Myasthenia gravis and five autoimmune diseases: a bidirectional Mendelian randomization study

Li, Kailin; Ouyang, Yuzhen; Yang, Huan

doi:10.1007/s10072-023-07163-3

Cited by 3 publications

(3 citation statements)

References 47 publications

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“…Bidirectional two-sample MR Results supported a bidirectional causal association between MG and SLE/T1DM [41].…”

Section: Five Autoimmune Diseasesmentioning

confidence: 75%

“… Physical activity and sedentary behavior LDSC; two-sample MR; MVMR Findings support a causal effect of sedentary behavior as measured by LST on MG [ 40 ]. Five autoimmune diseases Bidirectional two-sample MR Results supported a bidirectional causal association between MG and SLE/T1DM [ 41 ]. Gut microbiota Bidirectional two-sample MR Research results yielded evidence of a causality connection in both directions between gut microbiota and myasthenia gravis [ 42 ].…”

Section: Discussionmentioning

confidence: 99%

“…. Furthermore, it has been indicated that serum IL-21, a follicular Th cell-related CK [ 41 ], is linked with elevated QMG score in MG patients, which decreases after steroid treatment [ 48 ]. Moreover, the rate of IL-10 is increased after the treatment of MG [ 49 ].…”

Section: Discussionmentioning

confidence: 99%

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

Wang,

Ge,

Feng

et al. 2024

BMC Neurol

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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.

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“…Bidirectional two-sample MR Results supported a bidirectional causal association between MG and SLE/T1DM [41].…”

Section: Five Autoimmune Diseasesmentioning

confidence: 75%

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

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

Wang,

Ge,

Feng

et al. 2024

BMC Neurol

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Shared aetiology underlying multiple sclerosis and other immune mediated inflammatory diseases: Swedish familial co-aggregation and large-scale genetic correlation analyses

Liu,

Jiang,

Frisell

et al. 2024

Journal of Autoimmunity

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Application of Mendelian randomization in thyroid diseases: a review

Li,

Wang,

Liu

et al. 2024

Front. Endocrinol.

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Thyroid diseases are increasingly prevalent, posing significant challenges to patients’ quality of life and placing substantial financial burdens on families and society. Despite these impacts, the underlying pathophysiology of many thyroid conditions remains poorly understood, complicating efforts in treatment, management, and prevention. Observational studies can identify associations between exposure variables and disease; however, they often struggle to account for confounding factors and reverse causation. Understanding disease occurrence, epidemiological trends, and clinical diagnosis, prevention, and treatment relies heavily on robust etiological research. Mendelian randomization, a method grounded in genetics and epidemiology, has been widely employed in studying the etiology of thyroid diseases, offering a solution to some of these challenges. This paper categorizes thyroid diseases into thyroid dysfunction and thyroid cancer, reviewing related Mendelian randomization studies. It further provides novel perspectives and approaches for investigating the mechanisms underlying thyroid diseases and designing intervention strategies.

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Myasthenia gravis and five autoimmune diseases: a bidirectional Mendelian randomization study

Cited by 3 publications

References 47 publications

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

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

Shared aetiology underlying multiple sclerosis and other immune mediated inflammatory diseases: Swedish familial co-aggregation and large-scale genetic correlation analyses

Application of Mendelian randomization in thyroid diseases: a review

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