Dietary Interventions to Modulate the Gut Microbiome—How Far Away Are We From Precision Medicine

Abstract

The importance of the gut microbiome in human health and disease is fully acknowledged. A perturbation in the equilibrium among the different microbial populations living in the gut (dysbiosis) has been associated with the development of several types of diseases. Modulation of the gut microbiome through dietary intervention is an emerging therapeutic and preventive strategy for many conditions. Nevertheless, interpersonal differences in response to therapeutic treatments or dietary regimens are often observed during clinical trials, and recent research has suggested that subject-specific features of the gut microbiota may be responsible. In this review, we summarize recent findings in personalized nutrition, highlighting how individualized characterization of the microbiome may assist in designing ad hoc tailored dietary intervention for disease treatment and prevention. Moreover, we discuss the limitations and challenges encountered in integrating patient-specific microbial data into clinical practice.

Full text

Inflamm Bowel Dis
• Volume 24, Number 10, October 2018 2142
CliniCal Review aRtiCle
Dietary Interventions to Modulate the Gut Microbiome—How
Far Away Are We From Precision Medicine
FrancescaDe Filippis, PhD,*,† PaolaVitaglione, PhD,*,† RosarioCuomo, MD,†,‡
RobertoBerni Canani, PhD,†,§,¶,‖ and DaniloErcolini, PhD*,†
The importance of the gut microbiome in human health and disease is fully acknowledged. Aperturbation in the equilibrium among the different
microbial populations living in the gut (dysbiosis) has been associated with the development of several types of diseases. Modulation of the gut
microbiome through dietary intervention is an emerging therapeutic and preventive strategy for many conditions. Nevertheless, interpersonal
differences in response to therapeutic treatments or dietary regimens are often observed during clinical trials, and recent research has suggested
that subject-specic features of the gut microbiota may be responsible. In this review, we summarize recent ndings in personalized nutrition,
highlighting how individualized characterization of the microbiome may assist in designing ad hoc tailored dietary intervention for disease treat-
ment and prevention. Moreover, we discuss the limitations and challenges encountered in integrating patient-specic microbial data into clinical
practice.
Key Words: personalized nutrition, gut microbiome, dietary intervention, clinical trials
INTRODUCTION
The human body is home to at least 100 trillion (1014)
microorganisms, most of them inhabiting the human gut. This
community includes taxa from the 3 domains of life (Bacteria,
Eukarya, and Archaea) and viruses, whose combined genome
harbors at least 100 times as many genes as our own genome.1
The consortium of microbial symbionts that resides in and
on the human body collectively constitutes our “microbiota”;
when also considering their pool of genes and the functions
for which they encode, we refer to it as the “microbiome.”
The human body can be considered the result of human and
microbial cells, with our genetic and metabolic potential repre-
senting the arrangement of what comes from our genome and
microbiome. For these reasons, our gut microbiome has earned
the appellative of our “other genome.”2
Several studies have focused on the exploration of the
composition and functionality of the gut microbiome, with an
emphasis on its bacterial members.3 In healthy adults, 2 bac-
terial phyla dominate, namely Firmicutes and Bacteroidetes,
which vary in their proportions across the population.
Proteobacteria, Actinobacteria, and Verrucomicrobia are
present at lower levels.4 A categorization of individuals in 3
groups (“enterotypes”) based on the prevalence of Prevotella,
Bacteroides, or Ruminococcus in the gut microbiota was pro-
posed in an attempt to simplify the complexity of the gut
microbiome.5 This classication, although appealing for under-
standing microbial changes in health and disease, has recently
been criticized, as it may lead to an oversimplied vision of the
gut microbiome, whereas the existence of smooth gradients in
the abundance of dominant taxa is now considered to be more
plausible.6, 7
In this review, we focus on the role of diet in inuenc-
ing the composition and functions of the microbiome with
a particular emphasis on inammatory bowel disease (IBD)
and irritable bowel syndrome (IBS). We also discuss the most
recent evidence for the role of microbiome-targeted dietary
interventions for promoting host health.
MICROBIAL METABOLITES IN THEGUT
Microbial symbionts interact among themselves and
with the host, impacting human physiology and health. They
relate to the host immune system, promoting the maturation
of immune cells and driving the development of immune
functions.8, 9 Moreover, gut microbes perform a wide range of
useful activities, such as fermenting and absorbing undigested
compounds and synthesizing vitamins.10, 11 They can inuence
host health through the production of benecial or detrimen-
tal metabolites. Such compounds can be derived from both
metabolic intermediates of the host and dietary precursors.
Therefore, diet plays a major role in affecting the metabolic
Received for publications October 20, 2017; Editorial Decision January 8, 2018.
From the *Department of Agricultural Sciences, Division of Microbiology,
†Task Force on Microbiome Studies, ‡Department of Clinical Medicine and
Surgery, §Department of Translational Medical Science, ¶European Laboratory for
Investigation on Food Induced Diseases, and ‖Ceinge Advanced Biotechnologies,
University of Naples Federico II, Naples, Italy
© 2018 Crohn’s & Colitis Foundation.
Published by Oxford University Press. All rights reserved.
For permissions, please e-mail: journals.permissions@oup.com.
Conicts of interest: The authors have no conicts of interest to declare.
Supported by: The study was in part supported by the grant DINAMIC (Diet-
induced Arrangement of the gut Microbiome for Improvement of Cardiometabolic
health) funded within the Joint Programming Initiative “A Healthy Diet for a Healthy
life” (JPI HDHL) - Joint Action “Intestinal Microbiomics”.
Correspondence: Danilo Ercolini, PhD, Department of Agricultural Sciences,
Division of Microbiology, University of Naples Federico II, via Università, 100 -
80055 Portici, Italy (ercolini@unina.it).
doi: 10.1093/ibd/izy080
Published online 13 April 2018
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Dietary Interventions to Modulate the Gut Microbiome
potential of gut microbes. Some specic gut microbiota mem-
bers can produce short-chain fatty acids (SCFAs) from degrad-
ation of complex plant-derived polysaccharides. SCFAs, mainly
butyrate, propionate, and acetate, exert recognized health-pro-
moting functions, such as anti-inammatory, anticarcino-
genic, and immune-regulatory functions.12, 13 Nevertheless,
gut microbiota can also be responsible for the production of
harmful molecules associated with detrimental effects for the
host and related to the development of several diseases.12, 13
Ahigh-protein diet leads to the accumulation of several amino
acid–derived products in the colon, such as branched-chain
fatty acids, phenols, p-cresol, and phenylacetic acid, previously
reported to be associated with pro-inammatory and carcino-
genic effects.13, 14 Sulfate-reducing bacteria (eg,, Desulfovibrio
spp.) produce suldes through the catabolism of sulfur amino
acids and taurine, which are toxic to colonocytes.13 N-Nitroso
compounds (NOCs) produced by nitration of amines derived
from microbial fermentation of proteins may exert carcinogenic
and mutagenic effects and are correlated with the incidence of
colorectal cancer.13 In addition, a diet rich in fat attracts more
bile in the colon, where bile acids may be converted by micro-
bial enzymes into secondary bile acids, mainly deoxycholic and
lithocholic acids. These can be involved in processes linked to
colorectal carcinogenesis, such as apoptosis, cell proliferation,
and DNA damage induction.14
MICROBIOMERELATED DISORDERS
In recent years, the “1 microbe–1 disease” model has
been regarded as extremely simplistic and obsolete, whereas
an increasing number of studies of the human microbiome
have highlighted that many diseases may be a consequence of
an overall dysbiosis status of the gut microbiome. Several gut
commensal microbes may be considered pathobionts; that is,
they normally inhabit the gut but may act as pathogens and
cause disease when the normal gut microbial community is
altered.15 Indeed, perturbation of the equilibrium in the gut
microbiome has been linked to the development of several
disorders. As they are extensively reviewed elsewhere,16–18 we
provide a short overview below, with particular emphasis on
IBD andIBS.
• Obesity: Gut microbiota dysbiosis in obesity is often associ-
ated with increased Firmicutes-to-Bacteroidetes ratio19 and
persistent inammation triggered by increased systemic levels
of lipopolysaccharides arising from Gram-negative bacterial
cells (metabolic endotoxemia).20, 21 Indeed, the perturbation
in the gut microbiota composition caused by the consump-
tion of a high-fat diet leads to amplied gut permeability,
resulting in endotoxemia.21
• Type 2 diabetes and metabolic syndrome: The gut micro-
biome plays an important role in modulating the glycemic
response, and thus in the development of type 2 diabetes
(T2D). The gut microbiota of T2D patients is usually
depleted of ber-degrading and SCFA-producing bacteria,
such as Roseburia, Eubacterium, and Faecalibacterium.22
• Cardiovascular diseases: Gut microbiota metabolism of
choline, phosphatidylcholine, and carnitine leads to trimeth-
ylamine (TMA), which is oxidized in the liver to trimethyl-
amine oxide (TMAO) and seems to be associated with the
development of atherosclerotic plaques.23, 24
• Immune-mediated adverse food reactions: food allergy and
celiac disease. These conditions are characterized by an
abnormal response of the immune system to specic food
antigens that do not affect the normal population. Agenetic
predisposition is involved in the development of these con-
ditions, but environmental factors acting at least in part on
gut microbiota could be also implicated.25 Current evidence
suggests that the gut microbiota and its metabolites, together
with exposure to dietary factors in early life, critically inu-
ence the immunology of T-cells.26
• Colorectal cancer (CRC): Some bacterial species are suspected
to be involved in CRC development.27 Although the exact
mechanisms remain unknown, the production of pro-inam-
matory or pro-oxidative metabolites and/or toxins, such as
Bacteroides fragilis BFT toxin,27 and the transformation of
primary bile acids into secondary bile acids13 may be involved.
• Neurological disorders: Gut microbiota may interact with
the nervous system through the production of several neu-
ro-active molecules and modulate brain development, func-
tions, human mood, and behavior.28, 29 The complexity of
these interactions is implied by the term “gut-brain axis.”30
Moreover, recent evidence suggests that the gut microbiome
is implicated in the etiology of autism spectrum disorder,
Parkinson’s, Alzheimer’s, and other neurodegenerative dis-
eases, although the mechanisms underlying these diseases
remain unclear.31–33
GUT MICROBIOME IN IBD ANDIBS
Inammatory Bowel Diseases
Inammatory bowel diseases are chronic intestinal dis-
eases characterized by inammation of the bowel, including
Crohn’s disease (CD) and ulcerative colitis (UC). UC is man-
ifested exclusively in colonic mucosa, whereas CD affects all
areas of the gastrointestinal (GI) tract, with features such as
granulomas and intestinal brosis. IBD affects up to 0.5% of
the population, with the highest incidence in North America
and Europe.34 The incidence is increasing, especially in devel-
oping countries, with the rate of CD rising faster than that of
UC.35 This phenomenon seems to be related to changes in the
Western lifestyle, suggesting that environmental factors, par-
ticularly diet, play a role in the development and progression
of IBD.36
Furthermore, eating habits also seem to be a key factor
in the clinical care of patients with IBD. Indeed, acute CD
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De Filippis etal
treatment with an elemental diet resulted in a remission com-
parable to treatment with corticosteroids.37 As dietary and
bacterial antigens are the most common types of luminal anti-
gen, it is reasonable to suppose that dietary factors may play
an important role in the pathogenesis of IBD, possibly inter-
acting with the gut microbiota and the mucosal immune sys-
tem.38 Gut microbiota dysbiosis was often observed in IBD
patients, although a causal relationship has not been estab-
lished.39 Some studies reported a decrease of Firmicutes in
IBD patients, in particular the butyrate-producing Roseburia
hominis and Faecalibacterium prausnitzii.40, 41 Conversely,
Proteobacteria, particularly Escherichia coli,40, 42 are com-
monly increased in patients with IBD, whereas the implication
of some pathogenic bacteria, such as Mycobacterium avium
paratuberculosis (MAP), adherent invasive Escherichia coli
(AIEC), Clostridium difcile, Campylobacter, and Salmonella,
is still controversial.39 In addition, CD patients also showed a
higher proportion of fungi compared with bacteria, with an
increased Basidiomycota:Ascomycota ratio, a decreased propor-
tion of Saccharomyces cerevisiae, and an increased abundance
of Candida albicans.43, 44 However, whether the dysbiosis has a
causative role in the onset of the inammation that drives IBD
development or inammation arises independently and leads to
dysbiosis is a matter of ongoing debate.39, 45
Irritable Bowel Syndrome
IBS is a chronic disorder characterized by abdominal pain
related to defecation or changes in bowel habits.46 Several anal-
yses reported a global prevalence of 14% among females and
9% among males.47 IBS is commonly categorized into subtypes
according to the predominant bowel habit: diarrhea-predomi-
nant, constipation-predominant, or mixed/alternating.46 Several
factors seem to be involved in the development of IBS: visceral
hypersensitivity, altered brain-gut signaling, immune dysreg-
ulation, psychosocial factors, and microbiota modication.48
However, most IBS patients report symptoms being triggered
by specic foods; this causes them to limit or exclude these food
items, with consequent changes in dietary habits for the manage-
ment of IBS.49 IBS patients often show an increase in Firmicutes,
particularly unclassied Clostridium cluster IV and XIV, known
SCFA producers.50 Abnormal levels of butyrate can promote vis-
ceral hypersensitivity and atypical intestinal contractions, which
are the primary clinical manifestations of IBS.50, 51 Moreover,
higher levels of mucin-degrading bacteria, such as Ruminococcus
torques and Akkermansia muciniphila, were found. These spe-
cies can degrade the intestinal mucus barrier and therefore may
explain the gut inammatory status in these subjects.50
Microbiome anddiet
The gut microbiome may be inuenced by several factors,
among which diet may be considered the most important. The
long-term habitual diet seems to be the primary factor inu-
encing the gut microbiota. Several recent studies focused on
the co-evolution between humans and their gut microbiota to
understand to what extent the Westernization of diet and life-
style have impacted our microbial symbionts and how this has
affected human health. To this end, it is fundamental to study
rural and traditional African or South American populations,
whose lifestyles likely resemble those of Paleolithic or Neolithic
humans.14, 52–54 Consistent differences in the gut microbiome have
been found. Westernization induced a loss of microbial diver-
sity and the disappearance of specic taxa, with consequent
reduction in the capability to degrade complex polysaccharides
and to produce benecial metabolites from ber utilization.55
Agrarian populations around the world, habitually consuming
a diet rich in fruit, vegetables, and brous tubers and lacking
in animal products, often show an enrichment in ber-degrad-
ing bacteria, such as Prevotella, Lachnospira, Treponema, and
Xylanibacter.14, 52, 54 These changes in gut microbiota compos-
ition are reected in its functionality. Indeed, agrarians also
showed a different metabolome compared with Western sub-
jects, with higher levels of benecial metabolites of microbial
origin, for example, SCFA.14, 52, 54 Consistently, the consumption
of a diet rich in ber in Western subjects (vegetarian/vegan or
Mediterranean-style diet) promotes higher levels of Prevotella
and Lachnospira in the gut microbiota, boosting the production
of benecial SCFA.56 Nevertheless, studies also highlighted the
possibility of inducing changes in the gut microbiome through
a dietary intervention, although these changes are often tran-
sitory, and the gut microbiota tends to revert to the original
condition.57 The possibility of modulation of gut microbiota
composition and activity through ad hoc dietary interventions
is not only fascinating but also a promising research avenue in
the prevention and treatment of disease.
DIET, GUT MICROBIOTA, AND IBDIBS
TREATMENT
Several studies conrmed an association between high
animal protein and fat intake and increased risk of develop-
ing IBD, both in children and in adults,45, 58 whereas a diet rich
in olive oil, sh, vegetables, fruits, grains, and nuts has been
inversely associated with CD in children.59 Moreover, several
recent studies showed a protective role of breastfeeding against
the risk of IBD in pediatric patients, although the mechanism
is largely unclear.60
Based on the dietary recommendations of the National
Institute for Health and Care Excellence (NICE) and the
British Dietetic Association,61, 62 the “traditional” IBS diet is
based on “healthy eating,” reducing fats, caffeine, and excessive
ber intake, and avoiding soft drinks and gas-producing foods.
Furthermore, patients are advised to eat slowly and to chew
meticulously.61, 62
Several dietary therapies have been proposed for the
treatment of IBD/IBS patients or symptom relief; these have
been extensively and recently reviewed.45, 63 However, their ef-
cacy is still controversial, and little is known about the effects
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Dietary Interventions to Modulate the Gut Microbiome
of these dietary treatments on the gut microbiome and thus on
human health.
Specic CarbohydrateDiet
SCD is based on the restriction of complex carbohy-
drates and the exclusion of rened sugars from the diet, based
on the rationale that the sugars and complex carbohydrates are
badly absorbed and could promote intestinal inammation.64
SCD may contain almond, nut, and coconut ours and exclude
grains (wheat, rice, corn); most dairy products are avoided,
except for homemade yogurt fermented for 24 hours to deplete
lactose. Two retrospective studies that assessed SCD as the sole
method of treatment in CD children showed that the use of
SCD for 5 to 30months had positive effects on inammatory
markers and clinical presentation of the disease. The direct
reason for the improvement was not known, but modication
of the intestinal microbiome was proposed as one of the rea-
sons.65, 66
Exclusive Enteral Nutrition
Exclusive enteral nutrition (EEN), is likely to have sub-
stantial effects on gut microbiota, in part due to carbohydrate
composition. EEN therapy with elemental, semi-elemental,
or polymeric formula diets has been widely studied; it is the
only dietary intervention that induced remission of Crohn’s
disease and is therefore the rstline therapy in many parts of
the world. In addition to reducing symptoms, EEN has been
associated with mucosal healing, which may be a superior pre-
dictor of long-term outcome.67 The results about the effect of
EEN on gut microbiota are still preliminary and conicting.
Lewis and coworkers44 showed that EEN induces changes in the
gut microbiome of CD children, but these changes did not lead
to a microbiome resembling that of healthy controls, whereas
Shiga and collaborators68 reported a reduction of Bacteroides
fragilis group, commonly found in inammatory lesions of
CD patients. Markers commonly associated with health, such
as microbial diversity or abundance of butyrate-producing
microbes (eg,, Faecalibacterium prausnitzii) and butyrate levels
were decreased during EEN intervention.69, 70 Another inter-
esting observation was the higher efcacy of EEN in ileal CD
compared with colonic CD or UC.71 However, identifying the
exact role of the diet is hampered by interindividual variabil-
ity in the microbial community and response to intervention.
The role of specic bacteria in disease improvement is yet to be
conrmed, as conicting data have been reported on the protec-
tive effect of Faecalibacterium prausnitzii and other microbes in
pediatric patients.72, 73
Low-FODMAPsDiet
A recent dietary strategy proposed for IBD/IBS man-
agement is the low–fermentable oligo-, di- and monosaccha-
rides and polyols (FODMAPs) diet.45, 63, 74 Diets rich in highly
fermentable but poorly absorbed short-chain carbohydrates
and polyols are hypothesized to trigger symptoms in patients
with IBS.75 The digestibility of carbohydrates varies according
to the absence, or reduced production, of hydrolase enzymes
needed for their digestion. When these sugars arrive undigested
in the colon, they cause an osmotic effect that attracts water
in the small intestine. Moreover, they can be fermented by the
colonic microbiota, with accumulation of gases, including
hydrogen and methane. Both water and gas increase intestinal
volume, which, together with visceral hypersensitivity, causes
pain. However, other mechanisms are evoked in the injurious
effect of FODMAPs. Indeed, these molecules seem to increase
GI motility, which further reduces absorption and increases
potential colonic fermentation.76 A low-FODMAPs diet can
reduce the production of SCFAs as a result of limited avail-
ability of fermentable substrates and decreased levels of taxa
involved in SCFA production.77 Because SCFAs induce vis-
ceral hypersensitivity, the decrease in their luminal levels may
represent another mechanism accounting for the efcacy of a
low-FODMAPs diet.78, 79
FODMAPs might be considered “fast food” for bac-
teria and can lead to the expansion of specic bacterial pop-
ulations in the distal small intestine. This bacterial overgrowth
is similar in patients with IBS, celiac disease, and Crohn’s dis-
ease.80, 81 Bacterial overgrowth in the small intestine has been
associated with increased small intestinal permeability. Fructo-
oligosaccharides increase intestinal permeability also in the
colon, and in rats experimentally infected with Salmonella,
FODMAPs predispose to severe colitis, in comparison with a
mild colonic inammation occurring in controls.82 It is worth
emphasizing that rapidly fermentable ber compromises the
proximal large bowel, whereas concurrent ingestion of slowly
fermentable or nonfermentable substrates decreases the rate
of fermentation, shifting it more distally in the colon.83 This
mechanism could also be explained by the different localiza-
tion of the inammatory processes. Hence, the pathogenic
hypothesis of inammation development in IBD considers an
initial increase in fermentable sugar (eg,, FODMAPs) con-
sumption, which determines bacterial overgrowth and a con-
sequent increase in intestinal permeability. Bacterial or antigen
translocation triggers an immunologic response and acti-
vation of the inammatory cascade. Data from the literature
suggest that a low-FODMAPs diet decreases gut symptoms in
IBD and IBS patients, also promoting a shift in the gut micro-
biota.45, 48, 83 In a single-blind randomized clinical trial (RCT) in
patients with IBS, a low-FODMAPs diet promoted an increased
richness of Actinobacteria, Firmicutes, and Clostridiales
and a decreased abundance of bidobacteria compared with
a high-FODMAPs diet.83 In the same study, a higher abun-
dance of the hydrogen-consuming genus Adlercreutzia was
found in the low-FODMAPs group, possibly contributing
to a reduction of symptoms, due to the consumption of the
accumulated gas in the intestine.83 Consistently, another study
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reported a decreased proportion of bidobacteria in patients
with IBS after a low-FODMAPs diet.75 In patients with Crohn’s
disease, FODMAPs intake is also associated with changes in
fecal microbiota. Indeed, an Australian diet rich in FODMAPs
boosted the levels of butyrate-producing Clostridium cluster
XIVa and mucus-associated Akkermansia muciniphila. This diet
seems to increase IBS-like symptoms.75 Moreover, Chumpitazi
and coworkers84 observed that children with IBS showing a
positive response to a 2-day low-FODMAP intervention had
higher baseline abundance of Sporobacter and Subdoligranum
and decreased Bacteroides compared with nonresponders.
Modulation of FODMAPs intake seems to be a promising
strategy for treating abdominal symptoms in patients with
IBD and IBS. However, potential hazards do exist, such as the
decrease in bidobacteria and other ber-degrading bacteria,
recognized for their health-promoting benets, along with the
consequent reduction of benecial SCFA levels.85 Therefore,
the routine utilization of this strategy for IBD/IBS treatment
should be applied carefully, ideally coupled with gut microbiota
monitoring, to avoid induction of dysbiosis. Considering these
factors, the addition of probiotics during a low-FODMAPs
diet may be a possible solution to optimize clinical manage-
ment and prevent the detrimental effects of a low-FODMAPs
diet on the gut microbiome.
PERSONALIZED NUTRITION AND GUT
MICROBIOME
Key Factors in a Dietary Intervention for
Personalized Clinical Applications
Clinical interventions cannot be based solely on clinical
experience and observational studies but need to be based on
evidence provided by RCTs.86, 87 Despite their cost and labor-in-
tensiveness, RCTs are the most valid research design for evi-
dence-based medicine; nutrition is a eld in need of better
clinical research.88 This gap is the focus of the European Clinical
Research Infrastructures Network (ECRIN) Integrating
Activity (IA; http://www.ecrin.org/activities/projects), which
has identied barriers to good clinical research and offered
solutions to improve evidence-based clinical practice.89–91
Critical Factors in Nutritional Studies
The main difculty in identifying a causal relationship
between the consumption of a specic diet, food, or nutrient
and a health outcome is the coexistence of several factors that
interact and may possibly lead to biased results if not appropri-
ately considered. These factors include population characteris-
tics and lifestyle; the bioavailability of the nutrient (which is in
turn inuenced by aspects related to the technology of produc-
tion and method of consumption); the timing, frequency, and
duration of nutrient exposition; and contextual factors (eg,,
foods, supplements, medications, and diseases that can aid or
hinder absorption).
Therefore, to demonstrate a causal relationship of a
specic nutrient/diet on a health outcome, a multidisciplinary
and multisystem approach is necessary. This approach requires
simultaneously considering nutrition, genetics, the microbi-
ome, and environment (exposome) in the implementation of
nutritional intervention studies, as was recently suggested in
an epidemiological study.92 This strategy could have multiple
spillover effects, including being able to explain and overcome
the discrepancies present in the scientic literature for the ef-
cacy of some nutrients/diets, achieving stronger evidence and
consensus in the scientic community, and producing practical
and valuable applications in the elds of personalized nutri-
tion, preventive and precision medicine, and functional food
development.
Critical factors in the implementation of nutritional
intervention studies and opportunities beyond nutrition are
summarized in Figure1; a systems-based approach could work
in nutritional interventions and specically in nutritional RCTs.
The scheme highlights 4 critical points in RCTs, namely, study
design, subjects, biomarkers, and data analysis. Each of them
must be carefully considered during the implementation of the
trial tailored to nutrient/diet and targeted health outcomes.
Studydesign
The type and form of nutrient, whether provided as a
supplement or included in a food, can considerably inuence
the study design. Indeed, in the case of a supplement, a placebo
(a pill/powder/tablet/liquid similar to the experimental one but
without the putative bioactive compound) can be provided and
a double-blind trial (which is the gold standard design because
it guarantees the blinding of both subjects and investigators)
can be performed. Conversely, in the case of a nutrient included
in a food or a diet, nding the correct control intervention can
be a remarkably critical point. This affects the study design and
the data analysis. In the frame of study design, blinding can be
compromised because, without a placebo, a double-blind trial
is impossible and the dose/frequency of food consumption and
the duration of the intervention must be carefully considered
in view of the bioavailability of the putative bioactive nutrient
in the food.
Sample size calculation and studypower
Power analysis for sample size calculation is usually car-
ried out based on variations in clinical parameters. Calculating
sample size based on microbiome features, although possible,
may often be impracticable, as we do not know the effect that
a specic dietary intervention may have on the complex con-
sortium of gut microorganisms, with diverse taxa responding
in different ways to the treatment. Focusing on the abundance
of only a few taxa may be also unsuccessful. Moreover, due
to the high interpersonal variability in gut microbiome com-
position, the resulting sample size would be excessively high,
making the study unfeasible. As many of the studies found
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Dietary Interventions to Modulate the Gut Microbiome
in the literature are based on a small number of subjects, the
effects on the microbiome may be hidden by high interpersonal
variability, and this may explain the often inconclusive results
obtained in terms of the modulatory effect on the microbiome.
Tools for sample size calculation in microbiome studies have
been recently developed; however, their use remains limited.93, 94
Subjects selection
Subjects’ characteristics, such as age, nutritional and
health status, genetics, the gut microbiome, and behavioral
and lifestyle factors may enormously inuence the metabolic
response and the health effect of a nutrient/diet. Thus, having
clear and strict inclusion and exclusion criteria in RCTs may
allow investigators to have interventions with smaller numbers
of subjects while maintaining a good power of the study to
reduce costs and time of the trials and to enhance the probabil-
ity of clarifying the mechanisms underlying the health effect.
The latter aspect is also inuenced by biomarkers of effective-
ness monitored during the study. In the case of clinical trials
involving patients, the evaluation of markers of the specic
FIGURE1. Critical factors in the implementation of nutritional intervention studies and opportunities beyond nutrition. Randomized clinical trials
represent the gold standard to achieve evidence-based medicine. Eective nutritional RCTs must be tailored to the specic nutrient/diet and health
outcome of interest. The scientic validity of evidence achieved by RCTs depends on the critical management of 4 main points, namely study design,
subjects, biomarkers of responsiveness, and data analysis. Numerous factors coexist and interact between each other to inuence the eect of nutri-
ent/diet on a specic health outcome. These factors mainly include population characteristics and lifestyle, dose and bioavailability of the nutrient,
timing, frequency, and duration of nutrient exposition, and contextual factors. Due to the involvement of the gut microbiome in the ne interplay
between nutrient/diet-subjects-health, its consideration at multiple steps of RCTs (ie, at selection of subjects, biomarkers, and data analysis) may
be crucial. The proper consideration and management of all the critical factors allows scientists to achieve evidence that can nd application in the
elds of personalized nutrition, preventive and precision medicine, and functional food development.
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disease under investigation is necessary. In addition, other bio-
markers that are usually considered in subjects at a predisease
stage may also be monitored. These include inammatory,
nutritional, and metabolic biomarkers, and gut microbiota
composition. Most belong to the ne net of signaling medi-
ators involving the metabolic, neuroendocrine, and immune
systems; orchestrating the response to a nutrient/diet; and the
organ-by-organ communication and homeostasis processes
within the body.11, 95, 96 Finally, to monitor changes in the gut
microbiome, antibiotic or probiotic assumption should be con-
sidered as an exclusion criterion, or, when this is not possible
(eg, when intervention is addressed to patients), investigators
should consider it a possible confounding factor.
Biomarker evaluation and data analysis
In the frame of data analysis, the evaluation of individ-
ual compliance is the critical factor. Indeed, in the presence of
a supplement/placebo, the count of not-consumed doses may
be sufcient, whereas in the case of a food/diet-based interven-
tion, the evaluation of individual dietary intake (through food
frequency questionnaires, 24-hour recall, weighed food record,
etc.) or biomarkers of food/diet intake in biological uids
(through metabolomics analysis) is necessary. Although univo-
cal biomarkers of intake have not been recognized for many
foods, metabolomics of biological uids is inestimably valuable
for RCTs because it can show the impact of the intervention on
individual nutrient metabolism in relation to the subjects’ char-
acteristics being considered in the study. This aspect is funda-
mental in targeted nutrition and medicine. Mounting evidence
shows that through metabotyping—that is, grouping metabol-
ically similar individuals—personalized nutritional and phar-
macological strategies may be achieved.92, 97 On the other hand,
the approach of grouping similar individuals for some features
can be applied in RCTs both at the stage of subject selection
and during data analysis.
Overall, a multisystem approach in clinical trials is the
most valuable way to achieve evidence-based medicine and to
reduce the gap currently existing between research and clin-
ical ndings with possible practical applications in the elds of
personalized nutrition, preventive and precision medicine, and
functional food development.
Dietary Interventions for the Modulation of the
Gut Microbiome
Several studies highlighted the effect of a dietary inter-
vention on the gut microbiome, focusing on the addition of a
specic supplement to the diet (mainly different types of diet-
ary ber) or administering diets enriched in carbohydrates, pro-
teins, or fats (Table1). Adding prebiotic ber to the diet may
lead to the enrichment of ber-degrading bacteria in the gut
and improved metabolic health, but results reported in the cur-
rent literature have been conicting. Studies are often limited to
a small number of subjects (20 per treatment group or fewer in
many cases) (Table1).
Moreover, comparison of results across studies is not
always possible, as many confounding factors exist, making
it necessary to have standardized procedures for sample col-
lection, storage, and subsequent analyses,115 such as those
proposed by the International Human Microbiome Standard
Consortium (http://www.microbiome-standards.org).
Although host genomics may also be implicated, inter-
subject variation in gut microbiota composition may explain
the different metabolic responses observed with the same treat-
ment. Interpersonal differences in response to the same type of
drug have been often observed in therapeutic routines. The gut
microbiome may be involved in this process through bio-trans-
formation of bioactive compounds contained in administered
drugs, reducing or sometimes enhancing their effects.10, 116
Statins, commonly used to reduce plasma low-density lipopro-
tein (LDL) levels, are an example of microbiome-driven person-
alized response to drugs. Indeed, subjects positively responding
to statin treatment showed increased levels of specic secondary
bile acids of microbial origin.10 Therefore, the design of thera-
peutic treatments should consider personalized microbiome
features and their effects on drug metabolism, toxicity, and ef-
cacy. Accordingly, recent studies highlighted that subject-spe-
cic gut microbiome traits cannot be disregarded if diet must
be used to benecially modulate microbiome activities for ther-
apeutic approaches (Fig.2). Indeed, the gut microbiota may
be responsible for unpredictable results in intervention studies.
Features of the gut microbiome before starting the intervention
(eg, overall microbial diversity or abundance of specic taxa,
such as Prevotella copri or Akkermansia muciniphila) were pre-
viously suggested to be discriminant factors between subjects
showing a metabolic improvement (eg, decrease in LDL chol-
esterol, inammatory markers, or insulin resistance) to a diet-
ary intervention and those who were not benecially impacted
(Fig.2). For example, 3-day consumption of barley kernel ber
led to improved glucose metabolism, reducing postprandial gly-
cemic response (PPGR) and insulin, but only in a subset of the
cohort studied.108 Separating responders from nonresponders,
the authors observed higher Prevotella copri concentrations in
responders. Moreover, gavaging mice with live P.copri cells, they
conrmed the positive effect exerted on glucose metabolism,
possibly due to a promotion of hepatic glycogen storage.108 In
contrast, Pedersen and coworkers117 suggested that P.copri may
be responsible for branched-chain amino acid production and
induce insulin resistance, demonstrating that the association
of a whole microbial genus or species with a specic metabolic
outcome may be an oversimplication.118, 119
Indeed, it must be noted that high variability at the strain
level exists in the gut microbiome, and in any other complex
environment, although this point was largely overlooked until
recently. Every species may be represented by several different
strains, with intersubject variability.120 Strains belonging to
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TABLE1: Main Clinical Trials Assessing the Gut Microbiome and Metabolic Responses After Dietary Intervention
Study
Intervention Population Outcomes
Description No. Description Microbiota Bioclinical Variables
Bennet etal.,
201798
4 weeks of low-FODMAPs
or traditional IBS
67 IBS patients
BMI 24.0±6.0kg/m2
17% male
No change in the microbiota
after traditional IBS diet both
in responders and nonrespond-
ers; >Bacteroides stercoris,
Ruminococcus gnavus, Dorea,
and several Enterobacteriaceae
at baseline in nonresponders
compared with responders to
low-FODMAPs diet
Decrease in IBS symp-
toms Severity score
≥50 in responders
Candela etal.,
201699
3 weeks of macrobiotic diet
(Ma-Pi; enriched in ber,
hypocaloric) or control diet
with the same energy intake
40 Type 2 diabetes
BMI 34.3±6.5kg/m2
50% male
>Akkermansia, Ruminococcus,
Faecalibacterium, Blautia after
both the dietary intervention;
<Collinsella, Streptococcus, and
>Akkermansia after Ma-Pi com-
pared with control diet
Decrease of postpran-
dial glucose, LDL
cholesterol, insulin
resistance, inamma-
tory markers after
Ma-Pi diet
Chumpitazi
etal., 2015100
2days of low-FODMAPs or
typical American diet
33 IBS pediatric patients
(age 7–17years)
BMI and sex not
provided
>Bacteroides, Ruminococcaceae,
Dorea, Faecalibacterium praus-
nitzii at baseline in responders
Decrease in abdominal
pain and gastroin-
testinal symptoms in
responders
Costabile etal.,
2008101
3 weeks of supplement with
48g of whole grain (WG)
or wheat bran
31 BMI 25.0±5.0kg/m2
48% male
>Bidobacterium, Lactobacillus
after WG
Increase of phenolic
acids in WG, no
changes in blood
lipids, cholesterol, glu-
cose, insulin
Cotillard etal.,
2013102
6 weeks of hypocaloric,
high-protein diet
(1200 and 1500 Kcal/d for
men and women, respec-
tively); 6 weeks of stabi-
lization diet (20% caloric
increase)
49 BMI 33.2±0.5kg/m2
16% male
Divided into low (LGC;
n=20) and high
(HGC; n=29) gene
count
>diversity in LGC after the dietary
intervention
Decrease of insulin
resistance, triglycer-
ides, inammatory
markers in HGC after
intervention
Dao etal.,
2016103
6 weeks of hypocaloric,
high-protein, low-carbohy-
drate diet enriched in ber;
6 weeks of weight mainte-
nance diet
49 BMI 32.5±1.0kg/m2
17% male
Divided into high
(HAk; n=25) and
low (LAk; n=24)
Akkermansia mucin-
iphila abundance
<Akkermansia muciniphila after
the intervention in HAk but still
higher than LAk
Higher decrease of LDL
cholesterol, plasma
glucose, tryglycerides,
insulin resistance in
subjects with higher
baseline levels of
Akkermansia (HAk)
Hald etal.,
2016104
4 weeks of Western-style diet
or high-carbohydrate diet
(enriched in arabinoxylan
and resistant starch)
19 BMI 30.0±2.0kg/m2
Sex not provided
>Bidobacterium and
<Bacteroides, Odoribacter,
Desulfovibrionaceae,
Ruminococcus (Lachnospiraceae)
-
Haro etal.,
2016105
12months of Mediterranean-
style diet (MD; 35 fat—
22% monounsaturated;
6% polyunsaturated and
7% saturated) or low-fat,
high-carbohydrate diet
(LFHCD; 28% fat—12%
monounsaturated; 8%
polyunsaturated and 8%
saturated)
20 BMI 32.2±0.5kg/m2
100% male
>Roseburia, Oscillospira, and
<Prevotella in MD
>Prevotella, Faecalibacterium
prausnitzii, and <Roseburia in
LFHCD
Increase of insulin sensi-
tivity in both MD and
LFHCD
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De Filippis etal
Study
Intervention Population Outcomes
Description No. Description Microbiota Bioclinical Variables
Hjorth etal.,
2017106
6months of ad libitum New
Nordic Diet (NDD; rich in
fruit, vegetables, and whole
grains) or Average Danish
Diet
62 BMI 30.0±1.0kg/m2
33% male
Divided into high
(n=28) and low
(n=34) Prevotella-
to-Bacteroides ratio
groups
- Higher body fat and
waist circumference
loss after NDD in
high Prevotella-to-
Bacteroides group
Korem etal.,
2017107
1 week of supplement with
145g/d of sourdough-leav-
ened whole grain bread
or 110g/d of industrial
white bread, separated by 2
weeks of washout
20 BMI 27.9±4.0kg/m2
45% male
No effect detected Interpersonal varia-
tion in the glycemic
response after bread
consumption is
dependent on baseline
microbiome features
Kovatcheva-
Datchary
etal., 2015108
3days of supplement with
barley kernel bread (BKB)
or white bread
20 BMI 25±3.0kg/m2
10% male
Divided into responders
(n=10) and non-
responders (n=10)
based on metabolic
response to BKB
intervention
>Prevotella in responders com-
pared with nonresponders;
>Prevotella copri and methano-
genic Archaea after BKB inter-
vention only in responders
Decrease of postpran-
dial blood glucose
and insulin after BKB
intervention only in
responders
Louis etal.,
2016109
3months of very low-calorie
diet (800 Kcal/d, enriched
in inulin); 9months of
gradual reintroduction of a
normal diet; 12months of
weight maintenance diet
16 BMI 43.0±7.0kg/m2
44% male
Persistent success group
(PS; >10% weight
loss after 24months,
n=9); no persistent
success (NS; <10%
weight loss after
24months, n=7)
Different microbiota at baseline in
PS and NS groups
>Akkermansia, Alistipes,
Clostridium leptum, and
<Bacteroides in PS at baseline
Only Akkermansia stable after
2years
Decrease of insulin
resistance
Pedersen etal.,
2016110
12 weeks of supplement with
galacto-oligosaccharyde
mixture or placebo
29 Type 2 diabetes
BMI 28.0±6.5kg/m2
100% male
No effect detected No effect detected
Roager etal.,
2017111
8 weeks of intervention with
a whole grain–enriched diet
and 8 weeks of intervention
with a rened grain diet,
separated by a washout
period of 6 weeks
60 High risk of metabolic
syndrome
BMI 25–35kg/m2
Sex not provided
>Faecalibacterium prausnitzii and
Prevotella copri after whole grain
diet
Bacteroides thetaiotaomicron
increased after rened grain diet
Decrease of inamma-
tory markers
Weight loss
Vanegas etal.,
2017112
2 weeks of run-in consum-
ing a Western-style diet,
followed by 6 weeks of
weight-maintaining diet
supplemented with 8g/1000
Kcal of rened grains (RG)
or 16g/1000 Kcal WG
81 BMI 26±0.47kg/m2
63% and 59% male
in RG and WG,
respectively
>Lachnospira, Roseburia, and
<Enterobacteriaceae after WG
intervention compared with RG
No effect on inam-
matory and immune
markers
Vitaglione etal.,
2015113
8 weeks of WG (70g/d) or
rened grain (RF; 60g/d)
68 BMI 30±0.9kg/m2
31% and 37% male in
WG and RF groups,
respectively
>Prevotella and
<Dialister, Bidobacterium,
Blautia, Collinsella in WG
Decrease of inamma-
tory markers, increase
of phenolic acids
Walker etal.,
2011114
1 week of weight mainte-
nance, 3 weeks of non-
starch polysaccharides,
followed by 3 weeks of
resistant starch (RS) and
3 weeks of high-protein,
hypocaloric diet
14 BMI 39.4±1.5kg/m2
100% male
>Eubacterium rectale,
Ruminococcus bromii in RS
-
TABLE1: Continued
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Dietary Interventions to Modulate the Gut Microbiome
the same species may harbor a signicantly different genomic
repertoire and may respond in different ways to dietary com-
ponents,118, 119 making it even more difcult to demonstrate a
causative role of diet in the modulation of the gut microbiome.
Different subjects may have distinctive metabolic
responses to the same food. Subjects with a higher Prevotella-to-
Bacteroides ratio (P/B) had higher weight loss after consuming
a 6-month high-ber diet compared with the low P/B group,106
whereas Dao and coworkers103 observed that obese subjects
with higher levels of Akkermansia muciniphila showed better
metabolic outcomes (lower insulin resistance, LDL choles-
terol) compared with those with a lower baseline concentration
of this microbe, when treated with a hypocaloric, high-pro-
tein and -ber diet (Table1). In addition, it was demonstrated
that a meal cannot be considered “good” for everybody.121 The
authors integrated gut microbiota features with anthropomet-
ric and metabolic measures, dietary habits, physical activity,
and lifestyle in a machine-learning algorithm that accurately
predicted personalized PPGR to real-life meals. This predictive
strategy was then used to personalize dietary intervention and
modify postprandial glucose response. They demonstrated that
baseline microbiota composition may be implicated in the sub-
ject-specic response to a dietary intervention and that consid-
ering these differences may help in designing tailored meals for
improving metabolic health.121 Accordingly, the same authors
suggested that the glycemic index of a food alone cannot always
be useful in predicting the glycemic response. They found the
PPGR to white or whole grain bread to be person-specic and
used microbiome composition to predict which type of bread
resulted in the best glycemic response.107 Indeed, subject-spe-
cic signatures in the gut microbiome may be responsible for
weight regain after a dietary intervention, and the extent of
such regain may be predicted by integrating gut microbiome
features in a machine-learning algorithm.122
Although many studies focused on the administra-
tion of specic food supplements, the habitual consump-
tion of a healthy and diverse diet, such as that based on the
Mediterranean model, is recognized to shape the gut micro-
biome and to promote the production of benecial metabo-
lites.56 Although with a limited number of subjects, Haro and
coworkers105 demonstrated that dietary treatment for 1year
with a Mediterranean-style diet improved insulin sensitivity
and increased the abundance of SCFA-producing microbes
(Table1). These examples suggest that following a healthy and
diverse dietary pattern and lifestyle can contribute to main-
taining a “healthy” microbiome without necessarily adopting
microbiome-targeted nutritional interventions.
Most of the studies available on targeted dietary modu-
lation of the gut microbiome have focused on metabolic disor-
ders (Table1). However, the same approach may be useful for
FIGURE2. Subject-specic gut microbiota features may aect the response to a dietary intervention. The metabolic response to a dietary interven-
tion is person-specic, and the same type of food or dietary pattern may produce dierent eects. Dividing responders and nonresponders, recent
studies showed dierences in gut microbiota composition and that this may be the cause of the personalized response to a dietary intervention,
thus highlighting the necessity of personally tailored nutrition based on gut microbiota composition for therapeutic and preventive purposes.
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Inflamm Bowel Dis
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De Filippis etal
other pathologies, such as IBD and IBS. Indeed, Bennet and
coworkers98 found different baseline microbiota composition in
adult IBS patients responding or not to a low-FODMAP diet
(ie, showing a decrease of the IBS Symptoms Severity Score).
Nonresponders had higher baseline abundance of several taxa,
eg, Bacteroides stercoris, Pseudomonas, Acinetobacter, and
Ruminococcus gnavus, compared with responders. Baseline
microbiota features were implemented in a Random Forest
model, which was used to predict the probability of a posi-
tive response to the dietary treatment. This pioneer study rst
highlighted the possibility to choose the most appropriate diet-
ary treatment for IBS patients, based on their gut microbiota
composition.
Based on these observations, it is plausible that in the near
future, subjects will be stratied based on their gut microbiome
features and study enrollment will be performed considering
their baseline microbiome. As we know some associations of
specic microbial genera/species with diet and/or diseases, we
can speculate on the possibility of stratifying subjects accord-
ing to the abundance of microbial taxa recognized for certain
functional activities (eg, ber-degrading) or for the production
of benecial/detrimental metabolites. Although considering
the microbiota as a stratication factor for subject enrollment is
promising, several issues arise, including increased enrollment
costs and the intrasubject variability of the gut microbiota even
in a short time frame. The possibility of stratifying the study
population a posteriori for the similarity of the microbiome
or microbial metabolite prole during data analysis is also an
alternative. Nevertheless, it must be pointed out that these sec-
ondary analyses do not preserve the benets of randomization.
In addition, such stratications are less likely to be reproduci-
ble due to the risk of chance ndings related to multiple test-
ing. Despite the abovementioned limitations, modulating and
manipulating the gut microbiome with a personally designed
dietary intervention to induce changes in its composition and
functions is surely a promising application for both therapeutic
and preventive clinical strategies.
CONCLUSIONS
Microbiome-targeted dietary interventions constitute a
powerful and tantalizing tool for the prevention and treatment
of different diseases. We are still quite far from microbiome-tar-
geted precision medicine, but we are surely on the right scien-
tic path to developing an exhaustive set of tools and clinical
knowledge to ll the current gaps. Personalized nutrition based
on microbiome features is currently being attempted, although
its real impact and benets suffer from the aforementioned lim-
itations. Most of the studies available are observational, and
controlled clinical trials targeting the microbiome are still too
scarce to draw denitive conclusions or to propose a stand-
ardized protocol for modulating the gut microbiome through
the diet for therapeutic purposes. Future intervention studies
will surely provide new knowledge and will help in overcoming
the current issues associated with such types of interventions.
Indeed, interindividual variations in gut microbiome compos-
ition and functions, along with the need to study the effect of
dietary changes on microbiome functions at the strain level,
make the use of such interventions still only exploratory in clin-
ical practice.
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