Anne G Hoen, PhD
Associate Professor of Epidemiology
Associate Professor of Biomedical Data Science
Associate Professor of Microbiology and Immunology
Biomedical Data Science
Microbiology and Immunology
Molecular and Cellular Biology Graduate Programs
Quantitative Biomedical Sciences
Dartmouth-Hitchcock Medical Center
One Medical Center Drive
Lebanon NH 03756
Dr. Hoen's research focus is on the development of the microbiome in infants and children, and the associations between environmental and dietary exposures, the microbiome, and risk for infectious and other diseases. She has a broad interest in the predictors of disease risk and microbial colonization dynamics in human populations and the environment as reflected in microbial genetic sequence variation and health informatics streams over space and time. Interdisciplinary approaches used in her research include spatial and time-series statistics, population genetics and novel disease surveillance methodologies along with tools from the fields of microbial ecology, molecular epidemiology and landscape epidemiology.
Rotations and Thesis Projects
Development of novel computational methods for studying the human microbiota
Investigating the environmental drivers of infant intestinal microbiome development
Associations between patterns of infant intestinal microbiome establishment and health outcomes in children
Functional characterization of the developing infant gut microbiota using metabolomics
K01LM011985: Bioinformatics strategies for early life microbiomics
R01LM012723: Multi-omic functional integration using networks
QBS 136 Applied Epidemiologic Methods
Dr. Hoen completed her PhD in epidemiology and public health at Yale University and received post-doctoral training at Harvard Medical School. She has broad training in biostatistics, epidemiology and public health with research experience in the evaluation of interventions, understanding infectious disease emergence and spread, and evaluating associations between the microbiome and human health. Her research uses advanced statistical methods as well as informatics and complex systems approaches. Past studies include modeling the timing and spread of influenza to estimate the effects of interventions targeting children, modeling the evolutionary ecology of the Lyme disease agent, Borrelia burgdorferi and characterizing the initial development of the human microbiome in early life and its associations with common exposures and infectious outcomes.
Machine-learning analysis of cross-study samples according to the gut microbiome in 12 infant cohorts.
Human milk-associated bacterial communities associate with the infant gut microbiome over the first year of life.
Alterations in Microbial-Associated Fecal Metabolites in Relation to Arsenic Exposure Among Infants.
Umbilical cord blood immune cell profiles in relation to the infant gut microbiome.
Associations of maternal plasma and umbilical cord plasma metabolomics profiles with birth anthropometric measures.
The association between early life antibiotic exposure and the gut resistome of young children: a systematic review.
Metagenomic analysis reveals associations between salivary microbiota and body composition in early childhood.
The relationship between the gut microbiome and the risk of respiratory infections among newborns.
MarZIC: A Marginal Mediation Model for Zero-Inflated Compositional Mediators with Applications to Microbiome Data.
Bronchiolitis hospitalizations in rural New England: clues to disease prevention.