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Development of the Gut Microbiome in Children, and Lifetime Implications for Obesity and Cardiometabolic Disease

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Emerging evidence suggests that microbiome composition and function is associated with development of obesity and metabolic disease. Microbial colonization expands rapidly following birth, and microbiome composition is particularly variable during infancy. Factors that influence the formation of the gut microbiome during infancy and childhood may have a significant impact on development of obesity and metabolic dysfunction, with life-long consequences. In this review, we examine the determinants of gut microbiome composition during infancy and childhood, and evaluate the potential impact on obesity and cardiometabolic risk.
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children
Review
Development of the Gut Microbiome in Children,
and Lifetime Implications for Obesity and
Cardiometabolic Disease
Anica I. Mohammadkhah 1, , Eoin B. Simpson 1 ,† , Stephanie G. Patterson 2and
Jane F. Ferguson 1, *
1Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN 37232, USA;
anica.i.mohammadkhah.1@vanderbilt.edu (A.I.M.); simpsone@tcd.ie (E.B.S.)
2Division of Critical Care Medicine, Department of Pediatrics, Vanderbilt University Medical Center,
Nashville, TN 37232, USA; stephanie.g.patterson@vumc.org
*Correspondence: jane.f.ferguson@vanderbilt.edu; Tel.: +1-615-875-9896
These authors contributed equally to this work.
Received: 23 October 2018; Accepted: 22 November 2018; Published: 27 November 2018


Abstract:
Emerging evidence suggests that microbiome composition and function is associated with
development of obesity and metabolic disease. Microbial colonization expands rapidly following
birth, and microbiome composition is particularly variable during infancy. Factors that influence the
formation of the gut microbiome during infancy and childhood may have a significant impact on
development of obesity and metabolic dysfunction, with life-long consequences. In this review,
we examine the determinants of gut microbiome composition during infancy and childhood,
and evaluate the potential impact on obesity and cardiometabolic risk.
Keywords: microbiome; obesity; cardiometabolic disease
1. Introduction
Chronic cardiometabolic diseases are the leading cause of mortality in the US, with heart disease
and diabetes costing >$500 billion a year [
1
,
2
], and affecting around 60% of individuals over their
lifetime [
1
,
3
]. Many factors contribute to disease risk, including environmental exposures, diet,
and genetic background. Pathogenesis develops over decades, making risk factors that originate
in childhood of particular importance for life-long disease risk. The role of the microbiome as a
disease modulator is being increasingly recognized and studied [
4
,
5
]. The human gut microbiome
may act as a central regulator of metabolism, responsive to alterations in dietary intake or host
physiology [
6
,
7
]. The gut microbiome expands rapidly in infants following birth [
7
,
8
] and dysbiosis in
infancy or childhood may affect the long-term health of the gut microbiome. Within the sections of this
review, and as summarized in Figure 1, we evaluate several of the known determinants of microbiome
composition and examine how variation in microbiome composition in children may impact lifetime
risk of obesity and cardiometabolic disease.
Children 2018,5, 160; doi:10.3390/children5120160 www.mdpi.com/journal/children
Children 2018,5, 160 2 of 20
1
Figure 1.
Determinants of microbiome composition, and potential mechanisms linking microbiota
to disease.
2. Determinants of Gut Microbiome Colonization in Neonates
2.1. Delivery Method
Extensive colonization of the infant microbiome occurs at the time of birth, and may even occur
before birth. Inoculation has stochastic components, with contribution of maternal microbiota, but also
opportunistic colonization by microbiota present on other proximal individuals and in the local
environment. Gut microbiome composition is highly variable in early infancy, and of the strains
that reach the infant gut, only a subset successfully colonize [
7
]. In a study of 25 mother–infant
pairs, the development of the infant microbiome was assessed from birth to 4 months postpartum [
9
].
The early infant microbiome was found to contain maternal vaginal, skin, oral, and fecal strains,
with variability in which site contributed the most, despite all infants being delivered vaginally.
Skin and vaginal transmission appeared to be transient, with the infant gut microbiome having
greatest similarity to the maternal gut microbiome by 4 months post-birth [
9
]. Several studies
have examined the effect of vaginal delivery compared with cesarean section in order to test the
hypothesis that initial exposure to vaginal vs. skin microbiota has long-term effects on microbiome
composition. The intestinal colonization rate of infants delivered by Caesarean has been shown to
be delayed [
10
], with lower bacterial colonization rates in infants delivered by cesarean section [
11
].
Lower microbial diversity has been observed in infants born by Caesarean section, an effect which
may persist for at least two years [
12
]. However, in another sample, diversity was lower in preterm
infants born vaginally compared with cesarean section [
13
], which could potentially be linked to
the additional birth complications for preterm infants. Caesarean section has been associated with
some long-term outcomes, including overweight [
11
,
14
16
], although other studies have found no
differences, and causality has not been established [17,18].
2.2. Preterm Birth
Preterm infants have underdeveloped intestines, which may perturb the development of healthy
host–microbiota relationships early in life [
19
]. Preterm infants are at a much higher risk of developing
complications following birth, including necrotizing enterocolitis (NEC), which may be linked to
impaired gut microbiome acquisition [
20
]. Preterm infants who developed NEC were found to have
increased abundance of Proteobacteria and decreased abundance of Firmicutes and Bacteroidetes [
20
].
There is also evidence that altered maternal microbiome composition may be related to risk of preterm
birth [
21
], suggesting that altered microbiome composition is both a cause and a consequence of preterm
birth. Preterm infants have been shown to have differences in microbiome diversity, dependent on
Children 2018,5, 160 3 of 20
gestational age [
22
]. Dysbiosis in the preterm infant gut has been linked to delivery method, steroid
use, and antibiotic use, all of which affect intestinal microbiome development [13,23,24].
2.3. Pre-Natal Microbial Colonization
Whether maternal transmission of commensal microbes to the fetus is a common occurrence
remains an open question. Until relatively recently, the uterine environment was thought to be
sterile. This assumption has been challenged by several studies finding evidence of microbiota in the
uterus [
25
], placenta [
26
], umbilical cord [
27
], and amniotic fluid [
28
], as well as in meconium [
29
],
indicating that microbiota may be transmitted during fetal development. However, data are
conflicting [
30
,
31
]; microbial DNA may be detected due to contamination, presence of DNA from dead
bacteria, or collection after membrane rupture [
32
], and thus far microbes have not been proven to be
viable in utero. While evidence supports some transmission of microbial material to the fetus, whether
this is a significant contributor to a fetal microbiome, and whether this has an impact on development
or outcomes, remains to be determined.
3. Effects of Early Infant Feeding Practices on Microbiome Development
3.1. Breast Milk and Formula Feeding
It is thought that breast milk feeding is protective against development of multiple diseases,
including obesity [
33
], diabetes [
34
], and potentially also immune-mediated diseases such as asthma
and allergies [
35
]. The mechanism whereby breast milk determines a child’s predisposition to
cardiometabolic and inflammatory disease is yet to be fully determined, but may be mediated
through long-term effects on gut microbiota. In particular, as the sole source of nutrition in the
first 4–6 months of life, the composition of breast milk or formula determines nutrient availability
to gut microbiota in the infant, and may exert selective pressure. A key difference between
breast milk and formula is the presence of prebiotics, oligosaccharides, and antibodies, which can
selectively modulate bacterial abundance [
36
]. Breast milk itself contains microbiota, including
Bifidobacterium,Streptococcus, and Lactobacillus species [
37
39
], which may contribute directly to the
infant gastrointestinal microbiome. However, there is large variability in the composition of human
breast milk [
40
42
], which is modulated by maternal health status [
43
45
]. The composition of breast
milk is dynamic, changing over time, and may be responsive to infant characteristics such as sex [
46
],
or dynamic cues during illness. Whether a “core” group of breast milk components common to most
individuals are responsible for most of the protective effects remains to be determined [
47
]. In preterm
infants, breast milk feeding appeared to mitigate some of the negative consequences of low birth
weight on the development of the microbiome [
48
]. Studies of microbiomes in infants have focused on
specific bacterial abundance, as well as diversity. In one study, breast-fed infants were found to have
greater numbers of Bifidobacterium, but the microbiome of formula-fed infants was more diverse [
49
].
Another study found enrichment of Actinobacteria and Firmicutes and depletion of Proteobacteria in
breast-fed compared with formula-fed infants [
50
]. Formula feeding has been associated with altered
bacterial diversity in infants [
51
], with the microbiota of infants fed both breast milk and formula being
more similar to formula-fed infants than to exclusively breast-fed infants [
33
]. Formula feeding at 3
months was associated with greater risk of overweight at 12 months, defined as infants >85th percentile
for weight for length [
33
]. In a prospective study, children who were overweight at age 7 had lower
Bifidobacterium and higher Staphylococcus aureus colonization in infancy compared with matched normal
weight children [
52
]. Breast milk-derived immunoglobulins have been shown to modulate intestinal
immune function and gut microbiome composition [
53
], providing further evidence for mechanisms
linking breast milk feeding with immunoprotection. In a population at risk of undernutrition, lower
levels of sialylated oligosaccharides in breast milk were found to be associated with stunted infant
growth, and inclusion of sialylated oligosaccharides in the diet of lab animals was associated with
body mass in a gut microbiome-dependent manner [
54
]. Although many more studies are required,
Children 2018,5, 160 4 of 20
these data highlight early infancy as a critical period where microbial dysbiosis may lead to overweight
in later life because the microbiome may be unable to recover from dysbiosis established early in life.
Components in breast milk may shape the infant microbiome to confer lifelong protection against
obesity and other metabolic diseases. However, given the large variability in breast milk composition,
and the potential for interaction with genetic background, there may also be cases where breast milk
promotes less favorable microbiome development.
3.2. Prebiotic and Probiotic Supplementation
The specific composition of different types of formula may modulate the microbiome. Several
trials have assessed the inclusion of probiotics or prebiotics such as oligosaccharides in infant
formula to more closely mimic breast milk composition [
55
]. Infant formula supplemented
with several Bifidobacterium strains altered microbiome composition in infants, but did not affect
long-term colonization [
56
]. There was no significant effect of oligosaccharide and Bifidobacterium
supplementation on diarrhea or febrile infection, however, the microbiota of supplemented infants
more closely resembled that of breast-fed infants [
57
]. Inclusion of lactose in hydrolyzed formula
designed for infants with milk allergies promoted growth of Bifidobacterium and Lactobacillales,
and increased intestinal short chain fatty acids (SCFAs) [
58
]. Lactobacillus supplementation was
found to alter gut microbiome composition [
59
]. Current data suggest that inclusion of pre- and
probiotics in formula is well-tolerated, however, whether this has beneficial effects on longer-term
outcomes is not yet known.
3.3. Milk Delivery Method
Some evidence exists on different effects of direct breast feeding versus providing expressed
breast milk from a bottle [
60
]. During breast feeding, infants are exposed to maternal skin microbiota,
and also deposit saliva, which contains microbiota and pathogens that can be transmitted back to
the mother, potentially eliciting changes in breast milk composition through a feedback loop [
61
,
62
].
While intriguing, this area requires further research.
3.4. Donor Breastmilk
Because of the potential benefits of breastmilk, donor milk is sometimes used when milk from the
infant’s biological mother is not available. This is particularly promoted in preterm infants. However,
whether donor milk has the same protective properties remains unclear [
63
]. In a randomized trial in
preterm infants, donor milk did not appear to confer an advantage over formula when compared with
maternal milk [
64
]. Donor milk is general pasteurized to reduce risk of infection and is often pooled
from multiple donor sources. Pasteurization may destroy pre- and probiotics, reducing the beneficial
effects of human milk. Further, the variability in breast milk composition may result in donor milk
being suboptimal for an unrelated infant. However, much more research is required to establish the
potential benefits and risks of using donor milk as an alternative to formula.
4. Dietary Modulators of Gut Microbiome Composition throughout Childhood
The introduction of solid food is associated with a shift in the infant microbiome to more closely
resemble adult profiles, however, the pediatric microbiome remains in flux for at least the first 3 years
of life [
7
]. This suggests a period of relatively malleability and implies that diet in early childhood may
have a disproportionately large impact on lifetime microbiome composition and associated health
impacts. In adults, a change in diet significantly affects the composition of their gut microbiome,
with observable major shifts in microbe composition within 24 h of substantial or acute alterations
to the diet, such as suddenly switching to solely plant- or animal-based foods. A near return to the
starting composition can be observed 48 h after resumption of the normal diet [
6
]. Data are limited on
the effect of dietary intervention on the microbiome in children, but given that microbiome profiles in
Children 2018,5, 160 5 of 20
children after the age of 3 years closely resemble those of adults, it is likely that dietary changes can
rapidly affect microbiome composition in children.
4.1. The Effect of Western Diet on the Gut Microbiome
The Western diet, high in animal protein and fat, high in refined carbohydrates, and low in
plant-derived fiber, phytochemicals, and fermented foods has been associated with the relatively
recent rapid rise in inflammatory-related diseases, including cardiometabolic and intestinal disease.
There is increasing evidence that this may be mediated through gut microbiota [
65
,
66
]. The Western
diet has been found to decrease total bacterial load, as well as those of beneficial genera such as
Bifidobacterium and Eubacterium [
67
]. Studies of vegetarian and vegan diets have found varying
levels of differences in microbiome composition compared with the typical unrestricted Western
diet, with potential negligible differences in the overall functional capacity of the microbiota [
68
71
].
A study investigating the impact of the Western and traditional plant-based diet in children in Thailand
found differences in composition and used metagenomic prediction to identify underrepresentation
in genes for butyrate biosynthetic pathways in children consuming a Western diet [
72
], which may
modulate gut immune homeostasis [
73
]. Similarly, children consuming traditional diets in rural
Malawi and Venezuela were found to have differences in metabolic gene content of the microbiome
compared with US children consuming a Western diet [
7
]. In a small study of urban visitors to a
traditional rainforest village, the microbiome of children was found to be more prone to change
compared with a relatively stable microbiome in adults, highlighting the higher plasticity of the
microbiome in children [
74
]. High total protein diets have been linked to increased inflammatory
bowel disease (IBD) risk [
75
]. Pea and whey protein consumption has been linked to increased
levels of commensal Bifidobacterium and Lactobacillus [
76
], with fermented whey protein lowering
counts of potentially pathogenic species Bacteroides fragilis and Clostridium perfringens [
77
]. Several
genera that increase in abundance from ingestion of red meat are associated with higher levels of the
proatherogenic chemical trimethylamine-N-oxide (TMAO), linked to an increase in cardiovascular
disease risk [
78
]. High protein diets in individuals <65 years of age have been related to an increase in
the production of insulin-like growth factor 1, a risk factor for cancers, diabetes, and mortality [
79
].
High fat diets in humans have been shown to increase the relative abundance of anaerobic bacteria
and Bacteroidetes, while low fat diets increase fecal Bifidobacterium counts and reduce total cholesterol
and fasting glucose [
80
]. In mice, there was a significant effect on microbiome composition when
comparing polyunsaturated fat (fish oil) to saturated fat (lard) diets [
81
]. Lard-fed mice had increased
systemic and adipose inflammation and lowered insulin sensitivity compared to the fish oil mice.
Fecal transplantation replicated the metabolic and inflammatory phenotype, demonstrating a casual
effect of microbiota [
81
]. The intestinal microbiome of animals fed on a high fat or high sugar diet has
been observed to be more vulnerable to disruption of the circadian rhythm [
82
]. Given the particular
importance of sleep to children, the combination of a poor diet and disrupted sleep may lead to
alterations in gut microbiome composition.
4.2. Plant-Derived Prebiotics
Plant-derived non-digestible carbohydrates, such as some starches and fiber, survive in the colon,
where they are fermented by the colonic microbiome to produce short chain fatty acids (SCFAs) [
83
].
Colonic epithelial cells utilize SCFAs, particularly butyrate, for 60–70% of their energy, and they
contribute to strengthening of the mucosal barrier [
84
]. SCFAs also regulate glucose and lipid
metabolism and immune function [
73
,
85
]. Butyrate acts as a histone deacetylase inhibitor, involved in
the epigenetic control of regulatory T-cell production and maintenance [
86
]. Western diet-associated gut
dysbiosis may promote a leaky gut membrane and metabolic endotoxemia [
87
], leading to increased
cardiometabolic disease risk. A diet low in prebiotics decreases total bacterial load and diversity,
while a high plant-based diet increases the gene richness of the microbiome and improves markers of
inflammation [
88
90
]. In a study of commercially available infant cereal, different cereal types were
Children 2018,5, 160 6 of 20
associated with changes in microbiome composition, and differences in SCFA production in an
in vitro
infant gut model [91].
4.3. Other Dietary Modulators of Microbiome Composition
While the majority of diet–microbiome studies have focused broadly on Western vs. traditional
diets, other dietary components have also been studied. Both undernourished and obese children in
Mexico were found to have lower bacterial diversity compared with well-nourished normal-weight
children [
92
]. There are limited data available on individual dietary effects on the microbiome in
children, but evidence from adults suggest multiple diet-derived components shape microbiome
composition. Gluten-free diets have been associated with changes in microbiota, with reductions
in Bifidobacterium,Lactobacillus, and Clostridium, and increases in other bacteria including potential
opportunistic pathogens [
93
,
94
]. Artificial sweeteners have been shown to modify gut microbiota [
95
]
and have been suggested to induce glucose intolerance through their effects on gastrointestinal
microbiota [
96
]. Other plant components, including polyphenols, may also modulate the gut
microbiome [
97
99
]. Fermented foods act as a natural source of probiotics, with fermented dairy
products [
100
,
101
] and vegetables [
102
,
103
] contributing bacteria to the diet, although the extent
to which these bacteria survive and colonize the gut in individuals with established microbiomes
is unclear [
104
]. Infant probiotic supplementation trials have generally found no long-term effects
of supplementation on metabolic and inflammatory markers [
105
,
106
]. The microbiome adapts
to available food sources; while some profiles may be more beneficial than others, there is a
complex interaction between diet, microbiota, and downstream metabolic effects, which remains
to be further studied.
5. Other Determinants of Microbiome Composition throughout Childhood
5.1. Effect of Antibiotics and Drug Interactions
Frequent use of antibiotics during childhood is associated with increased risk of antibiotic
resistance [
107
] and may predispose individuals to increased risk of disease, including overweight
and obesity [
108
,
109
], and inflammatory diseases [
110
], potentially through modulation of the
microbiome. Use of antibiotics causes a decline in microbiome diversity and reduces resident beneficial
commensals in the gut [
111
]. Low diversity is associated with increased body weight, insulin resistance,
inflammatory tone, and dyslipidemia compared to higher gut diversity [
112
]. While broad-spectrum
antibiotics have the greatest impact, the effects are mitigated, but still present, if the antibiotic is
targeted to a specific pathogen. This disruption allows proliferation of both potentially pathogenic
bacteria and those that promote obesity and metabolic dysregulation [
113
,
114
]. The impacts may be
particularly large if these disruptions occur early in life, before the emergence of the relatively stable
mature microbiome at two to three years old [
115
,
116
]. It takes several weeks for the microbiome to
recover from a course of antibiotics, often never completely restoring to pre-antibiotic diversity [117].
Antibiotic use during the first 6 months of life was associated with higher risk of being overweight
among children of normal weight mothers, although interestingly antibiotic use was associated with
a decreased risk of being overweight among children of overweight mothers [
118
]. The association
between increased body mass index (BMI) and early childhood cumulative exposure to antibiotics
was found to be slightly higher if broad spectrum antibiotics were utilized [
119
]. A significant sex
interaction has been reported, with antibiotic usage in the first 12 months of life associated with
increased BMI in boys but not girls [120].
Emerging research is revealing interactions between the microbiome and drugs, both in how drug
efficacy is modulated by microbiota and how use of pharmacological agents can shape the microbiome.
Numerous drugs have been shown to be differentially metabolized by microbiota [
121
123
], and future
consideration of microbiome composition could inform drug dosing in children. Various medications
have also been shown to alter microbiome composition, including proton pump inhibitors, as well
Children 2018,5, 160 7 of 20
as statins and anti-diabetic drugs [
124
127
], although the long-term effects are unknown. Due to
the important role the gut microbiome plays in the development of the immune system, it has
been hypothesized that the gut flora may influence the host response to vaccines. While there
have been relatively few studies investigating microbiome composition and vaccination, the data
indicate that microbiota play a role in vaccine response [
128
]. A higher relative abundance of
Actinobacteria and Firmicutes was associated with higher humoral and cellular vaccine responses,
while high relative abundance of Proteobacteria and Bacteroidetes was associated with lower
responses [
129
131
]. Whether vaccination induces any changes in the microbiome remains to be
determined. Notwithstanding the life-saving benefits, data suggest that early and repeated use
of antibiotics and potentially other medications during childhood is an important determinant of
microbiome composition, which may impact future disease risk.
5.2. Sex and Genetic Differences in the Microbiome
Little is known about how host genetics may determine microbiome colonization during infancy,
however, data in adults suggest that there is a genetic component to the microbiome [
132
134
].
Whether sex is an important modulator of microbiome composition in children remains unclear. Male
infants were found to have a higher total bacterial count than female infants at birth, based on first
defecation, while sex differences in Lactobacillus colonization were observed both at birth and after
several months [
135
]. Sex differences in microbiome composition have been reported in adults [
136
],
and these may interact with sex hormones to alter disease risk [
137
,
138
]. The microbiome may act
as an intermediate mechanism linking genetics to disease, however, further research is required to
understand potential causal links.
5.3. Environmental Modifiers of Microbiome Composition
Early exposure to pets has been associated with increased bacterial richness and diversity in
the infant gut microbiome, which may protect against obesity and allergies [
139
,
140
]. The presence
of siblings in the household has been associated with both increased diversity [
141
], as well as with
reduced diversity and richness [
139
], and with differences in specific bacteria [
111
,
135
]. There is also
evidence that exposure to urban and rural environments helps shape the microbiome in children [
142
].
Consistent with the hygiene hypothesis, it is likely that exposure to microbiota from pets and other
children can contribute to development of a healthy microbiome. However, the relative importance
of exposure within a shared household versus all other geographic and environmental exposures
remains unclear.
5.4. Comorbidities
Significant medical events and comorbidities can have large effects on the microbiome.
Hospitalization is associated with increased risk of Clostridium difficile colonization [
111
,
143
]. Changes
in gut microbiota and increased translocation of intestinal bacteria have been found to occur following
traumatic injury, including burns and traumatic brain injury [
144
,
145
]. While such injuries can
by themselves cause long-term consequences in children, the effects of injury-related changes in
microbiome composition are an important consideration that remain understudied. Autism has been
associated with differences in microbiome composition [
146
], and treatments to alter microbiome
composition including fecal transplant and probiotic supplementation have been shown to improve
certain symptoms in children with autism [
147
,
148
]. Research is needed to clarify how comorbidities
both drive, and are influenced by, differences in microbiome composition and function.
6. Mechanisms Linking Altered Microbiome Composition to Development of Obesity and
Cardiometabolic Disease
As outlined, there are many different factors that shape the development of the microbiome,
and many of these have also been linked to health outcomes. There is currently a knowledge
Children 2018,5, 160 8 of 20
gap, where we do not have prospective longitudinal or interventional studies that causally link
altered microbiome composition to disease. However, as outlined, many studies suggest such a
link, and fecal microbiome transplant studies have established causality in mice and to a limited
extent also in humans
[113,149152]
. At present, the specific mechanisms whereby the microbiome
modifies cardiometabolic disease are less clear. Early events determining microbiome composition
likely effect lifetime disease risk by altering long-term microbiome function. As expanded upon
below, it is likely that microbiota affect cardiometabolic disease risk in the host through at least
three potential mechanisms: (1) controlling nutrient bioavailability; (2) interacting with the immune
system to modulate inflammation; and (3) production of specific protective or pathogenic metabolites.
Evidence supporting these mechanisms is discussed below.
6.1. Energy Metabolism and Obesity
Numerous studies have identified differences in microbiome composition by body
weight
[153155]
, with Bifidobacterium implicated in several studies linking the gut microbiome to
obesity [
52
]. Fecal microbiome transplant experiments have shown that microbiota from obese humans
or animals promote obesity, proving that microbiota themselves can cause obesity [
113
,
150
,
156
].
Further, fecal transplants have been shown to modulate insulin sensitivity in humans, although the
long-term effects are unknown [
151
,
152
]. Simplistic calculations of the energy content of food and
relationship to body weight assumes that the calories in a given food are equally available to all
individuals. However, with an increased understanding of the role of microbiota, it is becoming clear
that this is not the case [
113
,
157
]; because commensal microbes selectively metabolize food in the
gut, they can control the supply of nutrients, including short-chain fatty acids to the host. Microbiota
also contribute to biosynthesis of amino acids and vitamins, meaning the same foods may contribute
different caloric and nutrient bioavailability to different people. Microbiota preferentially digest dietary
prebiotics, including fiber, which are not easily digestible by the host. In individuals consuming
low-fiber diets, insufficient supply of prebiotics may prompt changes in microbiome composition and
metabolism that affects host metabolism [
158
]. While this process is complex, and confounded by
many variables influencing body weight and food choice, subtle differences in energy availability over
time could be enough to shift individuals from a lean to an obesogenic phenotype [159,160].
6.2. Inflammation
Inflammation is a key component of maintaining health, however, uncontrolled inflammation
can have devastating consequences, with chronic low-grade inflammation promoting cardiometabolic
disease development [161,162]. There is a complex interaction between commensal microbes and the
host immune system, which, if dysregulated, can promote pathogenic inflammation. Although data
suggest that the microbiome is partially modifiable throughout life, the initial development of the
microbiome may have particular significance in establishing a core microbiome that is resistant to later
modification. Dysregulation during early critical periods in infancy may have life-long implications
on immune and metabolic function that may be difficult to reverse [
163
166
]. Experiments in mice
have shown that age-dependent expression of TLR5 in the gut epithelium of neonates facilitates
selective colonization by non-flagellated microbiota [
166
]. This suggests critical periods during
development where exposure to specific bacteria allows normal development of host–microbiota
relationships. Animal studies have shown that microbiota are required for normal intestinal
development, and maturation of the immune system, through toll-like receptor 2 (TLR2)-mediated
signaling [
167
169
]. In studies of delivery method and feeding in infants, differences in biomarkers of
immune function including immunoglobulins and cytokines were observed concurrent with changes
in the microbiome [
12
,
170
]. Translocation of microbes, microbial nucleic acids, and bacterial-derived
lipopolysaccharide (LPS) from the intestine to the bloodstream occurs not only in the setting of
intestinal disease but regularly in individuals with or without compromised gut barrier function, for
example, during diet-induced post-prandial metabolic endotoxemia [
87
,
112
,
171
174
]. Bacteria and
Children 2018,5, 160 9 of 20
bacterial RNAs have been detected in tissues throughout the body, including atherosclerotic plaque
and lipoproteins [
175
], suggesting that translocation of commensal microbes may play a causal role in
disease etiology [176].
6.3. Modulation of Metabolites
Beyond effects on inflammatory signaling, microbiota also produce and modify other signaling
molecules. Metabolites are generated in the gut by microbial metabolism, microbe–host interaction,
and the action of microbiota on dietary substrates [
4
,
177
]. Gut microbial metabolism of dietary
carnitine and choline to trimethylamine and subsequent hepatic oxidation to the pro-atherogenic
metabolite TMAO was found to be associated with increased atherosclerotic risk [
5
,
178
,
179
], although
whether TMAO is consistently pathogenic remains unclear [
180
]. Gut-mediated metabolism of soy
food-derived isoflavones is associated with altered metabolism and cardiometabolic risk [
181
184
].
Many other diet–microbiome interactions may modulate disease risk through parallel mechanisms.
The microbiome may also modulate disease biomarkers independent of dietary intake, including
modulation of blood lipids [
185
], cardiovascular disease-related biomarkers [
133
], and glucose and
insulin homeostasis [186].
7. Conclusions
As outlined throughout this review, there is considerable evidence linking gut microbiome
composition to cardiometabolic disease pathophysiology. At present, our knowledge is mostly limited
to observational studies and short-term interventions that permit some assessment of which factors
affect gut microbiome composition and what consequences may be expected from dysregulation.
However, large-scale prospective longitudinal studies are required to advance our knowledge of
microbiome dynamics over time, and throughout disease development. While certain strategies to
alter microbiome composition exist, including changes in diet or fecal transplant, at present these are
non-specific and untargeted. Strategies that target specific bacteria or functional pathways may yield
promising results but remain to be tested in appropriately-designed human trials. A major limitation
is that we do not yet know what constitutes a “healthy” microbiome. Establishing this is imperative,
but will be challenging, because a healthy microbiome is likely to be impacted by many factors and
may differ between individuals and by life stage. Elucidation of the specific functions of different
microbiota within the context of the host–microbial ecosystem is needed and may significantly impact
our ability to understand the complex predictors of disease progression and identify targets for future
microbiome therapeutics.
Author Contributions:
Writing—Original Draft Preparation, A.I.M., E.B.S., and J.F.F.; Writing—Review and
Editing, A.I.M., E.B.S., S.G.W., and J.F.F.
Funding:
J.F.F. was supported by an American Heart Association Scientist Development Grant (15SDG24890015)
and a P&F award from Vanderbilt University Medical Center’s Digestive Disease Research Center supported
by P30DK058404.
Conflicts of Interest:
The authors declare no conflict of interest. The funders had no role in the design of the
study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, and in the decision to
publish the results.
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2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
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... Hughes (2020) states that the gut microbiome is a key factor in determining an individual's specific response to diet (Hughes, 2020). While Mohammadkhah et al. (2018) have stated that emerging evidence of studies have suggested microbiome composition and function is associated with development of obesity and metabolic disease (Mohammadkhah et al., 2018). Fig. 1.1 summarizes the role of the normal gut microbiota and the effects of gut dysbiosis. ...
... Hughes (2020) states that the gut microbiome is a key factor in determining an individual's specific response to diet (Hughes, 2020). While Mohammadkhah et al. (2018) have stated that emerging evidence of studies have suggested microbiome composition and function is associated with development of obesity and metabolic disease (Mohammadkhah et al., 2018). Fig. 1.1 summarizes the role of the normal gut microbiota and the effects of gut dysbiosis. ...
... Stunting in children is a nutritional problem that leads to developmental defects that may affect brain cognitive function and is linked with an increased risk of obesity during their adulthood (Muhammad, 2018). The gut microbiome expands rapidly in infants following birth, and dysbiosis in infancy or childhood may affect the long-term health of the gut microbiome (Mohammadkhah et al., 2018). ...
... Moreover, researchers are expanding upon Barker's theory of the Developmental Origins of Health and Disease (DOHaD) to demonstrate that exposure to environments such as stress during the perinatal period can contribute to longterm risks to adverse infant outcomes that extend into adulthood. These include metabolic diseases like obesity, cardiovascular disease, diabetes, along with immunological disease and neurobehavioral disorders [4,[13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29]. Obesity, high blood pressure, and high blood sugar rank among the top four risk factors for death and disease in developed countries [30], with the US estimating costs of such chronic conditions at $4.1 trillion in 2022 [31]. ...
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Background Perinatal maternal stress, which includes both psychological and physiological stress experienced by healthy women during pregnancy and the postpartum period, is becoming increasingly prevalent. Infant early exposure to adverse environments such as perinatal stress has been shown to increase the long-term risk to metabolic, immunologic and neurobehavioral disorders. Evidence suggests that the human microbiome facilitates the transmission of maternal factors to infants via the vaginal, gut, and human milk microbiomes. The colonization of aberrant microorganisms in the mother’s microbiome, influenced by the microbiome-brain-gut axis, may be transferred to infants during a critical early developmental period. This transfer may predispose infants to a more inflammatory-prone microbiome which is associated with dysregulated metabolic process leading to adverse health outcomes. Given the prevalence and potential impact of perinatal stress on maternal and infant health, with no systematic mapping or review of the data to date, the aim of this scoping review is to gather evidence on the relationship between perinatal maternal stress, and the human milk, maternal, and infant gut microbiomes. Methods This is an exploratory mapping scoping review, guided by the Joanna Briggs Institute’s methodology along with use of the Prisma Scr reporting guideline. A comprehensive search was conducted using the following databases, CINAHL Complete; MEDLINE; PsycINFO, Web of Science and Scopus with a protocol registered with Open Science Framework DOI 10.17605/OSF.IO/5SRMV. Results After screening 1145 papers there were 7 paper that met the inclusion criteria. Statistically significant associations were found in five of the studies which identify higher abundance of potentially pathogenic bacteria such as Erwinia, Serratia, T mayombie, Bacteroides with higher maternal stress, and lower levels of stress linked to potentially beneficial bacteria such Lactococcus, Lactobacillus, Akkermansia. However, one study presents conflicting results where it was reported that higher maternal stress was linked to the prevalence of more beneficial bacteria. Conclusion This review suggests that maternal stress does have an impact on the alteration of abundance and diversity of influential bacteria in the gut microbiome, however, it can affect colonisation in different ways. These bacterial changes have the capacity to influence long term health and disease. The review analyses data collection tools and methods, offers potential reasons for these findings as well as suggestions for future research.
... Currently, a large effort to characterize animal-associated microbial ecologies has resulted in an improved understanding of the importance of the microbiome [1]. In humans, studies have indicated the importance of the microbiome to health [2][3][4], digestion [5], growth and development [6], and behavior [7,8]. In parallel, recent research has increased the understanding of the microbiomes of domesticated livestock such as dairy cattle. ...
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The microbiome of dairy calves undergoes extensive change due to various forces during the first weeks of life. Importantly, diseases such as bovine respiratory disease (BRD) and calf diarrhea can have profound impacts on the early-life microbiome. Therefore, a longitudinal, repeated-measures pilot study was designed to characterize the establishment of nasal and fecal microbiomes of dairy calves, assess the governing forces of microbial assembly, and evaluate how disease states impact these microbial ecologies. Dairy calves (n = 19) were clinically evaluated for gastrointestinal and respiratory disease across three weeks beginning at age ≤ seven days old. Fecal (n = 57) and nasal (n = 57) microbial samples were taken for paired-end 16S rRNA gene amplicon sequencing. Taxonomy and diversity analyses were used to characterize early-life nasal and fecal microbiomes. Stochasticity and determinism were measured using normalized stochasticity testing (NST) and Dirichlet multinomial model (DMM). All analyses were tested for statistical significance. Clinical diarrhea was observed in 11 of the 19 calves. Clinical BRD was not independently observed among the cohort; however, two calves presented clinical signs of both BRD and diarrhea. Taxonomic analysis revealed that fecal samples were highlighted by Bacteroidaceae (40%; relative abundance), Ruminococcaceae (13%), and Lachnospiraceae (10%), with changes in diversity (Kruskal–Wallis; p < 0.05) and composition (PERMANOVA; p < 0.05). Clinical diarrhea reduced diversity in the fecal microbiome but did not impact composition. Nasal samples featured Moraxellaceae (49%), Mycoplasmataceae (16%), and Pasteurellaceae (3%). While no diversity changes were seen in nasal samples, compositional changes were observed (p < 0.05). NST metrics (Kruskal–Wallis; p > 0.01) and DMM (PERMANOVA; p < 0.01) revealed that stochastic, neutral theory-based assembly dynamics govern early-life microbial composition and that distinct microbial populations drive community composition in healthy and diarrheic calves.
... trillion, which is projected to double by 2030 (Arena et al. 2015). Research studies reported the association of gut microbial (GM) composition to cardio-metabolic disease and related risk mechanisms (Mohammadkhah et al. 2018;Zouiouich et al. 2021). GM influences CMD pathogenesis through the modulation of nutrient and energy availability, activation of the immune response, modulation of gut barrier integrity, and systemic effects via microbe-mediated signaling molecules (Gabriel and Ferguson 2023). ...
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Cardio-metabolic disease is a significant global health challenge with increasing prevalence. Recent research underscores the disruption of gut microbial balance as a key factor in disease susceptibility. We aimed to characterize the gut microbiota composition and function in cardio-metabolic disease and healthy controls. For this purpose, we collected stool samples of 18 subjects (12 diseased, 6 healthy) and we performed metagenomics analysis and functional prediction using QIIME2 and PICRUSt. Furthermore, we carried out assessments of microbe–gene interactions, gene ontology, and microbe–disease associations. Our findings revealed distinct microbial patterns in the diseased group, particularly evident in lower taxonomic levels with significant variations in 14 microbial features. The diseased cohort exhibited an enrichment of Lachnospiraceae family, correlating with obesity, insulin resistance, and metabolic disturbances. Conversely, reduced levels of Clostridium, Gemmiger, and Ruminococcus genera indicated a potential inflammatory state, linked to compromised butyrate production and gut permeability. Functional analyses highlighted dysregulated pathways in amino acid metabolism and energy equilibrium, with perturbations correlating with elevated branch-chain amino acid levels—a known contributor to insulin resistance and type 2 diabetes. These findings were consistent across biomarker assessments, microbe–gene associations, and gene ontology analyses, emphasizing the intricate interplay between gut microbial dysbiosis and cardio-metabolic disease progression. In conclusion, our study unveils significant shifts in gut microbial composition and function in cardio-metabolic disease, emphasizing the broader implications of microbial dysregulation. Addressing gut microbial balance emerges as a crucial therapeutic target in managing cardio-metabolic disease burden.
... The gut microbiome, composed of trillions of microorganisms in the digestive tract, influences gut, immune and metabolic health [25,26]. The balance of the gut microbiome is crucial for overall well-being, with disruptions linked to various health problems such as cardiometabolic diseases, digestive disorders, neurological disorders [25, [27][28][29][30][31][32][33]. There is now evidence that both the gut and human milk microbiome is altered by many maternal factors such as maternal health, maternal body mass index, mode of delivery, and antibiotic use [34][35][36][37][38]. ...
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Objective The objective of this scoping review is to review the research evidence regarding the impact of perinatal maternal stress on the maternal and infant gut and human milk microbiomes. Introduction Perinatal stress which refers to psychological stress experienced by individuals during pregnancy and the postpartum period is emerging as a public health concern. Early exposure of infants to perinatal maternal stress can potentially lead to metabolic, immune, and neurobehavioral disorders that extend into adulthood. The role of the gut and human milk microbiome in the microbiome-gut-brain axis as a mechanism of stress transfer has been previously reported. A transfer of colonised aberrant microbiota from mother to infant is proposed to predispose the infant to a pro- inflammatory microbiome with dysregulated metabolic process thereby initiating early risk of chronic diseases. The interplay of perinatal maternal stress and its relationship to the maternal and infant gut and human milk microbiome requires further systematic examination in the literature. Inclusion criteria This scoping review is an exploratory mapping review which will focus on the population of mothers and infants with the exploration of the key concepts of maternal stress and its impact on the maternal and infant gut and human milk microbiome in the context of the perinatal period. It will focus on the pregnancy and the post-natal period up to 6 months with infants who are exclusively breastfed. Methods This study will be guided by the Joanna Briggs Institute’s (JBI) methodology for scoping reviews along with use of the Prisma Scr reporting guideline. A comprehensive search will be conducted using the following databases, CINAHL Complete; MEDLINE; PsycINFO, Web of Science and Scopus. A search strategy with pre-defined inclusion and exclusion criteria will be used to retrieve peer reviewed data published in English from 2014 to present. Screening will involve a three-step process with screening tool checklists. Results will be presented in tabular and narrative summaries, covering thematic concepts and their relationships. This protocol is registered with Open Science Framework DOI 10.17605/OSF.IO/5SRMV.
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This systematic review aims to synthesize key empirical findings to understand how various elements of the built environment influence the microbiome concerning children’s health and well-being. A comprehensive literature search was conducted across multiple databases, focusing on studies that examined the relationship between built environment factors and the microbiome aspects of childhood. A total of 42 studies were included in the final systematic review. We analyzed these studies from a range of different lenses, starting with basic research questions and variables to types of built environments, age groups of children, sampling strategy, bioinformatics, and the biological methods utilized. This review highlights a growing emphasis on children’s exposure to nature within built environments and its potential to beneficially alter the microbiome, with 38% of studies addressing this link. It also identifies a significant research gap in connecting built environment design features (landscape and/or architectural) to microbiome outcomes and associated health, behavioral, and mental health impacts on children. The findings indicate that interventions aimed at improving the built environment quality via design could foster healthier microbiomes in children’s environments. This review underscores the need for interdisciplinary research and policy initiatives that integrate microbiome science with built environment design to promote children’s health and well-being.
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Ageing of the cardiovascular system is associated with frailty and various life-threatening diseases. As global populations grow older, age-related conditions increasingly determine healthspan and lifespan. The circulatory system not only supplies nutrients and oxygen to all tissues of the human body and removes by-products but also builds the largest interorgan communication network, thereby serving as a gatekeeper for healthy ageing. Therefore, elucidating organ-specific and cell-specific ageing mechanisms that compromise circulatory system functions could have the potential to prevent or ameliorate age-related cardiovascular diseases. In support of this concept, emerging evidence suggests that targeting the circulatory system might restore organ function. In this Roadmap, we delve into the organ-specific and cell-specific mechanisms that underlie ageing-related changes in the cardiovascular system. We raise unanswered questions regarding the optimal design of clinical trials, in which markers of biological ageing in humans could be assessed. We provide guidance for the development of gerotherapeutics, which will rely on the technological progress of the diagnostic toolbox to measure residual risk in elderly individuals. A major challenge in the quest to discover interventions that delay age-related conditions in humans is to identify molecular switches that can delay the onset of ageing changes. To overcome this roadblock, future clinical trials need to provide evidence that gerotherapeutics directly affect one or several hallmarks of ageing in such a manner as to delay, prevent, alleviate or treat age-associated dysfunction and diseases.
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Over the last two decades, advancements in sequencing technologies have significantly deepened our understanding of the human microbiome's complexity, leading to increased concerns about the detrimental effects of antibiotics on these intricate microbial ecosystems. Concurrently, the rise in antimicrobial resistance has intensified the focus on how beneficial microbes can be harnessed to treat diseases and improve health and offer potentially promising alternatives to traditional antibiotic treatments. Here, we provide a comprehensive overview of both established and emerging microbe‐centric therapies, from probiotics to advanced microbial ecosystem therapeutics, examine the sophisticated ways in which microbes are used medicinally, and consider their impacts on microbiome homeostasis and health outcomes through a microbial ecology lens. In addition, we explore the concept of rewilding the human microbiome by reintroducing “missing microbes” from nonindustrialized societies and personalizing microbiome modulation to fit individual microbial profiles—highlighting several promising directions for future research. Ultimately, the advancements in sequencing technologies combined with innovative microbial therapies and personalized approaches herald a new era in medicine poised to address antibiotic resistance and improve health outcomes through targeted microbiome management.
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Background Construction of co-occurrence networks in metagenomic data often employs correlation to infer pairwise relationships between microbes. However, biological systems are complex and often display qualities non-linear in nature. Therefore, the reliance on correlation alone may overlook important relationships and fail to capture the full breadth of intricacies presented in underlying interaction networks. It is of interest to incorporate metrics that are not only robust in detecting linear relationships, but non-linear ones as well. Results In this paper, we explore the use of various mutual information (MI) estimation approaches for quantifying pairwise relationships in biological data and compare their performances against two traditional measures–Pearson’s correlation coefficient, r, and Spearman’s rank correlation coefficient, ρ. Metrics are tested on both simulated data designed to mimic pairwise relationships that may be found in ecological systems and real data from a previous study on C. diff infection. The results demonstrate that, in the case of asymmetric relationships, mutual information estimators can provide better detection ability than Pearson’s or Spearman’s correlation coefficients. Specifically, we find that these estimators have elevated performances in the detection of exploitative relationships, demonstrating the potential benefit of including them in future metagenomic studies. Conclusions Mutual information (MI) can uncover complex pairwise relationships in biological data that may be missed by traditional measures of association. The inclusion of such relationships when constructing co-occurrence networks can result in a more comprehensive analysis than the use of correlation alone.
Chapter
The human gastrointestinal tract (GIT) is home to a vast array of microbes that play a crucial role in human health and disease. The balance between Bacteriodetes and Fermicutes, two major groups of gut bacteria, is particularly important for maintaining intestinal health. Among the trillions of bacterial species living in symbiosis with the human digestive tract, Bifidobacterium, Lactobacillus, Blautia, Akkermansia, Roseburia, Fecalibacterium, and Eubacterium are dominant groups that support GIT well-being. However, slight changes in the gut’s working mechanisms or the host immune response can cause various gastrointestinal conditions, such as coeliac disease, type 2 diabetes mellitus, and inflammatory bowel disease (IBD). To prevent these gastrointestinal disturbances, experts recommend several strategies for modulating the gut microbiome, including the addition of required macronutrients and micronutrients to the diet, oral administration of synthetic prebiotics, probiotics, and faecal microbiota transplantation. Additionally, certain vegetables, fruits, and cereals are excellent sources of flavonoids, lignans, and phenolic acids that aid in gut microbiome modulation. These innovative strategies have proven to be effective in maintaining gut homeostasis, retaining gut barrier integrity, and promoting the health of the human GIT.
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The composition of human milk is dynamic and can vary according to many maternal factors, such as diet and nutritional status. This study investigated the association of maternal nutrition and body composition with human milk composition. All measurements and analyses were done at three time points: during the first (n = 40), third (n = 22), and sixth (n = 15) month of lactation. Human milk was analyzed using the Miris human milk analyzer (HMA), body composition was measured with bioelectrical bioimpedance (BIA) using a Maltron BioScan 920-II, and the assessment of women’s nutrition was based on a three-day dietary record. The correlation coefficient (Pearson’s r) did not show a significant statistical relationship between human milk composition and nutrients in women’s diet at three time points. For women in the third month postpartum, we observed moderate to strong significant correlations (r ranged from 0.47 to 0.64) between total protein content in milk and the majority of body composition measures as follows: positive correlations: % fat mass (r = 0.60; p = 0.003), fat-free mass expressed in kg (r = 0.63; p = 0.001), and muscle mass (r = 0.47; p = 0.027); and negative correlation: % total body water (r = −0.60; p = 0.003). The variance in milk fat content was related to the body mass index (BMI), with a significant positive correlation in the first month postpartum (r = 0.33; p = 0.048). These findings suggest that it is not diet, but rather the maternal body composition that may be associated with the nutritional value of human milk.
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Despite a growing body of evidence, the role of the gut microbiome in cardiovascular diseases is still unclear. Here, we present a systems-genome-wide and metagenome-wide association study on plasma concentrations of 92 cardiovascular-disease-related proteins in the population cohort LifeLines-DEEP. We identified genetic components for 73 proteins and microbial associations for 41 proteins, of which 31 were associated to both. The genetic and microbial factors identified mostly exert additive effects and collectively explain up to 76.6% of inter-individual variation (17.5% on average). Genetics contribute most to concentrations of immune-related proteins, while the gut microbiome contributes most to proteins involved in metabolism and intestinal health. We found several host-microbe interactions that impact proteins involved in epithelial function, lipid metabolism, and central nervous system function. This study provides important evidence for a joint genetic and microbial effect in cardiovascular disease and provides directions for future applications in personalized medicine.
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