Identification of IBS Metabotypes Based on Physiological Responses to Food
Condition: Irritable Bowel Syndrome
MeSH terms: Irritable Bowel Syndrome
Study type: Interventional

Summary: 
      Irritable bowel syndrome (IBS) is a condition characterized by abdominal pain, bloating,
      constipation, diarrhea and gas and affects up to 15% of the Western population. In many
      individuals with IBS, symptoms can be triggered by foods, such as FODMAPs (easily fermentable
      dietary fiber containing Fermentable Oligosaccharides, Disaccharides, Monosaccharides, and
      Polyols). Some individuals with IBS may also benefit from a gluten-free diet. Current
      subtypes of IBS are based on symptoms (constipation, diarrhea, and mixed), rather than
      mechanistic differences. Another promising approach for identifying IBS subtypes is based on
      grouping individuals into similar metabolic phenotypes, i.e. metabotypes, that share
      similarities in metabolism and metabolic regulation in response to specific foods. Health and
      wellbeing could potentially be improved by personalized treatment through tailoring diet to
      subjects with different IBS subtypes.

      To investigate this hypothesis, the investigators will conduct an intervention study on
      subjects with IBS and identify specific food susceptibilities based on metabolic phenotype
      (metabotype). In total, 120 women and men with moderate to severe IBS will be recruited.
      Gluten intolerance, other gastrointestinal disease and abdominal surgery will constitute
      exclusion criteria. The study will be performed in a double-blind, randomized,
      placebo-controlled cross-over study design. Study participants will receive three 1-week
      diets with additions of either FODMAPs, gluten or an inert control with 1-week washout
      in-between. IBS metabotypes will be identified by integrative multivariate analysis of
      molecular phenotype data from metabolomics and microbiota measurements combined with data on
      bowel habits and stomach discomfort. Study participants will also be subjected to a cocktail
      provocation containing FODMAPs and gluten to develop a rapid diagnostic test based on
      identified plasma metabolomic biomarkers of IBS metabotypes.
    

Detailed description: 
      The current study is explorative with the primary aim to find and relate distinct subject
      metabotypes reflecting tolerance/intolerance to specific food components among IBS-patients
      by deducing and relating OMICs data patterns (metabolomics and gut microbiota data) to
      reported severity of IBS-symptoms indicated by the primary endpoint variable, i.e. IBS-SSS.
      Since the investigators don't have an estimation of the variation in the multivariate
      OMICs-data (both metabolomics and 16S rRNA analysis of bacterial RNA), it is not possible to
      perform an adequate power-calculation. There is a lack of consensus on how to best perform
      power analysis for these OMICs-designs (and therefore also a lack of tools), although some
      initiatives have been published. Power analysis is especially difficult in untargeted
      metabolomics, where the number of variables are not a priori determined, where there is
      strong multi-colinearity and where variables cannot be assumed to contribute with equal power
      to effect size. Moreover, there is a shortage of relevant untargeted metabolomics and
      microbiota study material on IBS x diet interactions from which to estimate relevant
      parameters such as multivariate effect sizes and variance estimates, due to the surprisingly
      few metabolomics studies on IBS and the total lack of publicly available raw data. However,
      significant differences in the metabolome was previously observed in children with or without
      diarrhea-dominant IBS (n=22 per group). Systematic differences were also shown in individual
      metabolites in persons with IBS consuming either a high or low FODMAP diet (n≈20 per
      treatment).

      In this study, a cross-over design will be performed, which will increase the power compared
      to parallel designs. Moreover, participants will be stratified with respect to subtype of IBS
      (i.e. diarrhea, constipation and mixed). However, the investigators will not know in advance
      how many IBS-metabotypes will be present in the material or the quantitative distribution
      between the metabotypes. Therefore, 120 participants will be recruited to be able to observe
      significant differences between dietary treatments, based on the assumptions that it will be
      possible to identify around 4±1 metabotypes, and an approximate equal distribution between
      metabotypes (≥20 persons per metabotype). In addition, a selection of 120 participants will,
      under these conditions allow for 20% drop-out from the study, which is a high estimate based
      on our previous experience from nutritional interventions. An important secondary outcome
      from this study material is that it will give the opportunity to be used for power
      calculations in future OMICs-studies where the effect sizes on both clinical parameters and
      OMICs-measures are uncertain.

      Discovery of IBS metabotypes Identification of metabotypes will be performed using
      predominantly multivariate data analytical techniques. During initial analyses, molecular
      phenotype data (metabolomics and microbiota) will be analyzed using unsupervised principal
      component analysis (PCA) and clustering techniques to investigate whether data
      self-aggregates into meaningful clusters. To adjust for between-individual variability and
      focus on the effects of interventions, variance partitioning (sometimes referred to as ANOVA
      decomposition) by individual will be performed. Clusters will be correlated with recorded
      IBS/clinical data (IBS-SSS, bowel emptying diary) to examine whether emerging clusters
      contain functional information in relation to IBS symptoms. Moreover, it is likely that
      different clusters are not similarly reflected in plasma and fecal metabolomics and fecal
      microbiota. To investigate to which extent the different clusters are associated with the
      different omics blocks, a series of techniques for subdivision of variability into common and
      distinct components will be applied to the unsupervised analysis.

      In a second line of unsupervised analysis, PCA and clustering analyses will be performed on
      molecular phenotype aggregated with IBS/clinical data, which will have the potential to
      influence clustering directly instead of investigating correlations afterwards. Again,
      subdivision of variability into common and distinct components will be applied to examine how
      clusters are reflected in the different data blocks.

      Finally, supervised analyses will be used to directly associate molecular phenotype data
      (independent variables) with IBS/clinical data (dependent variables) using in-house developed
      partial least squares (PLS) and random forest (RF) techniques. These in-house techniques are
      specifically adapted to identifying the most relevant set of independent variables to
      describe the covariability with the dependent data (submitted manuscript). IBS/clinical data
      can be used both as continuous multiple variables or directly by converting observations to
      clusters. To examine how clusters and IBS/clinical data are reflected in the different omics
      blocks, newly developed procedures to find common and distinct components in supervised
      analysis will be applied (submitted manuscript).

      The progression in these three approaches represent an increasing degree of supervision in
      multivariate analysis. After all analyses, emerging clusters from the PCA and clustering
      analyses and multivariate predictions from the PLS and RF analyses will further analyzed
      using bioinformatics tools adapted to provide meaningful biological interpretation with the
      aim to confirm correspondence between clusters and metabotypes.

      Rapid diagnostic test of metabotypes After metabotypes have been identified, multivariate
      predictive analysis of the mixed gluten/FODMAP exposure will be performed to identify
      predictive biomarkers of metabotypes. These models will similarly as above be based on
      in-house PLS and RF procedures using metabolomics data as independent variables and
      metabotype classification per individual as dependent variable.

      Plasma metabolic profiles will be analyzed regularly up to 4 hours post exposure and two
      different approaches will be undertaken to address the time-trends in metabolic profiling: In
      a first approach, time profiles will be converted to areas-under-the-curve per measured
      metabolite feature through numerical integration. These values will then be used directly as
      independent variables to give an indication of overall reflection of metabotype on metabolite
      levels after exposure. However, this direct approach will not be able to take into
      consideration potential differences in time-trends between metabotypes. Therefore, variance
      partitioning hyphenated with supervised learning will be used to investigate metabotype x
      time interactions. This approach will require method development in multivariate analysis,
      which is currently underway in the R Landbergs research group and expected to be ready and
      beta-tested during 2018, i.e. before data is available for analysis. This methodology is
      projected to allow for simultaneous analysis of overall differences in metabolite levels
      between treatments as well as differences in time profiles, thereby giving information also
      on the most opportune time points to draw samples for effective prediction of metabotype x.
    

Intervention name(s): FODMAP; Gluten; Placebo
Intervention type(s): Dietary Supplement; Dietary Supplement; Dietary Supplement
Intervention description(s): The intervention will run for seven weeks. During the whole intervention, the participants will hold a baseline diet with no gluten and low intake of FODMAPs. The first week, the participants will consume a one-time cocktail provocation consisting of gluten (17.3 gram) and FODMAPs (50 gram) Thereafter, study participants will receive three 1-week diets with additions of either FODMAPs, gluten or an inert control with 1-week washout in-between. The daily amount for gluten will be 17.3 gram and the daily amount for FODMAPs will be 50 gram. The order of the three weeks with extra diets (gluten/FODMAPs/control) will be randomized.; The intervention will run for seven weeks. During the whole intervention, the participants will hold a baseline diet with no gluten and low intake of FODMAPs. The first week, the participants will consume a one-time cocktail provocation consisting of gluten (17.3 gram) and FODMAPs (50 gram) Thereafter, study participants will receive three 1-week diets with additions of either FODMAPs, gluten or an inert control with 1-week washout in-between. The daily amount for gluten will be 17.3 gram and the daily amount for FODMAPs will be 50 gram. The order of the three weeks with extra diets (gluten/FODMAPs/control) will be randomized.; The intervention will run for seven weeks. During the whole intervention, the participants will hold a baseline diet with no gluten and low intake of FODMAPs. The first week, the participants will consume a one-time cocktail provocation consisting of gluten (17.3 gram) and FODMAPs (50 gram) Thereafter, study participants will receive three 1-week diets with additions of either FODMAPs, gluten or an inert control with 1-week washout in-between. The daily amount for gluten will be 17.3 gram and the daily amount for FODMAPs will be 50 gram. The order of the three weeks with extra diets (gluten/FODMAPs/control) will be randomized.
Allocation: Randomized
Intervention model: Crossover Assignment
Intervention model description: The study will be a double-blinded, randomized, placebo-controlled cross-over study.
Masking: Triple (Participant, Care Provider, Outcomes Assessor)
Primary purpose: Diagnostic
Keywords: IBS; metabotype; FODMAP; gluten