ArticleBMC microbiology2021
Associations between the gut microbiome and metabolome in early life.
Article in BMC microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
29 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Integrated Analysis of Gut Microbiota and Metabolome Profiling Reveals the Effects of Feeding Approaches on Infants' Gut Microenvironment.Food science & nutrition · 2026Article
- Impact of maternal, infant, and household factors on early-life gut microbiome development in a rural setting.The ISME journal · 2026Article
- Early-life microbiome trajectories as biomarkers to predict health outcomes.Microbiome research reports · 2026Review
- Comparative analysis of the metabolite compositions and antioxidant capacity of waxy and non-waxy black rice (Food chemistry: X · 2025Article
- Article
- Longitudinal Microbiome and Metabolome Shifts After Successful Intervention in Impending Stunting in Indonesian Infants.Nutrients · 2025Article
- Childhood gut microbiome is linked to internalizing symptoms at school age via the functional connectome.Nature communications · 2025Observational
- Article
- A systematic benchmark of integrative strategies for microbiome-metabolome data.Communications biology · 2025Article
- The fecal metabolomic signature of a plant-based (vegan) diet compared to an animal-based diet in healthy adult client-owned dogs.Journal of animal science · 2025Article
- MicrobiomeKG: bridging microbiome research and host health through knowledge graphs.Frontiers in systems biology · 2025Article
- Article
- Gut microbiota wellbeing index predicts overall health in a cohort of 1000 infants.Nature communications · 2024Observational
- Statistical and computational methods for integrating microbiome, host genomics, and metabolomics data.eLife · 2024Review
- High microbiome and metabolome diversification in coexisting sponges with different bio-ecological traits.Communications biology · 2024Article
- Multi-omic integration of microbiome data for identifying disease-associated modules.Nature communications · 2024Article
- Changes of gut microbiota and short chain fatty acids in patients with Peutz-Jeghers syndrome.BMC microbiology · 2023Article
- Strontium ranelate enriched Ruminococcus albus in the gut microbiome of Sprague-Dawley rats with postmenopausal osteoporosis.BMC microbiology · 2023Article
- The Bern Birth Cohort (BeBiCo) to study the development of the infant intestinal microbiota in a high-resource setting in Switzerland: rationale, design, and methods.BMC pediatrics · 2023Article
Corrections and comments
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Authors and funding
11 authors.
Funding
Abstract
backgroundThe infant intestinal microbiome plays an important role in metabolism and immune development with impacts on lifelong health. The linkage between the taxonomic composition of the microbiome and its metabolic phenotype is undefined and complicated by redundancies in the taxon-function relationship within microbial communities. To inform a more mechanistic understanding of the relationship between the microbiome and health, we performed an integrative statistical and machine learning-based analysis of microbe taxonomic structure and metabolic function in order to characterize the taxa-function relationship in early life.
resultsStool samples collected from infants enrolled in the New Hampshire Birth Cohort Study (NHBCS) at approximately 6-weeks (n = 158) and 12-months (n = 282) of age were profiled using targeted and untargeted nuclear magnetic resonance (NMR) spectroscopy as well as DNA sequencing of the V4-V5 hypervariable region from the bacterial 16S rRNA gene. There was significant inter-omic concordance based on Procrustes analysis (6 weeks: p = 0.056; 12 months: p = 0.001), however this association was no longer significant when accounting for phylogenetic relationships using generalized UniFrac distance metric (6 weeks: p = 0.376; 12 months: p = 0.069). Sparse canonical correlation analysis showed significant correlation, as well as identifying sets of microbe/metabolites driving microbiome-metabolome relatedness. Performance of machine learning models varied across different metabolites, with support vector machines (radial basis function kernel) being the consistently top ranked model. However, predictive R
conclusionsOur results suggest a degree of overall association between taxonomic profiles and metabolite concentrations. However, lack of predictive capacity for stool metabolic signatures reflects, in part, the possible role of functional redundancy in defining the taxa-function relationship in early life as well as the bidirectional nature of the microbiome-metabolome association. Our results provide evidence in favor of a multi-omic approach for microbiome studies, especially those focused on health outcomes.
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