3855 results for "*geneti*"

in 53.92 milliseconds.

• cfDNA in Hereditary And High-Risk Malignancies (CHARM)

  Our goal is to improve early cancer detection by developing a blood test to predict cancer development in carriers using circulating DNA. As carriers develop cancer, they may have pre-cancerous cells which release this DNA into the blood (cell-free DNA; cfDNA), which can be detected with novel genetic technologies. We propose to use three complementary cfDNA assays:shallow whole genome sequencing (sWGS), Liquid-Biopsy Sequencing (LB-Seq) and Cell-free Methylated DNA Immunoprecipitation and High-throughput Sequencing (cfMeDip-Seq) for early cancer detection.

  Study EGAS00001006539

• Separation of chronic myeloid leukemia stem cells from normal hematopoietic stem cells at single-cell resolution

  Chronic myeloid leukemia (CML) is a clonal disease, initiated and sustained by a subpopulation of CML stem cells (CML-SC) containing the BCR::ABL1 oncogene. Genetic markers that enrich for CML-SC have been identified, including CD26 being most specific. Genome sequencing analysis remain yet to be performed at single cell level in order to determine differences and heterogeneity in the genetic profile of CML-SC versus normal hematopoietic stem cells (HSC). Here we show that CD26 and CD33 separate CML-SC from normal HSC in freshly isolated bone marrow samples from newly diagnosed CML patients. DNA sequencing confirms that single CML-SC derived colonies are positive for BCR::ABL1 and harbor a recurrent set of patient-specific clonal somatic mutations across different CML-SC derived colonies. In contrast, marker-negative (CD26-CD33-) HSC from the same patients are negative for the BCR::ABL1 oncogene and do not carry recurrent, clonal mutation across different colonies. These results support the concept that CD26/CD33 expression separates genetically defined, clonal mutant CML-SC from normal HSC that carry individual sets of random mutations in CML patients. We provide whole exome DNA sequencing data for 23 clinical samples of CML-SC plus two buccal swipes derived normal samples. CML samples are comprised of 4 to 8 replicates from two patients, at diagnosis and after treatment. Single CML stem cells before treatment and single non-transformed HSC at remission were selected from bone marrow samples by FACS, according to genetic markers CD33+CD26+ at diagnosis and CD33+CD26-/CD33-CD26- at remission. WES libraries of colony forming assays derived CML-SC and HSC populations were prepared using Agilent SureSelect Human All Exon V6 kit and sequenced running 150 cycles (2x 75bp paired-end) on an Illumina NextSeq 500 platform. Following GATK best practices for somatic mutation calling, novel CML variants and random mutation events during remission phase were obtained.

  Study EGAS00001006904

• Gene copy number variation in pediatric mental illness in a general population

  We assessed the relationship of gene copy number variation (CNV) in mental health/neurodevelopmental traits and diagnoses, physical health, and cognitive biomarkers in a community sample of 7,100 unrelated European, and East Asian children and youth (Spit for Science). Diagnoses of mental health disorders were found in 17.5% of participants and 27.6% scored in the highest 10% on either or both ADHD and OCD trait measures. Clinically relevant CNVs were present in 3.9% of participants and were associated with elevated scores on a continuous measure of ADHD (p=5.0×10-3), on a cognitive biomarker of mental health (response inhibition (p=1.0×10-2)), and on prevalence of mental disorders (p=1.9×10-6, odds ratio: 3.09). With a rise of mental illness, our data establishes a baseline for delineating genetic contributors in paediatric-onset conditions.

  Study EGAS00001006659

• Single-cell ATAC-seq analysis for COVID19 patients

  While SARS-CoV-2 infection causes mild respiratory disease in most individuals, a small group of patients develops severe COVID-19. Dysfunctional innate immune responses have been identified to contribute to differences in COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell epigenetics, transcriptomic, and genetics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified 41.3% of significantly up-regulated genes in hospitalized COVID-19 patients potentially induced by differential chromatin accessibility. Sub-clustering and motif-enrichment analyses of monocytes reveal disease condition-specific regulation by transcription factors, such as C/EBPs and SPI1, and their targets, including a long-noncoding RNA LUCAT1, which further regulates interferon responses and is associated with the need for oxygen supply of COVID-19 patients. The interaction between C/EBPs and LUCAT1 was validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in promoters/enhancers of COVID-19 patients. Integrating our data with publicly available expression quantitative trait loci and chromosomal interactions indicates that ASoC SNP rs6800484-C is associated with lower expression of CCR2, which may contributeto higher viral loads in lungs and higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to the innate immune responses of different COVID-19 patients.

  Study EGAS00001006559

• Single-cell RNA-seq analysis for COVID19 patients

  While SARS-CoV-2 infection causes mild respiratory disease in most individuals, a small group of patients develops severe COVID-19. Dysfunctional innate immune responses have been identified to contribute to differences in COVID-19 severity, but the key regulators are still unknown. Here, we present an integrative single-cell epigenetics, transcriptomic, and genetics analysis of peripheral blood mononuclear cells from hospitalized and convalescent COVID-19 patients. In classical monocytes, we identified 41.3% of significantly up-regulated genes in hospitalized COVID-19 patients potentially induced by differential chromatin accessibility. Sub-clustering and motif-enrichment analyses of monocytes reveal disease condition-specific regulation by transcription factors, such as C/EBPs and SPI1, and their targets, including a long-noncoding RNA LUCAT1, which further regulates interferon responses and is associated with the need for oxygen supply of COVID-19 patients. The interaction between C/EBPs and LUCAT1 was validated through loss-of-function experiments. Finally, we investigated genetic risk variants that exhibit allele-specific open chromatin (ASoC) in promoters/enhancers of COVID-19 patients. Integrating our data with publicly available expression quantitative trait loci and chromosomal interactions indicates that ASoC SNP rs6800484-C is associated with lower expression of CCR2, which may contributeto higher viral loads in lungs and higher risk of COVID-19 hospitalization. Altogether, our study highlights the diverse genetic and epigenetic regulators that contribute to the innate immune responses of different COVID-19 patients.

  Study EGAS00001006560

• Comprehensive epigenomic profiling reveals the extent of disease-specific chromatin states and informs drug target discovery in ankylosing spondylitis

  Ankylosing spondylitis (AS) is a common, highly heritable inflammatory arthritis characterised by enthesitis of the spine and sacroiliac joints. Genome-wide association studies have revealed >100 genetic associations but their functional effects remain largely unresolved. Here, we present a comprehensive transcriptomic and epigenomic map of disease-relevant blood immune cell subsets from AS patients and healthy controls. We report differential disease signatures for specific genomic regions from individual -omic modalities and multi-omic integration, showing enrichment at genetically associated loci and evidence for altered monocyte function in AS. We link putative functional SNPs with cognate genes using high-resolution Capture-C at 10 loci, including PTGER4 and ETS1. We also show how disease-specific functional genomic data can be integrated with GWAS evidence to enhance therapeutic target discovery. This study combines multiple epigenetic and transcriptional analysis with GWAS to identify cell types, candidate drug target genes and transcriptional regulation of likely pathogenic relevance.

  Study EGAS00001006945

• Uncovering tumor intrinsic and extrinsic factors that regulate hepatocellular carcinoma growth using patient derived xenograft assays

  Several major factors limit our understanding of hepatocellular carcinoma (HCC). First, human HCCs are infrequently biopsied for diagnosis and thus are not often biologically interrogated. Second, HCC initiation and progression are strongly influenced by the cirrhotic microenvironment, and the exact contributions of intrinsic and extrinsic tumor factors are unclear. A powerful approach to examine the personalized biology of liver cancers and the influence of host tissues is with patient derived xenograft (PDX) models. In Asia, HCCs from hepatitis B virus patients have been efficiently converted into PDXs, but few parallel efforts from the west have been reported. In a large-scale analysis, we implanted 93 HCCs and 8 cholangiocarcinomas (CCAs) to systematically analyze host factors and to define an optimized platform for PDX development from both surgical and biopsy samples. NSG mice that had undergone partial hepatectomy (PHx) represented the best combination of engraftability, growth, and passageability, but overall rates were low and indicative of a unique intrinsic biology for HCCs in the US. PDX models preserved the histology and genetic features of parental tumors, and ultimately, 9 new models were usable for pre-clinical studies. Intriguingly, HCC PDXs were differentially sensitive to regorafenib and sorafenib and CCA PDXs were also highly sensitive to regorafenib. PDX models functionalize early and advanced stage HCCs and revealed unique biological features of liver cancers from the US.

  Study EGAS00001004020

• Multiome_HB

  Hepatoblastoma (HB) cells display strong phenotypic heterogeneity with a major impact on drug response, but the underlying mechanisms are poorly understood. Here, we use a single-cell multi-omic strategy to unravel the molecular determinants of this plasticity. HB display a continuum of single-cell states between hepatocytic (scH), liver progenitor (scLP) and mesenchymal (scM) differentiation poles, with an intermediate scH/LP population bordering scLP and scH areas in spatial transcriptomics. Chromatin accessibility landscapes reveal the gene regulatory networks of each differentiation pole, and the sequence of transcription factor activation underlying cell state transitions. Single-cell mapping of somatic alterations reveals the clonal architecture of each tumor, showing that each genetic subclone displays its own range of cellular plasticity across differentiation poles. The most scLP subclones, overexpressing stem cell and DNA repair genes, proliferate faster after neo-adjuvant chemotherapy. These results highlight how the interplay of clonal evolution and epigenetic plasticity shapes the potential of HB subclones to respond to chemotherapy.

  Study EGAS00001006932

• CYP2C19 long-read sequencing

  Inter-individual differences in drug response based on genetic variations can lead to drug toxicity and treatment inefficacy. A large part of this variability is caused by genetic variants in pharmacogenes. Unfortunately, the Single Nucleotide Variant (SNV) panels currently used in clinical pharmacogenomic (PGx) testing are unable to detect all genetic variability in these genes. Long-read sequencing, on the other hand, has been shown to be able to resolve complex (pharmaco)genes. In this study we have assessed the added value of long-read sequencing for PGx focusing on the clinically important and highly polymorphic CYP2C19 gene. With a capture-based long-read sequencing panel we were able to characterize the entire region and assign variants to their allele of origin (phasing), resulting in the identification of 813 unique variants in 37 samples. To assess the clinical utility of this data we have compared the performance of three different *-allele tools (Aldy, PharmCat and PharmaKU) which are specifically designed to assign clinical haplotypes to pharmacogenes based on all input variants. We conclude that long-read sequencing can improve our ability to characterize the CYP2C19 locus, help to identify novel haplotypes and that *-allele tools are an useful asset in phenotype prediction. Ultimately, this approach could help to better predict an individual’s drug response and improve therapy outcomes.

  Study EGAS00001006929

• Genomic_characterisation_of_MGUS__

  he hematological malignancy multiple myeloma (MM), also called Kahler’s disease or plasma cell (PC) myeloma, is characterized by a clonal expansion of PCs originating in the bone marrow (BM). The expansion of these cells leads to an overproduction of antibodies and results in typical symptoms such as anemia, renal failure and bone lesions. All cases of MM are preceded by the asymptomatic, non-malignant pre-stage monoclonal gammopathy of undetermined significance (MGUS). Of all MGUS patients, only 1% per year will progress to MM. Despite efforts to elucidate the molecular mechanisms underlying the MGUS-to-MM progression, its pathogenesis still remains largely unknown. Additionally, the genetic profiles of MGUS patients have only been limitedly investigated due to the only incidental finding of MGUS, the difficulties in BM sampling and isolating a sufficient number of aberrant PCs from the BM aspirates of MGUS patients. Consequently, reliable biomarkers to individually predict which MGUS patients will progress to MM and which will not, are lacking. Therefore, it is highly required to study the molecular pathogenesis of MGUS and the role of genetic events in relation to the malignant transformation to MM.

  Study EGAS00001004124