Language
English
Publication Date
1-1-2025
Journal
Trends in Pharmacological Sciences
DOI
10.1016/j.tips.2024.11.007
PMID
39732609
PMCID
PMC11786253
PubMedCentral® Posted Date
1-1-2026
PubMedCentral® Full Text Version
Author MSS
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.
Keywords
Animals, Humans, Computational Biology, Metagenomics, Microbiota, Precision Medicine, RNA, Ribosomal, 16S, Microbiome, clinical metagenomics, pan-microbiome profiling, C. difficile infection, inflammatory bowel disease, irritable bowel syndrome
Published Open-Access
yes
Recommended Citation
Henok Ayalew Tegegne and Tor C Savidge, "Leveraging Human Microbiomes for Disease Prediction and Treatment" (2025). Faculty, Staff and Students Publications. 7481.
https://digitalcommons.library.tmc.edu/baylor_docs/7481