Microbiota dysbiosis and myasthenia gravis: Do all roads lead to Rome?

Coexistence of Parkinson's disease and myasthenia gravis: A case report and literature review

The coexistence of Parkinson's disease (PD) and myasthenia gravis (MG) is rare. When similar symptoms of both diseases overlap, it is challenging to make a concomitant diagnosis of PD and MG. The present study describes the case of a patient with concomitant PD and MG. In addition, a systematic literature review was conducted by searching PubMed and Embase for reports on all patients with concomitant PD and MG, which were then grouped and compared according to different preexisting diseases. Finally, a total of 47 cases of concomitant PD and MG (35 men; 12 women), including the present case, were analyzed. The median age of the patients at first diagnosis was 66.59±9.91 years. The interval between the two diseases varied from 2 months to 22 years. Based on the sequential occurrence of these two diseases, the patients were categorized into three groups: The prePD-MG (30 cases), preMG-PD (12 cases), and coPD-MG (5 cases) groups. In the prePD-MG group, the onset age of MG was older and head drop was more common. In the preMG-PD group, the patients were more likely to have comorbid immune diseases.

Advances in Understanding and Managing Myasthenia Gravis: Current Trends and Future Directions

Myasthenia gravis (MG) is an autoimmune illness characterized by autoantibodies against the acetylcholine receptor (AChR), muscle-specific tyrosine kinase (MuSK), and an increasing number of extra postsynaptic proteins. Pathogenic autoantibodies reduce the number of functional AChRs in the neuromuscular junction's (NMJ) muscle end plate. The cause of the autoimmune response is unknown, but thymic abnormalities and immune regulatory deficiencies are significant. The disease's incidence is likely influenced by genetic predisposition, with sex hormones and exercise playing a role. MG can affect any age, race, or gender and can be caused by any stressor, with infections being the most frequent cause. Treatment focuses on airway support and the triggering incident. MG is a rare autoimmune disease causing fatigue-inducing weakness in the axial, respiratory, leg, and bulbar muscles. Initially affecting the eyes, most MG patients experience at least one worsening symptom during their illness. The disease is mainly caused by antibodies against the AChR, dependence on the immune system within cells, and engagement of the complement system. The complement system plays a significant role in MG, and complement inhibition can both prevent the onset and slow its development. Ocular MG affects around 15% of people, with most patients having blocking antibodies against the cholinergic receptor. There may be correlations between thymoma and other autoimmune conditions, especially thyroid illness. Treatment and management for MG involve removing autoantibodies from circulation or blocking effector mechanisms using techniques such as complement inhibition, plasmapheresis, and B-cell elimination.

An azole fungicide climbazole damages the gut-brain axis in the grass carp

Azole antifungal climbazole has frequently been detected in aquatic environments and shows various effects in fish. However, the underlying mechanism of toxicity through the gut-brain axis of climbazole is unclear. Here, we investigated the effects of climbazole at environmental concentrations on the microbiota-intestine-brain axis in grass carp via histopathological observation, gene expression and biochemical analyses, and high-throughput sequencing of the 16 S rRNA. Results showed that exposure to 0.2 to 20 μg/L climbazole for 42 days significantly disrupted gut microbiota and caused brain neurotoxicity in grass carp. In this study, there was an alteration in the phylum and genus compositions in the gut microbiota following climbazole treatment, including reducing Fusobacteria (e.g., Cetobacterium) and increasing Actinobacteria (e.g., Nocardia). Climbazole disrupted intestinal microbial abundance, leading to increased levels of lipopolysaccharide and tumor necrosis factor-alpha in the gut, serum, and brain. They passed through the impaired intestinal barrier into the circulation and caused the destruction of the blood-brain barrier through the gut-brain axis, allowing them into the brain. In the brain, climbazole activated the nuclear factor kappaB pathway to increase inflammation, and suppressed the E2-related factor 2 pathway to produce oxidative damage, resulting in apoptosis, which promoted neuroinflammation and neuronal death. Besides, our results suggested that this neurotoxicity was caused by the breakdown of the microbiota-gut-brain axis, mediated by reduced concentrations of dopamine, short chain fatty acids, and intestinal microbial activity induced by climbazole.

Probiotics in Allergy and Immunological Diseases: A Comprehensive Review

Allergy and immunological disorders like autoimmune diseases are vastly prevalent worldwide. These conditions account for a substantial amount of personal and social burden. Such illnesses have lengthy, uncertain, and spotted courses with unpredictable exacerbations. A definite tendency for improving the overall quality of life of individuals suffering from such diseases is crucial to tackling these diseases, especially through diet or lifestyle modification. Further, interventions like microbiome-based therapeutics such as prebiotics or probiotics were explored. Changes in the microbial population were evident during the flare-up of autoimmune and allergic conditions. The realization that the human microbiome is a central player in immunological diseases is a hallmark of its potential usefulness in therapy for such illnesses. This review focuses on the intricate symphony in the orchestra of the human microbiome and the immune system. New therapeutic strategies involving probiotics appear to be the future of personalized medicine. Through this review, we explore the narrative of probiotics and reaffirm their use as therapeutic and preventive agents in immunological disorders.

Causal relationship between gut microbiota and myasthenia gravis: a two-sample Mendelian randomization study

Background

Previous observational studies have provided cumulative data linking gut microbiota to myasthenia gravis (MG). However, the causal link between the two remains unexplored. Hence, the current study was performed to explore the causal link between them.

Methods

Mendelian randomization (MR) analysis was conducted using the summary statistics of 211 gut microbiota taxa and the largest genome-wide association studies (GWAS) for MG currently available. The inverse variance-weighted (IVW), MR-Egger, weighted median, and weighted mode methods were employed to ascertain the causal influence. Sensitivity studies utilizing several methodologies were then used to assess the robustness of the findings. Lastly, to evaluate reverse causality, a reverse MR analysis was performed.

Results

Seven suggestive causal associations between the gastrointestinal microbiota and MG were identified based on the outcomes of the MR analysis. Specifically, phylum Actinobacteria (OR: 0.602, 95% CI: 0.405-0.896, p = 0.012), class Gammaproteobacteria (OR: 0.587, 95% CI: 0.357-0.968, p = 0.037), and families Defluviitaleaceae (OR: 0.695, 95% CI: 0.485-0.996, p = 0.047), Family XIII (OR: 0.614, 95% CI: 0.412-0.916, p = 0.017), and Peptococcaceae (OR: 0.698, 95% CI: 0.505-0.964, p = 0.029) had suggestive protective effects on MG, while order Mollicutes RF9 (OR: 1.424, 95% CI: 1.015-1.998, p = 0.041) and genus Faecalibacterium (OR: 1.763, 95% CI: 1.220-2.547, p = 0.003) were suggestive risk factors for MG. The outcomes indicate that neither heterogeneity nor horizontal pleiotropy had any discernible impact. Nevertheless, this reverse analysis did not reveal any apparent effect of MG on the gut microbiota composition.

Conclusion

The MR investigation has substantiated the suggestive causal connection between gut microbiota and MG, which may provide helpful insights for innovative therapeutic and preventative approaches for MG. Further randomized controlled trials are needed to elucidate the gut microbiota's precise role and therapeutic potential in the pathogenesis of MG.

Mendelian randomization analyses of known and suspected risk factors and biomarkers for myasthenia gravis overall and by subtypes

BACKGROUND

Myasthenia gravis (MG) is an autoimmune disease that affects neuromuscular junction. The literature suggests the involvement of circulating cytokines (CK), gut microbiota (GM), and serum metabolites (SM) with MG. However, this research is limited to observational trials, and comprehensive causal relationship studies have not been conducted. Based on published datasets, this investigation employed Mendelian Randomization (MR) to analyze the known and suspected risk factors and biomarkers causal association of MG and its subtypes.

METHODS

This research used two-sample MR and linkage disequilibrium score (LDSC) regression of multiple datasets to aggregate datasets acquired from the genome-wide association studies (GWAS) to assess the association of MG with 41-CK, 221-GM, and 486-SM. For sensitivity analysis and to validate the robustness of the acquired data, six methods were utilized, including MR-Egger regression, inverse variance weighting (IVW), weighted median, and MR-PRESSO.

RESULTS

The MR method identified 20 factors significantly associated with MG, including 2 CKs, 6 GMs, and 9 SMs. Further analysis of the factors related to the two MG subtypes, early-onset MG (EOMG) and late-onset MG (LOMG), showed that EOMG had a high overlap with MG in the intestinal flora, while LOMG had a greater similarity in CKs and SMs. Furthermore, LDSC regression analysis indicated that Peptococcaceae, oxidized biliverdin, and Kynurenine had significant genetic correlations with general MG, whereas EOMG was highly correlated with Intestinibacter, while LOMG had significant genetic associations with Kynurenine and Glucose.

CONCLUSION

This research furnishes evidence for the potential causal associations of various risk factors with MG and indicates a heterogeneous relationship between CKs, GMs, and SMs with MG subtypes.

Evidence for genetic causal relationships between gut microbiome, metabolites, and myasthenia gravis: a bidirectional Mendelian randomization study

Background

Myasthenia gravis (MG) is an autoimmune disease observed to have connections with gut microbiome. We aimed to systematically assess the causal relationships between gut microbiome, gut microbiome-derived metabolites, and MG using Mendelian randomization (MR) approach.

Methods

Summary-level genetic datasets from large-scale genome-wide association studies regarding 196 gut microbial taxa from the MiBioGen consortium (n=18,340), 72 derived metabolites from the TwinsUK and KORA studies (n=7,824), and antiacetylcholine receptor (AChR) antibody-positive MG (case=1,873, control=36,370) were employed for MR causal estimates. The inverse-variance weighted (IVW) method was utilized as the main analysis with MR-Egger, maximum likelihood, simple mode, and weighted median as complements. The tests of Cochran's Q, MR-Egger intercept, Steiger, MR-PRESSO and leave-one-out were implemented for sensitivity analyses.

Results

The forward MR estimates of IVW revealed significant causal associations of the abundance of phylum Actinobacteria, class Gammaproteobacteria, family Defluviitaleac, family Family XIII, and family Peptococcaceae with a reduced risk of MG. Conversely, the abundance of phylum Lentisphaerae, order Mollicutes RF9, order Victivallales, and genus Faecalibacterium was causally associated with an increased risk of MG. The reversed MR analysis proved negative causal correlations between the MG and the abundance of family Peptostreptococcaceae, genus Romboutsia, and genus Subdoligranulum. Regarding the derived metabolites, the IVW estimates revealed that elevated levels of beta-hydroxyisovalerate and methionine were causally associated with a decreased risk of MG, while increased levels of choline and kynurenine were linked to an increased risk of MG. Furthermore, genetically predicted MG was associated with a decreased level of cholesterol. The results obtained from complementary MR methods were similar. These findings remained robust in all sensitivity analyses.

Conclusion

Our MR findings support the causal effects of specific gut microbiome taxa and derived metabolites on AChR antibody-positive MG, and vice versa, yielding novel insights into prevention and therapy targets of MG. Future studies may be warranted for validation and pursuing the precise mechanisms.

SOCS-JAK-STAT inhibitors and SOCS mimetics as treatment options for autoimmune uveitis, psoriasis, lupus, and autoimmune encephalitis

Autoimmune diseases arise from atypical immune responses that attack self-tissue epitopes, and their development is intricately connected to the disruption of the JAK-STAT signaling pathway, where SOCS proteins play crucial roles. Conditions such as autoimmune uveitis, psoriasis, lupus, and autoimmune encephalitis exhibit immune system dysfunctions associated with JAK-STAT signaling dysregulation. Emerging therapeutic strategies utilize JAK-STAT inhibitors and SOCS mimetics to modulate immune responses and alleviate autoimmune manifestations. Although more research and clinical studies are required to assess their effectiveness, safety profiles, and potential for personalized therapeutic approaches in autoimmune conditions, JAK-STAT inhibitors and SOCS mimetics show promise as potential treatment options. This review explores the action, effectiveness, safety profiles, and future prospects of JAK inhibitors and SOCS mimetics as therapeutic agents for psoriasis, autoimmune uveitis, systemic lupus erythematosus, and autoimmune encephalitis. The findings underscore the importance of investigating these targeted therapies to advance treatment options for individuals suffering from autoimmune diseases.

Machine learning strategy for identifying altered gut microbiomes for diagnostic screening in myasthenia gravis

Myasthenia gravis (MG) is a neuromuscular junction disease with a complex pathophysiology and clinical variation for which no clear biomarker has been discovered. We hypothesized that because changes in gut microbiome composition often occur in autoimmune diseases, the gut microbiome structures of patients with MG would differ from those without, and supervised machine learning (ML) analysis strategy could be trained using data from gut microbiota for diagnostic screening of MG. Genomic DNA from the stool samples of MG and those without were collected and established a sequencing library by constructing amplicon sequence variants (ASVs) and completing taxonomic classification of each representative DNA sequence. Four ML methods, namely least absolute shrinkage and selection operator, extreme gradient boosting (XGBoost), random forest, and classification and regression trees with nested leave-one-out cross-validation were trained using ASV taxon-based data and full ASV-based data to identify key ASVs in each data set. The results revealed XGBoost to have the best predicted performance. Overlapping key features extracted when XGBoost was trained using the full ASV-based and ASV taxon-based data were identified, and 31 high-importance ASVs (HIASVs) were obtained, assigned importance scores, and ranked. The most significant difference observed was in the abundance of bacteria in the Lachnospiraceae and Ruminococcaceae families. The 31 HIASVs were used to train the XGBoost algorithm to differentiate individuals with and without MG. The model had high diagnostic classification power and could accurately predict and identify patients with MG. In addition, the abundance of Lachnospiraceae was associated with limb weakness severity. In this study, we discovered that the composition of gut microbiomes differed between MG and non-MG subjects. In addition, the proposed XGBoost model trained using 31 HIASVs had the most favorable performance with respect to analyzing gut microbiomes. These HIASVs selected by the ML model may serve as biomarkers for clinical use and mechanistic study in the future. Our proposed ML model can identify several taxonomic markers and effectively discriminate patients with MG from those without with a high accuracy, the ML strategy can be applied as a benchmark to conduct noninvasive screening of MG.

Altered gut microbiota and metabolites in untreated myasthenia gravis patients

Objective

The homeostasis of the immune system is influenced by the gut microbiota. Previous studies have reported dysbiosis in the gut microbiota of myasthenia gravis (MG) patients. To investigate potential alterations in gut microbiota and metabolites in newly diagnosed and untreated MG patients, we conducted a case-control study.

Methods

Fecal samples were collected from 11 newly diagnosed and untreated MG patients as well as 11 age-and sex-matched healthy controls. These samples underwent analysis for gut microbiota using 16S ribosomal RNA (rRNA) gene sequencing, while fecal metabolome was analyzed using liquid chromatography-electrospray tandem mass spectrometry system (LC-ESI-MS/MS).

Results

The microbial community richness (observed species) and diversity (Shannon and Simpson indices) were significantly lower in the MG group compared to the control group. Microbiota composition analysis revealed significant differences between the MG and control groups at phylum, family, and genus levels. Linear discriminant analysis effect size (LEfSe) analysis showed a substantial decrease in abundance of the genus Faecalibacterium within the MG group. Fecal metabolome analysis identified three up-regulated metabolites involved in amino acid metabolism (taurine, creatinine, L-carnitine), one up-regulated metabolite involved in lipid metabolism (oleic acid), with correlation analysis indicating a positive association between Faecalibacterium abundance and creatinine levels.

Conclusion

Our findings suggest that dysbiosis already exists in newly diagnosed and untreated MG patients, implying that dysbiosis within the gut microbiota may be an initiating factor contributing to MG pathogenesis. Furthermore, F. prausnitzii may hold promise as a probiotic for treating MG.