Association of single nucleotide polymorphisms in the lens epithelium-derived growth factor (LEDGF/p75) with HIV-1 infection outcomes in Brazilian HIV-1+ individuals.

The lens epithelium-derived growth factor p75 (LEDGF/p75), coded by the PSIP1 gene, is an important host co-factor that interacts with HIV-1 integrase to target integration of viral cDNA into active genes. The aim of this study was to investigate the association of SNPs in the PSIP1 gene with disease outcome in HIV-1 infected patients. We performed a genetic association study in a cohort of 171 HIV-1 seropositive Brazilian individuals classified as rapid progressors (RP, n = 69), typical progressors (TP, n = 79) and long-term nonprogressors (LTNP, n = 23). The exonic SNP rs61744944 and 9 tag SNPs were genotyped. A group of 192 healthy subjects was analyzed to determine the frequency of SNPs and haplotypes in the general population. Linkage disequilibrium (LD) analyses indicated that the SNPs analyzed were not in high LD (r2<0.8). Logistic regression models suggested that patients carrying the T allele rs61744944 (472L) were more likely to develop a LTNP phenotype (OR = 4.98; p = 0.05) as compared to TP group. The same trend was observed when LTNPs were compared to the RP group (OR = 3.26). Results of haplotype analyses reinforced this association, since the OR values obtained for the haplotype carrying allele T at rs61744944 also reflected an association with LTNP status (OR = 6.05; p = 0.08 and OR = 3.44; p = 0.12 for comparisons to TP and RP, respectively). The rare missense variations Ile436Ser and Thr473Ile were not identified in the patients enrolled in this study. Gene expression analyses showed lower LEDGF/p75 mRNA levels in peripheral blood mononuclear cells obtained from HIV-1 infected individuals. However, these levels were not influenced by any of the SNPs investigated. In spite of the limited number of LTNPs, these data suggest that the PSIP1 gene could be associated with the outcome of HIV-1 infection. Further analyses of this gene may guide the identification of causative variants to help predict disease course.