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References Microbiome Signatures identifies and validates condition-specific microbiome shifts and interventions to accelerate clinical translation. Our multidisciplinary team supports clinicians, researchers, and innovators in turning microbiome science into actionable medicine.
Rheumatoid Arthritis
Rheumatoid arthritis (A) is a systemic autoimmune disease marked by chronic joint inflammation, synovitis, and bone erosion, driven by Th17 imbalance, excessive L-17, NF-α, and L-1 production, and macrophage activation. Emerging evidence links microbial dysbiosis and heavy metal exposure to A, [1][2] with gut microbiota influencing autoimmune activation via Toll-like receptor (LR) signaling, inflammasome activation, […]
Karen Pendergrass
Overview
Rheumatoid arthritis (RA) is a systemic autoimmune disease marked by chronic joint inflammation, synovitis, and bone erosion, driven by Treg/Th17 imbalance, excessive IL-17, TNF-α, and IL-1 production, and macrophage activation. Emerging evidence links microbial dysbiosis and heavy metal exposure to RA, [1][2] with gut microbiota influencing autoimmune activation via Toll-like receptor (TLR) signaling, inflammasome activation, and molecular mimicry, contributing to systemic immune dysfunction.
Associated Conditions
Conditions such as periodontitis, autoimmune thyroid disorders (Hashimoto’s, Graves’), multiple sclerosis (MS), and inflammatory bowel disease (IBD). RA is also linked to nonalcoholic fatty liver disease (NAFLD), fibromyalgia, and chronic fatigue syndrome (CFS). These associations highlight RA’s systemic complexity beyond joint inflammation.
Causes
Rheumatoid arthritis (RA) is a complex, multifactorial disease influenced by genetic predisposition, immune dysregulation, environmental exposures, and metabolic factors. While traditional theories emphasize the role of HLA-DR4 and HLA-DR1 genetic risk factors, along with autoantibody production and inflammatory cytokines such as TNF-α, IL-6, and IL-1β, a more holistic approach integrates emerging insights into microbial-metal interactions and their contribution to disease progression. Heavy metal dysregulation, in particular, has been implicated in immune dysfunction, oxidative stress, and the disruption of gut and oral microbiota, which collectively exacerbate RA pathogenesis.
Primer
Microbial-metal interactions play a significant role in the pathogenesis of rheumatoid arthritis (RA), with heavy metal dysregulation contributing to immune dysregulation and oxidative stress. High soil copper (Cu) exposure has been correlated with increased inflammation in RA patients, with Cu levels positively associated with erythrocyte sedimentation rate (ESR), platelet count, and disease activity (DAS28). [3] Lead (Pb) and cadmium (Cd) further exacerbate immune dysfunction, with Cd inhibiting superoxide dismutase, thereby reducing antioxidant defenses and increasing joint damage. [4][5] Elevated nickel (Ni) levels in RA patients have been linked to inflammasome activation, while increased chromium (Cr) concentrations affect immune tolerance and oxidative stress. [6] Additionally, microbial dysbiosis influences metal homeostasis, as Porphyromonas gingivalis enhances metal-driven citrullination, accelerating autoimmunity. [7] Gut microbial shifts, particularly Prevotella overgrowth and Akkermansia depletion, further impact metal absorption and immune function, reinforcing the intricate relationship between heavy metal exposure, microbial imbalances, and RA pathogenesis. [8]
Metal Homeostasis in RA
| Metal | Mechanism |
|---|---|
| Copper (Cu) | Promotes IL-6, TNF-α, neutrophil activation. [9] |
| Lead (Pb) | Induces ROS, disrupts immune tolerance. [10] |
| Cadmium (Cd) | Inhibits SOD, increases oxidative stress. [11] |
| Nickel (Ni) | Induces IL-1β, Th17 responses. [13] |
| Chromium (Cr) | Alters mitochondrial function, immune suppression. [14] |
Microbiome Signature: Rheumatoid Arthritis
Major Microbial Associations
Major Microbial Associations in RA patients:
| Increased Microbes (Pathobionts) | Decreased Microbes (Protective) & Viruses |
|---|---|
| Prevotella dentalis | Rothia dentocariosa |
| Prevotella denticola | Faecalibacterium prausnitzii |
| Treponema dentalis | Granulicatella |
| Selenomonadales | Veillonella rogosae |
| Selenomonas | Lactobacillus gasseri |
| Prevotella | |
| Epstein-Barr virus (EBV) | |
| Actinomyces | |
| Tannerella | |
| Treponema |
Research Feed
Role of Some Heavy Metals in Rheumatoid Arthritis
This study explored the association between rheumatoid arthritis and heavy metal exposure, identifying a significant deficiency of copper in RA patients. No significant correlations were found for zinc, cobalt, lead, or nickel. The findings suggest that copper deficiency may play a role in RA, warranting further research on trace metals in autoimmune diseases.
What was studied?
This study investigated the association between heavy metal concentrations and rheumatoid arthritis (RA). Specifically, it examined the serum levels of zinc (Zn), cobalt (Co), lead (Pb), nickel (Ni), and copper (Cu) in RA-positive and RA-negative individuals. The study also analyzed variations in metal levels based on sex and two age groups (below 35 years and 35 years and above) to determine if these factors influenced the relationship between heavy metal exposure and RA.
Who was studied?
The study included blood samples from patients suspected of having RA, collected from diagnostic laboratories in Sargodha, Pakistan. The participants were grouped based on their RA status (RA-positive and RA-negative), sex, and age category. Serum metal concentrations were analyzed using atomic absorption spectrophotometry (AAS), and statistical comparisons were made using a two-sample t-test to determine differences between groups.
Most Important Findings
The study found a significant decrease in serum copper (Cu) levels in RA-positive patients compared to RA-negative individuals (p=0.04). However, there was no significant relationship between RA and the concentrations of zinc (Zn), cobalt (Co), lead (Pb), and nickel (Ni). Additionally, no significant correlation was observed between heavy metal concentrations and sex or age group within the RA-positive cohort. While some previous studies reported lower zinc levels in RA patients, this study did not find any significant association between RA and Zn deficiency. The findings also contradicted prior research that suggested elevated Pb levels in RA patients, as no significant difference was observed in this study. The observed variations between this study and previous research may be due to genetic, environmental, or dietary differences in the study populations.
Greatest Implications
The study provides evidence that copper deficiency may be associated with RA, potentially implicating copper in the disease's pathophysiology. This aligns with existing research suggesting that copper plays a role in inflammatory and immune system regulation. However, the lack of significant findings for other metals highlights the need for further research to determine their exact impact on RA development and progression. Given that previous studies have reported conflicting results regarding heavy metals and RA, it is crucial to consider factors such as geographic variation, dietary intake, and environmental exposures in future research. Understanding the role of trace metals in RA could contribute to novel therapeutic strategies, including dietary interventions or supplementation for patients with confirmed deficiencies.
Analyzing the impact of heavy metal exposure on osteoarthritis and rheumatoid arthritis: an approach based on interpretable machine learning
Machine learning analysis of NHANES data (2003–2020) identifies tungsten, cadmium, arsenic, and antimony as major risk factors for arthritis. SHAP-based models suggest these metals contribute to inflammation and cartilage degradation, reinforcing environmental exposure as a key component of arthritis development.
What Was Studied?
This study examined the impact of heavy metal exposure on the prevalence and differentiation of osteoarthritis (OA) and rheumatoid arthritis (RA) using interpretable machine learning models. Researchers analyzed data from the National Health and Nutrition Examination Survey (NHANES) (2003–2020) to assess how various heavy metals contribute to arthritis risk.
Who Was Studied?
The study population consisted of 14,319 participants from NHANES who met specific inclusion criteria, including age ≥ 20 years and confirmed arthritis status via blood and urine heavy metal testing.
Key Findings
Using machine learning techniques such as LASSO regression and SHapley Additive exPlanations (SHAP), the study identified tungsten, cobalt, cadmium, antimony, arsenic, and blood cadmium as significant risk factors for arthritis, while molybdenum, thallium, lead, and mercury appeared to have a protective or neutral association. Cadmium exposure showed a strong correlation with rheumatoid arthritis (RA), likely due to its role in oxidative stress and inflammation, while arsenic exposure was linked to both osteoarthritis (OA) and RA, with previous studies indicating its contribution to cartilage degradation. Tungsten and antimony emerged as newly recognized risk factors, though their mechanisms remain unclear. In contrast, molybdenum exhibited a potential protective effect, possibly by counteracting inflammation. The study’s machine learning models demonstrated high predictive accuracy, with XGBoost achieving 81% accuracy in identifying arthritis and LightGBM distinguishing between OA and RA with 76% accuracy.
Greatest Implications
This study reinforces the environmental component of arthritis development, suggesting that heavy metal exposure contributes to arthritis risk and progression. Machine learning models, particularly SHAP-based interpretations, provide valuable predictive tools for early detection. The findings highlight tungsten, cobalt, cadmium, and arsenic as potential modifiable risk factors, paving the way for targeted interventions to reduce arthritis prevalence.
A comparative study of the gut microbiota in immune-mediated inflammatory diseases-does a common dysbiosis exist?
This study reveals that gut microbiota dysbiosis in immune-mediated inflammatory diseases includes shared enrichment of pro-inflammatory taxa like Streptococcus and Eggerthella, alongside depletion of beneficial genera such as Roseburia. These patterns support a common microbial signature across IMIDs and highlight potential targets for diagnosis and therapeutic intervention.
What was studied?
This study examined whether a common gut microbiota dysbiosis exists across multiple immune-mediated inflammatory diseases (IMIDs), specifically Crohn’s disease (CD), ulcerative colitis (UC), multiple sclerosis (MS), and rheumatoid arthritis (RA). Researchers employed 16S rRNA gene sequencing of stool samples and machine learning techniques to identify both disease-specific and shared microbial signatures. This pilot investigation also explored the potential of taxonomic features to classify disease states using random forest classifiers.
Who was studied?
The study included 99 participants: 20 with CD, 19 with UC, 19 with MS, 21 with RA, and 23 healthy controls (HC). Patients were recruited from clinical centers in Winnipeg, Canada, and met disease-specific diagnostic criteria. Inclusion criteria mandated age above 18 and no antibiotic use in the preceding 8 weeks. Biological replicates were collected approximately two months apart to assess microbial stability over time.
What were the most important findings?
The study identified a shared gut microbiota dysbiosis signature across IMIDs, marked by reduced diversity and distinct taxonomic shifts compared to healthy controls. Alpha diversity was significantly lower in IMID groups, especially in CD. Key genera enriched across all disease groups included Actinomyces, Eggerthella, Clostridium III, Faecalicoccus, and Streptococcus—potential Major Microbial Associations (MMAs) due to their pro-inflammatory profiles and consistent presence in IMID cohorts. In contrast, Gemmiger, Lachnospira, and Roseburia were significantly depleted in IMIDs and are known to produce anti-inflammatory metabolites like butyrate. Machine learning classifiers distinguished disease from HC with high accuracy (AUC up to 0.95 for CD), confirming the reliability of these microbial features as diagnostic indicators. Disease-specific signatures were also detected: Bifidobacterium was elevated in UC, Intestinibacter in CD, and unclassified Erysipelotrichaceae in MS.
| Key Domain | Details |
|---|---|
| Conditions Studied | Crohn’s disease, ulcerative colitis, multiple sclerosis, rheumatoid arthritis |
| Shared Microbial Increases | Actinomyces, Eggerthella, Clostridium III, Faecalicoccus, Streptococcus |
| Shared Microbial Decreases | Gemmiger, Lachnospira, Roseburia |
| Disease-Specific Associations | Intestinibacter (CD), Bifidobacterium (UC), Erysipelotrichaceae (MS), Roseburia (↓ in RA) |
| Microbiome Metrics | Alpha diversity lowest in CD, highest in healthy controls; compositional shifts significant |
| Clinical Implications | Supports development of microbiome-targeted diagnostics and interventions |
| Diagnostic Performance | AUCs: CD vs HC = 0.95; classification robust for all IMIDs using Gram-positive taxa |
What are the greatest implications of this study?
This study provides compelling evidence for a partially conserved gut microbiota dysbiosis pattern in IMIDs, despite their diverse clinical presentations. The findings suggest that microbial taxa such as Streptococcus and Eggerthella may contribute to shared pathogenic mechanisms via modulation of host immunity, while depletion of butyrate-producing genera like Roseburia may reflect a breakdown in mucosal tolerance. These MMAs highlight targets for microbiome-modulating interventions and support their integration into risk stratification and personalized treatment strategies. Furthermore, the study underscores the diagnostic potential of microbiota-based machine learning tools, offering a route to non-invasive, microbiome-informed screening across inflammatory conditions.
Interventions
Microbiome-targeted interventions offer a promising avenue for modulating immune responses in rheumatoid arthritis (RA), with probiotic therapy emerging as a potential intervention. Parabacteroides histicola has been shown to restore regulatory T cell (Treg) function, counteracting the pro-inflammatory effects of T helper 17 (Th17) cells, which play a central role in RA pathogenesis. By promoting immune tolerance and reducing systemic inflammation, P. histicola may help mitigate disease progression, offering a microbiome-based approach to complement conventional treatments.
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References
- Role of Some Heavy Metals in Rheumatoid Arthritis.. Arshad, M. ., Riaz, N. ., Bashir, R. ., Irfan, S. ., Khan, S. Y. ., & Tahir, H. M.. (Research Developments in Medicine and Medical Science Vol. 7, 44–50. 2023.)
- Comparative Evaluation of Heavy Metals in Patients with Rheumatoid Arthritis and Healthy Control in Pakistani Population.. Irfan S, Rani A, Riaz N, Arshad M, Kashif Nawaz S.. (Iran J Public Health. 2017)
- Increased inflammation in rheumatoid arthritis patients living where farm soils contain high levels of copper.. Yang TH, Yuan TH, Hwang YH, Lian IB, Meng M, Su CC.. (J Formos Med Assoc. 2016)
- Comparative Evaluation of Heavy Metals in Patients with Rheumatoid Arthritis and Healthy Control in Pakistani Population.. Irfan S, Rani A, Riaz N, Arshad M, Kashif Nawaz S.. (Iran J Public Health. 2017)
- Impact of heavy metals on serum vitamin D3 and PTH in fibromyalgia and rheumatoid arthritis and their correlation to disease activity.. Haddad, Rana & Elbeialy, Adel & Sawy, Soaad & Elzomor, Hala.. (2024.)
- Increased inflammation in rheumatoid arthritis patients living where farm soils contain high levels of copper.. Yang TH, Yuan TH, Hwang YH, Lian IB, Meng M, Su CC.. (J Formos Med Assoc. 2016)
- Comparative Evaluation of Heavy Metals in Patients with Rheumatoid Arthritis and Healthy Control in Pakistani Population.. Irfan S, Rani A, Riaz N, Arshad M, Kashif Nawaz S.. (Iran J Public Health. 2017)
- Analyzing the impact of heavy metal exposure on osteoarthritis and rheumatoid arthritis: an approach based on interpretable machine learning.. Fan W, Pi Z, Kong K, Qiao H, Jin M, Chang Y, Zhang J, Li H.. (Front Nutr. 2024)
- Increased inflammation in rheumatoid arthritis patients living where farm soils contain high levels of copper.. Yang TH, Yuan TH, Hwang YH, Lian IB, Meng M, Su CC.. (J Formos Med Assoc. 2016)
- Comparative Evaluation of Heavy Metals in Patients with Rheumatoid Arthritis and Healthy Control in Pakistani Population.. Irfan S, Rani A, Riaz N, Arshad M, Kashif Nawaz S.. (Iran J Public Health. 2017)
- Impact of heavy metals on serum vitamin D3 and PTH in fibromyalgia and rheumatoid arthritis and their correlation to disease activity.. Haddad, Rana & Elbeialy, Adel & Sawy, Soaad & Elzomor, Hala.. (2024.)
- Impact of heavy metals on serum vitamin D3 and PTH in fibromyalgia and rheumatoid arthritis and their correlation to disease activity.. Haddad, Rana & Elbeialy, Adel & Sawy, Soaad & Elzomor, Hala.. (2024.)
- Increased inflammation in rheumatoid arthritis patients living where farm soils contain high levels of copper.. Yang TH, Yuan TH, Hwang YH, Lian IB, Meng M, Su CC.. (J Formos Med Assoc. 2016)
- Impact of heavy metals on serum vitamin D3 and PTH in fibromyalgia and rheumatoid arthritis and their correlation to disease activity.. Haddad, Rana & Elbeialy, Adel & Sawy, Soaad & Elzomor, Hala.. (2024.)