Institution
Wellcome Trust Centre for Human Genetics
Facility•Oxford, United Kingdom•
About: Wellcome Trust Centre for Human Genetics is a facility organization based out in Oxford, United Kingdom. It is known for research contribution in the topics: Population & Genome-wide association study. The organization has 2122 authors who have published 4269 publications receiving 433899 citations.
Topics: Population, Genome-wide association study, Single-nucleotide polymorphism, Gene, Locus (genetics)
Papers published on a yearly basis
Papers
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TL;DR: The mechanisms by which mutations in the HNF-1alpha gene cause diabetes mellitus are unclear but might include abnormal pancreatic islet development during foetal life thereby limiting their later function, as well as impaired transcriptional regulation of genes that play a key role in normal pancreatic beta cell function.
Abstract: Maturity-onset diabetes of the young (MODY) is a genetically heterogeneous subtype of non-insulin-dependent diabetes mellitus (NIDDM) characterised by early onset, autosomal dominant inheritance and a primary defect in insulin secretion. Recent studies have shown that mutations in the two functionally related transcription factors, hepatocyte nuclear factor 4 alpha (HNF-4alpha) and hepatocyte nuclear factor 1 alpha (HNF-1alpha) are associated with the MODY1 and MODY3 forms of diabetes respectively, whereas mutations in the enzyme glucokinase are the cause of the MODY2 form. We have examined 10 unrelated Caucasian families in which MODY/NIDDM co-segregated with markers for MODY3 for mutations in the HNF-1alpha gene (TCF1). Ten different mutations were observed in these families, all of which co-segregated with diabetes. There were no obvious relationships between the nature of the mutations observed (i.e. frameshift, nonsense, or missense) or their location in the gene with clinical features of diabetes (age at onset, severity) in these families. The mechanisms by which mutations in the HNF-1alpha gene cause diabetes mellitus are unclear but might include abnormal pancreatic islet development during foetal life thereby limiting their later function, as well as impaired transcriptional regulation of genes that play a key role in normal pancreatic beta cell function.
156 citations
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TL;DR: It is shown that genetic variation in the majority of non-sarcomeric genes implicated in HCM is not associated with the condition, reinforce the fact that the sarcomeric gene variation is the primary cause of HCM known to date and underscore that the aetiology of H CM is unknown in themajority of patients.
Abstract: Aim Hypertrophic cardiomyopathy (HCM) exhibits genetic heterogeneity that is dominated by variation in eight sarcomeric genes. Genetic variation in a large number of non-sarcomeric genes has also been implicated in HCM but not formally assessed. Here we used very large case and control cohorts to determine the extent to which variation in non-sarcomeric genes contributes to HCM. Methods and results We sequenced known and putative HCM genes in a new large prospective HCM cohort (n = 804) and analysed data alongside the largest published series of clinically genotyped HCM patients (n = 6179), previously published HCM cohorts and reference population samples from the exome aggregation consortium (ExAC, n = 60 706) to assess variation in 31 genes implicated in HCM. We found no significant excess of rare (minor allele frequency < 1:10 000 in ExAC) protein-altering variants over controls for most genes tested and conclude that novel variants in these genes are rarely interpretable, even for genes with previous evidence of co-segregation (e.g. ACTN2). To provide an aid for variant interpretation, we integrated HCM gene sequence data with aggregated pedigree and functional data and suggest a means of assessing gene pathogenicity in HCM using this evidence. Conclusion We show that genetic variation in the majority of non-sarcomeric genes implicated in HCM is not associated with the condition, reinforce the fact that the sarcomeric gene variation is the primary cause of HCM known to date and underscore that the aetiology of HCM is unknown in the majority of patients.
156 citations
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TL;DR: A power‐calculation method is provided which reveals that sample sizes of a few thousand should offer sufficient statistical precision to detect 1H NMR‐based biomarkers quantifying predisposition to disease.
Abstract: variation in metabolite concentration into familial (genetic and common-environmental), individual-environmental, and longitudinally unstable components. We estimate that stable variation, comprising familial and individual-environmental factors, accounts on average for 60% (plasma) and 47% (urine) of biological variation in 1 H NMR-detectable metabolite concentrations. Clinically predictive metabolic variation is likely nested within this stable component, so our results have implications for the effective design of biomarker-discovery studies. We provide a power-calculation method which reveals that sample sizes of a few thousand should offer sufficient statistical precision to detect 1 H NMR-based biomarkers quantifying
155 citations
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TL;DR: In this article, the authors compare the individual strengths and weaknesses of SIM, STED, and SMLM by imaging a variety of different subcellular structures in fixed cells.
Abstract: Many biological questions require fluorescence microscopy with a resolution beyond the diffraction limit of light. Super-resolution methods such as Structured Illumination Microscopy (SIM), STimulated Emission Depletion (STED) microscopy and Single Molecule Localisation Microscopy (SMLM) enable an increase in image resolution beyond the classical diffraction-limit. Here, we compare the individual strengths and weaknesses of each technique by imaging a variety of different subcellular structures in fixed cells. We chose examples ranging from well separated vesicles to densely packed three dimensional filaments. We used quantitative and correlative analyses to assess the performance of SIM, STED and SMLM with the aim of establishing a rough guideline regarding the suitability for typical applications and to highlight pitfalls associated with the different techniques.
155 citations
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TL;DR: Nonparametric linkage analyses at microsatellites surrounding D12S83 were performed in 122 North American Caucasian families containing 208 genotyped IBD-affected relative pairs and independently confirmed linkage of IBD to the chromosome 12 region that was investigated.
Abstract: Summary Genetic epidemiological studies have shown that genetic factors are important in the pathogenesis of the idiopathic inflammatory bowel diseases (IBD), Crohn disease (CD), and ulcerative colitis (UC). A genome screen in the United Kingdom found linkage of IBD to a 41-cM region of chromosome 12, surrounding D12S83. We aimed to replicate this linkage and to narrow the region of interest. Nonparametric linkage analyses at microsatellites surrounding D12S83 were performed in 122 North American Caucasian families containing 208 genotyped IBD-affected relative pairs. Transmission/disequilibrium tests (TDTs) were also performed. We confirmed that IBD is linked to chromosome 12 (peak GENEHUNTER-PLUS LOD* score 2.76 [ P = .00016] between D12S1724 and D12S90). The evidence for linkage is contributed by both the group of CD-affected relative pairs (peak GENEHUNTER-PLUS LOD* score 1.79 [ P = .0021] between D12S1724 and D12S90) and the group of UC-affected relative pairs (peak GENEHUNTER-PLUS LOD* score 1.82 [ P = .0019] at D12S335). The TDT is positive at the D12S83 locus (global χ 2 = 16.41, 6 df, P = .012). In conclusion, we have independently confirmed linkage of IBD to the chromosome 12 region that we investigated. A positive TDT at D12S83 suggests that we have greatly narrowed the chromosome 12 region that contains an IBD locus.
155 citations
Authors
Showing all 2127 results
Name | H-index | Papers | Citations |
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Mark I. McCarthy | 200 | 1028 | 187898 |
John P. A. Ioannidis | 185 | 1311 | 193612 |
Gonçalo R. Abecasis | 179 | 595 | 230323 |
Simon I. Hay | 165 | 557 | 153307 |
Robert Plomin | 151 | 1104 | 88588 |
Ashok Kumar | 151 | 5654 | 164086 |
Julian Parkhill | 149 | 759 | 104736 |
James F. Wilson | 146 | 677 | 101883 |
Jeremy K. Nicholson | 141 | 773 | 80275 |
Hugh Watkins | 128 | 524 | 91317 |
Erik Ingelsson | 124 | 538 | 85407 |
Claudia Langenberg | 124 | 452 | 67326 |
Adrian V. S. Hill | 122 | 589 | 64613 |
John A. Todd | 121 | 515 | 67413 |
Elaine Holmes | 119 | 560 | 58975 |