Rare Variable M. tuberculosis Antigens induce predominant Th17 responses in human infection.

CD4 T cells are essential for immunity to M. tuberculosis (Mtb), and emerging evidence indicates that IL-17-producing Th17 cells contribute to immunity to Mtb. While identifying protective T cell effector functions is important for TB vaccine design, T cell antigen specificity is also likely to be important. To identify antigens that induce protective immunity, we reasoned that as in other pathogens, effective immune recognition drives sequence diversity in individual Mtb antigens. We previously identified Mtb genes under evolutionary diversifying selection pressure whose products we term Rare Variable Mtb Antigens (RVMA). Here, in two distinct human cohorts with recent exposure to TB, we found that RVMA preferentially induce CD4 T cells that express RoRγt and produce IL-17, in contrast to 'classical' Mtb antigens that induce T cells that produce IFNγ. Our results suggest that RVMA can be valuable antigens in vaccines for those already infected with Mtb to amplify existing antigen-specific Th17 responses to prevent TB disease.

Comparison of Masimo Total Hemoglobin SpHb® continuous non-invasive hemoglobin monitoring device with laboratory complete blood count measurement using venous sample: Protocol for an observational substudy of the Pregnancy Risk and Infant Surveillance and Measurement Alliance Maternal and Newborn Health (PRISMA MNH) study.

Background: The Masimo Total Hemoglobin SpHb® is a continuous and non-invasive handheld device to measure hemoglobin levels. Previous research has found that SpHb is able to accurately detect hemoglobin levels in adult patients with a similar degree of bias and standard deviation to point-of-care invasive method measurements. Generally, limited clinical evidence, lack of validation of Masimo at higher than and lower than hemoglobin threshold values, and scientific consensus supporting the use of Masimo for accurate hemoglobin testing for the diagnosis of anemia during pregnancy calls for further research. Methods and analysis: The proposed prospective cohort will be nested within the ongoing Pregnancy Risk and Infant Surveillance and Measurement Alliance (PRISMA) Maternal and Newborn Health (MNH) study. Three study sites (located in Zambia, Kenya, and Pakistan) will participate and collect hemoglobin data at five time points (<20 weeks, 20 weeks, 28 weeks, 36 weeks' gestation, and six weeks postpartum). We will measure hemoglobin using a venous blood sample via hematology auto-analyzer complete blood count (gold standard) and the non-invasive device. The primary objective is to assess agreement between Masimo total hemoglobin and complete blood count and on a continuous scale using Intraclass Correlation Coefficient and Bland-Altman Analysis. The second objective is to assess agreement between the two measures on a binary scale using Positive Percentage Agreement and Negative Percentage Agreement, Cohen's Kappa, and McNemar Test. On an ordinal scale, agreement will be measured using Weighted Cohen's Kappa and Harrel's Concordance Index. Lastly, we will assess factors that might affect the accuracy of Masimo total hemoglobin using linear mixed models. Conclusions: The primary aim of this study is to assess the validity of the non-invasive Masimo device compared to the gold standard method of invasive hemoglobin measurements during pregnancy and postpartum periods for the diagnosis of anemia.

Prediction of postpartum hemorrhage (PPH) using machine learning algorithms in a Kenyan population.

Introduction: Postpartum hemorrhage (PPH) is a significant cause of maternal mortality worldwide, particularly in low- and middle-income countries. It is essential to develop effective prediction models to identify women at risk of PPH and implement appropriate interventions to reduce maternal morbidity and mortality. This study aims to predict the occurrence of postpartum hemorrhage using machine learning models based on antenatal, intrapartum, and postnatal visit data obtained from the Kenya Antenatal and Postnatal Care Research Collective cohort. Method: Four machine learning models - logistic regression, naïve Bayes, decision tree, and random forest - were constructed using 67% training data (1,056/1,576). The training data was further split into 67% for model building and 33% cross validation. Once the models are built, the remaining 33% (520/1,576) independent test data was used for external validation to confirm the models' performance. Models were fine-tuned using feature selection through extra tree classifier technique. Model performance was assessed using accuracy, sensitivity, and area under the curve (AUC) of the receiver operating characteristics (ROC) curve. Result: The naïve Bayes model performed best with 0.95 accuracy, 0.97 specificity, and 0.76 AUC. Seven factors (anemia, limited prenatal care, hemoglobin concentrations, signs of pallor at intrapartum, intrapartum systolic blood pressure, intrapartum diastolic blood pressure, and intrapartum respiratory rate) were associated with PPH prediction in Kenyan population. Discussion: This study demonstrates the potential of machine learning models in predicting PPH in the Kenyan population. Future studies with larger datasets and more PPH cases should be conducted to improve prediction performance of machine learning model. Such prediction algorithms would immensely help to construct a personalized obstetric path for each pregnant patient, improve resource allocation, and reduce maternal mortality and morbidity.

Diagnostic performance of oral swabs for non-sputum based TB diagnosis in a TB/HIV endemic setting.

OBJECTIVE: We evaluated diagnostic performance of oral swab analysis (OSA) for tuberculosis (TB) in a high HIV/TB burden setting in Kenya. METHODS: In this cross-sectional study, buccal swabs and sputum were collected from 100 participants with suspected TB in outpatient clinics in Kenya at enrollment and subsequent morning visits. Buccal swabs underwent IS6110-targeted qPCR analysis. Sputum was evaluated by Xpert MTB/RIF (Xpert) and culture. Diagnostic performance of OSA for TB diagnosis was evaluated relative to a combined reference of sputum Xpert and culture. RESULTS: Among 100 participants, 54% were living with HIV (PLHIV). Twenty percent (20/100) of participants had confirmed TB (19/20 [95%] culture-positive, 17/20 [85%] Xpert-positive). Overall buccal swab sensitivity was 65.0% (95% CI 40.8-84.6%) vs. sputum Xpert/culture and 76.5% (95% CI 50.1-93.2%) vs. sputum Xpert alone. Specificity was 81.3% (95% CI 71.0-89.1%) and 81.9% (95% CI 72.0-89.5%) compared to sputum Xpert/culture and Xpert alone, respectively. Sensitivity among PLHIV (n = 54) with suspected TB was 83.3% (95% CI 35.9-99.6%) vs. sputum Xpert/culture and 100% (95% CI 47.8-100.0%) vs. sputum Xpert alone. Among participants with TB, mean OSA threshold quantitation cycle (Cq) value was lower (stronger signal) at subsequent morning compared to enrolment visit (33.4 SD ± 3.7 vs. 35.2 SD ± 2.9, p = 0.009). CONCLUSIONS: In this pilot study, results confirm M. tuberculosis DNA is detectable in oral swabs including among PLHIV with fair diagnostic performance. Further work is needed to optimize OSA and evaluate its utility in diverse settings.

Schistosoma mansoni Infection Is Associated With a Higher Probability of Tuberculosis Disease in HIV-Infected Adults in Kenya.

BACKGROUND: Helminth infections can modulate immunity to Mycobacterium tuberculosis (Mtb). However, the effect of helminths, including Schistosoma mansoni (SM), on Mtb infection outcomes is less clear. Furthermore, HIV is a known risk factor for tuberculosis (TB) disease and has been implicated in SM pathogenesis. Therefore, it is important to evaluate whether HIV modifies the association between SM and Mtb infection. SETTING: HIV-infected and HIV-uninfected adults were enrolled in Kisumu County, Kenya, between 2014 and 2017 and categorized into 3 groups based on Mtb infection status: Mtb-uninfected healthy controls, latent TB infection (LTBI), and active TB disease. Participants were subsequently evaluated for infection with SM. METHODS: We used targeted minimum loss estimation and super learning to estimate a covariate-adjusted association between SM and Mtb infection outcomes, defined as the probability of being Mtb-uninfected healthy controls, LTBI, or TB. HIV status was evaluated as an effect modifier of this association. RESULTS: SM was not associated with differences in baseline demographic or clinical features of participants in this study, nor with additional parasitic infections. Covariate-adjusted analyses indicated that infection with SM was associated with a 4% higher estimated proportion of active TB cases in HIV-uninfected individuals and a 14% higher estimated proportion of active TB cases in HIV-infected individuals. There were no differences in estimated proportions of LTBI cases. CONCLUSIONS: We provide evidence that SM infection is associated with a higher probability of active TB disease, particularly in HIV-infected individuals.

Development of colorimetric sensor array for diagnosis of tuberculosis through detection of urinary volatile organic compounds.

BACKGROUND: Top priorities for tuberculosis control and elimination include a simple, low-cost screening test using sputum and a non-sputum-based test in patients that do not produce sputum. The aim of this study was to evaluate the performance of a colorimetric sensor array (CSA) test, for analysis of volatile organic compounds in urine, in the diagnosis of pulmonary TB. MATERIAL AND METHODS: Urine samples were collected from individuals suspected of having pulmonary TB in Western Kenya. Reference methods included MGIT culture and/or Xpert MTB/RIF nucleic acid amplification test on sputa. Fresh urine samples were tested with the CSA, with acid and base and without an additive. The CSA were digitally imaged, and the resulting colorimetric response patterns were used for chemometric analysis. Sensitivity, specificity, and negative (NPV) and positive predictive (PPV) values were determined for HIV-positive and HIV-negative patients. RESULTS: In HIV-negative patients, the highest accuracy was obtained in urine samples pre-treated with a base, yielding a sensitivity, specificity, PPV, and NPV of 78.3% (65/83), 69.2% (54/78), 73.0% (n/89) and 75.0% (n/72). The highest sensitivity of 79.5% was achieved using sensor data from all three test conditions at a specificity of 65.4%. In HIV-positive subjects, the sensor performance was substantially lower with sensitivity, specificity, PPV, and NPV ranging from 48.3% to 62.3%, 54.1% to 74.0%, 55.9% to 64.2%, and 60.6% to 64.9%, respectively. CONCLUSION: The CSA fingerprint of urine headspace volatiles showed moderate accuracy in diagnosing TB in HIV-negative patients, but the sensor performance dropped substantially in HIV-coinfected patients. Further development of TB-responsive CSA indicators may improve the accuracy of CSA urine assay.

A High Throughput Whole Blood Assay for Analysis of Multiple Antigen-Specific T Cell Responses in Human Mycobacterium tuberculosis Infection.

Antigen-specific CD4 and CD8 T cells are important components of the immune response to Mycobacterium tuberculosis, yet little information is currently known regarding how the breadth, specificity, phenotype, and function of M. tuberculosis-specific T cells correlate with M. tuberculosis infection outcome in humans. To facilitate evaluation of human M. tuberculosis-specific T cell responses targeting multiple different Ags, we sought to develop a high throughput and reproducible T cell response spectrum assay requiring low blood sample volumes. We describe here the optimization and standardization of a microtiter plate-based, diluted whole blood stimulation assay utilizing overlapping peptide pools corresponding to a functionally diverse panel of 60 M. tuberculosis Ags. Using IFN-γ production as a readout of Ag specificity, the assay can be conducted using 50 µl of blood per test condition and can be expanded to accommodate additional Ags. We evaluated the intra- and interassay variability, and implemented testing of the assay in diverse cohorts of M. tuberculosis-unexposed healthy adults, foreign-born adults with latent M. tuberculosis infection residing in the United States, and tuberculosis household contacts with latent M. tuberculosis infection in a tuberculosis-endemic setting in Kenya. The M. tuberculosis-specific T cell response spectrum assay further enhances the immunological toolkit available for evaluating M. tuberculosis-specific T cell responses across different states of M. tuberculosis infection, and can be readily implemented in resource-limited settings. Moreover, application of the assay to longitudinal cohorts will facilitate evaluation of treatment- or vaccine-induced changes in the breadth and specificity of Ag-specific T cell responses, as well as identification of M. tuberculosis-specific T cell responses associated with M. tuberculosis infection outcomes.