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. 2013 Dec 1;208(11):1794-802.
doi: 10.1093/infdis/jit507. Epub 2013 Sep 16.

Etiology of diarrhea in Bangladeshi infants in the first year of life analyzed using molecular methods

Mami Taniuchi  1 , Shihab U Sobuz, Sharmin Begum, James A Platts-Mills, Jie Liu, Zhengyu Yang, Xin-Qun Wang, William A Petri Jr, Rashidul Haque, Eric R Houpt
Affiliations

Etiology of diarrhea in Bangladeshi infants in the first year of life analyzed using molecular methods

Mami Taniuchi et al. J Infect Dis. .

Abstract

Background: Diarrhea causes enormous morbidity and mortality in developing countries, yet the relative importance of multiple potential enteropathogens has been difficult to ascertain.

Methods: We performed a longitudinal cohort study from birth to 1 year of age in 147 infants in Dhaka, Bangladesh. Using multiplex polymerase chain reaction, we analyzed 420 episodes of diarrhea and 1385 monthly surveillance stool specimens for 32 enteropathogen gene targets. For each infant we examined enteropathogen quantities over time to ascribe each positive target as a probable or less-likely contributor to diarrhea.

Results: Multiple enteropathogens were detected by the first month of life. Diarrhea was associated with a state of overall pathogen excess (mean number of enteropathogen gene targets (± SE), 5.6 ± 0.1 vs 4.3 ± 0.1 in surveillance stool specimens; P < .05). After a longitudinal, quantitative approach was applied to filter out less-likely contributors, each diarrheal episode still had an average of 3.3 probable or dominant targets. Enteroaggregative Escherichia coli, Campylobacter, enteropathogenic E. coli, rotavirus, and Entamoeba histolytica were the most frequent probable contributors to diarrhea. Rotavirus was enriched in moderate to severe diarrheal episodes.

Conclusions: In this community-based study diarrhea seemed to be a multipathogen event and a state of enteropathogen excess above a high carriage baseline.

Keywords: Campylobacter; Diarrhea; PCR; enteroaggregative e.coli; rotavirus.

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Figures

Figure 1.
Figure 1.
Frequency of enteropathogen detection in Dhaka versus Virginia. Diarrheal and nondiarrheal stool samples were collected at the time points indicated and assayed for 29 enteropathogens by molecular methods. The total number of enteropathogens was summed for each sample; results are shown as mean ± SE. *Bonferroni adjusted P value < .05 (determined with linear mixed-effect regression model used to identify differences in the number of pathogens detected between diarrheal and surveillance samples for each month during the study period). **Nonparametric Wilcoxon 2-sample tests were used to compare numbers of pathogens between Virginia and Dhaka samples and between diarrheal and surveillance samples for Virginia alone.
Figure 2.
Figure 2.
Detection rate for pathogens in diarrheal and surveillance stool samples by nucleic acid target. Enteropathogens are shown along the x-axis (targets in parentheses). Nonparametric Wilcoxon signed rank tests were used to determine whether there was any difference between the percentages of positive stool samples in diarrhea and surveillance samples for a specific target over the study year. *Detection rate significantly greater in diarrheal than in surveillance stool samples (after Bonferroni correction for multiple comparisons). **Detection rate significantly less in diarrheal than in surveillance stool samples (after Bonferroni correction). Abbreviations: COWP, Cryptosporidium oocyst wall protein; EAEC, enteroaggregative E. coli; EIEC, enteroinvasive E. coli; EPEC, enteropathogenic E. coli; ETEC, enterotoxigenic E. coli; RdRp, RNA-dependent RNA polymerase; rRNA, ribosomal RNA; ssrRNA, small-subunit rRNA; STEC, Shiga toxin–producing E. coli.
Figure 3.
Figure 3.
Odds ratio (OR) for diarrhea by nucleic acid target. Enteropathogen targets were analyzed for diarrhea association by univariate analysis. Targets with statistically significant ORs are labeled. Green line indicates OR of 1. Abbreviation: EIEC, enteroinvasive Escherichia coli.
Figure 4.
Figure 4.
Longitudinal quantitative approach to determining the enteropathogen contribution to diarrhea. A Bangladeshi infant in the first year of life is shown. All detected nucleic acid targets in diarrheal and nondiarrheal stools samples are shown (pink and blue columns, respectively, with total numbers of targets indicated on the left y-axis). The enteropathogen target quantity is stratified by quartile (according to right y-axis). Pink text indicates probable contributors to diarrhea; gray text, less-likely contributors; and red text, subgroup of probable contributors at the highest quantity (dominant contributors; see text for further explanation of categories). For example, LT is considered a less-likely contributor to the first episode of diarrhea because it was detected at a higher quantity in a prior surveillance stool sample. Abbreviations: cMFI, corrected median fluorescent intensity; Rota, rotavirus; Campy, Campylobacter; Astro, astrovirus; Adeno, adenovirus; E. his, E. histolytica.
Figure 5.
Figure 5.
Distribution of targets found in diarrheal stool samples. We enumerated the total number of times each enteropathogen received a probable or less-likely call. The subset of probable targets at the highest quantity were termed dominant. To not overrepresent a diarrheal sample that had multiple pathogens over another that had few, every diarrheal episode was permitted a total of 1.0 dominant, 1.0 probable, and 1.0 less-likely pathogen; thus, the sum of all columns is approximately 1260 (420 diarrheal episodes × 3.0). Abbreviations: COWP, Cryptosporidium oocyst wall protein; EAEC, enteroaggregative E. coli; EHEC, enterohemorrhagic E. coli; EIEC, enteroinvasive E. coli; EPEC, enteropathogenic E. coli; ETEC, enterotoxigenic E. coli; RdRp, RNA-dependent RNA polymerase; rRNA, ribosomal RNA; ssrRNA, small-subunit rRNA; STEC, Shiga toxin–producing E. coli.
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