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• 'IL-17A-Producing ILC3s and Duodenal Adenoma in FAP'

  Familial Adenomatous Polyposis (FAP) is a hereditary tumor syndrome that significantly enhances the risk of duodenal adenomas, with variations observed even among carriers of the same genetic variant. In this study, intestinal ILCs were isolated from 82 FAP and 26 non-FAP patients and analyzed through flow cytometry, qRT-PCR, and bulkRNA-sequencing. The data revealed a heightened frequency of ILC3s in FAP patients, and increased IL-17A production of duodenal NKp44(-)ILC3s was associated with FAP. Significant elevations in IL1B, IL23A, and DLL4 mRNA expression levels were found in FAP duodenal adenoma tissue, along with enhanced expression of DUOX2 and DUOXA2. The results suggest the involvement of IL-17A-producing NKp44(-)ILC3s in duodenal adenoma formation in FAP.

  Study EGAS00001007347

• Genotyping_data_total

  Genotyping data for ACE2 (rs2285666), MX1 (rs469390) and TMPRSS2 (rs2070788) variants. Patients are classified as mild (n=34) and severe (n=32). DNA genotyping was performed using the TaqMan® Genotyping Master Mix (Applied Biosystems). Allelic discrimination assays were performed on a 7900HT Fast Real-Time PCR System (Applied Biosystems).

  Dataset EGAD00010002445

• Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC)

  In 2016 we established the Sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC) funded by the Ice Bucket Challenge Grant administered by the Motor Neurone Disease Research Institute of Australia. The goals of the SALSA-SGC are to collect biological samples from clinics across Australia with matched in depth clinical and self-report phenotypes and to generate multiple levels of genetic and genomic data. In this first data generation exercise of the SALSA-SGC the majority of the samples were collected prior to the formal establishment of SALSA-SGC from clinics across Australia.Briefly, the cohort includes the University of Sydney’s Australian Motor Neuron Disease DNA Bank (MND Bank) cohort recruited April 2000 to June 2011), with study protocol approved by the Sydney South West Area Health Service Human Research Ethics Committee (HREC). Cases were recruited from around Australia via state-based MND associations with diagnosis verified by a neurologist. The remainder of the cases were recruited from clinics across Australia between 2015 and 2017 under HREC approvals from Royal Brisbane and Women’s Hospital, Macquarie University Multidisciplinary Motor Neurone Disease Clinic,  Calvary Health Care Bethlehem in Melbourne , Fiona Stanley Hospital in Perth, and from 2016 under HREC approvals at each site for the sporadic ALS Australia Systems Genomics Consortium (SALSA-SGC). The ALS cases were diagnosed with definite or probable ALS according to the revised El Escorial criteria. Some controls were recruited as either partners or friends of patients, healthy individuals free of neuromuscular diseases. We are providing GWAS and MWAS data in this dataset. Individual level GWAS data were generated using Illumina Infinium CoreExome-24 version 1.1 chips for N= 846 cases and N=665 controls. Individual MWAS data was generated using the Illumina Human methylation 450K array for N=782 cases and N=613 controls. There 1315 individuals where GWAS and MWAS data has been generated and is available. Further information on these data sets can be found: Paper 1: Restuadi, R, Garton, FC, Benyamin, B, Lin, T, et al. Amyotrophic Lateral Sclerosis Genetic Correlation with Cognitive Performance, educational attainment and schizophrenia: evidence from polygenic risk score analysis. (submitted) Paper 2: Nabais, MF, Lin, T, Benyamin, B et al. Significant out-of-sample classification from methylation profile scoring for amyotrophic lateral sclerosis. 2020. NPJ genomic medicine. 5(10). Files provided in this submission include: GWAS: This folder contains QCed genotype for the Australian ALS case-control cohort. Contains PLINK files for genotyping data (not imputed yet). The individuals selected here have: good consistency on phenotype data ethics approval registered as part of sporadic ALS studies unrelated by GRM cut-off 0.05 No ancestry QC yet MWAS: This folder contains the IDAT and post-QC normalized DNAm (beta) for the Australian ALS case-control cohort. 2019_AUS_ALS_PCTG_DNAm.tar.gz - IDATS for 1315 individuals analyzed in the MWAS study normalized_beta_values - Binary files (created with the OSCA software) containing information on the individuals, probes and the DNAm (beta) values obtained after QC phenotype_file - contains all the covariates analysed in the MWAS including: case-control status, coded 0 = Control and 1 = ALS, predicted age, predicted cell-type proportions, predicted smoking scores, slide and chip position and sex Important Notes: The DNAm data were normalized together with samples that were not part of this ALS case/control study and thus, the normalization procedure may not be 100% reproducible using only the IDAT files uploaded here. Summary data has been made publicly available and can be accessed directly: Data collection and sample processing were performed at several clinics across Australia. Genotyping and DNA methylation arrays were performed by the Human Studies Unit, at the Institute for Molecular Bioscience (University of Queensland). Quality control of the genotypic, phenotypic and DNA methylation data was done by the Program of Complex Traits Genomics, at the Institute for Molecular Bioscience (University of Queensland).

  Study phs002068

• The Mutational Landscape of CTCL and Sezary Syndrome

  Sezary syndrome is a leukemic and aggressive form of cutaneous T-cell lymphoma (CTCL) resulting from the malignant transformation of skin-homing central memory CD4+ T cells. To identify new genetic alterations involved in Sezary syndrome and CTCL transformation we performed whole-exome sequencing of tumor-normal sample pairs from 26 Sezary syndrome and 16 CTCL patients. These analyses revealed a distinctive pattern of somatic copy number alterations in Sezary syndrome including highly prevalent recurrent chromosomal deletions involving the TP53, RB1, PTEN, DNMT3A, and CDKN1B tumor suppressor genes. Mutation analysis identified a broad spectrum of somatic mutations involving key genes involved in epigenetic regulation (TET2, CREBBP, MLL3, BRD9, SMARCA4 and CHD3) and signaling, including mutations in MAPK1, BRAF, CARD11 and PRKG1 driving increased MAPK, NFKB and NFAT activity upon T-cell receptor stimulation. Collectively, our findings provide new insights into the genetics of Sezary syndrome and CTCL and support the development of personalized therapies targeting key oncogenically activated signaling pathways for the treatment of these diseases.

  Study phs000994

• Molecular stratification of endometrioid ovarian carcinoma predicts clinical outcome

  Endometrioid ovarian carcinoma (EnOC) is an under-investigated type of ovarian carcinoma. Here, we report the largest genomic study of EnOCs to date, performing whole exome sequencing of 112 cases following rigorous pathological assessment. High frequencies of mutation were detected in CTNNB1(43%), PIK3CA(43%), ARID1A(36%), PTEN(29%), TP53(26%) and SOX8(19%), a novel target of recurrent mutation in EnOC. POLE and mismatch repair protein-encoding genes were mutated at lower frequency (6%, 18%) with significant co-occurrence. A molecular taxonomy was constructed using a novel algorithm (PRISTINE), identifying clinically distinct EnOC subtypes: TP53m cases demonstrated greater genomic complexity, were frequently FIGO stage III/IV at diagnosis (48%) and incompletely debulked (44%), and demonstrated inferior survival; conversely, CTNNB1m cases demonstrated low complexity and excellent clinical outcome, were predominantly stage I/II at diagnosis (89%) and completely resected (87%). Tumour complexity provides further resolution within the TP53wt/CTNNB1wt group. Moreover, we identify the WNT, MAPK/RAS and PI3K pathways as good candidate targets for molecular therapeutics in EnOC.

  Study EGAS00001004366

• Analyzing Somatic Mutagenesis in Systemic Sclerosis

  The study was undertaken with the aim of estimating differences in the mutational burden in lung tissues from healthy vs systemic sclerosis (SSc) patients. SSc is an auto-immune disease, with patients often developing cancer. However, the etiology of this phenomenon is poorly understood. As such we sought to uncover potential molecular mechanisms prevalent within SSc tissues that might be potentiating cancer. Samples were randomly collected from individuals from two broad ethnic groups, European (EA) and African American (AA). In total, samples were obtained from 7 individuals belonging to the EA group and 4 individuals from the AA group. For this study, ethnicity was not included as a confounding variable, given that the data set has roughly comparable number of individuals from both ethnicities for the healthy and SSc cohorts. Study participants ranged in age from 37-63 years old. Median age (52 years old) of healthy individuals was comparable to the SSc cohort (~48 years old). Participants were self-described as current/former smokers or non-smokers. Lung tissues were obtained under a protocol approved by the University of Pittsburgh Institutional Review Board. Written informed consent statements were provided to the University of Pittsburgh IRB by the study participants/patients. Sample sizes were determined by the ability of bulk lung fibroblast tissues to stably propagate in culture until single cell clones could be obtained. Samples for which sufficient cell density could not be achieved for downstream high-depth sequencing analysis were excluded from the study and are not reported. Five or greater than 5 samples are collected from each cohort including healthy and SSc patients. Subjects were allocated to two basic cohorts based on diagnosis at the time of explant. Participants with no reported lung anomalies were allocated to the "healthy" cohort, whereas individuals with reported lung abnormalities, primarily SSc with pulmonary fibrosis and/or hypertension were allocated to the "SSc" cohort. All tissue samples were cultured, propagated and processed in identical fashion without requiring individual-specific protocols. Additionally, equivalent amounts of DNA were used for preparing sequencing libraries from both cohorts, and all samples were sequenced using Illumina whole genome sequencing (WGS) and analyzed using identical computational pipelines. Our study primarily discovered that there is a significantly higher burden of somatic mutations in SSc samples, compared to healthy samples. We observed an overall increase in a range of mutations in genomes of SSc patients, including single base substitutions, indels, structural variants and copy number alterations. Additionally, we uncovered a novel mutation signature associated with SSc samples, hinting at the activity of POLH in these samples, and highlighting the potential nexus between inflammation, DNA damage, and cancer.

  Study phs003700

• DNA methylation database for gynecological cancer detection, classification and assay development

  MeD-seq data (fastq files) from gynecological cancers and associated healthy tissues. In total 292 fastq files generated by MeD-seq are deposited consisting of: healthy tissues (vulva n=11, cervix n=15, endometrium n=13, fallopian tube n=18 and ovary n=13), precursor lesions of cancer (vulva n=23 and cervix n=46) and cancer (vulva n=21, cervix n=45, endometrium n=26, fallopian tube n=8 and ovary n=33)

  Dataset EGAD50000000611

• Integrated genomic analysis for HCC

  Liver cancer is a common malignancy and is the third cause of cancer-related death in the world and hepatocellular carcinoma (HCC) is the major type of liver cancer, accounting for ~90% of cases. Only 20 ~ 30% of patients can benefit from combined immunotherapy and targeted therapy due to the high inter-tumor heterogeneity of HCC. This work aims to identify homogeneous and robust molecular subtypes in HCC based on a large, homogenous and well-annotated cohort. We performed whole genome/exome sequencing (WGS/WES) and/or RNA sequencing (RNA-seq) on 529 HCC from 461 patients collected mainly in France. Based on the great consistence between genomic and transcriptomic data, we identified 9 robust HCC subtypes mainly based on driver mutations. And we further characterized HCC subtypes using genomic, transcriptomic and clinicopathological features. Among 9 subtypes, 5 subtypes belonged to chromosome instable tumors, while 3 subtypes belonged to chromosome stable tumors. In addition, our subtypes were associated with prognosis and we also found different distributions of subtypes across various features, such as etiology and gender. Our study provided a robust molecular classification based on a large HCC dataset from Western country, it improves our understanding of the mechanisms of carcinogenesis and will facilitate development of genome-based precision medicine in HCC.

  Study EGAS00001007957

• The Sea Islands Genetic Network (SIGNET): Identifying genetic contributors to diabetes and dyslipidemia in African Americans

  Recent genome-wide association studies (GWAS) have successfully identified genetic variants that influence diabetes risk in European populations, however most do not have a major impact on diabetes risk in populations of African descent. The African American (AA) population from the Sea Islands of coastal South Carolina and Georgia has high rates of type 2 diabetes, low levels of admixture, and in general, consume a diet rich in saturated fats. We postulate that this unique combination of ancestral and environmental factors results in a more consistent penetrance of diabetes risk alleles, as well as enrichment of risk alleles of African origin. The existing DNA samples and rich phenotypic data from the Sea Island Families Project comprise a unique resource for genetic studies of type 2 diabetes and related metabolic traits such as dyslipidemia. Our central hypothesis is that the increased risk for T2DM in AA compared with European American (EA) is due, in part, to susceptibility alleles of African origin, and that these alleles can be identified using a GWAS. The Specific Aims are to: 1) Identify genetic risk factors for type 2 diabetes utilizing DNA samples and data from the Sea Island Families Project, Reasons for Geographic and Racial Differences in Stroke (REGARDS) Study recruited from SC, GA, NC, and AL; and a GWAS approach; 2) Identify genetic contributors to lipoprotein subclasses in African Americans using the lipoprotein subclass profile (particle size and concentration for multiple subclasses of VLDL, LDL, and HDL) assessed by NMR at LipoScience, Inc., and the GWAS data from Aim 1. The rationale for this project is that identification and validation of novel pathophysiological pathways and informed selection of candidate genes for diabetes risk will inform development of new, targeted prevention and treatment strategies in this underserved, high risk population.

  Study phs000433

• Substance Dependence GWAS in European- and African - Americans

  This study includes SSADDA (Semi Structured Assessment for Drug Dependence and Alcoholism) assessed subjects (mostly unrelated, but including some affected sibling pairs) recruited in the course of several substance dependence genetics projects. The sample includes 1,531 self-reported African-American (AA) subjects, 1,339 self-reported European-American (EA) subjects, and 2 who reported race as "unknown" or "missing".

  Study phs000952