@article {1381, title = {Prolonged mass azithromycin distributions and macrolide resistance determinants among preschool children in Niger: A sub-study of a cluster-randomized trial (MORDOR).}, journal = {PLoS Med}, volume = {21}, year = {2024}, month = {2024 May}, pages = {e1004386}, abstract = {

BACKGROUND: Randomized controlled trials found that twice-yearly mass azithromycin administration (MDA) reduces childhood mortality, presumably by reducing infection burden. World Health Organization (WHO) issued conditional guidelines for mass azithromycin administration in high-mortality settings in sub-Saharan Africa given concerns for antibiotic resistance. While prolonged twice-yearly MDA has been shown to increase antibiotic resistance in small randomized controlled trials, the objective of this study was to determine if macrolide and non-macrolide resistance in the gut increases with the duration of azithromycin MDA in a larger setting.

METHODS AND FINDINGS: The Macrolide Oraux pour R{\'e}duire les D{\'e}c{\`e}s avec un Oeil sur la R{\'e}sistance (MORDOR) study was conducted in Niger from December 2014 to June 2020. It was a cluster-randomized trial of azithromycin (A) versus placebo (P) aimed at evaluating childhood mortality. This is a sub-study in the MORDOR trial to track changes in antibiotic resistance after prolonged azithromycin MDA. A total of 594 communities were eligible. Children 1 to 59 months in 163 randomly chosen communities were eligible to receive treatment and included in resistance monitoring. Participants, staff, and investigators were masked to treatment allocation. At the conclusion of MORDOR Phase I, by design, all communities received an additional year of twice-yearly azithromycin treatments (Phase II). Thus, at the conclusion of Phase II, the treatment history (1 letter per 6-month period) for the participating communities was either (PP-PP-AA) or (AA-AA-AA). In Phase III, participating communities were then re-randomized to receive either another 3 rounds of azithromycin or placebo, thus resulting in 4 treatment histories: Group 1 (AA-AA-AA-AA-A, N = 51), Group 2 (PP-PP-AA-AA-A, N = 40), Group 3 (AA-AA-AA-PP-P, N = 27), and Group 4 (PP-PP-AA-PP-P, N = 32). Rectal swabs from each child (N = 5,340) were obtained 6 months after the last treatment. Each child contributed 1 rectal swab and these were pooled at the community level, processed for DNA-seq, and analyzed for genetic resistance determinants. The primary prespecified outcome was macrolide resistance determinants in the gut. Secondary outcomes were resistance to beta-lactams and other antibiotic classes. Communities recently randomized to azithromycin (groups 1 and 2) had significantly more macrolide resistance determinants than those recently randomized to placebo (groups 3 and 4) (fold change 2.18, 95\% CI 1.5 to 3.51, Punadj \< 0.001). However, there was no significant increase in macrolide resistance in communities treated 4.5 years (group 1) compared to just the most recent 2.5 years (group 2) (fold change 0.80, 95\% CI 0.50 to 1.00, Padj = 0.010), or between communities that had been treated for 3 years in the past (group 3) versus just 1 year in the past (group 4) (fold change 1.00, 95\% CI 0.78 to 2.35, Padj = 0.52). We also found no significant differences for beta-lactams or other antibiotic classes. The main limitations of our study were the absence of phenotypic characterization of resistance, no complete placebo arm, and no monitoring outside of Niger limiting generalizability.

CONCLUSIONS: In this study, we observed that mass azithromycin distribution for childhood mortality among preschool children in Niger increased macrolide resistance determinants in the gut but that resistance may plateau after 2 to 3 years of treatment. Co-selection to other classes needs to be monitored.

TRIAL REGISTRATION: NCT02047981 https://classic.clinicaltrials.gov/ct2/show/NCT02047981.

}, keywords = {Anti-Bacterial Agents, Azithromycin, Child Mortality, Child, Preschool, Drug Resistance, Bacterial, Female, Humans, Infant, Macrolides, Male, Mass Drug Administration, Niger}, issn = {1549-1676}, doi = {10.1371/journal.pmed.1004386}, author = {Arzika, Ahmed M and Abdou, Amza and Maliki, Ramatou and Beido, Nassirou and Kadri, Boubacar and Harouna, Abdoul N and Galo, Abdoul N and Alio, Mankara K and Lebas, Elodie and Oldenburg, Catherine E and O{\textquoteright}Brien, Kieran S and Chen, Cindi and Zhong, Lina and Zhou, Zhaoxia and Yan, Daisy and Hinterwirth, Armin and Keenan, Jeremy D and Porco, Travis C and Lietman, Thomas M and Doan, Thuy} } @article {86, title = {Post-antibiotic Ocular Surface Microbiome in Children: A Cluster-Randomized Trial.}, journal = {Ophthalmology}, volume = {127}, year = {2020}, month = {2020 08}, pages = {1127-1130}, keywords = {Anti-Bacterial Agents, Child, Cornea, Humans, Microbiota, Randomized Controlled Trials as Topic}, issn = {1549-4713}, doi = {10.1016/j.ophtha.2020.02.014}, author = {Doan, Thuy and Hinterwirth, Armin and Worden, Lee and Arzika, Ahmed M and Maliki, Ramatou and Chen, Cindi and Zhong, Lina and Zhou, Zhaoxia and Acharya, Nisha R and Porco, Travis C and Keenan, Jeremy D and Lietman, Thomas M} } @article {151, title = {High-throughput sequencing of pooled samples to determine community-level microbiome diversity.}, journal = {Ann Epidemiol}, volume = {39}, year = {2019}, month = {2019 11}, pages = {63-68}, abstract = {

PURPOSE: Community-level interventions in cluster randomized controlled trials may alter the gut microbiome of individuals. The current method of estimating community diversities uses microbiome data obtained from multiple individual{\textquoteright}s specimens. Here we propose randomly pooling a number of microbiome samples from the same community into one sample before sequencing to estimate community-level microbiome diversity.

METHODS: We design and analyze an experiment to compare community microbiome diversity (gamma-diversity) estimates derived from 16S rRNA gene sequencing of 1) individually sequenced specimens vs. 2) pooled specimens collected from a community. Pool sizes of 10, 20, and 40 are considered. We then compare the gamma-estimates using Pearson{\textquoteright}s correlation as well as using Bland and Altman agreement analysis for three established diversity indices including richness, Simpson{\textquoteright}s and Shannon{\textquoteright}s.

RESULTS: The gamma-diversity estimates are highly correlated, with most being statistically significant. All correlations between all three diversity estimates are significant in the 10-pooled data. Pools comprising 40 specimens are closest to the line of agreement, but all pooled samples and individual samples fall within the 95\% limits of agreement.

CONCLUSIONS: Pooling microbiome samples before DNA amplification and metagenomics sequencing to estimate community-level diversity is a viable measure to consider in population-level association research studies.

}, keywords = {Administration, Oral, Anti-Bacterial Agents, Azithromycin, Bacteria, Biodiversity, Child, Preschool, Female, Gastrointestinal Microbiome, Gastrointestinal Tract, High-Throughput Nucleotide Sequencing, Humans, Infant, Infant, Newborn, Male, Metagenomics, Microbiota, Niger, Placebos, RNA, Ribosomal, 16S, Sequence Analysis, DNA}, issn = {1873-2585}, doi = {10.1016/j.annepidem.2019.09.002}, author = {Ray, Kathryn J and Cotter, Sun Y and Arzika, Ahmed M and Kim, Jessica and Boubacar, Nameywa and Zhou, Zhaoxia and Zhong, Lina and Porco, Travis C and Keenan, Jeremy D and Lietman, Thomas M and Doan, Thuy} } @article {226, title = {Diversity of Chlamydia trachomatis in Trachoma-Hyperendemic Communities Treated With Azithromycin.}, journal = {Am J Epidemiol}, volume = {187}, year = {2018}, month = {2018 09 01}, pages = {1840-1845}, abstract = {

Prior studies have theorized that low chlamydial genetic diversity following mass azithromycin treatments for trachoma may create a population bottleneck that prevents the return of infection, but little empirical evidence exists to support this hypothesis. In this study, a single mass azithromycin distribution was administered to 21 communities in the Gurage Zone of Ethiopia in 2003. All children aged 1-5 years had conjunctival swabs performed before treatment and 2 and 6 months after treatment. All swabs positive for Chlamydia trachomatis at 2 months underwent typing of the gene encoding the major outer membrane protein (ompA) of C. trachomatis, as did the same number of swabs per community from the pretreatment and 6-month visits. Diversity of ompA types, expressed as the reciprocal of Simpson{\textquoteright}s index, was calculated for each community. In total, 15 ompA types belonging to the A and B genovars were identified. The mean diversity was 2.11 (95\% confidence interval: 1.79, 2.43) before treatment and 2.16 (95\% confidence interval: 1.76, 2.55) 2 months after treatment (P = 0.78, paired t test). Diversity of ompA was not associated with the prevalence of ocular chlamydia (P = 0.76) and did not predict subsequent changes in the prevalence of ocular chlamydia (P = 0.32). This study found no evidence to support the theory that ompA diversity is associated with transmission of ocular chlamydia.

}, keywords = {Anti-Bacterial Agents, Azithromycin, Bacterial Outer Membrane Proteins, Chlamydia trachomatis, Genetic Variation, Humans, Trachoma}, issn = {1476-6256}, doi = {10.1093/aje/kwy071}, author = {Chin, Stephanie A and Morberg, Daniel P and Alemayehu, Wondu and Melese, Muluken and Lakew, Takele and Chen, Michael C and Zhou, Zhaoxia and Doan, Thuy and Cevallos, Vicky and Lietman, Thomas M and Keenan, Jeremy D} } @article {276, title = {Gut Microbial Diversity in Antibiotic-Naive Children After Systemic Antibiotic Exposure: A Randomized Controlled Trial.}, journal = {Clin Infect Dis}, volume = {64}, year = {2017}, month = {2017 05 01}, pages = {1147-1153}, abstract = {

Background: Antibiotic exposure can alter the gut microbiome. We evaluate the effects of azithromycin on the gut microbiome diversity of children from an antibiotic-naive community in Niger.

Methods: A population-based sample of 80 children aged 1-60 months in the Dosso region of Niger was randomized to receive a single dose of either oral azithromycin or placebo. Fecal samples were collected immediately before treatment and 5 days after treatment for 16S rRNA gene sequencing. The prespecified outcome was α-diversity (inverse Simpson{\textquoteright}s α-diversity index), with secondary outcomes of β and γ Simpson{\textquoteright}s and Shannon{\textquoteright}s diversities.

Results: At 5 days after treatment, 40 children aged 1-60 months were analyzed in the azithromycin-treated group and 40 children in the placebo-treated group. Diversity of the gut microbiome was significantly lower in the treated group (inverse Simpson{\textquoteright}s α-diversity, 5.03; 95\% confidence interval [CI], 4.08-6.14) than in the placebo group (6.91; 95\% CI, 5.82-8.21; P = .03). Similarly, the Shannon{\textquoteright}s α-diversity was lower in the treated group (10.60; 95\% CI, 8.82-12.36) than the placebo group (15.42; 95\% CI, 13.24-17.80; P = .004). Simpson{\textquoteright}s community-level (γ) diversity decreased with azithromycin exposure from 17.72 (95\% CI, 13.80-20.21) to 10.10 (95\% CI, 7.80-11.40; P = .00008), although β-diversity was not significantly reduced (2.56, 95\% CI, 1.88-3.12; to 2.01, 95\% CI, 1.46-2.51; P = .26).

Conclusions: Oral administration of azithromycin definitively decreases the diversity of the gut microbiome of children in an antibiotic-naive community.

Clinical Trials Registration: NCT02048007.

}, keywords = {Administration, Oral, Anti-Bacterial Agents, Azithromycin, Bacteria, Biodiversity, Child, Preschool, Cluster Analysis, DNA, Ribosomal, Female, Gastrointestinal Microbiome, Gastrointestinal Tract, Humans, Infant, Male, Niger, Phylogeny, Placebos, RNA, Ribosomal, 16S, Sequence Analysis, DNA}, issn = {1537-6591}, doi = {10.1093/cid/cix141}, author = {Doan, Thuy and Arzika, Ahmed M and Ray, Kathryn J and Cotter, Sun Y and Kim, Jessica and Maliki, Ramatou and Zhong, Lina and Zhou, Zhaoxia and Porco, Travis C and Vanderschelden, Benjamin and Keenan, Jeremy D and Lietman, Thomas M} } @article {241, title = {Metagenomic DNA Sequencing for the Diagnosis of Intraocular Infections.}, journal = {Ophthalmology}, volume = {124}, year = {2017}, month = {2017 08}, pages = {1247-1248}, keywords = {Cytomegalovirus, Cytomegalovirus Infections, DNA, Protozoan, DNA, Viral, Eye Infections, Parasitic, Eye Infections, Viral, Herpes Simplex, Herpes Zoster Ophthalmicus, Herpesvirus 3, Human, Humans, Metagenomics, Polymerase Chain Reaction, Sensitivity and Specificity, Sequence Analysis, DNA, Simplexvirus, Toxoplasma, Toxoplasmosis, Ocular, Uveitis, Vitreous Body}, issn = {1549-4713}, doi = {10.1016/j.ophtha.2017.03.045}, author = {Doan, Thuy and Acharya, Nisha R and Pinsky, Benjamin A and Sahoo, Malaya K and Chow, Eric D and Banaei, Niaz and Budvytiene, Indre and Cevallos, Vicky and Zhong, Lina and Zhou, Zhaoxia and Lietman, Thomas M and DeRisi, Joseph L} }