Your unique microbiome can be used to improve and personalize your future medical experience

In a recent study published in the journal Nature Reviews Microbiologyresearchers summarize over 200 publications relating microbiomes to clinical diagnostic and precision therapeutic interventions.

Study: Harnessing the microbiome in personalized medicine. Image credit: FOTOGRIN / Shutterstock.com

The gut microbiota and its potential in personalized medicine

The gut microbiome, also referred to as the gut microbiome or gut flora, is a collective term for all the microorganisms that inhabit the digestive system of higher animals.

In stark contrast to their human host 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, often derived from the maternal microbiota and environment, and time.

“The composition of the microbiome varies significantly between individuals and can also shift within the same individual, reflecting dynamic changes that occur throughout life as a result of age, geographic location, daily rhythms, and environmental, dietary, and medical exposures.”

A growing body of evidence highlights the importance of the gut microbiota in providing nutritional, disease-resistant, and psychological benefits to their host. Consequently, significant disturbances in the gut microbial ecosystem, termed “dysbiosis,” have been associated with metabolic, gastrointestinal, neurological, and inflammatory outcomes.

Characterization of an individual’s gut microbiota can enable 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, primarily 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 lead to binary results with little scope for a nuanced understanding of an individual’s health dynamics. Similarly, the genetic phenotype fails to account for temporal changes in health or the phenotypic effects of gene–environment interactions.

Personalization based on the composition of a patient’s microbial community overcomes the time and generalizability limitations of current personalization approaches and ensures inter-individual stability, a critical requirement of diagnostic tests.

Automation and diagnostic improvements

Metagenomic sequencing, which is the process of analyzing the genetic makeup and diversity of the gut microbiome, has been successfully explored as a biomarker of overall patient health and disease-specific prevalence. These studies led to the identification of trimethylamine N-oxide (TMAO), a metabolite modulated by the microbiome, and its role in predicting cardiovascular disease (CVD) risk, as well as branched-chain amino acids that predict type 2 diabetes (T2D ).

Studies have further combined metagenomic sequencing with artificial intelligence machine learning (ML) algorithms to distinguish between glucose intolerance, T2D, and typical glucose metabolism with diagnostic accuracy that exceeds currently used diagnostic tools. These findings highlight how microbiome assays can not only replace current diagnostic tools, but, combined with artificial intelligence, significantly reduce the burden on overworked human doctors.

The use of targeted microbiome interventions as a means of modifying disease risk in disease-prone populations can complement and optimize current primary prevention methods.”

One man’s food is another man’s poison

Health behaviors have been identified as the most easily modifiable risk factor for many weight, age, cardiovascular health and other non-communicable chronic health conditions, with several studies suggesting “optimal” behaviors for improved overall health.

Unfortunately, a growing body of research suggests that different individuals may respond differently to behavioral interventions. Vigorous exercise, although helpful in weight loss, has been shown to cause increases in blood glucose levels, which is detrimental to people with type 1 diabetes (T1D). Similarly, individual gut microbial communities can process and absorb dietary nutrients with significant differences in the health outcomes of their hosts.

Phenotyping a patient’s gut microbiota can help individualize behavioral and clinical interventions against common and specific health conditions. In addition, repeated phenotyping can be used as an indicator of treatment response and intervention efficacy. Artificial intelligence models based on these concepts have been shown to outperform current gold standards in predicting and monitoring patient responses to clinical interventions.

Germs in the fight against germs?

A growing body of research aims to test the effectiveness of gut microbial supplements and targeted microbiome therapies to protect against or directly combat infectious diseases. These studies have evaluated the direct use of microorganisms as drugs, aiming to eliminate specific microbiome strains, “metabiotic therapy,” which involves the use of microbial metabolites as drugs.

“Beneficial” microbes such as pro- and probiotics are either administered directly or their growth is therapeutically promoted, with the goal of overpowering or neutralizing pathogens. The second category includes the reversal of dysbiosis, a common condition after antibiotic interventions, as this condition can have long-term and potentially serious effects on the health and immunity of patients, making probiotic supplements a standard prescription during or after courses of antibiotics.

The latter category includes the use of natural or genetically modified microbial metabolites as antibiotics. Penicillin, the first known antibiotic, belongs to this category.

Not all patients respond to these interventions, and therefore identifying patients who would benefit most from such approaches is essential. In this context, personalized microbiome fingerprinting could be harnessed as an effective ‘companion diagnostic’ method to tailor treatment to the individual.”

So why aren’t more doctors using it?

While the benefits of microbiome analyzes in the diagnosis and treatment of disease are numerous, the field remains in its infancy. Few studies have validated the safety of these interventions in humans.

Ironically, one of the main advantages of gut microbial interventions – the “personalized” aspects of treatment – ​​is one of its greatest challenges. Variations between individuals result in inconsistency in data within a study and even lower reproducibility between studies, thus preventing medical governing bodies from prescribing their use.

Another drawback of current research is that innovation increases costs. Most gut microbiota studies use next-generation sequencing techniques, which require expertise and incur costs far removed from 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 move from the realm of science to mainstream medicine.