Date of Degree
Doctor of Philosophy (Ph.D.)
Epidemiology and Biostatistics
C. Mary Schooling
Bioinformatics | Epidemiology | Microbiology | Public Health
microbiome, epidemiology, metagenomics, reporting, antibiotics, causal inference, predictive modeling
I consider two key areas in the growing field of human microbiome research: improving the quality of study reporting and the impact of antibiotics on participants in human gut microbiome research studies. In the first chapter, a team of evaluators used the Strengthening the Organization and Reporting of Microbiome Studies (STORMS) checklist to assess recently published microbiome literature. I found moderate agreement and reliability between evaluators, identified several items in STORMS that could be improved, and confirmed that the STORMS checklist can serve as a tool for assessing the reporting quality of published microbiome study. The next chapter considers pre-exposure gut microbiome composition as a potential effect modifier of the relationship between antibiotics and post-exposure microbiome. In a cohort study of infants, I find that it does modify this relationship for several important bacterial taxa linked to infant development. The fourth chapter looks at four datasets comparing stool microbiome measurements recently following antibiotics exposure to unexposed controls and fits predictive models for recent antibiotics exposure in each dataset. The results are mixed with smaller, more controlled studies having excellent model results while models becoming worse in less controlled conditions. The implications of this dissertation for improving the rigor of human microbiome research are discussed.
Mirzayi, Chloe A., "Improving Microbiome Research Through Enhanced Reporting and Modeling the Effects of Antibiotic Usage" (2023). CUNY Academic Works.
Available for download on Sunday, May 18, 2025