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Updated: Oct 28, 2026

DeepOmicsAE: Representing Signaling Modules in Alzheimer's Disease with Deep Learning Analysis of Proteomics, Metabolomics, and Clinical Data
Published on: December 15, 2023
Integrated Genetic and Multi-Omic Analyses Reveal Oral Microbial Associations with Brain Structure and Alzheimer's
Yilin Liu1,2, Xing Feng3,4,5,6,7,8, Hongwei Dong1,2
1Department of Neurobiology, School of Basic Medical Sciences, Chongqing Medical University, Chongqing 400010, China.
Abstract:
Oral microbial dysbiosis is linked to systemic inflammatory, vascular, and metabolic perturbations, but species-level relationships with human brain structure remain poorly defined. Using two-sample Mendelian randomization, we mapped 438 of 439 oral species with genome-wide association study instruments to 1325 adult brain imaging-derived phenotypes. In total, 87 associations involving 51 taxa and 79 traits passed Benjamini-Hochberg correction across taxa within each imaging-derived phenotype. The childhood and metabolomic screens identified 196 nominal taxon-volume associations and 1118 candidate metabolite-linked paths, respectively, as exploratory findings. Spatial and single-nucleus transcriptomics localized candidate regional and cell-associated variation in brain-structure gene programs. In total, 35 taxa showed nominal genetic associations with Alzheimer's disease. Integration with full-length oral 16S ribosomal ribonucleic acid gene sequencing from a 51-participant case-control cohort prioritized Selenomonas infelix, Capnocytophaga granulosa, and Dialister pneumosintes. In a secondary exploratory analysis, the three-taxon salivary model incorporating educational attainment yielded a leave-one-out cross-validated area under the receiver operating characteristic curve of 0.843. This post-selection estimate is subject to optimism, and the model remains a proof of concept requiring independent external validation. This cross-scale atlas prioritizes microbial and anatomical targets and provides a translational foundation for mechanistic validation and non-invasive neurodegenerative risk markers.
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