title: 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.
authors.affiliation: 1 University of Washington , Seattle, Washington.
authors.forename: Helen L
authors.initials: HL
authors.lastname: Gerns Storey
authors.forename: Barbra A
authors.initials: BA
authors.lastname: Richardson
authors.forename: Benson
authors.initials: B
authors.lastname: Singa
authors.forename: Jackie
authors.initials: J
authors.lastname: Naulikha
authors.forename: Vivian C
authors.initials: VC
authors.lastname: Prindle
authors.forename: Vladimir E
authors.initials: VE
authors.lastname: Diaz-Ochoa
authors.forename: Phil L
authors.initials: PL
authors.lastname: Felgner
authors.forename: David
authors.initials: D
authors.lastname: Camerini
authors.forename: Helen
authors.initials: H
authors.lastname: Horton
authors.forename: Grace
authors.initials: G
authors.lastname: John-Stewart
authors.forename: Judd L
authors.initials: JL
authors.lastname: Walson
mesh_terms: D000328:Adult; D018791:CD4 Lymphocyte Count; D002213:Capsid / Q000276:immunology; D003430:Cross-Sectional Studies; D018450:Disease Progression; D005260:Female; D015483:HIV Antibodies / Q000097:blood*; D015658:HIV Infections / Q000097:blood / Q000276:immunology / Q000821:virology; D019427:HIV Integrase / Q000276:immunology; D054303:HIV Reverse Transcriptase / Q000276:immunology; D006679:HIV Seropositivity; D015497:HIV-1 / Q000276:immunology; D006801:Humans; D007074:Immunoglobulin G / Q000097:blood*; D007630:Kenya; D008297:Male; D008562:Membrane Glycoproteins / Q000276:immunology; D008969:Molecular Sequence Data; D025341:Principal Component Analysis; D040081:Protein Array Analysis; D019562:Viral Load / Q000276:immunology; D014763:Viral Matrix Proteins / Q000276:immunology
chemical_list: D015483:HIV Antibodies; D007074:Immunoglobulin G; D008562:Membrane Glycoproteins; D014763:Viral Matrix Proteins; D019427:HIV Integrase; C514824:reverse transcriptase, Human immunodeficiency virus 1; D054303:HIV Reverse Transcriptase