IntroductionSeveral studies have reported alterations in gut microbiota composition of Alzheimer’s disease (AD) patients. However, the observed differences are not consistent across studies. We aimed to investigate associations between gut microbiota composition and AD biomarkers using machine learning models in patients with AD dementia, mild cognitive impairment (MCI) and subjective cognitive decline (SCD).Materials and MethodsWe included 170 patients from the Amsterdam Dementia Cohort, comprising 33 with AD dementia (66 ± 8 years, 46%F, mini-mental state examination (MMSE) 21[19-24]), 21 with MCI (64 ± 8 years, 43%F, MMSE 27[25-29]) and 116 with SCD (62 ± 8 years, 44%F, MMSE 29[28-30]). Fecal samples were collected and gut microbiome composition was determined using 16S rRNA sequencing. Biomarkers of AD included cerebrospinal fluid (CSF) amyloid-beta 1-42 (amyloid) and phosphorylated tau (p-tau), and MRI visual scores (medial temporal atrophy, global cortical atrophy, white matter hyperintensities). Associations between gut microbiota composition and dichotomized AD biomarkers were assessed with machine learning classification models. The two models with the highest area under the curve (AUC) were selected for logistic regression, to assess associations between the 20 best predicting microbes and the outcome measures from these machine learning models while adjusting for age, sex, BMI, diabetes, medication use, and MMSE.ResultsThe machine learning prediction for amyloid and p-tau from microbiota composition performed best with AUCs of 0.64 and 0.63. Highest ranked microbes included several short chain fatty acid (SCFA)-producing species. Higher abundance of [Clostridium] leptum and lower abundance of [Eubacterium] ventriosum group spp., Lachnospiraceae spp., Marvinbryantia spp., Monoglobus spp., [Ruminococcus] torques group spp., Roseburia hominis, and Christensenellaceae R-7 spp., was associated with higher odds of amyloid positivity. We found associations between lower abundance of Lachnospiraceae spp., Lachnoclostridium spp., Roseburia hominis and Bilophila wadsworthia and higher odds of positive p-tau status.ConclusionsGut microbiota composition was associated with amyloid and p-tau status. We extend on recent studies that observed associations between SCFA levels and AD CSF biomarkers by showing that lower abundances of SCFA-producing microbes were associated with higher odds of positive amyloid and p-tau status.

As malnutrition is common in patients with Alzheimer’s disease (AD), we evaluated nutritional status and body composition of patients with AD, mild cognitive impairment (MCI) and controls, and studied associations of AD biomarkers and cognitive performance with nutritional status and body composition. We included 552 participants, of which 198 patients had AD, 135 patients had MCI and 219 controls. We assessed nutritional status (mini nutritional assessment (MNA)) and body composition (body mass index (BMI), fat-free mass (FFM) and waist circumference). Linear regression analyses (adjusted for age, gender and education where appropriate) were applied to test associations of AD biomarkers and cognitive performance on five domains with nutritional parameters (dependent). Patients with MCI and AD had a lower BMI and MNA score than controls. Worse performance in all cognitive domains was associated with lower MNA score, but not with body composition. AD biomarkers were associated with MNA score, BMI and waist circumference, and associations with MNA score remained after adjustment for cognitive performance. Both AD biomarkers and cognitive performance were associated with nutritional status, associations with AD biomarkers remained after adjustment for cognition. Our data suggest that malnutrition is not only related to impaired cognition but also to AD pathology.

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