Dysbiosis testing and chronic intestinal inflammation

Abstract

Chronic intestinal inflammation is increasingly recognized as a key contributor to metabolic dysfunction and non-communicable diseases. Central to this process is gut dysbiosis, defined by alterations in microbial richness, function, and distribution that disrupt immune balance, compromise barrier integrity, and impair gut–brain–liver–adipose signaling. Clinical manifestations include irritable bowel syndrome (IBS), inflammatory bowel disease (IBD), and small intestinal bacterial overgrowth (SIBO). Importantly, the concept of a “healthy” microbiome is now seen as highly individualized, with microbial strains exerting context-dependent effects within different host environments.

Our next-generation sequencing datasets and predictive mathematical models across cohorts with IBS, IBD, atherosclerosis, and post-traumatic stress disorder highlight consistent features: depletion of protective species such as Faecalibacterium prausnitzii and Akkermansia muciniphila, alongside the expansion of pro-inflammatory organisms. These microbial shifts correlate with barrier damage, immune dysregulation, and greater disease severity. Despite advances in stool sequencing, molecular diagnostics, metabolomics, and breath testing, standardization and predictability remain major challenges.

Within predictive, preventive, and personalized medicine (3 PM), microbiome-based signatures hold promise for identifying at-risk individuals, guiding targeted interventions, and enabling longitudinal monitoring. Lifestyle interventions including fiber-rich diets, prebiotics, probiotics, physical activity, stress management, and circadian alignment represent practical strategies for restoring microbial homeostasis and reducing chronic inflammation. Furthermore, Delphi consensus efforts, artificial intelligence tools, and curated databases are advancing the development of precise pharmabiotics and targeted microbiome corrections.

This review advocates for an interdisciplinary approach that integrates microbiome diagnostics, computational modeling, and personalized therapeutics to improve metabolic health and reduce the burden of chronic diseases.