Differences in Response to the Flu Vaccine Among Adults With HIV and Without HIV in Uganda

• In group and between group comparison of immune parameters and gene expressions that change significantly following vaccination with the seasonal trivalent influenza vaccine (Vaxigrip®) [ Time Frame: From baseline (Day 0) to 100 days post vaccination ] [ Designated as safety issue: No ]
  Immune parameters or gene expressions that change significantly in groups over baseline post immunization and between the study groups will be analyzed. For immune parameters, we will use a two-sided paired t-test. Fold-change will be combined with the test p-value in a selection criterion as appropriate. The tentative selection criterion is p-value ≤ 0.01 and fold change ≥ 3. For the gene/miRNA expression data, we will use the method Significance Analysis of Microarrays (SAM) with paired design to find differentially expressed genes. False discovery rate (FDR) will be used as selection criterion. The tentative selection criterion is FDR ≤ 0.1.
  
  
• Proportion of subjects achieving 4-fold or greater hemagglutination inhibition (HAI)antibody titer increases. [ Time Frame: From baseline (Day 0) to 100 days following primary vaccination ] [ Designated as safety issue: No ]
  Proportion of subjects in different study groups achieving 4-fold or greater hemagglutination inhibition (HAI)antibody titer increases will be tabulated at each time point (Days 0, 1, 3, 7, 14, 28 and 100) and plotted across time. Fisher's exact test will be used to make comparisons between the study groups.
  
  
• Calculating correlation coefficient between the immune parameter and vaccine immunogenicity, as measured by the humoral immune response against seasonal influenza. [ Time Frame: From baseline (Day 0) to 100 days post vaccination ] [ Designated as safety issue: No ]
  For immune parameters, we will calculate the correlation coefficient between the immune parameter and vaccine immunogenicity, as measured by the humoral immune response against seasonal influenza. The p-values associated with the correlation coefficients will be used to select immune parameters that are associated with the respective adaptive immune responses. The tentative selection criterion is p-value ≤ 0.01. For gene expression data, we will use the method Significance Analysis of Microarrays (SAM) with quantitative outcome to identify genes that are significantly associated with the immune response. False discovery rate (FDR) will be used as selection criterion. The tentative selection criterion is FDR ≤ 0.1.
  
  
• Characterization of the gut microbiota to determine compositional differences between HIV-uninfected adults versus HIV-infected adults on HAART versus HIV-infected long-term non-progressors [ Time Frame: From baseline (Day 0) to Day 28 post vaccination ] [ Designated as safety issue: No ]
  Gut mircobiota will be characterized to determine what compositional differences exist between HIV-uninfected adults versus HIV-infected adults on HAARt versus HIV-infected long-term non-progressors at baseline (Day 0), Day 7 and Day 28 post vaccination
  
  
• Correlation between microbiata status and the quality of immune response elicited in vaccinated individuals [ Time Frame: From baseline (Day 0) to Day 28 post vaccination ] [ Designated as safety issue: No ]
  Determine whether the status of the microbita correlates with the quality of immune responses elicited in vaccinated individuals
  
  

This longitudinal, observational cohort study will be conducted at the Makerere University- Johns Hopkins University Research Collaboration, at the Mulago National Referral Hospital complex in Kampala Uganda. The study will consist of 2 groups. One group will consist of 25 healthy HIV uninfected adults and the other arm will consist of 35 HIV infected adults. Within the HIV infected arm there will be two groups, 25 HIV infected adults and 10 long term non-progressors. Vaccinees will receive a primary immunization at day 0, and blood samples will be obtained at days 0, 1, 3, 7, 14, 28 and 100 after immunization.

We will analyze the early molecular signatures (identified by microarray analyses, as well as by FACS analyses of innate immune cells and luminex analyses of cytokines and chemokines) that correlate and predict the later immune responses.