ArticlemSystems2019
Defining and Evaluating Microbial Contributions to Metabolite Variation in Microbiome-Metabolome Association Studies.
Article in mSystems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
35 citing papers in PubMed, 4 syntheses or guidelines pooled it, 67 citations in OpenAlex.
- The gut microbiome-metabolome dataset collection: a curated resource for integrative meta-analysis.NPJ biofilms and microbiomes · 2022Pooled it
- A meta-analysis study of the robustness and universality of gut microbiome-metabolome associations.Microbiome · 2021Pooled it
- The Potential of Metabolomic Analyses as Predictive Biomarkers of Preterm Delivery: A Systematic Review.Frontiers in endocrinology · 2021Pooled it
- Multi-omic meta-analysis identifies functional signatures of airway microbiome in chronic obstructive pulmonary disease.The ISME journal · 2020Pooled it
- Multi-omics characterization of microbial and metabolite profiles of Jeevamrit and Ghanjeevamrit cow-based bioformulations used in sustainable agriculture.Scientific reports · 2026Article
- Modeling diet-gut microbiome interactions and prebiotic responses in Thai adults.NPJ biofilms and microbiomes · 2026Article
- Toward the Next Generation of In Silico Modeling of Dynamic Host-Microbiota Interactions in the Skin.JID innovations : skin science from molecules to population health · 2025Review
- Deciphering dynamic antibiotics-microbiome-metabolome interactions in preterm infants using systems biology.iScience · 2025Article
- COmmunity and Single Microbe Optimisation System (COSMOS).NPJ systems biology and applications · 2025Article
- MiMeJF: Application of Coupled Matrix and Tensor Factorization (CMTF) for Enhanced Microbiome-Metabolome Multi-Omic Analysis.Metabolites · 2025Article
- Decoding emergent properties of microbial community functions through subcommunity observations and interpretable machine learning.The ISME journal · 2025Article
- Metabolome and Mycobiome ofPlants (Basel, Switzerland) · 2024Article
- Emerging tools and best practices for studying gut microbial community metabolism.Nature metabolism · 2024Review
- Characteristics of microbiome-derived metabolomics according to the progression of alcoholic liver disease.Hepatology international · 2024Article
- The endophytic microbiome response patterns ofFrontiers in microbiology · 2024Article
- Causal inference on microbiome-metabolome relations in observational host-microbiome data via in silico in vivo association pattern analyses.Cell reports methods · 2023Article
- Review
- Microbiome Dysbiosis Shows Strong Association of Gut-Derived Altered Metabolomic Profile in Gulf War Chronic Multisymptom Illness Symptom Persistence Following Western Diet Feeding and Development of Obesity.International journal of molecular sciences · 2023Article
- The impact of aquaculture system on the microbiome and gut metabolome of juvenile Chinese softshell turtle (iMeta · 2022Article
- Mass spectrometry-based metabolomics in microbiome investigations.Nature reviews. Microbiology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Correlation-based analysis of paired microbiome-metabolome data sets is becoming a widespread research approach, aiming to comprehensively identify microbial drivers of metabolic variation. To date, however, the limitations of this approach and other microbiome-metabolome analysis methods have not been comprehensively evaluated. To address this challenge, we have introduced a mathematical framework to quantify the contribution of each taxon to metabolite variation based on uptake and secretion fluxes. We additionally used a multispecies metabolic model to simulate simplified gut communities, generating idealized microbiome-metabolome data sets. We then compared observed taxon-metabolite correlations in these data sets to calculated ground truth taxonomic contribution values. We found that in simulations of both a representative simple 10-species community and complex human gut microbiota, correlation-based analysis poorly identified key contributors, with an extremely low predictive value despite the idealized setting. We further demonstrate that the predictive value of correlation analysis is strongly influenced by both metabolite and taxon properties, as well as by exogenous environmental variation. We finally discuss the practical implications of our findings for interpreting microbiome-metabolome studies.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.