RESUMEN
Background: Although Shigella is an important cause of diarrhea in Kenyan children, robust research platforms capable of conducting incidence-based Shigella estimates and eventual Shigella-targeted clinical trials are needed to improve Shigella-related outcomes in children. Here, we describe characteristics of a disease surveillance platform whose goal is to support incidence and consequences of Shigella diarrhea as part of multicounty surveillance aimed at preparing sites and assembling expertise for future Shigella vaccine trials. Methods: We mobilized our preexisting expertise in shigellosis, vaccinology, and diarrheal disease epidemiology, which we combined with our experience conducting population-based sampling, clinical trials with high (97%-98%) retention rates, and healthcare utilization surveys. We leveraged our established demographic surveillance system (DSS), our network of healthcare centers serving the DSS, and our laboratory facilities with staff experienced in performing microbiologic and molecular diagnostics to identify enteric infections. We joined these resources with an international network of sites with similar capabilities and infrastructure to form a cohesive scientific network, designated Enterics for Global Health (EFGH), with the aim of expanding and updating our knowledge of the epidemiology and adverse consequences of shigellosis and enriching local research and career development priorities. Conclusions: Shigella surveillance data from this platform could help inform Shigella vaccine trials.
RESUMEN
Background: Molecular diagnostics on human fecal samples have identified a larger burden of shigellosis than previously appreciated by culture. Evidence of fold changes in immunoglobulin G (IgG) to conserved and type-specific Shigella antigens could be used to validate the molecular assignment of type-specific Shigella as the etiology of acute diarrhea and support polymerase chain reaction (PCR)-based microbiologic end points for vaccine trials. Methods: We will test dried blood spots collected at enrollment and 4 weeks later using bead-based immunoassays for IgG to invasion plasmid antigen B and type-specific lipopolysaccharide O-antigen for Shigella flexneri 1b, 2a, 3a, and 6 and Shigella sonnei in Shigella-positive cases and age-, site-, and season-matched test-negative controls from all sites in the Enterics for Global Health (EFGH) Shigella surveillance study. Fold antibody responses will be compared between culture-positive, culture-negative but PCR-attributable, and PCR-positive but not attributable cases and test-negative controls. Age- and site-specific seroprevalence distributions will be identified, and the association between baseline antibodies and Shigella attribution will be estimated. Conclusions: The integration of these assays into the EFGH study will help support PCR-based attribution of acute diarrhea to type-specific Shigella, describe the baseline seroprevalence of conserved and type-specific Shigella antibodies, and support correlates of protection for immunity to Shigella diarrhea. These insights can help support the development and evaluation of Shigella vaccine candidates.
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Background: Quantitative polymerase chain reaction (qPCR) targeting ipaH has been proven to be highly efficient in detecting Shigella in clinical samples compared to culture-based methods, which underestimate Shigella burden by 2- to 3-fold. qPCR assays have also been developed for Shigella speciation and serotyping, which is critical for both vaccine development and evaluation. Methods: The Enterics for Global Health (EFGH) Shigella surveillance study will utilize a customized real-time PCR-based TaqMan Array Card (TAC) interrogating 82 targets, for the detection and differentiation of Shigella spp, Shigella sonnei, Shigella flexneri serotypes, other diarrhea-associated enteropathogens, and antimicrobial resistance (AMR) genes. Total nucleic acid will be extracted from rectal swabs or stool samples, and assayed on TAC. Quantitative analysis will be performed to determine the likely attribution of Shigella and other particular etiologies of diarrhea using the quantification cycle cutoffs derived from previous studies. The qPCR results will be compared to conventional culture, serotyping, and phenotypic susceptibility approaches in EFGH. Conclusions: TAC enables simultaneous detection of diarrheal etiologies, the principal pathogen subtypes, and AMR genes. The high sensitivity of the assay enables more accurate estimation of Shigella-attributed disease burden, which is critical to informing policy and in the design of future clinical trials.
RESUMEN
Background: The measurement of fecal inflammatory biomarkers among individuals presenting to care with diarrhea could improve the identification of bacterial diarrheal episodes that would benefit from antibiotic therapy. We reviewed prior literature in this area and describe our proposed methods to evaluate 4 biomarkers in the Enterics for Global Health (EFGH) Shigella surveillance study. Methods: We systematically reviewed studies since 1970 from PubMed and Embase that assessed the diagnostic characteristics of inflammatory biomarkers to identify bacterial diarrhea episodes. We extracted sensitivity and specificity and summarized the evidence by biomarker and diarrhea etiology. In EFGH, we propose using commercial enzyme-linked immunosorbent assays to test for myeloperoxidase, calprotectin, lipocalin-2, and hemoglobin in stored whole stool samples collected within 24 hours of enrollment from participants in the Bangladesh, Kenya, Malawi, Pakistan, Peru, and The Gambia sites. We will develop clinical prediction scores that incorporate the inflammatory biomarkers and evaluate their ability to identify Shigella and other bacterial etiologies of diarrhea as determined by quantitative polymerase chain reaction (qPCR). Results: Forty-nine studies that assessed fecal leukocytes (n = 39), red blood cells (n = 26), lactoferrin (n = 13), calprotectin (n = 8), and myeloperoxidase (n = 1) were included in the systematic review. Sensitivities were high for identifying Shigella, moderate for identifying any bacteria, and comparable across biomarkers. Specificities varied depending on the outcomes assessed. Prior studies were generally small, identified red and white blood cells by microscopy, and used insensitive gold standard diagnostics, such as conventional bacteriological culture for pathogen detection. Conclusions: Our evaluation of inflammatory biomarkers to distinguish diarrhea etiologies as determined by qPCR will provide an important addition to the prior literature, which was likely biased by the limited sensitivity of the gold standard diagnostics used. We will determine whether point-of-care biomarker tests could be a viable strategy to inform treatment decision making and increase appropriate targeting of antibiotic treatment to bacterial diarrhea episodes.