The two purposes of this study were to develop a sample preparation and analysis pipeline to assess the oral microbiome using high throughput DNA sequencing, and to expand an ongoing study on the relationship between oral health and cognitive function in older West Virginians.
The major advantage of the Illumina platform is its capacity to generate millions of reads from each sample. Because of the relatively short read lengths, care must be used in choosing an appropriate region of the 16S RNA gene for analysis using the Illumina platform. The V3 region was selected because the primers used are the same as those used for older methods of bacterial community analysis, and this region had been used previously in Illumina-based analysis of microbial communities from environmental samples . The region amplified in this study is longer (170 to 190 bases) than the V6 region (105 to 120 bases)  or the V5 region (approximately 82 bases)  sequenced in other studies. Using the PCR primers described in Bartram et al.  it was possible to run up to 12 samples per sequencing lane in this study, thereby substantially reducing the cost of the analysis. However, a challenge to using this system for microbiome analysis is the relatively short read lengths that are typically generated in a run (approximately 125 bp) and the lower quality of many of these reads. These disadvantages are obviated by using a paired-end sequencing approach, and successful microbiome analyses of various environmental niches  including the oral cavity [18, 31] have been documented. Furthermore, recent additions to the QIIME program have streamlined analysis of Illumina-generated data. We used the Greengenes database to identify the taxa corresponding to our sequences. About 5% of our sequences were not found in Greengenes; we believe that most of these are artifacts, but it is possible that a small number of rare OTUs could have been excluded, which limits the utility of this approach for identifying very rare phylotypes with a high level of confidence. Nevertheless, we successfully obtained millions of sequences from each sample, yielding profound details of the structure of the microbiome in subgingival plaque.
Although the main goal of this pilot study was to work out methods for obtaining high quality data and performing subsequent analysis using validated, universally available software and databases, two interesting observations were made during the phylogenetic analysis of the data. First, a very high level of Fusobacteria was found, particularly in the samples from normal and CIND participants. Fusobacteria are well-studied anaerobes that have been found with great frequency in the oral cavity using culture-independent analyses [32–35], and members of the genus Fusobacterium were previously found to be among the most commonly identified species in the oral cavities of elderly patients [34, 35], particularly in association with root caries . A second novel observation was that the levels of Fusobacteriaceae were lower, and that levels of Prevotellaceae were higher in samples from subjects with dementia compared to subjects without dementia. We had hundreds of taxa in our results, so by chance some of them would likely appear to be correlated with dementia. However, Prevotellaceae and Fusobacteriaceae are the two most abundant families of bacteria, and antibody levels to individual species in those families have been shown to increase to higher levels in people who develop dementia than in those who do not .
There are four possible explanations for the correlations between dementia and components of the microbiome: 1) the correlations are spurious due to the small sample size; 2) dementia affects the microbiome; 3) the microbiome affects dementia; and 4) a third variable affects both.
First, we acknowledge that the sample size is small and that many more subjects need to be evaluated to obtain a robust result. Whether a larger sample size will confirm these preliminary observations is an open question.
Second, it might seem self-evident that individuals with dementia have poor oral hygiene resulting from changes in diet or oral hygiene behavior, and therefore worse oral health than individuals without dementia. As expected, the participants with dementia in this study had on average, slightly more gingivitis, fewer teeth, more caries, and much higher plaque indices. However, while this is true on average, it was not always the case on an individual basis. Participant Normal 2 had poor oral health while participants Dementia 1 and Dementia 5 had relatively good oral health, albeit with fewer teeth. Participant Dementia 2 had the highest number of teeth of all those in the study. If dementia causes poor oral health, which in turn causes the changes in the microbiome, then the correlations between the directly related parameters (cognition and oral health, or oral health and the microbiome) should be higher than the correlation between the indirectly related parameters (cognition and the microbiome). Since we found the opposite, the data do not support the hypothesis that the observed differences are merely secondary effects of poor oral hygiene in subjects with dementia.
We found more Prevotella on average in the samples from participants with dementia than in the samples from participants without dementia. However, the difference was not large and the statistical significance of that finding was dependent on the statistical test used to analyze the data. The number of Prevotellaceae phylotypes was high in both groups of samples, supporting many previous studies that showed diversity in Prevotellaceae phylotypes/species in the oral cavity . In addition, there was a slight but statistically significant increase in the number of distinct OTUs in the dementia samples compared to the non-dementia samples, raising the question of whether there are phylotypes in the Prevotellaceae that contribute to dementia. At the species and strain levels there are examples of specific genes that could potentially contribute to virulence within the Prevotellaceae family including genes that encode fimbrial adhesins, phospholipases, host-resistance factors, adenine-specific DNA-methyltransferase and 8-amino-7-oxononanoate synthase [36, 37]. Species-specific insertion sequences have also been identified , but whether these or other genes are disproportionately expressed in dementia patients and play a role in disease awaits metagenomic analyses. There were no other predominant phylotypes found in higher levels in participants with dementia compared to non-dementia, arguing against the idea that the presence of certain bacteria promotes dementia. However, the fact that higher levels of Fusobacteriaceae were found in all samples from participants without dementia suggests an alternate explanation, that perhaps certain oral bacteria provide protection against dementia, possibly by filling environmental niches that could be populated by more inflammatory microorganisms, by actively suppressing local or systemic inflammatory responses, or by producing biomolecules that are neuroprotective.
The final possibility is that both dementia and the microbiome are affected by a third variable. There is a strong genetic link to some forms of dementia, including the presence of the APOE-e4 variant of the Apolipoprotein E gene . It is possible that the presence or absence of specific taxa could be due to genetic factors in the subject such as host immune responses, expression of adhesion molecules on host tissues that affect bacterial adherence, or other undefined factors. The relationship between human genotype and the oral microbiome needs to be studied carefully.
Sparks Stein et al.  found elevated levels of antibodies to Prevotella intermedia and Fusobacterium nucleatum in the blood of subjects who later developed AD. These investigators also found that subjects with Mild Cognitive Impairment (MCI), unlike AD subjects, had no differences in P. intermedia and F. nucleatum compared to normal subjects, but had reduced levels of antibodies to several other oral bacteria. Similarly, we found that our normal and CIND subjects did not separate based on their microbiome beta diversity and, in particular, that their Prevotellaceae and Fusobacteriaceae were similar. We hypothesize that our results can be reconciled with those of Sparks Stein et al. by predicting that subjects who will develop dementia have a leakier sub-gingival compartment resulting in increased interaction between the microbiome and the immune system, leading to higher antibody levels to the most prevalent bacteria: Fusobacterium and Prevotella. Compared to Prevotella, Fusobacteria are much less genetically diverse at the 16S gene, so they might be more sensitive to elevated serum antibody levels because of less diversity of surface proteins that could serve as targets for antibodies. Thus, later in life one might predict that higher levels of antibody might reduce levels of Fusobacteria yet fail to be as effective against genetically diverse Prevotella. Alternatively, it is possible that the difference in findings for Fusobacteriaceae might be because Sparks Stein et al. were using antibodies that would differentiate strains on the basis of surface proteins while we used 16S ribosomal sequences.
In summary, our results demonstrate, via high throughput DNA sequencing, that substantial inter-person variability exists in the oral microbiome of subgingival plaque. There appears to be a consistent difference in the levels of Fusobacteriaceae, and perhaps Prevotellaceae, in samples from patients who do or do not have dementia, which should be studied in more detail.