New Prototype Biomarker Distinguishes Gut Microbiota Disruptions


The prototype is being tested in clinical trials involving live microbiota therapeutics as a treatment for recurrent C difficile infections.

Ken Blount, PhD

Ken Blount, PhD

A new prototype biomarker can help identify potential human gut disruptions in patients with clostridium difficile infections (CDI) for post-antibiotic dysbiosis.

A team, led by Ken Blount, PhD, Chief Scientific Officer, Rebiotix, recently developed a prototype Microbiome Health Index for post-Antibiotic dysbiosis (MHI-A).

The Importance of Microbiome

It is well known how crucial the human gut microbiota is to health, with disrupted microbiota homeostasis often causing or contributing to gastrointestinal diseases. There are a number of factors in play here, but antibiotic treatment is the most notable.

Clinicians often can correct dysbiosis and restore healthier microbiota with a newer family of treatments called live biotherapeutic products, which are currently in clinical development programs.

However, biomarkers are needed to better guide and refine the development of these treatments. This could also help better inform the risk of antibiotic administration if the biomarkers distinguish post-antibiotic dysbiosis from the healthy microbiota.

Live Microbiota Therapeutics

In the study, the investigators examined longitudinal gut microbiome data from participants in a trio of clinical trials examining RBX2660 and RBX7455 as a live microbiota therapeutic being examined for the treatment recurrent CDI (rCDI).

The algorithm developed relates the relative abundances of microbiome taxonomic classes that changed the most following treatment, which correlated with clinical response and reflected biological mechanism important to rCDI.

The investigators used micr4obiome composition data from fecal samples collected from all 3 clinical trials. Each patient was asked to provide stool samples at baseline, as well as several time points following the initial treatment.

The team also used univariate logistic regression to test each class separately and estimate the probability a given sample is dysbiotic.

The investigators reinforced the diagnostic utility of MHI-A using available microbiome data from healthy or antibiotic-treated populations.

High Accuracy

The results show the tool is able to accurately distinguish post-antibiotic dysbiosis from healthy microbiota, with consistent values across multiple healthy populations. The values significantly shifted by antibiotic treatments known to alter microbiota compositions but shifted less by microbiota-sparing antibiotics.

In the RBX2660 data, MHI-A increased by an average of 87,000-fold from baseline to day 7, 33-fold from day 7 to day 30, and 4-fold from day 30-60.

In the placebo-treated arm, responders also showed MHI-A restoration, but the majority remained lower than 7.2 at all timepoints, with a median MHI-A significantly lower than RBX2660 responders at each timepoint (P < 0.05).

The investigators also analyzed the PUNCH Open Label trial of RBX2660 and a phase 1 trial of RBX7455. In the PUNCH trial, 79% of patients treated with RBX2660 were free of CDI recurrence at week 8, with microbiome compositions changed significantly from before to after treatment.

At the 7 day mark, the investigators found responders MHI-A shifted more than 7.2 and remained so to at least 24 months follow treatment.

In the open-label trial of RBX7455, 3 dosing regimens resulted in an aggregate 90% CDI recurrence-free rate at week 8 after the last received treatment with no apparent dose–response. The participant’s microbiomes shifted significantly from before to after treatment and by day 7 MHI-A shifted much higher.

The majority of responders were more than 7.2 at day 7, 30, and 60, as well as at 6 months following treatment.

The investigators also found clinical response to either C difficile treatment correlated with a shift of MHI-A from dysbiotic to healthy values.

“MHI-A is a promising biomarker of post-antibiotic dysbiosis and subsequent restoration,” the authors wrote. “MHI-A may be useful for rank-ordering the microbiota-disrupting effects of antibiotics and as a pharmacodynamic measure of microbiota restoration.”

The study, “Development and Validation of a Novel Microbiome-Based Biomarker of Post-antibiotic Dysbiosis and Subsequent Restoration,” was published online in Frontiers in Microbiology.

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