By Hugo Francisco de Souza Reviewed by Benedette Cuffari, M.Sc.
In a recent study published in the journal Nature Reviews Microbiology, researchers summarize over 200 publications associating microbiomes with clinical diagnostic and precision therapeutic interventions.
Study: Utilization of the microbiome in personalized medicine. Image Credit: FOTOGRIN / Shutterstock.com
Gut microbiota and its potential in personalized medicine
The gut microbiome, which is also referred to as the gut microbiota or gut flora, is a collective term for all microorganisms residing in the digestive tracts of higher animals.
In stark contrast to their human host’s genome, the gut microbial metagenome exhibits remarkable variability and plasticity, constantly evolving in response to host physiology and environment. Gut microbial assemblages are unique in both host specificity, as they are often obtained from maternal microbiota and the environment, and temporal.
The microbiome composition varies significantly among individuals, and may also shift within the same individual, reflecting dynamic changes that occur throughout life as a result of age, geographical location, diurnal rhythms, and environmental, nutritional and medicinal exposures.”
A growing body of evidence highlights the importance of gut microbiota in conferring nutritional, disease-resisting, and psychological benefits to their host. Consequently, significant disruptions in the gut microbial ecosystem, termed ‘dysbiosis,’ have been associated with metabolic, gastrointestinal, neurological, and inflammatory outcomes.
Characterizing an individual’s gut microflora may allow for an improved understanding of their current health and support the development of optimized clinical interventions. Current research on treatment personalization often focuses on chronic conditions, most notably cancer.
These studies typically include biochemical and genetic phenotyping to inform interventions for patients. However, these methods are associated with certain limitations; for example, biochemical phenotyping uses standardized methodologies, which can result in binary outcomes with little scope for a nuanced understanding of an individual’s dynamic health. Similarly, genetic phenotyping fails to account for temporal changes in health or the phenotypic outcomes of gene-environment interactions.
Personalization based on a patient’s microbial community composition overcomes the temporal and generalization limitations of current personalization approaches and ensures intra-individual stability, a critical requirement of diagnostic tests.
Automation and diagnostic improvements
Metagenomic sequencing, which is the process of analyzing the genetic composition and diversity of the gut microbiome, has been successfully investigated as a biomarker of patients’ overall health and specific disease prevalence. These studies have led to the identification of trimethylamine N-oxide (TMAO), a microbiome-modulated metabolite, and its role in predicting cardiovascular disease (CVD) risk, as well as branched-chain amino acids predicting type 2 diabetes (T2D).
Studies have further paired metagenomic sequencing with machine learning (ML) artificial intelligence (AI) algorithms to distinguish between glucose intolerance, T2D, and typical glucose metabolism with diagnostic accuracy exceeding currently used diagnostic tools. These findings highlight how microbiome analyses can not only replace current diagnostic tools but, in tandem with AI, significantly reduce the burden of overworked human clinicians.
Utilization of targeted microbiome interventions as a means of modifying disease risk in disease-prone populations may complement and optimize current primary prevention modalities.”
One man’s food is another’s poison
Health behaviors have been identified as the most easily modifiable risk deterrent in numerous weight, age, cardiovascular health, and other non-transmittable chronic health conditions, with several studies suggesting ‘optimal’ behaviors for improved general health.
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Unfortunately, a growing body of research suggests that different individuals may react differently to behavioral interventions. High-intensity physical exercise, while useful in weight loss, has been shown to cause spikes in blood glucose levels, which is detrimental for individuals with type 1 diabetes (T1D). Similarly, individual-specific gut microbiota communities can process and absorb dietary nutrients with significant differences in their hosts’ health outcomes.
Phenotyping a patient’s gut microbiota can help personalize behavioral and clinical interventions against both common and specific health conditions. Furthermore, repeated phenotyping can be used as a marker of treatment responsiveness and intervention efficacy. AI models based on these concepts have been shown to outperform current gold standards in predicting and monitoring patients’ responses to clinical interventions.
Microbes in the fight against microbes?
A growing body of research aims to test the efficacy of microbial gut supplements and targeted microbiome therapies to protect against or directly combat communicable diseases. These studies have evaluated the direct use of microorganisms as drugs, targeting the elimination of specific microbiome strains, ‘post-biotic therapy,’ which involves using microbial metabolites as drugs.
‘Beneficial’ microbes like pre- and probiotics are either directly administered or their growth therapeutically promoted, with the aim of their outcompeting or otherwise neutralizing pathogens. The second class involves the reversal of dysbiosis, a common condition following antibiotic interventions, as this condition can have long-lasting and potentially severe impacts on patients’ health and immunity, making probiotic supplements a standard prescription during or following antibiotic courses.
The final class involves the use of naturally derived or genetically engineered microbial metabolites as antibiotics. Penicillin, the first known antibiotic, falls in this class.
Not all patients are responsive to these interventions, and therefore identifying patients who would most benefit from such approaches is essentia. In this context, the microbiome’s individualized fingerprint could be harnessed as an effective ‘companion diagnostic’ modality in tailoring treatment to the individual.”
So why don’t more doctors use it?
While the benefits of microbiome analyses in disease diagnosis and treatment are numerous, the field remains in its infancy. Few studies have validated the safety of these interventions in humans.
Ironically, one of the foremost strengths of gut microbial interventions – the ‘personalized’ aspects of treatment – presents one of its biggest challenges. Inter-individual variations result in a lack of consistency in single study data and even lower reproducibility between studies, thus preventing medical governing bodies from prescribing their use.
Another demerit of current research is that novelty increases cost. Most studies on gut microbiota utilize next-generation sequencing techniques, which require expertise and incur costs well out of the reach of researchers and institutes in underdeveloped or developing countries.
Recent research suggests that microbial exposure, especially during early childhood, can significantly alter adult microbiome communities and innate immunity. These findings highlight the need for further investigation before the universal application of clinical personalization can transition from the realm of science into mainstream medicine.
Journal reference:
Ratiner, K., Ciocan, D., Abdeen, S. K., & Elinav, E. (2023). Utilization of the microbiome in personalized medicine. Nature Reviews Microbiology; 1-18. doi:10.1038/s41579-023-00998-9
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