGA is one such repository. Established in 2008 at EMBL’s European Bioinformatics Institute (EMBL-EBI) in the UK, since 2012 the EGA (“Central EGA”) has been jointly managed by EMBL-EBI and the Centre for Genomic Regulation (CRG) in Spain. Many countries have emerging personalised medicine programmes which generate data from national initiatives. These programmes are driving a transition in human genomics from being research-driven to receiving funding through healthcare. Data generated in a clinical context are subject to stricter governance than research data and must follow national data protection legislation. To solve these challenges, the Federated EGA provides a network of connected resources to enable transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. In this way, the Federated EGA infrastructure supports the goals of European initiatives such as the 1+ Million Genomes initiative (1+MG), the European Health Data Space, and a number of EU-funded 1+MG implementation projects including Beyond 1 Million Genomes. The Federated EGA is made up of “Nodes” – typically nationally funded and operated – which store and manage data locally while allowing global discovery within the Federated EGA network. Since 2016, multiple parallel efforts, supported by ELIXIR and other transnational and national initiatives, have created technical and legal frameworks for establishing the Federated EGA. In 2022, the first five Nodes – Finland, Germany, Norway, Spain, and Sweden – officially joined the Federated EGA by signing Federated EGA Collaboration Agreements with Central EGA. The Finnish FEGA Node is operated by CSC - IT Center for Science and provides data management services according to national laws and the requirements of the EU General Data Protection Regulation (GDPR). These services provide tools and support for the whole life-cycle of sensitive research data from collating to analysis, publication, and authorised re-use. The development of the services has been a joint effort with the other Nordic nodes within NeIC's Tryggve and Heilsa projects, and funded by Finnish Ministry of Education and Culture and projects coordinated by ELIXIR Finland. Read more about Finnish FEGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. In Norway, a key component of the infrastructure is the services of The Sensitive Data Service (TSD) offered by USIT at University of Oslo. The Federated EGA Norway Node is developed by ELIXIR Norway and operated by the University of Oslo as the responsible legal entity. Core software modules are developed jointly with the other Nordic nodes in the NeIC Tryggve and Heilsa projects. Read more about FEGA Norway signing. The Spanish FEGA (es-FEGA) is a national service for storing sensitive biomedical data in Spain. Supported by the Spanish Institute of Bioinformatics (INB) in collaboration with Central EGA, sensitive research datasets are primarily hosted at the Barcelona Supercomputing Centre facilities. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. By providing a solution for secure and efficient management of human omics data, the Federated EGA aims to foster data reuse, enable reproducibility, accelerate biomedical research, and improve human health. Find out more Interested in setting up your own Federated EGA Node? Check out the FEGA Onboarding Knowledge Base for more information. The ELIXIR Federated Human Data Community is a great entry point for anyone interested in learning more about the Federated EGA. You can: Join the ELIXIR Federated Human Data Community mailing list (select “Human Data”) Attend the ELIXIR Federated Human Data Community calls

Blog safe-access-to-sensitive-human-data-federated-ega

Predicting brain tumor recurrence: development and validation of a DNA-methylation based nomogram in meningioma

Our work is the first to demonstrate the transformative utility of integrating clinical and molecular factors for use beyond simple classification into the realm of individualized prognostication for any brain tumor. Using our developed and validated tools that are publicly available, clinicians will be able combine clinical and molecular factors to determine an individualized probability of recurrence for patients with meningiomas. This represents a major advance in the field of personalized medicine for neuro-oncology, and the use of this tool can help clinicians overcome one of the most challenging limitations we face when treating patients with meningiomas.

Study EGAS00001003490

Human genome-wide variations in the Massim region

The Massim, a cultural region encompassing the southeastern tip of mainland Papua New Guinea (PNG) and nearby islands, is famous for the Kula trading network, in which different valuables circulate in different directions among the islands. To explore Massim genetic history, we generated genome-wide data from across the region and found variable levels of Papuan-related (indigenous) ancestry, including a novel ancestry associated with Rossel Island, and Austronesian-related ancestry that arrived later. We find genetic evidence for different patterns of contact across PNG, the Massim, and the Bismarck and Solomon Archipelagoes for Austronesian-related vs. Papuan-related ancestry, with more geographic restriction for the latter. Moreover, Kula-practicing groups share more genetic similarity than do other groups, and this likely predates the origin of Kula, suggesting that high between-group contact facilitated the formation of Kula. Our study provides the first comprehensive genome-wide assessment of Massim inhabitants and new insights into the fascinating Kula system.

Study EGAS00001006010

Identification of gene mutations and fusion genes in patients with Sézary Syndrome

Sezary syndrome (SS) is a leukemic form of cutaneous T-cell lymphoma (CTCL) with an aggressive clinical course. The goal of our study is to understand the genetic basis of the disease by looking for driver gene mutations and fusion genes in 15 erythrodermic patients with circulating Sezary cels, fourteen of them fulfilling the diagnostic criteria of SS. Peripheral blood samples were collected for each patient and CD4+ T-lymphocytes and Granulocytes were isolated. DNA and RNA was extracted for matched normal and tumor materials. Whole exome sequencing was performed on matched normal and tumor tissues of 12 patients and RNA sequencing was performed on 10 patients. For 7 of these patients, we have both exome as well as RNA sequencing data. In this study, we present a complex genomic landscape of Sezary syndrome with several point mutations, copy number variations and fusion events which could contribute to the pathogenesis of SS.

Study EGAS00001001706

A Comparative Analysis of Algorithms for Somatic SNV Detection in Cancer

Four recently published algorithms for the detection of somatic SNV sites in matched cancer-normal sequencing datasets are VarScan, SomaticSniper, JointSNVMix and Strelka. In this analysis, we apply these four SNV calling algorithms to cancer- normal Illumina exome sequencing of a chronic myeloid leukaemia (CML) patient. The candidate SNV sites returned by each algorithm are filtered to remove likely false positives, then characterised and compared to investigate the strengths and weaknesses of each SNV calling algorithm.

Study EGAS00001000927

Neuroblastoma relapse trio series from the AMC

The majority of neuroblastoma patients have tumors that initially respond to chemotherapy, but a large proportion of patients will experience therapy-resistant relapses. The molecular basis of this aggressive phenotype is unknown. Whole genome sequencing of 23 paired diagnostic and relapsed neuroblastomas showed clonal evolution from the diagnostic tumor with a median of 29 somatic mutations unique to the relapse sample. Eighteen of the 23 relapse tumors (78%) showed RAS-MAPK pathway mutations. Seven events were detected only in the relapse tumor while the others showed clonal enrichment. In neuroblastoma cell lines we also detected a high frequency of activating mutations in the RAS-MAPK pathway (11/18, 61%) and these lesions predicted for sensitivity to MEK inhibition in vitro and in vivo. Our findings provide a rationale for genetic characterization of relapse neuroblastoma and show that RAS-MAPK pathway mutations may function as a biomarker for new therapeutic approaches to refractory disease.

Dataset EGAD00001001360

Genetic alterations that deregulate RB and PDGFRA signaling pathways drive tumor progression in IDH2-mutant astrocytoma

In IDH-mutant astrocytomas, IDH2 mutation is quite rare and biological mechanisms underlying tumor progression in IDH2-mutant astrocytoma remain elusive. Here, we report a unique case of IDH2 mutant astrocytoma, CNS WHO grade 3 that developed tumor progression. We performed a comprehensive genomic and epigenomic analysis for primary and recurrent tumors and found that both tumors harbored recurrent IDH2R172K and TP53R248W mutation with CDKN2A/B hemizygous deletion. We also found amplifications of CDK4 and MDM2 with PDGFRA gain in the recurrent tumor and upregulated protein expressions of these genes. We further developed, for the first time, a xenograft mouse model of IDH2R172K mutant astrocytoma from the recurrent tumor, but not from the primary tumor. Consistent with parent recurrent tumor cells, amplifications of CDK4 and MDM2 with PDGFRA gain was found, while CDKN2A/B was identified as homozygous deletion in the xenografts, qualifying for integrated diagnosis of astrocytoma, IDH2-mutant, CNS WHO grade 4. Cell viability assay found that CDK4/6 inhibitor and PDGFR inhibitor potently decreased cell viability in recurrent tumor cells, as compared to primary tumor cells. These findings suggest that gene alterations that activate retinoblastoma (RB) signaling pathways and PDGFR may drive tumor progression and xenograft formation in IDH2-mutant astrocytoma, which is equivalent to progressive IDH1-mutant astrocytoma. Also, our findings suggest that these genomic alterations may represent therapeutic targets in IDH2-mutant astrocytoma.

Study JGAS000646

Genomic-Enabled Medicine for Recurrent Glioblastoma

In this prospective study, we performed genome-wide tumor/normal exome sequencing and tumor RNA-sequencing for recurrent glioblastoma patients. A subset of patients had both enhancing tumor and non-enhancing tissue sequenced to investigate spatial heterogeneity of this disease. Together, this information builds our understanding of the genomic underpinnings of glioblastoma, and contributes toward the knowledge base for identifying and developing more effective treatments for patients with glioblastoma.

Study phs001460

Genome Wide Association Studies in ECOG 2997 Trial

The ECOG 2997 trial was a randomized controlled trial for patients with previously untreated CLL comparing fludarabine monotherapy to the combination of fludarabine and cyclophosphamide. The initial clinical findings of this study were published in the Journal of Clinical Oncology in 2007 (JCO 25:793-8). Additional laboratory studies have also published (JCO 25:799-804).

Study phs000621

Target sequencing of 11 hereditary breast cancer genes in Japanese

We performed a case control association study for variants in coding regions of 11 hereditary breast cancer genes in 7,051 female unselected breast cancer patients, 11,241 female controls, 53 male patients, and 12,490 male controls of Japanese ancestry. The 11 genes were ATM, BRCA1, BRCA2, CDH1, CHEK2, NBN, NF1, PALB2, PTEN, STK11, and TP53.

Study JGAS000140

Heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer

A mutation accumulation experiment in colorectal cancer (CRC) derived tumoroids, aimed at measuring the spontaneous rates of accumulation of new single-nucleotide sequence variations in seven microsatellite stable CRCs and one microsatellite unstable CRC. Mutations accumulated over six+six months were identified via whole genome sequencing of clonal tumoroids. 150x WGS for 7 samples.

Study EGAS50000000425

Signals of positive selection in Peruvians from three ecological regions

In this study, genome-wide single-nucleotide polymorphism (SNP) data (Illumina Infinium® MEGA array) was gathered for 200 individuals distributed across Perú, and then analyzed to investigate signals of recent positive selection specific to populations living in the high-altitude environments of the Andes, the arid Pacific coast and the Amazon rainforest.

Study EGAS00001005692

Single-cell RNA sequencing dissects gene-environment interactions on gene expression and regulation in immune cells.

This study aims to dissect gene-environment interactions on gene expression and regulation in immune cells using scRNA-seq data from 120 donors being stimulated with 3 pathogens, for 2 different timepoints. More specifically, we identified context- and cell-type-specific eQTLs and co-expression QTLs in PBMCs.

Study EGAS00001005376

PRDM9 loss of function follow up from Born-in-Bradford Autozygosity sequencing

In the autozygosity exome sequencing of Born-in-Bradford samples of Pakistani origin there is a mother who is homozygous for an apparent truncating stop codon in PRDM9, the gene responsible for localising recombination during meiosis. We plan to deep sequence mother and child with X10, and physically phase the mother with PacBio sequencing. We will use this data to identify recombination locations, and test whether these are consistent with the known fine scale recombination map. Data Access is controlled by the Wellcome Trust Sanger Institute DAC and the Born In Bradford Executive Group.

Dataset EGAD00001001686

Health and Retirement Study (HRS)

Introduction to V2: This data release comprises data from the V1 release combined with approximately 3,000 additional samples, collected during the HRS 2010 field period. The 2010 data include samples from a random half of the new cohort enrolled in 2010 along with a significant expansion of the minority sample. Description: The University of Michigan Health and Retirement Study (HRS) is a longitudinal panel study that surveys a representative sample of approximately 20,000 people in America over the age of 50 every two years. Supported by the National Institute on Aging (NIA U01AG009740) and the Social Security Administration, the HRS explores the changes in labor force participation and the health transitions that individuals undergo toward the end of their work lives and in the years that follow. The study collects information about income, work, assets, pension plans, health insurance, disability, physical health and functioning, cognitive functioning, and health care expenditures. Through its unique and in-depth interviews, the HRS provides an invaluable and growing body of multidisciplinary data that researchers can use to address important questions about the challenges and opportunities of aging. Because of its innovation and importance, the HRS has become the model and hub for a growing network of harmonized longitudinal aging studies around the world. Origins of the HRS. As the population ages it is increasingly important to obtain reliable data about aging and topics that are relevant to a range of policy issues in aging. To address this need, the National Institutes on Aging (NIA) established a cooperative agreement with the University of Michigan Institute for Social Research to collect such data. The HRS launched data collection in 1992 and has re-interviewed the original sample of respondents every two years since then. By adding new cohorts and refreshing the sample, the HRS has grown to become the largest, most representative longitudinal panel study of Americans 50 years and older. HRS Study Design. The target population for the original HRS cohort includes all adults in the contiguous United States born during the years 1931-1941 who reside in households, with a 2:1 oversample of African-American and Hispanic populations. The original sample is refreshed with new birth cohorts (51-56 years of age) every six years. The sample has been expanded over the years to include a broader range of birth cohorts as well. The target population for the AHEAD survey consists of United States household residents who were born in 1923 or earlier. Children of the Depression (CODA) recruits households born 1924-1930, War Babies 1942-47, Early Boomers 1948-53, and Mid-Boomers 1954-59. Data collection includes a mixed mode design combining in-person, telephone, mail, and Internet. For consenting respondents, HRS data are linked at the individual level to administrative records from Social Security and Medicare claims. Genetic Research in the HRS. The HRS has genotyped 2.5 million single nucleotide polymorphisms (SNPs) on respondents using Illumina's Human Omni2.5-Quad (Omni2.5) BeadChip. The genotyping was performed by the NIH Center for Inherited Disease Research (CIDR). Saliva was collected on half of the HRS sample each wave starting in 2006. In 2006, saliva was collected using a mouthwash collection method. From 2008 onward, the data collection method switched to the Oragene kit. Saliva completion rates were 83% in 2006, 84% in 2008, and 80% in 2010 among new cohort enrollees. HRS Phenotypic data. Phenotypic data are available on a variety of dimensions. Health measures include physical/psychological self-report, various health conditions, disabilities, cognitive performance, health behaviors (smoking, drinking, exercise), physical performance and anthropomorphic measures, and biomarkers (HbA1c, Total Cholesterol, HDL, CRP, Cystatin-C). Data are also available on health services including utilization, insurance and out-of-pocket spending with linkage to Medicare records. Economic measures include employment status/history, earnings, disability, retirement, type of work, income by source, wealth by asset type, capital gains/debt, consumption, linkage to pensions, Social Security earnings/benefit histories. There is also extensive information on family structure, proximity, transfers to/from of money, time, social and psychological characteristics, as well as a wide range of demographics. Performance on a cognitive test combining immediate and delayed word recall was selected as an example trait for the dbGaP data release. In the immediate word recall task the interviewer reads a list of 10 nouns to the respondent and asks the respondent to recall as many words as possible from the list in any order. After approximately five minutes of asking other survey questions, the respondent is asked to recall the nouns previously presented as part of the immediate recall task. The total recall score is the sum of the correct answers to these two tasks, with a range of 0 to 20. Researchers who wish to link to other HRS measures not in dbGaP will be able to apply for access from HRS. A separate Data Use Agreement (DUA) will be required for linkage to the HRS data. See the HRS website (http://hrsonline.isr.umich.edu/gwas) for details.

Study phs000428

University of Washington Cerebrospinal Fluid Biomarker Study for Parkinson disease

There is a clear need to develop biomarkers for Parkinson disease (PD) diagnosis and monitoring disease progression. In this study we evaluated cerebrospinal fluid (CSF) proteins, which are known to be critically involved in PD or identified in our preliminary profiling studies, aptamers, and RNAs as potential PD biomarkers. Access to subjects for this study was via the Pacific Northwest Udall Center (PANUC) and the Alzheimer's Disease Research Center (ADRC) at the University of Washington and Oregon Health and Sciences University (OHSU). Using CSF samples from 30 well-characterized patients with PD and 30 age-, sex-matched healthy controls, we prepared RNA seq libraries and performed deep sequencing of all RNA species, including small and long RNA, mRNAs, noncoding RNAs and differentially spliced transcripts. We then tried several methods for RNAseq data analysis to optimize our analysis pipeline. We identified a total of 3381 transcripts corresponding to 182 long intergenic RNAs (LincRNAs), 11 microRNAs (miRNAs), 2861 protein-coding transcripts, 200 pseudogenes and 127 antisense RNAs; some of them were differentially expressed between PD and control groups. Selected differentially expressed RNAs have been validated in the same set of CSF samples using real-time PCR (RT-PCR). Further validations in independent, larger cohorts of samples are still ongoing. Our results obtained so far suggested that CSF proteins and RNAs could be used as good indexes for PD diagnosis and disease severity/progression. This study is a part of the NIDDS-funded Parkinson's Disease Biomarkers Program (PDBP).

Study phs000901

Multiplexing cortical brain organoids for the longitudinal dissection of developmental traits at single cell resolution

Dissecting human neurobiology at high resolution and with mechanistic precision requires a major leap in scalability, given the need for experimental designs to multiple individuals and, prospectively, population cohorts. To lay the foundation for this, we have implemented and benchmarked complementary strategies to multiplex brain organoids by pooling cells from different pluripotent stem cell lines (PSC) either during organoid generation (mosaic models) or before single cell-RNAseq library preparation (downstream multiplexing). We have also developed a new computational method, SCanSNP, and a consensus call to deconvolve cell identities, overcoming current criticalities in doublets prediction and low quality cells identification. We validated both multiplexing methods for charting neurodevelopmental trajectories at high resolution, thus linking specificity to genetic variation. Finally, we modelled their scalability across different multiplexing combinations and showed that mosaic organoids represent an enabling method for high-throughput settings. Together, this multiplexing suite of experimental and computational methods provides a highly scalable resource for disease modelling.

Study EGAS50000000698

Adult human kidney organoids originate from CD24+ cells and represent an advanced model for adult polycystic kidney disease

Adult kidney organoids have been described as strictly tubular epithelial and termed tubuloids. While the cellular origin of tubuloids has remained elusive, here we report that they originate from a distinct CD24+ epithelial subpopulation. Long-term-cultured CD24+-derived tubuloids represent a functional human kidney tubule. We show that kidney tubuloids can be used to model the most common inherited kidney disease, namely autosomal dominant polycystic kidney disease (ADPKD), reconstituting the phenotypic hallmark of this disease with cyst formation. Single-cell RNA sequencing of CRISPR/Cas9 gene-edited PKD1 and PKD2 knockout tubuloids and human ADPKD and control tissue show similarities in upregulation of disease-driving genes. Furthermore, in a proof of concept, we demonstrate that tolvaptan, the only approved drug for ADPKD, shows a significant effect on cyst size in tubuloids but no effect in a pluripotent-stem-cell-derived model. Thus, tubuloids derive from a tubular epithelial subpopulation and represent an advanced model for ADPKD disease modeling.

Study EGAS00001006551

CIDR: NINDS High Throughput Genotyping Resource Access for Structural Hindbrain Disorders

Recessive forms for many structural brain disorders (SBDs), including cerebellar hypoplasia (CBH), corpus callosum hypoplasia (CCH), cobblestone lissencephaly (COB), classical lissencephaly (LIS), microcephaly (MIC), and pontocerebellar hypoplasia (PCH), have been described. Patients usually present to the clinic with neurodevelopmental disorders (NDDs), including autism, epilepsy, intellectual disability, and cerebral palsy. Subsequent brain MRI usually leads to the diagnosis of an SBD. While a handful of genes that cause these diseases have been identified, most patients do not have mutations in these genes, suggesting that there is still much work to be done in identifying the genetic causes of these disorders. We have recruited a cohort of families with inherited SBDs, most from families with documented parental consanguinity with more than one affected member. Current approaches utilizing exome sequencing of SBD affected members still leave most cases unsolved, in part because there are too many possible variants to consider. Linkage analysis will allow us to extract all the useful genetic information from the family, taking advantage of each genetically informative meiosis in each family. We propose to analyze up to 100 SBD families for 500 samples per year for 4 years, through the CIDR SNP Genotyping Service, in parallel with already-funded exome sequencing of affects, leveraging off an already funded Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) effort to identify new causes of SBDs. Understanding the pathogenetic mechanisms underlying recessive pediatric SBDs will lead to better diagnostic and therapeutic opportunities for patients, and may shed light on complex NDDs. Ultimately, this work will identify new genetic disease loci to provide insight into pediatric SBD, with the hope to mitigate the impact of SBD worldwide.Public Health Significance: NDDs affect approximately 4-6% of the general population, most notably children, and are evident in disorders, such as intellectual disability, epilepsy, and autism, with estimated yearly costs of $51.2B for intellectual disability, $11.5B for cerebral palsy, and $2.5B for visual impairment, making up >5% of total health care costs. Recessive NDDs impose enormous personal, social, and economic costs because of the early onset and the lifetime of medical dependence that often ensues. Genetic testing is critical to the diagnosis and treatment of these diseases. Many of the diseases under study have no treatment or cure. Structural brain diseases (SBDs) underlie a large percentage of these diseases, and are defined loosely as any condition in which defects in the structure or volume of a key brain component. SBDs are divided into major categories based upon the anatomical brain location. The major types involve the anatomical structures of the developing neural tube, forebrain, hindbrain, cerebral cortex, and those affecting overall brain size. For the purposes of this application, we have excluded SBDs resulting from environmental causes (i.e. prematurity-induced), those below the brainstem, or those unlikely to be due to a germline or de novo mutation (i.e. focal SBDs or simplex disease).

Study phs002621

Evolution of the African pygmy phenotype

The evolutionary history of the human ‘pygmy’ phenotype (small body size), a characteristic of African and Southeast Asian rainforest hunter-gatherers, is largely unknown. Here we use a genome-wide admixture mapping analysis to identify 16 genomic regions that are significantly associated with the pygmy phenotype in the Batwa, a rainforest hunter-gatherer population from Uganda (East Central Africa). The identified genomic regions have multiple attributes that provide supporting evidence of genuine association with the pygmy phenotype, including enrichments for SNPs previously associated with stature variation in Europeans and for genes with growth hormone receptor and regulation functions. To test adaptive evolutionary hypotheses we computed the haplotype-based iHS statistic and the level of population differentiation (FST) between the Batwa and their agricultural neighbors, the Bakiga, for each SNP. Both |iHS| and FST values were significantly higher for SNPs within the Batwa pygmy phenotype-associated regions than the remainder of the genome, a signature of polygenic adaptation. In contrast, when we expanded our analysis to include Baka rainforest hunter-gatherers from Cameroon and Gabon (West Central Africa) and Nzebi and Nzime neighboring agriculturalists, we did not observe elevated |iHS| or FST values in these genomic regions. Together, these results suggest adaptive and at least partially convergent origins of the pygmy phenotype even within Africa, supporting the hypothesis that small body size confers a selective advantage for tropical rainforest hunter-gatherers but raising questions about the antiquity of this behavior.

Study EGAS00001000908

Kids First: Whole Genome Sequencing in Structural Defects of the Neural Tube

Myelomeningocele (aka meningomyelocele, MM) is the most severe form of spina bifida, a neural tube defect (NTD) in humans and the most common CNS birth defect. MM is considered a genetically complex disease, and occurs in 3.72/10,000 live US birth, and is partly preventable with prenatal folate, but the genetic basis and the mechanisms by which folate work to reduce disease incidence remain obscure. MM is associated nearly uniformly with prenatal hydrocephalus and the Arnold-Chiari malformation, as well as paraplegia and lifelong neuromotor disability. The genes for several rare syndromic forms of NTDs are known, but the causes for the majority with sporadic MM remain unknown. Despite the importance of MM, most previous research has been limited to targeted sequencing and association studies of folate metabolism genes, or very small-scale exome sequencing. We hypothesize that de novo mutations (DNMs) produce likely gene disrupting (LGD) events that contribution to MM risk. Using conservative estimates of between 50-100 recurrently mutated discoverable genes contributing to risk, and our preliminary data demonstrating an excess of LGD DNMs in MM compared with control individuals, we estimate that with a cohort size of 1000 trios, we should uncover between 5-20 new recurrently mutated genes underlying MM, with minimal false-discovery. With this in mind, we formed the Spina Bifida Sequencing Consortium, and established a platform for data and sample sharing. Preliminary analysis of our first batch of 100 trios analyzed by WGS from GMKF suggests a wealth of important gene mutations. We have embarked on a new recruitment effort of an additional cohort of 400 new simplex MM trios, in collaboration with the US Spina Bifida Association, consented trios to allow for data sharing, and have performed detailed sample quality control. We also have preliminary data that use of dried bloodspot DNA from trios performs comparably to whole blood DNA, so will be happy to swap saliva for bloodspot recruitment at NIH's preference. This cohort is now half-way assembled, with the remaining cohort to be ascertained in the next 6 months. We have established a workflow for de novo SNP/INDEL/SV detection from WGS and have ample computer storage and nodes to see the project to completion. We also plan to continue recruitment into the future with the goal of 2000 trios in the next 5 years. We propose a detailed bioinformatics workflow to identify gene mutations within a statistical framework, considering detailed scRNA expression profiling from developing mammalian neural tube, and have developed a robust functional validation workflow using Xenopus and mouse gene targeting. Our project has the potential to uncover a host of causes for this most common of the CNS birth defects, paving the way for future breakthroughs in detection, treatment, and prevention.

Study phs002591

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

This study is a part of NHGRI'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, >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's Hospital. The Biobank has enrolled >100K individuals to study how genes, lifestyle, and other factors affect people's health and contribute to disease.

Study phs002018

Enhancing Open Data Sharing for Functional Genomics Experiments: Measures to Quantify Genomic Information Leakage and File Formats for Privacy Preservation

This study was designed to develop methods that address the privacy risk associated with genetic variants obtained from genomic sequencing experiments. The preponderance of readily available genetic sequencing experiments has enabled the generation of datasets whose target purposes range from the genotyping of individuals for medical and forensic analyses, to the acquisition of molecular information for biological model development. However, by virtue of the experimental procedure, the raw sequences are tagged with small bits of patients' private variant information. In addition, depending on the protocol, these experiments may identify sequences from exogenous species. Raw human and microbial sequences can be analyzed as a whole to learn both general facts about biology, but can also be used to determine sensitive information about an individual. This presents a privacy conundrum for data sharing.To address privacy concerns, we have developed several mathematical and computational approaches to quantify the risk of disclosure of sensitive information from genetic sequence data, and to sanitize the associated reads in a manner that optimally maintains the utility of the data. In addition, we have generated environmental samples containing genetic information from consented individuals to evaluate the risk posed by such data. These samples were then used to assess the efficacy of the computational methods. Human-derived and -associated samples that are damaged or obscured by environmental factors represent the scope of samples used for experimentation in this study. Samples include, but were not limited to, swabs of contacted objects and glass slides coated in saliva from consented individuals. Blood samples were also acquired from the same consented individuals to create gold-standard comparison datasets.

Study phs003166

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