OBJECTIVE: Prior hypothesis-driven studies identified immunophenotypic characteristics associated with the control of HIV replication without antiretroviral therapy (HIV controllers) as well as with the degree of CD4 T-cell recovery during ART. We hypothesized that an unbiased 'discovery-based' approach might identify novel immunologic characteristics of these phenotypes. DESIGN: We performed immunophenotyping on four 'aviremic' patient groups: HIV controllers (n = 98), antiretroviral-treated immunologic nonresponders (CD4 < 350; n = 59), antiretroviral-treated immunologic responders (CD4 > 350, n = 142), and as a control group HIV-negative adults (n = 43). We measured levels of T-cell maturation, activation, dysfunction, senescence, functionality, and proliferation. METHODS: Supervised learning assessed the relative importance of immune parameters in predicting clinical phenotypes (controller, immunologic responder, or immunologic nonresponder). Unsupervised learning clustered immune parameters and examined if these clusters corresponded to clinical phenotypes. RESULTS: HIV controllers were characterized by high percentages of HIV-specific T-cell responses and decreased percentages of cells expressing human leukocytic antigen-antigen D related in naive, central memory, and effector T-cell subsets. Immunologic nonresponders were characterized by higher percentages of CD4 T cells that were TNFα+ or INFγ+, higher percentages of activated naive and central memory T cells, and higher percentages of cells expressing programmed cell death protein 1. Unsupervised learning found two distinct clusters of controllers and two distinct clusters of immunologic nonresponders, perhaps suggesting different mechanisms for the clinical outcomes. CONCLUSION: Our discovery-based approach confirmed previously reported characteristics that distinguish aviremic individuals, but also identified novel immunologic phenotypes and distinct clinical subpopulations that should lead to more focused pathogenesis studies that might identify targets for novel therapeutic interventions.
OBJECTIVE: Prior hypothesis-driven studies identified immunophenotypic characteristics associated with the control of HIV replication without antiretroviral therapy (HIV controllers) as well as with the degree of CD4 T-cell recovery during ART. We hypothesized that an unbiased 'discovery-based' approach might identify novel immunologic characteristics of these phenotypes. DESIGN: We performed immunophenotyping on four 'aviremic' patient groups: HIV controllers (n = 98), antiretroviral-treated immunologic nonresponders (CD4 < 350; n = 59), antiretroviral-treated immunologic responders (CD4 > 350, n = 142), and as a control group HIV-negative adults (n = 43). We measured levels of T-cell maturation, activation, dysfunction, senescence, functionality, and proliferation. METHODS: Supervised learning assessed the relative importance of immune parameters in predicting clinical phenotypes (controller, immunologic responder, or immunologic nonresponder). Unsupervised learning clustered immune parameters and examined if these clusters corresponded to clinical phenotypes. RESULTS: HIV controllers were characterized by high percentages of HIV-specific T-cell responses and decreased percentages of cells expressing human leukocytic antigen-antigen D related in naive, central memory, and effector T-cell subsets. Immunologic nonresponders were characterized by higher percentages of CD4 T cells that were TNFα+ or INFγ+, higher percentages of activated naive and central memory T cells, and higher percentages of cells expressing programmed cell death protein 1. Unsupervised learning found two distinct clusters of controllers and two distinct clusters of immunologic nonresponders, perhaps suggesting different mechanisms for the clinical outcomes. CONCLUSION: Our discovery-based approach confirmed previously reported characteristics that distinguish aviremic individuals, but also identified novel immunologic phenotypes and distinct clinical subpopulations that should lead to more focused pathogenesis studies that might identify targets for novel therapeutic interventions.
Authors: R Mehrian-Shai; C D Chen; T Shi; S Horvath; S F Nelson; J K V Reichardt; C L Sawyers Journal: Proc Natl Acad Sci U S A Date: 2007-03-19 Impact factor: 11.205
Authors: Michael M Lederman; Leonard Calabrese; Nicholas T Funderburg; Brian Clagett; Kathy Medvik; Hector Bonilla; Barbara Gripshover; Robert A Salata; Alan Taege; Michelle Lisgaris; Grace A McComsey; Elizabeth Kirchner; Jane Baum; Carey Shive; Robert Asaad; Robert C Kalayjian; Scott F Sieg; Benigno Rodriguez Journal: J Infect Dis Date: 2011-10-15 Impact factor: 5.226
Authors: Sulggi A Lee; Elizabeth Sinclair; Vivek Jain; Yong Huang; Lorrie Epling; Mark Van Natta; Curtis L Meinert; Jeffrey N Martin; Joseph M McCune; Steven G Deeks; Michael M Lederman; Frederick M Hecht; Peter W Hunt Journal: J Infect Dis Date: 2014-02-28 Impact factor: 5.226
Authors: Matthew S Freiberg; Chung-Chou H Chang; Lewis H Kuller; Melissa Skanderson; Elliott Lowy; Kevin L Kraemer; Adeel A Butt; Matthew Bidwell Goetz; David Leaf; Kris Ann Oursler; David Rimland; Maria Rodriguez Barradas; Sheldon Brown; Cynthia Gibert; Kathy McGinnis; Kristina Crothers; Jason Sico; Heidi Crane; Alberta Warner; Stephen Gottlieb; John Gottdiener; Russell P Tracy; Matthew Budoff; Courtney Watson; Kaku A Armah; Donna Doebler; Kendall Bryant; Amy C Justice Journal: JAMA Intern Med Date: 2013-04-22 Impact factor: 21.873
Authors: Jason V Baker; Grace Peng; Joshua Rapkin; Donald I Abrams; Michael J Silverberg; Rodger D MacArthur; Winston P Cavert; W Keith Henry; James D Neaton Journal: AIDS Date: 2008-04-23 Impact factor: 4.177
Authors: Benoît Vingert; Daniela Benati; Olivier Lambotte; Pierre de Truchis; Laurence Slama; Patricia Jeannin; Moran Galperin; Santiago Perez-Patrigeon; Faroudy Boufassa; William W Kwok; Fabrice Lemaître; Jean-François Delfraissy; Jacques Thèze; Lisa A Chakrabarti Journal: J Virol Date: 2012-07-25 Impact factor: 5.103
Authors: Michael R Betts; Martha C Nason; Sadie M West; Stephen C De Rosa; Stephen A Migueles; Jonathan Abraham; Michael M Lederman; Jose M Benito; Paul A Goepfert; Mark Connors; Mario Roederer; Richard A Koup Journal: Blood Date: 2006-02-07 Impact factor: 22.113
Authors: José M Benito; María C Ortiz; Agathe León; Luis A Sarabia; José M Ligos; María Montoya; Marcial Garcia; Ezequiel Ruiz-Mateos; Rosario Palacios; Alfonso Cabello; Clara Restrepo; Carmen Rodriguez; Jorge Del Romero; Manuel Leal; María A Muñoz-Fernández; José Alcamí; Felipe García; Miguel Górgolas; Norma Rallón Journal: BMC Med Date: 2018-02-28 Impact factor: 8.775
Authors: Rachel L Rutishauser; Christian Deo T Deguit; Joseph Hiatt; Franziska Blaeschke; Theodore L Roth; Lynn Wang; Kyle A Raymond; Carly E Starke; Joseph C Mudd; Wenxuan Chen; Carolyn Smullin; Rodrigo Matus-Nicodemos; Rebecca Hoh; Melissa Krone; Frederick M Hecht; Christopher D Pilcher; Jeffrey N Martin; Richard A Koup; Daniel C Douek; Jason M Brenchley; Rafick-Pierre Sékaly; Satish K Pillai; Alexander Marson; Steven G Deeks; Joseph M McCune; Peter W Hunt Journal: JCI Insight Date: 2021-02-08
Authors: Malin Holm Meyer-Myklestad; Asle Wilhelm Medhus; Kristina Berg Lorvik; Ingebjørg Seljeflot; Simen Hyll Hansen; Kristian Holm; Birgitte Stiksrud; Marius Trøseid; Johannes Roksund Hov; Dag Kvale; Anne Margarita Dyrhol-Riise; Martin Kummen; Dag Henrik Reikvam Journal: J Infect Dis Date: 2022-02-15 Impact factor: 5.226
Authors: Kristina Berg Lorvik; Malin Holm Meyer-Myklestad; Kushi Kushekar; Charlotte Handeland; Asle Wilhelm Medhus; Marius Lund-Iversen; Birgitte Stiksrud; Dag Kvale; Anne Margarita Dyrhol-Riise; Kjetil Taskén; Dag Henrik Reikvam Journal: Front Immunol Date: 2021-10-07 Impact factor: 7.561