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BMC Neurology Jan 2024Myasthenia gravis (MG) is an autoimmune disease that affects neuromuscular junction. The literature suggests the involvement of circulating cytokines (CK), gut...
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.
Topics: Humans; Genome-Wide Association Study; Kynurenine; Mendelian Randomization Analysis; Myasthenia Gravis; Risk Factors; Biomarkers; Cytokines
PubMed: 38238684
DOI: 10.1186/s12883-024-03529-y -
Frontiers in Immunology 2023Myasthenia gravis (MG) is an autoimmune disease observed to have connections with gut microbiome. We aimed to systematically assess the causal relationships between gut...
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.
Topics: Humans; Gastrointestinal Microbiome; Genome-Wide Association Study; Mendelian Randomization Analysis; Myasthenia Gravis; Autoantibodies
PubMed: 38179043
DOI: 10.3389/fimmu.2023.1279845 -
Frontiers in Microbiology 2023Numerous studies have revealed associations between gut microbiota and adipose tissue. However, the specific functional bacterial taxa and their causal relationships...
BACKGROUND
Numerous studies have revealed associations between gut microbiota and adipose tissue. However, the specific functional bacterial taxa and their causal relationships with adipose tissue production in different regions of the body remain unclear.
METHODS
We conducted a bidirectional two-sample Mendelian Randomization (MR) study using aggregated data from genome-wide association studies (GWAS) for gut microbiota and adipose tissue. We employed methods such as inverse variance weighted (IVW), MR Egger, weighted median, simple mode, and weighted mode to assess the causal relationships between gut microbiota and subcutaneous adipose tissue (SAT) as well as visceral adipose tissue (VAT). Cochran's Q test, MR-Egger regression intercept analysis, and MR-PRESSO were used to test for heterogeneity, pleiotropy, and outliers of the instrumental variables, respectively. Reverse MR was employed to evaluate the reverse causal relationships between SAT, VAT, and gut microbiota with significant associations.
RESULTS
IVW results demonstrated that were protective factors for SAT production (OR = 0.88, 95% CI: 0.80-0.96, = 0.005) and VAT production (OR = 0.91, 95% CI: 0.83-0.99, = 0.030). Various bacterial taxa including (OR = 0.94, 95% CI: 0.89-0.99, = 0.017), (OR = 0.96, 95% CI: 0.92-1.00, = 0.029), and (OR = 0.90, 95% CI: 0.83-0.98, = 0.012) were associated only with decreased SAT production. (OR = 1.05, 95% CI: 1.02-1.10, = 0.005), (OR = 1.08, 95% CI: 1.01-1.15, = 0.028), (OR = 1.08, 95% CI: 1.01-1.17, = 0.034), and (OR = 1.05, 95% CI: 1.00-1.10, = 0.047) were risk factors for SAT production. Meanwhile, (OR = 0.95, 95% CI: 0.91-0.99, = 0.019), (OR = 0.93, 95% CI: 0.88-0.99, = 0.022), and Defluviitaleaceae UCG011 (OR = 0.94, 95% CI: 0.89-0.99, = 0.024) were protective factors for VAT production. Furthermore, (OR = 1.09, 95% CI: 1.01-1.17, = 0.018), (OR = 1.09, 95% CI: 1.01-1.19, = 0.037), Alloprevotella (OR = 1.05, 95% CI: 1.00-1.10, = 0.038), and (OR = 1.07, 95% CI: 1.00-1.15, = 0.042) were associated with VAT accumulation. Additionally, reverse MR revealed significant associations between SAT, VAT, and (IVW: OR = 1.57, 95% CI: 1.18-2.09, = 0.002) as well as (IVW: OR = 1.14, 95% CI: 1.01-1.29, = 0.029), both acting as risk factors. Sensitivity analyzes during bidirectional MR did not identify heterogeneity or pleiotropy.
CONCLUSION
This study unveils complex causal relationships between gut microbiota and SAT/VAT, providing novel insights into the diagnostic and therapeutic potential of gut microbiota in obesity and related metabolic disorders.
PubMed: 38029216
DOI: 10.3389/fmicb.2023.1285982 -
Frontiers in Cellular and Infection... 2023The gut microbiota has been found to be associated with the risk of lung cancer. However, its causal relationship with various types of lung cancer remains unclear.
BACKGROUND
The gut microbiota has been found to be associated with the risk of lung cancer. However, its causal relationship with various types of lung cancer remains unclear.
METHODS
We conducted a Mendelian randomization (MR) study using the largest genome-wide association analysis of gut microbiota data to date from the MiBioGen consortium, with pooled statistics for various types of lung cancer from the Transdisciplinary Research in Cancer of the Lung, the International Lung Cancer Consortium, and FinnGen Consortium R7 release data. Inverse variance weighted, weighted model, MR-Egger regression, and weighted median were adapted to assess the causal relationship between gut microbiota and various types of lung cancer. Sensitivity analysis was used to test for the presence of pleiotropy and heterogeneity in instrumental variables. A reverse MR analysis was performed on these bacteria to determine their potential role in causing lung cancer. A reverse MR analysis was performed on these bacteria to determine their potential role in causing lung cancer. Multivariable Mendelian randomization (MVMR) was conducted to assess the direct causal impact of gut microbiota on the risk of various types of lung cancer.
RESULTS
Using IVW as the primary analytical method, we identified a total of 40 groups of gut microbiota with potential causal associations with various subtypes of lung cancer, of which 10 were associated with lung cancer, 10 with lung adenocarcinoma, 9 with squamous cell lung cancer, and 11 groups of bacteria associated with small cell lung cancer. After performing FDR correction, we further found that there was still a significant causal relationship between Peptococcaceae and lung adenocarcinoma. Sensitivity analyses demonstrated the robustness of these results, with no heterogeneity or pleiotropy found.
CONCLUSIONS
Our results confirm a causal relationship between specific gut microbiota and lung cancer, providing new insights into the role of gut microbiota in mediating the development of lung cancer.
Topics: Humans; Lung Neoplasms; Gastrointestinal Microbiome; Genome-Wide Association Study; Mendelian Randomization Analysis; Adenocarcinoma of Lung
PubMed: 37829610
DOI: 10.3389/fcimb.2023.1200299 -
Journal of Electrocardiology 2023Past research based on observations has suggested that the gut microbiome (GM) could play a role in developing arrhythmias and conduction blocks. Nonetheless, the nature...
INTRODUCTION
Past research based on observations has suggested that the gut microbiome (GM) could play a role in developing arrhythmias and conduction blocks. Nonetheless, the nature of this association remains uncertain due to the potential for reverse causation and confounding factors in observational research. The aim of this investigation is to elucidate the causal relationship between GM and the development of arrhythmias as well as conduction blocks.
METHODS
This study collected summary statistics regarding GM, arrhythmias, and conduction blocks. Two-sample Mendelian randomization (MR) analysis was carried out employing various methods, with inverse variance weighted being the primary approach, followed by weighted median, simple mode, MR-Egger, and MR-PRESSO. Moreover, the MR findings were corroborated through multiple sensitivity analyses.
RESULTS
Among them, for atrial fibrillation and flutter (AF), phylum_Actinobacteria and genus_RuminococcaceaeUCG004 demonstrated a negative correlation, while order_Pasteurellales, family_Pasteurellaceae, and genus_Turicibacter were associated with an increased risk. In the case of paroxysmal tachycardia (PT), genus_Holdemania and genus_Roseburia were found to reduce risk. For atrioventricular block (AVB), order_Bifidobacteriales, family_Bifidobacteriaceae, and genus_Alistipes exhibited a negative correlation, whereas genus_CandidatusSoleaferrea showed a positive correlation. Concerning the left bundle-branch block (LBBB), family_Peptococcaceae appeared to decrease the risk, while genus_Flavonifractor was linked to an increased risk. Lastly, no causative GM was identified in the right bundle-branch block (RBBB) context.
CONCLUSION
We have uncovered potential causal links between some GM, arrhythmias, and conduction blocks. This insight may aid in designing microbiome-based interventions for these conditions and their risk factors in future trials. Additionally, it could facilitate the discovery of novel biomarkers for targeted prevention strategies.
Topics: Humans; Gastrointestinal Microbiome; Mendelian Randomization Analysis; Electrocardiography; Bundle-Branch Block; Atrial Fibrillation
PubMed: 37422943
DOI: 10.1016/j.jelectrocard.2023.06.006 -
Frontiers in Microbiology 2023A growing number of studies implies a strong association between gut microbiota and chronic obstructive pulmonary disease (COPD). However, the causal impact between gut...
BACKGROUND
A growing number of studies implies a strong association between gut microbiota and chronic obstructive pulmonary disease (COPD). However, the causal impact between gut microbiota and COPD remains unclear. As a result, we used a two-sample Mendelian randomization (MR) method to investigate the connection between gut microbiota and COPD in this study.
METHODS
The largest available genome-wide association study (GWAS) of gut microbiota was obtained from the MiBioGen consortium. Summary-level dataset for COPD were obtained from the FinnGen consortium. The main analysis method for determining the causal link between gut microbiota and COPD was inverse variance weighted (IVW). Subsequently, pleiotropy and heterogeneity tests were performed to determine the reliability of the results.
RESULTS
IVW method identified 9 bacterial taxa nominally associated with the risk of COPD. Class Actinobacteria ( = 0.020), genus ( = 0.024), genus ( = 0.002) and genus ( = 0.018) were protective against COPD. In addition, order Desulfovibrionales ( = 0.011), family Desulfovibrionaceae ( = 0.039), family Peptococcaceae ( = 0.020), family Victivallaceae ( = 0.012) and genus ( = 0.017) were associated with a higher risk of COPD. No pleiotropy or heterogeneity were found.
CONCLUSION
According to the findings of this MR analysis, a causal relationship exists between certain gut microbiota and COPD. New insights into the mechanisms of COPD mediated by gut microbiota are provided.
PubMed: 37405157
DOI: 10.3389/fmicb.2023.1196751 -
Food Science & Nutrition Jun 2023Ulcerative colitis is a chronic and recurrent gastrointestinal intestinal disease accompanied by inflammatory disorders, immunologic inadequacy, and intestinal flora...
Ulcerative colitis is a chronic and recurrent gastrointestinal intestinal disease accompanied by inflammatory disorders, immunologic inadequacy, and intestinal flora dysbiosis, and current therapeutic pharmaceuticals have limited side effects. In this study, we revealed the extraction method of , analyzed the main component, compared the effect of its extract, , and conventional drugs with different properties on DSS (dextran sodium sulfate)-induced colitis, and indicated extract regulatory properties of inestinal flora. A colitis model was established on experimental design, and BALB/c mice (male, 7 weeks old) were randomly assigned to five groups ( = 10): control, DSS model, extract (CSE), GG (LGG), and 5-aminosalicylic acid (5-ASA) groups. The three treatments could alleviate the symptoms and remit inflammation induced by DSS, in which CSE and LGG groups could both decrease the proinflammatory cytokine IL-6, IL-8, and TNF-α levels and increase anti-inflammatory cytokines IL-10 and TGF-β. The CSE intervention significantly promoted the higher production of butyric acid than LGG and 5-ASA groups ( < .05) after DSS challenge. Analysis of intestinal flora showed that CSE administration remarkably decreased the relative abundance of pathogenic bacteria and and exhibited higher abundance of and than LGG in intestinal tract of mice ( < .05). These findings indicated that extract may have been beneficial for preventing and treating colitis.
PubMed: 37324926
DOI: 10.1002/fsn3.3282 -
Frontiers in Microbiology 2023Studies demonstrate that time-restricted feeding (TRF) can regulate gut microbiota composition. However, it is unclear whether TRF could affect the gut microbial...
INTRODUCTION
Studies demonstrate that time-restricted feeding (TRF) can regulate gut microbiota composition. However, it is unclear whether TRF could affect the gut microbial rhythmicity in growing pigs. Therefore, the present study aimed to explore the effects of TRF on the dynamic fluctuation of the gut microbiota.
METHODS
A total of 10 healthy growing pigs equipped with T cannula were employed. Pigs were randomly allotted to the free access (FA) and the TRF groups with 5 replicates (1 pig/replicates). Pigs in the FA group were fed free access during the whole experimental period, whereas pigs in the TRF group were fed free access three times per day within limited times (7:00-8:00, 12:00-13:00, 17:00-18:00). The experiment lasted for 15 days, at 06:00 a.m. of the day 16, colonic digesta were collected at a 6-h interval for consecutive 24 h marked as T06 (06:00), T12 (12:00), T18 (18:00), T24 (24:00), T30 (06:00), respectively.
RESULTS
Results showed that TRF altered the distribution of feed intake without changing the total feed intake within a day ( = 0.870). TRF decreased the overall concentration of colonic cellulose and altered their oscillating patterns. All alpha-diversity indexes of different time points showed significant differences regardless of feeding pattern with a trough at T18 or T24. TRF shifted the trough of the alpha-diversity index Simpson and Invsimpson. TRF lost the rhythmicity of , , _S24-7_group, and and gained the rhythmicity of , _1, , and . Also, TRF altered the interaction pattern by increasing the microbes involved in the co-occurrence network and their crosstalk, especially at T24. Interestingly, the microbial variation at T24 could largely explained by colonic substrates starch (R = 0.369; = 0.001), cellulose (R = 0.235; = 0.009) and NH4-N (R = 0.489; = 0.001).
CONCLUSION
In conclusion, TRF has changed the concentrates of cellulose and the relative abundance of specific microbes and certain microbial metabolites. In addition, TRF has more powerful effects on the fluctuation modes of these nutrient substrates, microbes, and metabolites by shifting their peaks or troughs. This knowledge facilitates the development of precision regulation targeting gut microbial rhythmicity.
PubMed: 37275162
DOI: 10.3389/fmicb.2023.1162482 -
Microbiology Spectrum Mar 2023Undernutrition may change cecal microbiota-epithelium interactions to influence cecal feed fermentation, nutrient absorption and metabolism, and immune function. Sixteen...
Undernutrition may change cecal microbiota-epithelium interactions to influence cecal feed fermentation, nutrient absorption and metabolism, and immune function. Sixteen late-gestation Hu-sheep were randomly divided into control (normal feeding) and treatment (feed restriction) groups to establish an undernourished sheep model. Cecal digesta and epithelium were collected to analyze microbiota-host interactions based on 16S rRNA gene and transcriptome sequencing. Results showed that cecal weight and pH were decreased, volatile fatty acids and microbial proteins concentrations were increased, and epithelial morphology was changed upon undernutrition. Undernutrition reduced the diversity, richness, and evenness of cecal microbiota. The relative abundances of cecal genera involved in acetate production ( dgA-11 gut group, RC9 gut group, and ) and negatively correlated with butyrate proportion ( vadinBB60 group_norank) were decreased, while genera related to butyrate (_uncultured and _uncultured) and valerate (_uncultured) production were increased in undernourished ewes. These findings were consistent with the decreased molar proportion of acetate and the increased molar proportions of butyrate and valerate. Undernutrition changed the overall transcriptional profile and substance transport and metabolism in cecal epithelium. Undernutrition suppressed extracellular matrix-receptor interaction and intracellular phosphatidyl inositol 3-kinase (PI3K) signaling pathway then disrupted biological processes in cecal epithelium. Moreover, undernutrition repressed phagosome antigen processing and presentation, cytokine-cytokine receptor interaction, and intestinal immune network. In conclusion, undernutrition affected cecal microbial diversity and composition and fermentation parameters, inhibited extracellular matrix-receptor interaction and the PI3K signaling pathway, and then disrupted epithelial proliferation and renewal and intestinal immune functions. Our findings exposed cecal microbiota-host interactions upon undernutrition and contribute to their further exploration. Undernutrition is commonly encountered in ruminant production, especially during pregnancy and lactation in females. Undernutrition not only induces metabolic diseases and threatens pregnant mothers' health, but also inhibits fetal growth and development, leading to weakness or even death of fetuses. Cecum works importantly in hindgut fermentation, providing volatile fatty acids and microbial proteins to the organism. Intestinal epithelial tissue plays a role in nutrient absorption and transport, barrier function, and immune function. However, little is known about cecal microbiota and epithelium interactions upon undernutrition. Our findings showed that undernutrition affected bacterial structures and functions, which changed fermentation parameters and energy regimens, and therefore affected the substance transport and metabolism in cecal epithelium. Extracellular matrix-receptor interactions were inhibited, which repressed cecal epithelial morphology and cecal weight via the PI3K signaling pathway and lowered immune response function upon undernutrition. These findings will help in further exploring microbe-host interactions.
PubMed: 36976022
DOI: 10.1128/spectrum.05320-22 -
Frontiers in Immunology 2023An association between Graves' disease (GD) and the gut microbiome has been identified, but the causal effect between them remains unclear.
BACKGROUND
An association between Graves' disease (GD) and the gut microbiome has been identified, but the causal effect between them remains unclear.
METHODS
Bidirectional two-sample Mendelian randomization (MR) analysis was used to detect the causal effect between GD and the gut microbiome. Gut microbiome data were derived from samples from a range of different ethnicities (18,340 samples) and data on GD were obtained from samples of Asian ethnicity (212,453 samples). Single nucleotide polymorphisms (SNPs) were selected as instrumental variables according to different criteria. They were used to evaluate the causal effect between exposures and outcomes through inverse-variance weighting (IVW), weighted median, weighted mode, MR-Egger, and simple mode methods. -statistics and sensitivity analyses were performed to evaluate bias and reliability.
RESULTS
In total, 1,560 instrumental variables were extracted from the gut microbiome data (< 1 × 10). The classes [odds ratio (OR) = 3.603] and , as well as the genera group, , and UCG 011 were identified as risk factors for GD. The family and the genus (OR = 0.489) were protective factors for GD. In addition, 13 instrumental variables were extracted from GD (< 1 × 10), causing one family and eight genera to be regulated. The genus group ( = 0.024, OR = 0.918) and ( = 0.049, OR = 1.584) had the greatest probability of being regulated. Significant bias, heterogeneity, and horizontal pleiotropy were not detected.
CONCLUSION
A causal effect relationship exists between GD and the gut microbiome, demonstrating regulatory activity and interactions, and thus providing evidence supporting the involvement of a thyroid-gut axis.
Topics: Humans; Gastrointestinal Microbiome; Mendelian Randomization Analysis; Reproducibility of Results; Graves Disease; Clostridiales; Lactobacillales
PubMed: 36865531
DOI: 10.3389/fimmu.2023.977587