Intraplaque microbiome dynamics computationally associate with host transcriptomic alterations during carotid plaque evolution provides a hypothesis-generating framework linking microbial dysbiosis to plaque destabilization, offering novel mechanistic insights and highlighting the exploratory cross-kingdom biomarker panel as a highly promising foundation for future experimental validation and stage-tailored clinical diagnostics.
Abstract
Background: Carotid plaque rupture is a critical event in ischemic stroke, yet the potential involvement of the intraplaque microbiota across disease stages remains unclear. Methods: We performed dual-omics profiling by analyzing host transcriptomes and PathSeq-derived microbiomes from 48 human carotid RNA-seq specimens spanning early lesions (intimal thickening; n = 10), stable plaques (n = 20), and unstable plaques (n = 18). Host transcriptomes were profiled alongside intraplaque microbiomes extracted via the GATK PathSeq pipeline with rigorous in silico decontamination. We integrated differential expression analysis, microbial diversity metrics, and functional inference. Furthermore, an integrated machine learning approach (incorporating Boruta feature selection) was employed to identify exploratory cross-kingdom diagnostic biomarkers. Results: Microbial beta diversity diverged significantly across disease stages, accompanied by the progressive upregulation of 54 host genes critical for extracellular matrix remodeling and immune chemotaxis. Strikingly, despite the inherent noise and artifacts associated with low-biomass sequencing, we computationally detected the distinct enrichment of 21 bacterial taxa in unstable plaques, predominantly oral and gut mucosal pathobionts. Computationally inferred functional profiling revealed that these unstable plaque-associated microbiota were significantly linked to predicted cell death, IL-17, and HIF-1 signaling pathways and exhibited strong positive correlations with host matrix-degrading transcripts. Statistical modeling suggested associative links among specific microbial enrichment, host transcriptomic dysregulation, and plaque instability, highlighting concurrent biological cross-talk. Importantly, our integrated machine learning pipeline established a 14-feature cross-kingdom biomarker panel (10 host genes and 4 bacteria) that discriminated stable from unstable plaques (cross-validated AUC = 0.869). Conclusions: Intraplaque microbiome dynamics computationally associate with host transcriptomic alterations during carotid plaque evolution. This synergistic host–microbiome association provides a hypothesis-generating framework linking microbial dysbiosis to plaque destabilization, offering novel mechanistic insights and highlighting the exploratory cross-kingdom biomarker panel as a highly promising foundation for future experimental validation and stage-tailored clinical diagnostics.
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