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Gut microbiome alteration in MORDOR I: a community-randomized trial of mass azithromycin distribution

Nature Medicine volume 25, pages 1370–1376 (2019)Cite this article

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Abstract

The MORDOR I trial1, conducted in Niger, Malawi and Tanzania, demonstrated that mass azithromycin distribution to preschool children reduced childhood mortality1. However, the large but simple trial design precluded determination of the mechanisms involved. Here we examined the gut microbiome of preschool children from 30 Nigerien communities randomized to either biannual azithromycin or placebo. Gut microbiome γ-diversity was not significantly altered (P = 0.08), but the relative abundances of two Campylobacter species, along with another 33 gut bacteria, were significantly reduced in children treated with azithromycin at the 24-month follow-up. Metagenomic analysis revealed functional differences in gut bacteria between treatment groups. Resistome analysis showed an increase in macrolide resistance gene expression in gut microbiota in communities treated with azithromycin (P = 0.004). These results suggest that prolonged mass azithromycin distribution to reduce childhood mortality reduces certain gut bacteria, including known pathogens, while selecting for antibiotic resistance.

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Fig. 1: Study design.
Fig. 2: Gut microbiome community, diversity, and composition of preschool children randomized to the placebo- and azithromycin-treated groups.
Fig. 3: Relative abundances of individual microbial genera and species differ between children treated with placebo versus azithromycin.
Fig. 4: Bacterial functional profile and resistome between treatment groups.

Data availability

The data that support the findings of this study are available from the corresponding author upon request. The microbial sequencing reads have been deposited with the NCBI Sequence Read Archive under BioProject no. PRJNA549968. Additional processed data reported in this study are available upon request. Limitations apply to variables that may compromise participant privacy or consent.

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Acknowledgements

We thank S. Kumar for the helpful discussions regarding the gut pathogens identified in this study. We thank the program officers from the trial’s sponsor: Bill and Melinda Gates Foundation, R. Izadnegahdar, J. Jacobson, T. Kanyok, E. Shutes, C. Damman, A. Sarangi and L. Lamberti. We also thank the members of the Data and Safety Monitoring Committee: University of Washington, J. Walson; Liverpool School of Tropical Medicine, A. Hightower; Loyola University, E. Anderson; Berhan Public Health & Eye Care Consultancy, W. Alemayehu; Tulane University, L. Rajan. This work was supported by the Bill and Melinda Gates Foundation (award no. OPP1032340 to T.M.L.), the Peierls Foundation (T.M.L.), a Research to Prevent Blindness Career Development Award (award no. 127613A to T.D.) and an unrestricted grant from Research to Prevent Blindness. The funding organizations had no role in the analysis or interpretation of the data or the preparation of the manuscript.

Author information

Authors and Affiliations

  1. Francis I Proctor Foundation, University of California, San Francisco, CA, USA

    T. Doan, A. Hinterwirth, L. Worden, L. Zhong, S. L. Cummings, S. Sakar, C. Chen, C. Cook, E. Lebas, T. C. Porco, J. D. Keenan & T. M. Lietman

  2. Department of Ophthalmology, University of California, San Francisco, CA, USA

    T. Doan, T. C. Porco, J. D. Keenan & T. M. Lietman

  3. The Carter Center, Niamey, Niger

    A. M. Arzika, R. Maliki & S. Kane

  4. Ministry of Public Health, Niamey, Niger

    A. Abdou

  5. Programme National de Soins Oculaires, Niamey, Niger

    A. Abdou

  6. Department of Biochemistry and Biophysics, University of California, San Francisco, CA, USA

    E. D. Chow

  7. Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA

    I. Nachamkin

  8. Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA

    T. C. Porco & T. M. Lietman

  9. Institute for Global Health Sciences, University of California, San Francisco, CA, USA

    T. M. Lietman

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  1. T. Doan
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Contributions

T.D. and T.M.L designed the experiments and supervised the project. T.D., L.Z., S.L.C., S.S. and C. Chen performed the experiments. T.C.P. performed the randomization. A.M.A., R.M., S.K., A.A., C. Cook, E.L., J.D.K. and T.M.L. oversaw the field work and sample collection. E.D.C. assisted with sample sequencing. T.D., A.H., L.W. and T.C.P. wrote the scripts and performed the bioinformatics analyses with contributions from T.M.L. I.N. assisted with data interpretation. T.D. and T.M.L. wrote the initial draft; all coauthors reviewed the manuscript and agreed to publication.

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Correspondence to T. Doan.

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Peer review information: Alison Farrell is the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 Relative abundances of species significantly different between treatment groups.

Normalized abundance, averaged at the village level, arranged by supervised hierarchical clustering. Thirty-five differential species identified with a false discovery rate < 0.01 and log2(fold change) > 2 (two-sided negative binomial Wald test with Benjamini–Hochberg correction for multiple comparisons).

Source data

Extended Data Fig. 2 Resistome of the gut microbiome between treatment groups.

Box plots, with individual values shown as dots, for all classes of resistance determinants, except macrolides, detected in the rectal samples of preschool children at baseline and at 24 months for 30 villages. Each data point is the prevalence of resistance determinants per village. The boxes indicate the median and quartiles of prevalence; the whiskers indicate the estimated 95% CI. Az, azithromycin; Pl, placebo.

Source data

Extended Data Fig. 3 Campylobacter macrolide resistance between treatment groups.

Box plots, with individual values shown as dots, of the prevalence of any nucleotide change from A at position 2,075 of the 23S rRNA transcript detected in the rectal samples of preschool children at baseline and at 24 months (n = 30 villages; P = 0.66, ANCOVA). Each data point is the prevalence of resistance transcripts per village. The boxes indicate the median and quartiles of prevalence; the whiskers indicate the estimated 95% CI.

Source data

Supplementary information

Supplementary Information

Supplementary Tables 1–6 and Statistical Analysis Plan

Reporting Summary

Source data

Source Data Fig. 2

Statistical Data Analysis

Source Data Fig. 3

Statistical Data Analysis

Source Data Fig. 4

Statistical Data Analysis

Extended Data Fig. 1

Statistical Data Analysis

Extended Data Fig. 2

Statistical Data Analysis

Extended Data Fig. 3

Statistical Data Analysis

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Doan, T., Hinterwirth, A., Worden, L. et al. Gut microbiome alteration in MORDOR I: a community-randomized trial of mass azithromycin distribution. Nat Med 25, 1370–1376 (2019). https://doi.org/10.1038/s41591-019-0533-0

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