Psychobiome: From Experimental Hypothesis to Precision Medicine in Mental Health

1. Introduction

In view of the challenges currently shaping the roadmap that links the microbiome with mental health, it is imperative to endow the concept of the psychobiome with greater robustness and precision. No longer merely a “repository” of microbes that influence the brain, the psychobiome should be reconceptualised as a complete, malleable, and measurable biological infrastructure that underpins mental health in both basic research and contemporary clinical practice. In this regard, Science emphasises that gut microorganismswhose gene repertoire far surpasses that of humanscan synthesise neurotransmitters, modulate immune pathways, and even inspire the development of novel drugs for depression, insomnia, and visceral pain (Pennisi, 2020).

From this perspective, the term psychobiome can be understood as a chemical bridge that links the gut environment to the brain circuits responsible for emotion, thinking, and behavior. In this sense, the psychobiome is best described as a dynamic, two way communication system made up of gut microorganisms such as bacteria, archaea, fungi, and viruses along with the wide range of metabolites, neuropeptides, and immune-related molecules they produce locally. This complex ecosystem is in constant interaction with intestinal lining cells, the gut’s immune system, and the neuroendocrine net- work, creating both direct communication channels (like the vagus nerve) and indirect ones (such as systemic inflammation control) that influence how the brain functions (Pennisi, 2020).

2. Psychobiome and Recent Advances in GutBrain Axis Research

Over the past two decades, progress in psychobiome research has paralleled the evolution of the psychobiotic concept coined at University College Cork by John F. Cryan and Ted Dinan which has matured from a bold hypothesis into an experimental programme reshaping both psychiatry and psychopathology (Cryan et al., 2019). Equally influential are the convergent lines of inquiry led by Sarkis K. Mazmanian at Caltech and Christopher A. Lowry at the University of Colorado Boulder, whose work has consolidated the view that intestinal microbes and their metabolites modulate brain function and behavior in both animal models and humans (Needham et al., 2022; Winder et al., 2024).

Currently, three main mechanisms are at the center of research in this field: (i) neurotransmitters produced by gut microbes, (ii) short chain fatty acids (SCFAs) that influence gene expression, and (iii) phenolic compounds like 4 methylphenyl sulfate (4EPS), which, when elevated, have been shown to trigger anxiety like behaviors and interfere with brain myelination (Needham et al., 2022). These discoveries align with previous findings that point to the microbiota’s role in regulating the permeability of the blood brain barrier and activating microglial cells in models of neurodegeneration (Morais et al., 2024).

An increasing number of studies highlight the potential of precision psychobiotics in treating anxiety and depression. A recent systematic review found that formulations containing Bifidobacterium significantly reduced symptoms of depression (Huang & Liu, 2024). Within this group, the strain Bifidobacterium breve CCFM1025 has stood out: in a randomized clinical trial, it eased symptoms of major depression and helped restore normal tryptophan metabolism (Tian et al., 2022). On the prebiotic side, a double blind, randomized, placebo controlled study involving 64 young women with high levels of anxiety found that galacto oligosaccharides (GOS) not only had a calming effect but also boosted the presence of Bifidobacterium in the gut (Johnstone et al., 2023).

While psychobiotics are often described as broad spectrum regulators of inflammation, this claim has also been directly investigated. Researchers from University College Cork and KU Leuven found that depressive states tend to be associated with lower microbial diversity and richness, alongside elevated levels of inflammatory mark- ers such as interleukin 6, interleukin 8, TNF α, and Creactive protein (Kelly et al., 2016; Valles-Colomer et al., 2019). In addition, certain bacterial groups like Eggerthella, Sellimonas, Lachnoclostridium, and Hungatella show a strong correlation with the severity of depression and anxiety symptoms (Valles-Colomer et al., 2019).

Clinical trials involving patients with major depressive disorder have shown that taking a multistrain probiotic containing Lactobacillus acidophilus, L. casei, and Bifidobacterium bifidum for eight weeks can lead to significant improvements in depression symptoms. Similarly, taking Lactobacillus rhamnosus HN001 during the perinatal period has been associated with lower levels of postpartum depression and anxiety (Mosquera et al., 2024). While animal studies consistently show that these psychobiotics can reduce anxiety like behaviors, findings from human trials, though encouraging, are still mixed. This underscores the importance of pinpointing the specific strains and biological mechanisms that make psychobiotics effective (Mosquera et al., 2024).

3. Psychobiome in Precision Research: Genetics and Psychometrics

Given that results in this field can sometimes be inconsistent or hard to replicate, there are two experimental strategies that could significantly improve the accuracy and reliability of future studies: (i) the use of ancestry informative markers (AIMs) to better account for genetic differences across populations, and (ii) the thorough validation of clinical rating scales within the specific groups being studied.

3.1 The Role of Ancestry Informative Markers (AIMs)

To move from simply identifying correlations to making stronger causal claims, psychobiotic research needs to include a thorough analysis of population genetic structure. This involves using panels of ancestry informative markers (AIMs) specific DNA variants that differ significantly across global populations to determine each participant’s biogeographical ancestry. The idea behind this approach is that the makeup of the gut microbiome often reflects a population’s genetic background. If this genetic admixture isn’t properly accounted for, researchers might mistakenly attribute certain effects to the microbiome that are actually due to shared genetic traits or historical influences like diet, antibiotic use, or lifestyle.

A compelling example comes from the work of Winston Rojas, Gabriel Bedoya, and colleagues with genetically diverse Colombian populations. By genotyping 40 ancestry informative markers (AIMs), they were able to separate the effects of gut microbiota from those tied to the population’s European Indigenous African genetic mix, helping to avoid misleading conclusions about cardiometabolic health (Guzmán-Castañeda et al., 2019).

Another case highlighting the interplay between genes and microbes involves the ABO, FUT 2, and LCT genes, which influence the composition of gut mucosal sugars. These, in turn, affect which bacteria are able to colonize the gut and what metabolites they produce. A meta-analysis of over 9000 people found that a strain of Faecalibacterium prausnitzii capable of metabolizing Nacetyl galactosamine was more common in individuals with blood group A an association that held true even in African populations. This underscores the importance of adjusting for AIMs when exploring functional genemi- crobiota relationships (Zhernakova et al., 2016).

Despite this, most psychobiotic trials to date have been conducted in individuals of European ancestry (Bosch et al., 2022). However, the gut microbiome linked to depressive symptoms shows both universal and ethnicity specific patterns. In one study of six urban ethnic groups, up to 29% of the variation in depression symptoms was explained by differences in bacterial β diversity (Bosch et al., 2022). Including AIMs early in study design can therefore improve the generalizability of results and reduce the risk of false positives across interventions like probiotics, prebiotics, or even fecal microbiota transplants.

In the context of personalized therapies, how well a particular psychobiotic strain or combination works often depends on the individual’s existing gut microbiome, which itself is shaped by ancestry and diet. AIMs can help tailor treatments for example, by identifying ancestral groups likely to benefit from butyrate producing bacteria, or by selecting prebiotics that target metabolic pathways underrepresented in certain populations thus supporting a more precise psychobiome approach.

AIMs are also essential for understanding how genes, gut microbes, and medications interact. Genetic variants like those in SLC6A4 (involved in serotonin transport) or CY P 2C19 (affecting antidepressant metabolism) vary across populations. Identifying these variants with AIMs allows researchers to better model how the micro- biome might influence drug effectiveness and metabolism, paving the way for more effective combination therapies. By integrating AIM data with multiomic analyses both fecal and systemic researchers can improve ma- chine learning models, avoid overfitting tied to ancestry, and uncover microbial patterns that genuinely predict conditions like anxiety, autism spectrum disorder, or cognitive decline. This could lead to more accurate biomarkers for diagnosis, treatment, and prognosis.

In summary, ancestry informative markers (AIMs) are essential for moving beyond associations toward true causal understanding. They help ensure that findings are reproducible across diverse populations and support the development of psychobiotic interventions that are not only effective and equitable but also respectful of both human and microbial diversity.

3.2 The Importance of Validating Clinical Scales

A second key pillar of precision psychobiome research is the rigorous validation of measurement tools. Three elements are especially important for future personalized medicine applications:

• Cultural adaptation and conceptual equivalence. Before using any clinical scale, researchers must ensure that each item carries the same psychological meaning in the population being studied. This involves a thorough process of forward and backward translation, cognitive interviews, and cultural refinement to avoid semantic or cultural bias. In psychobiome research, where eating habits and beliefs about mental health vary across cultures and influence the microbiome using tools that don’t accurately reflect local experiences may lead to misleading associations between microbes and mental health symptoms.

• Strong psychometric properties and sensitivity to change. Effective assessment tools must show high internal consistency (α > .80) and good testretest reliability. They should also demonstrate convergent and discriminant validity, ensuring that they actually measure what they intend to rather than, say, somatization. Just as crucial is responsiveness, or the ability to detect even small clinical changes. This is particularly relevant in psychobiotic trials, where treatment effects are often modest.

• Factorial invariance, population specific norms. Establishing configural, metric, and scalar invariance ensures that the underlying structure of a scale is comparable across subgroups based on sex, age, or ancestry. Local norms and appropriate cut off scores allow for more accurate classification of clinical cases. In the con- text of psychobiome studies, this kind of measurement consistency enables meaningful comparisons across di- verse populations and supports more precise identification of treatment responders and non responders ultimately strengthening the link between clinical outcomes and microbial profiles.

4. Future Directions for Psychobiome Research

Moving forward, identifying bacterial strains with highly specific effect sand running long term studies to explore their lasting impact, optimal dosing, and appropriate treatment durations remains a top priority (Mosquera et al., 2024). The gut microbiota is inherently complex and constantly shifting, and high variability between individuals adds another layer of difficulty when interpreting results. Because of this, improving population stratification based on ancestry will be crucial for making future findings more accurate and meaningful.

Adopting a truly multilayered, multitopic approach is equally important. This means going beyond simply identifying which microbes are present and incorporating functional data like the metabolome, secretome, and virome. The core insight here is that what microbes do in real time can be just as important as which ones are there. The psychobiome can be thought of as a signaling hub where the nervous, immune, endocrine, and metabolic systems converge. It involves a wide range of molecules from short chain fatty acids and tryptophan derivatives to cytokines and hormones that together influence inflammation in the brain, neural plasticity, and neurotransmitter production.

Importantly, the psychobiome is not static it shows what researchers call “ecoclinical plasticity”. It’s shaped by diet, medications, plant compounds like polyphenols, and even psychosocial stress. All of these factors can reprogram the molecular behavior of gut microbes and, in turn, influence brain function and mental health over time.

In summary, psychobiome research is moving toward a flexible therapeutic framework that combines probiotics, prebiotics, and other interventions to restore disrupted signaling pathways involved in depression, anxiety, and neurodegeneration. At its core, the psychobiome reflects a deep evolutionary partnership between brain and gut microbes: human behavior influences microbial ecosystems, which then feedback to shape mental states a dynamic biocultural feedback loop. As this field continues to grow, it has the potential to uncover the roots of psychological vulnerability and transform how we approach the treatment of psychiatric disorders on a broad scale.