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Functional variants regulating LGALS1 (Galectin 1) expression affect human susceptibility to influenza A(H7N9).


ABSTRACT: The fatality of avian influenza A(H7N9) infection in humans was over 30%. To identify human genetic susceptibility to A(H7N9) infection, we performed a genome-wide association study (GWAS) involving 102 A(H7N9) patients and 106 heavily-exposed healthy poultry workers, a sample size critically restricted by the small number of human A(H7N9) cases. To tackle the stringent significance cutoff of GWAS, we utilized an artificial imputation program SnipSnip to improve the association signals. In single-SNP analysis, one of the top SNPs was rs13057866 of LGALS1. The artificial imputation (AI) identified three non-genotyped causal variants, which can be represented by three anchor/partner SNP pairs rs13057866/rs9622682 (AI P = 1.81 × 10(-7)), rs4820294/rs2899292 (2.13 × 10(-7)) and rs62236673/rs2899292 (4.25 × 10(-7)) respectively. Haplotype analysis of rs4820294 and rs2899292 could simulate the signal of a causal variant. The rs4820294/rs2899292 haplotype GG, in association with protection from A(H7N9) infection (OR = 0.26, P = 5.92 × 10(-7)) correlated to significantly higher levels of LGALS1 mRNA (P = 0.050) and protein expression (P = 0.025) in lymphoblast cell lines. Additionally, rs4820294 was mapped as an eQTL in human primary monocytes and lung tissues. In conclusion, functional variants of LGALS1 causing the expression variations are contributable to the differential susceptibility to influenza A(H7N9).

SUBMITTER: Chen Y 

PROVIDER: S-EPMC4649671 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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The fatality of avian influenza A(H7N9) infection in humans was over 30%. To identify human genetic susceptibility to A(H7N9) infection, we performed a genome-wide association study (GWAS) involving 102 A(H7N9) patients and 106 heavily-exposed healthy poultry workers, a sample size critically restricted by the small number of human A(H7N9) cases. To tackle the stringent significance cutoff of GWAS, we utilized an artificial imputation program SnipSnip to improve the association signals. In singl  ...[more]

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