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• Transcriptional Response to Hypoxia in iPSC-Derived Endothelial Cells from a High Altitude Adapted Population

  We established lymphoblastoid cell lines from 10 adult individuals of Tibetan ancestry living in the Chicago area. These lines were reprogrammed to induced pluripotent stem cells (iPSC). We validated genetic ancestry by genome-wide SNP array genotyping and population genetic analyses. After being subjected to standard quality control testing iPSCs were differentiated into endothelial cells. Following differentiation, endothelial cells were isolated via a pull down protocol using beads coated with an antibody for a canonical surface cell marker of the vascular endothelium (CD144). Purified vascular endothelial cells were cultured in parallel in normoxia (20% O2) and hypoxia (1% O2) for 48 hours prior to harvesting and processing for bulk RNA-sequencing. We provide imputed genotype data and bulk RNA-sequencing data in normoxia and in hypoxia for each of the 10 individuals. We also provide multiplexed scRNA-sequencing data for the 10 Tibetan individuals pooled with 10 CHB individuals from the 1000 Genome Project. Additionally, we provide scRNAseq data for the cardiomyocytes derived from the same iPSC lines from the Tibetan individuals pooled together with cardiomyocytes derived from iPSC lines of 10 CHB individuals from the 1000 Genome Project. Lymphoblastoid cell lines from the CHB were reprogrammed to iPSCs and differentiated to cardiomyocytes using the same protocols as used for the Tibetans. The batches of 4 lines were balanced by sex and population. These iPSC-derived cardiomyocytes were cultured in hypoxia (1% O2) for 48 hours and subjected to scRNAseq in pooled batches of 3 or 4 lines. The CHB individuals included in this analysis were: NA18528, NA18531, NA18557, NA18596, NA18606, NA18608, NA18614, NA18619, NA18633, and NA18748.

  Study phs003758

• Convergent evolution towards CD38 biallelic loss is a recurrent mechanism of resistance to anti-CD38 antibodies in multiple myeloma.

  Monoclonal antibodies directed against CD38 are a therapeutic mainstay in multiple myeloma (MM). While they have contributed to improved outcomes, most patients will still experience disease relapse. Despite their ubiquity, little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape, whereby tumor cells alter expression of cell surface immunotherapy targets, has been proposed as a potential avenue, and has been seen with other immunotherapies in MM. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, by using whole genome and whole exome sequencing data from 701 newly diagnosed patients, 72 patients at relapse with naivety to anti-CD38 antibodies, and 52 patients collected at relapse following anti-CD38 antibodies, we report biallelic inactivation of CD38 as a recurrent mechanism of resistance in 6% of patients, often via convergent evolution where distinct subclones are advantaged towards the same selective endpoint within the same patient. Monoallelic loss of the CD38 locus was seen in another 14% post-CD38-directed therapy. Three of the cases with biallelic events on CD38 presented with missense mutations and retained CD38 expression. Functional work demonstrated that two of these mutations decreased binding affinity and antibody-dependent cellular cytotoxicity of commercial antibodies Daratumumab and Isatuximab. However, the third mutation (R140G) provided relative resistance only towards one commercial product. Given that patients are often rechallenged with CD38 antibodies following disease progression, these data support the need for next generation sequencing to guide treatment selection.

  Study EGAS50000000709

• Development and validation of multivariate predictors of primary endocrine resistance to tamoxifen and aromatase inhibitors in luminal breast cancer reveal drug-specific differences

  Background: Endocrine therapy is highly effective in blocking the estrogen receptor pathway in HR+/HER2- early breast cancer (EBC). However, up to 40% of patients experience relapse during or after adjuvant endocrine therapy. Here, we investigate molecular mechanisms associated with primary resistance to endocrine therapy and develop predictive models. Results: TP53 mutations were prominently associated with primary resistance to both tamoxifen (TAM) and aromatase inhibitors (AI), with AI non-responders exhibiting resistance in up to 32% of cases. Additionally, we identified distinct DNA methylation patterns in TAM and AI non-responders, with TAM non-responders showing global DNA methylation loss, associated with KRAS signaling, apical junctions and epithelial-mesenchymal transition (EMT). Conversely, we observed methylation gain in AI non-responders affecting developmental transcription factors, hypoxia and estrogen signaling. TAM or AI resistance was associated with increased methylation-inferred proportions of immune cells and decreased proportions of endothelial cells. Based on these findings and patient age, we developed the Predictive Endocrine ResistanCe Index (PERCI). PERCI stratified NR and R cases in both treatment groups and cohorts with high accuracy (ROC AUC TAM discovery 93.9%, validation 83%; AI discovery 98.6%, validation 76.9%). A simplified PERCI efficiently predicted progression-free survival in the TCGA-BRCA sub-cohort (Kaplan-Meier log-rank p-value = 0.03 between low and high PERCI groups). Conclusions: We identified genomic and epigenomic features associated with primary resistance to TMA and AI. By combining information on genomic alterations, patient age, differential methylation and tumor microenvironment (TME) composition, we developed PERCI TAM and PERCI AI as novel predictors of primary resistance, with potential additional prognostic value. Applying PERCI in a clinical setting may allow patient-specific drug selection to overcome resistance.

  Study EGAS50000001102

• Response to Hepatitis B vaccine

  Approximately 5-10% of individuals, who are vaccinated with a hepatitis B (HB) vaccine designed based on the HBV genotype C, fail to acquire protective levels of antibodies. Host genetic factors behind low immune response to the HB vaccine were investigated by GWAS and HLA association tests. GWAS and HLA association tests were carried out using a total of 1,193 Japanese individuals including 107 low responders (HBsAb ?10 mIU/mL), 351 intermediate responders (10 mIU/mL< HBsAb <100 mIU/mL), and 735 high responders (HBsAb ?100 mIU/mL). Classical HLA class II alleles were statistically imputed using the genome-wide SNP typing data. GWAS identified independent associations of HLA-DRB1-DQB1 haplotypes, HLA-DPB1 alleles and BTNL2 gene with immune response to the HB vaccine designed based on the HBV genotype C. Five HLA-DRB1-DQB1 haplotypes and two DPB1 alleles showed significant associations with response to the HB vaccine in a comparison of three groups of 1,193 HB vaccinated individuals. When frequencies of DRB1-DQB1 haplotypes and DPB1 alleles were compared between low immune responders and HBV patients, significant associations were identified for three DRB1-DQB1 haplotypes, and no association was identified for any of DPB1 alleles. In contrast, no association for DRB1-DQB1 haplotypes and DPB1 alleles was identified in a comparison between high immune responders and healthy individuals. The findings in this study clearly show the importance of HLA-DR-DQ (i.e. recognition of a HB vaccine related HBsAg by specific DR-DQ haplotypes) and BTNL2 molecules (i.e. high immune response to the HB vaccine) for response to a HB vaccine designed based on the HBV genotype C.

  Study JGAS000341

• A Multifactorial Tumor and Immune Cell Profile Determines Response to Immune Checkpoint blockade in Melanoma

  The complex crosstalk between tumor and immune cells during immune checkpoint blockade mandates the development of integrated models that interpret the anti-tumor immune response and predict clinical outcome. We have integrated genome-wide sequence and structural alterations with pre and on-therapy transcriptomic and T cell repertoire features for a cohort of 64 immunotherapy-naïve melanomas treated with anti-PD1 monotherapy or combined anti-PD1 and anti-CTLA4 therapy. While tumor mutation burden (TMB) was associated with improved response to therapy, expressed mutation burden was superior to TMB in predicting outcome. An increased pre-existing T cell density differentiated responding from non-responding tumors independent of therapy. Importantly, T cell repertoire reshaping determined by T cell receptor (TCR) clonotypic regressions and expansions reflected response to therapy such that a more dynamic repertoire predicted improved clinical outcome. Through whole-transcriptome analyses, we discovered differential abundance of B cell subsets in responding tumors, which highlights the importance of the interplay between pre-existing T and B cell immunity in shaping therapeutic response. Tumor temporal trajectories during therapy revealed distinct patterns of molecular response related to expressed mutation elimination or retention that accurately interpreted clinical response. High-dimensional genomic, transcriptomic and immune repertoire data were integrated by both a machine learning and a censored regression approach, resulting in a harmonized multi-modal predictor of response to immune checkpoint blockade. B cell abundance, expressed mutation load and tumor aneuploidy were combined to identify patients at high risk for recurrence, such that high risk patients had a significantly shorter progression-free survival (HR=9.18, 95% CI: 3.14-26.85, p=3.4e-06) especially in the anti-PD1/anti-CTLA4 group (HR=20.34, 95% CI: 4.08-101.32, p=1.68e-06).

  Study EGAS00001004548

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• The Thrifty Microbiome: The Role of the Gut Microbiota in Obesity in the Amish

  Emerging evidence that the gut microbiota may contribute in important ways to human health and disease has led us and others to hypothesize that both symbiotic and pathological relationships between gut microbes and their host may be key contributors to obesity and the metabolic complications of obesity. Our "Thrifty Microbiome Hypothesis" poses that gut microbiota play a key role in human energy homeostasis. Specifically, constituents of the gut microbial community may introduce a survival advantage to its host in times of nutrient scarcity, promoting positive energy balance by increasing efficiency of nutrient absorption and improving metabolic efficiency and energy storage. However, in the presence of excess nutrients, fat accretion and obesity may result, and in genetically predisposed individuals, increased fat mass may result in preferential abdominal obesity, ectopic fat deposition (liver, muscle), and metabolic complications of obesity (insulin resistance, hypertension, hyperlipidemia). Furthermore, in the presence of excess nutrients, a pathological transition of the gut microbial community may occur, causing leakage of bacterial products into the intestinal lymphatics and portal circulation, thereby inducing an inflammatory state, further aggravating metabolic syndrome traits and accelerating atherosclerosis. This pathological transition and the extent to which antimicrobial leakage occurs and causes inflammatory and other maladaptive sequelae of obesity may also be influenced by host factors, including genetics. In the proposed study, we will directly test the Thrifty Microbiome Hypothesis by performing detailed genomic and functional assessment of gut microbial communities in intensively phenotyped and genotyped human subjects before and after intentional manipulation of the gut microbiome. To address these hypotheses, five specific aims are proposed: (1) enroll three age- and sex-matched groups from the Old Order Amish: (i) 50 obese subjects (BMI &gt; 30 kg/m2) with metabolic syndrome, (ii) 50 obese subjects (BMI &gt; 30 kg/m2) without metabolic syndrome, and (iii) 50 non-obese subjects (BMI &lt; 25 kg/m2) without metabolic syndrome and characterize the architecture of the gut microbiota from the subjects enrolled in this study by high-throughput sequencing of 16S rRNA genes; (2) characterize the gene content (metagenome) to assess the metabolic potential of the gut microbiota in 75 subjects to determine whether particular genes or pathways are correlated with disease phenotype; (3) characterize the transcriptome in 75 subjects to determine whether differences in gene expression in the gut microbiota are correlated with disease phenotype, (4) determine the effect of manipulation of the gut microbiota with antibiotics on energy homeostasis, inflammation markers, and metabolic syndrome traits in 50 obese subjects with metabolic syndrome and (5) study the relationship between gut microbiota and metabolic and cardiovascular disease traits, weight change, and host genomics in 1,000 Amish already characterized for these traits and in whom 500K Affymetrix SNP chips have already been completed. These studies will provide our deepest understanding to date of the role of gut microbes in terms of &#39;who&#39;s there?&#39;, &#39;what are they doing?&#39;, and &#39;how are they influencing host energy homeostasis, obesity and its metabolic complications? PUBLIC HEALTH RELEVANCE: This study aims to unravel the contribution of the bacteria that normally inhabit the human gastrointestinal tract to the development of obesity, and its more severe metabolic consequences including cardiovascular disease, insulin resistance and Type II diabetes. We will take a multidisciplinary approach to study changes in the structure and function of gut microbial communities in three sets of Old Order Amish patients from Lancaster, Pennsylvania: obese patients, obese patients with metabolic syndrome and non-obese individuals. The Old Order Amish are a genetically closed homogeneous Caucasian population of Central European ancestry ideal for genetic studies. These works have the potential to provide new mechanistic insights into the role of gut microflora in obesity and metabolic syndrome, a disease that is responsible for significant morbidity in the adult population, and may ultimately lead to novel approaches for prevention and treatment of this disorder.

  Study phs000258

• HG_Retroduplications_in_Neurodevelopmental_Disorders

  Mobile genetic Elements (MEs) are pieces of DNA which, through an RNA intermediate, can generate new copies of themselves elsewhere in the host genome. Additionally, MEs can facilitate the duplication of non-ME transcripts, typically genes, through the mechanism of retroduplication. In humans, several disorders have been directly attributed to ME-derived mutagenesis but not to retroduplication events. We propose to whole genome sequence the 7 individuals with putative de novo gene retroduplications in order to identify the site of insertion. This sequencing will serve two primary purposes: 1.) Identify the first documented case of a de novo retrogene insertion event causing a disease in humans 2.) provide additional whole genome sequencing of undiagnosed probands recruited into the DDD This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002907

• NOWAC blood-based breast cancer case-control study

  Tumor-host interactions extend beyond the local microenvironment and cancer development largely depends on the ability of malignant cells to hijack and exploit the normal physiological processes of the host. Although abnormalities in a host’s systemic immunity are associated with increased cancer susceptibility, the functional interplay between tumor cells and circulating immune cells in regulating tumorigenic responses is unclear. We employed the Norwegian Women and Cancer study, a large prospective population-based cohort study, to identify gene expression changes in blood cells that provide a robust and reproducible diagnostic signal specific to breast cancer patients. We further show that circulating blood cells in breast cancer patients are enriched in genes involved in systemic immunosuppression and the motility, metabolism, growth, and proliferation of immune cells. By mining of the cancer-associated blood transcriptome, we identified immune mediators or biomarkers that could permit early detection of breast cancer and open avenues to novel targeted immunotherapies.

  Study EGAS00000000134

• Colon cancer targeted sequencing study contaning WBCs, primary tumor tissue and plasma samples

  In the setting of localized colon cancer (CC), circulating tumor DNA (ctDNA) monitoring in plasma has shown potential for detecting minimal residual disease (MRD) and predicting higher risk of recurrence. With the tumor-only sequencing approach, however, germline variants may be misidentified as somatic variations, precluding the possibility of tracking in up to 11% of patients due to a lack of known somatic mutations. In this study comprising 148 prospectively recruited localized CC patients, a custom 29-gene panel was utilized to sequence both tumor tissue and matched white blood cells (WBCs) to enhance the accuracy of sequencing results. Performing targeted sequencing of paired tumor tissue and WBCs samples detected additional somatic mutations and increased the number of patients eligible for MRD tracking in plasma, although MRD detection sensitivity was not increased. Furthermore, the germline testing approach revealed the presence of pathogenic germline variants, thereby helping identify patients at elevated risk of hereditary cancer syndromes.

  Study EGAS50000000059