Background Accurate laboratory diagnosis of HIV is essential to reduce the risk of HIV-positive individuals transmitting HIV-1 infection. The goal of this study was to identify and assess a panel of host derived plasma miRNAs that could to serve as a prognostic and predictive biomarker to detect early/acute HIV-1 infection. Methods A total of 372 microRNAs were analyzed in nine plasma samples from HIV-1 infected individuals in the early phase of infection and three healthy controls using the miRNA PCR-array. Seventeen microRNAs were selected and validated in 80 plasma samples from HIV-1 infected individuals in the early phase of infection (20 each of eclipse stage, RNA+ stage, Ag + stage, and Ag + Ab+ stage of HIV-1 patients) and 25 healthy controls. Using the validation study results a plasma miRNA panel was developed and evaluated to detect early/acute HIV-1 infection in 49 blinded samples. Finding We identified an miRNA panel (P eHIV-1 ) containing four differentially expressed miRNAs (miR-16-5p, miR-20b-5p, miR-195-5p, and miR-223-3p) that could distinguish early HIV-1 infection from healthy controls with high AUC (1·000[1·00–1·00]), sensitivity (100%), and specificity (100%).We also found that miR-223-3p demonstrates 100% sensitivity and specificity (AUC 1·00[1·00–1·00]) and could distinguish eclipse stage of HIV-1 infection from healthy controls. To detect eclipse stage of HIV-1 infection we also developed a four-miRNA based (miR-16-5p, miR-206, let-7 g-3p, and miR-181c-3p) panel (P E ) with AUC 0·999 (0·995–1·000), 100% sensitivity and 95·8% specificity. Interpretation The miRNA panel, P eHIV-1 is a potential biomarker for detecting early/acute stage of HIV-1infection and could help initiate early antiretroviral treatment, thus preventing the spread of HIV-1 infection.

To further refine our current nanoparticle-based HIV-1 p24 antigen assay, we investigated immune responses to p24 to identify diagnostically significant immune dominant epitopes (IDEs) in HIV-infected human sera, to address cross-reactivity of anti-p24 antibodies to different subtypes, and to identify new biomarkers that distinguish acute from chronic HIV infection for more accurate incidence estimation. We