Julian Forton

TLR9 polymorphisms in African populations: no association with severe malaria, but evidence of cis-variants acting on gene expression

BackgroundDuring malaria infection the Toll-like receptor 9 (TLR9) is activated through induction with plasmodium DNA or another malaria motif not yet identified. Although TLR9 activation by malaria parasites is well reported, the implication to the susceptibility to severe malaria is not clear. The aim of this study was to assess the contribution of genetic variation at TLR9 to severe malaria.MethodsThis study explores the contribution of TLR9 genetic variants to severe malaria using two approaches. First, an association study of four common single nucleotide polymorphisms was performed on both family- and population-based studies from Malawian and Gambian populations (n>6000 individual). Subsequently, it was assessed whether TLR9 expression is affected by cis-acting variants and if these variants could be mapped. For this work, an allele specific expression (ASE) assay on a panel of HapMap cell lines was carried out.ResultsNo convincing association was found with polymorphisms in TLR9 for malaria severity, in either Gambian or Malawian populations, using both case-control and family based study designs. Using an allele specific expression assay it was observed that TLR9 expression is affected by cis-acting variants, these results were replicated in a second experiment using biological replicates.ConclusionBy using the largest cohorts analysed to date, as well as a standardized phenotype definition and study design, no association of TLR9 genetic variants with severe malaria was found. This analysis considered all common variants in the region, but it is remains possible that there are rare variants with association signals. This report also shows that TLR9 expression is potentially modulated through cis-regulatory variants, which may lead to differential inflammatory responses to infection between individuals.

Interferon regulatory factor-1 polymorphisms are associated with the control of Plasmodium falciparum infection

We describe the haplotypic structure of the interferon regulatory factor-1 (IRF-1) locus in two West African ethnic groups, Fulani and Mossi, that differ in their susceptibility and immune response to Plasmodium falciparum malaria. Both populations showed significant associations between IRF-1 polymorphisms and carriage of P. falciparum infection, with different patterns of association that may reflect their different haplotypic architecture. Genetic variation at this locus does not therefore account for the Fulani-specific resistance to malaria while it could contribute to parasite clearances ability in populations living in endemic areas. We then conducted a case–control study of three haplotype-tagging single nucleotide polymorphisms (htSNPs) in 370 hospitalised malaria patients (160 severe and 210 uncomplicated) and 410 healthy population controls, all from the Mossi ethnic group. All three htSNPs showed correlation with blood infection levels in malaria patients, and the rs10065633 polymorphism was associated with severe disease (P=0.02). These findings provide the first evidence of the involvement in malaria susceptibility of a specific locus within the 5q31 region, previously shown to be linked with P. falciparum infection levels.

A TNF region haplotype offers protection from typhoid fever in Vietnamese patients

The genomic region surrounding the TNF locus on human chromosome 6 has previously been associated with typhoid fever in Vietnam (Dunstan et al. in J Infect Dis 183:261–268, 2001). We used a haplotypic approach to understand this association further. Eighty single nucleotide polymorphisms (SNPs) spanning a 150xa0kb region were genotyped in 95 Vietnamese individuals (typhoid case/mother/father trios). A subset of data from 33 SNPs with a minor allele frequency of >4.3% was used to construct haplotypes. Fifteen SNPs, which tagged the 42 constructed haplotypes were selected. The haplotype tagging SNPs (T1–T15) were genotyped in 380 confirmed typhoid cases and 380 Vietnamese ethnically matched controls. Allelic frequencies of seven SNPs (T1, T2, T3, T5, T6, T7, T8) were significantly different between typhoid cases and controls. Logistic regression results support the hypothesis that there is just one signal associated with disease at this locus. Haplotype-based analysis of the tag SNPs provided positive evidence of association with typhoid (posterior probability 0.821). The analysis highlighted a low-risk cluster of haplotypes that each carry the minor allele of T1 or T7, but not both, and otherwise carry the combination of alleles *12122*1111 at T1–T11, further supporting the one associated signal hypothesis. Finally, individuals that carry the typhoid fever protective haplotype *12122*1111 also produce a relatively low TNF-α response to LPS.

Accuracy of haplotype reconstruction from haplotype-tagging single-nucleotide polymorphisms

Many investigators are now using haplotype-tagging single-nucleotide polymorphism (htSNPs) as a way of screening regions of the genome for association with disease. A common approach is to genotype htSNPs in a study population and to use this information to draw inferences about each individuals haplotypic makeup, including SNPs that were not directly genotyped. To test the validity of this approach, we simulated the exercise of typing htSNPs in a large sample of individuals and compared the true and inferred haplotypes. The accuracy of haplotype inference varied, depending on the method of selecting htSNPs, the linkage-disequilibrium structure of the region, and the amount of missing data. At the stage of selection of htSNPs, haplotype-block-based methods required a larger number of htSNPs than did unstructured methods but gave lower levels of error in haplotype inference, particularly when there was a significant amount of missing data. We present a Web-based utility that allows investigators to compare the likely error rates of different sets of htSNPs and to arrive at an economical set of htSNPs that provides acceptable levels of accuracy in haplotype inference.