The relationship between host-associated microbiomes and human health and disease has been the focus of increasing attention over the past decade. Microbiomes are made up of communities of microorganisms such as bacteria, viruses, fungi, archaea, and their genes, and two of the most commonly studied within the human body are the gut microbiome and oral microbiome. Research suggests that host microbiomes influence human health and disease via interactions with the immune system and metabolic function (Hou K. et al., 2022). For example, elevated pro-inflammatory cytokines (small proteins that act as chemical messengers in the body) are often a sign of underlying pathology and have been associated with specific bacterial variations within gut and oral microbiomes (Baker J. et al., 2024).
The body’s ability to mount an appropriate immune response when presented with pathology is called ‘immune fitness’ (Verster J. et al., 2022). Immune fitness is thought to be influenced by lifestyle factors such as diet and exercise, and is commonly measured subjectively via a self-reported rating scale (Verster J. et al., 2022).
This new study by Ulijn et al. (2026) aimed to determine whether there was a relationship between immune fitness and gut and oral microbiome composition within a group of young healthy volunteers. They hypothesised that gut and oral bacteria previously linked to the immune system would be associated with self-reported immune fitness.
Methods
Ulij et al. (2006) explored their hypothesis in a group of 29 healthy, young male and female participants aged 18-30 who were recruited as part of a wider study of alcohol hangover (Mackus et al., 2023). Participants who had underlying diseases, took medication, smoked, or took drugs were excluded, and those who did not sleep well the night before the test day were also excluded.
On the day of testing, participants completed the immune fitness scale in the morning and then hourly throughout the day. This single-item scale asks participants to rate their perceived immune fitness from 0 (very poor) to 10 (excellent). Saliva samples were taken to measure the oral microbiome and inflammatory cytokine levels. A subset of 16 participants also had stool samples taken to assess the gut microbiome.
The researchers then used correlational analyses to look at the relationship between the oral microbiome, gut microbiome, immune fitness, and inflammatory cytokines. They decided to use the first immune fitness rating from the day of testing as they reported that the immune fitness ratings were consistent during the day.
Results
Ulijn et al. (2026) highlight that associations were seen between the relative abundance of some genus-level bacteria in the oral microbiome and immune fitness scores. Specifically, as the relative abundance of the genera Selenomonas went up, immune fitness tended to decrease, representing a negative correlation (r = -0.610, p < 0.001). A similar pattern was seen for Lachnospiraceae uncultured (r = -0.501, p = 0.006). Both of these oral bacteria are suggested to be proinflammatory.
The researchers also explored whether there was any relationship between the alpha diversity (i.e., within-person diversity) of the oral microbiome and immune fitness, or between the Firmicutes/Bacteroidetes ratios (i.e., represents the balance between two dominant bacterial phyla in the microbiome) and immune fitness, however they reported that no statistically significant associations were found.
There were a few salivary inflammatory cytokines which showed an association with bacterial abundance within the oral microbiome. IL-1β (one such cytokine) was negatively correlated with the bacteria Lautropia (r = -0.591, p <0.001) and positively correlated with Saccharimonadales. This means that participants with increased levels of IL-1β were more likely to have lower levels of Lautropia, which the authors suggest is an anti-inflammatory bacteria. Higher levels of Saccharimonadales Lautropia were also negatively correlated with a different inflammatory cytokine, IL-8 (r = -0.546, p = 0.005).
The authors report that two other inflammatory cytokines, IL-6 and TNF-α, did not reveal any statistically significant associations with oral bacteria based on the criteria that they set for determining significance. However, a negative correlational trend was seen between the bacteria Alloprevotella and IL-6 (r = -0.386, p = 0.042), Bergeyella and IL-6 (r = -0.408, p = 0.031), Lautropia and IL-6 ( r -0.427, p = 0.024) and Lautropia and TNF-α ( r -0.411, p = 0.027). A positive correlational trend was seen between TNF-α and Granulicatella (r = 0.434, p = 0.019), which the authors point out is an oral opportunistic pathogen.
The gut microbiome was measured via stool samples in a subset of 16 participants. Alpha diversity of the gut microbiome was negatively correlated with immune fitness scores, meaning that as an individual’s within-person gut microbiome diversity increased, their immune fitness tended to decrease (r = -0.661). In terms of specific bacterial abundance, immune fitness was positively associated with Lachnoclostridium (r = 0.513, p = 0.042), indicating that as immune fitness scores increased so too did the relative abundance of Lachnoclostridium, which the authors suggest is an anti-inflammatory bacteria. Conversely, negative correlations were found with bacteria Colidextribacter (r = -0.582, p = 0.018) and Lachnospiraceae FCS020 group (r = -0.504, p = 0.047).
Conclusions
The authors conclude that:
self-reported immune fitness is associated with the relative abundance of oral and gut microbiota that are involved in immune function.
What that means is that a few bacteria from the oral and gut microbiome which have been previously shown to be associated with immune biomarkers, were shown here to be correlated with self-reported immune fitness.
Strengths and limitations
The researchers addressed an interesting and novel research question by exploring the associations between immune fitness and both the gut and oral microbiome.
Although the authors point out that due to the small sample size they were limited in scope regarding appropriate analyses that they could carry out, it would have been nice to see them extend their analyses beyond what they presented. For example, I would have found it interesting to see correlations between the gut microbiome and oral microbiome, to see how closely they resemble each other compositionally, as well as correlations between the gut microbiome and salivary inflammatory markers, to see if there was any consistency there between their relationship with the oral and gut microbiomes. Similarly, it would have been interesting to see whether immune fitness scores correlated with inflammatory biomarkers.
There were some aspects of the study design which were methodologically rigorous, such as taking saliva samples at the same time of day. Given that inflammatory cytokines can change throughout the day with our circadian rhythms, this was great to see. However, there were other aspects of the paper that were less rigorous or accurate in their descriptions. For example, although it was great that the authors used a statistical method called bootstrapping, they advised that they did this to account for the small sample size. Although the method can increase the accuracy of the results presented, it does not directly address the main issue of having a low sample size, which is the lack of statistical power. Similarly, although it appeared rigorous that the authors set stricter criteria than is usual for considering an association statistically and clinically significant (i.e., the magnitude of the correlation had to be greater than ± 0.5 in addition to the p value being < 0.05), this specific choice was not justified or explained on the basis of previous research or any other precedent.
Finally, it’s important to note that no causal interpretations can be drawn from the results of this study, which the authors did not touch upon within the reported limitations of the study. This is mainly because all the measures were taken at the same time (i.e., it’s cross-sectional) and also given that the authors did not include any confounders in their analyses. It is possible that other unmeasured factors (e.g., diet and other lifestyle factors, sex, socioeconomic factors, BMI) could explain the associations seen.
Implications for practice
The study by Ulijn et al. (2026) seeks to understand whether the oral and gut microbiomes are linked to the immune system, which they hypothesise could be a mechanism underlying some of the associations seen in other research between host microbiomes and human health and disease.
Understanding the complex interactions between host microbiomes and human health and disease certainly has the potential to be translated into changes in clinical practice in the future, and could result in specific recommendations for the administration of probiotics, prebiotics, synbiotics, fecal microbiome transplants (FMT), anti-inflammatory medication, or health and lifestyle advice that can modify host microbiomes. But, we are not there yet.
This study represents a very early step in that journey, attempting to establish whether there is any association between host microbiomes and immune fitness within a healthy population. However, due to some methodological issues, such as not including possible confounders like diet and lifestyle factors, we cannot be completely sure that the associations reported here would hold up once confounders were taken into consideration. It’s therefore unclear whether the results here tell us anything meaningful about whether the immune system is involved in host-microbiome and human health relationships.
Future research could build upon this study and explore similar research questions within populations of people with specific health conditions of interest, and use appropriate causal inference methods to understand the connection between host microbiomes and the immune system. Ideally, we need a combination of randomised controlled trials and longitudinal studies to unravel the complex interplay between host microbiomes, immune function, and human health and disease. It would certainly be interesting to see if future research finds similar connections between the oral and gut bacteria highlighted in this study and immune function. Multiple independent studies that highlight similar findings, particularly if they utilise different methods, can strengthen our confidence that the associations seen represent true biological mechanisms and therefore takes us further along the path to changing clinical practice.
Statement of interests
Susie Robinson-Molloy is currently working on a project that examines associations between the gut microbiome and depression and schizophrenia. She has no other conflicts of interest to declare.
Editor
Edited by Éimear Foley. ChatGPT assisted with language refinement and formatting during the editorial phase.
Links
Primary paper
Guusje A. Ulijn, Emina Išerić, Aurora J.A.E. van de Loo, Johan Garssen, Phillip A. Engen, Ankur Naqib, Stefan J. Green, Ali Keshavarzian, Joris C. Verster (2026) Immune fitness and biomarkers of immune function: Relationships with the oral and gut microbiome composition. Brain, Behavior, and Immunity – Health, 54, 101239. https://doi.org/10.1016/j.bbih.2026.101239
Other references
Baker J, Mark Welch M, Kauffman, K. et al (2024) The oral microbiome: diversity, biogeography and human health. Nat. Rev. Microbiol. 22, 89–104. https://doi.org/10.1038/s41579-023- 00963-6.
Hou K, Wu Z, Chen X. et al (2022) Microbiota in health and diseases. Signal Transduct. Targeted Ther. 7, 135. https://doi.org/10.1038/s41392-022-00974-4
Mackus M, van de Loo A, van Neer R. et al. (2023) Differences in next-day adverse effects and impact on mood of an evening of heavy alcohol consumption between hangover-sensitive drinkers and hangover-resistant drinkers. J. Clin. Med. 12, 2090. https://doi.org/10.3390/ jcm12062090.
Verster J, Kraneveld A, Garssen J. (2022) The assessment of immune fitness. J. Clin. Med. 12, 22. https://doi.org/10.3390/jcm12010022.