An Unbiased Systems Genetics Approach to Mapping Genetic Loci Modulating Susceptibility to Severe Streptococcal Sepsis

PLoS Pathogens

Yin Su¹  Ramy K. Aziz²  Hossam A. Abdelsamed²  William L. Taylor²  Lu Lu²  Malak Kotb²  Charity Brannen²  Sarah L. Rowe²  Robert W. Williams³  Lidia Gardner³  Nourtan F. Abdeltawab³  Rita Kansal⁴  Ramy R. Attia⁴  Mohammed M. Nooh⁴ 

[1] College of Pharmacy, Cairo University, Giza, Egypt;Department of Ophthalmology, The University of Tennessee Health Science Center, Memphis, Tennessee, United States of America;Mid-South Center for Biodefense and Security, The University of Tennessee Health Science Center, Memphis, Tennessee, United States of America;VA Medical Center, Memphis, Tennessee, United States of America

关键词: Gene expression;    Sepsis;    Spleen;    Quantitative trait loci;    Gene regulation;    Mouse models;    Genetic networks;    Immune response;   

DOI  :  10.1371/journal.ppat.1000042

学科分类：生物科学（综合）

来源: Public Library of Science

【 摘 要 】

Striking individual differences in severity of group A streptococcal (GAS) sepsis have been noted, even among patients infected with the same bacterial strain. We had provided evidence that HLA class II allelic variation contributes significantly to differences in systemic disease severity by modulating host responses to streptococcal superantigens. Inasmuch as the bacteria produce additional virulence factors that participate in the pathogenesis of this complex disease, we sought to identify additional gene networks modulating GAS sepsis. Accordingly, we applied a systems genetics approach using a panel of advanced recombinant inbred mice. By analyzing disease phenotypes in the context of mice genotypes we identified a highly significant quantitative trait locus (QTL) on Chromosome 2 between 22 and 34 Mb that strongly predicts disease severity, accounting for 25%–30% of variance. This QTL harbors several polymorphic genes known to regulate immune responses to bacterial infections. We evaluated candidate genes within this QTL using multiple parameters that included linkage, gene ontology, variation in gene expression, cocitation networks, and biological relevance, and identified interleukin1 alpha and prostaglandin E synthases pathways as key networks involved in modulating GAS sepsis severity. The association of GAS sepsis with multiple pathways underscores the complexity of traits modulating GAS sepsis and provides a powerful approach for analyzing interactive traits affecting outcomes of other infectious diseases.

【 授权许可】

CC BY