3930 results for "*geneti*"

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• Cancer Epigenetics Group

  Dac EGAC00001003349

• Multiomics characterisation of Long Covid

  We generated 10X, droplet-based paired snRNAseq+snATACseq (Multiome) of patients suffering from Long Covid. In total, we included 31 patients. Single nuclei libraries are genetically multiplexed across donors, genotype files are available to enable demultiplexing. Phenotype sheets provide information of pools/donors as well as donor phenotype.

  Dataset EGAD50000000202

• Multiomics characterisation of the response to stimulation in Long Covid patients

  We generated 10X, droplet-based paired snRNAseq+snATACseq (Multiome) of the response to P. Aeruginosa or RPMI in patients suffering from Long Covid. In total, we included 15 patients. Single nuclei libraries are genetically multiplexed across donors, genotype files are available to enable demultiplexing. Phenotype sheets provide information of pools/donors as well as donor phenotype.

  Dataset EGAD50000000203

• Knoll et al.: The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation

  Following the demonstration of its life-saving effect in clinical trials, dexamethasone quickly became standard-of-care in the treatment of severe COVID-19. Beneficial effects were reported for patients requiring supplemental oxygen or invasive mechanical ventilation. Yet, a substantial proportion of patients still progressed to a critical condition or succumbed to the disease, despite timely initiation of glucocorticoid treatment. No molecular or cellular correlate of this beneficial treatment response has been defined. Here, we identify distinct cellular and molecular changes in circulating immune cells in patients with COVID-19 elicited in response to dexamethasone treatment. The most profound transcriptional changes in response to dexamethasone treatment were noted in monocytes and in B cells. In monocytes, we observed a reversal of hallmark signatures previously associated with COVID-19 severity, and the induction of a specific monocyte substate enriched in glucocorticoid response gene expression which we here refer to as dexamethasone response cluster. Molecular responses to dexamethasone treatment were directly linked to clinical outcome, since the reversal of pathogenic signatures and induction of glucocorticoid response genes were enriched in patients who survived the disease in response to dexamethasone treatment. Cellular responsiveness of circulating monocytes was thus identified as a correlate of clinical response to dexamethasone treatment. Changes in monocyte transcriptomes could also be linked to epigenetic alterations highlighting early differences in monocytes of dexamethasone responders and non-responders. Further, monocyte single-cell transcriptome-derived signatures were enriched in whole blood transcriptomes from patients with fatal outcome in two independent cohorts, highlighting the potential clinical value for early identification of non-responders who are refractory to dexamethasone treatment. Overall, our findings indicate that the life-saving effects of dexamethasone in COVID-19 patients are linked to a specific immunomodulatory effect based on the reversion of monocyte dysregulation. Our study elucidates the potential mechanism of action of one of the most efficient and cost-effective drugs for the treatment of COVID-19. It further highlights the potential of single-cell omics for monitoring target engagement of immunomodulatory drugs and for the stratification of patients for precision medicine approaches.

  Study EGAS00001007461

• Genetic Mechanisms of Disease Lab DAC

  Data access for raw and processed H3K27ac ChIP-seq and ATAC-seq data from "Effect of ETS2 modulation on chromatin accessibility and enhancer activity in human macrophages".

  Dac EGAC50000000087

• Nanopore sequencing enables allelic phasing of FLG loss-of-function variants, intragenic copy number variation and methylation status in atopic dermatitis and ichthyosis vulgaris

  Loss-of-function (LoF) variants in the FLG gene are associated with ichthyosis vulgaris (IV) and atopic dermatitis (AD). IV and AD patients with two FLG LoF variants are reported to have a more severe disease course. However, subsets of compound heterozygous patients display phenotypic heterogeneity despite a prediction of a severe phenotype from their genotype. The underlying genetic mechanism of this phenotypic variability is unknown. One possibility is that two LoF FLG variants could be located in cis (on the same allele), thus altering the predicted gene dosage. To investigate the allelic contribution of compound heterozygous FLG LoF mutations to IV phenotypic variability, we employ long reads from Oxford Nanopore Technologies, utilising two methodologies to phase the entire coding region of FLG into parental alleles: an amplicon-sequencing approach and an adaptive-sampling strategy. We investigated the allelic phasing of FLG LoF variants and intragenic-repeat copy-number variations (CNV) of 21 subjects with known compound heterozygous genotypes and mixed IV severity. Our results suggest that IV severity is not linked to the presence of cis variants in our IV patient cohort. Nanopore reads enabled detection and accurate phasing of CNVs and LoF variants into parental alleles, providing a framework for future in-depth genetic analysis. These results highlight the usefulness of utilising long reads for interrogating the FLG gene and other highly repetitive genes for genetic stratification related to clinical phenotypes.

  Study EGAS50000000166

• VIB CCB Translational Genetics Data Access Committee

  Dac EGAC00001003421

• This DAC takes care of requests for data for the Swiss epigenetic colorectal cancer cohort study, SWEPIC

  Dac EGAC00001003471

• Shallow Whole Genome Sequencing of Patient Derived Xenografts

  Chemotherapy is the standard-of-care treatment for metastatic colorectal cancer (mCRC) and benefits some patients, but what distinguishes responders from non-responders is unclear. In this study, we leveraged a comprehensive collection of 27 molecularly annotated patient-derived xenografts to uncover functional predictors of response to 5-FU and irinotecan combination therapy (FOLFIRI) in mCRC. Genetic analyses revealed that treatment sensitivity was marked by genomic scars indicative of BRCAness, suggesting homologous recombination (HR) deficiency as a key determinant. Accordingly, we surveyed a manually curated panel of 44 genes with a documented role in HR for the potential presence of pathogenic mutations. We did not observe a specific enrichment of HR gene mutations based on response to FOLFIRI. This result, combined with the absence of widespread biallelic inactivation of the analyzed genes and the predominance of mutations categorized as variants of unknown significance, suggests that FOLFIRI sensitivity is not primarily governed by underlying mutations in HR genes responsible for mitigating the genotoxic effects of this therapeutic regimen.

  Dataset EGAD50000000277

• Clonally heritable gene expression imparts a layer of diversity within cell types

  Cell types can be classified according to shared patterns of transcription. Non-genetic variability among individual cells of the same type has been ascribed to stochastic transcriptional bursting and transient cell states. Using high coverage single cell RNA profiling, we asked whether long-term, heritable differences in gene expression can impart diversity within cells of the same type. Studying clonal human lymphocytes and mouse brain cells, we uncovered a vast diversity of heritable gene expression patterns among different clones of cells of the same type in vivo. We combined chromatin accessibility and RNA profiling on different lymphocyte clones to reveal thousands of regulatory regions exhibiting interclonal variation which could be directly linked to interclonal variation in gene expression. Our findings identify a source of cellular diversity, which may have important implications for how cellular populations are shaped by selective processes in development, aging and disease.

  Study EGAS50000000161