Evaluating a Prototype Microbiome Health Index (MHI) as a Measure of Microbiome Restoration Using Data Derived From Published Studies of Fecal Microbiota Transplant to Treat recurrent Clostridium difficile Infections (rCDI)

Ken Blount PhD, Courtney Jones BS, Elena Deych MS, Bill Shannon PhD MBA

Poster image from IDWeek 2018 - Evaluating a Prototype Microbiome Health Index (MHI) as a Measure of Microbiome Restoration Using Data Derived From Published Studies of Fecal Microbiota Transplant to Treat recurrent Clostridium difficile Infections (rCDI)

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IDWeek 2018
October 3-7, 2018, San Francisco, CA

Background

  • There are efforts to develop FDA-approved microbiotabased drugs to restore the microbiome, notably for recurrent Clostridium difficile infections (rCDI).
  • Given the lack of established biomarkers for microbiome restoration, we are evaluating unidimensional Microbiome Health Indices TM (MHI) to define changes in patient microbiomes after treatment.
  • We previously presented a prototype MHI for clinical trials of RBX2660—a standardized microbiota restoration therapy in Phase 3 clinical development.
  • Herein we assessed the utility of the MHI metric on published studies of fecal microbiota transplant (FMT) for treating rCDI.

Methods

  • The prototype MHI analysis included 127 RBX2660 product samples and 339 stool samples collected at indicated time points from a total of 176 participants with recurrent CDI who received at least one dose of RBX2660 as part of the PUNCH CD 2 Phase 2B trial (NCT02299570) or the PUNCH Open Label Phase 2 trial (NCT02589847). Success was defined as the absence of CDI at 8 weeks after the last treatment.
  • PUNCH CD2 participant samples underwent 16S sequencing. Data from the PUNCH OL participant samples were generated using a shallow shotgun sequencing that generates taxonomic profiles with species-level resolution (CoreBiome, Minneapolis, MN).
  • Relative taxonomic abundances at the class level were calculated from OTU data for each time, treatment, outcome group, and the mean and upper/lower confidence limits defined by fitting to a Dirichlet-multinomial distribution using maximum likelihood estimation.
  • MHI data for the published FMT cohorts were calculated using publicly available data derived from pre- and post-treatment fecal samples.The first external cohort consisted of 14 rCDI patients1, of which four were treated with FMT and provided longitudinal fecal samples. All patients were multi-recurrent CDI and were treated with vancomycin prior to FMT, with a 2-day washout period in which standard colonoscopy prep was administered. FMT, fresh or frozen, was administered via colonoscope. Fecal samples were collected at home and sequenced using standard 16S methodology, and OTU tables are deposited in public database.

    The second cohort consisted of 38 rCDI patients with or without codiagnosis of IBD2. FMT was administered by colonoscopy. All patients responded to FMT with respect to resolution of CDI; one recurred within 56 days of FMT, one between 56 days and 1 year, and three beyond 1 year.

MHI in RBX2660 Trials

  • See poster (2.5 MB)

MHI in Fecal Microbiota Transplants

  • See poster (2.5 MB)

Conclusions

  • MHI is highly effective at monitoring microbiome restoration after FMT, suggesting it as a useful dysbiosis measure beyond RBX2660 trials.
  • Lower MHI among patients co-diagnosed with IBD suggests the potential utility of MHI beyond rCDI.
  • Collectively our results continue to support the utility of MHI and its prospective evaluation in ongoing Phase 3 clinical trials.

References

  1. Weingarden A, González A, Vázquez-Baeza Y, et al. (2015) Dynamic changes in short- and long-term bacterial composition following fecal microbiota transplantation for recurrent Clostridium difficile infection. Microbiome 3:10.
  2. Khanna S, Vazquez-Baeza Y, González A, et al. (2017) Changes inmicrobial ecology after fecal microbiota transplantation for recurrent C. difficile infection affected by underlying inflammatory bowel disease. Microbiome. 5(1):55.