Methods
The narrative review was prepared by analyzing publications available in the PubMed database, as well as information provided by of the World Health Organization (WHO) and Atlas of MS (2023). The articles were selected based on keywords such as: microbiome, multiple sclerosis, dysbiosis, oral microbiome, skin microbiome, and gut microbiome. Keywords were aligned with Medical Subject Headings (MeSH) terminology to improve the precision and relevance of the search. The main scope of the search covered publications published between 2020 and 2025, earlier relevant studies were also included where relevant to provide essential background.
Introduction
Multiple sclerosis (MS) is a chronic, immune mediated disease of the central nervous system (CNS), characterized by inflammation, and neuroaxonal injury, with a complex etiology that remains incompletely understood. (Haase and Linker 2021 ; Haki et al. 2024 ). The disease is characterized by disseminated and heterogeneous perivascular inflammatory processes at the level of the blood–brain barrier (BBB), involving autoreactive T and B lymphocytes, macrophages, and microglial cells that target the white matter of the brain and spinal cord (Constantinescu and Gran 2010 ; Kutzelnigg and Lassmann 2014 ). Dysfunction and increased permeability of the BBB—a structure essential for maintaining CNS homeostasis and preventing the entry of peripheral immune factors—represent key molecular and cellular mechanisms underlying neuroinflammation in MS (Sun et al. 2025 ). Multiple sclerosis is one of the most common non-traumatic causes of disability and primarily affects young adults. The progressive decline in physical abilities and cognitive functions has a substantial impact on patients’ social, economic, and personal functioning, significantly reducing their quality of life (Poli et al. 2024 ). The major clinical phenotypes include relapsing–remitting MS (RRMS), secondary progressive MS (SPMS), and primary progressive MS (PPMS), which differ in the pattern of disease activity and disability progression (Lublin and Reingold 1996 ; Lublin et al. 2014 ; Klineova and Lublin 2018 ; Kuhlmann et al. 2023 ; Lomer et al. 2024 ). Clinically isolated syndrome (CIS) and radiologically isolated syndrome (RIS) may precede a definite diagnosis of MS (Nistri et al. 2024 ).
Comorbidities are highly prevalent among individuals with MS and can significantly influence both disease activity and treatment outcomes. Common comorbidities include psychiatric, cardiometabolic, vascular, and musculoskeletal disorders, which may influence disease course, disability progression, and treatment outcomes (Marrie et al. 2015 ; Peterson et al. 2022 ; Nociti and Romozzi 2023 ; Salter et al. 2024 ). Beyond these clinical factors, growing evidence suggests that interactions between environmental exposures, the human microbiome, and immune regulation may also be relevant to MS pathogenesis (Miyake and Yamamura 2019 ; Maglione et al. 2021 ). Understanding these interactions may provide further insight into complex mechanisms underlying disease development and progression.
Epidemiology and etiological factors
According to the Atlas of MS report, 2.9 million people worldwide are living with MS (Multiple Sclerosis International Federation 2020 ). The disease is most commonly diagnosed in individuals 20–50 years of age, with a predominance of women and an overall female-to-male ratio of 3:1. The median age of diagnosis is 32 years, and women are affected 2–5 years earlier than men (Jakimovski et al. 2024 ; Portaccio et al. 2024 ). Although approximately 10% of patients exhibit their first clinical manifestations before the age of 18 (Iaffaldano et al. 2017 ), recent epidemiological data indicate a growing incidence also after the age of 50 (Prosperini et al. 2022 ; Portaccio et al. 2024 ). The etiology of MS remains incompletely understood, and its development is influenced by genetic and environmental factors, including EBV infection, vitamin D deficiency, smoking, obesity, and dietary habits (Fig. 1 ) (Montgomery et al. 2024 ). Fig. 1 Etiology and risk factors of multiple sclerosis. Created with BioRender.com
The heritable component of MS susceptibility is estimated to be approximately 25%, whereas the remaining risk is likely attributable to environmental and epigenetic influences, as well as gene–gene and gene-environment interactions (Olsson et al. 2017 ). Despite numerous identified genetic associations, no single variant is necessary or sufficient to cause MS—instead, each contributes additively to the overall genetic risk (Goris et al. 2022 ). The strongest individual genetic risk factor is the HLA-DRB1*15:01 allele, located on the short arm of chromosome 6, which increases the likelihood of developing MS by approximately threefold. Notably, vitamin D has been shown to modulate HLA-DR expression and antigen presentation, underscoring potential interactions between genetic determinants and environmental exposures in MS pathogenesis (Handunnetthi et al. 2010 ). Environmental factors also contribute substantially to MS risk. The prevalence of MS demonstrates a clear association with geographic latitude, increasing with distance from the equator (Montague et al. 2025 ). The association between geographic latitude and the prevalence of MS is partly explained by variations in vitamin D status, as reduced sunlight exposure leads to lower serum vitamin D levels. Numerous studies have confirmed a correlation between vitamin D deficiency and increased MS risk, which is consistent with the immunomodulatory properties of vitamin D that may attenuate excessive immune activation (Sintzel et al. 2018 ). The largest randomized clinical trial to date evaluating vitamin D supplementation in MS—the D-Lay MS study demonstrated a 34% reduction in the risk of disease activity among individuals with CIS, an early demyelinating event preceding the onset of clinically definite MS. These findings suggest that both low vitamin D levels and a potentially impaired physiological response to vitamin D may influence pathophysiological processes at the earliest stages of the disease (Thouvenot et al. 2025 ; Montague et al. 2025 ). Other important environmental contributors include smoking and obesity, which likewise have well-established associations with increased MS susceptibility [24]. Smoking is consistently associated with an increased likelihood of developing MS. Cigarette smoke contains high levels of free radicals and adversely affects immune function. Smokers exhibit elevated concentrations of pro-inflammatory cytokines, including IL-6, fibrinogen, C-reactive protein, and other inflammatory markers that contribute to autoimmune activation (Baskara et al. 2020 ). Obesity is now recognized as an important modifiable risk factor for multiple sclerosis, particularly during childhood and adolescence (Alfredsson and Olsson 2019 ). Contemporary epidemiological studies and genetic analyses, including Mendelian randomization, provide consistent evidence supporting its role in MS pathogenesis. Evidence from cohort studies and Mendelian randomization analyses consistently links elevated body mass during childhood and adolescence with an increased risk of MS, suggesting that early-life obesity may represent a particularly relevant modifiable risk factor (Munger 2013 ; Hedström et al. 2016 ; Harroud et al. 2021 ). Nevertheless, the strongest established etiological factor for MS remains infection with EBV. The risk of MS among EBV-seronegative individuals is exceedingly low, suggesting that prior EBV infection is nearly a prerequisite for disease development (Bjornevik et al. 2022 ). Moreover, MS risk increases when primary EBV infection occurs after the age of 10, and elevated EBV antibody titers further indicate increased susceptibility to the disease (Bar-Or et al. 2020 ). The exact mechanism linking EBV infection to the development of MS remains unclear. One proposed hypothesis is that EBV-infected autoreactive naive B cells present antigens that mimic myelin structures(Soldan and Lieberman 2023 ). The influence of infection timing may be associated with the stage of thymic development and the period during which autoreactive T cells undergo negative selection (Soldan and Lieberman 2023 ; Thomas et al. 2023 ).
Genetic, environmental and lifestyle factors—such as HLA susceptibility alleles, viral infections (including HHV-6, MSRV, measles virus and Epstein-Barr), vitamin D deficiency, smoking, and obesity—have been associated with MS and are thought to promote a pro-inflammatory immune environment and impaired regulatory response, further pointing to immune dysregulation as a major pathogenic pathway (Montgomery et al. 2024 ). These diverse genetic and environmental determinants may converge on immune dysregulation, while some environmental exposures may additionally influence host-microbiome interactions. In this context, increasing attention has been directed toward the gut microbiome as a key modulator of immune homeostasis and a potential mediator connecting environmental exposures with the initiation and progression of MS, partly through bidirectional gut-brain axis signaling that enables intestinal microorganisms to influence both peripheral and central immune responses (Parodi and Kerlero de Rosbo 2021 ; Mohsen et al. 2025 ).
Microbiome and multiple sclerosis
Scientific interest in the interactions between the nervous system and peripheral organs can be traced back to the seventeenth century, when Thomas Willis provided the first detailed description of the brain’s structure and its connections to other parts of the body (Wragge-Morley 2018 ). Today, one of the most important areas of these interactions is the gut microbiota—a complex ecosystem of microorganisms that influence metabolism, immunity and nervous system function through gut-brain axis mechanisms. A growing number of studies indicate that alterations in the microbiota are associated with neurodegenerative disease, including MS, making the analysis of the human microbiome a key element of contemporary MS research (Jangi et al. 2016 ; Berer et al. 2017 ; Takewaki et al. 2020 ).
Composition, diversity, and dysbiosis of the gut microbiome in MS
An increasing number of studies indicate that alterations in the composition, structure, and function of the gut microbiota may be associated with both disease activity and disability progression in individuals with MS. In the study by Devolder et al. ( 2023 ), baseline gut microbiome profiles were evaluated in relation to subsequent disease progression. Among the identified enterotype-like clusters, the Bact2 cluster, which in general populations is characterized by a pro-inflammatory profile and reduced microbial diversity, demonstrated relative temporal stability and was associated with an increased risk of neurological worsening, suggesting its potential value as a prognostic biomarker. Moreover, Bact2 was marked by reduced abundance of short-chain fatty acid (SCFA)—producing bacteria, including Faecalibacterium, Coprococcus , and Roseburia . The association between Bact2 and disability progression remained significant in multivariable analyses, independent of clinical covariates (Devolder et al. 2023 ). The production of short-chain fatty acids (SCFAs)—particularly acetate, propionate, and butyrate—constitutes a key regulatory component of the gut-brain axis due to their ability to modulate the neuroendocrine system, strengthen the intestinal barrier, and attenuate inflammatory responses(Choileáin et al. 2020 ; Reynders et al. 2020 ; Takewaki et al. 2020 ; Moles et al. 2022 ; Montgomery et al. 2024 ). Alterations in SCFA-related microbial profiles have been reported across MS cohorts, including reduced butyrate levels alongside an increased abundance of bacteria from the phylum Proteobacteria , particularly the family Enterobacteriaceae . These alterations were more pronounced among patients with higher disability scores, suggesting a potential association with a more severe disease course. The expansion of Proteobacteria is widely interpreted as a marker of pro-inflammatory dysbiosis. Additionally, a decrease in the abundance of Dialister and Coprococcus was reported, further linking compositional alterations with reduced SCFA-producing and potentially anti-inflammatory capacity (Moles et al. 2022 ). Microbiome patterns may also differ according to MS phenotype. In PPMS, distinct community-level alterations have been reported, including significant enrichment of Gemmiger sp. and an unclassified member of the Ruminococcaceae family. Notably, patients with PPMS exhibited higher alpha diversity compared with healthy controls, indicating that MS-associated dysbiosis is not uniformly characterized by reduced microbial diversity and may instead involve broader changes in microbial community structure. (Kozhieva et al. 2019 ). Analyses conducted across multiple independent cohorts of patients with MS reveal some recurring patterns of gut dysbiosis, characterized by both an increased abundance of specific taxa and a reduction in bacteria with anti-inflammatory potential. Patients with both RRMS and PPMS exhibited elevated levels of Clostridium bolteae , Ruthenibacterium lactatiformans , and Akkermansia muciniphila , accompanied by decreased abundance of Blautia wexlerae , Dorea formicigenerans , and members of the Erysipelotrichaceae family CCMM. These findings indicate alterations in the relative abundance of several bacterial taxa in patients with MS, although the composition and direction of microbiome changes may vary across studies (Cox et al. 2021 ; Ghimire et al. 2025 ). The interpretation of the role of Akkermansia muciniphila remains inconclusive. Increased abundance of A. muciniphila has been observed in patients with MS (Jangi et al. 2016 ), while experimental work suggests that this species may promote pro-inflammatory immune responses (Cekanaviciute et al. 2017 ). More recent clinical observations suggest a more complex relationship between Akkermansia and disease severity. Higher abundance has been associated with lower disability in progressive MS, while longitudinal evidence has linked depletion of Akkermansia with subsequent disease progression (Cox et al. 2021 ; Montgomery et al. 2024 ). Experimental evidence further indicates that the effects of A. muciniphila on CNS autoimmunity may depend on the surrounding microbial community (Steimle et al. 2024 ; Peipert et al. 2025 ). These observations raise the possibility that the increased prevalence of this species in MS may reflect a compensatory, rather than exclusively pathogenic, response of the microbial ecosystem (Cox et al. 2021 ). These conflicting findings illustrate that the functional significance of individual microbial taxa in MS may vary according to disease phenotype, treatment exposure, cohort characteristics, microbial context, and study design.
In RRMS, a reduced abundance of key butyrate-producing taxa, including Eubacterium rectale and Ruminococcus , has also been documented. These reductions were associated with decreased expression of genes involved in short-chain fatty acid metabolism. Such alterations may be associated with impaired mucosal barrier function and the emergence of a more proinflammatory intestinal environment (Reynders et al. 2020 ; Horton et al. 2021 ). Despite numerous reported associations, no single stable microbiological biomarker with established clinical utility has yet been identified. A potentially informative parameter is the Bifidobacterium/Akkermansia ratio. A lower ratio of Bifidobacterium adolescentis to Akkermansia muciniphila (BA:AM) in patients with MS correlated with higher disability scores (EDSS). This association may reflect an altered balance between bacteria that support mucosal barrier integrity (e.g., Bifidobacterium ) and those that degrade mucin (e.g., A. muciniphila ), which may influence intestinal barrier integrity and modulate both local and systemic inflammatory processes (Jangi et al. 2016 ; Cosorich et al. 2017 ; Berer et al. 2017 ; Ghimire et al. 2025 ). The clinical and prognostic relevance of this ratio requires validation in independent longitudinal cohorts.
A valuable multi-center perspective was provided by a meta-analysis encompassing seven studies conducted in the USA, China, and Japan (Miyake et al. 2015 ; Chen et al. 2016 ; Jangi et al. 2016 ; Cekanaviciute et al. 2017 ; Zeng et al. 2019 ; Choileáin et al. 2020 ; Cantoni et al. 2022 ; Lin et al. 2024 ). Its findings confirmed that alpha diversity of the gut microbiota does not constitute a stable biomarker of MS: Choileáin et al. reported significantly lower alpha diversity in patients with MS, whereas Chen et al. demonstrated significantly higher taxonomic richness; the remaining five studies found no significant differences (Chen et al. 2016 ; Choileáin et al. 2020 ; Lin et al. 2024 ). Results concerning beta diversity were likewise inconsistent, although several studies indicated greater heterogeneity of the microbiota in individuals with MS. These findings illustrate the limited reproducibility of diversity-based measures across MS cohorts. In contrast, differences in taxonomic composition were markedly more consistent. Across the datasets included in the meta-analysis, 25 bacterial genera differed between MS and controls in at least two datasets, with 17 showing a consistent direction of change (Lin et al. 2024 ). Prevotella emerged as one of the most consistent taxonomic findings, with reduced abundance reported across all seven studies (Miyake et al. 2015 ; Chen et al. 2016 ; Jangi et al. 2016 ; Cekanaviciute et al. 2017 ; Zeng et al. 2019 ; Choileáin et al. 2020 ; Cantoni et al. 2022 ). Faecalibacterium , Lachnospira , and Megamonas were also significantly decreased in patients with MS in three of the studies re-analyzed by Lin et al. ( 2024 ). Importantly, the associations involving Actinomyces and Faecalibacterium remained consistent when individual studies were excluded from the analysis. Notably, taxa within the class Clostridia appeared to be particularly affected. Moreover, alterations were observed not only in the relative abundance of individual taxa but also in the overall structure of microbial correlation networks. The characteristic strong negative correlation between Bacteroides and Prevotella , typically present in healthy individuals, was markedly disrupted in patients with MS. This pattern indicates that the MS-associated microbiota undergoes a broader reorganization rather than merely exhibiting isolated shifts in bacterial abundance. Overall, the meta-analysis suggests that MS-associated gut dysbiosis may involve not only alterations in the abundance of individual bacterial taxa but also changes in their interrelationships and microbial network structure (Lin et al. 2024 ).
Beyond the gut: oral and skin microbiome alterations in MS
Oral and skin microbiota, alongside the gut microbiota, may be associated with MS and may contribute to immune modulation. The oral microbiota has received increasing attention because periodontal inflammation and dysbiotic oral bacteria may promote systemic inflammatory responses, while bacterial products may enter the circulation and potentially influence neuroinflammatory processes (Li et al. 2022 ). Experimental evidence further suggests a potential mechanistic link, as periodontal infection with Porphyromonas gingivalis aggravated experimental autoimmune encephalomyelitis (EAE) and enhanced peripheral pro-inflammatory T-cell responses (Li et al. 2022 ; Dai et al. 2025 ). Studies comparing patients with MS and healthy controls have reported alterations in the oral microbiota. Reported changes include enrichment of inflammation-associated taxa, such as Fusobacterium , Porphyromonas , and selected Prevotella , as well as depletion of selected commensal taxa, although the direction and magnitude of these alterations vary across studies (Troci et al. 2022 ; Boussamet et al. 2024 ; Dai et al. 2025 ). Oral dysbiosis has also been proposed to interact with Th17-related immune responses. Periodontal inflammation and oral pathobionts may promote Th17-cell expansion, although direct evidence connecting specific oral taxa with increased production of IL-17, IL-21 and IL-22 in patients with MS remains limited (Li et al. 2022 ).
Whether these alterations contribute directly to MS pathogenesis or instead represent secondary disease-associated changes remains unclear. Recent evidence indicates that the oral microbiota may also be associated with disease activity and disability (Troci et al. 2022 ). However, the interpretation of individual taxa remains dependent on the anatomical site sampled, treatment status, cohort characteristics, and study design (Zangeneh et al. 2021 ; Troci et al. 2022 ; Boussamet et al. 2024 ). Moreover, the relatively small cohorts and differences in treatment, sampling procedures, and study design limit direct comparisons between studies. Alterations have also been investigated in the skin microbiota, although evidence remains considerably more limited than that for the gut microbiome. In a Mendelian randomization analysis, the relative abundance of the Gammaproteobacteria class in the skin was associated with MS severity (Zancan et al. 2025 ). Because this finding was based on genetically proxied microbiome composition rather than direct longitudinal sampling of the skin microbiota in patients with MS, its causal and clinical significance remains to be established. These findings suggest that microbial communities outside the gastrointestinal tract may be relevant to MS susceptibility and disease severity. However, further longitudinal, mechanistic, and interventional studies are needed to clarify their functional and clinical significance.
Expanding the microbiome-immunity axis: the role of mucosa-associated microbiota in MS
Studies of the microbiome in MS are most commonly based on the analysis of fecal samples. Increasing evidence indicates that microorganisms associated with the intestinal mucosal layer may play a more significant role in the modulation of local immune responses. Fecal samples primarily reflect luminal microbial communities and may not fully represent microorganisms associated with the intestinal mucosa (Cosorich et al. 2017 ; Camara-Lemarroy et al. 2018 ). Mucosa-associated communities occupy distinct spatial and functional niches and remain in closer contact with the intestinal epithelium and host immune system (Vaga et al. 2020 ; Miyauchi et al. 2022 ). Microorganisms residing in close proximity to the intestinal epithelium, such as Bacteroides , may exhibit distinct metabolic activities, including tryptophan metabolism leading to the production of indoles, which are known for their immunomodulatory properties. These spatial differences may therefore be accompanied by functional differences in microbial metabolism and microbiota–host interactions (Vaga et al. 2020 ). The use of intestinal lavage-based methods has been proposed as a less invasive alternative to biopsy while allowing for the analysis of mucosa-associated microbiota that may be more mechanistically relevant to host–microbiome interactions. Lavage samples have been shown to capture mucosa-associated bacteria while providing higher bacterial DNA content and lower host DNA contamination than biopsy or brushing samples(Miyauchi et al. 2022 ). Consideration of distinct microbial niches and microbial metabolic activity may be critical for a more comprehensive understanding of microbiome-immune system interactions in MS (Cosorich et al. 2017 ; Camara-Lemarroy et al. 2018 ; Vaga et al. 2020 ; Miyauchi et al. 2022 ). The differences between fecal and mucosa-associated microbiota and their functional relevance are illustrated in Fig. 2 . Fig. 2 Differences between fecal and mucosa-associated microbiota in multiple sclerosis. Created in BioRender.com
Mechanistic links between microbiome, genetics and immunity in MS
Microbiota-dependent immune regulation in MS
A study by Jangi et al. ( 2016 ) demonstrated that alterations in the gut microbiome in MS were associated not only with compositional changes but also with differences in host immune gene expression. Patients with MS exhibited an increased relative abundance of Methanobrevibacter and Akkermansia and a reduced abundance of Butyricimonas compared with healthy controls. Correlation analyses demonstrated that the abundance of Methanobrevibacter and Akkermansia correlated with gene-expression patterns related to immune activation in T lymphocytes and monocytes, whereas Butyricimonas generally showed opposite associations. Despite the increased abundance of Methanobrevibacter in patients with MS, this alteration was not accompanied by a markedly enhanced humoral immune response (Jangi et al. 2016 ). These observations point to potential link between the gut microbiota and the modulation of peripheral immune responses in MS.
The relationship between gut dysbiosis and autoimmunity may involve mechanisms such as molecular mimicry between microbial antigens and host autoantigens, activation of proinflammatory T lymphocytes, and disruption of the balance between regulatory and effector T cells within an inflammatory environment (Regen et al. 2021 ; Nitzan et al. 2023 ). In patients with MS, increased numbers of T helper 17 (Th17) cells have been observed in the intestinal mucosa compared with healthy individuals. A high frequency of Th17 cells was associated with disease activity, particularly in RRMS. Additionally, a higher Firmicutes / Bacteroidetes ratio, increased relative abundance of Streptococcus , mainly S. mitis and S. oralis , and reduced abundance of Prevotella were observed in patients with active disease compared with healthy controls and patients with inactive MS, with the frequency of Th17 cells in the small intestine being inversely proportional to the relative abundance of Prevotella (Cosorich et al. 2017 ). These human observations demonstrate associations between intestinal microbial patterns, Th17 responses, and disease activity, but do not establish that microbiota-induced Th17 differentiation directly drives CNS autoimmunity in MS. Mechanistic evidence for this relationship is derived primarily from experimental models. The importance of the IL-17-microbiota axis is further supported by studies using the EAE model, in which mice deficient in IL-17A/F exhibited altered gut microbiota composition and loss of disease susceptibility, whereas reconstruction of a wild-type microbiota or reintroduction of IL-17A specifically into the intestinal epithelium restored susceptibility to EAE (Regen et al. 2021 ). These experimental findings support a mechanistic role for the IL-17–microbiota axis in intestinal homeostasis and CNS autoimmunity in EAE. Their relevance to human MS should nevertheless be interpreted cautiously, as mechanisms demonstrated in EAE cannot be directly extrapolated to human disease.
The gut mycobiome as an immunomodulatory component in MS
The gut mycobiome remains relatively poorly characterized in the context of autoimmune diseases. An increasing body of evidence suggests potential associations between the gut mycobiome, immune regulation, and MS (Shah et al. 2021 ). In patients with MS, a significantly higher α-diversity of the fungal component of the microbiome, as well as greater interindividual variability, has been demonstrated compared with healthy individuals. In the MS group, an overrepresentation of fungi from the genera Saccharomyces and Aspergillus was observed, and their abundance correlated with immunological parameters, including circulating basophil counts, regulatory B cell levels, and activated CD16 + dendritic cells (Gargano et al. 2022 ). Fungal isolates, particularly Candida albicans and Saccharomyces cerevisiae , induced stronger T cell activation in patients with MS, especially among MAIT cells, which exhibited increased CD69 expression. Neutralization of IL-23 markedly reduced MAIT cell proliferation induced by fungal extracts, supporting the involvement of this cytokine in the mycobiome-immunity axis. In postmortem brain tissue from patients with progressive MS, MAIT cells were detected within inflammatory infiltrates, where a subset of these cells exhibited expression of IFN-γ, IL-17, GM-CSF, and CCL20, suggesting a potential association with neuroinflammatory process. Together, these human observations indicate an association between fungal microbiome alterations and immune responses relevant to MS, although they do not establish that intestinal fungal dysbiosis directly contributes to CNS inflammation. Mechanistic evidence is provided primarily by experimental models. The relevance of the mycobiome is further supported by studies using the EAE model, in which prior infection with C. albicans resulted in a more severe disease course, increased production of encephalitogenic cytokines, and the presence of fungus-specific T lymphocytes in the central nervous system (Fraga-Silva et al. 2015 ). While these findings support a potential mechanistic link between fungal exposure and CNS autoimmunity in EAE, their relevance to human MS requires further investigation. Additionally, differences in the expression of the APR1 gene were identified in C. albicans isolates derived from patients with MS compared with isolates from healthy individuals, which may reflect fungal adaptation to altered host immunological conditions (Amri Saroukolaei et al. 2016 ).
Genetic and metabolic pathways linking the gut microbiome to autoimmunity in MS
Mechanistic evidence linking host genetics to microbiota is provided by studies using the EAE model, in which the impact of HLA class II gene polymorphisms on gut microbiota composition and susceptibility to autoimmunity was investigated. Transgenic mice expressing HLA-DR3 or HLA-DR3.DQ8 on a background lacking endogenous MHC class II genes exhibited susceptibility to EAE, with double-transgenic mice showing a more severe disease course. At the same time, gut microbiota profiles differed significantly between genotypes and correlated with EAE disease severity, suggesting a potential interaction between HLA genotype, gut microbiota composition, and susceptibility to CNS autoimmunity in this experimental model. Although these findings are derived from an animal model, they suggest that microbiome studies in patients with MS should take genetic background, including HLA haplotypes, into account as a potential factor contributing to interindividual variation in microbiome composition and disease-related associations (Shahi et al. 2021 ). Further studies are needed to determine whether similar interactions occur in patients with MS. The gut microbiome may also exert effects beyond the intestine through the production of metabolites capable of entering the systemic circulation and the cerebrospinal fluid (CSF), thereby potentially influencing inflammatory processes in multiple sclerosis. Bacterial metabolites have been detected in the plasma and CSF of patients with MS, including potentially neuroactive tryptophan metabolites and derivatives of indole (IS), tyrosine (pCS), and phenylalanine (PAG), collectively referred to as “red modules,” which were present at higher concentrations in patients with MS. These findings demonstrate an association between altered microbial metabolite profiles and MS, and suggest a potential route of gut–brain communication through circulating metabolites. Their direct contribution to neuroinflammation and neuronal injury in human MS remains to be established (Ntranos et al. 2022 ). Key studies investigating the role of the gut microbiome and MS are summarize in Table 1 . Table 1 Summary of key research articles on the associations between the microbiome and multiple sclerosis References Type of research Materials and methods Conclusions Thouvenot et al. ( 2025 ) Randomized controlled trail CIS patients randomized to high-dose vitamin D (100,000 IU biweekly) or placebo for 24 months; clinical and MRI outcomes assessed High-dose vitamin D significantly reduced disease activity in early MS; supports its role as a safe adjunctive therapy Bjornevik et al. ( 2022 ) Prospective cohort study > 10 million US military personnel; EBV seroconversion and serum NfL levels analyzed EBV infections increases MS risk 32-fold; NfL rises after infection, supporting EBV as a leading casual factor Choileáin et al. ( 2020 ) Case-control study 16S rRNA sequencing of gut microbiota and immune profiling (flow cytometry) in RRMS patients and controls Reduced abundance of SCFA-producing bacteria is linked to immune dysregulation; SCFAs support Treg responses and limit inflammation, suggesting their deficiency contributes to MS pathogenesis Takewaki et al. ( 2020 ) Case-control study Multi-omics analysis of gut microbiota (16S rRNA, metagenomics, metabolomics) in MS subtypes and controls Gut microbiome alterations differ by MS stage; reduced SCFA production in RRMS and increased oxidative stress in SPMS suggest stage-specific mechanisms and therapeutic targets Berer et al. ( 2017 ) Translational study Gut microbiota from MS-discordant twins analyzed (16S rRNA, metagenomics) and transferred to germ-free mice; EAE development and immune responses assessed Microbiota from MS patients increases susceptibility to CNS autoimmunity; findings provide causal evidence linking gut microbiota to MS pathogenesis Jangi et al. ( 2016 ) Case-control study 16S rRNA sequencing of gur microbiota (MS vs. controls); immune gene expression analysis MS patients show altered gut microbiota associated with pro-inflammatory immune profiles; microbiome may serve as a biomarker and therapeutic target Cosorich et al. ( 2017 ) Case-control study Gut mucosal microbiota (16S rRNA) and T cell subsets (flow cytometry) analyzed in RRMS patients and controls Expansion of pro-inflammatory Th17 cells correlates with gut microbiota alterations; findings link dysbiosis to immune-mediated CNS autoimmunity in MS Cox et al. ( 2021 ) Translational study 16S rRNA sequencing of gut microbiota in MS patients (RRMS, progressive) and controls; clinical correlations and EAE mouse model experiments Specific microbiota profiles correlate with disease severity; Akkermansia is associated with milder MS and reduces inflammation in EAE Peipert et al. ( 2025 ) Experimental study EAE mouse model with controlled microbiota; Akkermansia muciniphila colonization; microbiome, immune response, and SCFA analysis Akkermansia effects are microbiome-dependent; under specific conditions it enhances Th17 responses and reduces SCFA, exacerbating CNS autoimmunity Regen et al. ( 2021 ) Experimental study EAE mouse model with IL-17A/F knockout; microbiome analysis and reconstitution experiments IL-17 regulates CNS autoimmunity indirectly via the gut microbiome; loss of IL-17 alters microbiota and reduces disease susceptibility Ntranos et al. ( 2022 ) Translational study Metabolomic profiling of CFS and plasma in MS patients before/after DMF; in vitro neuronal assays Microbial-derived metabolites induce neurotoxicity and axonal damage; DMF reduces these metabolites and is associated with improved neurodegenerative markers
Table 1
Summary of key research articles on the associations between the microbiome and multiple sclerosis
| References | Type of research | Materials and methods | Conclusions |
| Thouvenot et al. ( 2025 ) | Randomized controlled trail | CIS patients randomized to high-dose vitamin D (100,000 IU biweekly) or placebo for 24 months; clinical and MRI outcomes assessed | High-dose vitamin D significantly reduced disease activity in early MS; supports its role as a safe adjunctive therapy |
| Bjornevik et al. ( 2022 ) | Prospective cohort study | > 10 million US military personnel; EBV seroconversion and serum NfL levels analyzed | EBV infections increases MS risk 32-fold; NfL rises after infection, supporting EBV as a leading casual factor |
| Choileáin et al. ( 2020 ) | Case-control study | 16S rRNA sequencing of gut microbiota and immune profiling (flow cytometry) in RRMS patients and controls | Reduced abundance of SCFA-producing bacteria is linked to immune dysregulation; SCFAs support Treg responses and limit inflammation, suggesting their deficiency contributes to MS pathogenesis |
| Takewaki et al. ( 2020 ) | Case-control study | Multi-omics analysis of gut microbiota (16S rRNA, metagenomics, metabolomics) in MS subtypes and controls | Gut microbiome alterations differ by MS stage; reduced SCFA production in RRMS and increased oxidative stress in SPMS suggest stage-specific mechanisms and therapeutic targets |
| Berer et al. ( 2017 ) | Translational study | Gut microbiota from MS-discordant twins analyzed (16S rRNA, metagenomics) and transferred to germ-free mice; EAE development and immune responses assessed | Microbiota from MS patients increases susceptibility to CNS autoimmunity; findings provide causal evidence linking gut microbiota to MS pathogenesis |
| Jangi et al. ( 2016 ) | Case-control study | 16S rRNA sequencing of gur microbiota (MS vs. controls); immune gene expression analysis | MS patients show altered gut microbiota associated with pro-inflammatory immune profiles; microbiome may serve as a biomarker and therapeutic target |
| Cosorich et al. ( 2017 ) | Case-control study | Gut mucosal microbiota (16S rRNA) and T cell subsets (flow cytometry) analyzed in RRMS patients and controls | Expansion of pro-inflammatory Th17 cells correlates with gut microbiota alterations; findings link dysbiosis to immune-mediated CNS autoimmunity in MS |
| Cox et al. ( 2021 ) | Translational study | 16S rRNA sequencing of gut microbiota in MS patients (RRMS, progressive) and controls; clinical correlations and EAE mouse model experiments | Specific microbiota profiles correlate with disease severity; Akkermansia is associated with milder MS and reduces inflammation in EAE |
| Peipert et al. ( 2025 ) | Experimental study | EAE mouse model with controlled microbiota; Akkermansia muciniphila colonization; microbiome, immune response, and SCFA analysis | Akkermansia effects are microbiome-dependent; under specific conditions it enhances Th17 responses and reduces SCFA, exacerbating CNS autoimmunity |
| Regen et al. ( 2021 ) | Experimental study | EAE mouse model with IL-17A/F knockout; microbiome analysis and reconstitution experiments | IL-17 regulates CNS autoimmunity indirectly via the gut microbiome; loss of IL-17 alters microbiota and reduces disease susceptibility |
| Ntranos et al. ( 2022 ) | Translational study | Metabolomic profiling of CFS and plasma in MS patients before/after DMF; in vitro neuronal assays | Microbial-derived metabolites induce neurotoxicity and axonal damage; DMF reduces these metabolites and is associated with improved neurodegenerative markers |
Conclusion
The collected evidence indicates that MS has a complex, multifactorial, and incompletely understood pathogenesis. Studies of the gut microbiome have demonstrated that patients with MS exhibit alterations in microbiota composition and function, which vary depending on clinical disease phenotype, inflammatory activity, and therapeutic interventions. The reproducibility of specific taxonomic changes across studies remains limited, likely reflecting differences in study populations, sampling procedures, and analytical methods. Increasing evidence suggests that the relevance of the microbiome is not limited solely to gut bacteria but also encompasses other microbial niches that may be associated local and peripheral immune responses. Mechanistic data suggest that alterations in microbiota composition correlate with immune gene expression and with the differentiation of effector T cell populations, particularly along the Th17/IL-17 axis. Evidence for direct mechanistic effects on CNS autoimmunity is derived largely from experimental models, whereas human studies remain predominantly associative. Host genetics may also contribute to these interactions, particularly through HLA class II polymorphisms associated with disease susceptibility and potentially with differences in gut microbiota composition. Furthermore, the presence of microbiome-derived metabolites in the systemic circulation and cerebrospinal fluid points to a potential role for gut-brain communication in neuroinflammatory processes.
In conclusion, current evidence supports an association between the microbiome, immune regulation, host genetics, and MS, but the direction and causal significance of these relationships remain unclear. Longitudinal and mechanistically informed studies in patients with MS are needed to determine whether microbiome alterations contribute to disease development and progression or occur as consequences of the disease and its treatment. A better understanding of these interactions may ultimately help clarify the potential diagnostic and therapeutic relevance of the microbiome in MS.
Abbreviations
Multiple sclerosis
Central nervous system
Blood–brain barrier
Relapsing-remitting multiple sclerosis
Secondary progressive multiple sclerosis
Primary progressive multiple sclerosis
Clinically isolated syndrome
Epstein-Barr virus
Body mass index
Cerebrospinal fluid
Short-chain fatty acid
Experimental autoimmune encephalomyelitis
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Acknowledgements
Funding This work was supported by project number SUPB.RN.26.006 financed by Jan Kochanowski University, Kielce, Poland.
Authors contributions
J.D., Z.S., I.K., and A.S. wrote the main manuscript text and prepared Table 1 . J.D. and I.K. prepared Figs. 1 and 2 . E.J. contributed to the revision and technical editing of the manuscript. W.A.B. contributed to the conception of the manuscript, supervised and critically revised manuscript. All authors reviewed the manuscript.
Funding
This work was supported by project number SUPB.RN.26.006 financed by Jan Kochanowski University, Kielce, Poland.
Data availability
No datasets were generated or analysed during the current study.
Declarations
Conflict of interest
The authors declare no conflict of interest.
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