Transitioning From Descriptive to Mechanistic Understanding of the Microbiome: The Need for a Prospective Longitudinal Approach to Predicting Disease.

HHS Public Access Author manuscript Author Manuscript

J Pediatr. Author manuscript; available in PMC 2017 June 21. Published in final edited form as: J Pediatr. 2016 December ; 179: 240–248. doi:10.1016/j.jpeds.2016.08.049.

Transitioning From Descriptive to Mechanistic Understanding of the Microbiome: The Need for a Prospective Longitudinal Approach to Predicting Disease

Author Manuscript

Victoria J. Martin, MD, Maureen M. Leonard, MD, MMSc, Lauren Fiechtner, MD, MPH, and Alessio Fasano, MD Department of Pediatric Gastroenterology and Nutrition, Massachusetts General Hospital for Children, Boston, MA

Author Manuscript

The incidences of chronic inflammatory diseases are rising dramatically in the developed world, with increasing disease burdens in childhood.1 Currently there are limited effective strategies for the treatment or prevention of these conditions. To date, a myriad of crosssectional studies has described alterations in the gut microbiota composition in a variety of disease states after the disease has become apparent. We suggest that to link these microbiome shifts mechanistically with disease pathogenesis, a prospective cohort design is required to capture changes that precede or coincide with disease and symptom onset. These prospective studies also must integrate microbiome, metagenomic, metatranscriptomic, and metabolomic data with comprehensive clinical and environmental data to build a systemslevel model of interactions between the host and the development of disease. The creation of novel biological computational models and a pathway to move from association to causation are essential to providing a mechanistic approach to exploring the development of chronic inflammatory diseases. This can only be done when these diseases are investigated as complex biological networks. In this commentary, we will discuss the current knowledge regarding the microbiome’s contribution to chronic inflammatory diseases in childhood by focusing on 5 important pediatric examples; allergy, autoimmune disease (celiac disease), inflammatory bowel disease (IBD), necrotizing enterocolitis (NEC), and obesity. We will discuss how to move research in these fields from descriptive to mechanistic approaches, with an ultimate goal of being able to predict and even prevent disease.

The Potential Role of the Human Microbiome in Chronic Inflammatory Author Manuscript

Diseases During the past few decades, we have been witness to a dramatic rise in allergic and autoimmune conditions in the US and other developed nations. A significant portion of that burden of disease rests on children. The “hygiene hypothesis” originally suggested that lack of early childhood infections in the developed world might be responsible for this rise in

Reprint requests: Alessio Fasano MD, Massachusetts General Hospital for Children, Massachusetts General Hospital, 175 Cambridge St, CPZS-574, Boston, MA 02114. [email protected]. A.F. holds stocks of Alba Therapeutics; serves as a consultant for Crestovo, General Mills, Innovate Biopharmaceuticals, and Pfizer, and serves as a speaker for and receives research from Mead Johnson Nutrition. The other authors declare no conflicts of interest.

Martin et al.

Page 2

Author Manuscript

allergic and autoimmune diseases.2,3 Knowledge of the human microbiome has accelerated rapidly thanks to the Human Microbiome Project and the increasing availability of highthroughput sequencing technology. As our understanding of the human microbiome expands, the hygiene hypothesis continues to be revised.4 Currently, there is evidence that microbiome-mediated maturation of epithelial barriers and of the gut-associated lymphoid tissue impacts capacity for the host to develop responses that maintain normal homeostasis and prevent aberrant proinflammatory or allergic responses.

Author Manuscript

Establishment of a healthy microbiome may begin even before birth. Despite a longstanding belief that the fetus resides in a sterile environment, recent studies revealed microbiota in both the placenta5 and meconium.6 Current mouse models suggest that presentation of maternal commensal bacterial components to the fetus in the last trimester of pregnancy likely is a mechanism for immune system maturation and oral tolerance.7 It also is now well established that mode of delivery, maternal diet, infant diet, antibiotic exposure, and the home environment all can have significant impact on the early development of the infant intestinal microbiome, which is susceptible to dramatic shifts until 1–3 years of age.8,9 These findings imply that disruptions in the development of a healthy microbiome ecosystem early in life can have lasting effects.10 There is growing evidence that exposure to healthy and diverse commensal species early in life confers protection against chronic inflammatory diseases (Figure 1). Technology now allows for vast and sophisticated study of the human microbiome (microbes present in the human host and their functions), metagenome (DNA extracted from samples and their functions), metatranscriptome (total content of gene transcripts, as RNA, and their functions), and metabolome (presence and function of metabolites). As the field expands exponentially in the wake of nonculture-based technologies to study the microbiome, a multi-omic systems biology research approach in pediatrics has the potential to revolutionize our understanding of many of the most common diseases our children face.

Author Manuscript

Ongoing Discovery in Five Common Pediatric Chronic Inflammatory Diseases Allergic Diseases

Author Manuscript

Recent studies have demonstrated differences in the intestinal microbiome of infants who develop an array of allergic diseases compared with their healthy peers.11 Food allergies are reported in 5% of America’s children and are on the rise, resulting in significant economic, psychological, and medical burdens.12 Therefore, the mechanisms behind oral tolerance to foods are under increasing investigation. Oral tolerance is the result of a complex interaction among food proteins, the microbiome inhabiting our gut, and immune and nonimmune cells co-localized there.13 The mechanism behind the breakdown of these interactions, leading to clinical food allergy, remains poorly understood. Children with adverse reactions to food have increased intestinal permeability, both at baseline14 and worsened by allergic reaction.15 T-regulatory cells (T-regs) play an important role in oral tolerance acquisition, and children with dysfunctional T-regs have an increased risk of food allergies.16 The importance of the timing and nature of antigen exposure recently was demonstrated in a landmark clinical trial that found that early exposure to peanuts decreased rates of clinical

J Pediatr. Author manuscript; available in PMC 2017 June 21.

Martin et al.

Page 3

Author Manuscript

food allergy in a high-risk group.17 Our understanding of that mechanism and its applicability to the general population, however, remain limited.

Author Manuscript

The role of the microbiome and metabolomics in oral tolerance is only beginning to be explored.18 It is known that children raised on farms with increased diversity of the microbiome in their home had decreased risk of asthma and atopic diseases19 and that antibiotic exposure early in life increases risks of the development of allergies.20 Limited data show that specific commensal microbial species may promote oral tolerance to food proteins. Data in antibiotic-treated mice suggest that Clostridium species promote oral tolerance via mechanisms of both intestinal permeability and innate lymphoid cell function.21 Certain families of commensal bacteria, such as Lachnospiraceae and Ruminococcaceae, are known to produce short-chain fatty acids, of which butyrate has been the most studied. Butyrate has multiple known immune cell-mediated effects22 in the context of food allergy and has been shown to increase the number of T-regs in the colon in mice.23 Many conflicting studies have shown alterations in the microbiome in children with food sensitization or allergies, but a unifying pattern has been difficult to elucidate. This likely is attributable to the limitations of small sample size, cross-sectional analyses, differing approaches, and the chaotic infant microbiome early in the life. Celiac Disease

Author Manuscript

Celiac disease is unique among autoimmune diseases in that there is a strong association with HLA DQ2 and/or DQ8,24 the environmental trigger (gluten) is known, and diseasespecific autoantibodies have been identified and can be measured. Therefore, exposure to the environmental trigger can be studied carefully, and frequent prospective screening against the autoantibody tissue transglutaminase can determine precisely when the loss of tolerance to gluten occurs.24 Dysbiosis has been implicated in the development of celiac disease. In vitro studies suggest that microbes can influence the digestion of gliadin, the production of cytokines in response to gliadin, and the increased intestinal epithelial permeability induced by gliadin.25,26 The vast majority of research describes differences in the composition, structure, and diversity of the fecal and small intestinal microbiota in patients with celiac disease on the basis of age, disease status, and associated signs and symptoms.27 Associated metabolic activity, as measured by patterns of short chain fatty acids in the stool, is altered in patients with active celiac disease and linked to the described dysbiosis.28 Differences in specimen collection, analysis techniques, age of the study population, and disease status, however, make it difficult to compare studies.

Author Manuscript

Underlying differences in the colonization of the gastrointestinal tract, related to genetic makeup, also may contribute to an infant’s future risk of developing celiac disease.29,30 Microbial communities in infants carrying the DQ2 haplotype were observed to have a greater abundance of Firmicutes and Proteobacteria compared with control infants.31 Infants with a first-degree family member with celiac disease and compatible genotype had a decreased representation of Bacteriodetes, a greater abundance of Firmicutes, and overall delayed maturation of the microbiota in the first 2 years after birth.31 Gluten ingestion is necessary for the development of celiac disease. Introducing gluten into an infant’s diet at 12 months of age compared with at 6 months transiently delays the onset J Pediatr. Author manuscript; available in PMC 2017 June 21.

Martin et al.

Page 4

Author Manuscript Author Manuscript

of celiac disease but does not prevent its development.32 Exposing infants to small amounts of gluten between 16 and 24 weeks was not shown to influence the prevalence of celiac disease.33 Although clinical studies evaluating the timing of gluten introduction have yet to unveil a meaningful pathologic or preventative time point, we know that the introduction of gluten alters the host microbiome in infants at risk for celiac disease. The introduction of gluten leads to notable changes in the abundance of the phyla Firmicutes and Proteobacteria.31 Infants who developed autoimmunity had high lactate signals in their stools preceding the first detection of celiac disease antibodies, corresponding to a greater relative abundance of Lactobacillus species. This finding opens the possibility of identifying biomarker predictors in the microbiota suggestive of autoimmunity onset.31 The CDGEMM (ie, celiac disease genomic environmental microbiome and metabolomic) study is a prospective observational cohort study designed to identify and validate a specific microbiome signature present in infants at risk of celiac disease before disease onset and ultimately to investigate the mechanism by which the identified microbes may contribute to the development of disease.34 Inflammatory Bowel Disease


The involvement of micro-organisms in the pathogenesis of IBD has been postulated for many years. Despite the great effort spent in search of the pathogen(s) triggering the chronic inflammatory process that characterizes IBD, however, the identification of microorganism(s) causing IBD has remained elusive. The parallel effort to search for the genetic trait(s) linked to IBD initially led to promising results with the identification of specific mutations in key pattern recognition receptors, including the Nod gene.35 The initial excitement was tempered partially, however, by the appreciation that these genetic mutations involved only a subgroup of patients with IBD and that genetic makeup can only explain part of the risk of IBD. This finding suggests that in addition to genetic predisposition, the immune dysregulation that characterizes IBD must be driven by additional factors.36 Now, there is good evidence that the pathogenesis of IBD is the consequence of an inappropriate immune response to commensal microbiota. This exaggerated response seems secondary to the combination of genetic mutations and dysbiosis.37–40 Disparities in methodologic approaches, including different techniques used to analyze gut microbiome, disease activity, site of inflammation, and different site of microbiota sampling (stools vs mucosa), however, make comparison across reported studies difficult. Nevertheless, a common theme emerges suggesting that this dysbiosis is characterized by reduction in biodiversity (α-diversity) and altered representation of several taxa.40,41 Some studies have reported an increase in Bacteroidetes and Firmicutes in Crohn’s disease; however, the number of ribotypes of Firmicutes was decreased compared with healthy controls.41 When disease activity was considered, opposite results were reported in patients with Crohn’s disease, showing a decreased diversity of Bacteroidetes during the acute phase of the disease compared with patients analyzed during remission.42 Even the site of the disease inflammation may influence the results of microbiota composition, with a reported increased diversity of Firmicutes in patients with colonic Crohn’s disease and decreased diversity in patients with ileal Crohn’s disease.43 The site of sampling also can highly influence microbiome analyses. Increased abundance of Enterobacteriaceae (mainly Escherichia coli) and decreased


Martin et al.

Page 5

Author Manuscript

diversity of Feacalibacteria were detected in patients with Crohn’s disease from their mucosal biopsies compared with fecal samples.44,45

Author Manuscript

Data on gut dysbiosis in pediatric patients with IBD are more limited. Microbiota analysis at the species level in the tissues of children affected by IBD led to the identification of 2 previously unreported strains of adhesive-invasive E coli mechanistically linked to upregulation of carcinoembryonic antigen-related cell adhesion molecule 6, tumor necrosis factor-α, and interleukin-8 gene/protein expression.46 Decreased diversity of the fecal microbiome, including of Firmicutes, Verrucomicrobiae, and Lentisphaerae, was more pronounced among corticosteroid-nonresponsive children with ulcerative colitis.47 Gut dysbiosis often is associated with specific dysfunctions of microbial metabolism and bacterial protein signaling, including involvement of oxidative stress pathways, decreased carbohydrate metabolism, and amino acid biosynthesis counterbalanced by an increase in nutrient transport and uptake.40 Even though these changes suggest a possible mechanistic link between modifications in microbiota composition and IBD pathogenesis, these studies mainly are associative. Necrotizing Enterocolitis


On the basis of the described importance of the gut microbiota development at birth and the influence of several pre-, peri-, and postnatal factors on its development, it is not surprising that this process is especially relevant for very preterm infants.48 The interaction between these early intestinal colonizers and a structurally, functionally, and immunologically immature gut mucosa likely influences health outcomes substantially.48 NEC, a devastating disease affecting the intestinal tract of premature infants leading to severe morbidity and mortality, likely is the most severe consequence of inappropriate cross talk between the gut microbiome and its immature host.48,49 Despite improvements in neonatal intensive care, the birth weight-specific incidence of NEC has not decreased during the past 2 decades, nor has resulting substantial morbidity and mortality rates. The immature defense mechanisms of preterm babies, including inefficient peristalsis and decreased expression of intercellular epithelial tight junction proteins,50 increase the likelihood that bacteria and their endotoxins normally confined to the intestinal lumen may cross the gut barrier and reach systemic organs and tissues. This uncontrolled passage of micro-organisms (and their byproducts) triggers the activation of an exaggerated inflammatory response that further compromises the gut barrier.51–54 Past research efforts have focused largely on identifying possible pathogenic bacteria as the cause of intestinal inflammatory processes leading to NEC.55 Such pathogens have not been identified, nor have any validated biomarkers that predict NEC in at-risk premature babies.56 A well-controlled, cross-sectional study in a prospective birth cohort described a “signature” microbiome of very preterm infants who eventually went on to develop NEC.57 The microbiome analysis of these infants showed a positive association with the Gram-negative facultative bacilli Gamma-proteobacteria and negative association with strictly anaerobic bacteria (Clostridia and Negativicutes).57 The explanation for these “hostile” settlers within the gastrointestinal tract of infants who develop NEC remains elusive; however, it is reasonable to hypothesize that the atypical oral intake (delayed enteral feeding, tube feeding, formula supplementation) and the ubiquitous exposure to antibiotics in very preterm infants play key pathogenic roles. Feeding very


Martin et al.

Page 6

Author Manuscript

premature infants with predominantly human breast milk has been shown to decrease the risk of NEC.58 It is not yet clear whether this is attributable to the maternal microbiome transferred in human milk, the role of human milk oligosaccharides, immune mediators, or more likely a complex interaction of all of these factors. The unusually clean environment of the neonatal intensive care unit, common cesarean delivery, limited breast feeding, and the lack of continuous close physical contact with parents may further influence the establishment of an unbalanced, proinflammatory microbiome.59 Obesity

Author Manuscript

Overweight and obesity in children have increased dramatically during the past 3 decades.60 Recent evidence indicates that environmental insults and dietary influences in the first 1000 days after conception61,62 may impact substantially the development of overweight or obesity by affecting future anatomic, physiological, and biochemical trajectories.63,64 Understanding the dynamics of the developing infant microbiome and its relation to nutrition65,66 and metabolism during this critical time could reveal the factors that predispose children to early infant weight gain and eventually obesity.

Author Manuscript

Multiple studies have found that early exposure to antibiotics is associated with obesity, both in children and in mice.67 In a recent study of nearly 65 000 children, a history of repeated exposure of antibiotics (>4 exposures) from 0 to 23 months of age and/or exposure to antibiotics before 5 months of age predicted obesity at 24–59 months of age.68 Another large database study (38 000 children including 92 twins discordant for antibiotic exposure), however, recently demonstrated no association between exposure to antibiotics in the first 6 months of life and weight gain in childhood.69 Many of these large database studies use administrative data in electronic health records to collect exposure to antibiotics, which limits detection of antibiotic use and also lacks other potentially important factors that might confound or mediate the relationship between antibiotic exposure and obesity. Furthermore, existing studies have not examined the effects of antibiotics on the intestinal microbiome, which provides a biologically plausible mechanism of how antibiotics would affect obesity risk. In a retrospective cohort of 42 children, those with short breastfeeding duration (0–6 months) and no early-life antibiotic use or those with long breastfeeding duration (8–16 months) and early life use of antibiotics had a lower abundance of bifidobacterie and Akkermansia compared with those with long duration of breastfeeding and no early antibiotics; however, there was no difference in body mass index z score between these groups.70

Author Manuscript

In mice, the administration of low-dose penicillin early in life induces lasting effects on weight status by modulating the intestinal microbiota.71 Early exposure to penicillin together with a high-fat diet led to greater fat mass compared with penicillin exposure and a low-fat diet, underscoring the interplay between diet and the microbiome. When germ-free mice were transferred microbiota from the penicillin-treated group, they gained total and fat mass faster than controls. Another mouse model examining lifelong subtherapeutic antibiotic treatment showed increased weight and fat mass, insulin resistance, and nonalcoholic fatty liver disease compared with controls. Those mice had shifts in their microbiome resembling an immature microbial community.72


Martin et al.

Page 7

Author Manuscript

Aside from antibiotics, sugar-sweetened beverages have been hypothesized to affect the microbiome. Sugar-sweetened beverages are the main source of added sugars in the American diet and have been linked to an increased risk of diabetes and obesity.73 Highfructose corn syrup is known to be a potent stimulant of lipogenesis, which leads to insulin resistance and ectopic fat deposition.74 Fructose does not stimulate leptin secretion, failing to provide hormonal satiety signals. It is hypothesized that free sugar in sugar-sweetened beverages may contribute to a less diverse intestinal flora, making individuals already ingesting non-nutritive calories more susceptible to developing obesity and diabetes.74 In mouse models, the use of probiotics to increase microbial diversity has been shown to inhibit metabolic alterations associated with consumption of high-fructose corn syrup.74

Author Manuscript

Processed food also has been linked to obesity and metabolic syndrome. Emulsifiers present in these foods have been shown to increase the weight and risk of metabolic syndrome in mice.45 Moreover, a high fat, high-carbohydrate diet was shown to affect the ratio of Firmicutes to Bacteroidetes, which was associated with impaired glucose and lipid oxidative rates in humans. This ratio has been linked to overweight, obesity, and type II diabetes, likely through inflammatory processes.74

Author Manuscript

The literature has begun to provide a plausible link among the gut microbiota, metabolites of micro-organisms, and the effect on the host in patients with obesity and type 2 diabetes. Alterations in bile acids, vitamins (specifically choline and niacin), branched fatty acids, purines, and phenolic compounds have been associated with obesity or diabetes. For example, a decrease of primary bile acids and an increase in secondary bile acids have been documented in the fasting serum of overweight patients with type 2 diabetes compared with healthy controls.75 Gut microbial-derived secondary bile acids are thought to activate signaling pathways in glucose and lipid metabolism, including activation of mitochondrial activity and oxidative phosphorylation in brown fat and muscle, which has been linked to insulin sensitization in genetic and diet-induced models of obesity and diabetes.76

Possible Interventions to Manipulate Microbiome and Challenges to Their Implementation There are several current approaches to the modification of the microbiome, all of which have significant limitations. Prebiotics and Probiotics

Author Manuscript

Prebiotics and probiotics represent promising potential interventions in the treatment and prevention of chronic inflammatory diseases. Theoretically, if dysbiosis is associated with disease, then manipulating its composition by prebiotic supplementation or providing probiotics to resupply/rebalance the gut ecosystem should contribute to an improvement in microbiome health, and thereby disease modulation or prevention. The depth of our understanding of the microbiome’s contribution to disease, however, remains shallow. We believe that a healthy microbiome is one that is diverse, and indeed there are multiple studies showing that reduced diversity of the microbiome is associated with many diseases. Yet we continue to work to simply understand what constitutes a “normal” microbiome.77 Most


Martin et al.

Page 8


studies describe dysbiosis at the phylum level, and probiotics are available on the species level, which exposes a major mismatch between what is understood and what is being offered therapeutically. Mechanistic work suggesting that certain species of probiotics may contribute to improve intestinal health has been done largely in the absence of accounting for the complex biological networks known to contribute to development of disease. Future research must focus on identifying specific microbiota signatures associated with disease development before therapeutic interventions are explored. This concept is illustrated by a recent phase 3 clinical trial that failed to show a benefit of administering the probiotic Bifidobacterium breve to premature infants in the prevention of NEC.78 This probiotic was chosen on the basis of availability and positive nutritional outcomes associated with the strain, rather than on any mechanistic data in the setting of NEC. A prospective crosssectional observational birth cohort study, recruiting during a similar time period, was successful in describing the “signature” microbiome of premature infants who went on to develop NEC. This study found no evidence that bifidobacteria were under-represented in the stools of infants who subsequently developed NEC, making the failure of the probiotic Bifidobacterium breve unsurprising.57 This work highlights the need for interventional studies to be designed based on preidentified microbiome signatures in disease states, supported by mechanistic understanding of the roles of specific bacterial populations in predisposing to or preventing disease. Probiotics may well become a highly promising interventional strategy, but only when informed by well-established mechanistic data. Fecal Transplantation

Author Manuscript

Fecal microbiota transplantation has been studied predominantly in the treatment of recurrent Clostridium difficile colitis and is an effective treatment strategy in adults and children,79,80 although the specific mechanism of action is not understood. Efficacy of fecal microbiota transplantation in treatment of IBD is less well established,81 and fecal transplant has not been well studied for prevention or in the context of other chronic inflammatory diseases. Studies examining varying delivery methods and donor selection and screening are important and are ongoing. Among other social, ethical, and legal challenges, there also are reported clinical adverse events warranting further study. Mouse models have showed behavioral phenotype transfer in fecal microbiota transplantation,82 underscoring our lack of mechanistic understanding. By its very nature, fecal microbiota transplantation is a less targeted approach, with perhaps increased potential for unforeseen consequences. In the future, more targeted probiotic therapy based on established dysbiotic disease signatures and known mechanisms of action likely will prevail.

Author Manuscript

Despite the current limitations of interventional studies, the possibility of a paradigm shift in therapeutic and treatment strategies for chronic inflammatory diseases in response to the proposed mechanistic studies will be feasible with the implementation of a multi-omic approach. Detailed and granular understanding of the mechanisms by which specific microbiota may lead to chronic inflammatory diseases through longitudinal birth cohort studies (Figure 2) will allow for identification of specific therapeutic and prevention targets. Although current therapies for these conditions are focused entirely on broad treatment of symptoms and sequelae (inflammation blockade, dietary elimination of offending antigens),


Martin et al.

Page 9

Author Manuscript

a multi-omic predictive disease model approach may lead to compelling strategies for personalized treatment (precision medicine) and/or primary disease prevention.

Discussion

Author Manuscript

Chronic inflammatory diseases are rising in prevalence and greatly affect children. Although research around the role of the microbiome is growing exponentially, clinical applicability is lacking. Current studies evaluate the microbiota at different taxonomic levels, at different time points, from different sites, by different platforms, and with different computational strategies. This is due to rapid growth in the field, challenged by narrow focus of individual studies, small sample sizes, cross-sectional design, and lack of standardization. The focus also has been mainly on the bacterial microbiota; viruses, parasites, and fungi also are likely to be important members of this large co-evolving ecosystem that lives on and within us. Further mechanistic study to understand these human-microbe interactions will be important. We are much more likely to discover clinically meaningful and successful interventions when design is based on established mechanistic understanding. Therefore, we need to transition from descriptive to mechanistic studies of the micro-biome for promising translational medicine to be possible. Pediatric researchers are particularly well positioned to lead this transition given the hypothesis that the development of the microbiome during the first 1000 days of life has a lasting effect on an individual’s future health and risk of disease.

Author Manuscript

Large-scale, collaborative, prospective, longitudinal, multi-omic studies will be required ultimately to create breakthrough therapeutic and targeted prevention strategies. Longitudinal data collection must begin before the onset of disease to understand the contribution of multi-omic covariates to the development of disease. It is now clear that knowing the functionality of the microbiota is central to understanding the mechanistic role of the microbiota in development of chronic inflammatory disease. Metatranscriptomics, metaproteomics, and metabolomic analyses all are necessary because gene expression is consistent with DNA abundance for less than 50% of genes in the microbiome.83 Optimal computational models to analyze longitudinal multi-omic covariates currently are under investigation, but large data sets, of which there are few, are necessary to evaluate them. Done well, these pediatric longitudinal multi-omic studies have the potential to impact dramatically our understanding of and approach to these complex chronic inflammatory diseases. Only then will breakthrough treatment and prevention strategies likely emerge.

Glossary Author Manuscript

IBD

Inflammatory bowel disease

NEC

Necrotizing enterocolitis

T-reg

T-regulatory cell


Martin et al.

Page 10

Author Manuscript

References

Author Manuscript Author Manuscript Author Manuscript

1. Bach J-F. The effect of infections on susceptibility to autoimmune and allergic diseases. N Engl J Med. 2002; 347:911–20. [PubMed: 12239261] 2. Greenwood BM. Autoimmune disease and parasitic infections in Nigerians. Lancet. 1968; 2:380–2. [PubMed: 4174413] 3. Strachan DP. Hay fever, hygiene, and household size. BMJ. 1989; 299:1259–60. [PubMed: 2513902] 4. Versini M, Jeandel P-Y, Bashi T, Bizzaro G, Blank M, Shoenfeld Y. Unraveling the hygiene hypothesis of helminthes and autoimmunity: origins, pathophysiology, and clinical applications. BMC Med. 2015; 13:81. [PubMed: 25879741] 5. Aagaard K, Ma J, Antony KM, Ganu R, Petrosino J, Versalovic J. The placenta harbors a unique microbiome. Sci Transl Med. 2014; 6:237ra65. 6. Vicario M, Blanchard C, Stringer KF, Collins MH, Mingler MK, Ahrens A, et al. Local B cells and IgE production in the oesophageal mucosa in eosinophilic oesophagitis. Gut. 2010; 59:12–20. [PubMed: 19528036] 7. Rescigno M, Urbano M, Valzasina B, Francolini M, Rotta G, Bonasio R, et al. Dendritic cells express tight junction proteins and penetrate gut epithelial monolayers to sample bacteria. Nat Immunol. 2001; 2:361–7. [PubMed: 11276208] 8. Dominguez-Bello MG, Costello EK, Contreras M, Magris M, Hidalgo G, Fierer N, et al. Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns. Proc Natl Acad Sci USA. 2010; 107:11971–5. [PubMed: 20566857] 9. Azad MB, Konya T, Maughan H, Guttman DS, Field CJ, Chari RS, et al. Gut microbiota of healthy Canadian infants: profiles by mode of delivery and infant diet at 4 months. CMAJ. 2013; 185:385– 94. [PubMed: 23401405] 10. Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Con-treras M, et al. Human gut microbiome viewed across age and geography. Nature. 2012; 486:222–7. [PubMed: 22699611] 11. Penders J, Thijs C, van den Brandt PA, Kummeling I, Snijders B, Stelma F, et al. Gut microbiota composition and development of atopic manifestations in infancy: the KOALA Birth Cohort Study. Gut. 2007; 56:661–7. [PubMed: 17047098] 12. Jackson KD, Howie LD, Akinbami LJ. Trends in allergic conditions among children: United States, 1997–2011. NCHS Data Brief. 2013; 121:1–8. 13. Chinthrajah RS, Hernandez JD, Boyd SD, Galli SJ, Nadeau KC. Molecular and cellular mechanisms of food allergy and food tolerance. J Allergy Clin Immunol. 2016; 137:984–97. [PubMed: 27059726] 14. Ventura MT, Polimeno L, Amoruso AC, Gatti F, Annoscia E, Marinaro M, et al. Intestinal permeability in patients with adverse reactions to food. Dig Liver Dis. 2006; 38:732–6. [PubMed: 16880015] 15. Perrier C, Corthésy B. Gut permeability and food allergies. Clin Exp Allergy. 2011; 41:20–8. [PubMed: 21070397] 16. Torgerson TR, Linane A, Moes N, Anover S, Mateo V, Rieux-Laucat F, et al. Severe food allergy as a variant of IPEX syndrome caused by a deletion in a noncoding region of the FOXP3 gene. Gastroenterology. 2007; 132:1705–17. [PubMed: 17484868] 17. Toit Du G, Roberts G, Sayre PH, Bahnson HT, Radulovic S, Santos AF, et al. Randomized trial of peanut consumption in infants at risk for peanut allergy. N Engl J Med. 2015; 372:803–13. [PubMed: 25705822] 18. Ling Z, Li Z, Liu X, Cheng Y, Luo Y, Tong X, et al. Altered fecal microbiota composition associated with food allergy in infants. Appl Environ Microbiol. 2014; 80:2546–54. [PubMed: 24532064] 19. Ege MJ, Mayer M, Normand A-C, Genuneit J, Cookson WOCM, Braun-Fahrländer C, et al. Exposure to environmental microorganisms and childhood asthma. N Engl J Med. 2011; 364:701– 9. [PubMed: 21345099]


Martin et al.

Page 11

Author Manuscript Author Manuscript Author Manuscript Author Manuscript

20. Azad MB, Konya T, Guttman DS, Field CJ, Sears MR, HayGlass KT, et al. Infant gut microbiota and food sensitization: associations in the first year of life. Clin Exp Allergy. 2015; 45:632–43. [PubMed: 25599982] 21. Stefka AT, Feehley T, Tripathi P, Qiu J, McCoy K, Mazmanian SK, et al. Commensal bacteria protect against food allergen sensitization. Proc Natl Acad Sci USA. 2014; 111:13145–50. [PubMed: 25157157] 22. Berni Canani R, Sangwan N, Stefka AT, Nocerino R, Paparo L, Aitoro R, et al. Lactobacillus rhamnosus GG-supplemented formula expands butyrate-producing bacterial strains in food allergic infants. ISME J. 2016; 10:742–50. [PubMed: 26394008] 23. Arpaia N, Campbell C, Fan X, Dikiy S, van der Veeken J, deRoos P, et al. Metabolites produced by commensal bacteria promote peripheral regulatory T-cell generation. Nature. 2013; 504:451–5. [PubMed: 24226773] 24. Schuppan D. Current concepts of celiac disease pathogenesis. Gastroenterology. 2000; 119:234– 42. [PubMed: 10889174] 25. Laparra JM, Sanz Y. Bifidobacteria inhibit the inflammatory response induced by gliadins in intestinal epithelial cells via modifications of toxic peptide generation during digestion. J Cell Biochem. 2010; 109:801–7. [PubMed: 20052669] 26. Lindfors K, Blomqvist T, Juuti-Uusitalo K, Stenman S, Venäläinen J, Mäki M, et al. Live probiotic Bifidobacterium lactis bacteria inhibit the toxic effects induced by wheat gliadin in epithelial cell culture. Clin Exp Immunol. 2008; 152:552–8. [PubMed: 18422736] 27. Wacklin P, Kaukinen K, Tuovinen E, Collin P, Lindfors K, Partanen J, et al. The duodenal microbiota composition of adult celiac disease patients is associated with the clinical manifestation of the disease. Inflamm Bowel Dis. 2013; 19:934–41. [PubMed: 23478804] 28. Di Cagno R, De Angelis M, De Pasquale I, Ndagijimana M, Vernocchi P, Ricciuti P, et al. Duodenal and faecal microbiota of celiac children: molecular, phenotype and metabolome characterization. BMC Microbiol. 2011; 11:219. [PubMed: 21970810] 29. Tjellström B, Stenhammar L, Högberg L, Fälth-Magnusson K, Magnusson K-E, Midtvedt T, et al. Screening-detected and symptomatic untreated celiac children show similar gut microfloraassociated characteristics. Scand J Gastroenterol. 2010; 45:1059–62. [PubMed: 20509753] 30. Olivares M, Neef A, Castillejo G, Palma GD, Varea V, Capilla A, et al. The HLA-DQ2 genotype selects for early intestinal microbiota composition in infants at high risk of developing coeliac disease. Gut. 2015; 64:406–17. [PubMed: 24939571] 31. Sellitto M, Bai G, Serena G, Fricke WF, Sturgeon C, Gajer P, et al. Proof of concept of microbiome-metabolome analysis and delayed gluten exposure on celiac disease autoimmunity in genetically at-risk infants. PLoS ONE. 2012; 7:e33387. [PubMed: 22432018] 32. Lionetti E, Castellaneta S, Francavilla R, Pulvirenti A, Tonutti E, Amarri S, et al. Introduction of gluten, HLA status, and the risk of celiac disease in children. N Engl J Med. 2014; 371:1295–303. [PubMed: 25271602] 33. Vriezinga SL, Auricchio R, Bravi E, Castillejo G, Chmielewska A, Crespo Escobar P, et al. Randomized feeding intervention in infants at high risk for celiac disease. N Engl J Med. 2014; 371:1304–15. [PubMed: 25271603] 34. Leonard MM, Camhi S, Huedo-Medina TB, Fasano A. Celiac Disease Genomic, Environmental, Microbiome, and Metabolomic (CDGEMM) study design: approach to the future of personalized prevention of celiac disease. Nutrients. 2015; 7:9325–36. [PubMed: 26569299] 35. Corridoni D, Arseneau KO, Cifone MG, Cominelli F. The dual role of nod-like receptors in mucosal innate immunity and chronic intestinal inflammation. Front Immunol. 2014; 5:317. [PubMed: 25071778] 36. Barclay AR, Morrison DJ, Weaver LT. What is the role of the metabolic activity of the gut microbiota in inflammatory bowel disease? Probing for answers with stable isotopes. J Pediatr Gastroenterol Nutr. 2008; 46:486–95. [PubMed: 18493202] 37. Khor B, Gardet A, Xavier RJ. Genetics and pathogenesis of inflammatory bowel disease. Nature. 2011; 474:307–17. [PubMed: 21677747] 38. Manichanh C, Borruel N, Casellas F, Guarner F. The gut microbiota in IBD. Nat Rev Gastroenterol Hepatol. 2012; 9:599–608. [PubMed: 22907164]


Martin et al.

Page 12


39. Gevers D, Kugathasan S, Denson LA, Vázquez-Baeza Y, Van Treuren W, Ren B, et al. The treatment-naive microbiome in new-onset Crohn’s disease. Cell Host Microbe. 2014; 15:382–92. [PubMed: 24629344] 40. Morgan XC, Tickle TL, Sokol H, Gevers D, Devaney KL, Ward DV, et al. Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment. Genome Biol. 2012; 13:R79. [PubMed: 23013615] 41. Manichanh C, Rigottier-Gois L, Bonnaud E, Gloux K, Pelletier E, Frangeul L, et al. Reduced diversity of faecal microbiota in Crohn’s disease revealed by a metagenomic approach. Gut. 2006; 55:205–11. [PubMed: 16188921] 42. Seksik P, Rigottier-Gois L, Gramet G, Sutren M, Pochart P, Marteau P, et al. Alterations of the dominant faecal bacterial groups in patients with Crohn’s disease of the colon. Gut. 2003; 52:237– 42. [PubMed: 12524406] 43. Willing BP, Dicksved J, Halfvarson J, Andersson AF, Lucio M, Zheng Z, et al. A pyrosequencing study in twins shows that gastrointestinal microbial profiles vary with inflammatory bowel disease phenotypes. Gastroenterology. 2010; 139:1844–54. e1. [PubMed: 20816835] 44. Swidsinski A, Ladhoff A, Pernthaler A, Swidsinski S, Loening-Baucke V, Ortner M, et al. Mucosal flora in inflammatory bowel disease. Gastroenterology. 2002; 122:44–54. [PubMed: 11781279] 45. Chassaing B, Koren O, Goodrich JK, Poole AC, Srinivasan S, Ley RE, et al. Dietary emulsifiers impact the mouse gut microbiota promoting colitis and metabolic syndrome. Nature. 2015; 519:92–6. [PubMed: 25731162] 46. Negroni A, Costanzo M, Vitali R, Superti F, Bertuccini L, Tinari A, et al. Characterization of adherent-invasive Escherichia coli isolated from pediatric patients with inflammatory bowel disease. Inflamm Bowel Dis. 2012; 18:913–24. [PubMed: 21994005] 47. Michail S, Durbin M, Turner D, Griffiths AM, Mack DR, Hyams J, et al. Alterations in the gut microbiome of children with severe ulcerative colitis. Inflamm Bowel Dis. 2012; 18:1799–808. [PubMed: 22170749] 48. Groer MW, Luciano AA, Dishaw LJ, Ashmeade TL, Miller E, Gilbert JA. Development of the preterm infant gut microbiome: a research priority. Microbiome. 2014; 2:38. [PubMed: 25332768] 49. Uauy RD, Fanaroff AA, Korones SB, Phillips EA, Phillips JB, Wright LL. Necrotizing enterocolitis in very low birth weight infants: biodemographic and clinical correlates. National Institute of Child Health and Human Development Neonatal Research Network. J Pediatr. 1991; 119:630–8. [PubMed: 1919897] 50. Fitzgibbons SC, Ching Y, Yu D, Carpenter J, Kenny M, Weldon C, et al. Mortality of necrotizing enterocolitis expressed by birth weight categories. J Pediatr Surg. 2009; 44:1072–5. discussion 1075–6. [PubMed: 19524719] 51. Claud EC, Walker WA. Bacterial colonization, probiotics, and necrotizing enterocolitis. J Clin Gastroenterol. 2008; 42(suppl 2):S46–52. [PubMed: 18520617] 52. Viscardi RM, Lyon NH, Sun CC, Hebel JR, Hasday JD. Inflammatory cytokine mRNAs in surgical specimens of necrotizing enterocolitis and normal newborn intestine. Pediatr Pathol Lab Med. 1997; 17:547–59. [PubMed: 9211547] 53. Halpern MD, Holubec H, Dominguez JA, Williams CS, Meza YG, McWilliam DL, et al. Upregulation of IL-18 and IL-12 in the ileum of neonatal rats with necrotizing enterocolitis. Pediatr Res. 2002; 51:733–9. [PubMed: 12032269] 54. Harris MC, D’Angio CT, Gallagher PR, Kaufman D, Evans J, Kilpatrick L. Cytokine elaboration in critically ill infants with bacterial sepsis, necrotizing entercolitis, or sepsis syndrome: correlation with clinical parameters of inflammation and mortality. J Pediatr. 2005; 147:462–8. [PubMed: 16227031] 55. Seitz G, Warmann SW, Guglielmetti A, Heitmann H, Ruck P, Kreis ME, et al. Protective effect of tumor necrosis factor alpha antibody on experimental necrotizing enterocolitis in the rat. J Pediatr Surg. 2005; 40:1440–5. [PubMed: 16150346] 56. Morowitz MJ, Poroyko V, Caplan M, Alverdy J, Liu DC. Redefining the role of intestinal microbes in the pathogenesis of necrotizing enterocolitis. Pediatrics. 2010; 125:777–85. [PubMed: 20308210]


Martin et al.

Page 13


57. Warner BB, Deych E, Zhou Y, Hall-Moore C, Weinstock GM, Sodergren E, et al. Gut bacteria dysbiosis and necrotising enterocolitis in very low birthweight infants: a prospective case-control study. Lancet. 2016; 387:1928–36. [PubMed: 26969089] 58. Colaizy TT, Bartick MC, Jegier BJ, Green BD, Reinhold AG, Schaefer AJ, et al. Impact of optimized breastfeeding on the costs of necrotizing enterocolitis in extremely low birthweight infants. J Pediatr. 2016; 175:100–5. e2. [PubMed: 27131403] 59. Neu J. Necrotizing enterocolitis: the mystery goes on. Neonatology. 2014; 106:289–95. [PubMed: 25171544] 60. World Health Organization. WHO global strategy on diet, physical activity and health. Geneva, Switzerland: WHO; 2006. 61. Mueller NT, Whyatt R, Hoepner L, Oberfield S, Dominguez-Bello MG, Widen EM, et al. Prenatal exposure to antibiotics, cesarean section and risk of childhood obesity. Int J Obes (Lond). 2015; 39:665–70. [PubMed: 25298276] 62. Cannon MV, Buchner DA, Hester J, Miller H, Sehayek E, Nadeau JH, et al. Maternal nutrition induces pervasive gene expression changes but no detectable DNA methylation differences in the liver of adult offspring. PLoS ONE. 2014; 9:e90335. [PubMed: 24594983] 63. Gluckman PD, Hanson MA. Living with the past: evolution, development, and patterns of disease. Science. 2004; 305:1733–6. [PubMed: 15375258] 64. Bateson P, Gluckman P, Hanson M. The biology of developmental plasticity and the Predictive Adaptive Response hypothesis. J Physiol. 2014; 592:2357–68. [PubMed: 24882817] 65. Bergström A, Skov TH, Bahl MI, Roager HM, Christensen LB, Ejlerskov KT, et al. Establishment of intestinal microbiota during early life: a longitudinal, explorative study of a large cohort of Danish infants. Appl Environ Microbiol. 2014; 80:2889–900. [PubMed: 24584251] 66. Fallani M, Amarri S, Uusijarvi A, Adam R, Khanna S, Aguilera M, et al. Determinants of the human infant intestinal microbiota after the introduction of first complementary foods in infant samples from five European centres. Microbiology (Reading, Engl). 2011; 157(Pt 5):1385–92. 67. Matamoros S, Gras-Leguen C, Le Vacon F, Potel G, de La Cochetiere M-F. Development of intestinal microbiota in infants and its impact on health. Trends Microbiol. 2013; 21:167–73. [PubMed: 23332725] 68. Bailey LC, Forrest CB, Zhang P, Richards TM, Livshits A, DeRusso PA. Association of antibiotics in infancy with early childhood obesity. JAMA Pediatr. 2014; 168:1063–9. [PubMed: 25265089] 69. Gerber JS, Bryan M, Ross RK, Daymont C, Parks EP, Localio AR, et al. Antibiotic exposure during the first 6 months of life and weight gain during childhood. JAMA. 2016; 315:1258–65. [PubMed: 27002447] 70. Korpela K, Salonen A, Virta LJ, Kekkonen RA, de Vos WM. Association of early-life antibiotic use and protective effects of breastfeeding. JAMA Pediatr. 2016; 170:750–7. [PubMed: 27294842] 71. Cox LM, Yamanishi S, Sohn J, Alekseyenko AV, Leung JM, Cho I, et al. Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences. Cell. 2014; 158:705–21. [PubMed: 25126780] 72. Mahana D, Trent CM, Kurtz ZD, Bokulich NA, Battaglia T, Chung J, et al. Antibiotic perturbation of the murine gut microbiome enhances the adiposity, insulin resistance, and liver disease associated with high-fat diet. Genome Med. 2016; 8:48. [PubMed: 27124954] 73. Glickman, D.Parker, L.Sim, LJ., et al., editors. Committee on Accelerating Progress in Obesity Prevention, Food and Nutrition Board, Institute of Medicine. Accelerating progress in obesity prevention: solving the weight of the nation. Washington (DC): National Academies Press (US); 2012. 74. Juneau M, Hayami D, Gayda M, Lacroix S, Nigam A. Provocative issues in heart disease prevention. Can J Cardiol. 2014; 30(12 suppl):S401–9. [PubMed: 25444498] 75. Suhre K, Meisinger C, Döring A, Altmaier E, Belcredi P, Gieger C, et al. Metabolic footprint of diabetes: a multiplatform metabolomics study in an epidemiological setting. PLoS ONE. 2010; 5:e13953. [PubMed: 21085649] 76. Palau-Rodriguez M, Tulipani S, Isabel Queipo-Ortuño M, Urpi-Sarda M, Tinahones FJ, AndresLacueva C. Metabolomic insights into the intricate gut microbial-host interaction in the development of obesity and type 2 diabetes. Front Microbiol. 2015; 6:1151. [PubMed: 26579078]


Martin et al.

Page 14


77. Falony G, Joossens M, Vieira-Silva S, Wang J, Darzi Y, Faust K, et al. Population-level analysis of gut microbiome variation. Science. 2016; 352:560–4. [PubMed: 27126039] 78. Costeloe K, Hardy P, Juszczak E, Wilks M, Millar MR. Probiotics in Preterm Infants Study Collaborative Group. Bifidobacterium breve BBG-001 in very preterm infants: a randomised controlled phase 3 trial. Lancet. 2016; 387:649–60. [PubMed: 26628328] 79. Lee CH, Steiner T, Petrof EO, Smieja M, Roscoe D, Nematallah A, et al. Frozen vs fresh fecal microbiota transplantation and clinical resolution of diarrhea in patients with recurrent clostridium difficile infection: a Randomized Clinical Trial. JAMA. 2016; 315:142–9. [PubMed: 26757463] 80. Hourigan SK, Oliva-Hemker M. Fecal microbiota transplantation in children: a brief review. Pediatr Res. 2016; 80:2–6. [PubMed: 26982451] 81. Bowman KA, Broussard EK, Surawicz CM. Fecal microbiota transplantation: current clinical efficacy and future prospects. Clin Exp Gastroenterol. 2015; 8:285–91. [PubMed: 26566371] 82. Collins SM, Kassam Z, Bercik P. The adoptive transfer of behavioral phenotype via the intestinal microbiota: experimental evidence and clinical implications. Curr Opin Microbiol. 2013; 16:240– 5. [PubMed: 23845749] 83. Franzosa EA, Morgan XC, Segata N, Waldron L, Reyes J, Earl AM, et al. Relating the metatranscriptome and metagenome of the human gut. Proc Natl Acad Sci USA. 2014; 111:E2329–38. [PubMed: 24843156]

Author Manuscript Author Manuscript J Pediatr. Author manuscript; available in PMC 2017 June 21.

Martin et al.

Page 15

Author Manuscript Author Manuscript Figure 1.

Author Manuscript

Proposed mechanism for the development of chronic inflammatory diseases in children, highlighting early-life risk factors that likely influence the pediatric microbiome and immune system development. CID, chronic inflammatory disease.

Author Manuscript J Pediatr. Author manuscript; available in PMC 2017 June 21.

Martin et al.

Page 16


Figure 2.

Path by which the proposed multi-omic approach will lead us from correlation to causation, while simultaneously allowing for novel discoveries in both diagnostic and therapeutic targets.

Author Manuscript Author Manuscript J Pediatr. Author manuscript; available in PMC 2017 June 21.

A vascular mechanistic approach to understanding Raynaud phenomenon.

The longitudinal approach to the pathogenesis of respiratory disease.

Transitioning from 1:1 to 1: 2 Supervision in Anesthesia Training: A Descriptive Survey.

Transitioning from First Drug Use to Dependence Onset: Illustration of a Multiparametric Approach for Comparative Epidemiology.

Membrane Binding of Recoverin: From Mechanistic Understanding to Biological Functionality.

The urgent need for a systems biology approach to neurology.

A mechanistic approach to understanding oral drug absorption in pediatrics: an overview of fundamentals.

Transitioning from Microbiome Composition to Microbial Community Interactions: The Potential of the Metaorganism Hydra as an Experimental Model.

A novel approach to teach the generation of bioelectrical potentials from a descriptive and quantitative perspective.

Understanding the evolution of Mammalian brain structures; the need for a (new) cerebrotype approach.

Congenital heart disease: transitioning from pediatric to adult cardiology care.

A mechanistic approach to modeling respiratory sensitization.

Predicting evidence-based treatment sustainment: results from a longitudinal study of the Adolescent-Community Reinforcement Approach.

Development of the cutaneous microbiome in the preterm infant: A prospective longitudinal study.

Understanding the role of gut microbiome in metabolic disease risk.

Understanding the apothecaries within: the necessity of a systematic approach for defining the chemical output of the human microbiome.

A mechanistic approach to tracing anthropometric charts: the extended mechanistic growth function method.

A seamless approach to understanding and predicting Arctic sea ice in Met Office modelling systems.

Evaluations of Factors Predicting the Need for an Extra-Cervical Approach for Intra-Thoracic Goiter.

The transitioning from trials to extended follow-up studies.

The growing demand for midtrimester amniocentesis: a systems approach to forecasting the need for facilities.

The free and cued selective reminding test for predicting progression to Alzheimer's disease in patients with mild cognitive impairment: A prospective longitudinal study.

What if fertility decline is not permanent? The need for an evolutionarily informed approach to understanding low fertility.

Predicting progression from mild cognitive impairment to Alzheimer's disease using longitudinal callosal atrophy.