Gut-microbiota-targeted diets modulate human immune status

May combine two claims.

The high-fiber arm did not increase fermented food intake, and the high-fermented arm did not increase fiber intake.

“Importantly, participants in the high-fiber diet arm did not increase their consumption of fermented foods (Figure 1C, dashed line), nor did participants consuming the high-fermented food diet increase their fiber intake (Figure 1D, dashed line) during the course of the study.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

All participants followed the dietary requirements, but they implemented the intervention differently in terms of specific food subcategories.

“While all participants followed the requirements for the dietary intervention, each implemented the intervention differently in terms of specific subcategories of fiber-rich or fermented foods they consumed (Figure S2A, S2B).”

May combine two claims.

Microbiota-based models predicted diet with accuracies of 80% for 16S rRNA composition, 74% for stool microbe proteomics, 67% for stool short-chain fatty acids, and 67% for metagenomic CAZymes.

“The four next highest-performing models were all generated using measurements of the microbiota including overall 16S rRNA-based composition (80% accuracy), stool microbe proteomics (74%), stool short-chained fatty acids (67%), and metagenomic measurement of carbohydrate active enzymes (67%).”

May combine two claims.

High-fiber participants decreased their intake of animal protein and sodium.

“These participants also decreased their consumption of animal protein and sodium (Table S3).”

May combine two claims.

No differences were observed in blood glucose, insulin, triglycerides, LDL-C, HDL-C, blood pressure, or waist circumference between arms or longitudinally.

“To assess participants overall health throughout the study, blood glucose, insulin, triglycerides, LDL-C, HDL-C, blood pressure, and waist circumference were measured; however, no differences were observed in this generally healthy cohort either between the two arms or longitudinally (within) (data not shown).”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Fermented food participants reported increased bloating from baseline to the end of ramp, which was no longer significant by the end of maintenance.

“the fermented food diet arm reported an increase in bloating from baseline (abdominal distention score=0.06 +/− 0.06) to the end of the ramp phase (score=0.4 +/− 0.1; p=0.03; paired t-test), which was no longer significant by the end of the maintenance phase.”

Probably not a substantial claim: may not pass S3 (load-bearing).

High-fiber participants reported increased stool softness from baseline to the end of ramp and maintenance phases.

“participants on the high-fiber diet reported an increase in stool softness from baseline (average Bristol stool type = 3.3 +/− 0.3) to end of ramp phase (stool type=4.1 +/− 0.3; p=0.04; paired t-test) and the end of maintenance phase (stool type=4.1 +/− 0.3, p=0.004; paired t-test).”

Probably not a substantial claim: may not pass S3 (load-bearing).

Race and gender were not significant covariates in the primary outcome analysis.

“The primary outcome of cytokine response score (Shen-Orr et al., 2016) difference from baseline to end of intervention was not significant for either arm of the study (Table S4), nor were race or gender significant covariates.”

• cites Shen-Orr et al., 2016 sourceNot checked yet

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May combine two claims.

High-fiber participants increased intake of soluble and insoluble fiber, carbohydrates, vegetable protein, calories, iron, magnesium, potassium, vitamin C, and calcium.

“High-fiber diet participants increased their intake of soluble and insoluble fiber, carbohydrates, vegetable protein, and had a modest increase in calories, along with increases in iron, magnesium, potassium, vitamin C, and calcium.”

May combine two claims.

Immune parameter models predicted diet arm with 61% accuracy for endogenous signaling, 61% for inflammatory cytokines, and 58% for immune cell frequency; signaling capacity was 49% and no better than chance.

“Models generated using measurements of host immune parameters including endogenous immune cell signaling (61%), inflammatory cytokines (61%), and immune cell frequency (58%) were predictive of diet arm, but less so than many of the observed changes to the microbiota listed above. Models generated using immune cell signaling capacity (49%) were no better than chance at predicting diet group.”

May combine two claims.

Over the 10-week intervention, fermented food consumers showed a cohort-wide decrease in many inflammatory markers together with an increase in microbiota diversity.

“Remarkably, over the course of the 10-week intervention, we observed a cohort-wide decrease in many inflammatory markers in individuals consuming fermented foods, coincident with an increase in microbiota diversity.”

May combine two claims.

The two dietary interventions produced distinct responses, with some responses cohort-wide and others individualized.

“We observed that each intervention produced a distinct response and that some responses were general, i.e., cohort-wide, while others were individualized.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The nutritional intake model relied on animal protein, total dietary fiber, and insoluble dietary fiber for classification.

“This model relied upon intake of animal protein, total dietary fiber, and insoluble dietary fiber for classification.”

May combine two claims.

The overall microbiota composition model showed an increase in Lachnospira in the high-fiber arm and a decrease in the high-fermented arm relative to baseline.

“The overall microbiota composition model was characterized by an increase in the genus Lachnospira in the high-fiber diet arm and a decrease in the high-fermented food arm relative to baseline (Figure 2C).”

May combine two claims.

In the fermented food arm, decreases in inflammatory markers and increases in microbiota diversity from baseline to end of intervention were significant.

“Decreases in inflammatory markers and increases in microbiota diversity from baseline to end of intervention were significant in the fermented food arm, a specific subset of short chain fatty acids (SCFAs) was significantly decreased in the high-fiber arm from baseline to end of intervention.”

May combine two claims.

Metagenomic sequencing showed increased relative abundance of 11 CAZymes, and all 10 putative non-ambiguous substrate predictions were for degradation of plant cell wall carbohydrates.

“Metagenomic sequencing revealed an increase in the relative abundance of 11 different carbohydrate active enzymes (CAZymes); of 10 putative non-ambiguous substrate predictions, all were predicted to degrade plant cell wall carbohydrates (Figure 3C).”

May combine two claims.

No significant changes were observed in perceived stress, well-being, fatigue, physical activity, or cognition between groups or longitudinally.

“Additional validated surveys were given to participants to assess perceived stress, well-being, fatigue, physical activity, and cognition; however, no significant changes were observed between the two groups or longitudinally within the groups (data not shown).”

May combine two claims.

Fecal butyrate did not rise significantly cohort-wide in the high-fiber arm, but most participants whose butyrate rose while B cell frequency fell were in that arm.

“Interestingly, while fecal butyrate did not increase significantly cohort-wide during the high-fiber diet intervention, the majority of participants whose butyrate increased while B cell frequency decreased were in the high-fiber diet arm.”

May combine two claims.

Most correlations between CAZymes and disease-associated proteins were negative, and inflammatory-response proteins had the most significant correlations.

“The majority of correlations between CAZymes and disease-associated proteins were negative, with proteins assigned to inflammatory response having the highest count of significant correlations (Figure 7B).”

May combine two claims.

Gender, race, and BMI were not significantly associated with alpha diversity over time.

“We additionally assessed gender, race, and BMI as covariates in the model of alpha diversity and time, but none were significantly associated (LME, p > 0.05).”

May combine two claims.

Total daily fermented food servings were positively correlated with alpha diversity, and yogurt or vegetable brine drink servings were most strongly correlated.

“Interestingly, while the total number of fermented food servings consumed per day was positively correlated with alpha diversity, the number of servings of yogurt or vegetable brine drinks was most strongly correlated (Figure 5C).”

May combine two claims.

The number of fermented food servings consumed was correlated with increased diversity, but this relationship was weaker than the relationship between diversity and time.

“Notably, while the number of servings of fermented food consumed was correlated to an increase in diversity, this relationship was not as strong as the relationship between diversity and time (Figure 5C).”

May combine two claims.

CyTOF analysis showed that effector memory CD4+ T cells increased and non-classical monocytes decreased during the intervention.

“Analysis of CyTOF data to identify the frequency of a larger set of immune cell types revealed that effector memory CD4+ T cells increased, and non-classical monocytes decreased during the intervention (Figure 6C, S3).”

May combine two claims.

There was no significant difference in alpha diversity between the high-inflammation and low-inflammation i groups (p=0.096), with a trend toward increasing diversity in low-inflammation i.

“While there was not a significant difference in microbiota alpha diversity between the ‘high-inflammation” and “low-inflammation i” groups (p-value=0.096), there was a trend towards increasing microbiota diversity in the “low-inflammation group i” that followed the intermediate inflammatory response observed.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Anaerostipes had a significant joint p-value in the ZIBR model and was previously described as a hyper-butyrate producer.

“Anaerostipes had a significant joint p-value in the ZIBR model (Table S7) and was previously described as a “hyper-butyrate producer” (2014).”

• cites [2014]Not checked yet

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May combine two claims.

In serum metabolomics, 38 metabolite-cytokine correlations were significant, with 18 positive and 20 negative.

“Thirty eight correlations were statistically significant (Pearson, adjusted p-value ≤ 0.05, Benjamini-Hochberg correction), 18 of which were positive and 20 of which were negative (Figure S6B).”

May combine two claims.

The immune clusters were driven by changes in endogenous signaling, with decreases in two low-inflammation clusters and an increase in the high-inflammation cluster.

“These clusters were driven by observed changes in endogenous signaling, most notably decreasing signaling in two clusters (“low-inflammation i” and “low-inflammation ii”), as opposed to an increase in signaling in the “high-inflammation” cluster.”

Probably not a substantial claim: may not pass S3 (load-bearing).

There was a modest difference in a Lachnospiraceae taxon between the two low-inflammation clusters.

“There was a modest difference in a Lachnospiraceae taxon between the two low-inflammation clusters.”

May combine two claims.

In the pairwise LME model comparing high-inflammation and low-inflammation i groups, the inflammation group factor was significant (p = 7.2e-4), while the time variable was not (p = 0.69).

“For the model comparing high-inflammation and low-inflammation i, the inflammation group factor was significant (p-value = 7.2e-4), but the time variable was not (p-value = 0.69).”

May combine two claims.

High-fiber consumption appeared to increase stool microbial protein density and carbohydrate-degrading capacity and to alter SCFA production.

“Importantly, high-fiber consumption did appear to increase stool microbial protein density, carbohydrate-degrading capacity, and altered SCFA production”

• AssumptionRests on an assumption: Fiber-rich foods contain microbiota-accessible carbohydrates that serve as a fermentable carbon source for the microbiota.

May combine two claims.

Nine ASVs increased over time, all in Firmicutes, including four Lachnospiraceae, two Ruminococcaceae, and one Streptococcaceae.

“Nine ASVs increased over time, all in the Firmicutes phylum, including four in the Lachnospiraceae family, two in the Ruminococcaceae family, and one in the Streptococcaceae family (Figure 5D).”

May combine two claims.

During the intervention, 14 of 60 cell-type-specific signaling responses decreased and only one increased.

“Specifically, there were decreased levels of activation in 14 of the 60 different cell type-specific signaling responses, and only one signaling increase (Figure 6B).”

May combine two claims.

Alcohol consumption did not differ between arms at baseline and did not change significantly over the study.

“There was no difference in alcohol consumption between arms at baseline, nor did alcohol consumption significantly change over the course of the study (LME, p > 0.05).”

Probably not a substantial claim: may not pass S3 (load-bearing).

The other two pairwise LME models comparing fiber inflammation groups did not yield significant p-values.

“The other two models did not have significant p-values.”

May combine two claims.

In the fermented-food arm, only 8 CAZymes changed, all decreasing from baseline to maintenance; 3 were starch-degrading and 5 plant-degrading.

“However, in the fermented food diet arm, the relative abundance of only 8 CAZymes (3 of which were annotated as starch-degrading and 5 annotated as plant-degrading) differed and all decreased in the maintenance phase relative to baseline.”

May combine two claims.

No differences in total fiber intake or BMI were observed between the inflammation clusters.

“Notably, no differences in total fiber intake were observed between inflammation clusters, nor were there significant differences in BMI (t-test, p-value > 0.05).”

May combine two claims.

The size of these cytokine changes did not differ significantly between high and low fermented-food consumers, and no change correlated with BMI.

“The magnitude of these changes were not significantly different between binned “high” and “low” fermented food consumers (t-test, adjusted p-value > 0.05, n = 19), nor did any change correlate with BMI.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The recursive feature random forest models identified the minimum feature set needed for highest accuracy.

“The recursive feature random forest models returned the minimum feature set needed for highest accuracy (Table S5).”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Of the 92 Olink inflammation proteins, 67 were detected in more than 75% of samples and included in the analysis.

“Out of 92 proteins, 67 were detected in >75% of samples and used in analysis.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Significant correlations (adjusted p ≤ 0.05) between changes in serum metabolites and cytokines are shown in Figure S6B.

“Significant correlations (p-value adjusted ≤ 0.05) shown in Figure S6B.”

May combine two claims.

A two-week food exchange between African Americans and rural Africans changed the microbiota and cancer risk markers.

“A 2-week food exchange study in which African Americans consumed a rural African diet and rural Africans ate a typical African American diet revealed measurable changes to the microbiota and markers of cancer risk despite the brevity of the dietary intervention (O’Keefe et al., 2015).”

• cites O’Keefe et al., 2015 sourceNot checked yet

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May combine two claims.

Fermented foods may be powerful modulators of the microbiome-immune axis and may help combat non-communicable chronic diseases.

“These results suggest that fermented foods may be powerful modulators of the human microbiome-immune system axis and may provide an avenue to combat NCCDs.”

• AssumptionRests on an assumption: Non-communicable chronic diseases are largely driven by chronic inflammation and their rates are increasing with industrialization.
• AssumptionRests on an assumption: The human microbiome influences inflammatory status.

May combine two claims.

The gap between average American fiber intake and recommended levels suggests that increasing fiber could modulate the human immune system through the microbiota.

“These findings and the shortfall between fiber consumption in the average American diet versus recommended levels suggest that boosting fiber intake could be a powerful way to modulate the human immune system via the microbiota (Deehan and Walter, 2016).”

• cites Deehan and Walter, 2016Not checked yet

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May combine two claims.

The data suggest that carbohydrate degradation by participants' microbiota was insufficient to process the increased fiber consumption, consistent with analyses of industrialized microbiomes.

“These data suggest the carbohydrate degradation by participants’ microbiota was insufficient to process the increased fiber consumption, consistent with analyses of industrialized microbiome (Smits et al., 2017; Vangay et al., 2018).”

• cites Smits et al., 2017 sourceNot checked yet

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• cites Vangay et al., 2018 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Fermented foods may provide compensatory exposure to safe environmental and foodborne microbes lost through sanitization.

“They may also provide compensatory exposure to safe environmental and foodborne microbes that have been lost over the course of sanitizing the industrialized environment.”

Probably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).

Consuming fermented foods may reintroduce evolutionarily important interactions.

“Given that fermented foods have historically been part of many diets around the world, consuming fermented foods may offer an effective way to reintroduce evolutionarily important interactions.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Fermented foods have become popular as reports of potential health benefits in animals and humans have appeared.

“Fermented foods, such as kombucha, yogurt, and kimchi, have gained popularity as reports of potential health benefits in animal models and humans have emerged (Dimidi et al., 2019; Villarreal-Soto et al., 2020).”

• cites Dimidi et al., 2019 sourceNot checked yet

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• cites Villarreal-Soto et al., 2020 sourceNot checked yet

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Classified as probably not a substantial claim.

Short-term dietary changes can rapidly alter the human gut microbiota.

“Short-term changes in diet during prospective dietary intervention studies have also been shown to rapidly change the human gut microbiota (David et al., 2014).”

• cites David et al., 2014 sourceNot checked yet

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May combine two claims.

Elevated isobutyric and isovaleric acid have been associated with hypercholesterolemia, and elevated valeric acid with autism spectrum disorder.

“Elevated isobutyric and isovaleric acid have been associated with hypercholesterolemia (Granado-Serrano et al., 2019) and elevated valeric acid in autism spectrum disorder (Liu et al., 2019).”

• cites Granado-Serrano et al., 2019 sourceNot checked yet

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• cites Liu et al., 2019 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

The increase in myosin-1 could indicate increased epithelial cell turnover in the small intestine in the high-fermented food cohort.

“Its increase could indicate increased epithelial cell turnover within the small intestine in the high-fermented food diet cohort (Benesh et al., 2010).”

• cites Benesh et al., 2010 sourceNot checked yet

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May combine two claims.

Within each arm, an individual's microbiota composition became more similar to others in the same arm over the intervention while retaining individuality.

“In other words, an individual’s microbiota composition became more similar to that of other participants within the same arm over the intervention, despite retaining the strong signal of individuality.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Cohort and limited interventional studies link fermented food consumption with weight maintenance and lower risks of diabetes, cancer, and cardiovascular disease.

“Large cohort studies as well as limited interventional studies have linked the consumption of fermented foods with weight maintenance and decreased diabetes, cancer, and cardiovascular disease risks (Mozaffarian et al., 2011; Díaz-López et al., 2016; Gille et al., 2018).”

• cites Mozaffarian et al., 2011 sourceNot checked yet

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• cites Díaz-López et al., 2016 sourceNot checked yet

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• cites Gille et al., 2018 sourceNot checked yet

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Classified as probably not a substantial claim.

The gut microbiota is important for human health.

“The importance of the gut microbiota, or microbiome, in human health (Lynch and Pedersen, 2016) necessitates enhanced understanding of the factors that influence the composition and function of this microbial community.”

• cites Lynch and Pedersen, 2016 sourceNot checked yet

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May combine two claims.

Human dietary fiber interventions have altered the microbiota and improved health markers.

“Dietary interventions that specifically alter dietary fiber, such as increases in total carbohydrates, whole grains, and resistant starch versus wheat bran consumption, have shown impacts on the microbiota along with improvements in health markers of the study participants (Duncan et al., 2007; Martínez et al., 2013; Walker et al., 2011).”

• cites Duncan et al., 2007 sourceNot checked yet

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• cites Martínez et al., 2013 sourceNot checked yet

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• cites Walker et al., 2011 sourceNot checked yet

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May combine two claims.

A subset of American Gut Project participants showed differences in microbiota composition and fecal metabolome between fermented food consumers and non-consumers.

“A recent longitudinal study of a subset of American Gut Project participants found differences in microbiota composition and fecal metabolome among fermented food consumers vs. non-consumers (Taylor et al., 2020).”

• cites Taylor et al., 2020Not checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

Lachnospira has been positively associated with high dietary fiber consumption in a human prospective study.

“Lachnospira has been positively associated with high dietary fiber consumption in a human prospective study (Lin et al., 2018).”

• cites Lin et al., 2018 sourceNot checked yet

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Probably not a substantial claim: may not pass S2 (checkable).

Manipulating gut microbes may be a powerful way to alter diverse aspects of human health.

“The integration of the gut microbiota into human biology suggests that manipulation of gut microbes may be a powerful means to alter diverse aspects of human health.”

May combine two claims.

Westernization of the gut microbiota in U.S. immigrants is accompanied by loss of microbial functions and taxa, deteriorating health markers, increased BMI, and rising inflammatory markers.

“Rapid “westernization” of the microbiota has been observed in U.S. immigrants, with loss of microbial functions and taxa accompanied by deteriorating markers of host health, increased BMI, and rising inflammatory markers typical in industrialized populations (Vangay et al., 2018; Sonnenburg and Sonnenburg, 2019).”

• cites Vangay et al., 2018 sourceNot checked yet

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• cites Sonnenburg and Sonnenburg, 2019 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The human microbiota is generally resilient over short periods and retains highly individualized identities.

“Although, we and others have reported a general resilience of the human microbiota over short time periods (days to months) coupled with retention of highly individualized microbiome identities (Wu et al., 2011; Fragiadakis et al., 2020).”

• cites Wu et al., 2011Not checked yet

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• cites Fragiadakis et al., 2020 sourceNot checked yet

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Probably not a substantial claim: may not pass S3 (load-bearing).

After one dropout and two antibiotic-related exclusions, the final number of participants was 18 per arm.

“One participant dropped out of the study due to personal reasons and two participants were prescribed antibiotics during the course of the study and were excluded from analysis. The final count for participants was identical in each arm, n=18.”

Probably not a substantial claim: may not pass S3 (load-bearing).

P-values for all ASVs tested against time were adjusted for multiple testing using a Benjamini-Hochberg correction.

“P-values for all ASVs in association with time were adjusted for multiple hypothesis testing using a Benjamini-Hochberg correction.”

Probably not a substantial claim: may not pass S3 (load-bearing).

P-values for correlations between serum metabolites and cytokines were corrected using Benjamini-Hochberg.

“p-values were corrected using Benjamini-Hochberg hypothesis correction.”

Probably not a substantial claim: may not pass S3 (load-bearing).

In cross-data-type comparisons, parameters were centered and scaled to remove experimental bias.

“In analyses comparing different data types to each other, parameters were centered and scaled (across columns) to eliminate experimental bias.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The trial was registered at ClinicalTrials.gov under NCT03275662.

“Trial was registered at ClinicalTrials.gov, identifier: NCT03275662.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The intervention had a 4-week ramp and 6-week maintenance; the durability of changes and effects of longer intervention are unknown.

“The dietary intervention phase was performed over a 4 week ramp period and a 6 week maintenance period; we do not know the durability of many of the changes we observed or if further changes would arise during a longer intervention.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The 16S findings for purchased fermented foods may not reflect the exact foods participants ate because of batch variation and self-purchasing.

“It is important to note that our findings for these foods may not directly reflect the composition of the exact foods (e.g., due to batch variation) eaten by the participants, who purchased their own fermented food.”

Classified as probably not a substantial claim. May combine two claims.

Participants were randomized to high-fiber or high-fermented-food diets using a random number generator, performed by a statistician not involved in intervention or data collection.

“A simple randomization was done for the two groups using a random number generator (Excel), performed by a statistician not involved in the intervention or data collection.”

May combine two claims.

These changes indicate that microbiome remodeling occurred within the study period without an increase in total species.

“indicating that microbiome remodeling was occurring within the study time frame, just not through an increase in total species.”

• AssumptionRests on an assumption: Fiber-rich foods contain microbiota-accessible carbohydrates that serve as a fermentable carbon source for the microbiota.

May combine two claims.

The data suggest divergent immune responses to the high-fiber intervention, with high-inflammation participants showing broad increases and low-inflammation participants showing decreases in steady-state immune activation.

“Taken together, these data suggest divergent immune system responses to the high-fiber intervention, with “high-inflammation” participants exhibiting broad increases in steady-state immune activation versus “low-inflammation” participants exhibiting decreases in steady-state immune activation.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The study was conducted in healthy individuals, so effects in disease or inflammatory conditions remain unknown.

“The study was performed among healthy individuals; future work should examine the effects of these diets in the context of disease or inflammatory conditions”

May combine two claims.

The slow, steady diversity increase suggests a time element in diet-driven microbiome remodeling, consistent with the human microbiota's resistance to rapid dietary change.

“The slow and steadily increasing diversity suggests a time element for remodeling of the microbiome composition through diet, consistent with the relative recalcitrance of the human microbiota to rapid diet-induced remodeling (Wu et al., 2011).”

• cites Wu et al., 2011Not checked yet

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May combine two claims.

Consuming fermented foods indirectly alters gut microbiota diversity, making the microbiota more receptive to incorporation or increased representation of previously undetected strains.

“These data support that fermented food consumption has an indirect effect on microbiota diversity, rendering the microbiota receptive to the incorporation or increased representation of previously undetected strains within the gut.”

• Also stated in: § Discussion · hedged

  “Notably, the new taxa contributing to the increased diversity were largely not from the fermented foods themselves, indicating an indirect effect of their consumption on remodeling the microbiota.”

• AssumptionRests on an assumption: The gut microbiota modulates chronic inflammation or immune status.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

The primary outcome calculation included only randomized participants; two high-fiber-arm participants were omitted.

“Only participants that were randomized were included in calculation of primary outcome (two participants in the high-fiber diet excluded).”

Probably not a substantial claim: may not pass S3 (load-bearing).

Validated health surveys were used, including PROMIS, WHO well-being, Perceived Stress Scale, and International Physical Activity Questionnaire.

“The following validated health surveys were used by participants: PROMIS v1.1 global health, PROMIS v1.0 - fatigue, WHO well-being index, PROMIS applied cognition short form, Perceived Stress Scale (Cohen et al., 1983), and the International Physical Activity Questionnaire (Craig et al., 2003).”

• cites Cohen et al., 1983 sourceNot checked yet

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• cites Craig et al., 2003 sourceNot checked yet

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Classified as probably not a substantial claim.

The linear mixed-effects models used participant as a random effect because repeated samples from the same person are not independent and introduce autocorrelation.

“Because samples from the same participant are not independent from one another and introduces autocorrelation, we used the participant term as a random variable in the lme function using the nLME package in R.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Two participants requested the high-fiber diet and were not randomized.

“Two participants requested to be placed on the high-fiber diet and were non-randomized.”

May combine two claims.

The current data show a profound effect of these diets on the microbiome and immune status.

“Finally, while current data demonstrates a profound effect of these diets on both the microbiome and immune status, further work must examine causality of these interrelated aspects of human biology with an emphasis on the mechanistic underpinnings using additional experimental models.”

Probably not a substantial claim: may not pass S3 (load-bearing).

In the ZIBR analysis, taxa with significant baseline coefficients were removed to focus on differences induced by the dietary intervention.

“Taxa with significant baseline coefficients were filtered out to focus on the significant differences induced by the dietary intervention (Table S7).”

May combine two claims.

The study had a modest sample size (n = 18 per arm), limiting statistical power and generalizability.

“The study included a modest number of participants (n = 18/arm) which limits statistical power and presents challenges with regard to generalizability of results.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The study was approved annually by the Stanford University Human Subjects Committee.

“The study was approved annually by the Stanford University Human Subjects Committee.”

May combine two claims.

The associations suggest that CAZymes and host proteins may respond to dietary interventions in coordinated opposing directions and may link diet, the microbiome, and host physiology.

“These associations suggest that CAZymes and host proteins may respond to dietary interventions in coordinated yet opposing directions (i.e., increased CAZyme abundance correlates with decreased levels of inflammation-associated proteins) and may serve as a direct link between diet, the microbiome and host physiology.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Baseline beta diversity was tested to determine whether the two diet arms differed at baseline.

“To determine if the high-fiber and high-fermented food diet arms were significantly different at baseline, the samples were filtered to week −2, β-diversity was calculated, and the analysis of variance using distance matrices was calculated with the adonis function (method = “euclidean”) in the vegan package in R (version 2.5.6).”

May combine two claims.

As participants' microbiome CAZymes increase in relative abundance, they may show lower basal inflammatory status and reduced responsiveness after cytokine stimulation.

“In other words, as participants’ microbiome CAZymes increase in relative abundance they may exhibit a decrease in basal inflammatory status combined with being less responsive after cytokine stimulation.”

May combine two claims.

The study lacked a control arm and relied on between-diet-arm and within-participant comparisons over time.

“The study had no control arm, and instead relied upon comparisons between the two dietary arms, and within-participant comparisons over time.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Participants and dieticians could not be blinded to randomization, and the study team was not blinded.

“Participants and dieticians could not be blinded to randomization assignments in order to perform and counsel the dietary changes, nor was the study team blinded.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The study did not pre-publish a Statistical Analysis Plan.

“A Statistical Analysis Plan was not pre-published”

Probably not a substantial claim: may not pass S3 (load-bearing).

Gender, race, and BMI were included as covariates in the model of diversity over time.

“Terms for gender, race, and BMI were included in the model as covariates in the analysis of diversity over time.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Akkermansia has been positively associated with metabolic health, but also with low-fiber diets, and is rare in populations consuming traditional diets.

“Akkermansia has been positively associated with metabolic health (Derrien et al., 2017), but has also been associated with low-fiber diets and is rare in populations consuming traditional diets (Earle et al., 2015; Desai et al., 2016; Smits et al., 2017).”

• cites Derrien et al., 2017 sourceNot checked yet

  Not checked in the free run.

• cites Earle et al., 2015 sourceNot checked yet

  Not checked in the free run.

• cites Desai et al., 2016 sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Coprococcus has been associated with higher quality-of-life indicators, and Ruminococcus and Oscillospira with improved health markers including leanness and improved lipid profile.

“Coprococcus has been associated with higher quality of life indicators and both Ruminococcus and Oscillospira have been associated with improved markers of health including leanness and improved lipid profile (Valles-Colomer et al., 2019; Klimenko et al., 2018; Chen et al., 2020).”

• cites Valles-Colomer et al., 2019 sourceNot checked yet

  Not checked in the free run.

• cites Klimenko et al., 2018 sourceNot checked yet

  Not checked in the free run.

• cites Chen et al., 2020 sourceNot checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S3 (load-bearing).

Multiple hypothesis testing correction was applied throughout the analyses.

“however multiple hypothesis testing correction was applied as described throughout.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

This dampening is striking because participants in the fermented-food arm changed little else in their diet and ate a variety of fermented foods.

“This result is especially striking given that participants in this arm changed little else in their diet and consumed a variety of fermented foods (i.e., some ate mostly fermented dairy products while others ate mostly fermented vegetable products).”

Probably not a substantial claim: may not pass S3 (load-bearing).

For the model of fermented food intake versus observed ASVs, p-values were adjusted using Benjamini-Hochberg correction.

“p-values were adjusted using Benjamini-Hochberg correction.”

Classified as probably not a substantial claim.

Significance analysis of serum cytokines used SAM two-class paired with FDR ≤ 0.05 and q-value ≤ 0.1.

“Significance was assessed using the siggenes package in R (SAM two-class paired, FDR ≤ 0.05, q-value ≤ 0.1).”

Probably not a substantial claim: may not pass S3 (load-bearing).

In CyTOF signaling analysis, features were restricted to four major cell types: CD4+ T cells, CD8+ T cells, B cells, and classical monocytes.

“features were restricted to those in four major cell types (CD4+ T cells, CD8+ T cells, B cells, classical monocytes)”

Probably not a substantial claim: may not pass S3 (load-bearing).

CyTOF samples were excluded if they contained fewer than 10,000 singlets.

“Samples were excluded if the number of singlets was less than 10,000 cells.”

Classified as probably not a substantial claim.

Significance analysis of CyTOF signaling proteins used SAM two-class paired with FDR ≤ 0.05 and q-value ≤ 0.1.

“analysis was performed using the siggenes package in R (SAM two-class paired, FDR ≤ 0.05, q-value ≤ 0.1).”

Probably not a substantial claim: may not pass S3 (load-bearing).

In flow cytometry analysis, the feature set was restricted to features with an average fold change greater than two.

“For analysis we restricted our feature set to features with an average fold change greater than two.”

Probably not a substantial claim: may not pass S3 (load-bearing).

In the ZIBR analysis, ASVs were filtered to those present in at least 25% of samples.

“filtered to only ASVs present in at least 25% of samples.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

For the random forest, host proteins were filtered to the top 75% (230 proteins) and microbe proteins to the top 50% (2,157 proteins) by variance across participants.

“Host proteins were filtered to top 75% (230 proteins total) and microbe proteins were filtered to top 50% proteins (2,157 proteins total) with the highest variance across participants.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

For the random forest, 16S data were filtered to ASVs present in at least 25% of samples and rank-normalized within each sample using the method of Callahan et al. (2017).

“16S data were filtered to only ASVs present in at least 25% of samples and rank-normalized within each sample according to the methods described by (Callahan et al., 2017).”

• cites Callahan et al., 2017Not checked yet

  Not checked in the free run.

Probably not a substantial claim: may not pass S1 (asserted), S3 (load-bearing), S4 (based).

Significance analysis of flow cytometry signaling used SAM two-class paired with FDR ≤ 0.05 and q-value ≤ 0.1.

“Significance was assessed using the siggenes package in R (SAM two-class paired, FDR ≤ 0.05, q-value ≤ 0.1).”

Probably not a substantial claim: may not pass S3 (load-bearing).

In the Spearman correlation analysis, correlations were restricted to host-microbe comparisons before Benjamini-Hochberg correction.

“Correlations were filtered to only host-microbe comparisons before Benjamini-Hochberg hypothesis correction.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Participants lacking both baseline and end-of-intervention samples for a given platform were excluded from that analysis.

“If a participant did not have both the baseline and end of intervention time point for a given experimental platform they were removed from analysis.”

• Also stated in: § QUANTIFICATION AND STATISTICAL ANALYSIS · plain

  “If a participant did not have both the baseline and end of intervention time point for a given experimental platform they were removed from analysis.”

Probably not a substantial claim: may not pass S3 (load-bearing).

The recursive feature random forest used leave-one-out cross-validation.

“a recursive feature random forest (caret, rfeControl, number=100, leave one out cross validation) was used.”

Probably not a substantial claim: may not pass S3 (load-bearing).

Because ZIBR cannot handle missing data, missing samples were filled with the average ASV abundance for each group at each timepoint.

“Since ZIBR cannot handle missing data, missing samples were filled with the average ASV abundance for each group at each timepoint.”

Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

Correlations between host proteins and microbe proteins were not reported because they came from the same sample and platform and had inflated internal bias relative to other cross-omic comparisons.

“Correlations between host proteins and microbe proteins are not shown here as they were derived from the same sample and experimental platform and had inflated internal bias compared to the other cross-omic comparisons.”

Probably not a substantial claim: may not pass S3 (load-bearing).

For significance analysis in CyTOF, participants with missing data were excluded.

“For significance analysis, participants with missing data were excluded.”