The goals of this clinical study are: 1. Survey approximately 600 persons between the ages of 18-80 regarding their medical history \& oral hygiene habits, diet \& exercise habits, and emotional \& physical stressors to understand the barriers this population may face in achieving or maintaining good oral care and whole body health. 2. Compare the survey results with the organic molecule data collected by oral swabs from each subject at three different time points over the course of their 60 day study participation to better understand how behaviors and medical history relate to oral and whole body health. 3. Assess the effectiveness of two marketed oral hygiene study products vs a control on oral microbiome--such as bacteria, fungi, viruses that live naturally in our body-as well as its impact on the oral microbiome of each subject. The study products used in this study are 1 marketed oral lozenge, 1 marketed water additive.
This clinical study had four objectives: 1. To survey 600 volunteers, representative of the Minneapolis / St. Paul population, for their (i) medical history and oral hygiene habits, (ii) diet and exercise habits, and (iii) emotional and physical stressors, to understand what impediments this subpopulation may face in attaining and maintaining good oral and systemic health. The culmination of this work will enable us to evaluate the population, and to better understand and inform us on how to potentially address oral and systemic health for this population, and its extrapolation into the larger Minnesota population. 2. To compare survey results to metabolomic, metagenomic and immune marker data to provide an improved understanding of the relationship between behaviors and medical history with sophisticated biomarkers in a representative Minneapolis / St. Paul population. The culmination of this work will enable us to begin to understand the public health and disease risk profiles for this population and its extrapolation into the larger Minnesota population. 3. To quantitatively assess, using multi-marker (metabolic, microbiome and immune) analyses, the effects of a dental lozenge and a drinking water additive on study participants' biomarkers versus control (no intervention). The culmination of this work will enable us to evaluate two potential options for a daily oral supplement and its modulation of the oral microbiome compared to a control cohort. 4. To assess, using multi-marker (metabolic, microbiome and immune) analyses, the effects between a dental lozenge and a drinking water additive on study participants' biomarkers. The culmination of this work will enable us to determine the best option for a daily oral health supplement and its modulation of the oral microbiome. The study was designed as an 8-week, double blinded trial comprising 60 days of product usage, targeting a maximum of 600 male and female participants aged 18-80. Recruitment focused on individuals from the Minneapolis-St. Paul metro area who met the specified Inclusion and Exclusion criteria. Upon arrival at the Enrollment visit, subjects underwent informed consent procedures, including engaging in an individual discussion about the study's design and associated risks, and confirmation of study eligibility. Participants not meeting key inclusion and exclusion criteria were excluded at this stage. During this visit, participants completed a questionnaire regarding their medical and dental history. Eligible participants were then randomly assigned to one of three cohorts: a control group without an assigned oral supplement, a dental lozenge, or a drinking water additive . Following randomization, participants were instructed to either take no action, take 2 oral lozenges 4 times a day, or consume a water additive twice daily. A qualified technician collected five oral swabs from each participant using the specified technique. Swabbing involved gentle strokes along the gum line on both the right and left sides (top and bottom), as well as resting the swab along the lower right gum line for 5-30 seconds. Participants returned to the clinical site at week 4 (Visit 2) and week 8 (Visit 3) for further assessments, including questionnaires at week 4 on diet and exercise history, and at week 8 on environmental and lifestyle stressors history. Additional swab collections of five swabs each were also conducted at these visits.
Study Type
INTERVENTIONAL
Allocation
RANDOMIZED
Purpose
BASIC_SCIENCE
Masking
TRIPLE
Enrollment
595
dissolvable mint flavored pHossident lozenges containing ingredients that are all FDA-approved with the GRAS (Generally Recognized As Safe) designation, and have years of safety demonstrated in animals, children, adults and pregnant women. The lozenge is not classified as a drug and is regulated as a nutritional supplement. The lozenge does contain the sugar substitutes called mannitol and sorbitol (sugar alcohols), as well as the natural sweetener, stevia, all of which can irritate the lower gastrointestinal tract at amounts that grossly exceed the levels that are contained in the lozenges (I lozenge contains \<l % of the recommended daily intake).
Commercially marketed over-the-counter Protektin drinking water additive contains ingredients that are all FDA-approved with the GRAS designation, and have years of safety demonstrated in animals, children, adults and pregnant women. The water additive is not classified as a drug and is regulated as a nutritional supplement. The water additive only contains active ingredients; it does not contain fillers, flavors or sweeteners.
Comprehensive Research Group
Minneapolis, Minnesota, United States
Metagenomic changes at 4 and 8 weeks from baseline in pHossident lozenge recipients vs Protektin water additive recipients vs control participants using shotgun sequencing of salivary DNA isolates sequencing depth of 35.4M read pairs per sample.
Shotgun sequencing (Illumina NovaSeq X, 2x150bp) of salivary DNA isolates using a sequencing depth of 35.4M read pairs per sample. Data processing through Cmbio Human Microbiome Profiler for taxonomic and functional profiling. Significance determination using the Student's t-test and FDR values for differential abundance across cohorts and over time. Changes in microbial metagenome with focus on the levels of specific commensal species and pathogen species are measured by copy number of specific genomic sequences in a sample relative to the total. High resolution taxonomic profiling will be used to identify species and strains and their relative abundance in a patient sample and how that abundance changes over time and between treatment groups for each microbial species. Anticipate decreases in pathogen species in treatment groups vs control. Units of measurement = # of genome copies and % abundance in the sample.
Time frame: Initial visit: baseline measurements to 8 week endpoint measurements
Metabolomic changes at 4 and 8 weeks from baseline in pHossident lozenge vs Protektin water additive recipients vs control using metabolite profiling of oral swab samples with UHPLC-Orbitrap MS.
Changes in oral metabolome, ie, the levels of specific metabolites that are measured by peak analyses derived from retention time and fragmentation compared to reference standards obtained from samples and measured using ultra-high pressure liquid chromatography-Orbitrap Mass Spectrometry. High resolution data are normalized for biological and sample variation and processed using Systematic Error Removal using Random Forest (SERRF). Probabalistic quotient normalization will be used to address dilution effects and concentration variability in the metabolomics dataset. Principal component analysis will be used to examine statistical patterns of metabolites within a group and across groups. Score plots will be used to show clustering of patient samples that are similar for each metabolite. Units of measurement = untransformed probailistic quotient normalized (PQN) peak areas of each metabolite, and power-transformed PQN peak areas.
Time frame: Baseline time point to week 8 endpoint.
Inflammation-related Analysis
Inflammation-related protein biomarker (IL-6, MMP-8, MMP-13) levels and their changes at 4 and 8 weeks from baseline in pHossident lozenge vs Protektin water additive recipients vs control is examined. Oral swab samples are collected and biomarkers are measured using standard curves of recombinant protein biomarker in the enzyme-linked immunosorbent assays (ELISA) specific to each protein biomarker. Significance is determined using the Student's t-test in each cohort over time and across cohorts at each time point. Units of measurement = micrograms/mL levels of each protein biomarker in a sample.
Time frame: Baseline time point to endpoint 8 week time point.
Inter-omics correlations
The purpose of this analysis is to answer the question: Does the intervention (lozenge or water additive) have a common co-varying effect across the metagenome, metabolome and/or the immunological marker(s)? Additionally, to identify statistically significant correlational relationships between species withing the metagenome, metabolites and inflammation biomarkers. Analyses will be conducted with regards to change from baseline in response to the intervention and compared to the control cohort. Additional analyses will be conducted to examine the differences in the metagenome, metabolome and/or immune markers between pHossident vs Protektin treatment groups. Machine learning prediction models will be used to assess association between datasets. False discovery rate (FDR) and P-values will be assessed using the Benjamini-Hochberg method. All statistical analyses will be performed in R version 4.4.2. Units of measurement = Relative abundance, unit variance, intensity in heat maps.
Time frame: Baseline to 8 week endpoint.
Exploratory baseline analyses
* Observational inspection of the oral metagenome and metabolome in the study population. * Analysis of the questionnaire data with respect to general physical health, dental hygiene, diet, mental health and exercise habits in the study population. * Analysis of the inflammation protein biomarkers MMP-8, MMP-13 and IL-6 levels in the study population. * Correlation analyses, cluster analysis, of the relationship in these meta-data and multi-omic data using machine learning to assess R-squared to test ordinal variables. Statistical analysis using R. Units of measurements = intensity, relative abundance, unit score will be presented in heat maps to show strength and type of correlation.
Time frame: Baseline
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