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An unbiased systems genetics approach to mapping genetic loci modulating susceptibility to severe streptococcal sepsis.

Abdeltawab NF, Aziz RK, Kansal R, Rowe SL, Su Y, Gardner L, Brannen C, Nooh MM, Attia RR, Abdelsamed HA, Taylor WL, Lu L, Williams RW, Kotb M - PLoS Pathog. (2008)

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Mid-South Center for Biodefense and Security, The University of Tennessee Health Science Center, Memphis, Tennessee, United States of America.

ABSTRACT
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.

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Genome-wide scan for mice susceptibility to GAS sepsis showing mapped QTL on Chr 2.(A) Interval mapping of survival (expressed as corrected relative survival index, cRSI), showing a significant QTL (based on 1000 permutation tests) on Chr 2 between 22–34 Mb with LRS of 34.2 (P≤0.0000001), and a suggestive QTL between 125–150 Mb with LRS of 12 (P≤0.001). (B) Whole genome interval mapping of GAS bacteremia using bacterial load 24 h post injection expressed as corrected log CFU/ml blood, showing two QTLs on Chr 2: first QTL between 22–34 Mb with LRS of 24.5 (P≤0.00001) and a second with LRS of 17 (P≤0.0001) between 125–150 Mb. (C) Whole genome mapping of GAS sepsis using tissue dissemination of GAS expressed as corrected log CFU/spleen with QTL between 125–150 Mb with LRS of 15 (P≤0.0001). Red line indicates significant LRS, while grey line indicates suggestive LRS. Upper x-axis shows mouse chromosomes, and lower x-axis shows physical map in mega bases, y-axis represents linkage in LRS score.
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ppat-1000042-g002: Genome-wide scan for mice susceptibility to GAS sepsis showing mapped QTL on Chr 2.(A) Interval mapping of survival (expressed as corrected relative survival index, cRSI), showing a significant QTL (based on 1000 permutation tests) on Chr 2 between 22–34 Mb with LRS of 34.2 (P≤0.0000001), and a suggestive QTL between 125–150 Mb with LRS of 12 (P≤0.001). (B) Whole genome interval mapping of GAS bacteremia using bacterial load 24 h post injection expressed as corrected log CFU/ml blood, showing two QTLs on Chr 2: first QTL between 22–34 Mb with LRS of 24.5 (P≤0.00001) and a second with LRS of 17 (P≤0.0001) between 125–150 Mb. (C) Whole genome mapping of GAS sepsis using tissue dissemination of GAS expressed as corrected log CFU/spleen with QTL between 125–150 Mb with LRS of 15 (P≤0.0001). Red line indicates significant LRS, while grey line indicates suggestive LRS. Upper x-axis shows mouse chromosomes, and lower x-axis shows physical map in mega bases, y-axis represents linkage in LRS score.

Mentions: The strongest QTL modulating mouse survival (cRSI) mapped to mouse Chr 2 between 22–34 Mb, with an likelihood ratio statistic (LRS) of 34.2 (P≤0.0000001), Figure 2A. A second less significant QTL was also mapped on the same chromosome between 125–150 Mb with an LRS of 12 (P≤0.001), and a third QTL on Chr X, Figure 2A. The QTLs for bacteremia and bacterial dissemination to spleen overlapped with those for survival, with slight difference in significance. The first QTL modulating bacteremia mapped to Chr 2 between 22–34 Mb with an LRS of 24.5 (P≤0.00001), Figure 2B. The second QTL mapped to the same chromosome between 125–150 Mb with an LRS of 17 (P≤0.0001), Figure 2B. A QTL modulating bacterial dissemination to spleen also mapped to Chr 2 between 125–150 Mb with LRS of 15 (P≤0.001), Figure 2C.


An unbiased systems genetics approach to mapping genetic loci modulating susceptibility to severe streptococcal sepsis.

Abdeltawab NF, Aziz RK, Kansal R, Rowe SL, Su Y, Gardner L, Brannen C, Nooh MM, Attia RR, Abdelsamed HA, Taylor WL, Lu L, Williams RW, Kotb M - PLoS Pathog. (2008)

Genome-wide scan for mice susceptibility to GAS sepsis showing mapped QTL on Chr 2.(A) Interval mapping of survival (expressed as corrected relative survival index, cRSI), showing a significant QTL (based on 1000 permutation tests) on Chr 2 between 22–34 Mb with LRS of 34.2 (P≤0.0000001), and a suggestive QTL between 125–150 Mb with LRS of 12 (P≤0.001). (B) Whole genome interval mapping of GAS bacteremia using bacterial load 24 h post injection expressed as corrected log CFU/ml blood, showing two QTLs on Chr 2: first QTL between 22–34 Mb with LRS of 24.5 (P≤0.00001) and a second with LRS of 17 (P≤0.0001) between 125–150 Mb. (C) Whole genome mapping of GAS sepsis using tissue dissemination of GAS expressed as corrected log CFU/spleen with QTL between 125–150 Mb with LRS of 15 (P≤0.0001). Red line indicates significant LRS, while grey line indicates suggestive LRS. Upper x-axis shows mouse chromosomes, and lower x-axis shows physical map in mega bases, y-axis represents linkage in LRS score.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2277464&req=5

ppat-1000042-g002: Genome-wide scan for mice susceptibility to GAS sepsis showing mapped QTL on Chr 2.(A) Interval mapping of survival (expressed as corrected relative survival index, cRSI), showing a significant QTL (based on 1000 permutation tests) on Chr 2 between 22–34 Mb with LRS of 34.2 (P≤0.0000001), and a suggestive QTL between 125–150 Mb with LRS of 12 (P≤0.001). (B) Whole genome interval mapping of GAS bacteremia using bacterial load 24 h post injection expressed as corrected log CFU/ml blood, showing two QTLs on Chr 2: first QTL between 22–34 Mb with LRS of 24.5 (P≤0.00001) and a second with LRS of 17 (P≤0.0001) between 125–150 Mb. (C) Whole genome mapping of GAS sepsis using tissue dissemination of GAS expressed as corrected log CFU/spleen with QTL between 125–150 Mb with LRS of 15 (P≤0.0001). Red line indicates significant LRS, while grey line indicates suggestive LRS. Upper x-axis shows mouse chromosomes, and lower x-axis shows physical map in mega bases, y-axis represents linkage in LRS score.
Mentions: The strongest QTL modulating mouse survival (cRSI) mapped to mouse Chr 2 between 22–34 Mb, with an likelihood ratio statistic (LRS) of 34.2 (P≤0.0000001), Figure 2A. A second less significant QTL was also mapped on the same chromosome between 125–150 Mb with an LRS of 12 (P≤0.001), and a third QTL on Chr X, Figure 2A. The QTLs for bacteremia and bacterial dissemination to spleen overlapped with those for survival, with slight difference in significance. The first QTL modulating bacteremia mapped to Chr 2 between 22–34 Mb with an LRS of 24.5 (P≤0.00001), Figure 2B. The second QTL mapped to the same chromosome between 125–150 Mb with an LRS of 17 (P≤0.0001), Figure 2B. A QTL modulating bacterial dissemination to spleen also mapped to Chr 2 between 125–150 Mb with LRS of 15 (P≤0.001), Figure 2C.

Bottom Line: 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.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.

View Article: PubMed Central - PubMed

Affiliation: Mid-South Center for Biodefense and Security, The University of Tennessee Health Science Center, Memphis, Tennessee, United States of America.

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus