3994 results for "*geneti*"

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• Pancreatic islets PISA RNA-seq samples

  GWAS have identified more than 700 genetic signals associated with type 2 diabetes (T2D). To gain insight into the underlying molecular mechanisms, we created the Translational human pancreatic Islet Genotype tissue-Expression Resource (TIGER), aggregating >500 human islet RNA-seq and genotyping datasets. We imputed genotypes using 4 reference panels and meta-analyzed cohorts to improve coverage of expression quantitative trait loci (eQTL) and developed a method to combine allele-specific expression across samples (cASE). We identified >1 million islet eQTLs (56% novel), of which 53 colocalize with T2D signals (60% novel). Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identified 8 novel cASE colocalizations, among which an SLC30A8 T2D associated variant. We make all the data available through the open-access TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translate this into therapeutic insight and precision medicine for T2D.

  Study EGAS00001005535

• Samples from the Greek island of Crete, MANOLIS cohort

  Genome-wide association studies of complex traits have been successful in identifying common variant associations, but a substantial heritability gap remains. The field of complex trait genetics is shifting towards the study of low frequency and rare variants, which are hypothesised to have larger effects. The study of these variants can be empowered by focusing on isolated populations, in which rare variants may have increased in frequency and linkage disequilibrium tends to be extended. This work focuses on isolated populations from Greece. Sequencing is very efficient in isolated populations, because variants found in a few samples will be shared by others in extended haplotype contexts, supporting accurate imputation.

  Study EGAS00001000067

• UK10K_RARE_NEUROMUSCULAR

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. The neuromuscular disorder samples are part of the “rare disease” group, and will undergo exome sequencing. For further information with regard to this cohort please contact Francesco Muntoni (f.muntoni@ucl.ac.uk).

  Study EGAS00001000101

• An Unusual Genomic Variant of Pancreatic Ductal Adenocarcinoma with an Indolent Clinical Course

  We describe a patient with biopsy-proven locally advanced pancreatic ductal adenocarcinoma (PDA) who underwent a modified course of gemcitabine and stereotactic body radiation therapy. Whole exome sequencing of this patient's tumor revealed a simple genome landscape with no evidence of mutations, copy number changes, or structural alterations in genes most commonly associated with PDA, i.e. KRAS, CDKN2A, TP53 or SMAD4. An analysis of germline DNA revealed no pathogenic variants of significance. Whole exome and whole genome sequencing identified a somatic mutation of RNF213 and an inversion/deletion of CTNNA2 as the genetic basis of this PDA. Although PDA is classically characterized by a predictable set of mutations, these data suggest that alternate genetic paths to PDA may exist, which can be associated with a more indolent clinical course.

  Study EGAS00001002192

• The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort

  The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort and biobank that we established. To date, approximately 28,000 participants have enrolled in the study, with over 13,000 having completed their initial visit. The project is aimed at identifying novel molecular signatures with diagnostic, prognostic and therapeutic value, and at developing AI-based predictive models for disease onset and progression. A unique feature of the HPP is its deep and longitudinal profiling that includes medical history, lifestyle and nutritional habits, vital signs, anthropometrics, blood tests, continuous glucose and sleep monitoring, imaging modalities and molecular profiling of the transcriptome, genetics, gut, vaginal and oral microbiome, metabolome and immune system. For several of these modalities, the HPP is the first or largest cohort of its kind. Our analyses of this data provide novel insights into the variation of phenotypes with age and ethnicity, highlighting the importance of having ethnically diverse cohorts and the need for establishing age-dependent norms. We demonstrate how the HPP can be used to unravel personalized molecular signatures of disease by comparison to patient-specific and disease-specific matched healthy controls. Leveraging the extensive dietary and lifestyle HPP data, we systematically identify associations between lifestyle factors and health outcomes. Finally, we present a multi-modal foundation AI model that is trained using self-supervised learning on diet and CGM data and outperforms existing methods in predicting future onset of disease. We extend this AI framework to integrate all data modalities of each subject as a continuous sequence of diverse medical events, creating a digital twin that can simulate interventions and predict health trajectories and outcomes.

  Study EGAS00001008040

• UK10K NEURO FSZNK

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches. This Finnish schizophrenia sample set has been collected from a population cohort using national registers. The entire sample collection consists of 2756 individuals from 458 families of whom 931 are diagnosed with schizophrenia spectrum disorder. Families outside Kuusamo (n=288) all had at least two affected siblings. All diagnoses are based on DSM-IV and for a large fraction of cases there is cognitive data.For further details/descriptions with regard to this data set please contact Tiina Paunio (tiina.paunio@thl.fi)

  Study EGAS00001000119

• Whole genome bisulfite sequencing of hepatitis B virus-associated hepatocellular carcinoma tumor and non-cancerous samples

  To understand comprehensive epigenetic alterations in hepatitis B virus-associated HCC, we have conducted a whole genome bisulfite sequencing of 5 tumor samples and 3 non-cancerous samples (3 pairs and 2 tumors).

  Study EGAS00001002230

• WGS_of_healhy_mesothelial_cells_and_primary_mesothelima_cell_lines

  Mesothelioma is a rare and aggressive cancer associated with previous exposure to asbestos. Currently there are no effective treatments for mesothelioma and majority of patients will die within a year after diagnosis. Although a large number of preclinical and clinical trials assessed the efficacy of various therapuetic modes, none of the tested molecules entered the clinic. Thus, to better understand what drives mesothelioma carcinogenesis and to identify novel targets for therapy, here we aim at performing WGS of heathy mesothelial cells and a panel of mesothelioma cells lines. Primary mesothelial cell lines were established in prof. Marciniak lab from human pleural specimens, while primary mesothelioma cell lines were obtained from MesobanK. Both models constitute low passage cell lines and therefore should closely represent genetics of the original tissue.

  Study EGAS00001005559

• Genome-wide DNA methylation profiles by MeDIP-seq of cord blood cells and cord blood mononuclear cells obtained from twins conceived through in vitro fertilization and naturally conceived controls

  The study included 47 newborn twins conceived though in vitro fertilisation (IVF) and 60 non-IVF-conceived twins from the Peri/postnatal Epigenetic Twins Study (PETS). Cord blood was collected at birth and used to process mononuclear cells. Whole blood cells (WBCs) from cord blood of 98 twins (40 IVF and 58 non-IVF) and cord blood mononuclear cells (CBMCs) of 82 twins (35 IVF and 47 non-IVF) were subjected to DNA methylation profiling. Methylated DNA immunoprecipitation followed by deep sequencing (MeDIP-seq) was applied to generate genome-wide DNA methylation profiles in a total of 180 samples. Single-end reads were mapped onto hg19 using BWA. Methylation levels were quantified using MEDIPS and used to identify IVF-associated differentially methylated regions.

  Study EGAS00001002248

• This study explored and validated the clinical application of targeted NGS of circulating tumor DNA in identifying tumor-specific mutations and uncovering clinical actionable targets in a variety of solid tumors in large patient cohorts.

  Cancer is a disease of genetic alterations. Comprehensive genetic diagnosis is needed to match each patient to appropriate cancer therapy. However, acquisition of representative tumor samples is invasive and often infeasible. Circulating tumor DNA (ctDNA) is a promising non-invasive biomarker for cancer mutational profiling. Here we implemented targeted next generation sequencing (NGS) with a customized pan-cancer gene panel on 605 clinical ctDNA samples in multiple cancer types. Overall, tumor-specific mutations were identified in 87% of ctDNA samples, with mutation spectra highly concordant with their matched tumor tissues. 71% of patients have at least one clinical actionable mutation with 76% of which have suggested drugs approved or in clinical trials. In particular, our study reveals a unique mutation spectrum in Chinese lung cancer patients, which could be used to guide treatment decision and monitor the appearance of drug-resistant mutations. Taken together, our study demonstrated the clinical utility of target NGS-based ctDNA mutational profiling to guide cancer treatment decision.

  Study EGAS00001002251