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IntroductionLatent tuberculosis infection (LTBI) is a common coinfection in people living with HIV (PWH). How LTBI and HIV exposure in utero influence the development of infant humoral immunity is not well characterized. To address this question, we assessed the relationship between maternal humoral responses in pregnant women with HIV or with HIV/LTBI on humoral responses in infants to BCG vaccination and TB acquisition.MethodsPlasma samples were obtained from mother infant pairs during pregnancy (14-34 wks gestation) and in infants at 12 and 44 wks of age from the IMPAACT P1078 clinical trial. LTBI was established by Interferon gamma release assay (IGRA). Progression to active TB (ATB) disease was observed in 5 women at various times after giving birth. All infants were BCG vaccinated at birth and tested for IGRA at 44 weeks. Mtb (PPD, ESAT6/CFP10, Ag85A, LAM), HIV (GP120), and Influenza (HA) specific IgG, IgM, and IgA were measured in plasma samples using a bead based Luminex assay with Flexmap 3D.ResultsIn maternal plasma there were no differences in Mtb-specific antibodies or viral antibodies in relation to maternal IGRA status. ATB progressors showed increases in Mtb-specific antibodies at diagnosis compared to study entry. However, when compared to the non-progressors at entry, progressors had higher levels of Ag85A IgG and reduced ESAT6/CFP10 IgG and LAM IgG, IgM, and IgA1. All infants showed a decrease in IgG to viral antigens (HIV GP120 and HA) from 12 to 44 weeks attributed to waning of maternally transferred antibody titers. However, Mtb-specific (PPD, ESAT6/CFP10, Ag85A, and LAM) IgG and IgM increased from 12 to 44 weeks. HIV and HA IgG levels in maternal and 12-week infant plasma were highly correlated, and ESAT6/CFP10 IgG and LAM IgG showed a relationship between maternal and infant Abs. Finally, in the subset of infants that tested IGRA positive at 44 weeks, we observed a trend for lower LAM IgM compared to IGRA- infants at 44 weeks.DiscussionThe results from our study raise the possibility that antibodies to LAM are associated with protection from progression to ATB and support further research into the development of humoral immunity against TB through infection or vaccination.

Cancer is one of the leading causes of death, but mortality can be reduced by detecting tumors earlier so that treatment is initiated at a less aggressive stage. The tradeoff between costs associated with screening and its benefit makes the decision of whom to screen and when a challenge. To enable comparisons across screening strategies for any cancer type, we demonstrate a mathematical modeling platform based on the theory of queuing networks designed for quantifying the benefits of screening strategies. Our methodology can be used to design optimal screening protocols and to estimate their benefits for specific patient populations. Our method is amenable to exact analysis, thus circumventing the need for simulations, and is capable of exactly quantifying outcomes given variability in the age of diagnosis, rate of progression, and screening sensitivity and intervention outcomes. We demonstrate the power of this methodology by applying it to data from the Surveillance, Epidemiology and End Results (SEER) program. Our approach estimates the benefits that various novel screening programs would confer to different patient populations, thus enabling us to formulate an optimal screening allocation and quantify its potential effects for any cancer type and intervention.