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 childrenResearch in context

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 childrenResearch in context

Background: Severe malarial anaemia (SMA) is a leading cause of childhood mortality in holoendemic Plasmodium falciparum regions. Methods: To gain an improved understanding of SMA pathogenesis, whole genome and transcriptome profiling was performed in Kenyan children (n = 144, 3–36 months) with disc...

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Main Authors: Angela O. Achieng, Nicolas W. Hengartner, Evans Raballah, Qiuying Cheng, Samuel B. Anyona, Nick Lauve, Bernard Guyah, Ivy Foo-Hurwitz, John M. Ong'echa, Benjamin H. McMahon, Collins Ouma, Christophe G. Lambert, Douglas J. Perkins
Format: Article
Language:English
Published: Elsevier 2019-07-01
Series:EBioMedicine
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396419304244

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http://www.sciencedirect.com/science/article/pii/S2352396419304244

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