Altered microbiomes distinguish Alzheimer’s disease from amnestic mild cognitive impairment and health in a Chinese cohort
Notice bibliographique
Résumé
OBJECTIVE: (Background): Alzheimer's disease (AD), clinically characterized by the progressive neurodegenerative condition and cognitive impairment, is one of the main causes of disability in elder people worldwide. Recently, several animal studies indicated that the 'gut-brain' axis might contribute to the amyloid deposition of AD. However, data about gut dysbiosis in human AD remains scarce in the literature, especially including the whole process of AD. In this prospective and cross-sectional study, we aimed at identifying differences in microbiome between patients with AD (Pre-onset stage amnestic mild cognitive impairment, aMCI; and AD) and the normal cognition healthy controls (HC). Additionally, the potential association between IM and clinical characteristics of AD was evaluated. METHODS: A total of 97 subjects (33 AD, 32 aMCI, and 32 HC) were recruited in the study. The composition of gut bacterial communities was determined by 16S ribosomal RNA Miseq sequencing. In addition, Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was used to predict function shift of intestinal microbiota. The Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA) or Clinical Dementia Rating (CDR) scores were used to evaluate the severity of cognitive impairment in patients. RESULTS: The fecal microbial diversity was decreased in AD patients compared with aMCI patients and HC. And the microbial composition was distinct among aMCI, AD and healthy control groups. Among bacterial taxa, the proportion of phylum Firmicutes was significantly reduced (P = 0.008), whereas Proteobacteria (P = 0.024) was highly enriched in the AD compared with HC. In addition, similar alterations were observed at the order, class and family levels of these two phyla. And Gammaproteobacteria, Enterobacteriales and Enterobacteriaceae showed a progressive enriched prevalence from HC to aMCI and AD patients. Further, a significant correlation was observed between the clinical severity scores of AD patients and the abundance of altered microbiomes. Moreover, the KEGG results showed the increased modules related to glycan biosynthesis and metabolism in AD and aMCI patients and decreased pathways related to immune system in AD patients. Importantly, the discriminating models based on predominant microbiota could effectively distinguish aMCI and AD from HC (AUC = 0.890, 0.940, respectively), and also AD from aMCI (AUC = 0.925). Notably, the models based on the abundance of family Enterobacteriaceae could distinguish AD from both aMCI (AUC = 0.688) and HC (AUC = 0.698). CONCLUSIONS: Distinct microbial communities, especially enriched Enterobacteriaceae, were associated with patients with AD when compared with predementia stage aMCI and healthy subjects. These novel findings will give new clues to understand the disease and provide new therapeutic target for intervention or a marker for this disease.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».