Signature of Alzheimer’s Disease in Intestinal Microbiome: Results From the AlzBiom Study

Frontiers in Neuroscience

Matthias H. J. Munk¹  Victoria Ruschil²  Iris Honold³  Stephan Müller³  Matthias Willmann⁴  Oliver Preische⁵  Christoph Laske⁵  Silke Peter⁶  Ulrich Schoppmeier⁶ 

[1] Department of Biology, Technische Universität Darmstadt, Darmstadt, Germany;Department of Neurology, Epileptology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany;Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany;Eurofins Medical Lab Gelsenkirchen, Gelsenkirchen, Germany;German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany;Institute of Medical Microbiology and Hygiene, University of Tübingen, Tübingen, Germany;Section for Dementia Research, Department of Psychiatry and Psychotherapy, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany;

关键词: Alzheimer’s disease;    intestinal microbiome;    taxonomic data;    functional data;    ensemble learning;   

DOI  :  10.3389/fnins.2022.792996

来源: DOAJ

【 摘 要 】

BackgroundChanges in intestinal microbiome composition have been described in animal models of Alzheimer’s disease (AD) and AD patients. Here we investigated how well taxonomic and functional intestinal microbiome data and their combination with clinical data can be used to discriminate between amyloid-positive AD patients and cognitively healthy elderly controls.MethodsIn the present study we investigated intestinal microbiome in 75 amyloid-positive AD patients and 100 cognitively healthy controls participating in the AlzBiom study. We randomly split the data into a training and a validation set. Intestinal microbiome was measured using shotgun metagenomics. Receiver operating characteristic (ROC) curve analysis was performed to examine the discriminatory ability of intestinal microbiome among diagnostic groups.ResultsThe best model for discrimination of amyloid-positive AD patients from healthy controls with taxonomic data was obtained analyzing 18 genera features, and yielded an area under the receiver operating characteristic curve (AUROC) of 0.76 in the training set and 0.61 in the validation set. The best models with functional data were obtained analyzing 17 GO (Gene Ontology) features with an AUROC of 0.81 in the training set and 0.75 in the validation set and 26 KO [Kyoto Encyclopedia of Genes and Genomes (KEGG) ortholog] features with an AUROC of 0.83 and 0.77, respectively. Using ensemble learning for these three models including a clinical model with the 4 parameters age, gender, BMI and ApoE yielded an AUROC of 0.92 in the training set and 0.80 in the validation set.DiscussionIn conclusion, we identified a specific Alzheimer signature in intestinal microbiome that can be used to discriminate amyloid-positive AD patients from healthy controls. The diagnostic accuracy increases from taxonomic to functional data and is even better when combining taxonomic, functional and clinical models. Intestinal microbiome represents an innovative diagnostic supplement and a promising area for developing novel interventions against AD.

【 授权许可】

Unknown