HIV-1-infected children and adults exhibit a high degree of variability in their rate of disease progression but, in the absence of highly active antiretroviral therapy (HAART) children progress more rapid than adults . Host's factors likely contribute to the variability in clinical outcome. Genetic variants of innate immunity genes may affect virus–host interactions and impact disease progression; this effect may be of particular interest in children who acquire infection when the adaptive immune response is still under development.
Toll-like receptors (TLRs) and defensins (DEFs), initiators and effectors of innate immunity, may influence HIV-1 pathogenesis. Genetic variants of TLR9 have been associated with the rate of disease progression in adults [2–4]. Specific variants of TLR9 and DEFβ1[6–8] were found to be associated with risk of mother-to-child transmission (MTCT) of HIV-1, but no data are available regarding their role in pediatric HIV-1 disease progression. The aim of this work was to investigate the impact of variability in TLR9 and DEFβ1 genes on the clinical outcome of HIV-1 infected children.
The study population included 95 HIV-1-infected children, born to HIV-1-seropositive mothers between 1984 and 1996. None of the mothers had undergone antiretroviral prophylaxis. The HIV-1-infected children attended the Pediatric Department of Padova University; their clinical and immunological status was defined according to the classification system of Centers for Disease Control and Prevention . The endpoint of the study was defined as the onset of disease (stage C) or the initiation of HAART. The median (interquartile) follow-up from birth to endpoint was 87 (46–134) months.
Genomic DNA was extracted from peripheral blood mononuclear cells with the QIAamp DNA Blood mini kit (Qiagen, Hilden, Germany), according to the manufacturer's instructions. Single nucleotide polymorphisms (SNPs) of TLR9 and DEFβ1 were analyzed by the TaqMan allelic discrimination assay (Applied Biosystems, Foster City, California, USA). Primers and probes used for TLR9 and DEFβ1 were previously described. Allele discrimination and genotype determination were based on the endpoint fluorescence measured by the Sequence Detection System software (Applied Biosystems). The accuracy of genotyping was confirmed by known DNA samples of each genotype and by direct sequencing of randomly selected samples as previously described .
The genotypes for each SNP were analyzed as a codominant variable and were also grouped according to the dominant, recessive or underdominant model. The C-free stage was defined as the time from birth to the onset of stage C or HAART entry. The probability of acquiring disease was calculated with the Kaplan–Meier method and the log-rank test was used to test for differences between genotype categories. Hazard ratios and their 95% confidence interval based on the Cox proportional hazards model were estimated to test the association between genotypes, haplotypes and risk of stage C. To estimate the haplotype effect on disease we used the Thesias program . Values of P less than 0.05 were considered statistically significant and all tests were two-sided. Analyses were carried out in R (http://http://www.r-project.org/).
Results indicated that the TLR9 1174AA genotype tended to be associated with a better prognosis in the codominant model and was significantly associated with a slow disease progression in the recessive model, with both Kaplan–Meier (P = 0.034) and Cox analyses (P = 0.042) (Table 1). Conversely, a significant correlation was observed between the TLR9 1635AG genotype and rapid disease progression with both Kaplan–Meier (P = 0.008) and Cox analyses (P = 0.009) (Table 1). This result is in agreement with a previous finding in adults ; the underdominant model might explain this unusual association between a heterozygous status and a disadvantageous condition . The TLR9 [G;G] haplotype was significantly associated with a higher risk of rapid disease progression (Table 1); this disadvantage is consistent with a previous finding, indicating the association of this haplotype with a higher risk of MTCT of HIV-1 . The DEFβ1 −44CG genotype was associated with a slower disease progression compared with the −44CC genotype with both Kaplan–Meier (P = 0.020) and Cox analyses (P = 0.024) (Table 1). The DEFβ1 −52 SNP, which has been found to play a role in MTCT of HIV-1 , did not influence clinical progression (Table 1). However, the DEFβ1 [G;G] haplotype, previously found to be protective against MTCT of HIV-1 , was also found to be associated with a better disease outcome (Table 1).
Overall, these results support a role of genetic variability of innate immunity genes in the clinical outcome of pediatric HIV-1 infection. The mechanisms by which these genetic variants may influence HIV-1 disease are still unknown. DEFβ1 is mainly produced by epithelial cells , and higher levels of DEFβ1 have been reported in exposed uninfected individuals than in seropositive patients . Specific variants of DEFβ1 may protect against disease progression by increasing DEFβ1 levels at the mucosa level . Furthermore, loss of mucosal surface integrity, particularly in the gastrointestinal tract, leads to microbial translocation , which, along with HIV-1 viremia, induce immune activation, a hallmark of disease progression in children as well as adults [16,17]. TLR9 and DEFβ1 expression, both of which play important roles in controlling the overall responses of immune cells to pathogens [12,18,19], may modulate immune activation. Lower levels of TLR9 expression have been found in viremic versus aviremic HIV-1-infected patients . Studies suggested that TLR9 1174 and 1635 SNP, although not inducing amino acid change, may affect TLR9 expression , and a role of these SNP in TLR9 immune activation has been advanced [2–5]. In conclusion, specific genotypes and haplotypes in the DEFβ1 and TLR9 genes may affect the functional ability of their encoded proteins to modulate innate immunity and immune activation, thus contributing to the variability of clinical outcome in HIV-1-infected children.
R.F. performed laboratory studies, analyzed the results and wrote the article; K.G. and M.Z. performed laboratory studies and analyzed the results; P.D.B. and S.M. analyzed the results and performed the statistical analyses; C.G. and O.R. carried out the clinical follow-up of the patients and analyzed the data; and A.D.R. designed the study, analyzed the results and wrote the article.
The authors thank Lisa Smith for editorial assistance and Pierantonio Gallo for the artwork.
Conflicts of interest
There are no conflicts of interest.
The study was supported by PENTA Labnet (FP7- N 201057) and PENTA Foundation. R.F. was supported by PENTA Foundation.
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