Gut Microbiome Alterations in Mild Cognitive Impairment: Findings from the ALBION Greek Cohort

Identificador:  imarina:9466770

Handle: https://hdl.handle.net/20.500.11797/imarina9466770

Autores:  Rouskas, K; Mamalaki, E; Ntanasi, E; Pantoura, M; Anezaki, M; Emmanouil, C; Novau-Ferre, N; Bulló, M; Dimas, AS; Papandreou, C; Yannakoulia, M; Argiriou, A; Scarmeas, N

Resumen:
Emerging evidence suggests a potential role of gut dysbiosis in neurodegenerative disorders and, in particular, Alzheimer's disease (AD) pathology and cognitive decline. However, the role of gut microbiome in the early prodromal stages of AD and particularly in mild cognitive impairment (MCI) remains understudied and has been mostly explored in Asian populations with no representation of European populations. To address this research gap in the literature and to suggest novel microbiome features associated with MCI, we conducted a cross-sectional study in a European population sample and profiled gut microbiota in 99 individuals without dementia through 16s ribosomal RNA (rRNA) sequencing. Individuals were categorized by cognitive status based on standard clinical criteria to cognitively normal (n = 49) or individuals with MCI (n = 50). Differential abundance through Microbiome Multivariable Associations with Linear model (MaAsLin2) and elastic net logistic regression analyses were used to identify gut microbiome features associated with MCI. MCI group was older than the CN group and age was used as covariate in the differential abundance analysis. No differences in alpha and beta diversity were found between the two groups (p > 0.05). At false discovery rate (FDR) < 0.05, we identified specific genera associated with MCI, mostly linked to short chain fatty acids (SCFAs) production (e.g., Candidatus_Soleaferrea q = 0.027, MaAsLin2 coefficient = 1.65, Sellimonas q = 0.017, MaAsLin2 coefficient = -4.45), while we highlight nominal (p < 0.05, q > 0.05) correlations of genera (e.g., Hydrogenoanaerobacterium, Subdoligranulum) with metrics of cognitive assessment. Microbiota was shown to have a fairly good discriminative capacity for MCI status (area under the curve AUC = 0.77), with Rothia genus found as the top predictor for MCI (beta coefficient [95% confidence intervals] = 0.224 [0.216-0.233]). Overall, our findings add to current knowledge reporting gut microbiome alterations in MCI by suggesting novel associated microbiome features; however, larger scale longitudinal studies are needed to further elucidate the underlying biological pathways linked to the disease.