Microbial functions in skin inflammation: a Mendelian randomization study

Abstract

Inflammatory skin diseases (ISDs) represent a significant global health burden, yet the role of the human microbiome in their pathogenesis remains unclear. This study employed a comprehensive two-sample Mendelian randomization (MR) framework to investigate potential causal associations between multi-site microbiota (3117 oral, 412 gut, and 150 skin microbial features) and five major ISDs: psoriasis, atopic dermatitis, acne, seborrheic dermatitis, and urticaria. Genetic instruments were selected from large-scale genome-wide association studies (GWAS) of microbiota composition and ISD outcomes. The inverse variance weighted (IVW) method served as the primary analytical approach, supplemented by MR-Egger regression, weighted median, and MR-PRESSO for sensitivity analyses. Multiple testing was controlled using the false discovery rate (FDR) method. Our analyses identified numerous suggestive associations between specific microbial taxa, metabolic pathways, and ISD risk. Notably, shared microbial signatures were observed across multiple ISDs, suggesting potentially shared microbiome-associated pathogenic pathways. These results provide genetic evidence supporting a role for the microbiome in ISD susceptibility and highlight potential microbial targets for future therapeutic development.

Supplementary Information

The online version contains supplementary material available at https://doi.org/10.1186/s13568-026-02094-6.

Introduction

The human body harbors a vast and diverse microbial ecosystem, with distinct communities colonizing the skin, oral cavity, and gastrointestinal tract. These microbial communities, collectively termed the microbiome, are active participants in host physiology, contributing to nutrient metabolism, immune maturation, and pathogen resistance (Belkaid et al. 2014). Disruption of these communities, a state known as dysbiosis, has been increasingly implicated in the pathogenesis of a wide range of chronic inflammatory conditions, including inflammatory skin diseases (ISDs) (Yang et al. 2022). The skin, the body's largest organ and primary interface with the external environment, supports a rich commensal microbiota that is essential for maintaining epidermal barrier integrity and educating the cutaneous immune system (Harris et al. 2022). Simultaneously, the gut microbiota, a metabolically active community, exerts systemic immunomodulatory effects beyond the intestinal lumen, a concept known as the 'gut-skin axis' (De et al. 2021; Jimenez et al. 2025).

The mechanisms by which the microbiome influences skin health are multifaceted and converge on several key biological processes. First, microbial communities are critical regulators of host barrier function. Commensal skin bacteria modulate keratinocyte signaling, for example through the aryl hydrocarbon receptor (AhR), to fortify the epidermal barrier (Uberoi et al. 2021). In the gut, a healthy microbiota maintains intestinal permeability; its disruption can facilitate the translocation of microbial components such as lipopolysaccharide (LPS) into the systemic circulation, triggering inflammatory cascades that manifest in the skin (Sikora et al. 2021). Second, the microbiota is a master regulator of both innate and adaptive immunity. Skin commensals such as Staphylococcus epidermidis prime resident immune cells, including dendritic cells and T lymphocytes, to mount effective responses against invading pathogens (Yamazaki et al. 2017; Brown et al. 2020). Systemically, the gut microbiota shapes the differentiation of T helper cell subsets, critically influencing the balance between pro-inflammatory Th17 and anti-inflammatory regulatory T cell (Treg) responses that are central to ISD pathogenesis (Lunjani et al. 2021). Third, microbial metabolites serve as key signaling molecules in the host-microbe dialogue. Short-chain fatty acids (SCFAs), particularly butyrate, produced by bacterial fermentation of dietary fiber in the gut, exert potent anti-inflammatory and barrier-protective effects (Trompette et al. 2022). Tryptophan metabolites generated by skin and gut commensals act as ligands for AhR, modulating cutaneous immune responses (Yu et al. 2019). Conversely, pro-inflammatory metabolites can exacerbate disease, underscoring the complex metabolic interplay between host and microbe (Stec et al. 2023).

While observational studies have identified associations between microbial dysbiosis and ISDs, establishing causality remains a formidable challenge due to confounding factors such as diet, medication use, lifestyle, and host genetics. Mendelian randomization (MR) offers a robust quasi-experimental approach to strengthen causal inference by leveraging genetic variants as instrumental variables (IVs) for an exposure of interest (Li et al. 2022). This study employs a comprehensive two-sample MR framework to systematically evaluate the potential causal associations between the microbiota of the skin, oral cavity, and gut and the risk of five prevalent ISDs: psoriasis, atopic dermatitis, acne vulgaris, seborrheic dermatitis, and urticaria. Crucially, our analysis moves beyond taxonomic enumeration to interrogate the functional and metabolic implications of these associations. By adopting this function-oriented perspective, we aim to provide an integrated understanding of the cross-body site microbiome in dermatological health and to identify actionable microbial and metabolic targets for future diagnostic and therapeutic development.

Materials and methods

Study design

This study employed a two-sample MR analysis to investigate the potential causal associations between 3117 oral microbiota, 412 intestinal microbiota and metabolites, 150 skin microbiota, and five inflammatory skin diseases (psoriasis, atopic dermatitis, acne, seborrheic dermatitis, urticaria). Multiple sensitivity analyses were conducted to ascertain the reliability of the results, as illustrated in Fig. 1.

Fig. 1.

Overview of the overall MR design

Data sources

Comprehensive information regarding the microbiota and inflammatory skin disease genome-wide association study (GWAS) data is provided in Tables 1 and 2, with detailed descriptions of the data sources available in Additional file 1.

Table 1.

Main Information of Microbial GWAS Data

Types of microbiota	Country/cohort	Sequencing methods and platforms	Sample size	Number of microbial features	Ethics review committee	Data source/accession numbers
Skin microbiota	Germany/PopGen cohortKORA FF4 cohort	16 s rRNA/Illumina MiSeq	647	150	Medical Faculty of Kiel University and Bavarian Med ical Association	GWAS Catalog https://www.ebi.ac.uk/gwas/ Accession: GCST90133164–GCST90133313
Gut microbiota	Netherlands/LifeLines cohort	Metagenomic sequencing/Illumina HiSeq	7738	412	University Medical Center Groningen	GWAS Catalog https://www.ebi.ac.uk/gwas/ Accession: GCST90027446–GCST90027857
Oral microbiota	China/4D-SZ cohort	Metagenomic sequencing/BGISEQ-500	2984	3117	Beijing Genomics institution-Shenzhen	China National GeneBank https://db.cngb.org/ Accession: CNP0001664

Table 2.

Main information of GWAS data for inflammatory skin diseases

Disease	Country/Poplution	ICD diagnostic criteria	Sample size	Number of SNPs	Ethics review committee	Data source/accession numbers
Psoriasis	Finland/European	ICD-10 L40	407,846	21,306,286	The Coordinating Ethics Committee of the Helsinki and Uusimaa Hospital District	FinnGen R10 https://r10.risteys.finngen.fi/
Atopic dermatitis	Finland/European	ICD-10 L20	382,254	21,305,750		FinnGen R10 https://r10.risteys.finngen.fi/
Acne	Finland/European	ICD-10 L70	397,350	21,306,099		FinnGen R10 https://r10.risteys.finngen.fi/
Urticaria	Finland/European	–	409,391	21,306,309		FinnGen R10 https://r10.risteys.finngen.fi/
Seborrheic dermatitis	Finland/European	ICD-10 L21	369,995	21,305,446		FinnGen R10 https://r10.risteys.finngen.fi/
Psoriasis	India/Asian	–	4310	8,792,205	–	IEU GWAS https://gwas.mrcieu.ac.uk/ Accession: ebi-a-GCST90019015
Atopic dermatitis	Japan/Asian	–	168,103	12,453,030	The Institute of Medical Sciences, the University of Tokyo and RIKEN Center for Integrative Medical Sciences	BioBank Japan (IEU GWAS) https://gwas.mrcieu.ac.uk/ Accession: ebi-a-GCST90018564
Urticaria	Japan/Asian	–	172,083	12,453,869		BioBank Japan (IEU GWAS) https://gwas.mrcieu.ac.uk/ Accession: ebi-a-GCST90018716

Selection of instrumental variables

The selection of instrumental variables involved the following steps: (1) Screening for instrumental variables associated with microbial communities, applying a correlation threshold of P < 1 × 10^–5. (2) SNPs exhibiting linkage disequilibrium among the instrumental variables were removed, with parameters set at r² < 0.001 and kb < 10,000. (3) Extracting the relevant instrumental variables from the GWAS data pertaining to skin diseases and excluding palindromic SNPs. (4) Calculating the F statistic and discarding weak instrumental variables with an F statistic < 10. The formula used for calculating F can be found in Additional file 1.

Mendelian randomization analysis

This study primarily utilized inverse variance weighting (IVW), MR Egger regression, the weighted median (WM), the weighted mode, and the simple mode to analyze the estimated effects between exposure factors and outcome factors. IVW is a conventional MR analysis model that integrates the assessment of estimated effects across multiple genetic variations while minimizing the influence of heterogeneity and pleiotropy. When all included SNPs are valid and independent, IVW provides the most accurate results (Lin et al. 2021). Consequently, the P value from the IVW analysis was designated the primary indicator for evaluation, with other methods serving as supplementary measures for assessing the MR effect size. The consistency of the effect size (β value) direction across the different methods corroborating the IVW findings underscores the robustness of the results. The Wald ratio method was employed to estimate the potential causal association between exposure and outcomes via a single instrumental variable (Figs. 2, 3, 4, 5, 6).

Fig. 2.

Forest plot: microbiota and acne

Fig. 3.

Forest plot: microbiota and seborrheic dermatitis

Fig. 4.

Forest plot: microbiota and atopic dermatitis

Fig. 5.

Forest plot: microbiota and psoriasis

Fig. 6.

Forest plot: microbiota and urticaria

Sensitivity analysis

The assessment of heterogeneity was conducted via Cochran's Q test (Niu et al. 2020), whereas pleiotropy was evaluated via the MR-PRESSO test and the intercept term from MR Egger regression. P value > 0.05 indicates the absence of heterogeneity or pleiotropy in the findings (Yin et al. 2022).

Statistical analysis

All the analytical methods utilized in this study were implemented through the two-sample MR package in R software (version 4.2.1), with a significance level of α = 0.05. The results are presented as odds ratios (ORs) with 95% confidence intervals (95% CI) and corresponding P values. False discovery rate (FDR) correction was applied to adjust for multiple testing on the IVW results, where P_IVW < 0.05 and P_FDR < 0.05 signify a robust potential causal association between microbiota and the risk of skin diseases, whereas P_IVW < 0.05 and P_FDR > 0.05 suggest a suggestive causal association.

Results

Microbiota and psoriasis

Four skin microbial taxa were identified as genetically associated with psoriasis risk. Micrococcus exhibited the strongest protective estimated effect (OR = 0.966, 95% CI 0.945–0.988, P_IVW = 0.002, P_FDR = 0.189), followed by Acinetobacter. Conversely, Lactobacillus showed a positive association with psoriasis risk (OR = 1.032, 95% CI 1.006–1.058, P_IVW = 0.014, P_FDR = 0.526). In the gut, five microbial taxa and twelve metabolic pathways were genetically linked to psoriasis. Notably, the reductive tricarboxylic acid (TCA) cycle I and L-tyrosine biosynthesis pathways were identified as potential mediators, with flavin biosynthesis representing the most pronounced hazardous metabolic pathway (OR = 1.180, 95% CI 1.024–1.359, P_IVW = 0.022, P_FDR = 0.827). Among 128 oral microbial species genetically associated with psoriasis, Prevotella was the most protective (OR = 0.436, 95% CI 0.200–0.951, P_IVW = 0.037), while Tannerella was the strongest risk factor (OR = 2.433, 95% CI 1.332–4.447, P_IVW = 0.004).More details are shown in Fig. 5.

Microbiota and atopic dermatitis

MR analysis suggested associations between seven skin microbial communities and the risk of atopic dermatitis. Corynebacterium exhibited the strongest protective estimated effect (OR = 0.972, 95% CI 0.947–0.997, P_IVW = 0.031, P_FDR = 0.933), whereas Haemophilus presented the most pronounced positive estimated effect (OR = 1.012, 95% CI 1.003–1.020, P_IVW = 0.006, P_FDR = 0.457). Additionally, 3 gut microbial taxa and ten metabolic pathways were found to be associated with the risk of atopic dermatitis, with fucose degradation being the most strongest hazardous pathway (OR = 1.115, 95% CI 1.015–1.224, P_IVW = 0.023, P_FDR = 0.958). In the oral microbiota, 97 species were genetically associated with atopic dermatitis risk. Campylobacter was the most beneficial for reducing risk (OR = 0.663, 95% CI 0.478–0.920, P_IVW = 0.014), whereas Treponema was the most strongest risk factor (OR = 1.566, 95% CI 1.187–2.066, P_IVW = 0.002).More details are shown in Fig. 4.

Microbiota and acne vulgaris

Nine skin microbial taxa were genetically associated with acne risk. Among the pathogenic bacteria, Burkholderiales exhibited the most pronounced estimated effect (OR = 1.075, 95% CI 1.014–1.140, P_IVW = 0.015, P_FDR = 0.613). Moreover, 8 bacterial genera and 8 metabolic pathways in the gut microbiota were identified as genetically associated with acne risk. An increase in Collinsella and Pseudoflavonifractor was associated with a decreased risk of acne, whereas elevated levels of Lactobacillus delbrueckii and Bilophila wadsworthii correlated with an increased risk. The metabolic pathways associated with acne risk predominantly included peptidoglycan biosynthesis and L-rhamnose degradation.More details are shown in Fig. 2.

Microbiota and seborrheic dermatitis

Five skin microbial taxa showed genetically predicted associations with the risk of seborrheic dermatitis. Paracoccus was identified as the taxon with the most pronounced protective effect (OR = 0.932, 95% CI 0.879–0.988, P_IVW = 0.018, P_FDR = 0.451). Additionally, 4 gut microbial taxa and 6 metabolic pathways, including L-methionine biosynthesis and galactonate degradation, showed genetically predicted associations with the risk of this disease.More details are shown in Fig. 3.

Microbiota and urticaria

A total of 8 skin microbial taxa were identified as genetically associated with the risk of developing urticaria. Propionibacterium granulosum had the most pronounced positive estimated effect (OR = 1.056, 95% CI 1.023–1.090, P_IVW = 0.0008, P_FDR = 0.125). Additionally, 6 bacterial genera and nine metabolic pathways associated with the gut microbiota were found to be correlated with the risk of urticaria. A total of 127 species of oral microbiota were identified as genetically associated with the risk of urticaria. Pauljensonia was the most beneficial oral taxon for reducing urticaria risk (OR = 0.710, 95% CI 0.524–0.962, P_IVW = 0.027), whereas Lachnoanaerobaculum was the strongest pathogenic risk factor (OR = 1.280, 95% CI 1.097–1.493, P_IVW = 0.002).More details are shown in Fig. 6.

Across all five diseases, microbial function showed consistent patterns across different body sites. Core metabolic pathways—including amino acid biosynthesis, SCFA-related metabolism, and carbohydrate degradation—were consistently implicated across analyses of gut, oral, and skin microbiota, suggesting that these functional activities may represent key nodes in the gut-skin axis, irrespective of the specific taxa performing them. Detailed results, including odds ratios and sensitivity analyses for all associations, are available in Additional file 2: Tables S1-S3.

Sensitivity analysis

The sensitivity analysis demonstrated the presence of heterogeneity and horizontal pleiotropy in the metabolic pathways associated with psoriasis and guanosine nucleoside degradation. Furthermore, significant heterogeneity and horizontal pleiotropy were observed in the findings related to acne and the skin microbiota, particularly involving S. salivarius and Clostridiales. Similar patterns of heterogeneity and horizontal pleiotropy were identified in the degradation results for atopic dermatitis, specifically concerning the skin microbiota, including Corynebacterium, Proteobacteria, and metabolic pathways associated with pyrimidine ribonucleotides. Additionally, the results for seborrheic dermatitis and Clostridiales also revealed horizontal pleiotropy, as detailed in Additional file 2: Tables S1-S3.

Discussion

In this study, we employed a comprehensive Mendelian randomization approach to evaluate the potential causal associations linking the microbiota of the skin, gut, and oral cavity to the risk of five prevalent inflammatory skin diseases. By shifting the analytical focus from taxonomic cataloging to functional and metabolic pathway analysis, our findings suggest convergent mechanisms that may underpin the gut-skin axis and provide a framework for understanding microbial contributions to cutaneous inflammation from an applied microbiology perspective.

Convergent metabolic pathways link multi-site microbiota to skin inflammation

One finding of this study is that the potential influence of the microbiome on inflammatory skin diseases may be better understood not through the lens of individual taxa, but through the metabolic functions these organisms perform. This functional perspective aligns with the growing recognition that microbial communities exhibit substantial functional redundancy, whereby phylogenetically distinct organisms can perform equivalent metabolic roles (Stec et al. 2023; Ferrara et al. 2024). Our results consistently implicated core metabolic functions—including the TCA cycle, amino acid biosynthesis (L-tyrosine, L-methionine), carbohydrate degradation (fucose, rhamnose), and SCFA production—as potential mediators of skin inflammation. This convergence across body sites is consistent with a model in which different microbial communities at the skin, gut, and oral niches contribute to the same pathological processes by modulating a shared set of host-interactive metabolic pathways.

The observed association between psoriasis risk and both gut Bacteroides and the TCA cycle pathway provides a hypothesis regarding the metabolic underpinnings of this disease. Psoriasis is characterized by aberrant epidermal differentiation and chronic dermal inflammation, processes that are accompanied by profound metabolic reprogramming in keratinocytes and infiltrating immune cells (Sarandi et al. 2023). The TCA cycle is central to this reprogramming, as it governs cellular bioenergetics and provides biosynthetic precursors essential for keratinocyte differentiation (Nakamizo et al. 2024). A reduction in TCA cycle activity, as suggested by our MR findings, could hypothetically result in insufficient energy supply for keratinocytes, potentially impairing their normal differentiation and contributing to the hyperproliferative phenotype characteristic of psoriatic plaques. Our data are consistent with a role of gut microbial function in this host pathology, suggesting the gut microbiome as a potential upstream regulator of epidermal metabolism. Consistent with this interpretation, alterations in the Firmicutes-to-Bacteroidetes ratio have been widely documented in psoriasis patients, with a decrease in Bacteroidetes being a reproducible finding across multiple cohorts (Sikora et al. 2020) (Codoñer et al. 2018).

The identification of the skin commensal Micrococcus as protective against psoriasis is consistent with the established role of certain skin commensals in maintaining cutaneous homeostasis. Micrococcus species have been reported to inhibit the activity of Staphylococcus aureus, thereby reducing the risk of secondary skin infections that can exacerbate inflammatory conditions (Khayyira et al. 2020). Furthermore, culture filtrates of Micrococcus luteus have been demonstrated to upregulate genes associated with skin hydration, hyaluronic acid synthesis, and barrier function in keratinocyte models, indicating a direct role in promoting epidermal health (Heo et al. 2024). The concurrent identification of L-tyrosine biosynthesis as a potential pathway associated with psoriasis risk provides a novel microbial perspective on the well-established IL-23/IL-17 inflammatory axis. IL-23 signaling through tyrosine kinase 2 (TYK2) is a critical mediator of chronic inflammation in psoriasis (Martin et al. 2023), and tyrosine kinase inhibitors have demonstrated clinical efficacy in this disease (Shalabi et al. 2022). Our findings raise the hypothesis that gut microbial production of L-tyrosine may serve as a substrate fueling TYK2-mediated inflammatory cascades, suggesting a potential link between gut microbial metabolism and cutaneous inflammation that requires experimental validation.

In atopic dermatitis, the identification of skin Corynebacterium as protective and gut Alistipes as a risk factor, alongside the implication of fucose degradation and polyamine biosynthesis pathways, is consistent with a multi-site, metabolically influenced pathology. Corynebacterium species are abundant commensals of healthy skin and have been shown to modulate cutaneous immune responses in a context-dependent manner, with low-level colonization promoting the activation of regulatory immune cell populations (Ridaura et al. 2018). The protective role of Corynebacterium identified in our analysis is consistent with observations that healthy skin harbors a greater diversity of Corynebacterium species compared with lesional atopic dermatitis skin (Tham et al. 2024). Fucose degradation, identified as a hazardous pathway, may deplete fucoidan, a sulfated polysaccharide with demonstrated anti-inflammatory properties in atopic dermatitis models, including inhibition of Staphylococcus aureus adhesion (Park et al. 2021), suppression of IgE production (Iwamoto et al. 2011), and promotion of probiotic colonization (Yang et al. 2021). The role of tryptophan metabolism in atopic dermatitis is gaining increasing recognition, as microbial tryptophan catabolites, particularly indole-3-aldehyde (IAld), act as potent ligands for the aryl hydrocarbon receptor (AhR), attenuating cutaneous inflammation (Yu et al. 2019) (Huang et al. 2024).

For acne vulgaris, our findings suggesting that skin Proteobacteria and gut Lactobacillus delbrueckii are potential risk factors, while gut Collinsella may be protective, can be interpreted through the lens of microbial metabolite production and immune modulation. The elevated abundance of Proteobacteria on acne-affected skin has been documented by high-throughput sequencing studies (Dreno et al. 2017), and administration of Lactobacillus plantarum has been shown to ameliorate acne symptoms, partly through reducing the proportion of Proteobacteria on the skin surface (Kim et al. 2021). Collinsella, a member of the phylum Actinobacteria, plays a role in maintaining gut microbial homeostasis; metabolites derived from actinomycetes have demonstrated capacity to target acne-associated pathogens, including Staphylococcus aureus and methicillin-resistant strains (De et al. 2022). The peptidoglycan biosynthesis pathway, which was negatively correlated with acne risk, is responsible for synthesizing key bacterial cell wall components; acidic peptidoglycan has been shown to activate immune cells such as CD3 − and CD69+ cells, thereby accelerating the clearance of inflammation-inciting bacterial antigens (Wilson et al. 2015). The rhamnose degradation pathway links to the beneficial effects of Lactobacillus rhamnosus, which has been demonstrated to mitigate acne lesions through inhibition of insulin signaling genes and downregulation of inflammatory cytokines including IL-1β, IL-6, and TNF-α (Huang et al. 2023) (Fabbrocini et al. 2016).

Our analysis of seborrheic dermatitis identified Acinetobacter and Salivarius as skin-associated risk factors, with gut Veillonella and Roseburia also contributing to increased disease risk. Acinetobacter is a highly pathogenic gram-negative bacterium characterized by unique lipid profiles, including cardiolipin and monolysocardiolipin (Lopalco et al. 2017). The bioactive lipids secreted by Acinetobacter can activate inflammatory signaling pathways (Tiku et al. 2022), and cardiolipin has been demonstrated to activate antigen-presenting cells via TLR2-PI3K-PKN1-AKT/p38-NF-κB signaling (Cho et al. 2018). Veillonella, a lipopolysaccharide-producing bacterium, has been associated with gut inflammation and can ectopically colonize the intestine under inflammatory conditions (Rojas et al. 2022). The LPS produced by Veillonella has been shown to induce skin inflammation in experimental models (Sveen et al. 1977), suggesting a plausible hypothesis by which gut dysbiosis may contribute to seborrheic dermatitis. The metabolic pathway associated with L-methionine biosynthesis, which was negatively correlated with disease risk, may exert protective effects through its antioxidant properties, as L-methionine supplementation has been shown to protect against oxidative stress and mitochondrial dysfunction (Catanesi et al. 2021).

In urticaria, Propionibacterium granulosum was identified as a significant skin-associated risk factor, consistent with clinical observations of elevated Propionibacterium abundance in the skin lesions of children with acute urticaria (Orlova et al. 2022). P. granulosum produces porphyrins with pro-inflammatory properties that may exacerbate cutaneous inflammation (Barnard et al. 2020). The identification of Corynebacterium as a risk factor for urticaria, in contrast to its protective role in atopic dermatitis, illustrates the context-dependent nature of host-microbe interactions; low levels of Corynebacterium have been shown to activate Vγ4 + γδT17 cells, which produce IL-17A and contribute to skin inflammation (Ridaura et al. 2018). Furthermore, plasma levels of L-lysine are elevated in patients with chronic urticaria (Jian et al. 2024), and poly-L-lysine has the capacity to activate mast cells, leading to histamine release (Kocak et al. 2022), suggesting a plausible hypothesis for the observed association between polyamine biosynthesis and urticaria risk. Diamine oxidase (DAO), involved in polyamine degradation, has been positively correlated with IgE levels in chronic urticaria patients (Daschner et al. 2015).

The oral cavity as an underappreciated reservoir of inflammatory triggers for skin disease

A notable contribution of this study is the systematic identification of potential causal associations between the oral microbiota and inflammatory skin diseases, supporting the concept of an 'oral-skin axis' that extends beyond the well-characterized gut-skin axis. The association of oral pathogens such as Tannerella with psoriasis and Lachnoanaerobaculum with urticaria suggests that the oral cavity serves as a significant and underappreciated reservoir of inflammatory triggers for dermatological conditions. Pathogens or their metabolites, particularly LPS from gram-negative bacteria, can translocate from the oral cavity, enter the systemic circulation, and trigger inflammatory responses that manifest in the skin (Kleinstein et al. 2020; Peng et al. 2022). In support of our findings, Fan and colleagues reported that patients with psoriasis and psoriatic arthritis exhibit reduced levels of Prevotella in the oral cavity compared with healthy individuals, suggesting that this decrease may contribute to disease exacerbation (Fan et al. 2024). The oral microbiome has been implicated in the pathogenesis of psoriasis, with psoriasis patients frequently suffering from streptococcal infections (Macklis et al. 2020; De et al. 2020), and specific IgA and CLA + T-cell IL-17 responses to Streptococcus pyogenes have been documented in psoriasis patients (De et al. 2020). Furthermore, psoriasis patients have been reported to suffer from worse periodontal status, including more severe gingivitis and increased alveolar bone loss (Qiao et al. 2019), reinforcing the bidirectional relationship between oral health and systemic skin inflammation.

In atopic dermatitis, our analysis identified potential causal associations between oral Streptococcus, Lachnospiraceae, Neisseria, and Veillonella and disease risk. Notably, Streptococcus exhibited both risk-conferring and protective roles depending on the species, underscoring the importance of strain-level resolution in microbiome research. Streptococcus has been found to be enriched in the intestinal tracts of infants with atopic dermatitis (Kang et al. 2021), and topical application of a Streptococcus postbiotic emollient has demonstrated efficacy in improving mild-to-moderate atopic dermatitis in a randomized controlled trial (Kim et al. 2024). Supplementation with Lachnospiraceae has shown therapeutic effects on atopic dermatitis, likely through regulation of the host immune system and modulation of the gut microbiota (Kim et al. 2019). These findings collectively suggest that the oral microbiota may represent a clinically relevant and therapeutically targetable component of the microbiome-skin disease axis.

Implications for microbiome-based therapeutic strategies

From an applied microbiology perspective, the analytical framework from our MR analysis generates hypotheses that may inform targeted microbiome modulation strategies for inflammatory skin diseases. The identification of protective taxa—such as skin Acinetobacter and Micrococcus for psoriasis, skin Corynebacterium for atopic dermatitis, and gut Collinsella for acne—provides a scientific rationale for their investigation as candidate next-generation probiotics (Paetzold et al. 2019). More importantly, the implicated metabolic pathways offer novel therapeutic targets that transcend the limitations of single-taxon interventions. Furthermore, while MR provides stronger evidence for causality than observational studies, MR findings should not be equated with definitive proof of causal mechanisms. The associations identified in this study represent genetically predicted effects that require experimental validation through in vitro and in vivo studies to confirm the underlying biological mechanisms.

Several therapeutic modalities emerge from our findings. First, supplementation with SCFA-producing bacteria or provision of prebiotic fibers that fuel their growth could systemically increase anti-inflammatory metabolites such as butyrate (Polak et al. 2021). Butyrate has been demonstrated to enhance skin barrier function by directly shaping keratinocyte metabolism and eliciting mitochondria-dependent differentiation programs (Trompette et al. 2022), and to inhibit Staphylococcus aureus-aggravated dermatitis through histone deacetylase 3 (HDAC3) inhibition (Luo et al. 2023). Second, postbiotic approaches utilizing specific microbial metabolites represent a promising therapeutic avenue. The administration of indole-3-aldehyde, a tryptophan metabolite produced by skin microbiota, has been shown to attenuate inflammation in atopic dermatitis patients via AhR activation (Yu et al. 2019). Our findings linking tryptophan metabolism to disease risk strengthen the rationale for such postbiotic therapies. Third, for severe and recalcitrant disease, fecal microbiota transplantation (FMT) represents a powerful tool to reset the entire gut microbial ecosystem. A recent randomized, double-blind controlled trial demonstrated that FMT was safe and effective in moderate-to-severe adult patients with atopic dermatitis, with treatment altering gut microbiota compositions and functions (Wu et al. 2024). Our data, which are consistent with a role of gut microbial function in skin inflammation, provide a hypothesis-generating rationale for the clinical efficacy of FMT in dermatological conditions (Zhao et al. 2025). By focusing on restoring microbial function rather than merely altering taxonomic composition, these strategies hold promise for more robust and durable clinical outcomes (Gilbert et al. 2025; Parhizkar et al. 2025).

Methodological considerations and limitations

While Mendelian randomization strengthens causal inference compared to observational studies, it does not establish definitive causality nor provide direct mechanistic evidence. The findings presented in this study should therefore be interpreted as indicative of potential causal relationships under specific assumptions, and require experimental validation. Several methodological limitations inherent to the application of MR in microbiome research also warrant careful consideration (Cupido et al. 2024). First, the issue of pleiotropy—where a genetic variant influences the outcome through a pathway independent of the exposure—represents a major concern. Although we employed statistical methods including MR-Egger regression and MR-PRESSO to detect and mitigate pleiotropy, its complete absence cannot be guaranteed. The complex and interconnected nature of microbial ecosystems means that a genetic variant influencing one bacterium could readily affect others, potentially violating the exclusion restriction assumption. Indeed, our sensitivity analyses revealed heterogeneity and horizontal pleiotropy in several associations, including those involving psoriasis and guanosine nucleoside degradation, and acne with S. salivarius, which should be interpreted with appropriate caution.

Second, the resolution and maturity of microbiome GWAS data impose important constraints on the precision of MR analyses. Many associations are resolved only at the genus or family level, rather than the species or strain level where functional differences are often most pronounced (Feng et al. 2023). Our finding that different Streptococcus species exert opposing effects on skin disease risk exemplifies this limitation and underscores the need for higher-resolution microbial GWAS. Third, measurement error and the complexity of the exposure present significant challenges. The composition of the microbiome is dynamic and influenced by numerous environmental factors, including diet, medication, and lifestyle, that are not fully captured by host genetics. Genetic variants typically explain only a small fraction of the variance in microbial abundance, potentially leading to weak instrument bias and underpowered analyses (Cupido et al. 2024).

Fourth, the current analysis was primarily conducted using data from European populations, which may limit the generalizability of our findings to other ethnic groups. The lack of GWAS data on seborrheic dermatitis and acne in Asian populations restricted our analysis to only three inflammatory skin conditions in relation to the oral microbiota. Future studies incorporating diverse populations are essential to validate these potential causal associations globally. Fifth, all reported associations were nominally significant (PIVW < 0.05) but none survived FDR correction (all PFDR > 0.05), reflecting the substantial multiple-testing burden. These findings should therefore be interpreted as hypothesis-generating.Finally, while microbiota-related genetic variations serve as instrumental variables to simulate long-term exposure effects, the dynamic nature of the microbiome over a lifetime may not be fully captured by genetic proxies, and changes in dietary content and patterns may influence the results in ways not accounted for by the current analytical framework.

Conclusion

This study provides genetic evidence consistent with the involvement of the skin, oral, and gut microbiota in the pathogenesis of inflammatory skin diseases. By shifting the analytical focus from taxonomy to function, we identify convergent metabolic mechanisms—including the TCA cycle, amino acid biosynthesis, SCFA metabolism, and tryptophan catabolism—that operate across body sites, offering an integrated understanding of the gut-skin and oral-skin axes. Our findings may inform the development of targeted microbiome modulation strategies, encompassing probiotics, prebiotics, postbiotics, and fecal microbiota transplantation, as candidate therapeutic approaches for these prevalent conditions. We also emphasize the inherent methodological limitations of MR in microbiome research and advocate for critical interpretation of the results. Future research should prioritize higher-resolution microbial GWAS, validation in ethnically diverse populations, and integration with experimental studies to translate these genetically informed insights into clinical practice.

Author contributions

Yujie Yang: Writing – original draft, Conceptualization. Yiyuan Zhong: Writing – Methodology, Formal analysis. Peng Wu: Writing – original draft, Project administration. MingXuan Li & Jingyi Cai & Xuwei Zheng: Project administration, Methodology, Formal analysis. Haiming Chen: Funding acquisition, Supervision.Yu Teng: Funding acquisition, Supervision.

Funding

This study was supported by grants from the National Project for Joint Development of Traditional Chinese Medicine Science and Technology (No: GZY-KJS-GD-2025-063); the Research Fund of Guangdong Provincial Hospital of Chinese Medicine (Nos. ZH2025QT07 and QZ2025ZZ34); the National Clinical Collaboration Project on Integrated Traditional Chinese and Western Medicine for Major Difficult and Intractable Diseases (No: ZDYN-2024-A-020); the National Natural Science Foundation of China (No. U23A6012); Shenzhen Natural Science Foundation (NO:JCYJ20250604190722028).

Data availability

The original contributions presented in the study are included in the article/Supplementary Materials, and further inquiries can be directed to the corresponding authors.

Declarations

Ethics approval and consent to participate

This research utilized publicly accessible data. Each individual study within the GWAS was approved by the appropriate Institutional Review Board, and the participants or their authorized representatives provided informed consent. No additional ethical approval was needed.

Consent for publication

All authors agree to publish this study.

Competing interests

The authors declare no competing interests.