Unique trans-kingdom microbiome structural and functional signatures predict cognitive decline in older adults

Abstract

The prevalence of age-related cognitive disorders/dementia is increasing, and effective prevention and treatment interventions are lacking due to an incomplete understanding of aging neuropathophysiology. Emerging evidence suggests that abnormalities in gut microbiome are linked with age-related cognitive decline and getting acceptance as one of the pillars of the Geroscience hypothesis. However, the potential clinical importance of gut microbiome abnormalities in predicting the risk of cognitive decline in older adults is unclear. Till now the majority of clinical studies were done using 16S rRNA sequencing which only accounts for analyzing bacterial abundance, while lacking an understanding of other crucial microbial kingdoms, such as viruses, fungi, archaea, and the functional profiling of the microbiome community. Utilizing data and samples of older adults with mild cognitive impairment (MCI; n = 23) and cognitively healthy controls (n = 25). Our whole-genome metagenomic sequencing revealed that the gut of older adults with MCI harbors a less diverse microbiome with a specific increase in total viruses and a decrease in bacterial abundance compared with controls. The virome, bacteriome, and microbial metabolic signatures were significantly distinct in subjects with MCI versus controls. Selected bacteriome signatures show high predictive potential of cognitive dysfunction than virome signatures while combining virome and metabolic signatures with bacteriome boosts the prediction power. Altogether, the results from our pilot study indicate that trans-kingdom microbiome signatures are significantly distinct in MCI gut compared with controls and may have utility for predicting the risk of developing cognitive decline and dementia- debilitating public health problems in older adults.

Keywords: Aging; Cognitive impairment; Gut microbiome; Gut-brain axis; MiaGB; Shotgun metagenomics.

Fig. 1

Trans-kingdom microbiome signatures significantly differ in the gut of older adults with mild cognitive impairment (MCI) compared with cognitively healthy controls. a) Bar plots depict the mean relative abundance of archaea, bacteria, fungi, and viruses in the gut microbiome of the participants with MCI and controls. b) Venn diagram depicting the presence of shared and unique microbial species of the archaea, bacteria, fungi, and viruses in the gut of older adults with MCI and controls

Fig. 2

The virome signature is significantly distinct in the gut of older adults with MCI compared with controls, with limited potential to predict cognitive health. a,b) The relative abundance of major viral families (a) and species (b) was distinct in the gut microbiome of older adults with MCI compared with controls. c) Heatmap depicting the clusters of increased and decreased abundance of viral species in the gut of older adults with MCI and controls. d) Random forest analysis (RFA) showing the top 15 viral species with the highest discriminatory power between MCI and control groups. Red color indicates high abundance, and blue indicates a low abundance of the particular viral species in MCI and control groups. (e) Receiver operating characteristic (ROC) curve plots represent the specificity and sensitivity of the five selected viral species for the two groups. (f) The Pearson correlation matrix shows the association between the relative abundance of selected 5 viral species with cognitive function measures such as MoCA and MiniCog. Abbreviations—Bacillus; Bc, Bacteroides; Ba, Clostridium; Cl, Enterobacteria; Eb, Enterococcus; Ec, Escherichia; Es, Klebsiella; Kl, Lactobacillus; Lb, Lactococcus; Lc, Pseudomonas; Ps, Salmonella; Sl, Streptococcus; St, Stx2 converting; Sc, Vibrio; Vi

Fig. 3

The bacteriome signatures in the gut of older adults with MCI significantly differ from cognitively healthy controls with a moderate predictive potential of cognitive health. a,b) The relative abundance of major bacterial phyla (b) and species (b) in the gut of the older adults with MCI in comparison to controls. (c) Heatmap depicting the group-specific enrichment of the bacterial species in the gut of older adults with MCI and controls. (d) Random forest analysis showing the top 15 bacterial species with the highest discriminatory power between the control and MCI groups. (e) ROC analyses of selected bacterial species to predict the cognitive health in older adults. (f) Correlation matrix showing the association between the relative abundance of selected bacterial species with MoCA and Mini-Cog. Abbreviations—Acidaminococcus; Ac, Akkermansia; Ak, Alistipes; Al, Anaerostipes; An, Bacteroides; Ba, Bifidobacterium; Bi, Blautia; Bl, Clostridium; Cl, Collinsella; Co, Dorea; Do, Escherichia; Es, Eubacterium; Eu, Faecalibacterium; Fa, Firmicutes; Fi, Fusicatenibacter; Fb, Fusicatenibacter; Fu, Lachnospiraceae; Ls, Lawsonibacter; La, Parabacteroides; Pb, Prevotella; Pr, Roseburia; Rb, Ruminococcus; Ru, Streptococcus; St, Subdoligranulum; Su, Tyzzerella; Ty

Fig. 4

The functional metabolic pathways of the microbiome in the gut of older adults with MCI were significantly distinct from their controls with a moderate predictive potential of cognition. a) Venn diagram representing the shared and unique microbial metabolic pathways in the gut of older adults with MCI compared to their controls. b) The relative abundance of the top 20 microbial metabolic pathways that are distinct between older adults with MCI and controls. c) Heatmap representing the group-specific enrichment of the pathways in the control and MCI participants. d) Random forest analysis showing the top 15 pathways with the highest discriminatory power between the control and MCI groups (e) ROC analysis showing the specificity and sensitivity of the four selected pathways with discriminating potential between MCI anda controls (f) Correlation matrix showing the association of the relative abundance of microbiome functional pathways with MoCA and Mini-Cog. Abbreviations—5-Aminoimidazole Ribonucleotide Biosynthesis I; 5-ARB, Acetylmuramoyl-pentapeptide; AP, Adenine and Adenosine; A&A, Biosynthesis; B, Building Blocks Biosynthesis; BB B, Corismate biosynthesis from 3-dehydroquinate; CB from 3DQ, Coenzyme A; CoA, Degradation; Guanosine ribonucleotides; GR, L-homoserine and L-methionine; LH and LM, Rhamnose; R, Tricaboxylic Cycle; TCA, Uridine 5'-monophosphate; UMP

Fig. 5

The combination of bacteriome, virome, and microbial metabolic pathways improves the prediction of cognitive health in older adults. a–c) ROC analyses depicting prediction model 1 (a), 2 (b), and 3 (c) with a distinct combination of bacteriome, virome, and microbial metabolic pathways to predict the cognitive health of older adults