ArticleTrends in pharmacological sciences2025
Leveraging human microbiomes for disease prediction and treatment.
Article in Trends in pharmacological sciences, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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
7 citing papers in PubMed.
- The interplay of microbiome, molecular mechanisms, and fertility -an integrated review.Folia microbiologica · 2026Review
- Artificial intelligence empowers gut microbiota research in neurodegenerative diseases molecular mechanisms and precision therapy.iScience · 2025Review
- Pharmacomicrobiomics.Clinical pharmacology and therapeutics · 2025Review
- Synthetic microbial consortia based on quorum-sensing for disease therapy.Bioresources and bioprocessing · 2025Review
- Sequence modeling tools to decode the biosynthetic diversity of the human microbiome.mSystems · 2025Review
- The Neonatal Microbiome: Implications for Amyotrophic Lateral Sclerosis and Other Neurodegenerations.Brain sciences · 2025Review
- Gut microbiota in colorectal cancer: a review of its influence on tumor immune surveillance and therapeutic response.Frontiers in oncology · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
The human microbiome consists of diverse microorganisms that inhabit various body sites. As these microbes are increasingly recognized as key determinants of health, there is significant interest in leveraging individual microbiome profiles for early disease detection, prevention, and drug efficacy prediction. However, the complexity of microbiome data, coupled with conflicting study outcomes, has hindered its integration into clinical practice. This challenge is partially due to demographic and technological biases that impede the development of reliable disease classifiers. Here, we examine recent advances in 16S rRNA and shotgun-metagenomics sequencing, along with bioinformatics tools designed to enhance microbiome data integration for precision diagnostics and personalized treatments. We also highlight progress in microbiome-based therapies and address the challenges of establishing causality to ensure robust diagnostics and effective treatments for complex diseases.
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What Socratic 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 Socratic graph.