3913 results for "*geneti*"

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• Genesis of Two Most Prevalent Variants Causing Combined Pituitary Hormone Deficiency in 21 Populations

  Two variants (c.[301_302delAG];[301_302delAG] and c.[150delA];[150delA]) in the PROP1 gene are the most common genetic causes of recessively inherited combined pituitary hormones deficiency (CPHD). Our objective was to analyze in detail the origin of the two most prevalent variants. In the multicentric study were included 237 patients with CPHD and their 15 relatives carrying c.[301_302delAG];[301_302delAG] or c.[150delA];[150delA] or c.[301_302delAG];[ 150delA]. They originated from 21 different countries worldwide. We genotyped 21 single nucleotide variant markers flanking the 9.6Mb region around the PROP1 gene that are not in mutual linkage disequilibrium in the general populations - a finding of a common haplotype would be indicative of ancestral origin of the variant. Haplotypes were reconstructed by Phase and Haploview software, and the variant age was estimated using an allelic association method. We demonstrated ancestral origin of both variants: c.[301_302delAG] was carried on 0.2Mb-long haplotype in a majority of European patients arising approximately 101 generations ago (confidence interval 90.1-116.4). Patients from the Iberian Peninsula displayed a different haplotype which was estimated to have emerged 23.3 (20.1-29.1) generations ago. Subsequently, the data indicated that both haplotypes were transmitted to Latin American patients approximately 13.8 (12.2-17.0) and 16.4 (14.4-20.1) generations ago, respectively. The c.[150delA] variant that was carried on a haplotype spanning about 0.3Mb was estimated to appear 43.7 (38.4-52.7) generations ago. We present strong evidence that the most frequent variants in the PROP1 gene are not a consequence of variant hot-spots as previously assumed, but are founder variants.

  Study EGAS00001001165

• Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

  DNA-methylation is an important epigenetic feature in health and disease. Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). However, objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples obtained from 65 glioblastoma and 5 non-tumoral brain tissues, using a gold standard free Bayesian modeling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. Also the genome-wide characteristics were compared, revealing that the HM450 probes assess less than 10% of the regions identified as methylated by MethylCap-seq. Hence the latter method may detect more potentially relevant DNA-methylation, defined by either functional location or previously reported differentially methylated candidate regions. Our results therefore indicate that – at least for the tissue under study - both methodologies are complementary, with a higher sensitivity for HM450, but a far larger genome-wide coverage for MethylCap-seq. Note that here only the relevant MethylCap-seq data is deposited, for the HM450 data we refer to GEO (GSE60274).

  Study EGAS00001001191

• Sequencing data of multiple sarcoma samples for personalized medicine and endotype identification

  Sequencing data derived from multiple patient samples was used to guide multiple patient-specific experiments and identify potential therapeutic options. These diseases are rare and high-risk (undifferentiated pleomorphic sarcoma, rhabdomyosarcoma) and thus have few available validated clinical options. This leaves the population of patients with few options if, and when, standard therapy fails to cure or control disease. An aspect of the personalize therapy design included the identification of broader disease endotypes (a combination of genetic and clinical data describing patient status) to identify subgroups of the individual disease that could better define treatments and could segment patient populations for deeper preclinical research.

  Study EGAS00001003981

• Genomics of enteropathy associated T cell lymphoma (EATL)

  Enteropathy-associated T cell lymphoma (EATL) is a lethal and the most common neoplastic complication of celiac disease. In this study, we applied whole exome sequencing in 69 EATL tumors to define the genetic landscape of EATLs. The most frequently mutated gene in EATL was SETD2 (32% of cases), with loss of function mutations comprising a large proportion (41%) of those mutations. The JAK-STAT pathway was the most frequently mutated signaling pathway, with mutations in STAT5B being the most common, followed by JAK1, JAK3, STAT3, and the negative regulator of the pathway, SOCS1. We also identified mutations in NRAS and KRAS, as well as TP53 and TERT. Interestingly, the two types of EATL had highly overlapping genetic alterations indicating shared mechanisms underlying their pathogenesis. Gene expression analysis of the two types of EATL identify robust differences in transcriptional profiles. We further modeled the effects of SETD2 loss in vivo by developing a T cell specific knockout mouse model. These mice manifested an expansion of γδ T cells that identify novel roles for SETD2 in T cell development and lymphomagenesis. Together, our data render the most comprehensive genetic portrait yet of this uncommon but lethal disease, and may inform future classification schemes.

  Study EGAS00001001954

• GWAS data on human pancreatic islets from 191 donors - Lund

  Most signals detected by genome-wide association studies map to non-coding sequence and their tissue-specific effects influence transcriptional regulation. However, many key tissues and cell-types required for appropriate functional inference are absent from large-scale resources such as ENCODE and GTEx. We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors. We find: (a) eQTLs have a variable replication rate across the 44 GTEx tissues (<73%), indicating that our study captured islet-specific cis-eQTL signals; (b) islet eQTL signals show marked overlap with islet epigenome annotation, though eQTL effect size is reduced in the stretch enhancers most strongly implicated in GWAS signal location; (c) selective enrichment of islet eQTL overlap with the subset of T2D variants implicated in islet dysfunction; and (d) colocalization between islet eQTLs and variants influencing T2D or related glycemic traits, delivering candidate effector transcripts at 23 loci, including DGKB and TCF7L2. Our findings illustrate the advantages of performing functional and regulatory studies in tissues of greatest disease-relevance while expanding our mechanistic insights into complex traits association loci activity with an expanded list of putative transcripts implicated in T2D development.

  Study EGAS00001004044

• RNA-seq study of longitudinal blood cell samples from children at risk of type 1 diabetes

  The appearance of type 1 diabetes (T1D)-associated autoantibodies is the first and only measurable parameter to predict progression toward T1D in genetically susceptible individuals. However, autoantibodies indicate an active autoimmune reaction, wherein the immune tolerance is already broken. Therefore, there is a clear and urgent need for new biomarkers that predict the onset of the autoimmune reaction preceding auto-antibody positivity or reflect progressive b-cell destruction. Here we report the mRNA sequencing–based analysis of 306 samples including fractionated samples of CD4+ and CD8+ T cells as well as CD4, CD8 cell fractions and unfractionated PBMC samples longitudinally collected from seven children who developed beta-cell autoimmunity (Case subjects) at a young age and matched control subjects.

  Study EGAS00001004071

• HipSci___Whole_Exome_sequencing___BPD

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform whole exome sequencing using Agilent whole exome pulldown method on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with blood and platelet disorders

  Study EGAS00001001976

• HipSci___Whole_Exome_sequencing___Ataxia

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform whole exome sequencing using Agilent whole exome pulldown method on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with hereditary cerebral ataxia

  Study EGAS00001001978

• HipSci HumanExome BeadChip analysis - Usher syndrome and congenital eye defects

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we performed Genotyping analysis using the Infinium HumanExome BeadChip on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Usher syndrome and congenital eye defects.

  Study EGAS00001002008

• HipSci HumanExome BeadChip analysis - Alport Syndrome

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we performed Genotyping analysis using the Infinium HumanExome BeadChip on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Alport Syndrome.

  Study EGAS00001002009