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Träfflista för sökning "WFRF:(Kingston Nathalie) "

Search: WFRF:(Kingston Nathalie)

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1.
  • Corbin, Laura J., et al. (author)
  • Formalising recall by genotype as an efficient approach to detailed phenotyping and causal inference
  • 2018
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 9:1
  • Journal article (peer-reviewed)abstract
    • Detailed phenotyping is required to deepen our understanding of the biological mechanisms behind genetic associations. In addition, the impact of potentially modifiable risk factors on disease requires analytical frameworks that allow causal inference. Here, we discuss the characteristics of Recall-by-Genotype (RbG) as a study design aimed at addressing both these needs. We describe two broad scenarios for the application of RbG: studies using single variants and those using multiple variants. We consider the efficacy and practicality of the RbG approach, provide a catalogue of UK-based resources for such studies and present an online RbG study planner.
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2.
  • Turro, Ernest, et al. (author)
  • Whole-genome sequencing of patients with rare diseases in a national health system.
  • 2020
  • In: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 583:7814, s. 96-102
  • Journal article (peer-reviewed)abstract
    • Most patients with rare diseases do not receive a molecular diagnosis and the aetiological variants and causative genes for more than half such disorders remain to be discovered1. Here we used whole-genome sequencing (WGS) in a national health system to streamline diagnosis and to discover unknown aetiological variants in the coding and non-coding regions of the genome. We generated WGS data for 13,037 participants, of whom 9,802 had a rare disease, and provided a genetic diagnosis to 1,138 of the 7,065extensively phenotypedparticipants. We identified 95 Mendelian associations between genes and rare diseases, of which 11 have been discovered since 2015 and at least 79 are confirmed to be aetiological. By generating WGS data ofUK Biobankparticipants2, we found that rare alleles can explain the presence of some individuals in the tails of a quantitative trait for red blood cells. Finally, we identified four novel non-coding variants that cause disease through the disruption of transcription of ARPC1B, GATA1, LRBA and MPL. Our study demonstrates a synergy by using WGS for diagnosis and aetiological discovery in routine healthcare.
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