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Limited knowledge exists on early HIV events that may inform preventive and therapeutic strategies. This study aims to characterize the earliest immunologic and virologic HIV events following infection and investigates the usage of a novel therapeutic strategy.We prospectively screened 24,430 subjects in Bangkok and identified 40 AHI individuals. Thirty Thais were enrolled (8 Fiebig I, 5 Fiebig II, 15 Fiebig III, 2 Fiebig IV) of whom 15 completed 24 weeks of megaHAART (tenofovir/emtricitabine/efavirenz/raltegravir/maraviroc). Sigmoid biopsies were completed in 24/30 at baseline and 13/15 at week 24. At baseline, the median age was 29 years and 83% were MSM. Most were symptomatic (87%), and were infected with R5-tropic (77%) CRF01_AE (70%). Median CD4 was 406 cells/mm(3). HIV RNA was 5.5 log(10) copies/ml. Median total blood HIV DNA was higher in Fiebig III (550 copy/10(6) PBMC) vs. Fiebig I (8 copy/10(6) PBMC) (p = 0.01) while the median %CD4+CCR5+ gut T cells was lower in Fiebig III (19%) vs. Fiebig I (59%) (p = 0.0008). After 24 weeks of megaHAART, HIV RNA levels of 0.050); subjects with less than 40% at baseline had a significant increase in CD4+CCR5+ T cells from baseline to week 24 (14% vs. 71%, p = 0.02).Gut T cell depletion and HIV reservoir seeding increases with progression of AHI. MegaHAART was associated with immune restoration and reduced reservoir size. Our findings could inform research on strategies to achieve HIV drug-free remission.

Genome wide association studies frequently reveal associations between disease susceptibility and polymorphisms outside coding regions. Such associations cannot always be explained by linkage disequilibrium with changes affecting the transcription products. This has stimulated the interest in characterising sequence variation influencing gene expression levels, in particular in changes acting in cis. Differences in transcription between the two alleles at an autosomal locus can be used to test the association between candidate polymorphisms and the modulation of gene expression in cis. This type of approach requires at least one transcribed polymorphism and one candidate polymorphism. In the past five years, different methods have been proposed to analyse such data. Here we use simulations and real data sets to compare the power of some of these methods. The results show that when it is not possible to determine the phase between the transcribed and potentially cis acting allele there is some advantage in using methods that estimate phased genotype and effect on expression simultaneously. However when the phase can be determined, simple regression models seem preferable because of their simplicity and flexibility. The simulations and the analysis of experimental data suggest that in the majority of situations, methods that assume a lognormal distribution of the allelic expression ratios are both robust to deviations from this assumption and more powerful than alternatives that do not make these assumptions.