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000278911 037__ $$aDZNE-2025-00637
000278911 041__ $$aEnglish
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000278911 1001_ $$aBauch, Anne$$b0
000278911 245__ $$aPrognostic Value of a Multivariate Gut Microbiome Model for Progression from Normal Cognition to Mild Cognitive Impairment Within 4 Years.
000278911 260__ $$aBasel$$bMolecular Diversity Preservation International$$c2025
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000278911 520__ $$aLittle is known about the dysbiosis of the gut microbiome in patients with mild cognitive impairment (MCI) potentially at risk for the development of Alzheimer's disease (AD). So far, only cross-sectional differences and not longitudinal changes and their prognostic significance have been in the scope of research in MCI. Therefore, we investigated the ability of longitudinal taxonomic and functional gut microbiome data from 100 healthy controls (HC) to predict the progression from normal cognition to MCI over a 4-year follow-up period (4yFU). Logistic regression models were built with baseline features that best discriminated between the two groups using an ANOVA-type statistical analysis. The best model for the discrimination of MCI converters was based on functional data using Gene Ontology (GO), which included 14 features. This model achieved an area under the receiver operating characteristic curve (AUROC) of 0.84 at baseline, 0.78 at the 1-year follow-up (1yFU), and 0.75 at 4yFU. This functional model outperformed the taxonomic model, which included 38 genera features, in terms of descriptive performance and showed comparable efficacy to combined analyses integrating functional, taxonomic, and clinical characteristics. Thus, gut microbiome algorithms have the potential to predict MCI conversion in HCs over a 4-year period, offering a promising innovative supplement for early AD identification.
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000278911 650_7 $$2Other$$aAlzheimer’s disease
000278911 650_7 $$2Other$$agut microbiome
000278911 650_7 $$2Other$$alongitudinal observational study
000278911 650_7 $$2Other$$amild cognitive impairment
000278911 650_7 $$2Other$$aprediction model
000278911 650_2 $$2MeSH$$aHumans
000278911 650_2 $$2MeSH$$aCognitive Dysfunction: microbiology
000278911 650_2 $$2MeSH$$aCognitive Dysfunction: diagnosis
000278911 650_2 $$2MeSH$$aGastrointestinal Microbiome
000278911 650_2 $$2MeSH$$aMale
000278911 650_2 $$2MeSH$$aFemale
000278911 650_2 $$2MeSH$$aPrognosis
000278911 650_2 $$2MeSH$$aDisease Progression
000278911 650_2 $$2MeSH$$aAged
000278911 650_2 $$2MeSH$$aCognition
000278911 650_2 $$2MeSH$$aAlzheimer Disease: microbiology
000278911 650_2 $$2MeSH$$aROC Curve
000278911 650_2 $$2MeSH$$aMiddle Aged
000278911 7001_ $$aBaur, Julia$$b1
000278911 7001_ $$aHonold, Iris$$b2
000278911 7001_ $$aWillmann, Matthias$$b3
000278911 7001_ $$aWeber, Greta Louise$$b4
000278911 7001_ $$0P:(DE-HGF)0$$aMüller, Stephan$$b5
000278911 7001_ $$0P:(DE-2719)9003152$$aSodenkamp, Sebastian$$b6$$udzne
000278911 7001_ $$aPeter, Silke$$b7
000278911 7001_ $$00009-0004-0769-6845$$aSchoppmeier, Ulrich$$b8
000278911 7001_ $$0P:(DE-2719)2000055$$aLaske, Christoph$$b9$$eLast author$$udzne
000278911 770__ $$aMolecular Research in Human Microbiome 2.0
000278911 773__ $$0PERI:(DE-600)2019364-6$$a10.3390/ijms26104735$$gVol. 26, no. 10, p. 4735 -$$n10$$p4735$$tInternational journal of molecular sciences$$v26$$x1422-0067$$y2025
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