Oral Microbiome Stamp in Alzheimer's Disease

Abstract

Recent studies have suggested that periodontal disease and alterations in the oral microbiome may be associated with cognitive decline and Alzheimer's disease (AD) development. Here, we report a case-control study of oral microbiota diversity in AD patients compared to healthy seniors from Central Asia. We have characterized the bacterial taxonomic composition of the oral microbiome from AD patients (n = 64) compared to the healthy group (n = 71) using 16S ribosomal RNA sequencing. According to our results, the oral microbiome of AD has a higher microbial diversity, with an increase in Firmicutes and a decrease in Bacteroidetes in the AD group. LEfSe analysis showed specific differences at the genus level in both study groups. A region-based analysis of the oral microbiome compartment in AD was also performed, and specific differences were identified, along with the absence of differences in bacterial richness and on the functional side. Noteworthy findings demonstrated the decrease in periodontitis-associated bacteria in the AD group. Distinct differences were revealed in the distribution of metabolic pathways between the two study groups. Our study confirms that the oral microbiome is altered in AD. However, a comprehensive picture of the complete composition of the oral microbiome in patients with AD requires further investigation.

Keywords: 16S rRNA; Alzheimer’s disease; Kazakhstan population; metabolic pathways; microbiome; oral cavity; sequencing.

Figure 1

Diagram of the study design.

Figure 2

Oral microbiome compositional dissimilarities in AD and control groups: (a) median relative abundance of most abundant species; (b) median relative abundance of the top genera of most abundant phyla; Mann–Whitney U test; (c) α-diversity. Shannon and Chao1 indices. Number of observed OTUs and Faith phylogenetic diversity (pd). Mann–Whitney U test, with abs. Cliff’s delta effect size (normalized U statistic) ^a; (d) β-diversity. Principal coordinate analysis (PCoA) ordination based on the unweighted UniFrac (U-UniFrac) distance. ANOSIM R, PERMANOVA F with permutations; (e) LefSe bar plot, LDA < 2 at the genus level; (f) LefSe cladogram at the genus and species levels. * p ≤ 0.05, ** p ≤ 0.01. ^a Cliff’s delta quantifies how often values in one distribution are higher than in the second distribution.

Figure 3

Oral microbiome compositional dissimilarities in AD subgroups in Almaty and Astana regions: (a) median relative abundance of most abundant species; (b) median relative abundance of the top genera of most abundant phyla; Mann–Whitney U test; (c) α-diversity. Shannon and Chao1 indices. Number of observed OTUs and Faith phylogenetic diversity (pd). Mann–Whitney U test, with abs. Cliff’s delta (d_a) effect size (normalized U statistic); (d) β-diversity. Principal coordinate analysis (PCoA) ordination based on the unweighted UniFrac (U-UniFrac) distance. ANOSIM R, PERMANOVA F with permutations; (e) LefSe bar plot, LDA < 2 at the genus level; (f) LefSe cladogram at the genus and species levels. * p ≤ 0.05, **** p ≤ 0.0001.

Figure 4

Significant correlations between differentially abundant features in AD and control groups: (a) between taxa and clinical parameters; (b) between pathways and clinical parameters; (c) between taxa, pathways, clinical parameters, and MMSE. Sankey plot of significant correlations. (d) Scatter plot comparing TC levels and MMSE scores. Spearman’s ρ, p ≤ 0.05; TC = total cholesterol; LDL = low-density lipoprotein; ALT = alanine transaminase; TG = triglycerides; MMSE = Minimized Mental State Examination. For differentially abundant features, a group with a higher relative abundance is highlighted: in green, the relative abundance is higher in the control group, and in purple, it is higher in the AD group. * p ≤ 0.05, ** p ≤ 0.01.

Figure 5

Significant correlations between differentially abundant features in AD subgroups in the Almaty and Astana regions: (a) between taxa, MMSE, and e4 status; (b) between taxa and demographic parameters; (c) between taxa and pathways; (d) between taxa, family history of dementia (PFHDEM), and self-reported depression (PPASTHX) status. Spearman’s ρ, p ≤ 0.05 for continuous parameters. Point-biserial r, p ≤ 0.05, for binary-continuous pairs; MMSE = Minimized Mental State Examination; BMI = body mass index. For differentially abundant features, a group with a higher relative abundance is highlighted: in coral, the relative abundance is higher in the Almaty-AD group, and in gray, it is higher in the Astana-AD group. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001, **** p ≤ 0.0001.

Figure 6

Feature importance analysis of AD and control groups. (Left): First 20 taxa, ranked by estimated importance for discriminating between groups. (Upper right): Principal coordinate analysis (PCoA) ordination based on the top 20 important taxa. Bray–Curtis dissimilarity with ANOSIM and PERMANOVA tests. (Lower right): AUC-ROC curve reflecting the degree of separability between groups during validation. GB = gradient boosting; LR = logistic regression; LOO = leave-one-out cross-validation; AUC = area under the curve. AUC > 0.5 suggests group separation, whereas AUC = 1 indicates absolute separation. Group with higher median abundance is indicated by (↑) in green for control and in purple for AD. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001.