This cross-scale atlas prioritizes microbial and anatomical targets and provides a translational foundation for mechanistic validation and non-invasive neurodegenerative risk markers.
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.
Background: Cellular heterogeneity limits causal inference in complex diseases. We applied an established cell-type-stratified Mendelian randomization (csMR) framework, originally developed by Hao et al. (2024), to investigate whether lipid phenotypes affect kidney disease through distinct brain cell populations, exten...
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Lu Zeng, Atlas Khan, Kathryn C. Fitzgerald et al.· Nature Genetics· 0 citations
These findings provide a cell-type-resolved and ancestry-aware atlas of genetically regulated expression in the human prefrontal cortex and illustrate how single-nucleus transcriptomics can sharpen gene discovery and therapeutic target prioritization for complex brain disorders.
S. Venkatesh, Roman Kosoy, Zhen-Yi Wu et al.· Nature· 7 citations
Findings potentially advance the translational understanding of the gut–brain metabolic axis in neurodegeneration and support the exploratory clinical utility of microbiota-linked peripheral metabolic signatures as non-invasive auxiliary diagnostic tools for AD, awaiting external validation in larger, multi-center coho...
Jiao Chen, Xu-Hui Chen, Weiwei Yu et al.· Frontiers in Pharmacology· 0 citations
Leveraging multi-omics to better understand the molecular signatures and pathways underlying Alzheimer’s disease (AD) pathogenesis is critical for early diagnosis and disease modifying interventions. We performed peripheral blood transcriptome (N = 669) and epigenome microarray analyses (N = 553) on non-Hispanic white...
Brendan A. Mitchell, I. Hausle, Sarah Smith et al.· npj Dementia· 0 citations
Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system characterized by demyelination disseminated in space and time. Here we performed a genome-wide association study (GWAS) using 688 MS cases and 205,199 controls from the Japanese population and identified significant associations in...
Rintaro Fujimoto, K. Ogawa, S. Namba et al.· Nature Genetics· 0 citations
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