Plasma Immunoglobulin A Responses Against 2 Salmonella Typhi Antigens Identify Patients With Typhoid Fever

Background There is a need for a reliable, simple diagnostic assay for typhoid fever. Available commercial serologic assays for typhoid fever have limited sensitivity and specificity. Using high-throughput immunoscreening technologies, we previously identified several immunoreactive Salmonella Typhi antigens that seem promising for possible inclusion in a new diagnostic assay: hemolysin E (HlyE), cytolethal distending toxin, S. Typhi lipopolysaccharide (LPS), and S. Typhi membrane preparation. Methods We assessed plasma antibody responses (immunoglobulin [Ig] M, IgA, and IgG) to these antigens by means of enzyme-linked immunosorbent assay in patients with suspected enteric fever, controls with other febrile illnesses, and healthy controls in Dhaka, Bangladesh and performed Tubex and Typhidot tests, the Widal assay, and the typhoid/paratyphoid test (TPTest) in each patient. Using machine learning methods, we identified a parsimonious serology signature to distinguish acute typhoid cases from controls and then validated our findings in an independent test cohort from Nepal of patients with culture-confirmed S. Typhi and controls with other bacteremic illnesses. Results We demonstrated that the use of 2 antigens (HlyE and LPS) with 1 antibody isotype (IgA) could distinguish typhoid from other invasive bacterial infections (area under the receiver operating characteristic curve [AUC], 0.95; sensitivity, 90%, specificity, 92%). Use of a single antigen (HlyE) and isotype (IgA) had an AUC of 0.93. Conclusion Our results suggest that development of a diagnostic assay for acute typhoid fever focused on detecting IgA responses against HlyE, with or without LPS, is warranted. Using machine learning methods, we identified and validated anti-hemolysin E immunoglobulin A and antilipopolysaccharide immunoglobulin A plasma responses as predictors of acute typhoid fever in 2 independent cohorts of patients in Bangladesh and Nepal (sensitivity, 90%; specificity, 92%).