B1269 - Salivary microbiome as a sensor for dietary exposures and disease risk a next generation sequencing approach - 21/06/2012

B number: 
B1269
Principal applicant name: 
Dr Tom Gaunt (University of Bristol, UK)
Co-applicants: 
Dr Philip Guthrie (University of Bristol, UK), Prof George Davey Smith (University of Bristol, UK)
Title of project: 
Salivary microbiome as a ?sensor? for dietary exposures and disease risk: a next generation sequencing approach.
Proposal summary: 

Background: The human microbiome comprises the microbial community inhabiting the human body. The total number of unique genes represented by the microbiome is thought to be orders of magnitude greater than the content of the human genome [1]. The composition of the microbiome has high potential importance as both a marker for disease risk (eg gut microbiome and colorectal cancer risk [2]) and potentially as a modifiable risk factor for disease. This project will investigate the role of the salivary microbiome in health and disease and its potential as a measure of dietary exposures and disease risk.

Aims: (1) To measure the salivary microbiome in saliva samples from the ALSPAC cohort using next generation sequencing. (2) To explore the potential of using the salivary microbiome as a sensor for dietary composition. (3) To analyse salivary microbiome associations with health outcomes.

Hypotheses: (1) That salivary microbiome composition (both combination of species and relative proportions) responds to dietary composition. (2) That salivary microbiome composition may serve as a useful indicator of dietary composition for research purposes. (3) That salivary microbiome may serve as a marker of risk for diet-influenced health outcomes. (4) That salivary microbiome is itself a risk factor for oral/dental disease.

Exposure variables: Diet data (hypotheses 1, 2 & 3) and salivary microbiome (hypotheses 3 & 4). Outcome variables: Salivary microbiome (hypotheses 1 & 2), blood lipids & anthropometry (hypothesis 3) and variables on dental health (hypothesis 4). Potential confounding variables: Diet, genetic variants and medications.

Date proposal received: 
Thursday, 24 November, 2011
Date proposal approved: 
Thursday, 21 June, 2012
Keywords: 
Genetics, Nutrition
Primary keyword: