Enteric dysfunction and enteropathogens among hospitalized south Asian and sub-Saharan African children

Abu Sadat Mohammad Sayeem Bin Shahid; Donna M Denno; Kevin Kariuki; Doreen Rwigi; Amran Gazi; Lubaba Shahrin; Wilson Gumbi; James M Njunge; Mohammod J Chisti; Tahmeed Ahmed; Eric R Houpt; Jie Liu; Mami Taniuchi; Benson O Singa; Robert H J Bandsma; Wieger Voskuijl; Ali F Saleem; Christina L Lancioni; Ezekiel Mupere; Abdoulaye H Diallo; Judd L Walson; James A Berkley; Kirkby D Tickell

doi:10.1371/journal.pgph.0006873

. 2026 Jul 24;6(7):e0006873. doi: 10.1371/journal.pgph.0006873

Enteric dysfunction and enteropathogens among hospitalized south Asian and sub-Saharan African children

Abu Sadat Mohammad Sayeem Bin Shahid ^1,², Donna M Denno ^1,^3,⁴, Kevin Kariuki ^1,⁵, Doreen Rwigi ^1,⁵, Amran Gazi ^1,², Lubaba Shahrin ^1,², Wilson Gumbi ^1,⁶, James M Njunge ^1,⁶, Mohammod J Chisti ^1,², Tahmeed Ahmed ^1,², Eric R Houpt ⁷, Jie Liu ⁸, Mami Taniuchi ^7,⁹, Benson O Singa ^1,¹⁰, Robert H J Bandsma ^1,^11,¹², Wieger Voskuijl ^1,¹³, Ali F Saleem ^1,¹⁴, Christina L Lancioni ^1,¹⁵, Ezekiel Mupere ^1,¹⁶, Abdoulaye H Diallo ^1,¹⁷, Judd L Walson ^1,¹⁸, James A Berkley ^1,^6,¹⁹, Kirkby D Tickell ^1,^4,^*

Editor: Ayse Ercumen²⁰

¹The Childhood Acute Illness and Nutrition Network, Nairobi, Kenya

²Nutrition Research Division, International Centre for Diarrhoeal Disease Research Bangladesh (icddr, b), Dhaka, Bangladesh

³Department of Pediatrics, University of Washington, Seattle, Washington, United States of America

⁴Department of Global Health, University of Washington, Seattle, Washington, United States of America

⁵Centre for Microbiology Research, Kenya Medical Research Institute (KEMRI), Nairobi, Kenya

⁶Kemri-Welcome Trust Research Program, Kilifi, Kenya

⁷Division of Infectious Diseases and International Health, University of Virginia, Charlottesville, Virgina, United States of America

⁸School of Public Health, Qingdao University, Qingdao, China

⁹Departments of Medicine, Biomedical Engineering and Civil and Environmental Engineering, University of Virginia, Charlottesville, Virginia, United States of America

¹⁰Centre for Clinical Research, Kenya Medical Research Institute (KEMRI), Nairobi, Kenya

¹¹Center for Global Child Health, Hospital for Sick Children, Toronto, Canada

¹²The Translational Medicine Program, Hospital for Sick Children, Toronto, Canada

¹³Amsterdam Institute for Global Child Health, Emma Children’s Hospital, Amsterdam, The Netherlands

¹⁴Paediatrics and Child Health, Aga Khan University, Karachi, Pakistan

¹⁵Department of Pediatrics, Oregon Health and Science University, Portland, Oregon, United States of America

¹⁶Department of Paediatrics and Child Health School of Medicine College of Health Sciences, Makerere University, Kampala, Uganda

¹⁷Department of Public Health, University Joseph Ki-Zerbo, Ouagadougou, Burkina Faso

¹⁸Departments of International Health, Medicine and Pediatrics, Johns Hopkins University, Baltimore, Maryland, United States of America

¹⁹Center for Tropical Medicine and Global Health, University of Oxford, Oxford, United Kingdom

²⁰North Carolina State University, UNITED STATES OF AMERICA

The authors have declared that no competing interests exist.

^✉

* E-mail: kirkbt@uw.edu

Roles

Abu Sadat Mohammad Sayeem Bin Shahid: Conceptualization, Formal analysis, Investigation, Methodology, Writing – original draft, Writing – review & editing

Donna M Denno: Conceptualization, Writing – review & editing

Kevin Kariuki: Conceptualization, Data curation, Formal analysis, Writing – review & editing

Doreen Rwigi: Formal analysis, Methodology, Writing – review & editing

Amran Gazi: Formal analysis, Investigation, Methodology, Writing – review & editing

Lubaba Shahrin: Investigation, Methodology, Writing – review & editing

Wilson Gumbi: Investigation, Methodology, Writing – review & editing

James M Njunge: Conceptualization, Data curation, Funding acquisition, Investigation, Methodology, Project administration, Writing – review & editing

Mohammod J Chisti: Conceptualization, Funding acquisition, Project administration, Writing – review & editing

Tahmeed Ahmed: Conceptualization, Funding acquisition, Methodology, Writing – review & editing

Eric R Houpt: Conceptualization, Investigation, Methodology, Writing – review & editing

Jie Liu: Investigation, Methodology, Writing – review & editing

Mami Taniuchi: Investigation, Methodology, Writing – review & editing

Benson O Singa: Investigation, Project administration, Supervision, Writing – review & editing

Robert H J Bandsma: Conceptualization, Funding acquisition, Methodology, Writing – review & editing

Wieger Voskuijl: Conceptualization, Writing – review & editing

Ali F Saleem: Conceptualization, Funding acquisition, Writing – review & editing

Christina L Lancioni: Conceptualization, Investigation, Writing – review & editing

Ezekiel Mupere: Conceptualization, Writing – review & editing

Abdoulaye H Diallo: Conceptualization, Writing – review & editing

Judd L Walson: Conceptualization, Funding acquisition, Investigation, Methodology, Writing – review & editing

James A Berkley: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Writing – review & editing

Kirkby D Tickell: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing

Ayse Ercumen: Editor

PMCID: PMC13399345 PMID: 42497154

Abstract

Enteropathogens and enteric dysfunction (ED) among acutely ill children in low-and-middle income countries (LMICs) may contribute to poor post-discharge outcomes. Enteropathogen prevalence and fecal ED biomarkers (myeloperoxidase, calprotectin, α-1-antitrypsin) from children aged 2–23 months hospitalized at nine LMIC facilities (n = 811) were compared to community children (n = 248). Host and pathogen correlates of ED biomarkers were identified through crude and adjusted linear mixed effect models, and Cox-proportional hazard models assessed ED biomarker associations with mortality in the 30-days following admission and 180-days following discharge. Invasive enteropathogens were more prevalent at admission (69%) than discharge (60%, p < 0.001) or among community children (61%, p = 0.004). Among the biomarkers, myeloperoxidase was higher at admission (2290 ng/ml, interquartile range [IQR]: 868, 6052, p = 0.014), and lower at discharge (1380 ng/ml, IQR: 611, 3193, p < 0.001) compared to community children (2268 ng/ml, IQR: 1051, 5421), while calprotectin was similar at admission (215 ug/ml, IQR: 77, 746, p = 0.351), but lower at discharge (170 ug/ml, IQR: 68, 369, p = 0.007) when compared the community children (252 ug/ml, IQR: 124, 691). α-1-antitrypsin concentrations were lower at admission (121 mg/l, IQR: 49, 303, p = 0.049) compared to the community (201 mg/ml, IQR: 100, 412), but more comparable at discharge (144 mg/ml, IQR: 69, 275, p = 0.380). Admission myeloperoxidase and calprotectin concentrations were associated with invasive enteropathogens detection (respectively, p = 0.003 and p = 0.002) and lower MUAC (respectively, p = 0.002 and p = 0.012), while admission α-1-antitrypsin was associated with breastfeeding, diarrhea, malaria and pneumonia (all p < 0.05). The only ED biomarker associated with mortality after confounder adjustment was fecal calprotectin (hazard ratio: 1.36, 95% CI:1.07,1.72, p = 0.011) at discharge. Enteric inflammation biomarker concentrations and enteropathogen prevalence were high at hospital admission, but by discharge were lower than among community peers. Interventions to prevent re-colonization with enteropathogens and increased enteric inflammation may improve child health in the post discharge period.

Introduction

Pediatric mortality following discharge from hospitals in low- and middle-income countries (LMICs) is unacceptably high, with estimates suggesting that nearly half of deaths among hospitalized children occurring post-discharge [1–3]. Many of these post-discharge deaths occur within the first 45 days following hospitalization, and are attributable to broad range of acute and chronic conditions [3]. However, the risk of mortality remains elevated up to six or even 12 months after hospitalization suggesting that underlying vulnerabilities predispose these children to poor outcomes.

Enteric dysfunction (ED) due to various etiologies may contribute to poor outcomes after hospital discharge. Environmental enteric dysfunction (EED) is a prevalent, largely asymptomatic condition in LMICs characterized by small bowel injury, inflammation, increased gut permeability, translocation of microbes or microbial products, and systemic inflammation. EED is highly consequential to child growth and neurodevelopment, with impacts on health across the life course [4–6]. Frequent exposure to enteric pathogens has been associated with EED among children in the community [7–11]. Children admitted to hospital have a high prevalence of other conditions which can also cause ED, including malnutrition, acute gastrointestinal infections, and chronic infections such as HIV [5,12,13]. Furthermore, exposure to treatments, such as antibiotics and therapeutic foods, can disrupt the gut microbiome and intestinal homeostasis. Data from Zambia and Zimbabwe associated ED and systemic inflammation biomarkers with increased risk of mortality and rehospitalization in the post-discharge period among children with severe acute malnutrition [14]. Data from the cohort used for this analysis found detection lipopolysaccharide, a marker of translocation of gram negative bacteria or bacterial antigens, to be associated with mortality among hospitalized children [15]. A deeper understanding of ED, broadly defined and regardless of specific etiology, during acute illness may lead to interventions that prevent post-discharge morbidity and mortality.

Fecal myeloperoxidase and calprotectin are commonly used enteric inflammation biomarkers, while fecal α-1-antitrypsin is used to measure intestinal permeability [7,16]. These biomarkers have been associated with enteropathogens among community-based pediatric cohorts, particularly those classified as enteroinvasive [7]. However, few studies have examined ED biomarkers among acutely unwell children in LMICs. This analysis aimed to understand a) trends in ED biomarkers and enteropathogens in acutely unwell children across a nutritional spectrum in LMICs, b) enteropathogen, clinical, and sociodemographic correlates of ED, and c) ED biomarkers’ association with mortality in the 30-days following admission and 180-days following discharge.

Methods

The Childhood Acute Illness and Nutrition (CHAIN) cohort characterized biomedical and social pathways to mortality among acutely ill young children [3]. Between November 2016 and January 2019, the CHAIN cohort enrolled 3,101 acutely ill children aged 2–23 months at nine hospitals: Dhaka and Matlab Hospitals (Bangladesh), Banfora Referral Hospital (Burkina Faso), Kilifi County, Mbagathi County and Migori County Hospitals (Kenya), Queen Elizabeth Hospital (Malawi), Karachi Civil Hospital (Pakistan), and Mulago National Referral Hospital (Uganda). These hospitals serve a range of urban and rural communities with varying healthcare access and disease endemicity, including HIV and malaria.

Study design, setting and population

Enrollment was stratified by mid-upper-arm circumference (MUAC) to oversample undernourished children in a 2-1-2 ratio: no wasting (MUAC ≥12.5 cm [age ≥ 6 months] or MUAC≥12.0 cm [age < 6 months]), moderate wasting (MUAC 11.5–12.5 cm [age ≥ 6 months] or MUAC 11.0–12.0 cm [age < 6 months]), and severe wasting or kwashiorkor (MUAC <11.5 cm [age ≥ 6 months] or MUAC <11.0 cm [age < 6 months], or bilateral pedal edema) at hospital admission. To provide normative social and biological data for local populations, similarly aged community participants were recruited from households proximate to the index hospitalized child’s home using pseudo-random selection (3^rd house north of index home), if they had no hospital admission in the 14 days prior to contact with the study team and did not currently have an illness requiring medical attention.

Definitions, procedures, data, and sample collection and processing were harmonized across sites through training, standard operating procedures and case report forms (available at https://chainnetwork.org/resources/). Stool samples were collected at admission and discharge for hospitalized children and at a single timepoint for community participants.

The CHAIN nested case cohort (NCC) analyzed CHAIN samples to gain further insights into mortality, and was powered to detect a Hazard Ratio of 1.5 with 80% power in both the 30-day and 180-day mortality analyses.[17] Therefore, the CHAIN NCC randomly selected 24% of children in the CHAIN cohort, all remaining deaths, and 30 community children from each site (to provide reference values for biomarkers without well-established clinical cutoffs) to undergo a panel of analyses including fecal ED biomarker quantification by ELISA and TaqMan probe-based real-time PCR Arrays for detection of enteropathogens [17].

Ethics statement

Formal written informed consent was obtained from parents or guardians of the children. Ethical approval was granted by the Oxford Tropical Research Ethics Committee, UK; the Kenya Medical Research Institute, Kenya; Makerere University School of Biomedical Sciences Research Ethics Committee and the Uganda National Council for Science and Technology, Uganda; Aga Khan University, Pakistan; International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b); The University of Malawi; The Centre Muraz, Burkina Faso; and the Hospital for Sick Children, Canada.

Laboratory analysis and data preprocessing

Biological samples were stored at -80°C and shipped on dry ice. Stool myeloperoxidase, calprotectin, and α-1-antitrypsin were quantified by ELISA assay and absolute concentrations were calculated for 15mg of stool using manufacturer’s standard dose response curves at KEMRI’s Nairobi laboratory. For myeloperoxidase (Immunodiagnostik AG, Bensheim, Germany, intra-assay repeatability coefficient of variation (CV) 5%, inter-assay reproducibility CV 9–12%), [18] samples were diluted 1:10 and run on a final dilution of 1:500. α-1-antitrypsin (Immunodiagnostik AG, Bensheim, Germany, intra-assay repeatability CV 5–9%, inter-assay reproducibility CV 10–12%) [19] at a final dilution of 1:25000, while calprotectin (Immunodiagnostik AG, Bensheim, Germany, intra-assay repeatability CV 3–5%, inter-assay reproducibility CV 9–12%) [20] had a final dilution of 1:2500. Further dilutions were run if biomarker concentrations exceeded the standard curve range. Up to five samples per plate were duplicated to assess the coefficient of variance. All plates were read on ELx 808 ELISA plate reader (BioTek, USA) at wavelength of 450 nanometers and background absorbance was subtracted. Absolute quantification was performed against standard curves created using the manufacturer’s standards and compared against manufacturer provided controls.

TaqMan Array Cards (TAC) were run in Kenya and Bangladesh [17]. Total nucleic acid was extracted from rectal swabs using the QIAamp Fast DNA Stool Mini kit (Qiagen, Valencia, CA). 46 μl nucleic acid extract from rectal swab was mixed with AgPath One Step RT-PCR reagents (Thermo Fisher, Carlsbad, CA) in a 100 μl reaction, then loaded into the TAC card and run in a ViiA 7 or QuantStudio 7 Flex Real Time PCR system (Thermo Fisher, CA). TAC cards were customized to detect 29 pathogens commonly associated with diarrhea [S1 Appendix]. Cycle threshold (Ct) value of 30 was set as a threshold for analysis, whereby a Ct ≥ 30 was considered negative [21].

Statistical analysis

Sociodemographic and clinical characteristics at hospital admission and discharge, and among the community participants, were presented using descriptive statistics. Enteropathogen prevalence adjusted for selection into the NCC at each timepoint was evaluated using chi-Square tests comparing admission to discharge, and each timepoint to the community. ED biomarker concentrations adjusted for selection into the NCC were described at admission, discharge, and for the community children using median (interquartile range [IQR]).Crude linear regression compared admission and discharge ED biomarker values to those from community children, rather than directly comparing the two hospitalized timepoints to avoid paired data. Sensitivity analyses stratifying hospitalized children into those with and without diarrhea reported as a presenting complaint were conducted. A final sensitivity analysis included only children with both admission and discharge samples to ensure trends between timepoints were not attributable to inpatient mortality.

Correlates of ED biomarkers

Enteropathogens were grouped into categories, mirroring the approach taken by Kosek et al.[7] Dehydrating viruses that cause only limited mucosal disruption included adenovirus, astrovirus, norovirus and rotavirus. Invasive pathogens that cause mucosal disruption included Aeromonas spp., Campylobacter spp., enteroaggregative Escherichia coli (EAEC), typical and atypical enteropathogenic E. coli (EPEC), Salmonella spp., and Shigella spp. Enterotoxigenic E. coli (ETEC) was a third group as it causes secretory diarrhea with limited mucosal disturbances. Finally, Giardia spp. and Cryptosporidium spp. were modeled separately. Univariate linear mixed effect models with random effects for site estimated the association of age, anthropometry (nutritional edema, MUAC, length-for-age Z score [LAZ]), breastfeeding (exclusive/partial/none), clinical conditions (malaria, diarrhea, pneumonia, sepsis), and enteropathogen detection (dehydrating, enteroinvasive, etc) with each biomarker concentration at admission. A priori specified confounders; age (0–5 months, 6–11 months, ≥ 12 months), sex, MUAC, and enrollment site random effects were included in all multivariate models, and any of the additional variables associated with a biomarker (p < 0.05) in univariate analyses were also included in multivariable models.

Mortality analysis

Cox proportional hazard models weighted for the CHAIN sampling strategy and the NCC design modelled mortality in the 30-days following hospital admission and the 180-days following discharge [3]. The 30-day period following admission was chosen because inpatient mortality is biased by discharge decisions. Crude 30-day models assessed associations between the ED biomarkers at admission and mortality. These models were then adjusted for admission variables a-priori identified confounder from the correlates analysis above (age, sex, MUAC, and enrollment site), in addition to other important risk factors for ED and mortality including LAZ, current breastfeeding (none, partial, exclusive), HIV status (infected/uninfected), invasive pathogen detection, caregiver reported recent diarrhea, and diagnoses of pneumonia, malaria and sepsis. Post-discharge models examined associations between discharge biomarkers concentrations and 180-day post-discharge mortality. Confounder adjusted post-discharge models included age, sex, discharge MUAC, enrollment site, discharge LAZ, current breastfeeding (none, partial, exclusive), HIV status (infected/uninfected), enteroinvasive pathogen detection at discharge, reported diarrhea at admission, and diagnoses of pneumonia, malaria and sepsis during admission. All analyses were performed in R (v3.6.1) with p < 0.05 (two-tailed) considered significant.

Results

Among 811 included hospitalized children, 709 also had discharge data available (Fig 1). The median ages in months of hospitalized (10.6, IQR: 6.6-15.8) and community (12.2, IQR: 7.4-17.5) children were similar. Hospitalized children were less commonly exclusive breastfed (Table 1). Caregivers reported recent diarrhea among 457 (56%) children at admission. Compared to the community group, fewer hospitalized children were female and they had a higher prevalence of HIV infection, stunting, wasting and antibiotic exposure in the seven days prior to admission. By discharge, 92% of hospitalized children had received antibiotics. The median duration of hospitalization was 5 days (IQR 3–8).

Table 1. Baseline characteristics of study participants.

	Admission (N = 811)		Discharge (N = 709)		Community (N = 248)
	n	%	n	%	n	%
Site
Banfora	103	12.7	90	12.7	28	11.3
Blantyre	80	9.9	67	9.4	28	11.3
Kampala	109	13.4	94	13.3	24	9.7
Migori	93	11.5	65	9.2	25	10.1
Mbagathi	86	10.6	71	10	29	11.7
Kilifi	59	7.3	52	7.3	27	10.9
Karachi	95	11.7	95	13.4	27	10.9
Dhaka	108	13.3	100	14.1	30	12.1
Matlab	78	9.6	75	10.6	30	12.1
Sex (Female)	354	43.6	303	42.7	126	50.8
Age
< 6 months	165	20.3	148	20.9	41	16.5
6-12 months	297	36.6	255	36	78	31.5
>12 months	349	43.0	306	43.2	129	52.0
Any breastfeeding	559	68.9	501	70.7	218	87.9
Exclusive breastfeeding ^a	65	8.0	56	7.9	36	14.5
Antibiotics in last 7 days	365	45.0	653	92.1	34	13.7
Stunted (LAZ < -2)	439	54.1	367	51.8	83	33.5
Severe wasting/kwashiorkor ^b	389	48.0	312	44.0	0	0.0
Moderate wasting ^b	182	22.4	167	23.6	26	10.5
Presenting Compliant
Diarrhea	457	56.4	385	54.3	–	–
Fever	594	73.2	530	74.8	–	–
Cough	401	49.4	403	56.8	–	–
≥1 IMCI Danger sign	353	43.5	280	39.5	–	–
Diagnoses
Gastroenteritis	399	49.2	340	48.0	–	–
LRTI	321	39.6	92	13	–	–
Sepsis	109	13.4	279	39.4	–	–
Malaria (by RDT)	102	12.6	87	12.3	12	4.8
HIV exposed uninfected	58	7.2	47	6.6	19	7.7
HIV infected	54	6.7	33	4.7	3	1.2
Household characteristics
Livestock ownership	275	33.9	244	34.4	109	44.0
Improve water source access	657	81.0	595	83.9	202	81.5
Improved sanitation access	614	75.7	559	78.8	178	71.8
Food insecure^c	145	17.9	98	13.8	34	13.7

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IMCI: Integrated Management of Childhood Illness, LAZ: Height-for-age Z-score, LRTI: lower respiratory tract infection; RDT: rapid diagnostic test; WHZ: Weight-for-height Z-score. ^aAmong infants under six months old, admission 59 (35.8%), discharge 53 (35.8%), community 30 (73.2%). ^bDefined as per CHAIN study: Severe wasting/kwashiorkor (nutritional oedema, MUAC <11.5 cm if ≥6 months old, or MUAC <11 cm if <6 months old, Moderate wasting (MUAC <12.5 cm if ≥6 months old, or MUAC <12 cm if <6 months old) ^cmoderate to severe food insecurity.

Pathogen prevalence

Detection of any enteropathogen was common, with prevalence of 84% at admission, 90% at discharge, and 61% among community children (Table 2). The prevalence of enteropathogens associated with dehydration at admission (29%) and discharge (27%) was comparable, but higher than among the community children (8%, p < 0.001 compared to admission). During hospitalization norovirus prevalence nearly doubled (p < 0.001), with no sites observing a decrease in norovirus detection, and seven sites having a higher prevalence at discharge than admission.

Table 2. Pathogen prevalence and ED biomarkers among included children, adjusted for sample selection into the nested case cohort.

	Admission			Discharge				Community
	n	%¹	(95% CI) ¹	n	%¹		(95% CI) ¹	n	%¹		(95% CI) ¹
Any pathogen	675	84.1	(82,87)	496	90.4		(88, 93)	151	60.9		(55, 67)
Dehydrating ¹	209	28.9	(26, 32)	178	27.0		(24, 30)	20	8.1		(5, 12)
Adenovirus	44	5.7	(4, 7)	85	3.0		(2, 4)	7	2.8		(1, 6)
Astrovirus	24	3.0	(2, 4)	47	7.0		(5, 9)	2	0.8		(0, 3)
Norovirus	53	7.1	(5, 9)	85	12.4		(10, 15)	10	4.0		(2, 7)
Rotavirus	111	15.8	(13, 18)	54	7.9		(6, 10)	1	0.4		(0, 2)
Invasive ²	576	69.4	(66, 73)	391	59.6		(56, 63)	151	60.9		(55, 67)
Aeromonas	4	0.1	(0, 1)	2	0.0		(0, 0)	3	1.2		(0, 3)
Campylobacter	211	25.7	(23, 29)	86	13		(11, 16)	49	19.8		(15, 25)
EAEC	444	52.9	(49, 56)	331	50.1		(47, 54)	99	39.9		(34, 46)
Atypical EPEC	80	9.8	(8, 12)	37	4.9		(3, 6)	22	8.9		(6, 13)
Typical EPEC	113	11.9	(10, 14)	50	6.8		(5, 9)	19	7.7		(5, 12)
Salmonella	12	1.6	(0, 2)	9	1.2		(0, 2)	1	0.4		(0, 2)
Shigella	100	11.1	(9, 13)	26	3.6		(2, 5)	18	7.3		(5, 11)
ETEC	142	17.8	(15, 20)	58	8.9		(7, 10)	27	10.9		(8, 15)
*Giardia*	56	8.0	(6, 10)	46	7.9		(6, 10)	26	10.5		(7, 15)
*Cryptosporidium*	94	10.1	(8, 12)	59	7.9		(6, 11)	13	5.2		(3, 9)
	n	median	(IQR)	n	median		(IQR)	n	median		(IQR)
Myeloperoxidase (ng/ml)	681	2290	(868, 6052)	558		1380	(611, 3193)	248		2268	(1051, 5421)
Calprotectin (ug/ml)	652	215	(77, 746)	549		170	(68, 369)	242		252	(124, 691)
α-1-antitrypsin (mg/l)	678	121	(49, 303)	555		144	(69, 275)	247		201	(100, 412)

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¹Percentages and 95% Confidence intervals have been weighted for the nested case cohort sample selection. ²Based on Kosek et al (2017), EAEC: enteroaggregative E. coli, EPEC: enteropathogenic E. coli, ETEC: enterotoxigenic E. coli, IQR: inter-quartile range

Enteroinvasive pathogens were most prevalent at admission (69%) compared to discharge from hospital (60%, p < 0.001) or the community (61%, p = 0.004). Several invasive pathogens had non-significant declines during hospitalization to levels comparable or slightly below the community including Campylobacter (26% admission, 13% discharge, 20% community), atypical EPEC (10% admission, 5% discharge, 9% community), and Shigella (11% admission, 4% discharge, 7% community).

ETEC was more prevalent at admission (18%) than discharge (9%, p < 0.001) and community groups (11%, p = 0.014). Cryptosporidium was more prevalent at admission (10%, p = 0.033), but similar at discharge (8%, p = 0.100), compared to community children (5%). Finally, Giardia was similar at admission (8%, p = 0.060) and discharge (8%, p = 0.080) compared to the community group (11%).

ED biomarkers

Median admission fecal myeloperoxidase concentrations among hospitalized children were higher than in the community (p = 0.014), but fell below community levels at discharge (p < 0.001, Fig 2). Admission calprotectin among hospitalized children was comparable with the community (p = 0.351), but fell below community levels by discharge (p = 0.007, S1 Appendix). α-1-antitrypsin concentrations among hospitalized children were lower at admission (p = 0.049), but similar at discharge (p = 0.380), as compared to the community.

Sensitivity analyses

Children with reported diarrhea had higher rotavirus, norovirus, typical EPEC and Shigella prevalence at admission, but fewer detections of Giardia than children without diarrhea. However, the trend of decreased pathogen prevalence between admission and discharge, particularly invasive enteropathogens, was similar among hospitalized children with and without reported diarrhea (S1 Appendix).

The decline in myeloperoxidase and calprotectin across the admission was consistent in hospitalized children with and without reported diarrhea. However, higher median α-1-antitrypsin concentrations during admission were isolated to children with reported diarrhea at admission. Sensitivity analyses including only children with both admission and discharge samples showed very similar trends to the main analysis (S1 Appendix).

Correlates of ED biomarkers at admission

In crude models, myeloperoxidase concentrations were positively associated with younger age, oedema, lower MUAC, lower LAZ, absence of dehydrating pathogens, enteroinvasive pathogen detection, and being hospitalized (Table 3). Multivariable models found MUAC, LAZ, age, and invasive enteropathogen detection remained associated with myeloperoxidase. Invasive pathogen detection was associated with a 0.28 SD (95% CI: 0.10, 0.46; p = 0.003) higher fecal myeloperoxidase. A one cm smaller MUAC was associated with 0.07 SD (95% CI: 0.12, 0.03; p = 0.002) higher myeloperoxidase, while a one SD decrease in LAZ had a corresponding 0.06 SD (95% CI: 0.10, 0.01; p = 0.014) higher myeloperoxidase. Children who were 6–11 months old had a 0.20 SD (95% CI: 0.38, 0.02, p = 0.026) lower myeloperoxidase than those ≥12 months old. Correlates of biomarkers among the community group are provided for comparison (S1 Appendix).

Table 3. Correlates of ED fecal biomarkers.

	Myeloperoxidase				Calprotectin				α-1-antitrypsin
	Unadjusted		Adjusted¹		Unadjusted		Adjusted¹		Unadjusted		Adjusted¹
	Coef	(95% CI)	Coef	(95% CI)	Coef	(95% CI)	Coef	(95% CI)	Coef	(95% CI)	Coef	(95% CI)
Hospital vs community	0.16	(0.02, 0.31)	0.09	(-0.10, 0.28)	0.08	(-0.07, 0.22)			-0.13	(-0.28, 0.01)
Hospitalized cohort only
Oedema	0.24	(0.01, 0.48)	0.14	(-0.10, 0.38)	0.02	(-0.24, 0.21)	--		-0.19	(-0.42, 0.03)	--
MUAC	-0.07	(-0.12, -0.02)	-0.07	(-0.12, -0.03)	-0.06	(-0.10, -0.01)	-0.06	(-0.10, -0.01)	0.04	(-0.00, 0.08)	--
Height-for-age	-0.07	(-0.11, -0.02)	-0.06	(-0.10, -0.01)	-0.06	(-0.10, -0.01)	-0.05	(-0.09, -0.01)	0.03	(-0.01, 0.07)	--
Breastfeeding
Partial vs exclusive	0.04	(-0.32, 0.25)	--		-0.13	(-0.40, 0.13)	--		0.13	(-0.13, 0.40)	--
None vs exclusive	-0.01	(-0.20, 0.18)	--		-0.09	(-0.27, 0.09)	--		-0.22	(-0.40, -0.04)	-0.13	(-0.15, -0.40)
Months of age
<6 vs>12	-0.11	(-0.32, 0.11)	--		-0.09	(-0.30, 0.12)	--		-0.11	(-0.31, 0.10)	--
6-12 vs > 12	-0.23	(-0.42, -0.01)	0.20 (-0.38, -0.02)		-0.11	(-0.28, 0.07)	--		-0.29	(-0.46, -0.11)	--
Reported diarrhea	-0.09	(-0.27, 0.08)	--		0.03	(-0.14, 0.20)	--		-0.57	(-0.73, -0.41)	-0.43	(-0.59, -0.27)
Diagnosis sepsis	0.16	(-0.10, 0.41)	--		0.21	(-0.04, 0.45)	--		-0.10	(-0.35, 0.14)	--
Diagnosis pneumonia	0.04	(-0.13, 0.41)	--		0.09	(-0.08, 0.26)	--		0.31	(0.15, 0.49)	0.16	(-0.08, 0.41)
Diagnosis malaria²	-0.24	(-0.52, 0.04)	--		-0.04	(-0.31, 0.22)	--		0.23	(0.01, 0.48)	0.16	(-0.00, 0.31)
Dehydrating pathogen	-0.25	(-0.44, -0.06)	-0.16	(-0.35, 0.03)	-0.18	(-0.37, 0.00)	--		-0.28	(-0.46, -0.09)	-0.15	(-0.32, 0.03)
Invasive pathogen	0.32	(0.14, 0.49)	0.28	(0.10, 0.46)	0.32	(0.15, 0.50)	0.29	(0.11, 0.47)	0.04	(-0.13, 0.22)	--

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¹Models were adjusted for invasive pathogens, dehydrating pathogens, reported diarrhea, age group, sex and mid-upper arm circumference with site as a random effect. Height-for-age z-score models did not include MUAC due to co-linearity. ²Based on positive malaria rapid diagnostic. MUAC: mid upper arm circumference.

Similarly, lower MUAC, lower LAZ and invasive pathogen detection were associated with calprotectin in crude models and remained associated in multivariable models: invasive pathogen detection (0.29 SD; 95% CI: 0.11, 0.47; p = 0.002), lower MUAC (0.06 SD, 95% CI: 0.10, 0.01, p = 0.012), and lower LAZ (0.05 SD, 95% CI: 0.09, 0.01, p = 0.023). Among the invasive enteropathogens, both Shigella spp. and EAEC were associated with increased myeloperoxidase and calprotectin (S1 Appendix).

Higher α-1-antitrypsin levels were associated with younger age, not breastfeeding, and having a pneumonia or malaria diagnosis, while reported diarrhea or detection of dehydrating pathogens were associated with lower α-1-antitrypsin. In multivariable regression, only reported diarrhea remained significantly associated α-1-antitrypsin (-0.43 SD; 95%CI: -0.59, -0.27; p < 0.001).

Mortality

Crude models found admission myeloperoxidase and calprotectin concentrations were associated with mortality in the 30-days following hospital admission (Table 4). However, after adjustment for confounding, neither biomarker remained associated with 30-day mortality. α-1-antitrypsin at admission was not associated with subsequent 30-day mortality in either crude or adjusted models

Table 4. Association between enteric dysfunction biomarkers and mortality in the hospital cohort.

		Crude				Adjusted¹
		HR	(95% CI)		P-value	HR	(95% CI)		p-value
Admission 30-day mortality²	MPO	1.34	(1.12,	1.59)	0.001	1.11	0.90	1.38	0.324
	CAL	1.20	(1.02,	1.42)	0.033	0.99	0.80	1.23	0.957
	AAT	1.09	(0.92,	1.29)	0.310	1.07	0.86	1.35	0.529
Discharge 180-day mortality³	MPO	1.31	(1.09,	1.56)	0.004	1.16	0.94	1.42	0.161
	CAL	1.19	(0.99,	1.42)	0.069	1.36	1.07	1.73	0.011
	AAT	0.99	(0.80,	1.22)	0.931	0.97	0.76	1.23	0.792

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¹Models were adjusted for invasive pathogens, recent diarrhea, age group, sex, breastfeeding, mid-upper arm circumference, height-for-age z-score, site and diagnoses of pneumonia, diarrhea and malaria. ²Mortality model for admission to 30 days. ³Discharge to 180-days post-discharge.

Abbreviations: MPO: Myeloperoxidase, CAL: calprotectin, AAT: α-1-antitrypsin, HR: Hazard ratio, CI: Confidence Interval. EAEC: entero-aggregative E. coli, EPEC: enteropathogenic E. coli, ETEC: enter-toxigenic E. coli,

Myeloperoxidase and calprotectin at discharge were associated with 180-day mortality following discharge in crude models. Discharge myeloperoxidase was not associated with mortality after adjustment, but a one SD increase in calprotectin at discharge was associated with 36% (hazard ratio 1.36, 95% CI: 1.07,1.72, p = 0.011) mortality increase. α-1-antitrypsin at discharge was not associated with 180-day post-discharge mortality in either crude or adjusted models.

Discussion

Biomarkers of enteric inflammation, including fecal myeloperoxidase and calprotectin, decreased during hospitalization to levels significantly lower than community peers, although the majority of children at admission, discharge (and in the community) had levels above what is considered normal for age (2000ng/ml for myeloperoxidase and 77 ug/ml for calprotectin) [22,23]. We also observed a decrease in invasive enteropathogen prevalence during hospitalization and the detection of invasive enteropathogens was strongly associated with enteric inflammation biomarkers among hospitalized children. Finally, fecal calprotectin at discharge from hospital was associated with post-discharge mortality in the adjusted model. Collectively, these data support the hypothesis that a high prevalence of invasive enteropathogens promotes enteric inflammation among acutely unwell children.

There was a high prevalence of enteropathogens among the community children, but an even greater burden among children admitted to hospital. The individual pathogen prevalence in our analysis aligned well with the consensus understanding of diarrhea etiology and asymptomatic carriage in LMICs [9,16,24–26]. EAEC and Campylobacter were commonly detected but were not specifically associated with diarrhea, while rotavirus and Shigella were most prevalent at admission among children presenting with diarrhea. Giardia appeared to be more common among community than hospitalized children, as has been observed in other settings, although the difference was not significant [27]. The prevalence of many pathogens substantially decreased between admission and discharge and this decline was prominent among Campylobacter, Shigella, and ETEC. Children enrolled in CHAIN were hospitalized for an average of five days, and 92% of admitted children received antibiotics. Penicillin, cephalosporin and gentamicin use was common and is likely to have played a role in the decline of bacterial enteropathogens during hospitalization. Changes in water and sanitation exposures and food types and preparation practices may also have contributed to declines in enteropathogens during hospitalization, although the evidence for the effectiveness of these interventions in community setting is mixed [28]. The lower fecal myeloperoxidase and calprotectin concentrations at discharge compared to the community may be partially attributable to the decline in invasive enteropathogens, or the direct effects of antibiotic, nutritional and environmental exposures common to inpatient management.

Enteric inflammatory biomarkers have been associated with increased morbidity, systemic inflammation, reduced vaccine responsiveness, and linear or ponderal growth delays [4,5,29]. Both systemic inflammation and poor nutritional status have been shown to be strongly predictors of post-discharge mortality [3,30–32]. It is possible that post-discharge morbidity and mortality could be reduced by therapeutics that help children avoid re-colonization with enteroinvasive pathogens or extend the period of reduced enteric inflammation after hospitalization by promoting nutrient uptake and decreasing systemic inflammation. A pilot trial in Kenya demonstrated that intestinal immunosuppression with the aminosalicylate mesalazine is safe among children with severe acute malnutrition and may be beneficial in reducing enteric inflammation [33]. A recent trial of enteric interventions at hospital discharge among children with severe acute malnutrition found that teduglutide, a glucagon-like peptide that promotes mucosal regeneration, reduced enteric inflammation, while oral budesonide, a corticosteroid active in the gut, was associated with reduced plasma C-reactive protein [34].

The observed increase in levels of fecal α-1-antitrypsin, an enteric permeability biomarker, during hospitalization was in the opposite direction compared to the enteric inflammatory biomarkers. However, this trend was isolated to children who had presented with diarrhea. A dilutional effect of diarrhea on α-1-antitrypsin concentrations at admission is highly likely, supported by our finding of a strong association between lower α-1-antitrypsin concentrations and dehydrating enteropathogens. However, α-1-antitrypsin did appear to be raised among children with either pneumonia or malaria. P. Falciparum malaria sequesters in intestinal capillaries and is thought to cause local hypoxia and increased permeability which may explain the association with α-1-antitrypsin [35,36].

Norovirus prevalence increased during hospitalization across multiple sites. Norovirus acquisition was most common among children admitted with diarrhea, which may indicate missed norovirus detections at admission or that norovirus is adept at infecting children with recent diarrhea. Children with diarrhea are often accommodated in distinct units within pediatric wards which may facilitate nosocomial norovirus acquisition. This finding suggests that norovirus testing for norovirus and isolation of infected patients could prevent nosocomial spread on paediatric units in LMICs.

The associations between ED biomarkers at admission and mortality were strongly confounded by factors such as MUAC, age and background illnesses suggesting ED at admission is either not a driver of mortality, that its contribution is masked by other factors of more substantial magnitude, or that it acts as a mediator for known risks factors of mortality. A case-control analysis among unwell severely malnourished children in Malawi and Kenya also found no association between fecal myeloperoxidase or calprotectin and inpatient deaths, [37] perhaps suggesting ED is not a strong determinant of inpatient mortality.

We did find that higher discharge calprotectin levels were associated with post-discharge mortality, potentially indicating that enteric inflammation undermines recovery in the post-discharge period. It is interesting to note that while the mean calprotectin was lower among children at admission, and especially at discharge, compared to community peers, the mean admission and discharge calprotectin concentrations were above levels considered within normal limits for age and even above levels considered sensitive and specific for inflammatory bowel disease [23, 38]. The association calprotectin-post-discharge mortality association suggests that enteric inflammation interplays with other factors among vulnerable children to increase the risk of death.

This analysis included data from nine hospitals in six countries and leveraged a broad panel of enteropathogens and ED biomarkers. However, the analysis has several limitations. These data were observational limiting our ability to infer causality. For example, systemic inflammation is known to be associated with post-discharge outcomes [31,32,39]. While systemic inflammation is considered to be a downstream consequence of enteric inflammation, [12,40] it is plausible that systemic inflammation may contribute to enteric inflammation. We did adjust for major diagnoses associated with systemic inflammation – namely sepsis, pneumonia, and malaria. However, systemic inflammation, especially due to other etiologies could be a residual confounder in the association between discharge calprotectin and mortality. Our cohort oversampled children with wasting to gain insights into patients with a high risk of mortality, but this may limit the generalizability or our findings to lower risk populations. Stool for measuring the concentration of ED biomarkers was not available for all children, which may have introduced selection bias. Diarrhea may have caused some dilution effect in ED biomarkers, although the trends observed in our analysis were also present among children without diarrhea. Finally, molecular enteropathogen diagnostics are highly sensitive, and detection of bacterial DNA after a course of antibiotics may be due to remnant nucleic acid rather than live bacteria. This would suggest our results could overestimate enteropathogen prevalence at discharge. Ultimately, interventional trials of therapeutics are needed to determine the clinical significance of ED in the post-discharge period.

Conclusions

Enteropathogens were common among community children, but even more prevalent among those admitted to hospital. During the hospitalization, the prevalence of bacterial pathogens and the concentration of enteric inflammatory biomarkers decreased to the point that children at discharge had lower enteric inflammation and fewer bacterial pathogen detections than comparable children in the community. However, most children had fecal calprotectin concentrations at discharge above levels considered within normal for age, and it was associated with post-discharge mortality. Collectively, these results suggest that at the point of discharge children may have relatively lower enteropathogen burden and less severe enteric inflammation and it is possible extending this period of relative enteric health may be opportunity to improve post-discharge outcomes.

Supporting information

S1 Appendix. Additional methods and results as cited in the main text.

(DOCX)

pgph.0006873.s001.docx^{(8.3MB, docx)}

S1 Checklist. Inclusivity in global research checklist.

(DOCX)

pgph.0006873.s002.docx^{(65.7KB, docx)}

Acknowledgments

We thank the CHAIN cohort participants and their families for their generous contribution to the study. We are indebted to the CHAIN teams at all sites, and the management and staff in hospitals and communities who kindly assisted in the conduct of the study.

Data Availability

Data are available on the Harvard Dataverse: https://doi.org/10.7910/DVN/HNK8GM.

Funding Statement

This work was supported, in whole or in part, by the Gates Foundation [Grant number OPP1131320 to JAB and INV-003225 To JLW]. The conclusions and opinions expressed in this work are those of the authors alone and shall not be attributed to the Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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Ayse Ercumen

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PGPH-D-25-03032

Enteric dysfunction and enteropathogens among hospitalized south Asian and sub-Saharan African children

PLOS Global Public Health

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Reviewer #1 : Overall Comments:

● What are the noteworthy results?

The noteworthy results of this paper are that ED biomarkers were higher in hospitalized children at admission than in community children, and that by the time hospitalized children were discharged, their ED biomarkers were lower, sometimes even lower than community children. Additionally, this paper found that ED biomarkers were higher in children who had an invasive enteropathogen detected from a rectal swab. Finally, fecal calprotectin at discharge was associated with mortality.

● Will the work be of significance to the field and related fields? How does it compare to the established literature? If the work is not original, please provide relevant references.

This study strengthens the existing evidence for a potential connection between enteric dysfunction, enteric pathogens, and mortality in hospitalized children, finding consistently that sicker children have higher ED biomarkers and more enteric pathogens, that these markers of illness improve during their hospital stay, and that discharge levels of calprotectin were associated with mortality. This study improves upon the existing literature with a larger and more diverse cohort of children.

● Does the work support the conclusions and claims, or is additional evidence needed?

Yes, the work supports the conclusions and claims.

● Are there any flaws in the data analysis, interpretation and conclusions? Do these prohibit publication or require revision?

Yes, the statistical analysis lacks adjustment for multiple comparisons. Given the magnitude of comparisons made, this should be addressed. At the very least, the choice not to make such adjustments must be defended in the text.

● Is the methodology sound? Does the work meet the expected standards in your field?

Besides the lack of adjustment for multiple comparisons, the methodology is sound.

● Is there enough detail provided in the methods for the work to be reproduced?

Yes

Major Comments:

Introduction

Page 4, Line 80: Additional context regarding the causes of post-discharge mortality would be useful. I.e. manner of death, associated dehydration, diarrhea, cardiovascular problems etc.

Page 4, Line 84: A more nuanced treatment of the interrelated conditions listed here (EED, ED, malnutrition, GI infections, systemic inflammation, and microbiome dysbiosis) is warranted. Additionally, this sentence lacks proper citation or rationale.

Page 4, Line 92-97: A more thorough review of other studies examining ED biomarkers in hospitalized children in LMICs is warranted here. There are a few I do not see cited in the paper, particularly Sturgeon 2024 and the recent Allen 2025 in Nature Comms. Going over their findings and highlighting potential differences in the authors’ study design would be a valuable addition. As this study is described in lines 94-97, be sure to highlight the timing of biomarker measurement (admission vs. discharge) and comparisons with community children.

Methods: Identification and adjustment of confounders was unclear in this section, though tables were helpful; please clarify and emphasize this part of the analysis. Additionally, please provide the coefficient of variation for the ELISA assays.

Discussion

Page 14, Line 327-329: I certainly would understand if the authors choose to address this in another work, but I would be very curious to see what additional analyses of the relationship between antibiotic use, ED biomarkers, and enteropathogen presence would reveal. For this paper, I wonder whether antibiotic use should have been run in the ED biomarker correlate analysis or as a potential confounder in every multivariate analysis performed. It would be interesting to see whether antibiotics would be associated with more detection of norovirus, for example.

Page 14, Line 329–331: Including some additional information and citations regarding the impacts of sanitation changes on ED biomarkers and enteropathogens would strengthen this hypothesis.

Page 15, Line 338-341: This idea would be strengthened if the authors would add information about the details of post-discharge morbidity and mortality here or elsewhere in the introduction/discussion.

Page 15, Line 346: Additional information about budesonide, as the authors have provided about teduglutide and mesalazine, is warranted.

Table 1: Would be valuable to add reason for hospitalization to the characteristics table, or somewhere else if more appropriate, assuming this would be different than Diagnoses. If diagnoses is equivalent to reason for hospitalization please clarify this.

Figure 2: Resolution is poor on this image. Include n for each group. Note that most papers use ng/mL to report MPO concentrations (see Kosek 2013). Keeping units the same from paper to paper is important for the purpose of comparison. It also appears the authors use different units in tables vs. this figure, please amend. This image tells a strong story that did not come off so clearly in the text of the results - perhaps consider strengthening the text for this section.

S2 Table 6: This table should be included in the main text given that it is a whole section of the results.

Minor Comments:

Page 3, Line 65: strike “was associated with mortality”; redundant with first part of sentence.

Page 4, Line 82: add microbial to specify what kind of translocation

Page 4, Line 92: would be valuable to add some additional citations after enteroinvasive to further support the consensus on the relationship between ED biomarkers and enteropathogens.

Page 10, Line 229: Awk sentence, recommend adding a semicolon after “During hospitalization norovirus presences nearly doubled”

Page 14, Lines 313-316: Recommend reordering these two sentences so that the statement outlining how the authors’ evidence supports the hypothesis concludes the paragraph.

Page 14, Line 325: typo; change “his” to “this”

Page 15, Line 349: Formatting may have been altered by forces outside the authors’ control but be sure to italize latin name for P. falciparum malaria.

Page 17, Line 381: typo; change “diagnostic is” to “diagnostics are”

Table 3: Appears to be a missed bold or typo in None vs. exclusive breastfeeding; a-1-antitrypsin for adjusted comparison; Coef is positive, 95% CI is negative. Typo in second line under table. Change “due” to “of”. Appears to be minor alignment issue with center column as coef’s are lower than corresponding CIs.

Reviewer #2 : This manuscript addresses an important and underexplored question regarding enteric dysfunction and enteropathogen burden in hospitalized children across LMICs. The data are drawn from the well-established CHAIN cohort and benefit from a large, multi-site, multi-country design. However, the manuscript has several substantive methodological, analytical, and interpretive concerns that must be addressed before it can be considered for publication. The specific issues are detailed below, organized by section, with line numbers provided for the authors' reference.

Abstract

Lines 48-49 vs. Lines 199-200: abstract states that cox-proportional hazard models assessed ED biomarker associations with 'inpatient and post-discharge mortality.' while methods later clarifies that 30-day period following admission was chosen. Why are these two framings contradictory? The abstract must be corrected to accurately reflect what was actually measured.

Lines 53-55: Calprotectin at discharge was significantly lower than community, yet the abstract goes on to report that discharge calprotectin was the only biomarker associated with mortality. If discharge calprotectin was not elevated, the premise that enteric inflammation at admission is a clinically important finding in this hospitalized group becomes difficult to defend. The authors need to address why a biomarker that behaves no differently from the community would carry mortality-predictive value at discharge.

Introduction

Lines 78-97: The introduction is well-structured and provides limited background. However, it does not provide the specific hypothesis being tested regarding whether enteric dysfunction in acutely ill hospitalized children is etiologically distinct from environmental enteric dysfunction in community children. This distinction is critical for interpreting the results and should be stated more explicitly.

Methods

Lines 128-132: What is the justification for nested case-cohort (NCC) randomly selected 24% of children from the CHAIN cohort along with all deaths. Was a formal sample size calculation performed to ensure this sub-cohort was powered to detect associations between ED biomarkers and mortality? If so, the assumed effect sizes, alpha, and power should be reported. If not, this is a significant methodological gap that must be acknowledged.

Lines 129-132: The decision to recruit 30 community children per site also lacks justification.

Lines 199-201: The authors state that the 30-day period following hospital admission was chosen because 'inpatient mortality is biased by discharge decisions.' While this reasoning is understandable, labelling this as inpatient mortality anywhere in the manuscript is inaccurate. Children discharged within that 30-day window who subsequently die are not inpatient deaths.

Lines 199-204: Using ED biomarkers measured at admission to predict mortality over the subsequent 30 days, without accounting for or even reporting the number of days each child remained hospitalized, is a fundamental flaw. A child admitted with a high myeloperoxidase value who dies on day two of admission versus from one who survives, is treated, and dies on day 28? The length of hospital stay is not reported anywhere in the manuscript, no mean or median duration of admission is provided despite the discussion (line 327) mentioning 'an average of five days.' If this figure exists, it belongs in Table 1 or the results section, and its implications for the mortality models must be examined.

Lines 206-211: Using discharge biomarker concentrations to predict mortality over 180 days following discharge is a very long causal window. The biological rationale for why a stool biomarker measured at the point of discharge would independently predict mortality six months later, against the backdrop of all the life events, re-infections, nutritional deterioration, or new illnesses that could occur in that period, is not adequately established. The authors must provide a scientific justification for this association as it is highlighted in the conclusions that is drawn from it.

Lines 202-210: MUAC is used as a covariate in both the admission and discharge models. The authors should clarify whether admission MUAC or discharge MUAC is used in each respective model. More importantly, it is biologically implausible that MUAC would change meaningfully over a median hospital stay of five days in these children. If admission MUAC is used in the discharge model, this needs to be justified. If discharge MUAC is used, the authors need to explain what meaningful change is expected in this short a window in acutely ill malnourished children, and whether this creates collinearity with admission MUAC.

Results

Line 218: The statement that hospitalized children were 'less commonly exclusive breastfed' requires clarification. A comparison of breastfeeding rates across the broad age group confound the age-appropriate feeding practices with what may simply be an age distribution difference between the hospitalized and community groups. This should be stratified by age group or the comparison should be appropriately caveated.

Lines 216-222: Table 1 provides sociodemographic and clinical characteristics but does not report the distribution of MUAC strata (no wasting, moderate wasting, severe wasting or kwashiorkor) separately for the hospitalized group. Given that enrollment was deliberately stratified by MUAC in a 2-1-2 ratio, and that MUAC is strongly associated with both biomarker levels and mortality, the reader needs to know how many children fell into each nutritional stratum. Failure to present this renders the clinical context of the acutely ill cohort incomplete and makes it impossible to assess the degree of confounding by nutritional status.

Lines 225-231: The paper compares the prevalence of dehydrating pathogens between hospitalized and community children and reports a significant difference (25-27% vs 8%, p<0.001). While this is numerically striking, the clinical relevance of this comparison is questionable. Children admitted to hospital are there precisely because they are acutely unwell, and a significant proportion presented with diarrhea. Comparing pathogen prevalence for dehydrating organisms in acutely ill hospitalized children with healthy community children tells us little beyond the expected. The authors should clarify what clinical or public health inference they intend the reader to draw from this comparison.

Lines 242-243: Giardia was lower among hospitalized children at both admission and discharge compared to community children (7% vs 11%), and this finding is never discussed. Given that Giardia is associated with asymptomatic carriage and positive growth outcomes in some cohorts, its higher prevalence in the community group warrants at least a brief acknowledgment in the discussion.

Lines 246-252: The alpha-1-antitrypsin findings are counterintuitive and insufficiently explained in the results. Concentrations are lower at admission compared to the community, but then recover to community levels by discharge. The direction of this change is opposite to that of the inflammatory markers and the biological interpretation is unclear. The authors invoke a dilutional effect of diarrhea in the discussion, but this is not examined rigorously in the results. Given that this biomarker reflects intestinal permeability, not inflammation, and given that these children are acutely ill with multiple conditions that could compromise gut barrier function, this unexpected pattern deserves a proper mechanistic discussion rather than a brief mentioning.

Lines 254-256: The text states that 'trends in pathogen prevalence were similar among hospitalized children with and without reported diarrhea,' yet the very next sentence reports that children with diarrhea had higher rotavirus, norovirus, typical EPEC, and Shigella prevalence. These two statements are not consistent. If the distributions of individual pathogens differ substantially by diarrhea status, the overall trends cannot be described as similar without qualification.

Lines 267-285 (Table 3): The correlate models in Table 3 are restricted to the hospitalized cohort. No equivalent model is presented for community children. It is therefore unknown whether the association between lower MUAC and higher myeloperoxidase or calprotectin is specific to the acutely ill or is equally present in the community. The same applies to the association with invasive enteropathogens. Without a community reference model, it is impossible to determine whether these associations are a feature of acute illness or simply reflect the biology of these children in their home environment.

Lines 267-285 (Table 3): Acutely ill children in this cohort have a high prevalence of sepsis (13.4%), pneumonia (39.6%), and malaria (12.6%). Fecal biomarkers such as myeloperoxidase and calprotectin reflect systemic as well as local intestinal inflammation. In children with these co-morbidities, attributing elevated biomarker values to enteropathogen detection, whether or not diarrhea is present, is methodologically problematic. The presence of these systemic illnesses is a major unmeasured confounder for the enteropathogen-biomarker relationship, and this is insufficiently acknowledged.

Lines 293-297: The crude models found that admission myeloperoxidase and calprotectin were associated with 30-day mortality, but this association was lost after adjustment. This is an important null finding that deserves more interpretive weight in the discussion. If the biomarker-mortality relationship at admission disappears entirely after adjusting for MUAC, age, and co-morbidities, then the biomarkers add no independent prognostic information at admission. The authors should reflect on what this means for the utility of measuring these biomarkers at admission?

Lines 299-304: The finding that discharge calprotectin is associated with 180-day post-discharge mortality, while no admission biomarker retains significance after adjustment, raises the question of whether this reflects a true biological relationship or residual confounding. Discharge calprotectin was already lower than community levels (171.2 vs 252.4 ug/ml). Explaining how a biomarker that is already below community norms at discharge independently predicts mortality six months later requires more than a hazard ratio; it requires a mechanistic and contextual argument that is not currently present.

Lines 299-304: The text does not clearly specify for which model admission versus discharge biomarker values were used. The description of crude and adjusted models for 30-day and 180-day outcomes would benefit from explicit clarification in each case as to which timepoint's biomarker was entered into each model.

Lines 299-304: The HIV-infected rate in this cohort is 6.7%. HIV infection is independently associated with enteropathy, impaired immunity, and mortality. The handling of HIV-infected children in the mortality models is not described. Were they excluded, included without stratification, or included with HIV status as a covariate? Given the known impact of HIV on both enteric inflammation and post-discharge mortality, this requires explicit reporting.

Figure 2

Figure 2: A dedicated figure is presented comparing myeloperoxidase at admission and discharge, stratified by invasive pathogen detection. However, myeloperoxidase was not associated with mortality in either crude or adjusted post-discharge models. Presenting a detailed figure for a biomarker that does not ultimately predict the primary outcome of interest, while calprotectin, which did retain significance, is not similarly visualized, represents a disconnect between the analytical focus and the visual emphasis of the manuscript. The authors should reconsider this figure or add a parallel figure for calprotectin.

Discussion

Lines 307-397: The discussion section reads largely as an overview of the broader literature on enteric dysfunction and EED rather than an interpretation of the authors' own findings. Key results from this study, particularly the null findings for myeloperoxidase and alpha-1-antitrypsin in the mortality models, the counterintuitive direction of alpha-1-antitrypsin across timepoints, and the paradox of below-community calprotectin at discharge predicting mortality six months later, are not given adequate analytical attention. The discussion should be restructured to lead with the authors' own results and use the literature to contextualize them, not the other way around.

Lines 338-346: The authors conclude by recommending 'interventions to prevent re-colonization with enteropathogens' as a strategy to improve post-discharge health. However, the study did not collect any post-discharge stool samples. There are no data in this manuscript on enteropathogen burden after discharge, whether re-colonization occurred, at what rate, with which pathogens, or how it related to outcomes. The conclusion that re-colonization is the mechanism driving post-discharge mortality is entirely speculative and unsupported by the data presented. This recommendation either needs to be removed or framed as a hypothesis to be tested, not a conclusion from this study.

Lines 364-373: The authors note that the association between discharge calprotectin and post-discharge mortality may reflect residual confounding by systemic inflammation. This is an important caveat but it is buried. If systemic inflammation is a plausible confounder and was not measured or adjusted for, this is a significant limitation that should be prominently stated.

Conclusions

Lines 388-397: The conclusions overstate what the data support. The study found that discharge calprotectin was associated with 180-day post-discharge mortality after adjustment for a set of measured confounders. It did not test any intervention, did not follow children after discharge to assess re-colonization, and did not demonstrate that reducing calprotectin at discharge improves outcomes. The concluding statement that interventions to prevent enteropathogen recolonization and prolong reduced enteric inflammation 'may be useful adjuncts to discharge care' cannot be inferred from the results of this observational study. The conclusions must be restricted to what the data actually show.

Lines 388-397: cohort was oversampled for malnourished children and includes a sizeable proportion with severe wasting or kwashiorkor, HIV infection, malaria, pneumonia, and sepsis. These are not representative of all hospitalized children. The generalizability of these findings to hospitalized children without severe malnutrition or these comorbidities is entirely unclear and should be stated explicitly as a limitation.

Additional Concerns:

Norovirus (Lines 229-231): The near-doubling of norovirus prevalence during hospitalization, observed consistently across seven of nine sites, is a notable signal for nosocomial acquisition. This finding has direct infection prevention and control implications. It deserves greater prominence in the discussion and should be flagged as a clinical concern, not merely noted as a descriptive finding.

Table 2: The IQR for discharge myeloperoxidase is reported as 0.6 to 33, which appears to be a typographical error given the median is 1.4 ug/ml. This should be verified and corrected.

Statistical methods (Lines 166-212): P values for comparing enteropathogen prevalence across groups are described as derived from chi-square tests, but no details are provided regarding how the nested case-cohort weighting was applied to these comparisons. Given that the NCC design over-represents deaths, unadjusted proportions and chi-square tests may not reflect the true prevalence in the parent CHAIN cohort. The authors should clarify whether these prevalence estimates are weighted or unweighted.

Major revision required. The manuscript addresses a clinically relevant question using a well-designed multi-site cohort, but the current version has major gaps in the reporting of basic descriptive statistics, an insufficient scientific basis for several key analytical choices, an overclaiming of conclusions relative to the data, and a discussion that does not adequately support the results or defend the findings. The concerns raised above must be addressed systematically before this work is suitable for publication.

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Reviewer #1: No

Reviewer #2: Yes: Zehra Jamil

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PLOS Glob Public Health. 2026 Jul 24;6(7):e0006873. doi: 10.1371/journal.pgph.0006873.r003

Author response to Decision Letter 1

12 May 2026

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PLOS Glob Public Health. doi: 10.1371/journal.pgph.0006873.r004

Decision Letter 1

Ayse Ercumen

30 Jun 2026

Enteric dysfunction and enteropathogens among hospitalized south Asian and sub-Saharan African children

PGPH-D-25-03032R1

Dear Dr. Tickell,

We are pleased to inform you that your manuscript 'Enteric dysfunction and enteropathogens among hospitalized south Asian and sub-Saharan African children' has been provisionally accepted for publication in PLOS Global Public Health.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

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Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Global Public Health.

Best regards,

Ayse Ercumen, Ph.D.

Academic Editor

PLOS Global Public Health

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Reviewer #1: All comments have been addressed

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Reviewer #1: Yes

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Reviewer #1: Yes

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Reviewer #1: Yes

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-->6. Review Comments to the Author

Reviewer #1: The authors have addressed all my major concerns.

I found two dropped words that might be considered for minor revisions:

Page 4, Line 81: add "a" after "attributable to"

Page Line 453: add "an" before "opportunity"

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 Appendix. Additional methods and results as cited in the main text.

(DOCX)

pgph.0006873.s001.docx^{(8.3MB, docx)}

S1 Checklist. Inclusivity in global research checklist.

(DOCX)

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Submitted filename: Response letter_12Nov2025.pdf

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Data Availability Statement

Data are available on the Harvard Dataverse: https://doi.org/10.7910/DVN/HNK8GM.

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PERMALINK

Enteric dysfunction and enteropathogens among hospitalized south Asian and sub-Saharan African children

Abu Sadat Mohammad Sayeem Bin Shahid

Donna M Denno

Kevin Kariuki

Doreen Rwigi

Amran Gazi

Lubaba Shahrin

Wilson Gumbi

James M Njunge

Mohammod J Chisti

Tahmeed Ahmed

Eric R Houpt

Jie Liu

Mami Taniuchi

Benson O Singa

Robert H J Bandsma

Wieger Voskuijl

Ali F Saleem

Christina L Lancioni

Ezekiel Mupere

Abdoulaye H Diallo

Judd L Walson

James A Berkley

Kirkby D Tickell

Roles

Abstract

Introduction

Methods

Study design, setting and population

Ethics statement

Laboratory analysis and data preprocessing

Statistical analysis

Correlates of ED biomarkers

Mortality analysis

Results

Fig 1. Study participant flow chart.

Table 1. Baseline characteristics of study participants.

Pathogen prevalence

Table 2. Pathogen prevalence and ED biomarkers among included children, adjusted for sample selection into the nested case cohort.

ED biomarkers

Fig 2. Median myeloperoxidase concentrations at admission and discharge from hospital compared to community levels, stratified by the detection of invasive pathogens.

Sensitivity analyses

Correlates of ED biomarkers at admission

Table 3. Correlates of ED fecal biomarkers.

Mortality

Table 4. Association between enteric dysfunction biomarkers and mortality in the hospital cohort.

Discussion

Conclusions

Supporting information

Acknowledgments

Data Availability

Funding Statement

References

Author response to Decision Letter 0

Transfer Alert

Decision Letter 0

Ayse Ercumen

Roles

Author response to Decision Letter 1

Decision Letter 1

Ayse Ercumen

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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