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Paper Details

Integrated OMICS platforms identify LAIR1 genetic variants as novel predictors of cross-sectional and longitudinal susceptibility to severe malaria and all-cause mortality in Kenyan children.
EBioMedicine
8
2019
16231C, 18, 18,835, 18835G, C16231A, G18835A, LAIR1, LAIR1 genetic variants, LAIR1 polymorphisms, LAIR1 transcripts, Leukocyte associated immunoglobulin like receptor 1, Plasmodium falciparum, SMA, Severe malarial anaemia, all, childhood, childhood mortality, children, polymorphisms, rs2287827, rs6509867
Author NameAffiliation
Angela O AchiengUniversity of New Mexico-Kenya Global Health Programs, School of Public Health and Community Development, Maseno University
Nicolas W HengartnerLos Alamos National Laboratory
Evans RaballahUniversity of New Mexico-Kenya Global Health Programs, School of Public Health Biomedical Sciences and Technology, Masinde Muliro University of Science and Technology
Qiuying ChengUniversity of New Mexico, Center for Global Health
Samuel B AnyonaUniversity of New Mexico-Kenya Global Health Programs, Maseno University
Nick LauveUniversity of New Mexico, Center for Global Health
Bernard GuyahSchool of Public Health and Community Development, Maseno University
Ivy Foo-HurwitzUniversity of New Mexico, Center for Global Health
John M Ong'echaKenya Medical Research Institute
Benjamin H McMahonLos Alamos National Laboratory
Collins OumaUniversity of New Mexico-Kenya Global Health Programs, School of Public Health and Community Development, Maseno University
Christophe G LambertUniversity of New Mexico, Center for Global Health
Christophe G LambertUniversity of New Mexico, Center for Global Health
Douglas J PerkinsUniversity of New Mexico-Kenya Global Health Programs, Kenya University of New Mexico, Center for Global Health
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