Proteome-Scale Antibody Responses and Outcome of Mycobacterium tuberculosis Infection in Nonhuman Primates and in Tuberculosis Patients
Year: 2012
Type: article
Abstract: BACKGROUND: Biomarkers of progression from latent Mycobacterium tuberculosis infection to active tuberculosis are needed. We assessed correlations between infection outcome and antibody responses in macaques and humans by high-throughput, proteome-scale serological studies. METHODS: Mycobacterium tuberculosis proteome microarrays were probed with serial sera from macaques representing various infection outcomes and with single-point human sera from tuberculosis suspects. Fluorescence intensity data were analyzed by calculating Z scores and associated P values. Temporal changes in macaque antibody responses were analyzed by polynomial regression. Correlations between human responses and sputum bacillary burden were assessed by quantile and hurdle regression. RESULTS: Macaque outcome groups exhibited distinct antibody profiles: early, transient responses in latent infection and stable antibody increase in active and reactivation disease. In humans, antibody levels and reactive protein numbers increased with bacillary burden. Responses to a subset of 10 proteins were more tightly associated with disease state than reactivity to the broader reactive proteome. CONCLUSIONS: Integration of macaque and human data reveals dynamic properties of antibody responses in relation to outcome and leads to actionable findings for translational research. These include the potential of antibody responses to detect acute infection and preclinical tuberculosis and to identify serodiagnostic proteins for the spectrum of bacillary burden in tuberculosis.
Institutions: Rutgers New Jersey Medical School, Rutgers, The State University of New Jersey, University of Medicine and Dentistry of New Jersey, State Key Laboratory of Oncology in South China, Antigen Discovery (United States), FIND, University of California, Irvine, University of Pittsburgh, University of California San Diego
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: bronze
OpenAlex ID: W2128222622
