Fecal metabolome alterations in infants at risk of developing allergies during the first year of life

Fecal metabolome alterations in infants at risk of developing allergies during the first year of life | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 23 June 2025 V1 Latest version Share on Fecal metabolome alterations in infants at risk of developing allergies during the first year of life Authors : Mariyana Savova , Pingping Zhu 0009-0004-5949-5746 , Alida Kindt , Harm Wopereis , Clara Belzer 0000-0001-6922-836X , Amy Harms C 0000-0002-2931-4295 [email protected] , and Thomas Hankemeier Authors Info & Affiliations https://doi.org/10.22541/au.175068919.99322403/v1 268 views 141 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Background Disturbances in the gut microbiome (GM) during the first year of life may contribute to allergy risk. This period is characterized by rapid microbial colonization, influenced by factors like delivery mode and infant feeding practices. This study investigated changes in key GM taxa and fecal metabolites in relation to allergy development, delivery mode, age, and infant feeding practices during the first year of life. Methods In this study, 72 infants, exclusively breastfed for at least 16 weeks and at risk of developing allergies, were followed in their first year during which allergy manifestations were recorded and fecal samples were collected. The samples were subjected to metabolic profiling covering host and microbial metabolites and fluorescent in situ hybridization to quantify Bifidobacterium spp. and the Eubacterium rectale/Clostridium coccoides group. Results Strong age-associated metabolic shifts were observed, particularly in aromatic amino acid metabolites, bile acids, B vitamins, and short and long-chain fatty acids. Introduction of complementary feeding and the cessation of breastfeeding were significantly associated with changes to the fecal metabolome. Delivery mode had a pronounced impact on the metabolome, with differences persisting until 6 months of age. Infants who developed an allergy (n=20) had lower Bifidobacterium spp. and higher polyunsaturated fatty acid levels before the age of 16 weeks. Conclusion This study offers valuable insights into the longitudinal development of the fecal metabolome during infancy. It highlights potential early biomarkers for allergy risk, which could inform future dietary strategies to support gut health and reduce the risk of developing allergies. math_shortcuts Fecal metabolome alterations in infants at risk of developing allergies during the first year of life Authors: Mariyana V. Savova 1 , Pingping Zhu 1 , Alida Kindt 1 , the TEMPO study team, Harm Wopereis 2 , Clara Belzer 3 , Amy C. Harms 1* , Thomas Hankemeier 1 1 Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, the Netherlands 2 Danone Research & Innovation, Uppsalalaan 12, 3584 CT Utrecht, the Netherlands 3 Laboratory of Microbiology, Wageningen University, Stippeneng 4, 6708 WE Wageningen, the Netherlands * Corresponding author: Dr. Amy C. Harms, Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden University, Leiden 2333 CC, Netherlands E-mail: [email protected] A running title: Fecal metabolome in allergy-risk infants List of abbreviations: HMOs: human milk oligosaccharides; FISH: Fluorescence in situ hybridization; ER/CC: Eubacterium rectale/Clostridium coccoides ; GC-FID: gas chromatography coupled - flame ionization detector; LC-MS: liquid chromatography – mass spectrometry; LMM linear mixed model; AAs: amino acids; PUFA: polyunsaturated fatty acids; Word count: 3487 Number of figures: 4 Number of tables: 1 Conflict of interest statement Harm Wopereis is an employee of Danone Research & Innovation. The project is part of a partnership programme between NWO-TTW and Danone Research & Innovation. The other authors declare that they have no known conflicts of interest. math_shortcuts Financial support This study was part of the EARLYFIT project (Partnership programme NWO Domain AES-Danone Research & Innovation), funded by the Dutch Research Council (NWO) and Danone Research & Innovation (project number: 16490). Pingping Zhu Would like to acknowledge the China Scholarship Council (CSC, No. 201906240049). A.C.H and T.H. are supported by the Dutch Research Council (NWO) funded Netherlands X-omics Initiative (project number 184.034.019). Background math_shortcuts Disturbances in the gut microbiome (GM) during the first year of life may contribute to allergy risk. This period is characterized by rapid microbial colonization, influenced by factors like delivery mode and infant feeding practices. This study investigated changes in key GM taxa and fecal metabolites in relation to allergy development, delivery mode, age, and infant feeding practices during the first year of life. math_shortcuts Methods In this study, 72 infants, exclusively breastfed for at least 16 weeks and at risk of developing allergies, were followed in their first year during which allergy manifestations were recorded and fecal samples were collected. The samples were subjected to metabolic profiling covering host and microbial metabolites and fluorescent in situ hybridization to quantify Bifidobacterium spp. and the Eubacterium rectale/Clostridium coccoides group. Results Strong age-associated metabolic shifts were observed, particularly in aromatic amino acid metabolites, bile acids, B vitamins, and short and long-chain fatty acids. Introduction of complementary feeding and the cessation of breastfeeding were significantly associated with changes to the fecal metabolome. Delivery mode had a pronounced impact on the metabolome, with differences persisting until 6 months of age. Infants who developed an allergy (n=20) had lower Bifidobacterium spp. and higher polyunsaturated fatty acid levels before the age of 16 weeks. Conclusion This study offers valuable insights into the longitudinal development of the fecal metabolome during infancy. It highlights potential early biomarkers for allergy risk, which could inform future dietary strategies to support gut health and reduce the risk of developing allergies. Clinicaltrials.gov identifier: NCT03067714 Keywords: early life, birth mode, stool metabolomics, solid food introduction, infant, children, allergy Introduction Our guts are home to trillions of bacteria that live in a symbiotic relationship with us as hosts. 1 The first year of life is crucial for the development and maturation of the gut microbiome (GM). 2 This period coincides with the development of the immune system 3 and is a key window in which GM colonization shapes the host’s immune system. 4 An accumulating body of research links the disturbances of the GM composition in early life to a multitude of immune-mediated diseases, 5 including allergies. 6,7 Allergic disease often follows a temporal progression from atopic dermatitis and food allergy in infancy to allergic asthma and rhinitis in childhood, also known as “atopic march”. 8 The study of early life GM composition and function in relation to allergy development is therefore a topic of considerable interest. Many factors are known to influence the GM composition in infancy, including use of antibiotics, mode of delivery (vaginal versus C-section), milk feeding practices (breastfeeding versus formula feeding), and the transition to solid foods (complementary feeding). 9 The use of antibiotics and C-section have been associated with dysbiosis in early life and risk of developing of atopic dermatitis and other diseases later in life. 10,11 Even though the effect of breastfeeding on allergy is still debatable, breastfeeding is the recommended infant nutrition for allergy prevention. 12 Breastmilk is considered the optimal nutrition for infants due to its balanced composition of macronutrients and bioactive compounds satisfying the infant’s nutritional and physiological requirements. 13 It is also an important source of bifidobacteria and lactobacilli as well as human milk oligosaccharides (HMOs). 14 Bifidobacteria, e.g. B. breve , B. bifidum , B. longum, capable of utilizing HMOs and derivatives for energy, 15 thrive in the guts of healthy breastfed infants and are crucial for immune system development. 15 While the impact of the above-mentioned factors on the GM composition is relatively well-studied, their influence on GM activity remains understudied. Similarly, research examining the link between allergies and the GM have mainly focused on compositional analysis. 7 Since the GM influences the host’s physiology via the production of metabolites, researchers are increasingly examining the metabolome to get insights into host-microbiota interactions. 16 In this study, healthy breastfed infants at increased risk of developing allergies were followed during their first year. Data on delivery mode, allergy development, feeding practices were collected, and key gut microbial taxa along with the fecal metabolome were analyzed at three visits. This allowed us to assess microbiome and metabolomic changes associated with allergy, delivery mode, age, milk feeding practices (breastfeeding and formula feeding), and complementary feeding. Experimental section Study design, sample collection and storage The samples for this work arise from a randomized, double-blind, controlled, parallel-group, multi-country study called TEMPO (clinicaltrials.gov identifier: NCT03067714). Detailed information on ethics committees, institutional review boards, and regulatory authorities that approved the study was previously published. 17 TEMPO enrolled healthy term infants (age: family history. Subjects who began formula feeding before 16 weeks entered one of two intervention arms, while those exclusively breastfed exclusively for at least 16 weeks comprised the breastfed reference group. Exclusive breastfeeding was defined as receiving only breastmilk, with no other liquids or solids except water or formula in the first 72 hours of life, disregarding vitamins, minerals, or medicines. All participants were followed for a year, during which events of allergic manifestations were diagnosed by qualified physicians and classified as skin, food, or respiratory allergies. Allergy manifestations were considered IgE-mediated if either the skin prick test to any tested allergen or specific IgE blood test was positive at 12m. In this study, we selected a subset of 72 subjects from the breastfed reference group based on the availability of fecal samples collected before 16 weeks (baseline), at 6 months (6m), and at 12 months (12m) of age. Sample collection and storage procedure is available in Supplementary materials. Microbiome data acquisition Fluorescence in situ hybridization (FISH) quantification of Bifidobacterium genus and Eubacterium rectale/Clostridium coccoides group (ER/CC) was performed on a subset of subjects as described previously. 18 Metabolomic data acquisition Liquid chromatography–mass spectrometry (LC-MS) metabolomic data acquisition and preprocessing were performed as previously described. 19 Briefly, wet fecal samples went through lyophilization and liquid-liquid extraction prior to the analysis by reverse phase LC-MS (RPLC-MS) using two separate assays one covering polar to semi-polar metabolites and a second covering bile acids (BAs) and long-chain fatty acids (LCFAs). In case of coelution, the targets were reported using the name or abbreviation of one of the targets followed by a “#” (Table S1). Data quality inspection, including between-batch correction and removal of metabolites with high technical variance (quality control RSD > 30%) was conducted using mzQuality. 20 The analysis of short-chain fatty acids (SCFAs) and lactic acid was conducted as already described. 21 Data analysis Data handling and statistical analyses were performed in R (version 4.3.3). After dry weight normalization, metabolites with a median signal below five times the mean signal of the procedure blanks were excluded. To detect group bias in missing data, the Fisher’s exact test was applied to metabolites with any missing measurements (Tables S2-3). The 57 metabolites with missingness >20% were subjected to unpaired Mann-Whitney U test to assess the difference between visits and between the study groups (allergic vs non-allergic, vaginal vs C-section delivery, complementary-fed vs non-complementary-fed, formula-fed vs non-formula-fed, breastfed vs non-breastfed) at the relevant visits. Missing values of the 162 metabolites with missingness <20% were imputed after log 2 transformation. Then, linear mixed models (LMMs) were used to examine the metabolomic difference between the study groups over time. Clinical characteristics were checked for associations to allergy, delivery mode, and feeding practices using Mann-Whitney U-test for numeric variables and the Fisher’s exact test for binary variables. Differences in the microbiome data across visits and between the study groups at each visit were assessed using the Mann-Whitney U test. Spearman’s correlation analysis was conducted to assess the relationship between LCFAs and microbiome taxa. Multiple testing correction was performed using the Benjamini-Hochberg method where Q<0.1 was considered as statistically significant. Further data analysis details are available in Supplementary Material. Results Patient characteristics Table 1 summarizes the characteristics of the 72 infants at risk of developing allergy who were followed throughout their first year. The associations between the clinical characteristics and allergy manifestation, delivery mode, and feeding practices, were examined (Table S4-6). Potential confounders excluded from this analysis include: i) clinical characteristics describing symptoms of allergy and its treatment, as well as gestational age and maternal pre-pregnancy BMI associated with c-sections; ii) patient characteristics such as country and mineral supplementation which were excluded due to low sample size. Age has a significant impact on the fecal metabolome To explore the impact of age, diet, delivery mode, and allergy on the fecal metabolome, a range of host and gut microbial metabolites, including amino acids (AAs) and derivatives, vitamins, nucleobases, nucleosides, BAs, LCFAs, and SCFAs were examined (Table S1). Age had a strong effect on the metabolome, with LMM analysis identifying 99 metabolites that significantly changed within the first 6 months of life and 92 metabolites in the second half of the first year (Figure 1A, Table S7). B vitamins and derivatives, AAs and derivatives, BAs, nucleobases, nucleosides and derivatives, SCFAs, and phenolic acids increased significantly throughout the whole first year, between baseline and 6m or between 6m and 12m. Among those the primary BAs, CA and CDCA, increased in the first six months, glyco-conjugated BAs in the latter six months, and secondary BAs during either or both halves of the year (Figure 1A). Host tryptophan metabolites also increased with age, whereas the microbial aromatic acid metabolites followed varying time trends. Aromatic lactic acids (PLA, ILA, 4-OH-PLA#) increased until 6m. Then, while PLA remained unchanged, ILA and 4-OH-PLA# decreased. The tryptophan-derived indoxyl sulfuric and phenylalanine-derived PAGIn and hippuric acid also declined after 6m. Meanwhile, the acetic aromatic acids 4-OH-PAA# and IAA increased after 6m, with IAA decreasing before 6m (Figure 1A). LCFAs declined through the first year, except for ALA#, LA, and mead acid which declined significantly only until 6m. Even though an overall decline in acylcarnitines was observed after 6m, before 6m the long-chain acylcarnitines increased, whereas the short- and medium-chain acylcarnitines remained unchanged (Figure 1A). The metabolites that could not be analyzed using LMM analysis were assessed using a Mann-Whitney U test (Figure S1A). Consistent with LMM findings, acylcarnitines decreased, whereas AAs and derivatives; B vitamins and derivatives; nucleobases, nucleosides and derivatives; SCFAs; and phenolic acids increased over time. Similarly host tryptophan metabolites, the acetic aromatic acid PAA, and propionic aromatic acid 4-OH-PPA also showed age-related increases. The levels of the tryptophan microbial metabolite IPA were stable during the first year, while its missingness declined (Table S3). Meanwhile, TUDCA and secondary BAs increased, particularly in the second half of the first year (Figure S1A). Although LCA and DCA did not pass QC, visual inspection suggested a rise, especially in some subjects at 12m (Figure S3). Dietary changes were associated with fecal metabolome alterations Infant diets evolved during the first year (Table 1), where at baseline (<16 weeks), all infants were breastfed, at 6m 90% infants were breastfed, 8.3% mixed-milk-fed (breastfed and formula-fed), and 1.4% formula-fed, while at 12m, 68% were breastfed, 15% mixed-milk-fed, and 17% formula-fed. Meanwhile, complementary feeding had started for 76% of the participants by 6m and for all by 12m. Initiation of formula-feeding had a minor effect on the metabolome (LMM, Table S7). It was associated with lower levels of B vitamins i.e. pyridoxal, pantothenic acid, nicotinic acid as well as thymine, 2-deoxyuridine, 2-deoxyinosine but with higher guanosine# and allantoin until 6m. However, following multiple testing correction, only the association of thymine remained significant. Complementary feeding was associated with significantly higher propionate, carnosine and aromatic acetic acids 4-OH-PAA# and IAA but lower uric acid and pyruvate levels among others (Table S7, Figure 1C). Until 6m, complementary feeding was also negatively associated with the primary BAs CA, CDCA, alloCA but positively with the secondary BA UDCA and syringic acid. The latter was detected only after the introduction of complementary food except for one infant (Figure S2). Meanwhile, the cessation of breastfeeding was associated with higher EDCA but lower long-chain acylcarnitines, caffeine and metabolites, Neu5Ac, and 4-hydroxycinnamic acid. The tryptophan and tyrosine metabolites kynurenic acid, indoxyl glucoside, xanthurenic acid (Q<0.1), ILA, tyramine, and 4-OH-PLA# (0.01<P0.1) were also negatively associated with cessation of breastfeeding (Figure 1B). The effect of feeding practices for metabolites that could not be analyzed using LMM analysis, were assessed using the Mann-Whitney U test (Figure S1B-C, Table S8). Butyrate, secondary BAs, and phenolic acids were found to be higher in the complementary-fed versus non-complementary-fed infants at 6m (Q<0.1) and breastfed versus non-breastfed subjects at 12m (P<0.05). N2,N2-dimethylguanosine and 2-octenoylcarnitine were respectively higher and lower in the complementary-fed versus non-complementary-fed infants, whereas the tryptophan metabolite IPA was higher in the non-breastfed versus breastfed infants. Delivery mode affected the fecal metabolome up to 6 months of age TEMPO enrolled infants delivered vaginally and via a C-section, allowing an investigation into the effect of the delivery mode on the metabolome. Fifteen metabolites, including Neu5Ac, AAs and derivatives, pyrimidine and purine derivatives, and carboxylic acids, were significantly lower in the C-section compared to the vaginal group at baseline (Figure 2, Table S9). For all, the group differences decreased with age until the groups completely overlapped at 12m. Notably, Neu5Ac levels remained stable over time in the C-section group, while they declined in the vaginal group. In contrast, proline and tryptophan were stable in the vaginal group but increased over time in the C-section group. Citrate and isocitrate also followed opposing trends, decreasing in the vaginal group while increasing in the C-section group. Higher LCFA levels in infants who developed allergy LMMs were used to examine the longitudinal metabolite alterations with age between the infants who developed allergies during the first year of life and those who did not. At baseline, no participants were allergic and allergies developed between 69 and 299 days (median age 126.5 days). A few LCFAs, namely LA, EPA, ALA#, DHA, OA, and mead acid, were found to be significantly higher at baseline in the allergic compared to the non-allergic group (Table S10). However, the group separation disappeared over time and the groups overlapped at 6m and 12m (Figure 3). Lower Bifidobacterium spp. in infants prior to allergy development FISH was applied to quantify the Bifidobacterium spp. which are characteristic GM members in breastfed infants and ER/CC, which is primarily composed of Lachnospiraceae species and is more common in adults. 22 The analysis showed that the Bifidobacterium spp. levels were significantly lower at 12m compared to baseline and 6m, whereas the opposite was the case for ER/CC (P<0.05, Q<0.1, Figure 4A). ER/CC was also significantly lower in infants that were still breastfed versus non-breastfed infants (P<0.05, Q<0.1, Figure 4C) and those not receiving formula versus those that did at 12m (P0.1, Figure S4). Complementary feeding and delivery mode were not associated with significant differences in the examined taxa (Figure S4). The baseline Bifidobacterium spp. levels of the infants who developed allergy by 12m were lower than those that did not (P0.01, Figure 4B). A follow-up Spearman correlation analysis showed no evidence of a correlation between reduced Bifidobacterium spp. levels and elevated LCFAs levels (Figure S5). Discussion In this study, healthy breastfed infants at risk of allergy were followed throughout their first year. During this period, alteration in the fecal metabolome and key microbiome members ( Bifidobacterium spp., ER/CC) were examined in relation to age, feeding practices, mode of delivery, and allergy development. Strong age-associated alterations were observed including an overall increase in AAs and derivatives, BAs, nucleobases, nucleosides and derivatives, B vitamins and derivatives, SCFAs, and phenolic acids, along with a decrease in LCFAs and acylcarnitines. Feeding practices, specifically the intake of complementary food and cessation of breastfeeding were significantly associated with changes to the metabolome. Delivery mode had a pronounced impact on the metabolome with distinct differences observed mainly at baseline, some of which persisted until 6m. Meanwhile, infants who developed allergy had significantly lower Bifidobacteria spp. and higher LCFA levels at baseline. These strong age-associated metabolome changes align with previous studies examining the fecal metabolome in early life. 23,24 These pronounced shifts are expected, given the rapid physical growth 2 and GM diversification associated with the transition from milk to solid food during this period. 25 In our cohort, the diversification is evident by the significant decline in bifidobacteria and the increase in the adult-like ER/CC at 12m as well as higher ER/CC in non-breastfed versus breastfed infants at 12m. The shift to a diet richer in fiber and protein, and the resulting GM diversification, is also clearly reflected at the metabolomic level. The decline in pyruvate after 6m following an initial increase, and its negative association with complementary feeding, likely reflects its conversion to downstream metabolites as the GM diversifies. 26 The increase in fiber intake was also evident by the rise of butyrate and propionate after 6m and their positive association with complementary feeding and cessation of breastfeeding, respectively, in agreement with Tsukuda et al . 27 That aligns well with the observed increase in the well-known butyrate producers within ER/CC. 28 The observed temporal increase in phenolic acids, alongside associations with breastfeeding and complementary feeding, is consistent with their diverse origins, including plants, 29 breastmilk, 30 and microbial flavonoid and tyrosine transformation. 29 Meanwhile, the higher levels of carnosine 31 and N2,N2-dimethylguanosine 32 in complementary-fed infants may indicate meat consumption. A shift from a bifidobacteria-rich to a more adult-like microbiome was also evident by the change in microbial aromatic AA metabolites. As expected, the aromatic lactic acids ILA, 4-OH-PLA#, and PLA#, known to be produced by infant-type bifidobacterial species, 33 increased until 6m. Subsequently PLA# levels remained unchanged, whereas those of ILA and 4-OH-PLA# declined and were lower in infants who received no breastmilk at 12m, supporting Sillner et al. ’s findings. 34 The observations also align with the bifidobacterial decline at 12m. The aromatic acetic and propionic acids IAA, 4-OH-PAA, PAA, and 4-OH-PPA increased after 6m and were positively associated with complementary feeding, likely reflecting increased microbial protein degradation. 26 In contrast, IPA did not rise with age, however, it was detected in more infants at 12m compared to 6m and was positively associated with cessation of breastfeeding, suggesting that IPA producers are more common GM members at 12m. The phenylalanine-derived PAGIn and tryptophan-derived indoxyl sulfuric acid, declined with the introduction of complementary feeding contrary to their expected increase. 26 These metabolites are of particular interest due to their known detrimental effects on health in adults and remain understudied in early life. 26 Though B vitamins can be obtained from the diet, including breastmilk, 35 their temporal rise is also likely attributed to microbial production as multiple GM members are well-established B vitamin producers. 36 As anticipated, the abundance and diversity of secondary BAs increased with age and the two drivers of GM diversification: introduction to complementary foods and the cessation of breastfeeding. Similar to Sillner et al. 34 we report on less-studied secondary BAs in infancy, along with almost complete absence of LCA and DCA until 12m. 34 The latter aligns with the observed increase in ER/CC well-known for its high 7α-dehydroxylating activity required for their production. 37 Meanwhile, the rise in glyco-BAs after 6m likely reflects the reduction in particularly effective glyco-BAs deconjugators bifidobacteria. 38 The decline in acylcarnitines after 6m and their positive association with breastfeeding, along with the negative association of LCFAs with age suggest increasing reliance on beta oxidation for energy. Production of conjugated linoleic and linolenic acid isomers by bifidobacteria 39 likely also contributes to the decline in LA and ALA# before 6m, a period characterized by bifidobacterial dominance. Multiple studies have shown strong fecal metabolome differences between breastfed and formula-fed infants. 23,34,40,41 However, unlike these studies, our cohort consisted of infants breastfed for at least 16 weeks, with formula-feeding often initiated alongside breastfeeding, mainly after the introduction of complementary feeding. The minor significant associations observed with formula feeding in this cohort, agree with He et al ., 40 who reported convergence of the metabolome profiles between breast-fed and formula-fed infants following complementary feeding. Despite its known importance in shaping the GM, 42 delivery mode was not associated with microbiome differences in our cohort. It did, however, affect the metabolome, especially at baseline and up to 6 months. Earlier studies reported no metabolome changes despite shifts in the microbiome composition, 43 or significant alterations that differ from our findings and between each other. 24,44 These discrepancies may reflect ethnic or age-related cohort differences. We found the HMO building-block Neu5Ac to be significantly higher in the vaginal compared to the C-section group and maternal pre-pregnancy BMI to be associated with C-section. Knowing that pre-pregnancy BMI has been linked to HMO composition 45 , the difference in Neu5Ac may be attributed to variations in breastmilk composition. Another possibility is that vaginally-delivered infants’ guts are richer in taxa like Bacteroides capable of cleaving sialic acids HMO residues. 46 Unexpectedly, no metabolome differences were observed between the allergic groups at 6m and 12m, despite the emergence of allergic symptoms in this period. Feeding changes and the resulting GM shifts may have masked these differences. Infants who developed allergy during the study did, however, have significantly higher baseline levels of the LCFAs, mainly polyunsaturated fatty acids (PUFAs), includingn-6 LA and n-3 EPA, ALA#, DHA. Although elevated plasma n-3 and n-6 PUFA levels have also been reported in children with food allergy, 47 lower n-3 PUFA levels are generally associated with increased allergy risk. 48,49 Along with the higher LCFA levels, we observed lower Bifidobacterium spp. in the allergic group. The absence of significant correlation between the two, however, suggests that the lower LCFA levels in the allergic infants are unlikely to be due to bifidobacteria. Instead, the difference may be due to variations in mother’s breastmilk composition, 50 microbial transformation, 39 or differences in intestinal absorption. Our study has several limitations, including the small sample size, the wide age range at baseline, and the infrequent sampling. The limited sample size, especially in the allergic group, prevented a separate analysis of the different allergy types. To enhance metabolomic interpretation and clarify the GM–allergy link, future research should consider whole microbiome dynamics rather than focusing solely on specific taxa. Meanwhile, examining the circulating metabolome and breastmilk compositional analysis are of interest to respectively understand the plausible link between LCFAs and allergy and aid the interpretation of the delivery mode findings. Despite these limitations, this study offers valuable new insights into the longitudinal fecal metabolome development in infancy, a critical period with lasting implications for immune system development. Our findings reveal substantial metabolomic shifts with age likely due to changes to the host metabolism, diet, and the GM. Notably, we show that C-section is significantly associated with fecal metabolome alterations up to 6m, though the health implications of these changes require further investigation. This study showed that low Bifidobacterium spp. and LCFAs precede allergy, suggesting potential targets for early dietary intervention to decrease the risk of developing allergies. Author contributions M.V.S: Conceptualization, Investigation, Methodology, Formal Analysis, Visualization, Data curation, Writing – Original Draft Preparation; P.Z.: Conceptualization, Investigation, Methodology, Writing – Review & Editing; A.K.: Conceptualization, Supervision, Writing – Review & Editing; The TEMPO study team: Resources; H.W.: Conceptualization, Writing – review and editing C.B.: Conceptualization, Funding acquisition, Writing – review and editing; A.C.H.: Conceptualization, Supervision, Writing – Review & Editing; T.H.: Conceptualization, Supervision, Funding acquisition, Writing – review & editing. math_shortcuts Acknowledgments Pascal Mass is greatly appreciated for his invaluable assistance in metabolomics data pre-processing. We thank all the study investigators for their contribution in data and sample collection in the TEMPO study, namely: Mazin Alhakim, László Barkai, Csaba Bartha, Ildikó Batta, Viktor Bauer, Shira Benor, Kirsten Beyer, Elena Bradatan, Katrina Cathie, Chong Chan Poh, An-Chyi Chen, Shih-Ming Chu, Elisa Civardi, Ronit Confino-Cohen, Maria Couce Pico, Daniel Drazan, Jitka Fabianova, Allessandro Giovanni Fiocchi, Montserrat Garriga, Francisco Giménez Sánchez, Anne Goh Eng Neo, Monique Gorissen, Martin Gregora, Ludmila Grossmanova, Zuzana Havlicekova, Stephen Hughes, Jose Hurtado, Natalia Klocanova, Éva Kovács, Silvia Labovska, István Laki, Anja Lange, Yu Lung Lau, Ting F. Leung, Danica Mankova, Nofar Marcus, Louise J. Michaelis, Zuzana Nagyova, López Eduardo Narbona, Antonio Nieto, Lee Noimark, Daniela Olexova, Miroslava Ondrejkova, Nikolaos G. Papadopoulos, Stefaan Peeters, Paola Roggero, Renata Ruzkova, Miguel Sáenz de Pipaón, Ignacio Salamanca de la Cueva, Vered Schichter-Konfino, Beata Sediva, Eduardo Shahar, Pavol Simurka, Sylva Skalova, Françoise Smets, László Somorjai, Zev Sthoeger, Zbynek Stranak, Edina Stunya, Erzsebet Szakos, Ron van Beek, Vivienne van de Walle, Hans van Goudoever, Yvan Vandenplas, Mirko Zibolen. Ethical Approval and Trial Registration Statements The samples for this work arise from a randomized, double-blind, controlled, parallel-group, multi-country study called TEMPO (clinicaltrials.gov identifier: NCT03067714). Detailed information on ethics committees, institutional review boards, and regulatory authorities that approved the study was previously published. 17 Data availability The metabolomics data of this study are submitted in MetaboLights at http://www.ebi.ac.uk/metabolights/ with reference number REQ20250515210510, along with limited clinical metadata. Additional individual-level metadata, even pseudonymized, are sensitive and are protected by the GDPR and not publicly available. Reasonable data sharing requests based on data processing and material transfer agreements can be made to Danone Research & Innovation (https://www.danoneresearch.com/). Key Message This study gives new insights into the longitudinal fecal metabolome development during infancy, a period of rapid gut microbial colonization and immune system development. The analysis revealed that delivery mode exerts lasting effects on the fecal metabolome and identified potential early markers of allergy. These findings may guide future dietary interventions to promote gut health and reduce the risk of developing allergies. References 1. Wu, Z. A. & Wang, H. X. A Systematic Review of the Interaction Between Gut Microbiota and Host Health from a Symbiotic Perspective. SN Compr. Clin. Med. 1 , 224–235 (2019).2. Yatsunenko, T. et al. 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Table 1 Clinical characteristics. Numeric variables are presented as median [range]; categorical variables are presented as numbers of participants. Sex (female/male) 35 / 37 9 / 11 26 / 26 12 / 8 23 / 29 Allergy manifestation (Allergic/Not allergic) 20 / 52† - - 7 / 13 13 / 39 Type of allergy (IgE/non-IgE) 10/10 10/10 - 3 / 4 7 / 6 Type of allergy† (skin / food / respiratory) 18 / 2 / 2 18 / 2 / 2 - 7 / 1 / 0 11 / 2 / 1 Age onset allergy (days) - 126.5 [69, 299] - - - Mode of delivery (Vaginal/Cesarean) 52 / 20 ‡ 13 / 7 39 / 13 - - Country Belgium 1 1 0 0 1 Czech Republic 36 15 21 8 28 United Kingdom 1 0 1 0 1 Hungary 14 2 12 5 9 Slovakia 20 2 18 7 13 Gestational age (weeks) 39.3 [37.6-41.9] 39.2 [37.6-41.7] 39.3 [37.6-41.9] 38.8 [37.6-40.9] 39.6 [37.6-41.9] Birth head circumference (cm) 34.5 [32-39] 34.0 [33-38] 35.0 [32-39] 35.0 [33-39] 34.0 [32-38] Birth weight (kg) 3.4 [2.6-4.2] 3.4 [2.9-4.2] 3.4 [2.6-4] 3.4 [2.9-4] 3.4 [2.6-4.2] Birth length (cm) 50 ± 2.4 50 ± 1.8 50 ± 2.6 50 ± 1.8 50 ± 2.6 birth length (cm) 50 [47-58] 50 [47-54] 50 [47-58] 50 [47-53] 50 [47-58] Mother’s BMI pre-pregnancy 23.3 [18.4-40] 22.2 [18.4-35] 23.9 [18.6-40] 24.6 [19.9-40] 22.8 [18.4-35] Age (days) baseline 41.5 [1-111] 23 [1-111] 52.5 [2-111] 53 [2-108] 37 [1-111] 6 months 180 [166-227] 179 [166-192] 180 [167-227] 180 [168-227] 180 [166-206] 12 months 364 [345-383] 365.5 [348-383] 363.5 [345-378] 365 [345-377] 363.5 [348-383] Breastfeeding (yes/no) baseline 72 / 0 20 / 0 52 / 0 20 / 0 52 / 0 6 months 71 / 1 20 / 0 51 / 1 20 / 0 51 / 1 12 months 58 / 14 17 / 3 41 / 11 18 / 2 40 / 12 Formula Feeding (yes/no) baseline 0 / 72 0 / 20 0 / 52 0 / 20 0 / 52 6 months 7 / 65 2 / 18 5 / 47 1 / 19 6 / 46 12 months 23 / 49 6 / 14 17 / 35 4 / 16 19 / 33 Milk feeding§ (BF / FF / MMF) baseline 72 / 0 / 0 20 / 0 / 0 52 / 0 / 0 20 / 0 / 0 52 / 0 / 0 6 months 65 / 1 / 6 18 / 0 / 2 47 / 1 / 4 19 / 0 / 1 46 / 1 / 5 12 months 49 / 12 / 11 12 / 2 / 4 35 / 10 / 7 48 / 2 / 2 33 / 10 / 9 Complementary Feeding (yes/no) baseline 0 / 72 0 / 20 0 / 52 0 / 20 0 / 52 6 months 55 / 17 13 / 7 42 / 10 15 / 5 40 / 12 12 months 72 / 0 20 / 0 52 / 0 20 / 0 52 / 0 †The two subjects who had developed IgE-mediated food/respiratory allergy were also diagnosed with IgE-mediated skin allergy ‡Even though the numbers for allergy and delivery mode are the same (20 / 52), the infants in the four groups are different. More specifically 39 non-allergic and 13 allergic subjects were delivered vaginally; while 13 were non-allergic and delivered via a C-section; 7 were allergic and delivered via a C-section. §BF – breastfed, infants receiving breastmilk and no formula milk; FF – formula-fed, infants receiving infant formula milk and not breastmilk, MMF – mixed milk-fed – infants receiving breastmilk and formula milk Figure 1 , Fecal metabolome alterations associated with age (A), cessation of breastfeeding (B), introduction of complementary feeding (C) between baseline and 6m and/or 6m and 12m, assessed using LMM. Colors represent the model coefficient: positive (red), negative (blue), p>0.05 (white). In (A) a positive coefficient represents an increase of the metabolite between the visits; in (B) a positive coefficient represents an increase of the metabolite associated with cessation of breastfeeding; while in (C) a positive coefficient represents an increase of the metabolite with introduction of complementary feeding. Class annotation: a - AAs and derivatives; b aromatic AAs metabolites; c - dipeptides and tripeptides; d - B vitamins and derivatives; e - nucleobases, nucleosides and derivatives; f – BAs; g – LCFAs; h – carnitines; j – energy metabolites; k – SCFAs; l - hydroxy acids and derivatives; m - phenolic acids; n – xanthines; o – other. Asterisks indicate statistical significance: Q < 0.1 (*), Q < 0.01 (**), Q < 0.001 (***), Q < 0.0001 (****). The “#” in the metabolite names indicates that the metabolite coeluted with another target metabolite. All abbreviations and coeluting metabolites can be found in Table S1. Figure 2 , Scaled abundance levels of the metabolites that significantly differed between infants delivered vaginally (purple, solid) and via C-section (green, solid) group as a function of age, based on LMM analysis. The shaded areas represent the 95% confidence intervals, while the dotted grey lines represent the median age at each visit (baseline, 6m, 12m). All abbreviations and coeluting metabolites can be found in Table S1. Figure 3 , Scaled relative abundance levels of LCFAs as a function of age in allergic (blue, solid) and non-allergic (orange, solid) groups, based on LMM analysis. The shaded areas represent the 95% confidence intervals, while the dotted grey lines represent the median age at each visit (baseline, 6m, 12m). The “#” in the metabolite names indicates that the metabolite coeluted with another target metabolite. All abbreviations and coeluting metabolites can be found in Table S1. Figure 4 , The levels of A) Bifidobacterium spp. between visits; B) ER/CC between visits; C) between the allergic (blue) and non-allergic (orange) infants at each visit; D) between breastfed (pink) and non-breasted (green) at 12m. Statistical analysis was performed using Mann-Whitney test: P < 0.05 (*), P < 0.01 (**), P < 0.001 (***), P < 0.0001 (****), for Q values refer to Table S8. Number of measurements per group and visit: Bifidobacterium spp.: n = [50, 62, 70]; ER/CC: n = [48, 60, 71] for baseline, 6m and 12m, respectively. Information & Authors Information Version history V1 Version 1 23 June 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Authors Affiliations Mariyana Savova Universiteit Leiden Leiden Academic Centre for Drug Research View all articles by this author Pingping Zhu 0009-0004-5949-5746 Universiteit Leiden Leiden Academic Centre for Drug Research View all articles by this author Alida Kindt Universiteit Leiden Leiden Academic Centre for Drug Research View all articles by this author Harm Wopereis Danone Research & Innovation View all articles by this author Clara Belzer 0000-0001-6922-836X Wageningen University & Research Laboratory of Microbiology View all articles by this author Amy Harms C 0000-0002-2931-4295 [email protected] Universiteit Leiden Leiden Academic Centre for Drug Research View all articles by this author Thomas Hankemeier Universiteit Leiden Leiden Academic Centre for Drug Research View all articles by this author Metrics & Citations Metrics Article Usage 268 views 141 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Mariyana Savova, Pingping Zhu, Alida Kindt, et al. 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