Specific compositions of periodontal microbiota are associated with risk for the various forms of periodontitis. Serum antibody levels are considered as surrogate markers for the activity levels of periodontal microbiota, which represent the protein synthesis and inflammatory potential of the microbiota. The chronic trickling of periodontal microbiota into the bloodstream also elicits a low-grade systemic inflammation which has been suggested to increase the risk for several extra-oral diseases, such as atherosclerosis, rheumatoid arthritis, metabolic disorders, and neurodegenerative diseases, including cognitive impairment and Alzheimer's disease. Furthermore, our recent study using data from the Third National Health and Nutrition Examination Survey (NHANES III) indicated that specific compositions of periodontal microbiota, even without inducing clinically significant periodontitis, may have a significant impact on the risk for human disease and mortality, and that Porphyromonas gingivalis (P gingivalis) play a key role in the dysbiotic periodontal microbiota. In this proposal, we will collaborate with experts from related disciplines to test our hypothesis that the activity levels of specific periodontal microbiota/P gingivalis are associated with the occurrence of age-related macular degeneration (AMD). We will first use partial least squares (PLS) regression to identify specific patterns of 21 serum immunoglobulin G (IgG) levels for periodontal microbiota which are associated with the risk for AMD in a case-control study from a representative sample of the US population, the NHANES III. PLS is an important statistical method in bioinformatics and used to discover variables (i.e. specific patterns of IgG levels) that are not directly observed but are rather inferred from other observed variables (i.e. 21 individual IgG levels). Since our hypothesis is novel and no previous study in the topic has been done, it is possible that the observed associations between specific IgG patterns and AMD will be confounded in spite of adjusting for confounding variables. To further verify the associations, we will use complement factor H (CFH) genetic polymorphisms as an instrumental variable in our Mendelian randomization study. CFH genetic polymorphisms are a well-established risk factor for AMD. The Mendelian randomization approach is a novel epidemiologic study design that incorporates genetic information into traditional epidemiologic methods and addresses exposure-outcome relationships without many of the typical biases that impact the validity of traditional epidemiologic approaches. The Mendelian randomization approach is especially useful when a randomized trial is impossible. This project will serve as our first step toward our long-term objectives of understanding how the phenotypes (such as serological markers) and genotypes/strains (microbiome) of oral microbiota, together with the human genome and nutrition and other known risk factors, affect eye health. Since periodontitis is one of the most prevalent diseases in humans and AMD is the leading cause of blindness among elders, understanding the associations between periodontal microbiota and AMD may lead to new therapeutic and preventative strategies for AMD.

Public Health Relevance

A human being is an ecosystem, which consists of a human body (host) and trillions of microbes (microbiota). These microbes have significant implications on human health. In this multidisciplinary project, we will explore if the microbiota in the mouth may have an impact on our eye health.

Agency
National Institute of Health (NIH)
Institute
National Eye Institute (NEI)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21EY028209-01A1
Application #
9600238
Study Section
Special Emphasis Panel (ZEY1)
Program Officer
Mckie, George Ann
Project Start
2018-09-30
Project End
2020-08-31
Budget Start
2018-09-30
Budget End
2019-08-31
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Forsyth Institute
Department
Type
DUNS #
062190616
City
Cambridge
State
MA
Country
United States
Zip Code