title: Environmental Correlation Analysis for Genes Associated with Protection against Malaria.
abstract: Genome-wide searches for loci involved in human resistance to malaria are currently being conducted on a large scale in Africa using case-control studies. Here, we explore the utility of an alternative approach-"environmental correlation analysis, ECA," which tests for clines in allele frequencies across a gradient of an environmental selection pressure-to identify genes that have historically protected against death from malaria. We collected genotype data from 12,425 newborns on 57 candidate malaria resistance loci and 9,756 single nucleotide polymorphisms (SNPs) selected at random from across the genome, and examined their allele frequencies for geographic correlations with long-term malaria prevalence data based on 84,042 individuals living under different historical selection pressures from malaria in coastal Kenya. None of the 57 candidate SNPs showed significant (P < 0.05) correlations in allele frequency with local malaria transmission intensity after adjusting for population structure and multiple testing. In contrast, two of the random SNPs that had highly significant correlations (P < 0.01) were in genes previously linked to malaria resistance, namely, CDH13, encoding cadherin 13, and HS3ST3B1, encoding heparan sulfate 3-O-sulfotransferase 3B1. Both proteins play a role in glycoprotein-mediated cell-cell adhesion which has been widely implicated in cerebral malaria, the most life-threatening form of this disease. Other top genes, including CTNND2 which encodes δ-catenin, a molecular partner to cadherin, were significantly enriched in cadherin-mediated pathways affecting inflammation of the brain vascular endothelium. These results demonstrate the utility of ECA in the discovery of novel genes and pathways affecting infectious disease.
authors.forename: Margaret J
authors.initials: MJ
authors.lastname: Mackinnon
authors.affiliation: Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.
authors.forename: Carolyne
authors.initials: C
authors.lastname: Ndila
authors.affiliation: Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.
authors.forename: Sophie
authors.initials: S
authors.lastname: Uyoga
authors.affiliation: Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya.
authors.forename: Alex
authors.initials: A
authors.lastname: Macharia
authors.affiliation: Department of Public Health Research, KEMRI-Wellcome Trust Research Programme, Nairobi, Kenya Centre for Tropical Medicine, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, United Kingdom.
authors.forename: Robert W
authors.initials: RW
authors.lastname: Snow
authors.affiliation: Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
authors.forename: Gavin
authors.initials: G
authors.lastname: Band
authors.affiliation: Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom.
authors.forename: Anna
authors.initials: A
authors.lastname: Rautanen
authors.affiliation: Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom The Wellcome Trust Sanger Institute, Cambridge, United Kingdom.
authors.forename: Kirk A
authors.initials: KA
authors.lastname: Rockett
authors.affiliation: Wellcome Trust Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom The Wellcome Trust Sanger Institute, Cambridge, United Kingdom.
authors.forename: Dominic P
authors.initials: DP
authors.lastname: Kwiatkowski
authors.affiliation: Department of Epidemiology and Demography, KEMRI-Wellcome Trust Research Programme, Kilifi, Kenya Department of Medicine, Imperial College, London, United Kingdom INDEPTH Network, Kanda, Accra, Ghana.
authors.forename: Thomas N
authors.initials: TN
authors.lastname: Williams
mesh_terms: D000293:Adolescent; D000483:Alleles; D016022:Case-Control Studies; D002648:Child; D002675:Child, Preschool; D060467:Disease Resistance / Q000235:genetics; D004777:Environment; D005787:Gene Frequency; D056726:Genetic Association Studies / Q000379:methods; D020022:Genetic Predisposition to Disease; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D007630:Kenya / Q000453:epidemiology; D008288:Malaria / Q000453:epidemiology / Q000235:genetics* / Q000517:prevention & control; D016778:Malaria, Falciparum / Q000453:epidemiology / Q000235:genetics / Q000517:prevention & control; D010963:Plasmodium falciparum / Q000235:genetics / Q000382:microbiology; D020641:Polymorphism, Single Nucleotide; D012641:Selection, Genetic
keywords: balancing selection; environmental correlation analysis; local adaptation; malaria