Microbial Biomarkers and Personalized Medicine in Respiratory Disorders: Bench to Bedside

Respiratory diseases such as asthma, chronic obstructive pulmonary disease (COPD), bronchiectasis, pneumonia, and tuberculosis are a significant health burden to the world because of their heterogeneity, inconsistent progression, and unpredictabileness to treatment. The development of microbial and host-derived biomarkers promises to aid in improving diagnosis, prognosis, treatment stratification and disease monitoring as a part of personalized medicine. Recent advances in specimen-based techniques including sputum, bronchoalveolar lavage, blood, stool, and exhaled breath, and multi-omics methods, like metagenomics, transcriptomics, proteomics, metabolomics, and breathomics are summarized in this review. Evidence on disease-specific is addressed and microbiome signatures in asthma and COPD, transcriptomic and microbial biomarkers in tuberculosis and the emerging clinical utility of volatile and non-volatile exhaled compounds as non-invasive diagnostics are discussed. The combination of machine learning and artificial intelligence to combine multi-omics data into a clinically actionable model is critically assessed, and several of the major obstacles, including analytical validation, multicenter reproducibility, cost-efficacy, regulatory approval, and equity of access, are considered. This review has emphasized the frameworks such as the FDA-NIH BEST taxonomy, STORMS, STARD-AI, and TRIPOD+AI and has highlighted the need to have rigor in methodology in order to translate clinical findings. When combined, microbial biomarkers, along with host-response and multi-omics approaches, possess high value to change the face of respiratory medicine by focusing on symptoms to precision diagnostics and personalized treatment.