Early childhood caries is the most common chronic disease of childhood and affects hundreds of millions of children worldwide. The condition can cause pain, difficulty eating, impaired learning and development, reduced quality of life, and significant health care costs for families and communities. Although highly prevalent, early childhood caries is largely preventable when children receive effective preventive care before disease develops.
Researchers in the University of Iowa College of Dentistry and Dental Clinics have received a new National Institutes of Health R01 award to better understand how early preventive interventions influence the oral microbiome and protect children from developing tooth decay.
The project, led by Erliang Zeng and Jeff Banas as multiple principal investigators, with Karin Weber-Gasparoni serving as co-investigator, will examine how microbial communities in the mouth change during early childhood and how those changes relate to behaviors, diet, caregiver knowledge, and future risk of tooth decay.
The new study builds upon an Karin Weber-Gasparoni’s ongoing NIH-supported clinical trial that uses a Self-Determination Theory (SDT)-based educational intervention to help caregivers adopt behaviors that support children's oral health. In that trial, researchers evaluate children's dental health outcomes while also tracking changes in caregiver knowledge, dietary practices, oral hygiene behaviors, dental plaque levels, and cariogenic bacteria.
While previous studies have identified individual bacteria associated with tooth decay, much less is known about how entire microbial communities respond to preventive interventions or how those changes interact with other risk factors over time. The Iowa research team aims to address that gap using advanced DNA sequencing and computational approaches to analyze the oral microbiome in children from birth through age three.
The project has two primary goals.
The first is to determine whether the SDT-based intervention helps maintain or restore a healthy oral microbiome that protects against tooth decay. Researchers will compare microbial communities among children who remain cavity-free and those who develop disease in both intervention and control groups. The team hopes to identify microbial patterns that are associated with successful prevention and long-term oral health.
The second goal is to understand how oral microbial communities interact with other factors known to influence childhood caries, including caregiver knowledge, dietary habits, oral health behaviors, and enamel health. By combining advanced statistical methods with machine learning approaches, investigators will identify which combinations of biological, behavioral, and environmental factors have the greatest impact on a child's risk for developing disease.
“Children's risk for tooth decay is influenced by a combination of microbial, behavioral, and environmental factors that interact in complex ways. Advanced statistical methods and machine learning allow us to uncover patterns across these data that would otherwise remain hidden. By identifying the factors most predictive of future disease, we hope to improve prevention strategies and help more children remain cavity-free,” said Erliang Zeng.
A central focus of the research is improving outcomes for children and families. Understanding the biological pathways through which preventive interventions work could help clinicians identify children at greatest risk earlier, personalize prevention strategies, and reduce the burden of dental disease before symptoms occur.
“Every child deserves the opportunity to grow up free from preventable dental disease. By understanding how healthy behaviors influence the oral microbiome during the earliest years of life, we hope to strengthen prevention strategies that can reduce pain, improve quality of life, and help children start school healthy and ready to learn,” said Weber-Gasparoni.
The investigators expect the study to identify key microbial signals associated with successful prevention and to generate new insights that can be used to strengthen future intervention programs. Ultimately, the findings may help oral health professionals and public health practitioners develop more effective approaches to preventing tooth decay during the earliest years of life, when prevention can have the greatest lifelong impact.
The research team brings together expertise in computational biology, oral microbiology, pediatric dentistry, and dental public health. Erliang Zeng is a professor in the Division of Biostatistics and Computational Biology at the University of Iowa and the Department of Preventive and Community Dentistry, and he directs the BioComs Lab (bioinformatics and computational systems biology laboratory). He also leads the project's computational and data science efforts. Jeff Banas is the associate dean for research at the University of Iowa College of Dentistry, and he contributes extensive expertise in oral microbiology and NIH-funded research. Karin Weber-Gasparoni is the Department Executive Officer and professor of Pediatric Dentistry at the University of Iowa, and she provides leadership in pediatric dentistry and community-based prevention research.
Research reported on this website is supported by the National Institute of Dental and Craniofacial Research of the National Institutes of Health under Award Number R01 DE033955-01A1. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.