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• Genome-wide search to find the genetic elements underlying visual contour perception

  Contour integration is a key function of the visual system to deal with occlusion and discontinuity in natural scenes. The current study is the first one to investigate the genetic basis of this visual function in humans. A total of 2619 normal participants were tested on their ability to detect continuous contours embedded in a cluttered background with a standard psychophysical protocol. Multi-level genomic analysis was performed, involving heritability estimation based on single nucleotide polymorphism (SNP) and association testing at SNP and gene levels.

  Study EGAS00001003639

• Human adipose tissue immune cells

  We describe a novel and conserved Trem2+ lipid-associated macrophage (LAM) subset and identify markers, spatial localization, origin, and functional pathways associated with these cells. Genetic ablation of Trem2 in mice globally inhibits the downstream molecular LAM program, leading to adipocyte hypertrophy as well as systemic hypercholesterolemia, body fat accumulation, and glucose intolerance. These findings identify Trem2 signaling as a major pathway by which macrophages respond to loss of tissue-level lipid homeostasis, highlighting Trem2 as a key sensor of metabolic pathologies across multiple tissues and a potential therapeutic target in metabolic diseases.

  Study EGAS00001003725

• Gene signature for predicting homologous recombination deficiency in triple-negative breast cancer

  We developed a gene expression-based classifier for homologous recombination deficiency (HRD) in breast cancer patients using WES and RNA-seq data obtained from 94 TNBC samples from a Malaysian hospital-based cohort (MyBrCa). This classifier was able to predict for high levels of a mutational signature associated with HRD in an additional MyBrCa TNBC validation cohort (this EGA study) as well as in TNBCs from TCGA. We also validated the classifier on a NanoString platform with both fresh frozen and FFPE tissue.

  Study EGAS00001006518

• Methylation Biomarkers can Distinguish Pleural Mesothelioma from Healthy Pleura and other Pleural Pathologies

  Pleural mesothelioma (PM) is a rare cancer type. This study developed a methylation-based biomarker assay to distinguish PM from healthy pleura and other pleural conditions. By analyzing methylation data, 744 hypermethylated CpG sites specific to PM were identified and validated with high accuracy. Using the bisulfite-free IMPRESS technique, the assay was further validated in a diverse cohort, showing strong performance in distinguishing tumoral from non-tumoral samples and PM from pleural metastases. These findings support the assay’s potential as a robust diagnostic tool for PM.

  Study EGAS00001008153

• Genetic Analysis of Parkinson's Disease

  A portion of the sample includes multiplex PD families recruited as part of a previously funded study (R01NS037167; PI: Tatiana Foroud). Families were ascertained initially through a living affected sibling pair. Subsequently, ascertainment was loosened to include PD probands having a positive family history of PD in a first degree relative, who was not required to be part of the study. All individuals completed an in-person evaluation at one of the > 65 Parkinson Study Group sites participating in this study. Individuals completed a detailed evaluation that included the Unified Parkinson Disease Rating Scale (UPDRS), Mini-Mental State Examination (MMSE), Geriatric Depression Scale (GDS) and a diagnostic checklist that implemented the UK PD Brain Bank inclusion and exclusion criteria. An autopsy program was established in this study and brain tissue for confirmation of diagnosis and further experimental study are available from over 100 participants. Autopsy confirmation of the PD diagnosis was nearly 100% for those who met UK PD Brain Bank criteria. In addition, because this was a cross sectional study and family members were often seen very early in disease course, among those who did not meet UK PD Brain Bank criteria but had a subsequent autopsy, a significant subset (>1/3) had autopsy confirmation of PD. The second source of samples is from the NINDS Human Genetics DNA and Cell Line Repository located at the Coriell Institute. Currently DNA from 4,509 PD patients is available from the Coriell Institute. We restricted the selected sample to include only Caucasians and ensured there was no overlap with samples contributed by the PROGENI Study.

  Study phs001004

• Blood Transcriptome Profiling Following Seizures

  The retrospective diagnosis or confirmation of a seizure, after the event, is very challenging. Many times clinicians can only use a patient's self-reported history. To further complicate the diagnosis, it is known that 20-30% of patients reporting a seizure actually suffer from psychogenic non-epileptic seizure (PNES). The patient has the behavior of a seizure, but does not suffer from brain seizure activity. Considerable time and resources are used to monitor PNES, and many patients undergo unnecessary therapy with anti-epileptic drugs. These resources could be more effectively used if we could confirm a seizure after the event (retrospective diagnosis). Here we propose a novel approach to distinguish seizures from PNES after the seizure event has happened.We have developed an accurate blood biomarker technology to diagnose acute brain injury, and assess chronic progression following brain injury. Previous studies support the premise that seizures affect blood RNA expression; here we assess temporal RNA expression pattern changes following seizure. We present preliminary preclinical data showing the discrimination of electric-stimulation evoked animal seizures. Here, we validate this maturing technology to assist with the discrimination of epileptic seizures from psychogenic non-epileptic seizures. We will analyze blood samples from patients undergoing video EEG monitoring in an epilepsy monitoring unit (Emory University Hospital, Atlanta GA). We expect 20% of these patients will have PNES. Once a patient has an EEG verified seizure, we will collect blood at various time points and identify biomarker RNA molecules in the blood. Blood samples will be collected from patients with non-verified seizures as control. These RNA expression values will be used to develop a predictive test for the occurrence of seizures. A biomarker gene panel will be developed from this exploratory project for validation in a larger patient population.

  Study phs003460

• Genetic diversity and continuity of the population of the UAE

  With high consanguinity rates on the Arabian Peninsula, it would not have been unexpected if the population of the UAE was shown to be relatively homogenous. However, this study of 1,000 UAE nationals, provided a contrasting perspective, one of a relatively heterogeneous population. Located at the apex of Europe, Asia and Africa, the observed diversity could be explained by a plethora of migration patterns since the first Out-of-Africa movement. A strategy to explore the extent of genetic variation of the population of the UAE is presented. The first step involved a comprehensive population stratification study that was instructive for subsequent Whole Genome Sequencing (WGS) of suitable representatives (which is described elsewhere). When this UAE data was compared to previous smaller studies from the region, the findings were consistent with a population that is a diverse and admixed group of people. However, rather than sharp and distinctive clusters, a continuous genotype distribution was observed. The analysis showed a continuous gradient of ancestral populations, suggesting that admixture on the south eastern tip of Arabian Peninsula occurred gradually. When visualized using a unique technique that combined admixture ratios and Principal Component Analysis (PCA), unappreciated diversity was revealed while mitigating projection bias of conventional PCA. The analytical strategy used here highlights the complementary nature of data from genotype array and WGS for anthropological studies. Specifically, genotype array data was instructive to select representative subjects for WGS. Furthermore, from the 2.3 million allele frequencies obtained from genotype arrays, we identified 46,481 loci with allele frequencies that were significantly different with respect to other world populations. This comparison of allele frequencies facilitates variant prioritization in common diseases. In addition, these loci bear great potential as biomarkers in anthropological and forensic studies.

  Study EGAS00001004362

• Tanzania dietary intervention study 2019-2020

  We performed a dietary intervention study comparing western diet, traditional diet and the supplementation of fermented banana beverage in a cohort of 66 individuals (22 in each study arm)

  Study EGAS50000000317

• Elucidation of disease state by multi-layered omics analysis

  We performed a comprehensive metagenome-wide association study by utilizing whole-genome shotgun sequencing. We elucidated a gut microbiome???s role in human biology of the Japanese population.

  Study JGAS000205

• SureTypeSC - accurate genotyping of single-cell SNP array data

  We used a collection of single cells from two Coriell cell lines to train and validate a machine learning method for quality assessment of the single cell genotypes

  Study EGAS00001004621

• Germline DNMT3A mutation in mother-son pair with AML

  A mother/son pair with adult onset diploid AML were evaluated and found to have a dominant negative germline mutation in DNMT3A that is associated with global hypomethylation

  Study EGAS00001002940

• Correction of a Factor VIII genomic inversion with designer recombinases

  PromethION-based whole genome sequencing of endothelial cells differentiated from patient derived induced pluripotent stem cells (iPSCs) of a hemophilic donor, transiently treated with a Cre recombinase, a RecF8 recombinase, and untreated cells. The dataset contains fastq files with all sequencing reads passing the standard quality filtering.

  Dataset EGAD00001007923

• MutaSeq data for A.10-12

  MutaSeq was applied to CD34+ cells from patient samples A.10, A.11 and A.12 of the study. The protocol followed is described in https://doi.org/10.1038/s41467-021-21650-1 and in the methods of the manuscript

  Dataset EGAD00001010189

• Transdisciplinary Research Into Cancer of the Lung (TRICL) - Exome Plus Targeted Sequencing

  The study was conducted under the auspices of the Transdisciplinary Research In Cancer of the Lung (TRICL) Research Team, which is a part of the Genetic Associations and MEchanisms in ONcology (GAME-ON) consortium, and associated with the International Lung Cancer Consortium (ILCCO). Ethics All participants provided written informed consent. All studies were reviewed and approved by institutional ethics review committees at the involved institutions. Sequencing data are derived from four sub-studies. The sub-studies that contributed include Harvard, Liverpool, Toronto, and IARC. The IARC and Toronto studies are described above. A description of the Harvard and Liverpool studies is provided below. Liverpool Lung Project: The Liverpool Lung Project (LLP)1 is a case control and cohort study, which has over 11,500 individuals, with detailed epidemiological, clinical and outcome data with associated specimens (i.e. tumour tissue, blood, plasma, sputum, bronchial lavage, EBUS and oral brushings). The participants have completed a detailed lifestyle questionnaire and updated data on clinical outcome and hospital events are collected through the Office of National Statistics, Cancer Registry and from Health Episode Statistics. The project is registered on the UK National Institute for Health Research (NIHR) lung cancer portfolio and has all the required ethical approvals and sponsorship arrangements in place. The LLP has detailed standard operating procedures (SOP) for all aspects of the recruitment, data, specimen collection as well as the data storage. The LLP Cohort study has 8,224 participants with blood and 7,761 with plasma samples. The LLP case-control samples have been incorporated into in a large number of international GWAS and molecular studies 2,3, methylation 4-7, microRNA 8and next generation studies 9-11, resulting in high ranking publications, as well as forming the basis for the LLP risk prediction model 12-14 which has been utilised in the UK lung cancer screening trial (UKLS) 15-17 Patient and control DNAs were derived from EDTA-venous blood samples. Harvard Samples. David Christiani at the Harvard University School of Public Health has been directing research studies to investigate etiological factors influencing lung cancer development since 1983 and has amassed a collection of 2000 controls and 5055 lung cancer cases. He has been actively collecting and storing snap frozen tumor samples since 1992. Around 1500 tumor samples have been collected and the average wet tumor yield is about 30 grams of tumor, of which 631 cases have completely annotated clinical and survival information. Pathology confirmation is provided by two pathologists. At the time of surgery, a minimum of 30 grams of wet lung tumor tissue and 30 grams of non-involved tissue from the same lobe is sectioned, flash frozen and sent to Dr. Christiani's lab for logging and storage. A blood sample for DNA and serum is collected. A structured interview by trained research staff is conducted on each case, and clinical outcomes and treatments is extracted and entered into the molecular epidemiology data base at Harvard. Fresh frozen samples have been collected from 1451 lung cancer and are available for study. Samples from this collaborative study have played key roles in major studies, including the initial finding describing EGFR mutations in lung cancer 22. Participants in this study are patients, > 18 years of age, with newly diagnosed histologically confirmed lung cancer. Samples that are included in the analysis have the following histologies: Adenocarcinoma: 8140/3, 8250/3, 8260/3, 8310/3, 8480/3 8560/3; LCC: 8012/3, 8031/3; squamous carcinoma: 8070/3, 8071/3, 8072/3, 8074/3; and other NSCLC: 8010/3, 8020/3, 8021/3, 8032/3, 8230/3. The Toronto Study: The Toronto study was conducted in the Great Toronto Area between 1997 and 2014. Cases were recruited at the hospitals in the network of University of Toronto and Lunenfeld- Tanenbaum Research Institute. At the time of recruitment in the clinical setting, provisional diagnoses of lung carcinoma were first assigned based on clinical criteria. Diagnoses for all cases included were histologically confirmed by the reference pathologist who is a specialist in pulmonary pathology, based on review of pathology reports from surgery, biopsy or cytology samples in 100% of cases. Diagnostic classification was done initially according to ICD-9, ICD-10, and ICD for oncology-2, and subsequently converted to ICD-O-3. Tumors were grouped into the major categories included in this analysis according to primary cancer type based on the ICD-3 definitions. Controls were randomly selected from individual visiting family medicine clinics and Ministry of Finance Municipal Tax Tapes. All subjects were interviewed using a standard questionnaire and information on lifestyle risk factors, occupational history, medical and family history was collected. Blood samples were collected from more than 85% of the subjects. IARC: The IARC data are derived from case-control studies conducted in Russia and include samples that have available tissue samples. Patient and control DNAs were derived from EDTA-venous blood samples. The lung cancer patients were classified according to ICD-O-3; SQ: 8070/3, 8071/3, 8072/3, 8074/3; AD: 8140/3, 8250/3, 8260/3, 8310/3, 8480/3, 8560/3, 8251/3, 8490/3, 8570/3, 8574/3; with tumous with overlapping histologies classified as mixed. The Lung Cancer Transdisciplinary Research Cohort is utilized in the following dbGaP sub-studies. To view genotypes, other molecular data, and derived variables collected in these sub-studies, please click on the following sub-studies below or in the "Sub-studies" section of this top-level study page phs000876 Lung Cancer Transdisciplinary Research Cohort. phs000877 Meta Analysis phs000878 CIDR Lung Cancer phs001681 Affy Axiom Array

  Study phs000876

• Deciphering Intratumoral Molecular Heterogeneity in Clear Cell Renal Cell Carcinoma with a Radiogenomics Platform

  Intratumoral heterogeneity (ITH) challenges the molecular characterization of clear cell renal cell Carcinoma (ccRCC) with percutaneous biopsies and is a confounding factor in selection of molecular-targeted versus immune-based therapy. Magnetic Resonance (MR) Imaging can noninvasively assess the spatial landscape of the entire tumor. To validate MRI for ITH assessment, we implemented a radiogenomic platform through a systematic imaging based co-localization approach for multi region tissue acquisition from single tumors. We investigated if the spatial changes in imaging can predict the molecular changes using transcriptome and histopathological correlatives. Our study confirmed imaging heterogeneity as a predictor of molecular heterogeneity in ccRCC.

  Study EGAS00001003846

• A personalised medicine approach for ponatinib-resistant chronic myeloid leukaemia

  Chronic myeloid leukaemia (CML) is characterised by the presence of a fusion driver oncogene, BCR-ABL1, which is a constitutive tyrosine kinase. Tyrosine kinase inhibitors (TKIs) are the central treatment strategy for CML patients and have significantly improved survival rates, but the T315I mutation in the kinase domain of BCR-ABL1 confers resistance to all clinically approved TKIs, except ponatinib. However, compound mutations can mediate resistance even to ponatinib and remain a clinical challenge in CML therapy. Here, we investigated a ponatinib-resistant CML patient through whole genome sequencing (WGS) to identify the cause of resistance and to find alternative therapeutic targets.

  Study EGAS00001001150

• A GWAS in uveal melanoma identifies risk polymorphisms in the CLPTM1L locus.

  Uveal melanoma, a rare malignant tumor of the eye, is predominantly observed in populations of European ancestry. A genome-wide association study of 259 uveal melanoma patients compared to 401 controls all of European ancestry revealed a candidate locus at chromosome 5p15.33 (region rs421284: OR = 1.7, CI 1.43-2.05). This locus was replicated in an independent set of 276 cases and 184 controls. In addition, risk variants from this region were positively associated with higher expression of CLPTM1L. In conclusion, the CLPTM1L region contains risk alleles for uveal melanoma susceptibility, suggesting that CLPTM1L could play a role in uveal melanoma oncogenesis.

  Study EGAS00001002334

• Functional Significance of Prostate Cancer Risk-SNPs

  Prostate Cancer (PrCa), the most frequently diagnosed solid tumor in men in the U.S., results in ~192,000 new cases and ~27,000 deaths per year. Although the variation of PrCa incidence is likely to be the result of several factors, there is a large body of literature that strongly implicates a genetic etiology. Genome-wide association studies (GWAS) have emerged as the most widely used contemporary approach to identify genetic variants (in particular SNPs) that are associated with increased risk of human disease. For PrCa, at least five GWAS have now been performed yielding a substantial number of well-validated SNPs that are associated with an increased risk of PrCa, and that number continues to grow. A significant problem for many of the PrCa risk-SNPs identified so far, however, is that they do not lie within or near a known gene and they have no obvious functional properties. These findings suggest that many (if not most) of these risk-SNPs will be located in regulatory regions that control gene expression rather than in coding regions that may directly affect protein function. Therefore, in order to define the functional role of currently known risk-SNPs, the target genes must first be identified. A promising strategy to address this problem involves the use of expression quantitative trait loci (eQTL) analysis. Unfortunately, most of the publically available SNP-Transcript eQTL datasets utilize lymphoblastoid cells with only a handful using tissue from target organs. Although useful, these datasets alone are unlikely to be sufficient. Recent studies have demonstrated that gene expression and gene regulation occur in both a tissue-specific and tissue independent fashion and suggest that a complete repertoire of regulatory SNPs can only be uncovered in the context of cell type specificity. To date, such a tissue-specific dataset for normal prostate tissue does not exist. In this study, we have constructed a normal prostate tissue specific eQTL data set.

  Study phs000985

• Everything you need to know about Federated EGA Affiliates: Q&A

  Addressing common questions about Federated EGA (FEGA) Affiliates and providing answers. FEGA Affiliates have recently been defined as the third tier within the newly approved “Federated EGA Structure and Organisation” document, alongside Central EGA (CEGA) and the FEGA Nodes. In this blog post, we aim to answer the questions that may arise on this topic. For more general information about FEGA Affiliates, you can refer to this blog post. Let's now start with the questions and answers! What is the difference between a FEGA Affiliate and a FEGA Node? FEGA Nodes A FEGA Node is a national-level service that accepts submissions and provides archiving and access services within a single country's jurisdiction. Nodes provide end-to-end services for submitters in that jurisdiction, including submission support, processing, permissions management, and distribution. FEGA Affiliates A FEGA Affiliate is not a national submission service. Instead, it archives data from its own legal entity and/or selected partner institutions (for example, consortium partners). Affiliates are designed for organisations and consortia that need to keep data stewardship and access decisions within their own governance model, while still enabling discovery through the broader FEGA ecosystem. What do Affiliates commit to? Here is a practical checklist of the core expectations for a FEGA Affiliate. FEGA Affiliate checklist Discovery and metadata Submit non-personal metadata to CEGA to obtain EGA accessions and enable discovery (with metadata validation handled by the CEGA Helpdesk). Operations and resilience Maintain a data storage system and a defined backup/recovery approach. Ensure operational capacity (personnel and infrastructure) to deliver Affiliate services. Maintain systems and practices that support local data security and align with EGA best-practices. Access and user support Provide data distribution or access (e.g in a trusted research environment) to authorised users to datasets hosted at the Affiliate. Provide permissions management for datasets archived by the Affiliate (the CEGA DAC (Data Access Committee) Portal is always at your disposal to use). Provide a minimal helpdesk with sufficient capacity to support relevant DACs and approved users. Membership term Commit to a minimum membership term of four years. Governance and participation (lightweight by design) Affiliates integrate into the FEGA network operationally, but without the committee obligations associated with Nodes. When is becoming an Affiliate the right fit? Consider the Affiliate tier if: You host (or plan to host) controlled-access datasets that must be managed under your organisation’s or consortium’s governance, you want studies to be discoverable through EGA, but need access control and/or distribution to remain local, and you are not aiming to operate a national submission service tier.. What if a FEGA Node already exists in my jurisdiction? We encourage any potential Affiliate to reach out to their national FEGA Node to explore collaboration at the national level. Why? Federated models within a country already exist in FEGA, where a national Node operates like a Central EGA for their country. FEGA Nodes can also represent the interests of any Affiliates within their jurisdiction at the FEGA Committees. FEGA Nodes have experience and can support you on your FEGA journey. Ready to join as a FEGA Affiliate? We’re excited to open this formally defined pathway for organisations and consortia to participate in the federation. If you think the FEGA Affiliate tier fits your needs, start by assessing: Your scope (organisation/consortium-held data rather than public external submissions), Your ability to provide the core services (permissions, distribution/access, helpdesk, monitoring), and Your readiness to submit non-personal metadata to CEGA for accessioning and discovery. To express interest, please contact us here, and we'll help you understand the onboarding steps and how Affiliates integrate into the FEGA network.

  Blog fega-affiliates-q&a

• Transcriptome of (monocytes and dendritic cells ), from donor S9, replicate 2 control

  Dataset EGAD00001009023

• Transcriptome of (monocytes and dendritic cells ), from donor S5, replicate 2 control

  Dataset EGAD00001009015

• Transcriptome of (monocytes and dendritic cells ), from donor S6, replicate 2 control

  Dataset EGAD00001009017

• Transcriptome of (monocytes and dendritic cells ), from donor S14, replicate 2 control

  Dataset EGAD00001009033

• Transcriptome of (monocytes and dendritic cells ), from donor S7, replicate 2 patient

  Dataset EGAD00001009019

• Transcriptome of (monocytes and dendritic cells ), from donor S8, replicate 2 patient

  Dataset EGAD00001009021