Home Research Feeds Integrated analysis of gut microbiome and fecal metabolome reveals potential non-invasive biomarkers for early-stage silicosis

Integrated analysis of gut microbiome and fecal metabolome reveals potential non-invasive biomarkers for early-stage silicosisOriginal paper

Researched by:

  • Karen Pendergrass

Last Updated: 2026-07-04

Karen Pendergrass
Karen Pendergrass

Karen Pendergrass is a microbiome researcher specializing in microbiome-targeted interventions (MBTIs). She systematically analyzes scientific literature to identify microbial patterns, develop hypotheses, and validate interventions. As the founder of the Microbiome Signatures Database, she bridges microbiome research with clinical practice. In 2012, based on her own investigative research, she became the first documented case of FMT for Celiac Disease, four years before the first published case study.

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Location
China
Sample Site
Feces
Species
Homo sapiens

What was studied?

Researchers examined gut microbiome and fecal metabolome changes across silicosis stages, comparing 78 patients (stage I, II, III) with 30 matched healthy controls.

How was it studied?

The team ran 16S rRNA gene sequencing on fecal samples from all participants, then performed untargeted fecal metabolomics profiling specifically in stage I patients, identified as the critical point for microbial dysbiosis.

What did they find?

Silicosis patients showed altered beta diversity, with Proteobacteria progressively increasing and Bacteroidota declining across stages. Pantoea, Kluyvera, and unclassified Pasteurellaceae were enriched in stage I and remained altered in later stages. Stage I metabolomes were enriched in tyrosine, histidine, purine metabolism, and arginine biosynthesis pathways, and a Lactobacillus plus N-succinyl-2-amino-6-ketopimelate signature reached an AUC of 0.84 for distinguishing stage I from controls.

Why it matters

The findings position stage I as a key turning point for gut dysbiosis in silicosis and suggest combined microbe-metabolite signatures could serve as non-invasive biomarkers for early detection.

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