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
| dc.contributor.author | 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 | |
| dc.date.accessioned | 2022-02-09T07:54:46Z | |
| dc.date.available | 2022-02-09T07:54:46Z | |
| dc.date.issued | 2019 | |
| dc.identifier.uri | https://repository.maseno.ac.ke/handle/123456789/4916 | |
| dc.description | DOI: 10.1016/j.ebiom.2019.06.043 journal homepage: www.ebiomedicine.com | en_US |
| dc.description.abstract | Severe malarial anaemia (SMA) is a leading cause of childhood mortality in holoendemic Plasmodium falciparum regions. | en_US |
| dc.publisher | PubMed | en_US |
| dc.subject | : All-cause mortality; Leukocyte associated immunoglobulin like receptor 1; Plasmodium falciparum malaria; Severe malarial anaemia. | en_US |
| dc.title | 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 | en_US |
| dc.type | Article | en_US |