Use of principal components analysis and protein microarray to explore the association of HIV-1-specific IgG responses with disease progression

Abstract

The role of HIV-1-specific antibody responses in HIV disease progression is complex and would benefit from analysis techniques that examine clusterings of responses. Protein microarray platforms facilitate the simultaneous evaluation of numerous protein-specific antibody responses, though excessive data are cumbersome in analyses. Principal components analysis (PCA) reduces data dimensionality by generating fewer composite variables that maximally account for variance in a dataset. To identify clusters of antibody responses involved in disease control, we investigated the association of HIV-1-specific antibody responses by protein microarray, and assessed their association with disease progression using PCA in a nested cohort design. Associations observed among collections of antibody responses paralleled protein-specific responses. At baseline, greater antibody responses to the transmembrane glycoprotein (TM) and reverse transcriptase (RT) were associated with higher viral loads, while responses to the surface glycoprotein (SU), capsid (CA), matrix (MA), and integrase (IN) proteins were associated with lower viral loads. Over 12 months greater antibody responses were associated with smaller decreases in CD4 count (CA, MA, IN), and reduced likelihood of disease progression (CA, IN). PCA and protein microarray analyses highlighted a collection of HIV-specific antibody responses that together were associated with reduced disease progression, and may not have been identified by examining individual antibody responses. This technique may be useful to explore multifaceted host-disease interactions, such as HIV coinfections.

Trial registration: ClinicalTrials.gov NCT00507221.

Figures

FIG. 1.

Microarray heat map of all HIV-specific antibody responses, with seroreactive responses boxed in red. Each column represents a patient and each row represents an antigen-specific antibody response. HIV-uninfected controls, on the right, were evaluated using the same batch of microarray slides showing no reactivity to the HIV-specific antigens. Color images available online at www.liebertpub.com/aid

FIG. 2.

Graphic representation of the contributions of each antibody response to the retained components after principle components analysis for total (A) and gene-specific analyses: Env (B), Gag (C), and Pol (D). The y-axis represents the loadings of each antibody response to the retained components after orthogonal rotation. Loadings are similar to the weight each antibody response provides to the components. Rotation causes antigens to load predominately to one component by maximally aligning the principle component axes with the projected points in the coordinate space. Color images available online at www.liebertpub.com/aid

FIG. 3.

Odds of disease progression at 24 months by total and gene-specific components. Disease progression was determined by antiretroviral treatment (ART) use or CD4 count n=66).