Dynamic immune markers predict HIV acquisition and augment associations with sociobehavioral factors for HIV exposure
Rachel A. Bender Ignacio,
Sayan Dasgupta,
Rogelio Valdez,
Urvashi Pandey,
Siavash Pasalar,
Ricardo Alfaro,
Florian Hladik,
Germán Gornalusse,
Javier R. Lama,
Ann Duerr
Affiliations
Rachel A. Bender Ignacio
Division of Allergy and Infectious Diseases, Department of Medicine, University of Washington, Seattle, WA 98104, USA; Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; Department of Global Health, University of Washington, Seattle, WA 98195, USA; Corresponding author
Sayan Dasgupta
Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
Rogelio Valdez
Case Western Reserve University School of Medicine, Cleveland, OH 44106, USA
Urvashi Pandey
Department of Obstetrics and Gynecology, University of Washington, Seattle, WA 98195, USA
Siavash Pasalar
Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
Ricardo Alfaro
Centro de Investigaciones Tecnológicas Biomédicas y Medioambientales, Universidad Nacional Mayor de San Marcos, Bellavista, Lima 07006, Peru
Florian Hladik
Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; Department of Obstetrics and Gynecology, University of Washington, Seattle, WA 98195, USA
Germán Gornalusse
Department of Obstetrics and Gynecology, University of Washington, Seattle, WA 98195, USA
Javier R. Lama
Asociación Civil Impacta Salud y Educación, Lima 15063, Peru; Department of Global Health, University of Washington, Seattle, WA 98195, USA
Ann Duerr
Vaccine and Infectious Diseases Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA; Department of Global Health, University of Washington, Seattle, WA 98195, USA
Summary: Prior studies attempting to link biomarkers of immune activation with risk of acquiring HIV have relied on cross sectional samples, most without proximity to HIV acquisition. We created a nested case-control study within the Sabes study in Peru, and assessed a panel of plasma immune biomarkers at enrollment and longitudinally, including within a month of diagnosis of primary HIV or matched timepoint in controls. We used machine learning to select biomarkers and sociobehavioral covariates predictive of HIV acquisition. Most biomarkers were indistinguishable between cases and controls one month before HIV diagnosis. However, levels differed between cases and controls at study entry, months to years earlier. Dynamic changes in IL-2, IL-7, IL-10, IP-10 and IL-12, rather than absolute levels, jointly predicted HIV risk when added to traditional risk factors, and there was modest effect modification of biomarkers on association between sociobehavioral risk factors and HIV acquisition.
