ArticlemSystems
Health and Disease Imprinted in the Time Variability of the Human Microbiome.
Article in mSystems. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Comparison of the gut microbiota in older people with and without sarcopenia: a systematic review and meta-analysis.Frontiers in cellular and infection microbiology · 2025Pooled it
- Efficacy and Safety ofNutrients · 2019Trial
- CoDaLoMic: An R package for modeling microbiome compositional and longitudinal data.PLoS computational biology · 2026Article
- Lifetime existence of a core of mutualistic symbionts and functionally uncoupled taxa in the gut of a Mediterranean cohort.Scientific reports · 2026Article
- Patterns of gut microbiome composition, function and dynamics in toddlers, adolescents and adults over a three-year period.Frontiers in microbiology · 2026Article
- Inulin Reverses Intestinal Mrp2 Downregulation in a Diet-Induced Obesity Mouse Model: Role of Intestinal Microbiota as a Pivotal Modulator.Pharmaceutics · 2025Article
- Taylor's Power Law rules the dynamics of allele frequencies during viral evolution in response to host changes.Journal of the Royal Society, Interface · 2025Article
- Addressing the dynamic nature of reference data: a new nucleotide database for robust metagenomic classification.mSystems · 2025Article
- Article
- Longitudinal Microbiome-based Interpretable Machine Learning for Identification of Time-Varying Biomarkers in Early Prediction of Disease Outcomes.bioRxiv : the preprint server for biology · 2024Article
- Interaction Between Early Meals (Big-Breakfast Diet), Clock Gene mRNA Expression, and Gut Microbiome to Regulate Weight Loss and Glucose Metabolism in Obesity and Type 2 Diabetes.International journal of molecular sciences · 2024Review
- Coronavirus Disease 2019 (COVID-19) Pandemic Lifestyle Changes May Have Influenced Small Bowel Microbial Composition and Microbial Resistance.Digestive diseases and sciences · 2023Article
- Characteristics of the fecal microbiome and metabolome in older patients with heart failure and sarcopenia.Frontiers in cellular and infection microbiology · 2023Article
- The global scientific publications on gut microbiota in type 2 diabetes; a bibliometric, Scientometric, and descriptive analysis.Journal of diabetes and metabolic disorders · 2022Article
- Of Cockroaches and Symbionts: Recent Advances in the Characterization of the Relationship betweenLife (Basel, Switzerland) · 2022Review
- High-Fat, Western-Style Diet, Systemic Inflammation, and Gut Microbiota: A Narrative Review.Cells · 2021Review
- The Spanish gut microbiome reveals links between microorganisms and Mediterranean diet.Scientific reports · 2021Article
- Article
- C. elegans: A biosensor for host-microbe interactions.Lab animal · 2021Review
- Microbiota and Diabetes Mellitus: Role of Lipid Mediators.Nutrients · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The animal microbiota (including the human microbiota) plays an important role in keeping the physiological status of the host healthy. Research seeks greater insight into whether changes in the composition and function of the microbiota are associated with disease. We analyzed published 16S rRNA and shotgun metagenomic sequencing (SMS) data pertaining to the gut microbiotas of 99 subjects monitored over time. Temporal fluctuations in the microbial composition revealed significant differences due to factors such as dietary changes, antibiotic intake, age, and disease. This article shows that a fluctuation scaling law can describe the temporal changes in the gut microbiota. This law estimates the temporal variability of the microbial population and quantitatively characterizes the path toward disease via a noise-induced phase transition. Estimation of the systemic parameters may be of clinical utility in follow-up studies and have more general applications in fields where it is important to know whether a given community is stable or not.
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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.