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Two complement receptor one alleles have opposing associations with cerebral malaria and interact with α+thalassaemia.

D Herbert Opi | Olivia Swann | Alexander Macharia | Sophie Uyoga | Gavin Band | Carolyne M Ndila | Ewen M Harrison | Mahamadou A Thera | Abdoulaye K Kone | Dapa A Diallo | Ogobara K Doumbo | Kirsten E Lyke | Christopher V Plowe | Joann M Moulds | Mohammed Shebbe | Neema Mturi | Norbert Peshu | Kathryn Maitland | Ahmed Raza | Dominic P Kwiatkowski | Kirk A Rockett | Thomas N Williams | J Alexandra Rowe
eLife | 2018

Malaria has been a major driving force in the evolution of the human genome. In sub-Saharan African populations, two neighbouring polymorphisms in the Complement Receptor One (CR1) gene, named Sl2 and McCb, occur at high frequencies, consistent with selection by malaria. Previous studies have been inconclusive. Using a large case-control study of severe malaria in Kenyan children and statistical models adjusted for confounders, we estimate the relationship between Sl2 and McCb and malaria phenotypes, and find they have opposing associations. The Sl2 polymorphism is associated with markedly reduced odds of cerebral malaria and death, while the McCb polymorphism is associated with increased odds of cerebral malaria. We also identify an apparent interaction between Sl2 and α+thalassaemia, with the protective association of Sl2 greatest in children with normal α-globin. The complex relationship between these three mutations may explain previous conflicting findings, highlighting the importance of considering genetic interactions in disease-association studies.

Pubmed ID: 29690995

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Associated grants

  • Agency: Wellcome Trust, United Kingdom
    Id: 101910/Z/13/Z
  • Agency: Wellcome Trust, United Kingdom
    Id: Senior Research Fellowship 091758
  • Agency: Wellcome Trust, United Kingdom
    Id: 084226
  • Agency: Wellcome Trust, United Kingdom
    Id: 067431
  • Agency: Wellcome Trust, United Kingdom
    Id: Senior Research Fellowship084226
  • Agency: Wellcome Trust, United Kingdom
    Id: 204911/Z/16/Z
  • Agency: Wellcome Trust, United Kingdom
    Id: 84538
  • Agency: Wellcome Trust, United Kingdom
    Id: 202800
  • Agency: Wellcome Trust, United Kingdom
    Id: 091758
  • Agency: Wellcome Trust, United Kingdom
    Id: Senior Research Fellowship202800
  • Agency: Wellcome Trust, United Kingdom
    Id: 084538
  • Agency: Medical Research Council, United Kingdom
    Id: MR/M006212/1
  • Agency: Wellcome Trust, United Kingdom
  • Agency: Wellcome Trust, United Kingdom
    Id: 203077
  • Agency: Medical Research Council, United Kingdom
    Id: G19/9

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PRISM (tool)

RRID:SCR_005375

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.

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Stata (tool)

RRID:SCR_012763

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