Study design and flow chart of immunomonitoring model development. We investigated 84 subjects in whom HLA class I genotype was determined at the A, B, and C loci by high-resolution typing.37 For all alleles present at medium or high frequency in our cohorts, we defined panels of optimal HIV-1 epitopes referenced in the Los Alamos National Laboratory databases (http://www.hiv.lanl.gov) and published data.51,52 The 6 alleles of the HLA genotype of each subject then determined a panel of 16-26 (median 22) HIV-1 epitopes tested in functional assays. The participants were randomly subdivided into a discovery cohort and a validation cohort. Subjects were further classified as controllers, progressors, and ART-treated subjects. The progressor and ART-treated groups were enriched in subjects carrying protective HLA alleles to approximately match their prevalence in the controller groups. We used freshly isolated PBMCs to measure proliferation and cytokine secretion by HIV-1–specific CD8 T cells in response to the single optimal HIV-1 epitopes. We first analyzed individually the immunologic variables generated in the discovery cohort and subsequently combined them to build high-dimensional integrated models. The validation cohort was investigated to verify data consistency with the discovery cohort and to assess the ability of the models trained on the discovery dataset to appropriately discriminate among classes of subjects in independent groups of HIV-1–infected subjects. *Treated and untreated progressors were grouped in the validation dataset to develop a binary predictive model (controller vs treated/progressor classification). Detailed analyses of the discovery cohort dataset showed that combination of these groups is appropriate. †For each subject investigated, the panel of epitopes tested in the functional assays was determined by the HLA class I genotype. §Data were analyzed by general linear mixed models controlling for clustering within subjects. §§Data were analyzed by general linear mixed models controlling for clustering within subjects, with time integrated as a continuous variable.
