The food we eat, the water we drink, the air we breathe, not to mention our living and working environment... To what extent do the factors we’re exposed to from cradle to grave play a role in the relentless advance of chronic disease? This question poses a real challenge for the scientific community. 

While scientists have been working for many years to measure the impact on health of each of these factors, we still know very little about the physiological harm they cause when combined and accumulated over the years.

Some act synergistically (cocktail effect), while others offset each other. Furthermore, their impact differs according to the stage of life when one is exposed to them and on the duration of exposure¹. 

Exposome: a global approach to health

Urbanization, stress, climate change, modern diet, toxic products... In 2005, driven by the need to better understand the often complex exposure to these multiple environmental factors, British epidemiologist Christopher P. Wild (current director of the International Agency for Research on Cancer – IARC) proposed the concept of “exposome”. Wild defines the exposome as “the sum of all exposures a person experiences from conception to death.” 

He sees the exposome as“a complex and dynamic representation of the exposures we experience during our lifetime that integrates chemical, microbiological, physical, recreational, medicinal, lifestyle and dietary environments, as well as infections.”²  

Breathing, washing, dressing, eating, working, and sleeping are not so trivial after all. They expose us to sources of micro-particles, chemicals, pollutants, heavy metals, stress, noise, radiation... all potentially harmful to our bodies and microbiota.

A better understanding of the exposome, i.e. the exposures we experience during our lifetime, is therefore crucial to reducing the risk of disease and making good habits part of our daily lives. But what about the microbiota? 

Microbiota and exposome: a dialog at the core of our health 

What if our health depended on the dialogue between our environment and the billions of micro-organisms that inhabit our bodies? Pollutants, food, stress, nature... the exposome constantly interacts with our microbiota and can influence their fragile balance. A little-known but central link, particularly in the prevention of chronic diseases. The impact of nature on our microbiota, and that of urbanization, bear witness to this.

Discover how this silent exchange shapes our health.

Microbiota under pressure: how the exposome promotes chronic disease

Our environment has a profound influence on our health... by affecting our microbiota. Endocrine disruptors, microplastics, drugs, ultra-processed foods: these are all components of the exposome that weaken our intestinal ecosystem and promote chronic disease. Science is now revealing how these disturbances can lead to obesity, depression, IBD and allergies. Examples include the fungal exposome and bacterial resistance.

Explore the links between environment, dysbiosis and modern diseases

From birth to death, an exposome with different consequences on our health

Our sensitivity to the environment evolves with age. From pregnancy onwards, the exposome modulates immunity, shapes the infant's microbiota and influences his or her future risk of asthma or allergy. In adolescence, it impacts mental and skin health. In adulthood, it determines inflammation and overall well-being. In senior citizens, it can preserve or alter longevity, as shown by the study on the microbiota of centenarians.

Discover how each stage of life interacts with the exposome.

Towards a more favorable exposome 

We may not have everything under control, but we can do something about it! A beneficial exposome is possible: a fiber-rich diet, physical activity, living in contact with nature, gentle hygiene, reducing disruptors... all simple levers to protect our microbiota and prevent disease. The Mediterranean diet and a rich microbial environment are living proof of this.

Discover concrete ways to cultivate a healthy environment.

Microbiota are the sentinels of our environment. Living interfaces between our bodies and the outside world, microbiota are a faithful reflection of our environment. Understanding the exposome means identifying the levers we need to live better, age better and prevent the diseases of tomorrow. The exposomic approach sheds new light on our relationship with public health, ecology and everyday behavior.

The vaginal microbiome is crucial to gynecological health. But with one main difference: unlike many other microbiomes, where healthy means diverse, the “gold standard” for a healthy vaginal flora is (at present) an ample predominance of Lactobacilli. 

However, in an opinion article on vaginal health, a group of international experts have pointed out the limitations of the current five CST (sidenote: Five community state types (CST) - CST I dominated by Lactobacillus crispatus, 
- CST II dominated by L. gasseri,
- CST III dominated by L. iners 
- CST V dominated by L. jensenii
- and the more diverse CST IV, which is not dominated by Lactobacillus but by a group of anaerobic bacteria, including Gardnerella, Atopobium, Prevotella, and Finegoldia. 
  ) classification: it does not reflect the full biology and functionality of the vaginal microbiome. The authors cite the Belgian Isala study, where 10.4% of participants displayed a co-dominance of L. crispatus (CST I) and L. iners (CST III), suggesting that CSTs may co-exist in some women. Another limitation is that the role of fungi, eukaryotes, archaea, and viruses remains largely unexplored.

Data mainly from wealthy countries

To illustrate their point, the authors considered bacterial vaginosis. This condition is diagnosed using the Nugent score (sidenote: Nugent score A diagnostic scoring system used to assess bacterial vaginosis based on the presence and proportions of certain bacteria in a Gram-stained vaginal sample. ) or the Amsel criteria (sidenote: Amsel criteria The Amsel criteria might provide a more clinical diagnosis of BV because they are based on the following four signs: vaginal fluid pH above 4.5, positive whiff test (foul odor after adding 10% potassium hydroxide – KOH), presence of clue cells, and abnormal vaginal discharge. At least three of these signs must be present before BV is diagnosed. ) , but these systems suffer from biases, particularly geographical biases.

Is the lower presence of Lactobacilli and higher frequency of vaginosis in black and Latin American women (vs. women of Asian or European origin) in the United States real or simply due to methodological limitations? Could socioeconomic inequalities between populations explain some of the differences? What about different behaviors, such as douching, a noted risk factor for vaginal dysbiosis? What about the many American women classified as African American even though (more than) half of their ancestors were white Europeans?

Ultimately, what do we really know about the make-up of a “healthy” and balanced vaginal microbiota in women with distinct geographical and ethnic origins?

Projects on every continent

The authors highlight the lack of studies in low- and middle-income countries, despite a growing number of initiatives attempting to fill this gap:

• The Vaginal Human Microbiome Project (VaHMP) maps data on the vaginal flora of women from different ethnic backgrounds in the United States;
• The VIRGO database supplements the US data with data from six countries on different continents;
• The Vaginal Microbial Genome Collection (VMGC) contains data from 14 countries; 
• The Vaginal Microbiome Research Consortium has a specific section for Africa and Bangladesh.

Another approach is citizen science (public contribution to vaginal microbiome research around the world using a bottom-up, local approach), such as the authors’ Isala project on vaginal flora. Following its success in Belgium (more than 6,000 applications for 200 women sought), the initiative has been extended to a global network of partners on different continents (the Americas, Africa, Asia, and Europe), promoting collaboration between teams.

The authors consider all these initiatives necessary for a more complete understanding of a “healthy” vaginal microbiome. 

These advances may also help us to better understand the conditions that promote a balanced vaginal microbiota, in particular by further investigating the protective role of certain species, such as Lactobacillus crispatus, and by rigorously evaluating the benefits of probiotics in this equation.

Sodas and other sugary drinks are a major target of public health policies. The harmful effects associated with consuming too many of them include diabetes (sidenote: Diabetes mellitus Chronic disease that occurs either when the pancreas does not produce enough insulin or when the body cannot effectively use the insulin it produces. Over time, diabetes can damage blood vessels in the heart, eyes, kidneys and nerves. ) , more specifically type 2 diabetes. How does this happen? Undoubtedly through weight gain, insulin resistance (sidenote: Insulin-resistance An altered response of cells to the action of insulin (a hormone that helps the body use sugar for energy), insulin resistance results in poor regulation of blood sugar levels. Sources
Inserm. La résistance à l’insuline, une histoire de communication. 2018. 
Centers for disease control and prevention. Diabetes - Resources and Publications -Glossary  ) , inflammation and dyslipidemia. But research carried out on Hispanic and Latino Americans shows that our gut microbiota also plays a role.

More sodas, more bad bacteria

A weakness for sugary drinks (especially if you drink more than 2 glasses a day) has serious consequences for the gut microbiota. In fact, regular consumption of these drinks appears to reduce the number of various bacteria that are considered beneficial because they produce short-chain fatty acids (sidenote: Short chain fatty acids (SCFA) Short chain fatty acids (SCFA) are a source of energy (fuel) for an individual’s cells. They interact with the immune system and are involved in communication between the intestine and the brain. Silva YP, Bernardi A, Frozza RL. The Role of Short-Chain Fatty Acids From Gut Microbiota in Gut-Brain Communication. Front Endocrinol (Lausanne). 2020;11:25. ) (SCFAs), which are known for their protective effects.

For example, Bacteroides pectinophilus, which feeds on pectin but doesn't know what to do with the sugars found in sodas, declines when soda is consumed. However, this isn’t true of all bacteria: those that like to feed on fructose and glucose (two sugars found in high amounts in sugary drinks) multiply like wildfire.

Diabetes-linked bacterial metabolites 

As a direct consequence of this bacterial disturbance, our microbiota changes, so it no longer produces the same metabolites (sidenote: Metabolites Small molecules produced during cellular or bacterial metabolism. For example, short-chain fatty acids are metabolites produced by intestinal microbiota during fermentation of non-digestible complex carbohydrates (fibers, etc.). Silva YP, Bernardi A, Frozza RL. The Role of Short-Chain Fatty Acids From Gut Microbiota in Gut-Brain Communication. Front Endocrinol (Lausanne). 2020;11:25.  Lamichhane S, Sen P, Dickens AM, et al An overview of metabolomics data analysis: current tools and future perspectives. Comprehensive analytical chemistry. 2018 ; 82: 387-413 ) and it impacts our health differently. With sodas, we're no longer getting the good SCFAs that are so beneficial for our bodies! Instead, the molecules produced by the intestinal flora of people who drink a lot of sugary drinks are linked to blood sugar issues and the risk of diabetes. And the more sodas and sugary drinks you consume, the greater the presence of these harmful molecules in your blood, leading to an increased risk of diabetes.

Note: being overweight could play a role in this phenomenon, as extra pounds seem to be part of the link between sugary drinks, metabolites and diabetes.

It’s time to cut down on sodas

These findings suggest that the gut microbiota and bacterial metabolites may play a role in the link between drinking sugary drinks and an increased risk of diabetes. Of course, further studies on other populations are still needed to better understand this link. But in the meantime, this study should be seen as yet another reason to drink less sodas! Instead, how about a glass of horchata, which boosts good bacteria?

Intratumoral dynamics in colon cancer are complex, with microbiota, fatty acid metabolism (FAM) (sidenote: Fatty Acid Metabolism (FAM) The cellular process involved in breaking down and synthesizing fats, influencing tumor growth and progression. ) , and the tumour microenvironment (TME) (sidenote: Tumor Microenvironment (TME) The surrounding environment of a tumor, including immune cells, blood vessels, and signaling molecules that impact cancer development. ) all playing a role. A recent study ¹ delved into this "unresolved trinity" in colon adenocarcinoma (COAD) (sidenote: Colon Adenocarcinoma (COAD) A type of colon cancer originating in the glandular cells of the colon. ) . By leveraging a substantial cohort of patient data from The Cancer Genome Atlas (TCGA) and employing sophisticated bioinformatic and pathological image analysis techniques, the researchers aimed to uncover novel diagnostic and therapeutic avenues for this aggressive cancer.

Microbial-metabolic connections

The research team initiated their investigation by analysing comprehensive data from 420 patients diagnosed with COAD. A key methodological step involved categorising these patients into two distinct subgroups:

• those exhibiting high fatty acid metabolism (FAM_high)
• and those with low fatty acid metabolism (FAM_low).

This stratification based on the Gene Set Variation Analysis (GSVA) (sidenote: Gene Set Variation Analysis (GSVA) A computational method used to evaluate the activity of specific gene pathways in patient samples, aiding in diagnostic subtyping. ) score calculated for FAM pathway genes.

Surprisingly, despite the overall microbial alpha diversity (a measure of within-sample diversity) appearing similar between the two groups, deeper analysis of the microbial beta diversity (a measure of between-sample diversity) revealed remarkably distinct bacterial compositions strongly linked to these underlying metabolic profiles.

The researchers observed that patients whose tumors exhibited a low FAM signature (FAM_low group) experienced significantly better overall survival (OS) compared to their FAM_high counterparts. The identification of four specific genes (ADIPOR2, HAO2, ALAD, HPGD) whose expression levels were significantly correlated with patient survival, solidifying the critical prognostic role of FAM in COAD.

Metabolic signatures as predictive tools

Beyond diagnosis and prognosis, the study's comprehensive drug sensitivity analysis illuminated substantial and potentially clinically actionable differences in how the two FAM-defined subtypes responded to a broad spectrum of therapeutic agents.

By calculating the IC50 values (the concentration of a drug required to inhibit 50% of cells) for an extensive panel of 195 candidate drugs, the researchers uncovered that the FAM_high and FAM_low groups exhibited significantly different sensitivities to a remarkable 120 of these compounds. For example, the high FAM group showed less sensitivity to drugs like JQ1, suggesting these agents might be less effective in this metabolic context. Such insights could support more personalized cancer treatment strategies.

When it comes to nutrition, fruit and vegetable juices provide a vitamin, mineral, and antioxidant boost. However, according to a clinical trial published in the journal Nutrients, “detox juice cleanses” may not be the best option when it comes to the recommended “five portions of fruit and vegetables a day”. ¹

Students on a diet

The authors put 14 students on three different diets for three days:

• five followed a diet consisting exclusively of cold-pressed fruit and vegetable juices (800 to 900 kcal per day, i.e. about 10 glasses); 
• four followed a “normal” diet accompanied by fruit and vegetable juices; while
• five followed a low-calorie diet rich in “whole” plant foods containing fiber (800 to 900 kcal).

Before starting their respective diets, in order to assess the influence of different foods on microbial composition, all participants followed a three-day “elimination diet” consisting of organic fruit, vegetables, whole grains, and eggs, with very little or no red meat, dairy products, processed foods, gluten, alcohol, coffee, or sugar.

To analyze how the different diets impacted the microorganisms in the volunteers’ gut, oral, and salivary microbiota, the researchers collected samples from their stool, saliva, and from the inside of their cheeks before the experiment, between the two diets, and afterwards.

Increased risk of periodontitis and tooth decay

They found that fruit and vegetable juices, whether consumed alone or with food, significantly alter the oral microbiota by increasing pro-inflammatory bacteria, even if these changes are temporary.

The researchers noted a reduction in Veillonellaceae, a bacterium capable of converting salivary nitrates into nitrites. However, fewer nitrites means less effective inhibition of the bacteria responsible for periodontitis and an increased risk of tooth decay.

For the gut microbiota, the impact of juices was less pronounced, but the researchers noted an increase in bacteria associated with inflammation, intestinal permeability, and cognitive decline.

Too much sugar, too little fiber

According to the authors, juices are higher in sugar and carbohydrates, and lower in fiber than whole fruits and vegetables, which adversely impacts both the oral and gut microbial flora.

The elimination diet had the most positive impact on the gut microbiota: by providing more fiber, it promoted the growth of bacteria that produce highly beneficial short-chain fatty acids (sidenote: Short chain fatty acids (SCFA) Short chain fatty acids (SCFA) are a source of energy (fuel) for an individual’s cells. They interact with the immune system and are involved in communication between the intestine and the brain. Silva YP, Bernardi A, Frozza RL. The Role of Short-Chain Fatty Acids From Gut Microbiota in Gut-Brain Communication. Front Endocrinol (Lausanne). 2020;11:25. ) (SCFAs) such as butyrate. 

While the scope of this study is limited by its small size and short duration, it confirms that the priority for microbiota health should be the consumption of whole fruits and vegetables in order to fully benefit from their fiber.

For decades, the conversation around Chlamydia trachomatis, the most common bacterial sexually transmitted infection globally, has revolved around sexual behavior: number of partners, condom use, prior STI history.

But a groundbreaking new study published in Cell  ¹ invites us to reframe that narrative. Instead of focusing solely on behavior, we’re asked to consider a more intimate and microscopic protagonist: the cervicovaginal microbiome (CVM).

In a longitudinal study, researchers tracked 560 Black and Hispanic adolescent and young adult (AYA) women in New York City, communities disproportionately impacted by Chlamydia infections.

They followed participants before, during, and after an incident Chlamydia infection. But rather than just charting symptoms or behaviors, they analyzed the entire microbial community of the cervicovaginal tract using high-resolution 16S rRNA and ITS1 gene sequencing.

The result? A nuanced and highly predictive microbial fingerprint for Chlamydia risk, reinfection, and even possible complications like pelvic inflammatory disease (PID) and miscarriage.

mBV-A and CST-IV-A: microbial fingerprints of risk

The team used a powerful molecular algorithm (molBV) to quantify bacterial vaginosis (BV)-like states, then categorized microbial communities into “Community State Types” (CSTs).

Among these, CST-IV-A, dominated by Candidatus Lachnocurva vaginae, emerged as the microbial signature most strongly associated with incident Chlamydia infection.

When CST-IV-A overlapped with a high molBV score, a state dubbed mBV-A, the risk of acquiring Chlamydia skyrocketed. Women with this mBV-A profile had more than double the risk of infection compared to those with a Lactobacillus-dominant microbiome (e.g., L. crispatus).

Even more striking? This elevated risk existed months before infection, revealing mBV-A not as a result of Chlamydia, but as a harbinger. This microbial landscape, characterized by high diversity and a drop in protective Lactobacilli, undermines the vaginal environment's natural defenses. It’s not just about pH or lactic acid. 
 

Candidatus Lachnocurva vaginae (sidenote: Candidatus Lachnocurva vaginae A bacterium commonly found in women with bacterial vaginosis and strongly associated with CST-IV-A. It is not yet cultivable in the lab ("Candidatus" denotes this) but has been implicated in increased susceptibility to sexually transmitted infections like Chlamydia. ) , the star of CST-IV-A, may metabolize D-lactate, a compound with antimicrobial properties, potentially weakening the cervicovaginal defense against pathogens like Chlamydia.
And it doesn’t stop there. The researchers identified a network of 10 bacterial genera, including Prevotella, Megasphaera, and Clostridium, tightly linked and predictive of infection. These weren’t isolated villains; they were a microbial clique.

Their collective presence formed a Microbial Risk Score (sidenote: Microbial Risk Score (MRS) A composite score representing the cumulative risk posed by a group of specific microbial taxa associated with disease. In this study, it predicts Chlamydia risk based on the presence and abundance of 10 interrelated bacterial genera. ) (MRS), essentially a microbial polygraph test, that outperformed any single genus in predicting Chlamydia acquisition.

Reinfection, recovery, and the microbial set point

Even after treatment, the microbiome tells a story. Most women treated for Chlamydia saw their microbiome shift back toward its pre-infection state. But among those who carried the mBV-A profile post-treatment, the risk of reinfection tripled.

One in five previously infected women experienced reinfection, compared to just 4% of controls. The CVM, in a sense, carried a microbial “memory” of susceptibility, one that wasn't erased by antibiotics.

This points to a deeper truth: treatment of the pathogen does not equal treatment of the terrain. Even more provocatively, the researchers found that some women developed the high-risk mBV-A profile after antibiotic treatment, raising questions about how treatment regimens may unintentionally reshape the microbiome in ways that increase future vulnerability.

There were also early signs, though limited by small sample size, that this microbial fingerprint may be associated with complications like PID and miscarriage. 

While food additives (sidenote: Food additives Food additives are substances primarily added to processed foods, or other foods produced on an industrial scale, for technical purposes, e.g. to improve safety, increase the amount of time a food can be stored, or modify sensory properties of food.  Source: World Health Organization )  improve the texture and shelf life of many foods, they also raise health concerns. Some are suspected of promoting chronic inflammatory diseases by acting directly on our gut microbiota.

Nevertheless, the effects vary widely from one individual to another, according to a previous randomized controlled trial in humans (FRESH study: acronym for Functional Research on Emulsifiers in Humans). The additive used: carboxymethylcellulose (sidenote: Sodium carboxymethyl cellulose Sodium carboxymethyl cellulose (or cellulose gum, E466) is a food additive with multiple functional properties: firming agent, coating agent, bulking agent, emulsifier, thickener, gelling agent, humectant, stabilizer, etc. Its use is authorized in a wide range of products from dairy products (creams, fresh or processed cheese, dairy desserts, etc.) to cooked fish, from ice creams to dried or canned vegetables, from confectionery to breakfast cereals, from certain meats or fish to mustards and soups, from appetizers to beer or certain spirits, and so on. Source: Food and Agriculture Organization of the United Nations   ) (or E466).

How can this sensitivity be explained or even predicted? The team ¹ has continued its previous work by focusing on the microbiota. Their in vitro demonstration used a mini laboratory reactor capable of mimicking the human gut microbiota.

The reactor predicts sensitivity or resistance

When the researchers exposed the microbiota collected from the FRESH study volunteers to carboxymethylcellulose in the bioreactor, they found the same difference in sensitivity as observed in vivo in the FRESH trial: the microbiota of the same 2 of the 7 volunteers exposed to E466 were disturbed when exposed to the emulsifier.

In other words, the microreactor faithfully reproduces the variations between individuals observed in the FRESH trial, making it possible to predict whether a given microbiota is sensitive to E466, without the need for in vivo studies..

Transplanted flora transmit sensitivity to mice

To confirm that this intestinal flora was responsible for the intestinal inflammation observed in some FRESH trial subjects exposed to E466, the microbiota of 2 E466-"sensitive" individuals and 2 non-sensitive individuals were transplanted into flora-free mice.

Only mice given the "sensitive" flora and exposed to the additive developed intestinal inflammation and severe colitis:

• shortening of the colon
• damage to the mucosa
• macrophage infiltration 

Certain bacteria, including Adlercreutzia equolifaciens and Frisingicoccus caecimuris, were associated with this inflammation.

Emulsifiers, texturizers, preservatives, colorants: food additives (sidenote: Food additives Food additives are substances primarily added to processed foods, or other foods produced on an industrial scale, for technical purposes, e.g. to improve safety, increase the amount of time a food can be stored, or modify sensory properties of food.  Source: World Health Organization )  which are very common in ultra-processed products, have invaded our cupboards. These include E466, or carboxymethylcellulose (sidenote: Sodium carboxymethyl cellulose Sodium carboxymethyl cellulose (or cellulose gum, E466) is a food additive with multiple functional properties: firming agent, coating agent, bulking agent, emulsifier, thickener, gelling agent, humectant, stabilizer, etc. Its use is authorized in a wide range of products from dairy products (creams, fresh or processed cheese, dairy desserts, etc.) to cooked fish, from ice creams to dried or canned vegetables, from confectionery to breakfast cereals, from certain meats or fish to mustards and soups, from appetizers to beer or certain spirits, and so on. Source: Food and Agriculture Organization of the United Nations   ) , which is used in industrial ice creams and buns. The problem: several studies have alerted us to its potentially harmful effect on our intestinal and metabolic health.

A recent study ¹ also points out that the composition of our microbiota could be altered by repeated consumption of this type of emulsifier. In a clinical trial previously carried out on healthy volunteers (7 consuming E466, and 9 controls not consuming it, for comparison), researchers had shown that people’s responses to this additive differ: some people are sensitive, and their gut microbiota is disrupted, while others are resistant and their flora remains unaffected.

This difference is explained by the microbial composition in our gut, according to the latest studies by the same researchers. In other words, your flora predicts whether you're one of the lucky ones who digest fluffy industrial buns without a care in the world or one of those people who react badly to E466!

The gut microbiota predicts... and transmits!

To understand these differences, the researchers used a mini laboratory reactor capable of mimicking the human microbiota and testing the effect of E466 on different microbiota in vitro, in this case using the stools of the 7 volunteers from the previous study. And the experiment was a success! Only the stools of the sensitive patients hyper-reacted to the food emulsifier E466, making it possible to identify sensitive patients. This new approach could eventually allow us to predict the microbiota's response to certain emulsifiers.

What's more, sensitivity to the effects of E466 has been shown to be transmissible to mice, via fecal microbiota transplants. Flora from volunteers who are sensitive to E466 cause severe colitis in animals who consume the emulsifier, illustrating possible direct health consequences. These results also show the extent to which the bacteria in our microbiota can play an active role in the inflammatory response to certain additives.

A signature requiring refinement

It remained to be seen whether analyzing the DNA of the stool bacteria cocktail alone would be sufficient to predict sensitivity to E466. The researchers trained an algorithm to identify differences between the stool DNA of sensitive and non-sensitive volunteers. Results: 78 markers were counted. These bacterial markers, present in the microbiota of certain individuals, could predict sensitivity to emulsifiers. But this signature is not yet perfect: it worked in the clinical trial cohort, but its application to subjects from other studies has not yielded the expected results. Further studies are needed to validate this signature in wider populations.

While we wait for a universal signature that could facilitate screening, and thus avoid intestinal disorders in sensitive individuals, perhaps it's time to start cooking from scratch at home, especially since additives may also contribute to behavioral disorders. Not to mention microplastics in takeaway food packaging. We can't stress this enough: our diet is our primary medicine, and more sensible consumption, with unprocessed products, would also limit exposure to emulsifiers.

In recent years, the idea of using gut microbiota as a diagnostic tool has captured the imagination of the medical community. Yet, despite mounting interest, the clinical benefits of microbiome testing remain largely unproven.

A newly released international consensus report ¹ has now thrown light on this pressing issue. Spearheaded by 69 experts hailing from 18 countries, the initiative set out to build a clear, evidence‐based framework to guide clinicians and laboratories in adopting standardized microbiome testing practices.

The right panel

The panel, comprising clinicians, microbiologists, microbial ecologists, computational biologists, and bioinformaticians, embraced the Delphi method (sidenote: Delphi method A structured process for achieving expert consensus through multiple rounds of anonymous surveys and feedback. ) to forge a set of recommendations. Working in five dedicated groups, the experts tackled general principles, pre-test procedures, microbiome analysis, reporting standards, and clinical relevance. Each statement underwent rigorous scrutiny and was rated on a Likert scale, with an 80% agreement threshold ensuring only robust recommendations made the final cut.

The consensus: what you need to know

The below are four recommendations are a MUST for every clinician interested into using the microbiome in their clinical practice. 

• Ditch Direct-to-Consumer: The consensus strongly discourages patients self-requesting microbiome tests. Testing should ideally be initiated by a physician or licensed healthcare professional with a clear clinical rationale. This highlight concerns over misinterpretation and inappropriate interventions.
• Beyond F/B Ratio: Forget the Firmicutes/Bacteroidetes ratio (sidenote: Firmicutes/Bacteroidetes ratio A once-popular but now-questioned measure comparing two major bacterial phyla in the gut, often linked (incorrectly) to health or disease. ) ; experts advise against its reporting due to insufficient evidence. Similarly, routine dysbiosis indices lack validation. Focus should be on comprehensive taxonomic profiling (sidenote: Taxonomic profiling Analyzing a microbial community by identifying and categorizing its members at various taxonomic levels, such as genus or species. ) using 16S rRNA or whole-metagenome sequencing.
• Clinical Context is King: Reports must include detailed clinical metadata (sidenote: Clinical metadata Essential patient details (e.g., age, diet, medications) that accompany a test sample and help interpret microbiome data in a medical context. ) (age, BMI, diet, medications) to aid interpretation. Comparisons to matched healthy controls are crucial. Surprisingly, testing providers should not offer post-test therapeutic advice; this remains the remit of the referring clinician.
• Quality and Transparency: High-quality, accredited labs using validated software are essential. Detailed reporting of the entire testing protocol, from sample collection to analysis, ensures transparency.