Gut Microbiome

Exploratory Metabolomic and Metagenomic Profiling of Fecal Samples in Isolated REM Sleep Behavior Disorder.

TL;DR

In this exploratory cross-sectional study of 21 iRBD patients and 15 healthy controls, integrated fecal metabolomics and 16S microbiome profiling identified candidate signatures of a shift toward proteolytic fermentation, reduced tryptophan-indole metabolism, bile acid depletion, and altered microbiota that discriminated iRBD from controls (84.8% cross-validated accuracy), but these findings are hypothesis-generating given the limited sample size.

Key Findings

Linear short-chain fatty acids were preserved in iRBD, whereas branched-chain fatty acids were selectively increased.

  • Short-chain fatty acids were quantified by targeted HS-SPME GC-EI-high-resolution MS.
  • The authors interpret the selective rise in branched-chain fatty acids as indicating a shift toward proteolytic fermentation.
  • The cohort comprised 21 iRBD patients and 15 healthy controls.

Volatilomic profiling showed reduced indole and increased p-cresol and 2-octanone in iRBD feces.

  • Volatile compounds were profiled by untargeted HS-SPME GC-EI-high-resolution MS.
  • Reduced indole alongside increased p-cresol is consistent with the proteolytic shift described.

Untargeted LC-MS/MS of the non-volatile fraction showed attenuation of the tryptophan-indole axis, class-level bile acid depletion, and increased acylcarnitines in iRBD.

  • The tryptophan-indole attenuation paralleled the reduced volatile indole.
  • Bile acid depletion was observed at the class level.
  • Acylcarnitines were increased in iRBD patients relative to controls.

The gut microbiome of iRBD patients was depleted of Blautia and Faecalibacterium and enriched in Oscillospirales.

  • Microbial composition was characterized by 16S rRNA gene sequencing on the same fecal material used for metabolomics.

DIABLO multi-omics integration of metabolomic and microbial layers produced a host-microbe signature that discriminated iRBD patients from controls.

  • Cross-validated accuracy was 84.8% within this discovery cohort.
  • The integration combined the metabolomic datasets and 16S microbiome data.
  • The signature was described as coherent across layers.

The findings are exploratory and hypothesis-generating; the value of these signatures for predicting phenoconversion remains unestablished.

  • The study was cross-sectional with a small sample (21 iRBD, 15 controls).
  • Prospective studies are needed to test prediction of phenoconversion to α-synucleinopathies.
  • The study is framed within the body-first (gut-first) model of α-synuclein pathology.

What This Means

Isolated REM sleep behavior disorder (iRBD), in which people physically act out their dreams, is one of the strongest early warning signs of diseases like Parkinson's. Some theories suggest these diseases may start in the gut and travel to the brain, so the researchers looked at stool samples from 21 people with iRBD and 15 healthy controls. They measured chemicals in the stool and the types of bacteria present. People with iRBD showed signs that gut bacteria were fermenting more protein (higher branched-chain fatty acids and p-cresol) and lower levels of indole and related tryptophan-derived compounds. They also had lower bile acids, higher acylcarnitines, fewer Blautia and Faecalibacterium bacteria, and more Oscillospirales. Combining chemical and bacterial data, a statistical model separated patients from controls with about 85% cross-validated accuracy within this group. This research suggests there may be detectable gut-related differences in iRBD, but the study was small, cross-sectional, and exploratory, so the results are preliminary. It cannot show that gut changes cause disease or predict who will develop Parkinson's or related conditions; larger, long-term studies are needed.

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Citation

Ascari F, Baldelli L, Scicchitano D, Pellegrini C, Ravaioli F, De Fanti S, et al.. (2026). Exploratory Metabolomic and Metagenomic Profiling of Fecal Samples in Isolated REM Sleep Behavior Disorder.. Biomolecules. https://doi.org/10.3390/biom16101456