TaqMan Array Card Research Articles

Influence of Enterocytozoon bieneusi Infection on Child Growth: A Secondary Analysis of the MAL-ED Birth Cohort Study.

Malnutrition in the early days of life is a global public health concern that affects children's growth. It results from a variety of factors, including pathogenic infections. Enterocytozoon bieneusi is a microsporidian parasite that can cause diarrhea and malnutrition in children. The study aimed to assess the impact of E. bieneusi on child growth. The MAL-ED study, a multicountry birth cohort research project, investigated the relationship between enteric infections and malnutrition in participating children from eight countries. A customized real-time polymerase chain reaction-based TaqMan array card was used in this study to identify enteropathogens from stool samples, where E. bieneusi was one of the target pathogens. The impacts of E. bieneusi infection on growth measures were assessed. Mixed-effect linear models were used to investigate the relationship between E. bieneusi and growth outcomes, including length-for-age (LAZ), weight-for-age (WAZ), and weight-for-length (WLZ) Z scores. At the endpoint (last month of measurement), the infected group had significantly lower scores than the noninfected group for all outcomes. The adjusted difference-in-difference (D-in-D) values were -0.53 (95% CI: -0.67 to -0.38) for LAZ, -0.38 (95% CI: -0.52 to -0.23) for WAZ, and -0.22 (95% CI: -0.38 to -0.06) for WLZ. Enterocytozoon bieneusi infection has been identified as a factor associated with reduced linear growth, weight gain, and weight gain relative to linear growth in children, underscoring the importance of treating this infection.

Effect of one prophylactic dose of Azithromycin on Bifidobacterium infantis colonization in infants from the Mumta Trial.

The effects of antibiotics on the microbiome remain incompletely understood. Azithromycin (AZ) has been shown to improve child survival and infant growth outcomes. This study aimed to assess the impact of AZ on B. infantis colonization and bacterial enteropathogen count in the infant gut. We analyzed clinical, biomarker, B. infantis and enteropathogen data from 150 mother-infant dyads from the MUMTA Lactating Women study. Colonization of B. infantis was assessed using quantitative PCR of fecal samples. We utilized a customized PCR-based TaqMan Array Card (TAC) for enteropathogen detection. AZ administration was associated with a 1.99-fold (95% CI 1.33-2.97) increase in colonization by B. infantis. B. infantis colonization was highest when inflammatory biomarker levels were within normal range. Mode of delivery (RR 2.43; 95% CI: 1.58, 3.76) and colostrum (RR2.05; 95% CI: 1.41, 2.98) given to the infant within 24 hours of birth were associated with B. infantis colonization. A single dose of AZ on day 42 reduced bacterial enteropathogen count in the AZ group on day 56, as compared to the pre-AZ count. Bacterial enteropathogen count for infants with wasting (Weight for length Z-score WLZ<-2) was 1.43-fold higher (95% CI: 1.00-2.03) than for infants with WLZ≥ -2. Over 60% of infants harboured with the macrolide resistance mph(A) gene CONCLUSIONS: AZ administration increases B. infantis colonization and reduces bacterial enteropathogen count in infants.

Multiplex PCR detection of enteric pathogens in a community-based birth cohort in Ecuador: comparison of xTAG-GPP and TaqMan array card assays

Multiplex PCR detection of enteric pathogens in a community-based birth cohort in Ecuador: comparison of xTAG-GPP and TaqMan array card assays

Automated post-run analysis of arrayed quantitative PCR amplification curves using machine learning.

The TaqMan Array Card (TAC) is an arrayed, high-throughput qPCR platform that can simultaneously detect multiple targets in a single reaction. However, the manual post-run analysis of TAC data is time consuming and subject to interpretation. We sought to automate the post-run analysis of TAC data using machine learning models. We used 165,214 qPCR amplification curves from two studies to train and test two eXtreme Gradient Boosting (XGBoost) models. Previous manual analyses of the amplification curves by experts in qPCR analysis were used as the gold standard. First, a classification model predicted whether amplification occurred or not, and if so, a second model predicted the cycle threshold (Ct) value. We used 5-fold cross-validation to tune the models and assessed performance using accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and mean absolute error (MAE). For external validation, we used 1,472 reactions previously analyzed by 17 laboratory scientists as part of an external quality assessment for a multisite study. In internal validation, the classification model achieved an accuracy of 0.996, sensitivity of 0.997, specificity of 0.993, PPV of 0.998, and NPV of 0.991. The Ct prediction model achieved a MAE of 0.590. In external validation, the automated analysis achieved an accuracy of 0.997 and a MAE of 0.611, and the automated analysis was more accurate than manual analyses by 14 of the 17 laboratory scientists. We automated the post-run analysis of highly-arrayed qPCR data using machine learning models with high accuracy in comparison to a manual gold standard. This approach has the potential to save time and improve reproducibility in laboratories using the TAC platform and other high-throughput qPCR approaches.

Environmental Exposures Associated with Enteropathogen Infection in Six-Month-Old Children Enrolled in the ECoMiD Cohort along a Rural-Urban Gradient in Northern Ecuador†.

Enteropathogens are major contributors to mortality and morbidity, particularly in settings with limited access to water, sanitation, and hygiene infrastructure. To assess transmission pathways associated with enteropathogen infection, we measured household environmental conditions and assayed 22 enteropathogens using TaqMan Array Cards in stool samples from 276 six-month-old children living in communities along a rural-urban gradient in Northern Ecuador. We utilized multivariable models, risk factor importance, and distance-based statistical methods to test factors associated with infection. Most children (89%) carried at least one pathogen, and 72% carried two or more. Bacterial infections (82% of participants) were more common than viruses (58%) or parasites (9.1%). Infants living in the urban site had decreased infection risks compared to those in rural locations. Improved water and sanitation were most predictive of reduced infection risk. Improved water was associated with decreased enterotoxigenic E. coli prevalence, and improved sanitation was associated with lower prevalence of any infection and specifically norovirus. Animal exposure was associated with increased Salmonella prevalence. Children measured during the rainy season had fewer viral and more bacterial infections. Identifying environmental exposures associated with specific pathogen outcomes provides insights into transmission pathways, which contribute critical information for developing effective strategies to improve child health.

Enteric Pathogens in Humans, Domesticated Animals, and Drinking Water in a Low-Income Urban Area of Nairobi, Kenya.

To explore the sources of and associated risks with drinking water contamination in low-income, densely populated urban areas, we collected human feces, domesticated animal feces, and source and stored drinking water samples in Nairobi, Kenya in 2019; and analyzed them using microbial source tracking (MST) and enteric pathogen TaqMan Array Cards (TACs). We established host-pathogen relationships in this setting, including detecting Shigella and Norovirus─which are typically associated with humans─in dog feces. We evaluated stored and source drinking water quality using indicator Escherichia coli (E. coli), MST markers, and TACs, detecting pathogen targets in drinking water that were also detected in specific animal feces. This work highlights the need for further evaluation of host-pathogen relationships and the directionality of pathogen transmission to prevent the disease burden associated with unsafe drinking water and domestic animal ownership.

Respiratory viruses associated with severe acute respiratory infection in children aged

With the increased availability of licensed vaccines for respiratory viruses such as severe acute respiratory syndrome coronavirus 2, respiratory syncytial virus (RSV), and influenza virus, a better understanding of the viral aetiology of severe acute respiratory infections (SARI) among children could help in optimising the use of these vaccines. We conducted a study among children aged <5 years hospitalised with SARI at a tertiary care children's hospital in north India and tested for common respiratory pathogens. We randomly enrolled eligible SARI cases aged <5 years from August 2013 to July 2015. SARI cases were defined as either <7-day history of fever with cough or in children aged eight days to three months, a physician diagnosis of acute lower respiratory infection requiring hospitalisation. We also enrolled an age-group matched control without any acute illness in a 2:1 ratio from the outpatient clinic within 24 hours of case enrolment. Nasopharyngeal and/or oropharyngeal swabs were collected and tested using TaqMan Array Cards, a real-time reverse transcription polymerase chain reaction-based multi-pathogen testing platform for selected respiratory viruses among the enrolled cases and controls. We compared the prevalence of each pathogen among cases and controls using the χ2 (χ2) or Fisher exact test (P < 0.05). We used logistic regression to estimate adjusted odds ratios (aORs) which were then used to calculate aetiologic fractions (EFs). We enrolled 840 cases and 419 outpatient controls. Almost half of the individuals in the whole sample were aged <6 months (n = 521, 41.4%). Females made up 33.7% of cases and 37.2% of controls. Viral detections were more common among cases (69%, 95% confidence interval (CI) = 66, 73) compared to controls (33%; 95% CI = 29, 38) (P < 0.01). RSV (n = 257, 31%; 95% CI = 28, 34%) was the most common virus detected among cases. Influenza A was detected among 24 (3%; 95% CI = 2, 4%), and influenza B among 5 (1%; 95% CI = 0, 1%) cases. The association between the virus and SARI was strongest for RSV (aOR = 23; 95% CI = 12, 47; EF = 96%). Antivirals were administered to 1% of SARI cases while 78% received antibiotics. Using a multi-pathogen molecular detection method, we detected respiratory viruses among more than two-thirds of children aged <5 years admitted with SARI in the Delhi tertiary care children's hospital. The guidelines for preventing and managing SARI cases among children could be optimised further with the improved availability of antivirals and vaccines.

Combined analysis of a serum mRNA/miRNA marker signature and CA 19-9 for timely and accurate diagnosis of recurrence after resection of pancreatic ductal adenocarcinoma: A prospective multicenter cohort study.

Timely and accurate detection of tumor recurrence in pancreatic ductal adenocarcinoma (PDAC) patients is an urgent and unmet medical need. This study aimed to develop a noninvasive molecular diagnostic procedure for the detection of recurrence after PDAC resection based on quantification of circulating mRNA and miRNA biomarkers in serum samples. In a multicentric study, serum samples from a total of 146 patients were prospectively collected after resection. Samples were classified into a "No Evidence of Disease" and a "Recurrence" group based on clinical follow-up data. A multianalyte biomarker panel was composed of mRNAs and miRNA markers and simultaneously analyzed in serum samples using custom microfluidic qPCR arrays (TaqMan array cards). A diagnostic algorithm was developed combining a 7-gene marker signature with CA19-9 data. The best-performing marker combination achieved 90% diagnostic accuracy in predicting the presence of tumor recurrence (98% sensitivity; 84% specificity), clearly outperforming the singular CA 19-9 analysis. Moreover, time series data obtained by analyzing successively collected samples from 5 patients during extended follow-up suggested that molecular diagnosis has the potential to detect recurrence earlier than routine clinical procedures. TaqMan array card measurements were found to be biologically valid and technically reproducible. The BioPac multianalyte marker panel is capable of sensitive and accurate detection of recurrence in patients resected for PDAC using a simple blood test. This could allow a closer follow-up using shorter time intervals than currently used for imaging, thus potentially prompting an earlier work-up with additional modalities to allow for earlier therapeutic intervention. This study provides a promising approach for improved postoperative monitoring of resected PDAC patients, which is an urgent and unmet clinical need.

Infectious etiology of intussusception in Indian children less than 2 years old: a matched case-control analysis

BackgroundEnteric infections are hypothesized to be associated with intussusception in children. A small increase in intussusception following rotavirus vaccination has been seen in some settings. We conducted post-marketing surveillance for intussusception following rotavirus vaccine, Rotavac introduction in India and evaluated association of intussusception with enteric pathogens.MethodsIn a case-control study nested within a large sentinel hospital-based surveillance program in India, stool samples from 272 children aged less than 2 years admitted for intussusception and 272 age-, gender- and location-matched controls were evaluated with Taqman array card based molecular assays to detect enteric viruses, bacterial enteropathogens and parasites. Matched case-control analysis with conditional logistic regression evaluated association of enteropathogens with intussusception. Population attributable fractions (PAF) were calculated for enteropathogens significantly associated with intussusception.ResultsThe most prevalent enteropathogens in cases and controls were enteroaggregative Escherichia coli, adenovirus 40/41, adenovirus C serotypes and enteroviruses. Children with intussusception were more likely to harbor adenovirus C serotypes (adjusted odds-ratio (aOR) = 1.74; 95% confidence interval (CI) 1.06–2.87) and enteroviruses (aOR = 1.77; 95% CI 1.05–2.97) than controls. Rotavirus was not associated with increased intussusception risk. Adenovirus C (PAF = 16.9%; 95% CI 4.7% − 27.6%) and enteroviruses (PAF = 14.7%; 95% CI 4.2% − 24.1%) had the highest population attributable fraction for intussusception.ConclusionAdenovirus C serotypes and enteroviruses were significantly associated with intussusception in Indian children. Rotavirus was not associated with risk of intussusception.

Multiplex PCR detection of enteric pathogens in a community-based birth cohort in Ecuador: comparison of xTAG-GPP and TaqMan array card assays.

We compared the performance of two multiplex platforms, Luminex xTAG Gastrointestinal Pathogen PanelⓇ and TaqMan Array Card, against a panel of 14 enteric pathogen targets in a community-based birth cohort in Ecuador. We found high levels of agreement and similar prevalence estimates across most pathogens.

Spatial-Temporal Patterns in the Enteric Pathogen Contamination of Soil in the Public Environments of Low- and Middle-Income Neighborhoods in Nairobi, Kenya.

Public spaces in countries with limited societal development can be contaminated with feces containing pathogenic microbes from animals and people. Data on contamination levels, spatial distribution, and the diversity of enteric pathogens in the public settings of low- and middle-income neighborhoods are crucial for devising strategies that minimize the enteric infection burden. The objective of this study was to compare spatial-temporal differences in the detection rate and diversity of enteric pathogens in the public spaces of low- and middle-income neighborhoods of Nairobi, Kenya. TaqMan array card (TAC) molecular assays were employed to analyze soil samples for 19 enteropathogens, along with a selective bacterial culture for pathogenic Enterobacteriaceae. An observational assessment was conducted during every site visit to document the hygienic infrastructure and sanitation conditions at the sites. We detected at least one pathogen in 79% (127/160) and ≥2 pathogens in 67.5% (108/160) of the soil samples tested. The four most frequently detected pathogens were EAEC (67.5%), ETEC (59%), EPEC (57.5%), and STEC (31%). The detection rate (91% vs. 66%) and mean number of enteric pathogens (5 vs. 4.7) were higher in low-income Kibera than in middle-income Jericho. The more extensive spatial distribution of pathogens in Kibera resulted in increases in the detection of different enteric pathogens from within-site (area < 50 m2) and across-site (across-neighborhood) movements compared to Jericho. The pathogen detection rates fluctuated seasonally in Jericho but remained at sustained high levels in Kibera. While better neighborhood conditions were linked with lower pathogen detection rates, pathogenic E. coli remained prevalent in the public environment across both neighborhoods. Future studies should focus on identifying how the sources of pathogen contamination are modified by improved environmental sanitation and hygiene and the role of these contaminated public environments in enteric infections in children.

Automated post-run analysis of arrayed quantitative PCR amplification curves using machine learning

Background The TaqMan Array Card (TAC) is an arrayed, high-throughput qPCR platform that can simultaneously detect multiple targets in a single reaction. However, the manual post-run analysis of TAC data is time consuming and subject to interpretation. We sought to automate the post-run analysis of TAC data using machine learning models. Methods We used 165,214 qPCR amplification curves from two studies to train and test two eXtreme Gradient Boosting (XGBoost) models. Previous manual analyses of the amplification curves by experts in qPCR analysis were used as the gold standard. First, a classification model predicted whether amplification occurred or not, and if so, a second model predicted the cycle threshold (Ct) value. We used 5-fold cross-validation to tune the models and assessed performance using accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and mean absolute error (MAE). For external validation, we used 1,472 reactions previously analyzed by 17 laboratory scientists as part of an external quality assessment for a multisite study. Results In internal validation, the classification model achieved an accuracy of 0.996, sensitivity of 0.997, specificity of 0.993, PPV of 0.998, and NPV of 0.991. The Ct prediction model achieved a MAE of 0.590. In external validation, the automated analysis achieved an accuracy of 0.997 and a MAE of 0.611, and the automated analysis was more accurate than manual analyses by 14 of the 17 laboratory scientists. Conclusions We automated the post-run analysis of highly-arrayed qPCR data using machine learning models with high accuracy in comparison to a manual gold standard. This approach has the potential to save time and improve reproducibility in laboratories using the TAC platform and other high-throughput qPCR approaches.

Harnessing non-standard nucleic acids for highly sensitive icosaplex (20-plex) detection of microbial threats.

Environmental surveillance and clinical diagnostics heavily rely on the polymerase chain reaction (PCR) for target detection. A growing list of microbial threats warrants new PCR-based detection methods that are highly sensitive, specific, and multiplexable. Here, we introduce a PCR-based icosaplex (20-plex) assay for detecting 18 enteropathogen and two antimicrobial resistance genes. This multiplexed PCR assay leverages the self-avoiding molecular recognition system (SAMRS) to avoid primer dimer formation, the artificially expanded genetic information system (AEGIS) for amplification specificity, and next-generation sequencing for amplicon identification. We benchmarked this assay using a low-cost, portable sequencing platform (Oxford Nanopore) on wastewater, soil, and human stool samples. Using parallelized multi-target TaqMan Array Cards (TAC) to benchmark performance of the 20-plex assay, there was 74% agreement on positive calls and 97% agreement on negative calls. Additionally, we show how sequencing information from the 20-plex can be used to further classify allelic variants of genes and distinguish sub-species. The strategy presented offers sensitive, affordable, and robust multiplex detection that can be used to support efforts in wastewater-based epidemiology, environmental monitoring, and human/animal diagnostics.

Enteric pathogens relationship with small bowel histologic features of environmental enteric dysfunction in a multicountry cohort study

BackgroundEnvironmental Enteric Dysfunction (EED) is an acquired disorder of asymptomatic altered gut function, the etiology of which is unknown. EED is postulated to be a major contributor to growth faltering in early childhood in regions where early-life enteropathogenic carriage is prevalent. Few studies have examined the critical organ (the upper small bowel) with enteropathogens in the evolution of small bowel disease. ObjectivesThe objective of this study was to determine if fecal enteropathogenic detection predicts subsequent EED histology. MethodsFecal samples were obtained from undernourished children aged <2 y without diarrhea enrolled in 3 cohort studies, who failed nutritional intervention and subsequently underwent endoscopy. Duodenal biopsies from 245 (Bangladesh n = 120, Pakistan n = 57, and Zambia n = 68) children were scored using a semiquantitative histologic grading protocol. Thirteen enteropathogens were sought in common across the 3 centers using TaqMan array cards (TAC) (Bangladesh and Pakistan) and the Luminex platform (Zambia). An additional 18 pathogens and 32 virulence loci were sought by TAC and included in sensitivity analyses restricted to TAC data. ResultsMultivariable linear regressions adjusting for study center, age at stool collection, and stool-to-biopsy interval demonstrated the following: 1) an association of norovirus and Shigella detection with subsequent enterocyte injury [β 0.2 (95% CI: 0.1, 0.3); P = 0.002 and β 0.2 (95% CI: 0.0, 0.3); P = 0.008, respectively], 2) association of Campylobacter with intraepithelial lymphocytes [β 0.2 (95% CI: 0.0, 0.4); P = 0.046], and 3) association of Campylobacter and enterotoxigenic Escherichia coli with a summative EED histopathology index score [β 4.2 (95% CI: 0.8, 7.7); P = 0.017 and β 3.9 (95% CI: 0.5, 7.3); P = 0.027, respectively]. All but 2 of these associations (Shigella-enterocyte injury and Campylobacter-index score) were also demonstrated in TAC-only sensitivity analyses, which identified additional associations between other pathogens, pathogen burden, or virulence loci primarily with the same histologic parameters. ConclusionsThe detection of some enteropathogens in asymptomatic infections is associated with subsequent EED histopathology. These novel findings offer a basis for future EED etiology and pathogenesis studies.

Etiology of diarrheal hospitalizations following rotavirus vaccine implementation and association of enteric pathogens with malnutrition among under-five children in India

Malnourished children are at higher risk of mortality and morbidity following diarrheal illness and certain enteropathogens have been associated with malnutrition in children. Very few studies have comprehensively looked at the etiology of diarrhea in malnourished children and most have used conventional diagnostic methods with suboptimal sensitivity. We used a highly sensitive molecular approach against a broad range of pathogens causing diarrhea and examined their association with malnutrition. In addition, we looked at the pathogen diversity of pediatric diarrhea, three years after the nationwide rotavirus vaccine introduction to understand the evolving landscape of pathogens, which is crucial for planning strategies to further reduce the diarrhea burden. Clinical details and diarrheal stool samples were collected from hospitalized children aged < 5 years from three sentinel sites in India for a period of one year. The samples were tested by qPCR for 16 established causes of diarrhea using TaqMan Array Cards. A total of 772 children were enrolled, from whom 482 (62.4%) stool specimens were tested. No specific pathogen was associated with diarrhea among children with acute or chronic malnutrition compared to those with better nutritional status. Overall, adenovirus was the leading pathogen (attributable fraction (AF) 16.9%; 95% CI 14.1 to 19.2) followed by rotavirus (AF 12.6%; 95% CI 11.8 to 13.1) and Shigella (AF 10.9%; 95% CI 8.4 to 16.4). The majority of diarrhea requiring hospitalization in children aged < 2 years could be attributed to viruses, while Shigella was the most common pathogen among children aged > 2 years. These data on the prevalence and epidemiology of enteropathogens identified potential pathogens for public health interventions.

Shigella Detection and Molecular Serotyping With a Customized TaqMan Array Card in the Enterics for Global Health (EFGH): Shigella Surveillance Study.

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. 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. 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.

Simultaneous detection and quantification of multiple pathogen targets in wastewater

Wastewater-based epidemiology has emerged as a critical tool for public health surveillance, building on decades of environmental surveillance work for pathogens such as poliovirus. Work to date has been limited to monitoring a single pathogen or small numbers of pathogens in targeted studies; however, few studies consider simultaneous quantitative analysis of a wide variety of pathogens, which could greatly increase the utility of wastewater surveillance. We developed a novel quantitative multi-pathogen surveillance approach (35 pathogen targets including bacteria, viruses, protozoa, and helminths) using TaqMan Array Cards (TAC) and applied the method on concentrated wastewater samples collected at four wastewater treatment plants in Atlanta, GA from February to October of 2020. From sewersheds serving approximately 2 million people, we detected a wide range of targets including many we expected to find in wastewater (e.g., enterotoxigenic E. coli and Giardia in 97% of 29 samples at stable concentrations) as well as unexpected targets including Strongyloides stercoralis (a human threadworm rarely observed in the USA). Other notable detections included SARS-CoV-2, but also several pathogen targets that are not commonly included in wastewater surveillance like Acanthamoeba spp., Balantidium coli, Entamoeba histolytica, astrovirus, norovirus, and sapovirus. Our data suggest broad utility in expanding the scope of enteric pathogen surveillance in wastewaters, with potential for application in a variety of settings where pathogen quantification in fecal waste streams can inform public health surveillance and selection of control measures to limit infections.

Acute febrile illness in Kenya: Clinical characteristics and pathogens detected among patients hospitalized with fever, 2017-2019.

Acute febrile illness (AFI) is a common reason for healthcare seeking and hospitalization in Sub-Saharan Africa and is often presumed to be malaria. However, a broad range of pathogens cause fever, and more comprehensive data on AFI etiology can improve clinical management, prevent unnecessary prescriptions, and guide public health interventions. We conducted surveillance for AFI (temperature ≥38.0°C <14 days duration) among hospitalized patients of all ages at four sites in Kenya (Nairobi, Mombasa, Kakamega, and Kakuma). For cases of undifferentiated fever (UF), defined as AFI without diarrhea (≥3 loose stools in 24 hours) or lower respiratory tract symptoms (cough/difficulty breathing plus oxygen saturation <90% or [in children <5 years] chest indrawing), we tested venous blood with real-time PCR-based TaqMan array cards (TAC) for 17 viral, 8 bacterial, and 3 protozoal fever-causing pathogens. From June 2017 to March 2019, we enrolled 3,232 AFI cases; 2,529 (78.2%) were aged <5 years. Among 3,021 with outcome data, 131 (4.3%) cases died while in hospital, including 106/2,369 (4.5%) among those <5 years. Among 1,735 (53.7%) UF cases, blood was collected from 1,340 (77.2%) of which 1,314 (98.1%) were tested by TAC; 715 (54.4%) had no pathogens detected, including 147/196 (75.0%) of those aged <12 months. The most common pathogen detected was Plasmodium, as a single pathogen in 471 (35.8%) cases and in combination with other pathogens in 38 (2.9%). HIV was detected in 51 (3.8%) UF cases tested by TAC and was most common in adults (25/236 [10.6%] ages 18-49, 4/40 [10.0%] ages ≥50 years). Chikungunya virus was found in 30 (2.3%) UF cases, detected only in the Mombasa site. Malaria prevention and control efforts are critical for reducing the burden of AFI, and improved diagnostic testing is needed to provide better insight into non-malarial causes of fever. The high case fatality of AFI underscores the need to optimize diagnosis and appropriate management of AFI to the local epidemiology.

Cross-Sectional Study of Soil-Transmitted Helminthiases in Black Belt Region of Alabama, USA.

We conducted a cross-sectional study to determine the prevalence of soil-transmitted helminthiases (STH) in areas of rural Alabama, USA, that have sanitation deficits. We enrolled 777 children; 704 submitted stool specimens and 227 a dried blood spot sample. We microscopically examined stool specimens from all 704 children by using Mini-FLOTAC for helminth eggs. We tested a subset by using molecular techniques: real-time PCR analysis for 5 STH species, TaqMan Array Cards for enteric helminths, and digital PCR for Necator americanus hookworm. We analyzed dried blood spots for Strongyloides stercoralis and Toxocara spp. roundworms by using serologic testing. Despite 12% of our cohort reporting living in homes that directly discharge untreated domestic wastewater, stool testing for STH was negative; however, 5% of dried blood spots were positive for Toxocara spp. roundworms. Survey data suggests substantial numbers of children in this region may be exposed to raw sewage, which is itself a major public health concern.

A Rapid Test to Evaluate the Tumor Differentiation State of Acute Myeloid Leukemias

Introduction: The combination of the hypomethylating agent Azacitidine with Venetoclax, a BCL2 inhibitor (Aza+Ven), is the frontline therapy for patients with acute myeloid leukemia (AML) who are elderly or unfit for intensive chemotherapy. However, identifying responsiveness to Aza+Ven a priori remains a clinical challenge.Aza+Ven effectively targets the primitive leukemia stem cell population (Pollyea, 2018), whereas resistance is observed in differentiated tumors (Pei, 2020). Further insights into the hierarchical organization of hematopoiesis have led to a definition of malignant AML cell types that follow the progression from hematopoietic stem cell to myeloid differentiated cells based on gene expression signatures, and these have been used to classify AML tumors (van Galen, 2019). Classification schemes using gene expression to capture variations in leukemic composition represent key biomarkers of response to targeted agents (Zeng, 2022; Bottomly, 2022). However, the prompt availability of nuanced cell state signatures to guide clinical decision making is limited by the laborious nature of performing and analyzing RNA-sequencing studies. Rapid AML stratification based on these classifications permits the possibility of identifying patients most likely to benefit from a drug or combination. Methods: To classify cell states based on transcriptomic signatures, we developed two assay formats, involving custom Nanostring and TaqMan Array card panels, for evaluation of tumor cell states for AML patients. Both formats contained gene sets representative of the six hematopoietic lineage states (van Galen, 2019) and both provide outputs that are compatible with the timeline for clinical decision-making. Assays were run according to the manufacturers' specifications, and enrichment of each of the six gene signatures was assessed using the Singscore stable method (Foroutan, 2018). Banked AML patient samples with matched RNA-seq and ex vivo Aza+Ven drug sensitivity data were used to validate the assay formats. Data obtained from the rapid assays were validated against cell states determined by deconvolution of bulk RNA sequence and compared with respect to clinical immunophenotype data where available. Results : Both the Nanostring and quantitative PCR-based assay formats detected gene expression representative of the appropriate cell state as previously determined by bulk RNA sequencing (Fig. 1A). Correlation of Aza+Ven ex vivo sensitivity with tumor cell state signatures revealed patterns where primitive but not differentiated cell states associated with sensitivity. In contrast, RNA isolated from healthy donor samples showed expression of all six cell state signatures. Across a cohort of 50 primary AML patient specimens, enrichment scores for each gene set correlated well with those derived for the same patients using deconvolution of bulk RNA-seq (Pearson r values: 0.785 to 0.944). Cell state characterization by rapid gene expression assays also aligned well with clinical immunophenotype, a routinely available diagnostic characterization of tumor blasts. Surface expression of primitive (CD117) and mature (CD11b) markers associated with Aza+Ven ex vivo sensitivity and resistance overall, respectively (p=0.03 &amp; 0.04); however, ex vivo sensitivity could be significantly further stratified among samples expressing these markers when considering the gene expression-based enrichment scores for progenitor- and monocyte-like gene signatures (low vs high p-values: 0.02-0.05) (Fig. 1B). Analysis of matched samples from individual patients before and after treatment also showed cell state signature changes that reflected their temporal disease progression and correlated with differences in ex vivo drug sensitivity and clinical immunophenotype. Conclusion:Incorporation of cell state into prospective evaluations of AML patients provides an early indication of responsiveness to Aza+Ven. With rapid turnaround, assays such as these may augment treatment stratification and improve patient outcomes. These assays offer additional versatility to detect changes in AML cells after forced differentiation or acquired drug resistance.