Multi-omics analysis reveals the influence of genetic and environmental risk factors on developing gut microbiota in infants at risk of celiac disease

Multi-omics analysis reveals the influence of genetic and environmental risk factors on developing gut microbiota in infants at risk of celiac disease | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Multi-omics analysis reveals the influence of genetic and environmental risk factors on developing gut microbiota in infants at risk of celiac disease Maureen M Leonard, Hiren Karathia, Meritxell Pujolassos, Jacopo Troisi, and 17 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.2.24237/v3 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Sep, 2020 Read the published version in Microbiome → Version 3 posted 7 You are reading this latest preprint version Show more versions Abstract Background : Celiac disease (CD) is an autoimmune digestive disorder that occurs in genetically susceptible individuals in response to ingesting gluten, a protein found in wheat, rye, and barley. Research shows that genetic predisposition and exposure to gluten are necessary but not sufficient to trigger the development of CD. This suggests that exposure to other environmental stimuli early in life, e.g., cesarean section delivery, exposure to antibiotics or formula feeding, may also play a key role in CD pathogenesis through yet unknown mechanisms. Here, we use multi-omics analysis to investigate how genetic and early environmental risk factors alter the development of the gut microbiota in infants at risk of CD. Results : Toward this end, we selected 31 infants from a large-scale prospective birth cohort study of infants with a first-degree relative with CD. We then performed rigorous multivariate association, cross-sectional and longitudinal analyses using metagenomic and metabolomic data collected at birth, three months and six months of age to explore the impact of genetic predisposition and environmental risk factors on the gut microbiota composition, function and metabolome prior to the introduction of trigger (gluten). These analyses revealed several microbial species, functional pathways and metabolites that are associated with each genetic and environmental risk factor or that are differentially abundant between environmentally exposed and non-exposed infants or between time points. Among our significant findings, we found that cesarean section delivery is associated with a decreased abundance of Bacteroides vulgatus and Bacteroides dorei and of folate biosynthesis pathway, and with an increased abundance of hydroxyphenylacetic acid, alterations that are implicated in immune system dysfunction and inflammatory conditions. Additionally, longitudinal analysis revealed that, in infants not exposed to any environmental risk factor, the abundances of Bacteroides uniformis and of metabolite 3-3-hydroxyphenylproprionic acid increase over time while those for lipoic acid and methane metabolism pathways decrease, patterns that are linked to beneficial immunomodulatory and anti-inflammatory effects. Conclusions : Overall, our study provides unprecedented insights into major taxonomic and functional shifts in the developing gut microbiota of infants at risk of CD linking genetic and environmental risk factors to detrimental immunomodulatory and inflammatory effects. General Microbiology Microbiota Celiac disease Multi-omics analysis gut microbiome Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Celiac disease (CD) is an autoimmune enteropathy, which affects three million Americans and 1% of the population worldwide [1]. CD occurs in genetically predisposed individuals that have specific variants of the human leukocyte antigen (HLA) DQ2 and DQ8 genes in response to ingesting gluten, a protein found in wheat, rye, and barley [2]. Notably, CD is the only autoimmune disorder for which the environmental trigger (ingestion of gluten) is known [3]. Given that the timing of exposure to gluten and the dose of gluten ingested can be carefully monitored, and since gluten removal results in the resolution of symptoms and enteropathy for most patients [4-8], CD can serve as a tunable model of chronic immune-based disorders [9]. This allows for insights into its pathogenesis to be applied not only to individuals with CD but those with other autoimmune diseases as well. Globally, the incidence of autoimmune diseases including CD is expected to triple by 2050 [10, 11], yet the genes associated with CD (HLA DQ2) and DQ8, and the trigger (gluten) have not changed. Research shows that more than 30% of the population carry the predisposing gene(s) and are exposed to the trigger yet only 2-3% of these individuals develop CD in their lifetime thus suggesting a critical role for environmental factors [12]. Mode of delivery, infant feeding type, timing of gluten introduction into the diet, occurrence of viral infections and early exposure to antibiotics are just a few of the many environmental factors suggested to influence the development of chronic inflammatory diseases such as CD [13]. When evaluating these factors independently, case-control studies and meta-analyses have found that cesarean section delivery [14, 15], lack of breast-feeding [16, 17], timing of gluten introduction [17, 18] and exposure to antibiotics [19] increase the risk of developing CD. However, two independent double blind placebo controlled prospective studies in Europe involving infants with compatible HLA genetics and a first-degree relative with CD (who are therefore at high risk of developing CD) found that vaginal delivery, breast-feeding, and timing of gluten introduction were not protective against developing CD [20, 21]. Accumulating evidence suggests that the gut microbiota may be involved in several immune based disorders [13] such as inflammatory bowel disease (IBD) [22], type 1 diabetes (T1D) [23] and multiple sclerosis [24]. A limited number of studies have also started to explore the link between the gut microbiota and CD development [25-30]. Initial studies focused on the contribution of HLA genetics to the developing microbiota. In particular, two studies analyzed exclusively breastmilk-fed infants up to 4 months of age with a first-degree relative with CD and found that Bacteroides-Prevotella group [25], Firmicutes , Proteobacteria , and Bifidobacterium [26] were more abundant in infants at high genetic risk for CD (those with two copies of HLA DQ2). Additionally, in a preliminary prospective study, we used 16S rRNA amplicon sequencing to examine the microbiota from 16 infants with a first-degree relative with CD and with a compatible HLA type and found a lower abundance of Bacteroides and a higher abundance of Firmicutes in these subjects compared to controls [27]. Other studies of the gut microbiota and CD have assessed changes, within one year of age, in the microbiota composition of individuals who later developed CD compared to controls [29, 30]. For example, Olivares et al [29] identified increases in the abundances of Firmicutes, Enterococcaceae , and Peptostreptococcaceae in controls from 4 to 6 months but no differences over time were observed in cases [29]. While the link between environmental factors and alterations in the gut microbiota of at-risk subjects has been recently explored for a number of chronic immune based disorders [31, 32], studies addressing this question for CD are scarce [28]. The only study in this direction is the work of Pozo-Rubio et al [28], where they found associations between a limited number of pre-selected fecal microbial taxa in subjects at risk of CD and delivery mode, infant feeding type, antibiotic exposure and rotavirus vaccine administration [28]. While these studies have provided valuable insights into the development of the gut microbiota early in life in subjects at risk of CD, solid food has already been introduced into the infants’ diet in many of these studies without accounting for its impact on the microbiota. In addition, to the best of our knowledge, no microbiome-wide study of the effect of environmental risk factors for CD currently exists. More importantly, existing studies are primarily based on 16S rRNA amplicon sequencing, which is not capable of fully addressing how the functional characterization of the microbiota will affect CD onset. To mitigate these limitations, here, we utilize a large-scale prospective cohort study called the Celiac Disease Genomic, Environmental, Microbiome and Metabolome study (CDGEMM) [33], where we have been following over 400 infants with a first-degree relative with CD who are thus at a high risk of developing CD. In this study, we present multivariate association as well as inter-subject and intra-subject analyses using metagenomic and metabolomic data collected over the first six months after birth to investigate the impact of both genetic and environmental risk factors on the development of the gut microbiota of infants at risk of CD prior to the introduction of solid foods. Results We selected 31 children recruited into the CDGEMM cohort for whom stool samples were available at birth, 3 months, and 4-6 months for this study (see Figure 1, Table 1 and see Additional File 1 for more detailed metadata). None of these infants consumed solid foods before 6 months, which makes them ideal for studying the effect of genetic and environmental risk factors on the gut microbiota in the absence of gluten as a confounder. Twenty-six of these infants were genetically susceptible to developing CD out of which 19 were either heterozygous for DQ2 or DQ8 or carried both DQ2 and DQ8 (referred to as “standard genetic risk” hereafter) and seven were homozygous for DQ2 (referred to as “high genetic risk” hereafter). Additionally, 19 infants who were genetically predisposed to CD and that have been exposed to at least one environmental risk factor are referred to as “environmentally exposed” infants throughout the rest of manuscript. The environmental factors that we considered in this study include delivery model, antibiotic exposure and infant feeding type. Therefore, environmentally exposed infants are the ones who were born via cesarean section or were exposed to antibiotics at or during birth (i.e., antibiotics administered to the mother during delivery) or were not exclusively breastmilk-fed (i.e., formula-fed or both formula- and breastmilk-fed). The choice of these environmental risk factors and their grouping is clinically relevant since cesarean section delivery is often associated with antibiotic administration at birth and formula feeding due to delayed breastmilk production. Seven infants who were genetically susceptible and that were not exposed to any of these environmental risk factors, i.e., those born vaginally and not exposed to antibiotics at or during delivery and exclusively breastmilk-fed, are referred to as “environmentally non-exposed” hereafter (see Figure 1). Collected stool samples underwent shotgun metagenomic sequencing and metabolomic profiling. We analyzed metagenomic sequencing reads (see Methods) to profile microbial taxa at species-level resolution (see Additional File 2 see also Additional File 3 for the taxonomic composition of each sample at the genus and family levels) and functional pathways encoded by metagenomes (see Additional File 4). While we identified non-bacterial species (fungi, viruses, protists) in our taxonomic profiling, in this paper, we focus only on the bacterial species. Additionally, stool samples underwent metabolomic profiling and were analyzed to identify metabolites present in each stool sample (see Additional File 5). The identified microbial taxa, functional pathways and metabolites were then analyzed to explore how genetic and environmental risk factors influence the development of the gut microbiota as outlined below. Associations between genetic and environmental risk factors and microbiota features We used the MaAslin procedure [34] to investigate how various microbiome features including microbial species, functional pathways and metabolites at each time point are associated with genetic risk for developing CD and three key environmental risk factors including mode of delivery, exposure to antibiotics and infant feeding type (see Figures 2-4). Genetic risk: We found that both high and standard genetic risk to develop CD are associated with a decreased abundance of several species of Streptococcus and Coprococcus at 4-6 months of age compared to those lacking genetic compatibility (Figure 2; p-value < 0.05). Notably, a decreased abundance of Coprococcus has been previously reported in the gut of individuals who carry a genetic risk to develop autoimmune conditions including CD [35]. Standard and high genetic risk for developing CD are also associated with an increased abundance of Bacteroides and Enterococcus species, respectively, at enrollment compared to no genetic risk. These observations are in agreement with previous studies [25, 26], however, an association between genetic risk and increased abundance of Bifidobacterium or Proteobacteria , which were reported before [25, 26] were not observed here. Among other significant associations, we found a decreased abundance of Veillonella, Parabacteroides and Clostridium perfringens at 4-6 months after birth in infants with high and standard genetic compatibility. This observation is contrary to case-control studies that report an increased abundance of these microbes in autoimmune conditions such as autoimmune liver disease [36], Bechet’s disease [37] and neuromyelitis optica [38]. In addition to association with microbial species, we found that a high genetic risk of developing CD is associated with a decreased abundance of a number of functional pathways at 4-6 months of age (Figure 3; p-value < 0.05). These pathways include amino acid metabolism, biosynthesis of secondary metabolites and metabolism of cofactors including ubiquinone and other terpenoid-quinone biosynthesis. Furthermore, we identified an association between high genetic risk and a number of metabolites, e.g., an increased abundance of butanoic acid and a decreased abundance of dihydroxyacteone at 3 and 4-6 months of age (Figure 4, p-value < 0.05). Mode of delivery: We found that cesarean section delivery is associated with a decreased abundance of several species of Bacteroides and Parabacteroides at all time points and with an increased abundance of Enterococcus faecalis (at 3 months after birth) compared to vaginal delivery (Figure 2; p-value < 0.05) in agreement with previous work [23, 39-41]. For example, we found associations between cesarean section delivery and a decreased abundance of beneficial species Bacteroides vulgatus and Bacteroides dorei. An increased abundance of these species has been reported to lead to a decreased gut microbial production of lipopolysaccharide, which will improve immune function through mechanisms such as major histocompatibility production and T cell activation, among others [42]. Analysis of pathways shows also an association between cesarean section delivery and decreased riboflavin metabolism and folate biosynthesis at 4-6 months after birth and an increase in the abundance of glycerolipid metabolism at 3 and 4-6 months (Figure 3; p-value < 0.05). Of note, defects in folate biosynthesis have been linked to an impaired immune response to viral infections and reduced natural killer cell response possibly contributing to T1D onset [43]. Finally, metabolites analysis unveiled an association between cesarean section delivery and an increase in the abundance of a number of metabolites such as butanoic acid (at 3 and 4-6 months), glycolic acid, oxalic acid, and hydroxyphenlacetic acid (at 4-6 months) and a decrease in that of valine, serine, and arabinoic acid among others (at 4-6 months) (Figure 4, p-value < 0.05). An increased abundance of hydroxyphenlacetic acid in the serum has been associated with ulcerative colitis in a previous study [44], however, no clear links between the level of metabolites in the gut and those in the serum have been established yet. Additionally, serine, which is decreased in cesarean section delivery, has been reported to be required for effector T cell expansion and thus for modulating the adaptive immune response [45]. Infant feeding type: We examined three infant feeding types in this study including exclusive breastmilk feeding, exclusive formula feeding and both breastmilk and formula feeding, the last two of which were considered as environmental risk factors. Previous work shows an association between infant feeding type and distinct species of Bifidobacterium [23, 46]. Consistent with these reports, we observed that exposure to both breastmilk and formula is associated with a decreased abundance of Bifidobacterium breve ( at 4-6 months) while exclusive formula feeding is associated with an increased abundance of Bifidobacterium adolescentis compared to exclusive breastmilk feeding (Figure 2; p-value < 0.05). We also found that exclusive formula feeding is associated with a decreased abundance of Staphylococcus epidermis (at enrollment) consistent with previous work [47], and with an increased abundance of Ruminococcus gnavus and Lachnospiraceae bacterium (at 3 and 4-6 months), which have been linked to allergic disease [48], diabetes [49] and colonic inflammation [50]. Pathway analysis shows that exposure to formula only or both breastmilk and formula is associated with an increased abundance of pathways for lipids, amino acids and terpendoids metabolism and xenobiotic degradation, and with a decreased abundance of pathways for carbohydrate and energy metabolism (Figure 3; p-value < 0.05). Additionally, metabolomic analysis uncovered an association between both breastmilk and formula feeding with a decreased abundance of homoserine, alpha-D-glucopyranoside, and hydrocinnamic acid (at 4-6 months) (Figure 4; p-value < 0.05). Exclusive formula feeding is also associated with an increase in sucrose and threonine and a decrease in oxalic acid and dihydroxyacetone abundances, among others (at 4-6 months). Antibiotic use : We found an association between antibiotic exposure (as an environmental risk factor) and an increased abundance of Bacteroides thetaiotaomicron (at 4-6 months of age) (Figure 2; p-value < 0.05). This is corroborated with previous work suggesting that this species, which is an important metabolizer of polysaccharides, increases in abundance in response to amoxicillin exposure [51]. Other identified associations for antibiotic exposure not previously reported include an increased Propionibacterium , Subdoligranulum species and a decreased abundance of Bifidobacterium merycicum and Strepotococcus lutetiensis (at 4-6 months). Pathway analysis also revealed an association between antibiotic exposure and a decreased abundance of phenylalanine metabolism and an increased abundance of cyanoamino acid (3 and 4-6 months) and galactose metabolism (4-6 months) (Figure 3; p-value < 0.05). Analysis of metabolites showed associations between antibiotic exposure and a number of metabolites including decreased sucrose abundance (at 4-6 months) (Figure 4; p-value < 0.05). Changes in the microbiota of environmentally exposed vs. non-exposed infants Here, we performed a cross-sectional (inter-subject) analysis to explore how various features of the gut microbiota (microbes, pathways and metabolites) change between genetically predisposed infants who were exposed to at least one environmental risk factor noted before (environmentally exposed infants) vs. those who were not (environmentally non-exposed infants) (Figure 5). This analysis did not identify any microbial species whose abundance is significantly different between the environmentally exposed and non-exposed infants. Pathways analysis, however, revealed that environmentally exposed infants have a higher abundance of pathways for xenobiotic degradation, fatty acid metabolism, and lipid metabolism among others (at enrollment) and of pathways such as toluene and xylene and biphenyl degradation (at 4-6 months) (Figure 5A; p-value < 0.05). Metabolomic analysis identified alterations such as a decreased abundance of homoserine (at enrollment and 3 months) and of 2-ketobutryic acid (at enrollment) as well as an increased abundance of ribose (peak 2) (at 3 and 4-6 months) in environmentally exposed infants compared to non-exposed infants (Figure 5B; p-value < 0.05). Longitudinal changes in the microbiota of environmentally exposed and non-exposed infants Given the unique prospective study design of our cohort, we were able to perform a longitudinal (intra-subject) analysis to gain additional insights beyond a cross-sectional analysis by identifying dynamic alterations in the gut microbiota composition, function and metabolome in the first six months after birth. To this end, we explored changes in the microbiota features noted above between all pairs of time points that are observed exclusively in environmentally exposed or exclusively in environmentally non-exposed infants (Figure 6). By longitudinal analysis of microbial species, we found that the abundance of a number of species increases over time in the environmentally exposed infants (Figure 6A; p-value < 0.05). For example, the abundance of Anaerostipes caccae monotonically increases during the study period and that of Klebsiella species and Erysipelotrichaceae bacterium increases from enrollment to 4-6 months. Among these, Klebsiella, has been associated with the autoimmune condition ankylosing spondylitis [52]. When examining environmentally non-exposed infants, we observe that the abundance of Bacteroides uniformis monotonically increases during the first 6 months after birth, a pattern which has previously been reported in breastmilk-fed infants [53]. In addition, work in mice found that Bacteroides uniformis improves immune defense mechanisms, which are impaired in obesity, by decreasing TNF-a production and increasing IL-10 production [54]. In our study, we also observed a decrease in the abundance of Veillonella species from enrollment to 4-6 months in non-exposed infants. An increased abundance of Veillonella species has been associated with autoimmune hepatitis [36]. Longitudinal pathway analysis revealed that the abundance of ether lipid metabolism increases from 3 to 4-6 months of age in environmentally exposed infants (Figure 6B; p-value < 0.05). Notably, a decreased abundance of ether lipids in the serum of children with T1D compared to healthy controls has been observed, [55] although the relationship between the abundance of microbial pathways for ether lipid metabolism in the gut and the level of ether lipids in the serum are yet to be explored. For the non-exposed infants, we observe a decrease in the abundance of sulfur metabolism and lipoic acid metabolism at 3 and 4-6 months, and of methane metabolism and biotin metabolism at 4-6 months compared to enrollment. These patterns are consistent with previous reports [34, 56-62]. For example, increased sulfur metabolism is associated with the development of T1D [56] and is linked to IBD [34]. Additionally, lipoic acid is an antioxidant that has been suggested to have beneficial immunomodulatory effects on the innate and adaptive immune systems in autoimmune diseases [57]. Methane has also been shown to have an anti-inflammatory effect, promoting immune tolerance in the intestine when tested in animal models [58, 59]. Furthermore, biotin is known to enhance innate [60] and adaptive immune responses [61] and biotin deficiency has been associated with immune disorders and inflammation [63, 64]. A previous study also found that high dose of biotin may be useful in treating multiple sclerosis [62]. Metabolomic analysis revealed a monotonic increase in erythritol abundances during the study period and a decrease in propionic acid abundance from enrollment to 4-6 months in environmentally exposed infants (Figure 6C; p-value < 0.05). Propionic acid produced in the colon via bacterial fermentation of fiber promotes regulatory T cell generation [65]. Additionally, increased serum levels of erythritol have been associated with central obesity and weight gain [66], though the link between metabolite levels in the gut and those in the serum is not clear. In environmentally non-exposed infants, we observed an increased abundance of uracil, 3-3-hydroxyphenylpropionic acid and dihydroxyacetone from enrollment to 4-6 months. Previous work suggests that 3-hydroxyphenylproprionic acid acts as an anti-inflammatory and antioxidant agent [67]. Linking Microbial Species, Pathways and Metabolites In order to link microbial species, pathways and metabolites identified in these analyses, we performed a correlation analysis (using Spearman rank correlation) as detailed in Additional File 6, which resulted in several significant correlations between these features as summarized in Additional File 7. For example, exploring the links between pathways and metabolites with altered abundance in the cross-sectional analysis identified positive associations between ribose (peak 2) and biphenyl degradation and between toluene and xylene degradation in the environmentally exposed infants. In addition, association analysis between significant pathways and metabolites in the longitudinal analysis identified a negative association at 3 and 4-6 months between 3-3-hydroxyphenylpropionic acid and sulfur, lipoic acid, methane and biotin metabolism in non-exposed infants (Additional File 7). Discussion Several studies have linked exposure to a variety of genetic and environmental risk factors with the onset of non-infective chronic inflammatory diseases [13]. This link has been typically based on the results obtained from either clinical case-control studies [14, 15, 19, 68] or metanalyses [69-72] in which cause-effect relationship cannot always conclusively be determined. Since host genetics and environmental factors are known to influence the gut microbiota composition and function, researchers have started to explore alterations in the gut microbiota of infants at risk of autoimmune conditions such as IBD [31] or T1D [32]. However, to date, there is no systematic study of how protective or detrimental genetic and environmental factors may change the gut microbiota engraftment and its maturation during the first months of life in infants at-risk of CD. In an effort to fill this gap, in this study we used metagenomic and metabolomic data collected in the first 6 months after birth to associate individual risk factors (HLA DQ2/DQ8 genetics, cesarean section delivery, antibiotic use and partial or exclusive formula feeding) with microbial species, pathways and metabolites in the gut. Additionally, we performed cross-sectional analysis to identify microbes, pathways and metabolites that are differentially abundant between infants exposed to at least one environmental risk factor and infants who were not, as well as longitudinal analysis to identify dynamic changes in the gut microbiota in the first six months of life. Notably, we restricted our analysis only to the first six months after birth prior to the introduction of solid foods in order to focus exclusively on the effect of the genetic predisposition and early environmental exposures on the development of the gut microbiota in at-risk infants without any noise from differences in infants diets including gluten. Many microbes, pathways, or metabolites that we identified in these analyses are well supported in the literature to be associated with inflammation, autoimmune disease, or immune system dysfunction, thereby suggesting that they may have similar effects in CD. For example, we found that high risk HLA genetics and formula feeding are both associated with an increased abundance of Ruminococcus gnavus and Lachnospiraceae bacterium , which are linked to allergic diseases [48] and diabetes [49], respectively. Among other significant findings are associations between cesarean section delivery and a decreased abundance of Bacteroides vulgatus and Bacteroides dorei and folate biosynthesis pathway along with an increased abundance of hydroxyphenlacetic acid. All of these patterns have been reported to be associated with impaired immune function [42] and inflammatory conditions such as T1D and ulcerative colitis [43, 44] suggesting that they could also predispose infants to develop CD. While the cross-sectional analysis did not identify any microbial species whose abundance significantly changes between the environmentally exposed and non-exposed infants at any given time point, our longitudinal analysis yielded significant results further stressing the power of intra-subject analysis. This allows us to prospectively evaluate the impact of risk factors on the dynamics of the gut microbiota development and to link dynamics to increased susceptibility to inflammation. For example, environmentally exposed infants show an increasing abundance over time of Klebsiella species, a microbe linked to autoimmune disease [52] and a decreasing abundance over time of propionic acid, a metabolite that promotes innate and adaptive immunity[65]. In contrast, in infants not exposed to environmental risk factors, we observe patterns associated with beneficial immunomodulatory effects and protection against immune system activation and inflammation such as increasing abundance of Bacteroides uniformis over time and decreasing abundance of lipoic acid and methane metabolism [54, 57-59, 67]. Notably, during our analyses, we identified a number of metabolites and pathways with altered abundances in the gut (including hydroxyphenlacetic acid, erythritol and ether lipid metabolism) for which similar variations in the serum are reported to be associated with autoimmune conditions. While the importance of gut-blood axis has been realized fairly recently [73, 74], further investigations are needed to better understand the relationship between different features of the gut microbiota and host- or microbially-derived metabolites in the blood. Unlike previous microbiome studies for CD that are often based on 16S rRNA amplicon sequencing, here, we use shotgun metagenomic sequencing, which is amenable to functional characterization of the microbiota. This is particularly important as previous studies have shown that functional characterization is a more robust descriptor of the status of the microbiota compared to taxonomic composition alone [75, 76]. Furthermore, unlike typical case-control studies, where disease symptoms have already emerged in cases, our prospective birth cohort provides the opportunity to mechanistically link major shifts in the gut microbiota early in life, due to genetic risk factors and environmental exposures, in infants at-risk of CD. Nevertheless, our data should be considered exploratory given the relatively small sample size. This limitation can be mitigated through ongoing recruitment into our CDGEMM cohort, which will allow us to validate our findings using a much larger number of subjects in the future. Conclusions In this paper, we utilized an ongoing prospective study and multi-omics analysis to perform an in-depth analysis of the impact of genetic and environmental risk factors on the longitudinal development of the gut microbiota in infants at risk for CD, before solid foods (including the trigger of CD, gluten) is introduced. These analyses revealed several microbial species, functional pathways and metabolites that have been previously linked to inflammation or immune system dysfunction as well as several new ones that have not been reported before and could be specific to CD. In this study, we restricted our analysis to the first 6 months of life and particularly prior to the introduction of solid foods in order to proactively “regress out” the effect of gluten on the gut microbiota as a major confounder when analyzing the effect of genetic and environmental risk factors. However, while our analysis suggests that the microbiome shifts that we observed during the first six months after birth increase the risk of developing autoimmune conditions including CD based on existing literature, it is unclear whether they indeed contribute to the future development of CD. Therefore, further work is required to investigate alterations in the gut microbiota over a longer period of time, including through the onset of CD. Future work should also consider other environmental factors such as viral infections, timing of solid food (gluten) introduction, amount of gluten ingested and household exposures, e.g. family size and contact with pets, which have been reported to be associated with altered microbiomes [77], or with protection against autoimmune conditions such as asthma [78] and T1D [79]. These investigations warrant future studies, which can utilize this longitudinal study design and multi-omics analysis as a basis to connect alterations in the gut microbiota early in life to the loss of tolerance to gluten and the development of CD. Methods Subjects, sampling, and factors of interest Thirty one healthy infants from the United States (18) and Italy (13) with a first-degree relative with CD participating in the CDGEMM prospective birth cohort study [33] were included in our analysis. These subjects consist of all infants from CDGEMM with available stool samples collected before the introduction of solid foods at 7-15 days (enrollment), 3 months and 4-6 months after birth. Parents answered a detailed questionnaire at enrollment that addressed pregnancy, delivery, family history, household factors, and many other factors related to the infants’ environment before birth and at delivery. Parents also filled out monthly diaries, which addressed infant food intake and any exposure to antibiotics. Infant feeding type was determined according to the reported exclusive feeding type for at least two of the three sample time point collections. Infants who received both breastmilk and formula for at least two of three sample collection points were classified as “both breastmilk and formula fed.” HLA genetic type was determined from whole blood at time of birth (cord blood) or 12 months of age using the DQ-CD Typing Plus (BioDiagne, Palermo, Italy) per the manufacturer’s instructions. Written informed consent was obtained from the parents of infants included in the study according to the standards outlined and approved by the Partners Human Research Committee Institutional Review Board. DNA extraction All fecal samples included in the metagenomic analysis were stored and processed centrally in the United States. Total DNA from each sample was extracted using the Qiagen Power soil DNA extraction kit (Qiagen, Hilden, Germany). Taxonomic profiling General sequencing statistics of all samples, as well as mean sequence quality distribution for metagenomics samples were measured by MultiQC [80]. Since the mean quality value across each base position in the trimmed reads obtained with mulitQC was above quality score 17 for at least 80% of the read length (i.e., probability of correct base call ~98%), reads were not subjected to additional quality trimming steps before uploading to the CosmosID cloud platform. Metagenomic sequencing reads were then analyzed by using the CosmosID’s (CosmosID Inc., Rockville, MD) commercial metagenomic analysis platform (formerly knowns as GENIUS; https://app.cosmosid.com/login) [81, 82], which is based on an assembly-free kmer-based method, to reveal the underlying microbial community composition up to the species-level resolution (see Additional File 6 for a detailed description of this platform and Additional File 2 for information on the sequencing depth of each sample and the number of reads with a taxon assignment. Functional profiling After trimming the raw sequencing reads using BBDuk ( https://jgi.doe.gov/data-and-tools/bbtools/ ) (with parameters), we used the SPAdes tool [83] (with parameter --only-assembler -k 77,99,12 7 ) for the assembly of metagenomes and subsequently and after removing short contigs (length threshold = 500 bp), we used Prodigal (v2.6 using - d parameter) [84] to identify protein coding sequences in the assembled metagenomes. We then utilized InterProScan [85] (with parameters -appl Hamap, ProDom -p and -f tsv ) to annotate the identified genes with biochemical functions based on the KEGG pathways [86]. The relative abundance of each gene was computed as , where, is fragments per kilobase per million (FPKM) for each gene, is the length of the gene, is the coverage of contig in which the gene is identified, is the read length and is the -mer size [87]. The relative abundance of each KEGG pathway was then quantified by summing the relative abundances of all the genes associated to that pathway. Metabolomic profiling All stool samples for metabolomics were stored and processed in Italy. The metabolome extraction, purification and derivatization were carried by the MetaboPrep GC kit (Theoreo, Montecorvino Pugliano, Italy) according to manufacturer instructions. Instrumental analyses were performed with a GC-MS system (GC-2010 Plus gas chromatograph and QP2010 Plus mass spectrometer; Shimadzu Corp., Kyoto, Japan). Sample analysis was performed in triplicate. Additional information related to the extraction, purification, derivatization, GC-MS analysis, and data preprocessing can be found in Additional File 6. The molecular identity of metabolites was determined by analysis of the corresponding mass spectrum in the chromatogram, setting the linear index difference max tolerance to 10. These identified metabolites were further confirmed using external standards according to level 1 Metabolomics Standards Initiative (MSI) [88]. Identifying associations between genetic and environmental risk factors and microbiome features We used the widely-used multivariate statistical framework, MaAsLin, [22] to determine associations between microbial species, functional pathways or metabolites and genetic and environmental risk factors including HLA genetics, delivery mode, infant feeding type and antibiotic exposure at each time point. No genetic risk, vaginal delivery, exclusive breastmilk-feeding and no antibiotic exposure were considered as the reference levels for HLA genetics, delivery mode, infant feeding type and antibiotic exposure, respectively. All metadata variables were forced simultaneously to control for confounders. Significant results were reported using a p-value threshold of 0.05. Cross-sectional and longitudinal analysis For the cross-sectional analysis, we performed the Mann-Whitney U (Wilcoxon Rank Sum) test to compare the abundance of microbial species, pathways and metabolites at each time point between the environmentally exposed and non-exposed groups (using a p-value threshold of 0.05 to report significant results). For the longitudinal analysis, we performed the paired Wilcoxon (Wilcoxon Signed Rank) test to compare the abundances of microbial species, pathways and metabolites between each pair of time points using the same p-value threshold noted above to report the significant results. Analyses of microbial species and pathways were performed in Python (using scipy.stats.mannwhitneyu and scipy.stats.wilcoxon functions) and those for metabolites were performed in R (using Ttest.Anal function of the MetaboAnalyst package [89] using parameters nonpar=TRUE and paired=FALSE for the cross-sectional and paired=TRUE for the longitudinal analysis). Declarations Ethics approval and consent to participate : Written informed consent was obtained from the parents of infants included in the study according the standards outlined and approved by the Partners Human Research Committee Institutional Review Board. Clinical trial registration This study is registered at clinicaltrials.gov with the identifier NCT02061306. Availability of data and material The datasets supporting the conclusions of this article are submitted to the NCBI Short Read Archive (SRA) repository, under BioProjectID: PRJNA486782 and SRA accession number SRP158417. Additional data from the analyses presented in this paper are available in the Supplementary Material. Competing interests AF is a stockholder at Alba Therapeutics, serves as a consultant for Inova Diagnostics and Innovate Biopharmaceuticals, is an advisory board member for Axial Biotherapeutics and Ubiome, and has a speaker agreement with Mead Johnson Nutrition. MML serves as a consultant to HealthMode and Anokion, has a speaker agreement with Takeda Pharmaceuticals, and performs sponsored research with Glutenostics LLC. HK is a former employee, BF is a current employee, PS is a consultant and RRC and NAH are stockholders at CosmosID Inc. Other authors have declared no competing interests exist. Authors' contributions MML designed the study, analyzed the data analysis results and drafted the manuscript. HK performed taxonomic and functional analysis. PS contributed to taxonomic profiling and analysis. MP, JT, and AC designed metabolomic studies and performed metabolomic data analysis. GS isolated the DNA. SC and VK recruited participants and coordinated the US study. FV recruited and supervised the Italian sites and secured sample collection. SC, MM, BM, RF, and LE recruited and coordinated the study, secured sample collection, and subject participation. NAH and RRC oversee CosmosID metagenomic sequencing and data analysis platforms. BF and NAH performed taxonomic profiling of metagenomic data analysis. ARZ designed all the computational studies, analyzed the data analysis results and drafted the manuscript. AF conceived the study, analyzed the data analysis results and aided in manuscript preparation. All authors read and approved the manuscript. Acknowledgements: The authors would like to thank the families that participate in this study and whose contribution was instrumental to the findings described in this manuscript and the CDGEMM team including Pasqua Piemontese, Angela Calvi, Mariella Baldassarre, Lorenzo Norsa, Chiara Maria Trovato, Celeste Lidia Raguseo, Tiziana Passaro, Paola Roggero, Marco Crocco, Annalisa Morelli, Michela Perrone, Marcello Chieppa, Giovanni Scala,Maria Elena Lionetti, Carlo Catassi, Adelaide Serretiello, Corrado Vecchi, and Gemma Castillejo de Villsante. Funding This work was partially supported by funding from the NIH NIDDK; DK104344 to AF, DK109620 and K23DK122127 to MML, funding from Nutrition Obesity Research Center at Harvard (P30-DK040561) and the Thrasher Research Fund to MML, and the faculty start-up funding by Mucosal Immunology and Biology Research Center at Massachusetts General Hospital to ARZ, and through the generous support of Joyce and Hugh McCormick. Supplementary information Additional File 1. Clinical metadata for the subjects in this study. Additional File 2. Results of the taxonomic profiling of metagenomic samples. Additional File 3. Taxonomic composition at the genus and family level for metagenomes. Additional File 4. Results of the functional profiling of metagenomic samples. Additional File 5. Results of the metabolomic profiling of stool samples. Additional File 6. Supplementary text describing details of data analysis methods. Additional File 7. The results of association studies between significant features (microbes, pathways and metabolites). Additional File 8. Functional categorization of pathways with significantly altered abundances. Additional File 9. Boxplots for significant features in the cross-sectional and longitudinal analysis Abbreviations Celiac disease (CD); Human leukocyte antigen (HLA); Inflammatory bowel disease (IBD), Type 1 diabetes (T1D). References Lionetti E, Gatti S, Pulvirenti A, Catassi C: Celiac disease from a global perspective . Best Pract Res Clin Gastroenterol 2015, 29 (3):365-379. Schuppan D: Current concepts of celiac disease pathogenesis . Gastroenterology 2000, 119 (1):234-242. Green PH, Cellier C: Celiac disease . N Engl J Med 2007, 357 (17):1731-1743. 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USA (n=18) Italy (n=13) Total (n=31) Gender (%) Male 11 (61.1) 7 (53.8) 18 (58.0) Female 7 (38.9) 6 (46.2) 13 (42.0) Mode of Delivery (%) Vaginal 11 (61.1) 7 (53.8) 18 (58.0) C-section 7 (38.9) 6 (46.2) 13 (42.0) Feeding Type (4-6 months of age) (%) Breastmilk only 12 (66.7) 4 (30.7) 16 (51.6) Formula only 5 (27.8) 6 (46.2) 11 (35.5) Both 1 (5.5) 3 (23.1) 4 (12.9) Antibiotic Exposure (%) At delivery (mother) 7 (38.9) 2 (15.4) 9 (29.0) At birth (infant) 2 (11.1) 2 (15.4) 4 (12.9) Before 6 months of age (infant) 0 (0.0) 4 (30.8) 4 (12.9) Genotype (%) DQ2 Homozygous 6 (33.3) 1 (7.7) 7 (22.6) DQ2 Heterozygous 6 (33.3) 6 (46.2) 12 (38.7) DQ2/DQ8 3 (16.7) 2 (15.4) 5 (16.1) DQ8 1 (5.5) 1 (7.7) 2 (6.5) Negative 2 (11.1) 3 (23.1) 5 (16.1) Relative with CD Mother 15 (83.3) 7 (53.8) 22 (70.9) Father 1 (5.5) 1 (7.7) 2 (6.5) Sibling 2 (11.1) 5 (38.4) 7 (22.6) Supplementary Files AdditionalFile1.xlsx AdditionalFile3.pdf AdditionalFile9.pdf AdditionalFile4.xlsx AdditionalFile5.xlsx AdditionalFile7.xlsx AdditionalFile8.xlsx AdditionalFile6.docx AdditionalFile2.xlsx Cite Share Download PDF Status: Published Journal Publication published 11 Sep, 2020 Read the published version in Microbiome → Version 3 posted Editorial decision: Accept 09 Aug, 2020 Reviewers invited by journal 07 Aug, 2020 Reviewer # 1 agreed at journal 07 Aug, 2020 Review # 1 received at journal 07 Aug, 2020 Editor assigned by journal 05 Aug, 2020 Submission checks completed at journal 04 Aug, 2020 Editor invited by journal 04 Aug, 2020 You are reading this latest preprint version Show more versions Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-14796","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research","associatedPublications":[],"authors":[{"id":1222780,"identity":"4aebca63-9ea8-4bab-bcb8-7037801cd590","order_by":0,"name":"Maureen M Leonard","email":"","orcid":"","institution":"MassGeneral Hospital for Children, Harvard Medical School, Mucosal Immunology and Biology Research Center, Celiac Research Program","correspondingAuthor":false,"prefix":"","firstName":"Maureen","middleName":"M","lastName":"Leonard","suffix":""},{"id":1222781,"identity":"4a527220-50e2-4274-8051-22ce0f2e0785","order_by":1,"name":"Hiren 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Fasano","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAUlEQVRIiWNgGAWjYDAC5gNgSo6BgYeBGSpmwMDAhkcLWwKYMiZdS2ID0Vr425gff/i5wyZ9bf/aA8wFNfcS+2cf3sDwoewwTi0Sx9jMJHvPpOVuu/EugXnGseLEGefSChhnnMOtheF+gxkDb9thoJYzBsw8bAnGDGd4DJiBIjh1yB9j//zxb9vhdDOwln8JxvIgLX/xaDE4xmMgDTQzwex8D8jwBDkDkBZGPFoMj/GUScu2pRluu8FjcJi3L0HO8AxbwcGec+k4tcgdY9/88W2bjbzZ+TOGj3m+JfDInWHe+OBHmTVu78OBRALDARj7AG5lyICfSHWjYBSMglEw8gAAfBpWqXl4KSMAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-2134-0261","institution":"Massachusetts General Hospital","correspondingAuthor":true,"prefix":"","firstName":"Alessio","middleName":"","lastName":"Fasano","suffix":""},{"id":1222800,"identity":"ce773dda-da6a-4499-83a9-635fe502b730","order_by":20,"name":"CDGEMM Study Team","email":"","orcid":"","institution":"MassGeneral Hospital for Children, European Biomedical Research Institute of Salernopean","correspondingAuthor":false,"prefix":"","firstName":"CDGEMM","middleName":"Study","lastName":"Team","suffix":""}],"badges":[],"createdAt":"2020-02-20 15:40:57","currentVersionCode":3,"declarations":"","doi":"10.21203/rs.2.24237/v3","doiUrl":"https://doi.org/10.21203/rs.2.24237/v3","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40168-020-00906-w","type":"published","date":"2020-09-11T12:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":1933023,"identity":"613f45f4-dcc8-496b-83e4-f62b1c9cc704","added_by":"auto","created_at":"2020-08-14 17:57:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":106953,"visible":true,"origin":"","legend":"Schematic representing the sample selection and study design. We selected 31 infants from the CDGEMM study [33] with fecal samples available at enrollment, 3 months and 4-6 months after birth. The sample underwent metagenomic and metabolomic profiling and were next analyzed to identify associations between genetic and environmental risk factors and inter-subject and intra-subject variations. ","description":"","filename":"fig1.PNG","url":"https://assets-eu.researchsquare.com/files/rs-14796/v3/fig1.PNG"},{"id":1933024,"identity":"9d631324-18ad-416b-8ce1-123715ad0283","added_by":"auto","created_at":"2020-08-14 17:57:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":156808,"visible":true,"origin":"","legend":"Analysis of associations between genetic and environmental risk factors and microbial species. We used MaAsLin [34], a widely-used multivariate statistical framework, to identify statistically significant associations between each genetic and environmental risk factor and (A) microbial species (p-value \u003c 0.01), No genetic risk, vaginal delivery, exclusive breastmilk feeding and no exposure to antibiotics were taken as reference for genetic risk, delivery mode, feeding type and antibiotic exposure, respectively. Microbial species were clustered based on Euclidean distance. Here, “u_s” denotes and unspecified species.","description":"","filename":"fig2.PNG","url":"https://assets-eu.researchsquare.com/files/rs-14796/v3/fig2.PNG"},{"id":1933025,"identity":"ec530c79-9156-4ae5-9f5f-d6c65d5e7bcf","added_by":"auto","created_at":"2020-08-14 17:57:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":182856,"visible":true,"origin":"","legend":"Analysis of associations between genetic and environmental risk factors and functional pathways. We used MaAsLin [34] to identify statistically significant associations between each genetic and environmental risk factor and functional pathways (p-value \u003c 0.01), Pathways were clustered based on Euclidean distance. Additional File 8 for grouping of these pathways based on KEGG categorizations.","description":"","filename":"fig3.PNG","url":"https://assets-eu.researchsquare.com/files/rs-14796/v3/fig3.PNG"},{"id":1933026,"identity":"5270859b-5849-4e6e-bc24-ddfa888f507a","added_by":"auto","created_at":"2020-08-14 17:57:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":298127,"visible":true,"origin":"","legend":"Analysis of associations between genetic and environmental risk factors and metabolites. We used MaAsLin [34] to identify statistically significant associations between each genetic and environmental risk factor and metabolites (p-value \u003c 0.01), Metabolites were clustered based on Euclidean distance. ","description":"","filename":"fig4.PNG","url":"https://assets-eu.researchsquare.com/files/rs-14796/v3/fig4.PNG"},{"id":1933027,"identity":"b2b26560-e8be-4eeb-95cd-bcb24bd8548c","added_by":"auto","created_at":"2020-08-14 17:57:14","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":237892,"visible":true,"origin":"","legend":"Cross-sectional analysis of microbiota features for genetically predisposed infants. (A) functional pathways (p-value \u003c 0.05), and (B) metabolites that are differentially abundant between environmentally exposed and non-exposed infants according to Mann-Whitney U test (p-value \u003c 0.05). Additional File 8 for grouping of pathways based on KEGG categorizations. See Additional File 9 for boxplots showing altered abundances for these pathways and metabolites. Brackets show time points at which a significant difference between the exposed and non-exposed groups was observed.","description":"","filename":"fig5.PNG","url":"https://assets-eu.researchsquare.com/files/rs-14796/v3/fig5.PNG"},{"id":1933028,"identity":"3f7887b3-c44e-4560-b95c-91d2cf06581a","added_by":"auto","created_at":"2020-08-14 17:57:14","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":373982,"visible":true,"origin":"","legend":"Longitudinal analysis of microbiota features for genetically predisposed infants (A) microbial species, (B) functional pathways, and (c) metabolites that are differentially abundant between each pair of time points (enrollment, 3 months, and 4-6 months) according to a paired Wilcoxon (Wilcoxon Signed Rank) test (p-value \u003c 0.05). Here, ‘Time1’ denotes the earlier time point. In this figure “u_s” denotes and unspecified species. Additional File 8 for grouping of pathways based on KEGG categorizations. See Additional File 9 for boxplots showing altered abundances for these pathways and metabolites. 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CD occurs in genetically predisposed individuals that have specific variants of the human leukocyte antigen (HLA) DQ2 and DQ8 genes in response to ingesting gluten, a protein found in wheat, rye, and barley [2]. Notably, CD is the only autoimmune disorder for which the environmental trigger (ingestion of gluten) is known [3].\u0026nbsp; Given that the timing of exposure to gluten and the dose of gluten ingested can be carefully monitored, and since gluten removal results in the resolution of symptoms and enteropathy for most patients [4-8], CD can serve as a tunable model of chronic immune-based disorders [9]. \u0026nbsp;This allows for insights into its pathogenesis to be applied not only to individuals with CD but those with other autoimmune diseases as well. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGlobally, the incidence of autoimmune diseases including CD is expected to triple by 2050 [10, 11], yet the genes associated with CD (HLA DQ2) and DQ8, and the trigger (gluten) have not changed. Research shows that more than 30% of the population carry the predisposing gene(s) and are exposed to the trigger yet only 2-3% of these individuals develop CD in their lifetime thus suggesting a critical role for environmental factors [12]. Mode of delivery, infant feeding type, timing of gluten introduction into the diet, occurrence of viral infections and early exposure to antibiotics are just a few of the many environmental factors suggested to influence the development of chronic inflammatory diseases such as CD [13]. When evaluating these factors independently, case-control studies and meta-analyses have found that cesarean section delivery [14, 15], lack of breast-feeding [16, 17], timing of gluten introduction [17, 18] and exposure to antibiotics [19] increase the risk of developing CD. However, two independent double blind placebo controlled prospective studies in Europe involving infants with compatible HLA genetics and a first-degree relative with CD \u0026nbsp;(who are therefore at high risk of developing CD) found that vaginal delivery, breast-feeding, and timing of gluten introduction were not protective against developing CD [20, 21].\u003c/p\u003e\n\u003cp\u003eAccumulating evidence suggests that the gut microbiota may be involved in several immune based disorders [13] such as inflammatory bowel disease (IBD) [22], type 1 diabetes (T1D) [23] and multiple sclerosis [24]. A limited number of studies have also started to explore the link between the gut microbiota and CD development [25-30]. Initial studies focused on the contribution of HLA genetics to the developing microbiota. In particular, two studies analyzed exclusively breastmilk-fed infants up to 4 months of age with a first-degree relative with CD and found that \u003cem\u003eBacteroides-Prevotella\u003c/em\u003e group [25], \u003cem\u003eFirmicutes\u003c/em\u003e, \u003cem\u003eProteobacteria\u003c/em\u003e, and \u003cem\u003eBifidobacterium\u003c/em\u003e [26] were more abundant in infants at high genetic risk for CD (those with two copies of HLA DQ2). Additionally, in a preliminary prospective study, we used 16S rRNA amplicon sequencing to examine the microbiota from 16 infants with a first-degree relative with CD and with a compatible HLA type and found a lower abundance of \u003cem\u003eBacteroides \u003c/em\u003eand a higher abundance of \u003cem\u003eFirmicutes \u003c/em\u003ein these subjects compared to controls [27]. Other studies of the gut microbiota and CD have assessed changes, within one year of age, in the microbiota composition of individuals who later developed CD compared to controls [29, 30]. For example, Olivares et al [29] identified increases in the abundances of \u003cem\u003eFirmicutes, Enterococcaceae\u003c/em\u003e, and \u003cem\u003ePeptostreptococcaceae\u003c/em\u003e in controls from 4 to 6 months but no differences over time were observed in cases [29]. While the link between environmental factors and alterations in the gut microbiota of at-risk subjects has been recently explored for a number of chronic immune based disorders [31, 32], studies addressing this question for CD are scarce [28]. The only study in this direction is the work of Pozo-Rubio et al [28], where they found associations between a limited number of pre-selected fecal microbial taxa in subjects at risk of CD and delivery mode, infant feeding type, antibiotic exposure and rotavirus vaccine administration [28].\u003c/p\u003e\n\u003cp\u003eWhile these studies have provided valuable insights into the development of the gut microbiota early in life in subjects at risk of CD, solid food has already been introduced into the infants\u0026rsquo; diet in many of these studies without accounting for its impact on the microbiota. In addition, to the best of our knowledge, no microbiome-wide study of the effect of environmental risk factors for CD currently exists. More importantly, existing studies are primarily based on 16S rRNA amplicon sequencing, which is not capable of fully addressing how the functional characterization of the microbiota will affect CD onset. To mitigate these limitations, here, we utilize a large-scale prospective cohort study called the Celiac Disease Genomic, Environmental, Microbiome and Metabolome study (CDGEMM) [33], where we have been following over 400 infants with a first-degree relative with CD who are thus at a high risk of developing CD. In this study, we present multivariate association as well as inter-subject and intra-subject analyses using metagenomic and metabolomic data collected over the first six months after birth to investigate the impact of both genetic and environmental risk factors on the development of the gut microbiota of infants at risk of CD prior to the introduction of solid foods.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eWe selected 31 children recruited into the CDGEMM cohort for whom stool samples were available at birth, 3 months, and 4-6 months for this study (see Figure 1, Table 1 and see Additional File 1 for more detailed metadata). None of these infants consumed solid foods before 6 months, which makes them ideal for studying the effect of genetic and environmental risk factors on the gut microbiota in the absence of gluten as a confounder. Twenty-six of these infants were genetically susceptible to developing CD out of which 19 were either heterozygous for DQ2 or DQ8 or carried both DQ2 and DQ8 (referred to as \u0026ldquo;standard genetic risk\u0026rdquo; hereafter) and seven were homozygous for DQ2 (referred to as \u0026ldquo;high genetic risk\u0026rdquo; hereafter). Additionally, 19 infants who were genetically predisposed to CD and that have been exposed to at least one environmental risk factor are referred to as \u0026ldquo;environmentally exposed\u0026rdquo; infants throughout the rest of manuscript. The environmental factors that we considered in this study include delivery model, antibiotic exposure and infant feeding type. Therefore, environmentally exposed infants are the ones who were born via cesarean section or were exposed to antibiotics at or during birth (i.e., antibiotics administered to the mother during delivery) or were not exclusively breastmilk-fed (i.e., formula-fed or both formula- and breastmilk-fed). The choice of these environmental risk factors and their grouping is clinically relevant since cesarean section delivery is often associated with antibiotic administration at birth and formula feeding due to delayed breastmilk production. Seven infants who were genetically susceptible and that were not exposed to any of these environmental risk factors, i.e., those born vaginally and not exposed to antibiotics at or during delivery and exclusively breastmilk-fed, are referred to as \u0026ldquo;environmentally non-exposed\u0026rdquo; hereafter (see Figure 1).\u003c/p\u003e\n\u003cp\u003eCollected stool samples underwent shotgun metagenomic sequencing and metabolomic profiling. We analyzed metagenomic sequencing reads (see Methods) to profile microbial taxa at species-level resolution (see Additional File 2 see also Additional File 3 for the taxonomic composition of each sample at the genus and family levels) and functional pathways encoded by metagenomes (see Additional File 4). While we identified non-bacterial species (fungi, viruses, protists) in our taxonomic profiling, in this paper, we focus only on the bacterial species.\u003c/p\u003e\n\u003cp\u003eAdditionally, stool samples underwent metabolomic profiling and were analyzed to identify metabolites present in each stool sample (see Additional File 5). The identified microbial taxa, functional pathways and metabolites were then analyzed to explore how genetic and environmental risk factors influence the development of the gut microbiota as outlined below.\u003c/p\u003e\n\u003ch3\u003eAssociations between genetic and environmental risk factors and microbiota features\u003c/h3\u003e\n\u003cp\u003eWe used the MaAslin procedure [34] to investigate how various microbiome features including microbial species, functional pathways and metabolites at each time point are associated with genetic risk for developing CD and three key environmental risk factors including mode of delivery, exposure to antibiotics and infant feeding type (see Figures 2-4).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGenetic risk: \u003c/strong\u003eWe found that both high and standard genetic risk to develop CD are associated with a decreased abundance of several species of \u003cem\u003eStreptococcus\u003c/em\u003e and \u003cem\u003eCoprococcus\u003c/em\u003e at 4-6 months of age compared to those lacking genetic compatibility (Figure 2; p-value \u0026lt; 0.05). Notably, a decreased abundance of \u003cem\u003eCoprococcus\u003c/em\u003e has been previously reported in the gut of individuals who carry a genetic risk to develop autoimmune conditions including CD [35]. Standard and high genetic risk for developing CD are also associated with an increased abundance of \u003cem\u003eBacteroides\u003c/em\u003e and \u003cem\u003eEnterococcus\u003c/em\u003e species, respectively, at enrollment compared to no genetic risk. These observations are in agreement with previous studies [25, 26], however, an association between genetic risk and increased abundance of \u003cem\u003eBifidobacterium\u003c/em\u003e or \u003cem\u003eProteobacteria\u003c/em\u003e, which were reported before [25, 26] were not observed here. Among other significant associations, we found a decreased abundance of \u003cem\u003eVeillonella, Parabacteroides\u003c/em\u003e and \u003cem\u003eClostridium perfringens\u003c/em\u003e at 4-6 months after birth in infants with high and standard genetic compatibility. \u0026nbsp;This observation is contrary to case-control studies that report an increased abundance of these microbes in autoimmune conditions such as autoimmune liver disease [36], Bechet\u0026rsquo;s disease [37] and neuromyelitis optica [38].\u003c/p\u003e\n\u003cp\u003eIn addition to association with microbial species, we found that a high genetic risk of developing CD is associated with a decreased abundance of a number of functional pathways at 4-6 months of age (Figure 3; p-value \u0026lt; 0.05). These pathways include amino acid metabolism, biosynthesis of secondary metabolites and metabolism of cofactors including ubiquinone and other terpenoid-quinone biosynthesis. Furthermore, we identified an association between high genetic risk and a number of metabolites, e.g., an increased abundance of butanoic acid and a decreased abundance of dihydroxyacteone at 3 and 4-6 months of age (Figure 4, p-value \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMode of delivery:\u003c/strong\u003e We found that cesarean section delivery is associated with a decreased abundance of several species of \u003cem\u003eBacteroides \u003c/em\u003eand \u003cem\u003eParabacteroides \u003c/em\u003eat all time points and with an increased abundance of \u003cem\u003eEnterococcus faecalis\u003c/em\u003e (at 3 months after birth) compared to vaginal delivery (Figure 2; p-value \u0026lt; 0.05) in agreement with previous work [23, 39-41]. For example, we found associations between cesarean section delivery and a decreased abundance of beneficial species \u003cem\u003eBacteroides vulgatus\u003c/em\u003e and \u003cem\u003eBacteroides dorei. \u003c/em\u003eAn increased abundance of these species has been reported to lead to a decreased gut microbial production of lipopolysaccharide, which will improve immune function through mechanisms such as major histocompatibility production and T cell activation, among others [42]. Analysis of pathways shows also an association between cesarean section delivery and decreased riboflavin metabolism and folate biosynthesis at 4-6 months after birth and an increase in the abundance of glycerolipid metabolism at 3 and 4-6 months (Figure 3; p-value \u0026lt; 0.05). Of note, defects in folate biosynthesis have been linked to an impaired immune response to viral infections and reduced natural killer cell response possibly contributing to T1D onset [43]. Finally, metabolites analysis unveiled an association between cesarean section delivery and an increase in the abundance of a number of metabolites such as butanoic acid (at 3 and 4-6 months), glycolic acid, oxalic acid, and hydroxyphenlacetic acid (at 4-6 months) and a decrease in that of valine, serine, and arabinoic acid among others (at 4-6 months) (Figure 4, p-value \u0026lt; 0.05). An increased abundance of hydroxyphenlacetic acid in the serum has been associated with ulcerative colitis in a previous study [44], however, no clear links between the level of metabolites in the gut and those in the serum have been established yet. Additionally, serine, which is decreased in cesarean section delivery, has been reported to be required for effector T cell expansion and thus for modulating the adaptive immune response [45].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInfant feeding type:\u003c/strong\u003e We examined three infant feeding types in this study including exclusive breastmilk feeding, exclusive formula feeding and both breastmilk and formula feeding, the last two of which were considered as environmental risk factors. Previous work shows an association between infant feeding type and distinct species of \u003cem\u003eBifidobacterium \u003c/em\u003e[23, 46]. Consistent with these reports, we observed that exposure to both breastmilk and formula is associated with a decreased abundance \u003cem\u003eof Bifidobacterium breve (\u003c/em\u003eat 4-6 months) while exclusive formula feeding is associated with an increased abundance of \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e compared to exclusive breastmilk feeding (Figure 2; p-value \u0026lt; 0.05). We also found that exclusive formula feeding is associated with a decreased abundance of \u003cem\u003eStaphylococcus epidermis\u003c/em\u003e (at enrollment) consistent with previous work [47], and with an increased abundance of \u003cem\u003eRuminococcus gnavus\u003c/em\u003e and \u003cem\u003eLachnospiraceae bacterium\u003c/em\u003e (at 3 and 4-6 months), which have been linked to allergic disease [48], diabetes [49] and colonic inflammation [50]. Pathway analysis shows that exposure to formula only or both breastmilk and formula is associated with an increased abundance of pathways for lipids, amino acids and terpendoids metabolism and xenobiotic degradation, and with a decreased abundance of pathways for carbohydrate and energy metabolism (Figure 3; p-value \u0026lt; 0.05). Additionally, metabolomic analysis uncovered an association between both breastmilk and formula feeding with a decreased abundance of homoserine, alpha-D-glucopyranoside, and hydrocinnamic acid (at 4-6 months) (Figure 4; p-value \u0026lt; 0.05). Exclusive formula feeding is also associated with an increase in sucrose and threonine and a decrease in oxalic acid and dihydroxyacetone abundances, among others (at 4-6 months).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAntibiotic use\u003c/strong\u003e: We found an association between antibiotic exposure (as an environmental risk factor) and an increased abundance of \u003cem\u003eBacteroides thetaiotaomicron\u003c/em\u003e (at 4-6 months of age) (Figure 2; p-value \u0026lt; 0.05). This is corroborated with previous work suggesting that this species, which is an important metabolizer of polysaccharides, increases in abundance in response to amoxicillin exposure [51]. Other identified associations for antibiotic exposure not previously reported include an increased \u003cem\u003ePropionibacterium\u003c/em\u003e, \u003cem\u003eSubdoligranulum\u003c/em\u003e species and a decreased abundance of \u003cem\u003eBifidobacterium merycicum\u003c/em\u003e and \u003cem\u003eStrepotococcus lutetiensis \u003c/em\u003e(at 4-6 months). Pathway analysis also revealed an association between antibiotic exposure and a decreased abundance of phenylalanine metabolism and an increased abundance of cyanoamino acid (3 and 4-6 months) and galactose metabolism (4-6 months) (Figure 3; p-value \u0026lt; 0.05). Analysis of metabolites showed associations between antibiotic exposure and a number of metabolites including decreased sucrose abundance (at 4-6 months) (Figure 4; p-value \u0026lt; 0.05).\u003c/p\u003e\n\u003ch3\u003eChanges in the microbiota of environmentally exposed vs. non-exposed infants\u003c/h3\u003e\n\u003cp\u003eHere, we performed a cross-sectional (inter-subject) analysis to explore how various features of the gut microbiota (microbes, pathways and metabolites) change between genetically predisposed infants who were exposed to at least one environmental risk factor noted before (environmentally exposed infants) vs. those who were not (environmentally non-exposed infants) (Figure 5). This analysis did not identify any microbial species whose abundance is significantly different between the environmentally exposed and non-exposed infants. Pathways analysis, however, revealed that environmentally exposed infants have a higher abundance of pathways for xenobiotic degradation, fatty acid metabolism, and lipid metabolism among others (at enrollment) and of pathways such as toluene and xylene and biphenyl degradation (at 4-6 months) (Figure 5A; p-value \u0026lt; 0.05). Metabolomic analysis identified alterations such as a decreased abundance of homoserine (at enrollment and 3 months) and of 2-ketobutryic acid (at enrollment) as well as an increased abundance of ribose (peak 2) (at 3 and 4-6 months) in environmentally exposed infants compared to non-exposed infants (Figure 5B; p-value \u0026lt; 0.05). \u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eLongitudinal changes in the microbiota of environmentally exposed and non-exposed infants\u003c/h3\u003e\n\u003cp\u003eGiven the unique prospective study design of our cohort, we were able to perform a longitudinal (intra-subject) analysis to gain additional insights beyond a cross-sectional analysis by identifying dynamic alterations in the gut microbiota composition, function and metabolome in the first six months after birth. To this end, we explored changes in the microbiota features noted above between all pairs of time points that are observed exclusively in environmentally exposed or exclusively in environmentally non-exposed infants (Figure 6).\u003c/p\u003e\n\u003cp\u003eBy longitudinal analysis of microbial species, we found that the abundance of a number of species increases over time in the environmentally exposed infants (Figure 6A; p-value \u0026lt; 0.05). For example, the abundance of \u003cem\u003eAnaerostipes caccae\u003c/em\u003e monotonically increases during the study period and that of \u003cem\u003eKlebsiella\u003c/em\u003e species and \u003cem\u003eErysipelotrichaceae bacterium \u003c/em\u003eincreases from enrollment to 4-6 months. Among these, \u003cem\u003eKlebsiella, \u003c/em\u003ehas been associated with the autoimmune condition ankylosing spondylitis [52]. When examining environmentally non-exposed infants, we observe that the abundance of \u003cem\u003eBacteroides uniformis\u003c/em\u003e monotonically increases during the first 6 months after birth, a pattern which has previously been reported in breastmilk-fed infants [53]. In addition, work in mice found that \u003cem\u003eBacteroides uniformis\u003c/em\u003e improves immune defense mechanisms, which are impaired in obesity, by decreasing TNF-a production and increasing IL-10 production [54]. In our study, we also observed a decrease in the abundance of \u003cem\u003eVeillonella \u003c/em\u003especies from enrollment to 4-6 months in non-exposed infants. An increased abundance of \u003cem\u003eVeillonella \u003c/em\u003especies has been associated with autoimmune hepatitis [36].\u003c/p\u003e\n\u003cp\u003eLongitudinal pathway analysis revealed that the abundance of ether lipid metabolism increases from 3 to 4-6 months of age in environmentally exposed infants (Figure 6B; p-value \u0026lt; 0.05). Notably, a decreased abundance of ether lipids in the serum of children with T1D compared to healthy controls has been observed, [55] although the relationship between the abundance of microbial pathways for ether lipid metabolism in the gut and the level of ether lipids in the serum are yet to be explored. For the non-exposed infants, we observe a decrease in the abundance of sulfur metabolism and lipoic acid metabolism at 3 and 4-6 months, and of methane metabolism and biotin metabolism at 4-6 months compared to enrollment. These patterns are consistent with previous reports [34, 56-62]. For example, increased sulfur metabolism is associated with the development of T1D [56] and is linked to IBD [34]. Additionally, lipoic acid is an antioxidant that has been suggested to have beneficial immunomodulatory effects on the innate and adaptive immune systems in autoimmune diseases [57]. Methane has also been shown to have an anti-inflammatory effect, promoting immune tolerance in the intestine when tested in animal models [58, 59]. Furthermore, biotin is known to enhance innate [60] and adaptive immune responses [61] and biotin deficiency has been associated with immune disorders and inflammation [63, 64]. A previous study also found that high dose of biotin may be useful in treating multiple sclerosis [62].\u003c/p\u003e\n\u003cp\u003eMetabolomic analysis revealed a monotonic increase in erythritol abundances during the study period and a decrease in propionic acid abundance from enrollment to 4-6 months in environmentally exposed infants (Figure 6C; p-value \u0026lt; 0.05). Propionic acid produced in the colon via bacterial fermentation of fiber promotes regulatory T cell generation [65]. Additionally, increased serum levels of erythritol have been associated with central obesity and weight gain [66], though the link between metabolite levels in the gut and those in the serum is not clear. In environmentally non-exposed infants, we observed an increased abundance of uracil, 3-3-hydroxyphenylpropionic acid and dihydroxyacetone from enrollment to 4-6 months. Previous work suggests that 3-hydroxyphenylproprionic acid acts as an anti-inflammatory and antioxidant agent [67].\u003c/p\u003e\n\u003ch2\u003eLinking Microbial Species, Pathways and Metabolites\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eIn order to link microbial species, pathways and metabolites identified in these analyses, we performed a correlation analysis (using Spearman rank correlation) as detailed in Additional File 6, which resulted in several significant correlations between these features as summarized in Additional File 7. For example, exploring the links between pathways and metabolites with altered abundance in the cross-sectional analysis identified positive associations between ribose (peak 2) and biphenyl degradation and between toluene and xylene degradation in the environmentally exposed infants. In addition, association analysis between significant pathways and metabolites in the longitudinal analysis identified a negative association at 3 and 4-6 months between 3-3-hydroxyphenylpropionic acid and sulfur, lipoic acid, methane and biotin metabolism in non-exposed infants (Additional File 7).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eSeveral studies have linked exposure to a variety of genetic and environmental risk factors with the onset of non-infective chronic inflammatory diseases [13]. \u0026nbsp;This link has been typically based on the results obtained from either clinical case-control studies [14, 15, 19, 68] or metanalyses [69-72] in which cause-effect relationship cannot always conclusively be determined. Since host genetics and environmental factors are known to influence the gut microbiota composition and function, researchers have started to explore alterations in the gut microbiota of infants at risk of autoimmune conditions such as IBD [31] or T1D [32]. However, to date, there is no systematic study of how protective or detrimental genetic and environmental factors may change the gut microbiota engraftment and its maturation during the first months of life in infants at-risk of CD. In an effort to fill this gap, in this study we used metagenomic and metabolomic data collected in the first 6 months after birth to associate individual risk factors (HLA DQ2/DQ8 genetics, cesarean section delivery, antibiotic use and partial or exclusive formula feeding) with microbial species, pathways and metabolites in the gut. Additionally, we performed cross-sectional analysis to identify microbes, pathways and metabolites that are differentially abundant between infants exposed to at least one environmental risk factor and infants who were not, as well as longitudinal analysis to identify dynamic changes in the gut microbiota in the first six months of life. Notably, we restricted our analysis only to the first six months after birth prior to the introduction of solid foods in order to focus exclusively on the effect of the genetic predisposition and early environmental exposures on the development of the gut microbiota in at-risk infants without any noise from differences in infants diets including gluten.\u003c/p\u003e\n\u003cp\u003eMany microbes, pathways, or metabolites that we identified in these analyses are well supported in the literature to be associated with inflammation, autoimmune disease, or immune system dysfunction, thereby suggesting that they may have similar effects in CD. For example, we found that high risk HLA genetics and formula feeding are both associated with an increased abundance of \u003cem\u003eRuminococcus gnavus \u003c/em\u003eand \u003cem\u003eLachnospiraceae bacterium\u003c/em\u003e, which are linked to allergic diseases [48] and diabetes [49], respectively. Among other significant findings are associations between cesarean section delivery and a decreased abundance of \u003cem\u003eBacteroides vulgatus\u003c/em\u003e and \u003cem\u003eBacteroides dorei\u003c/em\u003e and folate biosynthesis pathway along with an increased abundance of hydroxyphenlacetic acid. All of these patterns have been reported to be associated with impaired immune function [42] and inflammatory conditions such as T1D and ulcerative colitis [43, 44] suggesting that they could also predispose infants to develop CD.\u003c/p\u003e\n\u003cp\u003eWhile the cross-sectional analysis did not identify any microbial species whose abundance significantly changes between the environmentally exposed and non-exposed infants at any given time point, our longitudinal analysis yielded significant results further stressing the power of intra-subject analysis. This allows us to prospectively evaluate the impact of risk factors on the dynamics of the gut microbiota development and to link dynamics to increased susceptibility to inflammation. For example,\u0026nbsp; environmentally exposed infants show an increasing abundance over time of \u003cem\u003eKlebsiella \u003c/em\u003especies, a microbe linked to autoimmune disease [52] and a decreasing abundance over time of propionic acid, a metabolite that promotes innate and adaptive immunity[65]. In contrast, in infants not exposed to environmental risk factors, we observe patterns associated with beneficial immunomodulatory effects and protection against immune system activation and inflammation such as increasing abundance of \u003cem\u003eBacteroides uniformis\u003c/em\u003e over time and decreasing abundance of lipoic acid and methane metabolism [54, 57-59, 67]. Notably, during our analyses, we identified a number of metabolites and pathways with altered abundances in the gut (including hydroxyphenlacetic acid, erythritol and ether lipid metabolism) for which similar variations in the serum are reported to be associated with autoimmune conditions. While the importance of gut-blood axis has been realized fairly recently [73, 74], further investigations are needed to better understand the relationship between different features of the gut microbiota and host- or microbially-derived metabolites in the blood.\u003c/p\u003e\n\u003cp\u003eUnlike previous microbiome studies for CD that are often based on 16S rRNA amplicon sequencing, here, we use shotgun metagenomic sequencing, which is amenable to functional characterization of the microbiota. This is particularly important as previous studies have shown that functional characterization is a more robust descriptor of the status of the microbiota compared to taxonomic composition alone [75, 76]. Furthermore, unlike typical case-control studies, where disease symptoms have already emerged in cases, our prospective birth cohort provides the opportunity to mechanistically link major shifts in the gut microbiota early in life, due to genetic risk factors and environmental exposures, in infants at-risk of CD. \u0026nbsp;Nevertheless, our data should be considered exploratory given the relatively small sample size.\u0026nbsp; This limitation can be mitigated through ongoing recruitment into our CDGEMM cohort, which will allow us to validate our findings using a much larger number of subjects in the future.\u0026nbsp;\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this paper, we utilized an ongoing prospective study and multi-omics analysis to perform an in-depth analysis of the impact of genetic and environmental risk factors on the longitudinal development of the gut microbiota in infants at risk for CD, before solid foods (including the trigger of CD, gluten) is introduced. These analyses revealed several microbial species, functional pathways and metabolites that have been previously linked to inflammation or immune system dysfunction as well as several new ones that have not been reported before and could be specific to CD. In this study, we restricted our analysis to the first 6 months of life and particularly prior to the introduction of solid foods in order to proactively \u0026ldquo;regress out\u0026rdquo; the effect of gluten on the gut microbiota as a major confounder when analyzing the effect of genetic and environmental risk factors. However, while our analysis suggests that the microbiome shifts that we observed during the first six months after birth increase the risk of developing autoimmune conditions including CD based on existing literature, it is unclear whether they indeed contribute to the future development of CD. Therefore, further work is required to investigate alterations in the gut microbiota over a longer period of time, including through the onset of CD. Future work should also consider other environmental factors such as viral infections, timing of solid food (gluten) introduction, amount of gluten ingested and household exposures, e.g. family size and contact with pets, which have been reported to be associated with altered microbiomes [77], or with protection against autoimmune conditions such as asthma [78] and T1D [79]. These investigations warrant future studies, which can utilize this longitudinal study design and multi-omics analysis as a basis to connect alterations in the gut microbiota early in life to the loss of tolerance to gluten and the development of CD. \u0026nbsp;\u003c/p\u003e"},{"header":"Methods","content":"\u003ch3\u003eSubjects, sampling, and factors of interest\u003c/h3\u003e\n\u003cp\u003eThirty one healthy infants from the United States (18) and Italy (13) with a first-degree relative with CD participating in the CDGEMM prospective birth cohort study [33] were included in our analysis. These subjects consist of all infants from CDGEMM with available stool samples collected before the introduction of solid foods at 7-15 days (enrollment), 3 months and 4-6 months after birth. Parents answered a detailed questionnaire at enrollment that addressed pregnancy, delivery, family history, household factors, and many other factors related to the infants\u0026rsquo; environment before birth and at delivery. Parents also filled out monthly diaries, which addressed infant food intake and any exposure to antibiotics. Infant feeding type was determined according to the reported exclusive feeding type for at least two of the three sample time point collections. Infants who received both breastmilk and formula for at least two of three sample collection points were classified as \u0026ldquo;both breastmilk and formula fed.\u0026rdquo;\u0026nbsp; HLA genetic type was determined from whole blood at time of birth (cord blood) or 12 months of age using the DQ-CD Typing Plus (BioDiagne, Palermo, Italy) per the manufacturer\u0026rsquo;s instructions. Written informed consent was obtained from the parents of infants included in the study according to the standards outlined and approved by the Partners Human Research Committee Institutional Review Board.\u003c/p\u003e\n\u003ch3\u003eDNA extraction\u003c/h3\u003e\n\u003cp\u003eAll fecal samples included in the metagenomic analysis were stored and processed centrally in the United States. Total DNA from each sample was extracted using the Qiagen Power soil DNA extraction kit (Qiagen, Hilden, Germany).\u003c/p\u003e\n\u003ch3\u003eTaxonomic profiling\u003c/h3\u003e\n\u003cp\u003eGeneral sequencing statistics of all samples, as well as mean sequence quality distribution for metagenomics samples were measured by MultiQC [80]. Since the mean quality value across each base position in the trimmed reads obtained with mulitQC was above quality score 17 for at least 80% of the read length (i.e., probability of correct base call ~98%), reads were not subjected to additional quality trimming steps before uploading to the CosmosID cloud platform. Metagenomic sequencing reads were then analyzed by using the CosmosID\u0026rsquo;s (CosmosID Inc., Rockville, MD) commercial metagenomic analysis platform (formerly knowns as GENIUS; https://app.cosmosid.com/login) [81, 82], which is based on an assembly-free kmer-based method, to reveal the underlying microbial community composition up to the species-level resolution (see Additional File 6 for a detailed description of this platform and Additional File 2 for information on the sequencing depth of each sample and the number of reads with a taxon assignment.\u003c/p\u003e\n\u003ch3\u003eFunctional profiling\u003c/h3\u003e\n\u003cp\u003eAfter trimming the raw sequencing reads using BBDuk (\u003ca href=\"https://jgi.doe.gov/data-and-tools/bbtools/\"\u003ehttps://jgi.doe.gov/data-and-tools/bbtools/\u003c/a\u003e) (with parameters), we used the SPAdes tool [83] (with parameter \u003cem\u003e--only-assembler -k \u003c/em\u003e77,99,12\u003cem\u003e7\u003c/em\u003e) for the assembly of metagenomes and subsequently and after removing short contigs (length threshold = 500 bp), we used Prodigal (v2.6 using -\u003cem\u003ed\u003c/em\u003e parameter) [84] to identify protein coding sequences in the assembled metagenomes. We then utilized InterProScan [85] (with parameters \u003cem\u003e-appl Hamap, ProDom -p\u003c/em\u003e and \u003cem\u003e-f tsv\u003c/em\u003e) to annotate the identified genes with biochemical functions based on the KEGG pathways [86]. The relative abundance of each gene was computed as , where, \u0026nbsp;is fragments per kilobase per million (FPKM) for each gene,\u0026nbsp; \u0026nbsp;is the length of the gene, \u0026nbsp; is the coverage of contig in which the gene is identified, \u0026nbsp;is the read length and\u0026nbsp;is the -mer size [87].\u0026nbsp; The relative abundance of each KEGG pathway was then quantified by summing the relative abundances of all the genes associated to that pathway.\u003c/p\u003e\n\u003ch3\u003eMetabolomic profiling\u003c/h3\u003e\n\u003cp\u003eAll stool samples for metabolomics were stored and processed in Italy. The metabolome extraction, purification and derivatization were carried by the MetaboPrep GC kit (Theoreo, Montecorvino Pugliano, Italy) according to manufacturer instructions. Instrumental analyses were performed with a GC-MS system (GC-2010 Plus gas chromatograph and QP2010 Plus mass spectrometer; Shimadzu Corp., Kyoto, Japan). Sample analysis was performed in triplicate. Additional information related to the extraction, purification, derivatization, GC-MS analysis, and data preprocessing can be found in Additional File 6. The molecular identity of metabolites was determined by analysis of the corresponding mass spectrum in the chromatogram, setting the linear index difference max tolerance to 10. These identified metabolites were further confirmed using external standards according to level 1 Metabolomics Standards Initiative (MSI) [88].\u003c/p\u003e\n\u003ch3\u003eIdentifying associations between genetic and environmental risk factors and microbiome features\u003c/h3\u003e\n\u003cp\u003eWe used the widely-used multivariate statistical framework, MaAsLin, [22] to determine associations between microbial species, functional pathways or metabolites and genetic and environmental risk factors including HLA genetics, delivery mode, infant feeding type and antibiotic exposure at each time point. No genetic risk, vaginal delivery, exclusive breastmilk-feeding and no antibiotic exposure were considered as the reference levels for HLA genetics, delivery mode, infant feeding type and antibiotic exposure, respectively. All metadata variables were forced simultaneously to control for confounders. Significant results were reported using a p-value threshold of 0.05.\u003c/p\u003e\n\u003ch3\u003eCross-sectional and longitudinal analysis\u003c/h3\u003e\n\u003cp\u003eFor the cross-sectional analysis, we performed the Mann-Whitney U (Wilcoxon Rank Sum) test to compare the abundance of microbial species, pathways and metabolites at each time point between the environmentally exposed and non-exposed groups (using a p-value threshold of 0.05 to report significant results). For the longitudinal analysis, we performed the paired Wilcoxon (Wilcoxon Signed Rank) test to compare the abundances of microbial species, pathways and metabolites between each pair of time points using the same p-value threshold noted above to report the significant results. Analyses of microbial species and pathways were performed in Python (using scipy.stats.mannwhitneyu and scipy.stats.wilcoxon functions) and those for metabolites were performed in R (using Ttest.Anal function of the MetaboAnalyst package [89] using parameters \u003cem\u003enonpar=TRUE\u003c/em\u003e and \u003cem\u003epaired=FALSE\u003c/em\u003e for the cross-sectional and \u003cem\u003epaired=TRUE\u003c/em\u003e for the longitudinal analysis).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e: Written informed consent was obtained from the parents of infants included in the study according the standards outlined and approved by the Partners Human Research Committee Institutional Review Board.\u003c/p\u003e\n\u003ch3\u003eClinical trial registration\u003c/h3\u003e\n\u003cp\u003eThis study is registered at clinicaltrials.gov with the identifier NCT02061306.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and material\u003c/h2\u003e\n\u003cp\u003eThe datasets supporting the conclusions of this article are submitted to the NCBI Short Read Archive (SRA) repository, under BioProjectID:\u0026nbsp; PRJNA486782 and SRA accession number SRP158417. Additional data from the analyses presented in this paper are available in the Supplementary Material.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eAF is a stockholder at Alba Therapeutics, serves as a consultant for Inova Diagnostics and Innovate Biopharmaceuticals, is an advisory board member for Axial Biotherapeutics and Ubiome, and has a speaker agreement with Mead Johnson Nutrition. MML serves as a consultant to HealthMode and Anokion, has a speaker agreement with Takeda Pharmaceuticals, and performs sponsored research with Glutenostics LLC. HK is a former employee, BF is a current employee, PS is a consultant and RRC and NAH are stockholders at CosmosID Inc. Other authors have declared no competing interests exist.\u003c/p\u003e\n\u003ch2\u003eAuthors' contributions\u003c/h2\u003e\n\u003cp\u003eMML designed the study, analyzed the data analysis results and drafted the manuscript. HK performed taxonomic and functional analysis. PS contributed to taxonomic profiling and analysis. MP, JT, and AC designed metabolomic studies and performed metabolomic data analysis. GS isolated the DNA. SC and VK recruited participants and coordinated the US study. FV recruited and supervised the Italian sites and secured sample collection. SC, MM, BM, RF, and LE recruited and coordinated the study, secured sample collection, and subject participation. NAH and RRC oversee CosmosID metagenomic sequencing and data analysis platforms. BF and NAH performed taxonomic profiling of metagenomic data analysis. ARZ designed all the computational studies, analyzed the data analysis results and drafted the manuscript. AF conceived the study, analyzed the data analysis results and aided in manuscript preparation. All authors read and approved the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements:\u003c/h2\u003e\n\u003cp\u003eThe authors would like to thank the families that participate in this study and whose contribution was instrumental to the findings described in this manuscript and the CDGEMM team including Pasqua Piemontese, Angela Calvi, Mariella Baldassarre, Lorenzo Norsa, Chiara Maria Trovato, Celeste Lidia Raguseo, Tiziana Passaro, Paola Roggero, Marco Crocco, Annalisa Morelli, Michela Perrone, Marcello Chieppa, Giovanni Scala,Maria Elena\u0026nbsp;Lionetti, Carlo Catassi,\u0026nbsp;Adelaide Serretiello, Corrado Vecchi, and Gemma Castillejo de Villsante.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis work was partially supported by funding from the NIH NIDDK; DK104344 to AF, DK109620 and K23DK122127\u0026nbsp;to MML, funding from Nutrition Obesity Research Center at Harvard (P30-DK040561) and the Thrasher Research Fund to MML, and the faculty start-up funding by Mucosal Immunology and Biology Research Center at Massachusetts General Hospital to ARZ, and through the generous support of \u0026nbsp;Joyce and Hugh McCormick.\u003c/p\u003e\n\u003ch2\u003eSupplementary information\u003c/h2\u003e\n\u003cp\u003eAdditional File 1. Clinical metadata for the subjects in this study.\u003c/p\u003e\n\u003cp\u003eAdditional File 2. Results of the taxonomic profiling of metagenomic samples.\u003c/p\u003e\n\u003cp\u003eAdditional File 3. Taxonomic composition at the genus and family level for metagenomes.\u003c/p\u003e\n\u003cp\u003eAdditional File 4. Results of the functional profiling of metagenomic samples.\u003c/p\u003e\n\u003cp\u003eAdditional File 5. Results of the metabolomic profiling of stool samples.\u003c/p\u003e\n\u003cp\u003eAdditional File 6. Supplementary text describing details of data analysis methods.\u003c/p\u003e\n\u003cp\u003eAdditional File 7. The results of association studies between significant features (microbes, pathways and metabolites).\u003c/p\u003e\n\u003cp\u003eAdditional File 8. Functional categorization of pathways with significantly altered abundances.\u003c/p\u003e\n\u003cp\u003eAdditional File 9. Boxplots for significant features in the cross-sectional and longitudinal analysis\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eCeliac disease (CD); Human leukocyte antigen (HLA); Inflammatory bowel disease (IBD), Type 1 diabetes (T1D).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eLionetti E, Gatti S, Pulvirenti A, Catassi C: \u003cstrong\u003eCeliac disease from a global perspective\u003c/strong\u003e. \u003cem\u003eBest Pract Res Clin Gastroenterol \u003c/em\u003e2015, \u003cstrong\u003e29\u003c/strong\u003e(3):365-379.\u003c/li\u003e\n\u003cli\u003eSchuppan D: \u003cstrong\u003eCurrent concepts of celiac disease pathogenesis\u003c/strong\u003e. \u003cem\u003eGastroenterology \u003c/em\u003e2000, \u003cstrong\u003e119\u003c/strong\u003e(1):234-242.\u003c/li\u003e\n\u003cli\u003eGreen PH, Cellier C: \u003cstrong\u003eCeliac disease\u003c/strong\u003e. \u003cem\u003eN Engl J Med \u003c/em\u003e2007, 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\u003c/em\u003e2004.\u003c/li\u003e\n\u003cli\u003eSumner LW, Amberg A, Barrett D, Beale MH, Beger R, Daykin CA, Fan TW-M, Fiehn O, Goodacre R, Griffin JL: \u003cstrong\u003eProposed minimum reporting standards for chemical analysis\u003c/strong\u003e. \u003cem\u003eMetabolomics \u003c/em\u003e2007, \u003cstrong\u003e3\u003c/strong\u003e(3):211-221.\u003c/li\u003e\n\u003cli\u003eChong J, Soufan O, Li C, Caraus I, Li S, Bourque G, Wishart DS, Xia J: \u003cstrong\u003eMetaboAnalyst 4.0: towards more transparent and integrative metabolomics analysis\u003c/strong\u003e. \u003cem\u003eNucleic Acids Res \u003c/em\u003e2018, \u003cstrong\u003e46\u003c/strong\u003e(W1):W486-W494.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Table","content":"\u003cp style='margin-top:0in;margin-right:0in;margin-bottom:8.0pt;margin-left:0in;line-height:200%;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cstrong\u003e\u003cspan style='font-size: 16px; line-height: 200%; font-family: \"Times New Roman\", serif; color: rgb(0, 0, 0);'\u003eTable 1. Study cohort metadata and genotype.\u003c/span\u003e\u003c/strong\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size:16px;line-height:200%;font-family:\"Times New Roman\",serif;'\u003e\u0026nbsp;This study cohort was extracted from the larger CDGEMM prospective longitudinal birth cohort study\u0026nbsp;[33].\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n\u003ctable style=\"border: none;width:447.55pt;border-collapse:collapse;\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 19.75pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:71.0pt;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:19.75pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cstrong\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003eUSA (n=18)\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:66.55pt;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:19.75pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cstrong\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003eItaly (n=13)\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width:70.0pt;border:none;border-bottom:solid windowtext 1.0pt;background:white;padding:0in 5.4pt 0in 5.4pt;height:19.75pt;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cstrong\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003eTotal (n=31)\u003c/span\u003e\u003c/strong\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"25\" style=\"width: 53pt;border-top: none;border-right: none;border-left: none;border-image: initial;border-bottom: 1pt solid windowtext;background: white;padding: 0in 5.4pt;height: 19.75pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cem\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003eGender (%)\u003c/span\u003e\u003c/em\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Male\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e11 (61.1)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e7 (53.8)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e18 (58.0)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Female\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e7 (38.9)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e6 (46.2)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e13 (42.0)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cem\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003eMode of Delivery (%)\u003c/span\u003e\u003c/em\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Vaginal\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e11 (61.1)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e7 (53.8)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e18 (58.0)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;C-section\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e7 (38.9)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e6 (46.2)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e13 (42.0)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cem\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003eFeeding Type (4-6 months of age) (%)\u003c/span\u003e\u003c/em\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Breastmilk only\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e12 (66.7)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e4 (30.7)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e16 (51.6)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Formula only\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e5 (27.8)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e6 (46.2)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e11 (35.5)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Both\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e1 (5.5)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e3 (23.1)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e4 (12.9)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cem\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003eAntibiotic Exposure (%)\u003c/span\u003e\u003c/em\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;At delivery (mother)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e7 (38.9)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e2 (15.4)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e9 (29.0)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;At birth (infant)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e2 (11.1)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e2 (15.4)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e4 (12.9)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Before 6 months of age (infant)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e0 (0.0)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e4 (30.8)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e4 (12.9)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cem\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003eGenotype (%)\u003c/span\u003e\u003c/em\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp;\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;DQ2 Homozygous\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e6 (33.3)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e1 (7.7)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e7 (22.6)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;DQ2 Heterozygous\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e6 (33.3)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e6 (46.2)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e12 (38.7)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;DQ2/DQ8\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e3 (16.7)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e2 (15.4)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 70pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e5 (16.1)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 187pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height: normal;font-size:15px;font-family:\"Calibri\",sans-serif;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;DQ8\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 71pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; font-family: \"Times New Roman\", serif;'\u003e1 (5.5)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 66.55pt;background: white;padding: 0in 5.4pt;height: 15pt;vertical-align: bottom;\"\u003e\n \u003cp style='margin-top:0in;margin-right:0in;margin-bottom:.0001pt;margin-left:0in;line-height:normal;font-size:15px;font-family:\"Calibri\",sans-serif;text-align:center;'\u003e\u003cspan style=\"color: rgb(0, 0, 0);\"\u003e\u003cspan style='font-size: 16px; 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font-family: \"Times New Roman\", serif; color: rgb(0, 0, 0);'\u003e\u0026nbsp;\u003c/span\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mbio","sideBox":"Learn more about [Microbiome](http://microbiomejournal.biomedcentral.com/)","snPcode":"40168","submissionUrl":"https://submission.nature.com/new-submission/40168/3","title":"Microbiome","twitterHandle":"@MicrobiomeJ","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":" Microbiota, Celiac disease, Multi-omics analysis, gut microbiome","lastPublishedDoi":"10.21203/rs.2.24237/v3","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.2.24237/v3","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Celiac disease (CD) is an autoimmune digestive disorder that occurs in genetically susceptible individuals in response to ingesting gluten, a protein found in wheat, rye, and barley. Research shows that genetic predisposition and exposure to gluten are necessary but not sufficient to trigger the development of CD. This suggests that exposure to other environmental stimuli early in life, e.g., cesarean section delivery, exposure to antibiotics or formula feeding, may also play a key role in CD pathogenesis through yet unknown mechanisms.\u0026nbsp;Here, we use multi-omics analysis to investigate how genetic and early environmental risk factors alter the development of the gut microbiota in infants at risk of CD.\u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Toward this end, we selected 31 infants from a large-scale prospective birth cohort study of infants with a first-degree relative with CD. We then performed rigorous multivariate association, cross-sectional and longitudinal analyses using metagenomic and metabolomic data collected at birth, three months and six months of age to explore the impact of genetic predisposition and environmental risk factors on the gut microbiota composition, function and metabolome prior to the introduction of trigger (gluten).\u0026nbsp;These analyses revealed several microbial species, functional pathways and metabolites that are associated with each genetic and environmental risk factor or that are differentially abundant between environmentally exposed and non-exposed infants or between time points. Among our significant findings, we found that cesarean section delivery is associated with a decreased abundance of \u003cem\u003eBacteroides vulgatus\u003c/em\u003e and \u003cem\u003eBacteroides dorei\u003c/em\u003e and of folate biosynthesis pathway, and with an increased abundance of hydroxyphenylacetic acid, alterations that are implicated in immune system dysfunction and inflammatory conditions. Additionally, longitudinal analysis revealed that, in infants not exposed to any environmental risk factor, the abundances of \u003cem\u003eBacteroides uniformis\u003c/em\u003e and of metabolite 3-3-hydroxyphenylproprionic acid increase over time while those for lipoic acid and methane metabolism pathways decrease, patterns that are linked to beneficial immunomodulatory and anti-inflammatory effects. \u0026nbsp;\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: Overall, our study provides unprecedented insights into major taxonomic and functional shifts in the developing gut microbiota of infants at risk of CD linking genetic and environmental risk factors to detrimental immunomodulatory and inflammatory effects.\u003c/p\u003e","manuscriptTitle":"Multi-omics analysis reveals the influence of genetic and environmental risk factors on developing gut microbiota in infants at risk of celiac disease","msid":"","msnumber":"","nonDraftVersions":[{"code":3,"date":"2020-08-14 17:41:44","doi":"10.21203/rs.2.24237/v3","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accept","date":"2020-08-09T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewersInvited","content":"","date":"2020-08-07T12:00:00+00:00","index":"","fulltext":""},{"type":"reviewerAgreed","content":"","date":"2020-08-07T12:00:00+00:00","index":1,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2020-08-07T12:00:00+00:00","index":1,"fulltext":"Recommendation: Reviewer's comments unavailable due to the journal's policy.\n"},{"type":"editorAssigned","content":"","date":"2020-08-05T12:00:00+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2020-08-04T12:00:00+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2020-08-04T12:00:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"microbiome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mbio","sideBox":"Learn more about [Microbiome](http://microbiomejournal.biomedcentral.com/)","snPcode":"40168","submissionUrl":"https://submission.nature.com/new-submission/40168/3","title":"Microbiome","twitterHandle":"@MicrobiomeJ","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}},{"code":2,"date":"2020-06-16 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