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• DNA methylation and the adverse metabolic outcomes of adiposity

  Overweight and obesity affect ~1.5 billion people worldwide, and are major risk factors for type-2 diabetes (T2D), cardiovascular disease and related metabolic and inflammatory disturbances.1,2 Although the mechanisms linking adiposity to its clinical sequelae are poorly understood, recent studies suggest that adiposity may influence DNA methylation,3-6 a key regulator of gene expression and molecular phenotype.7 Here we use epigenome-wide association to show that body mass index (BMI, a key measure of adiposity) is associated with widespread changes in DNA methylation (187 genetic loci at P<1x10-7, range P=9.2x10-8 to 6.0x10-46; N=10,261 samples). Genetic association analyses demonstrate that the alterations in DNA methylation are predominantly the consequence of adiposity, rather than the cause. We find the methylation loci are enriched for functional genomic features in multiple tissues (P<0.05), and show that sentinel methylation markers identify gene expression signatures at 38 loci (P<9.0x10-6, range P=5.5x10-6 to 6.1x10-35, N=1,785 samples). The methylation loci identified highlight genes involved in lipid and lipoprotein metabolism, substrate transport, and inflammatory pathways. Finally, we show that the disturbances in DNA methylation predict future type-2 diabetes (relative risk per 1SD increase in Methylation Risk Score: 2.3 [2.07-2.56]; P=1.1x10-54). Our results provide new insights into the biologic pathways influenced by adiposity, and may enable development of new strategies for prediction and prevention of type-2 diabetes and other adverse clinical consequences of obesity.

  Study EGAS00001001922

• Single cell sequencing of breast cancer T cells reveals a tissue-resident memory subset associated with improved prognosis

  The quantity of tumor infiltrating lymphocytes (TILs) in breast cancer (BC) is a robust prognostic factor for improved patient survival particularly in triple negative and HER2-overexpressing BC subtypes. Whilst T cells are the predominant TIL population, the relationship between quantitative and qualitative differences in T cell subpopulations and patient prognosis remains unknown. We performed single-cell RNA sequencing (scRNA-seq) of 6311 T cells isolated from human BCs, and show for the first time that significant heterogeneity exists in the infiltrating T cell population. We demonstrated that high TIL BCs contained significant numbers of CD8+ T cells with features of tissue-resident memory T (TRM) cell differentiation and that these CD8+ TRM cells expressed high levels of immune checkpoint molecules and effector proteins. A CD8+ TRM gene signature developed from the scRNA-seq data was significantly associated with improved patient survival in early-stage triple negative breast cancer (TNBC) and provided better prognostication compared with CD8 expression alone. Our data suggests that CD8+ TRM contribute to BC immunosurveillance and are the key targets of modulation through immune checkpoint inhibition. Further understanding of the development, maintenance and regulation of TRM cells will be crucial for successful immunotherapeutic development in BC.

  Study EGAS00001002845

• A GWAS of Progression in Multiple Sclerosis

  This is a genome wide association study (GWAS) of disease progression in multiple sclerosis (MS). The study involved a total of 12584 cases recruited from multiple centres around the world and tested at 7.8 million common autosomal single nucleotide variants. The data from the European cases (n=4853) are included in this EGA submission in 10 country specific data sub-sets.

  Study EGAS00001007162

• Study of Addiction: Genetics and Environment (SAGE)

  This study is part of the Gene Environment Association Studies initiative (GENEVA) funded by the National Human Genome Research Institute. The overarching goal is to identify novel genetic factors that contribute to addiction through a large-scale genome-wide association study of DSM-IV alcohol dependent (and frequently illicit drug dependent) cases and non-dependent, unrelated control subjects of European and African American descent. The focus of this proposal is a case-control design of unrelated individuals for a genetic association study of addiction. Cases are defined as individuals with DSM-IV alcohol dependence (lifetime) and potentially other illicit drug dependence. In addition to the categorical diagnosis, we have data on ordinal measurements of number of DSM-IV symptoms for alcohol, nicotine, marijuana, cocaine, opiates and other drugs so that we will able to construct quantitative measurements of addiction severity over a wide range of substances. Controls are defined as individuals who have been exposed to alcohol (and possibly to other drugs), but have never met lifetime diagnosis for alcohol dependence or dependence on other illicit substances. Analyses that include refinement of the phenotype and incorporation of important demographic and environmental factors into association studies will be pursued. Cases and controls were selected from three large, complementary datasets: the Collaborative Study on the Genetics of Alcoholism (COGA), the Family Study of Cocaine Dependence (FSCD), and the Collaborative Genetic Study of Nicotine Dependence (COGEND). COGA: COGA was initiated in 1989 and is a large-scale family study that has had as its primary aim the identification of genes that contribute to alcoholism susceptibility and related characteristics. COGA is funded through the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Subjects were recruited from 7 sites across the U.S. Alcohol dependent probands were recruited from treatment facilities and assessed by personal interview. After securing permission, other family members were also assessed. A set of comparison families was drawn from the same communities as the families recruited through the alcohol dependent probands. Assessment involved a comprehensive personal interview developed for this project, the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA), which gathers detailed information on alcoholism related symptoms along with other drugs and psychiatric symptoms. Families with three or more first-degree relatives who were alcohol dependent were invited for more extensive testing, including neurophysiology evaluations (ERPs and EEGs) and a battery of neuropsychological assessments. Blood was obtained for genetic studies. Institutional Review Boards at all sites approved the protocols, including sharing in the NIAAA national repository. COGA has four Co-Principal Investigators Bernice Porjesz, Victor Hesselbrock, Howard Edenberg, and Laura Bierut. COGA includes nine different centers where data collection, analysis, and storage take place. The nine sites and Principal Investigators and Co-investigators are: University of Connecticut (Victor Hesselbrock); Indiana University (Howard Edenberg, John Nurnberger, Jr., Tatiana Foroud); University of Iowa (Samuel Kuperman); SUNY Downstate (Bernice Porjesz); Washington University in St. Louis (Laura Bierut, Alison Goate, John Rice); University of California at San Diego (Marc Schuckit); Howard University (Robert Taylor); Rutgers University (Jay Tischfield); Southwest Foundation (Laura Almasy). Q. Max Guo serves as the NIAAA Staff Collaborator. This national collaborative study is supported by the NIH Grant U10AA008401 from the National Institute on Alcohol Abuse and Alcoholism (NIAAA) and the National Institute on Drug Abuse (NIDA). Family Study of Cocaine Dependence (FSCD): This project was initiated in 2000 as a case-control family study of cocaine dependence funded through the National Institute on Drug Abuse (NIDA; PI: Laura Bierut). The primary goal was to increase the understanding of the familial and non-familial antecedents and consequences of cocaine dependence. Cocaine dependent individuals were systematically recruited from chemical dependency treatment units (both public and private; residential and outpatient) in the greater St. Louis metropolitan area. Community based control subjects were identified through a Missouri Driver's License Registry (maintained at Washington University for research purposes) and matched by age, race, gender, and residential zip code. As a supplement to this project, blood samples were collected for future genetic analysis and were included in the NIDA Genetics Consortium. Phenotypic data, DNA, and cell lines are in the NIDA Center for Genetics Studies. Collaborative Genetic Study of Nicotine Dependence (COGEND): COGEND was initiated in 2001 as a three-part program project grant funded through the National Cancer Institute (NCI; PI: Laura Bierut). The three projects included a study of the familial transmission of nicotine dependence, a genetic study of nicotine dependence, and a study of the relationship of nicotine dependence with nicotine metabolism. The primary goal is to detect, localize, and characterize genes that predispose or protect an individual with respect to heavy tobacco consumption, nicotine dependence, and related phenotypes and to integrate these findings with the family transmission and nicotine metabolism findings. The primary design is a community based case-control family study. All subjects were recruited from Detroit and St. Louis. Nicotine dependent cases and non-dependent smoking controls were identified and recruited. In addition, one sibling for each case and control subject was recruited in a subset of the sample. Over 56,000 subjects aged 25-44 years were screened by telephone, over 3,100 subjects were personally interviewed, and over 2,900 donated blood samples for genetic studies. All three studies (COGA, COGEND, FSCD) include measures of basic socio-demographic variables, including age, sex, race/ethnicity, family income, educational attainment, religious participation, and family structure. Other important covariates and/or potential moderators of genetic effects include comorbid addictions and age at initiation of use for cigarettes, alcohol and drugs. The assessments also include measures of various life stressors, such as physical and sexual abuse, which have been implicated in gene-environment interactions for several disorders. Coding for both individual variables and indices has been standardized across studies. All subjects were assessed in person by trained research assistants. Funding support for genotyping, which was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR), was provided by the NIH GEI (U01HG004438), the National Institute on Alcohol Abuse and Alcoholism, the National Institute on Drug Abuse, and the NIH contract "High throughput genotyping for studying the genetic contributions to human disease"(HHSN268200782096C). Note for Publications Related to Study: The Study of Addiction: Genetics and Environment (SAGE) has not yet generated publications. Below is a listing of publications related to the three studies from which the SAGE sample was selected. COGA has over 228 publications listed at www.niaaagenetics.org This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to addiction through a large-scale genome-wide association study of DSM-IV alcohol dependent (and frequently illicit drug dependent) cases and non-dependent, unrelated control subjects of European and African American descent. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000092

• Robust methylation-based classification of brain tumours using nanopore sequencing

  Background: DNA methylation-based classification of cancer provides a comprehensive molecular approach to diagnose tumours. In fact, DNA methylation profiling of human brain tumours already profoundly impacts clinical neuro-oncology. However, current implementations using hybridization microarrays are time-consuming and costly. We recently reported on shallow nanopore whole-genome sequencing for rapid and cost-effective generation of genome-wide 5-methylcytosine profiles as input to supervised classification. Here, we demonstrate that this approach allows to discriminate a wide spectrum of primary brain tumours. Results: Using public reference data of 82 distinct tumour entities, we performed nanopore genome sequencing on N=382 tissue samples covering 46 brain tumour (sub)types. Using bootstrap sampling in a cohort of N = 56 cases, we find that a minimum set of 1,000 random CpG features is sufficient for high-confidence classification by ad hoc random forests. We implemented score recalibration as confidence measure for interpretation in a clinical context and empirically determined a platform-specific threshold in a randomly sampled discovery cohort (N = 185). Applying this cut-off to an independent validation series (N = 184) yielded 148 classifiable cases (sensitivity 80.4%) and demonstrated 100 % specificity. Cross-lab validation demonstrated robustness with concordant results across four laboratories in 10/11 (90.9%) cases. In a prospective benchmarking (N = 15), median time to results was 21.1 hours. Conclusions: In conclusion, nanopore sequencing allows robust and rapid methylation-based classification across the full spectrum of brain tumours. Platform-specific confidence scores facilitate clinical implementation for which prospective evaluation is warranted and ongoing.

  Study EGAS00001006540

• ALS Compute

  Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disorder characterized by the progressive loss of brain and spinal cord motor neurons. Half of ALS patients display cognitive symptoms of frontotemporal dementia (FTD); reciprocally, about 40% of FTD patients show motor neuron deficits, and approximately 15% develop overt ALS. The clinical overlap between ALS and FTD means that the two conditions are thought to represent a disease spectrum (ALS/FTD). In recent years, the identification of several genetic causes of ALS/FTD has contributed significantly to our understanding of disease pathogenesis. Unfortunately, one-third of the underlying genetic causes of familial cases and ~90% of sporadic cases of ALS/FTD remain unexplained. As such, there is a dire need to identify additional genetic factors contributing to ALS/FTD. Such studies require huge cohorts of harmonized whole genome sequencing (WGS) data sets from cases and controls. Currently, there are several major ongoing sequencing efforts for ALS patients. Numerous centers lead to inefficiency, especially in terms of overall costs. At a minimum, this includes the cost of high-performance computing, the storage of large data files, and the duplication of effort between groups. This lack of data harmonization between groups precludes sharing of genetic information and weakens collaborative efforts. The cost and logistics are also a barrier to attracting talented investigators to the ALS/FTD field. To overcome this unmet need, we have founded the ALS Compute project. We are centralizing the storage of ALS/FTD WGS data from every significant sequencing effort in the United States and beyond within a single Cloud environment. This approach will facilitate data harmonization and improve accessibility to the data. To accomplish this, we have made the data and the computational infrastructure available via the Terra platform hosted by NHGRI's Genomic Data Science Analysis, Visualization, and Informatics Lab-Space (AnVIL). This will allow researchers worldwide to access this wealth of data, develop new theories of the disease, and yield breakthroughs in our understanding of ALS/FTD.

  Study phs003184

• ICGC Oesophageal adenocarcinoma - tumour samples

  The oesophageal project will focus on adenocarcinoma which is increasing in incidence in the UK and other developed countries and has a very poor outcome. The primary aims of this project are to deeply sequence tumour and normal genomic DNA (including the precursor condition Barrett’s oesophagus when material is available) to provide a comprehensive catalogue of somatic mutations. This will be achieved through a UK-wide network of hospitals involved in a research collaboration called the OCCAMS consortium. The goal of this project is to use high quality clinical material with accurately annotated clinic-pathological, treatment and outcome data.

  Study EGAS00001000725

• Association of Age at Diagnosis and Genetic Mutations in Patients with Neuroblastoma

  Neuroblastoma is diagnosed over a wide age range from birth through young adulthood, and older age at diagnosis is associated with a decline in survivability. We performed whole genome sequencing of DNA from diagnostic tumors and their matched germlines from 40 patients with metastatic neuroblastoma obtained between 1987 and 2009. To identify genetic lesions that are associated with age at diagnosis in patients with metastatic neuroblastoma. Age groups at diagnosis included infants (0-18 months), children (18 months-12 years), and adolescents and young adults (>12 years). To confirm the findings from this discovery cohort, validation testing using tumors from an additional 64 patients obtained between 1985 and 2009 was also performed. Formalin-fixed paraffin-embedded tumor tissue was used for immunohistochemistry and fluorescent in situ hybridization. Telomere lengths were analyzed using the whole genome sequencing data, quantitative polymerase chain reaction and fluorescent in situ hybridization

  Study EGAS00001000213

• Genome-wide discovery of somatic coding and regulatory variants in Diffuse Large B-cell Lymphoma

  Diffuse large B-cell lymphoma (DLBCL) is an aggressive cancer originating from mature B-cells. Prognosis is strongly associated with molecular subgroup, although the driver mutations that distinguish the two main subgroups remain poorly defined. Through an integrative analysis of whole genomes, exomes, and transcriptomes, we have uncovered genes and non-coding loci that are commonly mutated in DLBCL. Our analysis has identified novel cis-regulatory sites, and implicates recurrent mutations in the 3'UTR of NFKBIZ as a novel mechanism of oncogene deregulation and NFκB pathway activation in the activated B-cell (ABC) subgroup. Small amplifications associated with over-expression of FCGR2B (the Fcγ receptor protein IIB), primarily in the germinal centre B-cell (GCB) subgroup, correlate with poor patient outcomes suggestive of a novel oncogene. These results expand the list of subgroup driver mutations that may facilitate implementation of improved diagnostic assays and could offer new avenues for the development of targeted therapeutics.

  Study EGAS00001002936

• High-Resolution Spatial Transcriptomics Uncover Epidermal-Dermal Divergences in Merkel Cell Carcinoma: Spatial Context Reshapes the Gene Expression Landscape

  Merkel cell carcinoma (MCC) is an aggressive malignancy with neuroendocrine differentiation marked by high plasticity, often manifesting as rapid therapy resistance. Although the cell-of-origin is presumed to be epithelial, epidermal localization of MCC is rarely observed, largely because in situ MCC is typically an incidental finding. Nevertheless, a subset of MCC tumors exhibits epidermotropism, wherein tumor cells are present in the epidermis. The behavior of cancer cells is profoundly influenced by the tumor microenvironment and interactions with neighboring cells. Notably, the normal counterparts of the cancer’s cell-of-origin have been shown to attenuate tumor aggressiveness. Thus, epidermotropic MCC presents a unique opportunity to explore the potential role of surrounding keratinocytes in modulating tumor cell behavior. While the epidermotropic tumor nests share histological resemblance with their dermal counterparts, their transcriptomic profiles remain unexplored. Here, we employed high-definition spatial and single cell transcriptomics to dissect the gene expression profiles of epidermotropic MCC cells, comparing them to MCC cells in the tumor core and those adjacent to blood vessels. Notably, epidermotropic MCC cells exhibit a transcriptomic signature reminiscent of cutaneous squamous cell carcinoma, characterized by upregulation of genes encoding keratins, S100A proteins, as well as calmodulin-like proteins 3 and 5. Mechanistically, this keratinocytic differentiation is associated with enhanced p63 activity, leading to the upregulation of PERP. Collectively, our study demonstrates that MCC cells can adopt a keratinocytic differentiation program in response to microenvironmental cues, underscoring the remarkable phenotypic plasticity of this malignancy and the importance of the tumor microenvironment for tumor characteristics.

  Study EGAS00001008157