16S rRNA sequencing of stool samples from patients with mild cognitive impairment

Accumulating evidence suggests a link between gut microbiota/metabolomics, mild cognitive impairment (MCI) and Alzheimer's disease (AD); however, it remains unknown whether changes in the gut microbiota and metabolite profiles can aid diagnosis and prediction of progression in MCI. Given the urgent need for better and simpler biomarkers for diagnosis and prognosis in people presenting with MCI, we explored whether alterations in faecal microbiome could be used for this purpose. We comprehensively characterized gut microbiota profiles in faeces samples from 35 individuals (17 cognitively healthy, 18 with MCI), including 16 husband/wife pairs where one partner had MCI. For MCI cases, cognition was assessed at study entry and at one year. The composition and relative abundance of the microbiota were compared between MCI and controls at study entry. Machine learning models were developed based on abundances of different bacterial genera at baseline to differentiate cases from controls and to predict progression of their cognitive impairment at one year.