Causal effects of specific gut microbiota on musculoskeletal diseases: a bidirectional two-sample Mendelian randomization study

Urolithiasis Causes Osteoporosis in Asians: Genetic Evidence from Mendelian Randomization and Pathway Analysis

BACKGROUND

It is an indisputable fact that patients with urolithiasis are prone to osteoporosis (OP), but the specific mechanism of their association is unclear. Previous studies have focused on the mediation of environmental factors such as diet; however, the potential of urolithiasis itself to induce OP remains uncertain.

METHODS

In this study, we used data from the Japan BioBank (6638 urolithiasis and 7788 OP cases) to investigate the direct causal relationship and mechanism between urolithiasis and OP, applying Mendelian randomization, genetic correlation analysis, colocalization, and pathway analysis. We selected 10 genetic variants as instrumental variables for urolithiasis.

RESULTS

The results showed a positive association between genetically predicted urolithiasis and OP, with significant direct effects persisting after adjusting for OP-associated factors in 4 models. Reverse analysis revealed no significant causal effect of genetically predicted OP on urolithiasis. While genetic correlation analysis and colocalization did not find conclusive evidence, mediation analysis identified estimated glomerular rate as a significant contributor. Co-risk factor analysis unveiled cardiovascular elements as common risks for both conditions. Bioanalysis implicates that cytokine, metabolic, and calcium signaling pathways may bridge urolithiasis and OP, with BCAS3, DGKH, TBX2, and TBX2-AS1 identified as potential causal genes.

CONCLUSION

In conclusion, the study establishes a direct causal link between urolithiasis and OP, independent of environmental factors. Regardless of lifestyle, urolithiasis patients should remain vigilant about the risk of OP and consider regular OP screening. The biological mechanism of urolithiasis combined with OP and related drugs still needs to be further explored.

Granola consumption with multiple prebiotics in Japanese participants increases Bifidobacterium abundance and improves stress and subjective sleepiness

Background

Sleep is essential for physical and mental health. However, stress-related sleep disorders are common in Japan, and the gut-brain axis may play a role in sleep and stress management. This study investigated whether the consumption of granola containing multiple prebiotic ingredients could alleviate stress and improve insomnia in adults with stress-related sleep problems, regardless of individual differences in the gut microbiota. Additionally, we aimed to investigate the relationship between changes in gut microbiota and the observed improvements.

Method

A single-arm uncontrolled trial was conducted with 27 adults with high stress levels and sleep disturbance. The participants consumed 50 g of prebiotics-containing granola daily for 8 weeks. Subjective sleep quality was assessed using the Athens Insomnia Scale, Epworth Sleep Scale, and Oguri-Shirakawa-Azumi Sleep Inventory-Middle-aged and Aged version (OSA-MA). Stress levels were assessed by administering the Brief Job Stress Questionnaire and Profile of Mood States 2nd edition (POMS2). Gut microbiota composition was analyzed using 16S rDNA sequencing.

Results

After 8 weeks, subjective insomnia scores and sleep onset and maintenance improved significantly, whereas the stress and mood disturbance scores decreased significantly. Gut microbiota analysis showed that the relative abundance of Bifidobacterium increased, whereas that of Bacteroides decreased. Correlation analysis suggested a significant association between increased Bifidobacterium level and reduced stress (r = -0.39, p = 0.0035) and insomnia levels (r = -0.3, p = 0.026).

Conclusion

Prebiotics-containing granola improved subjective sleep quality and reduced stress in adults with stress-related sleep disturbances, which may be attributed to alterations in gut microbiota, particularly the increase in Bifidobacterium abundance.

Causal associations between 26 musculoskeletal disorders and gut microbiota: a Mendelian randomization analysis with Bayesian validation

Emerging evidence suggests that gut microbiota imbalances may influence the onset of musculoskeletal disorders (MSDs), yet conclusive evidence establishing causation remains limited. This study investigates the causal relationship between gut microbiota and a range of MSDs, aiming to identify potential therapeutic targets. Using data on 211 gut microbiome taxa from a genome-wide association study (GWAS) and summary statistics for 26 MSDs from the Finnish Biobank, we employed Mendelian randomization (MR) with inverse-variance weighting (IVW) as the primary analytical approach, complemented by Bayesian model validation to ensure robust results. Our MR analyses revealed significant causal associations between gut microbiota and nine MSDs within four categories, including osteoporosis (IVW-Beta = 0.011, P = 0.025), rheumatoid arthritis (IVW-Beta = - 0.016, P < 0.001), rotator cuff syndrome (IVW-Beta = - 0.007, P = 0.022), and calcific tendonitis of the shoulder (IVW-Beta = - 0.021, P = 0.034). Bayesian validation underscored the plausibility of these relationships, supporting the potential causal role of gut microbiota in the development of these disorders. Our findings present a library of causal associations that underscore the gut microbiome's role in MSD pathogenesis, providing genetic evidence that highlights specific gut microbiota taxa as prospective therapeutic targets. This research offers novel insights into the pathogenic mechanisms underlying MSDs and points toward new directions for future investigation into microbiome-based therapies.

Gut microbiota in patients with sarcopenia: a systematic review and meta-analysis

Background

Intestinal dysbiosis was considered a pivotal pathological mechanism underlying sarcopenia. Despite the fervor surrounding research in this domain, substantial controversy persists regarding the obtained outcomes.

Objective

To systematically summarized the disparities in gut microbiota composition between the group afflicted by sarcopenia and non-sarcopenia controls.

Methods

PubMed, Medline, CINAHL, EMBASE, Scopus, Web of Science and Google Scholer, Cochrane Library and gray literature sources were systematically searched for in randomized controlled trials. Meta-analysis and random-effects meta-regression were conducted using Rev. Man 5.3. Overall effect was measured using Hedges's g and determined using Z-statistics. Cochran's Q test and I 2 were used to investigate heterogeneity. The Newcastle-Ottawa Scale was used to assess overall quality of evidence.

Results

Ten studies, including 421 cases of sarcopenia and 1,642 cases of controls, were included in the meta-analysis. Patients with sarcopenia showed significantly reduced gut microbiota in α diversity, and β diversity was significantly different in 8/9 of included studies. We also found more abundance of phylum Proteobacteria and genus Escherichia-Shigella, and less abundance of phylum Firmicutes and genus Faecalibacterium, Prevotella 9, Blautia in the sarcopenia group.

Conclusion

The gut microbiota composition in patients with sarcopenia has undergone alterations, serving as a fundamental reference for further investigation into the potential pathogenic mechanisms and treatment strategies for sarcopenia.

Mendelian randomization studies of risk and protective factors for osteoporosis: a systematic review and meta-analysis

Background

Mendelian randomization is believed to attenuate the biases inherent in observational studies, yet a meta-analysis of Mendelian randomization studies in osteoporosis has not been conducted thus far. This study aims to evaluate the connection between potential causal factors and the risk of osteoporosis by synthesizing evidence from Mendelian randomization studies.

Methods

The databases PubMed, Web of Science, and Embase were systematically searched for Mendelian randomization studies investigating factors influencing osteoporosis up to May 2024. Meta-analyses were conducted to assess the associations between various potential pathogenic factors and osteoporosis using Mendelian Randomization studies. The quality of the study was evaluated according to the Strengthening the Reporting of Observational Studies in Epidemiology via Mendelian Randomization (STROBE-MR) guidelines.

Results

A total of 706 potentially relevant articles were screened, resulting in the inclusion of 53 studies in the systematic review, of which 30 were eligible for the meta-analysis. The combined findings from these 30 studies revealed that rheumatoid arthritis, inflammatory bowel disease, sex hormone binding globulin, depression, non-alcoholic fatty liver disease, primary biliary cholangitis and asthma are associated with increased risk of osteoporosis, while basal metabolic rate and gut microbiota (NB1n) serves as a protective factor. However, the association between obesity, type 2 diabetes mellitus, metformin, ulcerative colitis, leisure sedentary behaviors, systemic lupus erythematosus, serum iron and osteoporosis was found to be nonsignificant.

Conclusion

In summary, our meta-analysis indicates that significant causal relationships with osteoporosis's onset and progression have been established for rheumatoid arthritis, inflammatory bowel disease, primary biliary cholangitis, non-alcoholic fatty liver disease, depression, sex hormone binding globulin, basal metabolic rate, gut microbiota (NB1n), and asthma.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, identifier PROSPERO CRD42024540504.

Mendelian randomization studies in ankylosing spondylitis: A systematic review

INTRODUCTION

Previous research has revealed connections between ankylosing spondylitis (AS) and comorbid conditions. However, observational studies frequently encounter difficulties in establishing definitive causal links between potential risk factors and AS. In contrast, Mendelian randomization (MR) offers a more robust approach to exploring causality by leveraging the random allocation of alleles at birth, thereby minimizing confounding factors.

METHODS

The PubMed, Web of Science, and Cochrane databases were searched for MR studies related to AS with a time frame of database creation to May 2024. Information on authors, exposures, outcomes, data sources, SNPs, MR analysis methods, ORs (95% CIs), and p-values was extracted. Quality assessment was performed using the Critical Appraisal Skills Program (CASP) checklist.

RESULTS

We systematically reviewed 42 MR studies in AS. Health behaviors, comorbidities, and serum markers were involved. Overall, physical activity, inflammatory bowel disease, and specific intestinal flora with serum markers as exposures were causally associated with AS, which leads to an increased risk with several comorbidities.

CONCLUSIONS

MR is a powerful tool for assessing causal relationships between risk factors and outcomes. Specific intestinal flora and inflammatory bowel disease appear to be uncontroversial risk factors that increase the risk of AS. Reliable and robust MR findings may provide a more comprehensive health management strategy for patients with AS.

Chronic Low Back Pain Causal Risk Factors Identified by Mendelian Randomization: a Cross-Sectional Cohort Analysis

Background Context

There are a number of risk factors- from biological, psychological, and social domains- for non-specific chronic low back pain (cLBP). Many cLBP treatments target risk factors on the assumption that the targeted factor is not just associated with cLBP but is also a cause (i.e, a causal risk factor). In most cases this is a strong assumption, primarily due to the possibility of confounding variables. False assumptions about the causal relationships between risk factors and cLBP likely contribute to the generally marginal results from cLBP treatments.

Purpose

The objectives of this study were to a) using rigorous confounding control compare associations between modifiable causal risk factors identified by Mendelian randomization (MR) studies with associations in a cLBP population and b) estimate the association of these risk factors with cLBP outcomes.

Study Design/Setting

Cross sectional analysis of a longitudinal, online, observational study.

Patient Sample

1,376 participants in BACKHOME, a longitudinal observational e-Cohort of U.S. adults with cLBP that is part of the NIH Back Pain Consortium (BACPAC) Research Program.

Outcome Measures

Pain, Enjoyment of Life, and General Activity (PEG) Scale.

Methods

Five risk factors were selected based on evidence from MR randomization studies: sleep disturbance, depression, BMI, alcohol use, and smoking status. Confounders were identified using the ESC-DAG approach, a rigorous method for building directed acyclic graphs based on causal criteria. Strong evidence for confounding was found for age, female sex, education, relationship status, financial strain, anxiety, fear avoidance and catastrophizing. These variables were used to determine the adjustment sets for the primary analysis. Potential confounders with weaker evidence were used for a sensitivity analysis.

Results

Participants had the following characteristics: age 54.9 ± 14.4 years, 67.4% female, 60% never smokers, 29.9% overweight, 39.5% obese, PROMIS sleep disturbance T-score 54.8 ± 8.0, PROMIS depression T-score 52.6 ± 10.1, Fear-avoidance Beliefs Questionnaire 11.6 ± 5.9, Patient Catastrophizing Scale 4.5 ± 2.6, PEG 4.4 ± 2.2. In the adjusted models alcohol use, sleep disturbance, depression, and obesity were associated with PEG, after adjusting for confounding variables identified via a DAG constructed using a rigorous protocol. The adjusted effect estimates- the expected change in the PEG outcome for every standard deviation increase or decrease in the exposure (or category shift for categorical exposures) were the largest for sleep disturbance and obesity. Each SD increase in the PROMIS sleep disturbance T-score resulted in a mean 0.77 (95% CI: 0.66, 0.88) point increase in baseline PEG score. Compared to participants with normal BMI, adjusted mean PEG score was slightly higher by 0.37 points (95% CI: 0.09, 0.65) for overweight participants, about 0.8 to 0.9 points higher for those in obesity classes I and II, and 1.39 (95% CI: 0.98, 1.80) points higher for the most obese participants. Each SD increase in the PROMIS depression T-score was associated with a mean 0.28 (95% CI: 0.17, 0.40) point increase in baseline PEG score, while each SD decrease in number of alcoholic drinks per week resulted in a mean 0.12 (95%CI: 0.01, 0.23) increase in baseline PEG score in the adjusted model.

Conclusions

Several modifiable causal risk factors for cLBP - alcohol use, sleep disturbance, depression, and obesity- are associated with PEG, after adjusting for confounding variables identified via a DAG constructed using a rigorous protocol. Convergence of our findings for sleep disturbance, depression, and obesity with the results from MR studies, which have different designs and biases, strengthens the evidence for causal relationships between these risk factors and cLBP (1). The estimated effect of change in a risk factors on change in PEG were the largest for sleep disturbance and obesity. Future analyses will evaluate these relationships with longitudinal data.

Causal association of juvenile idiopathic arthritis or JIA-associated uveitis and gut microbiota: a bidirectional two-sample Mendelian randomisation study

Background

The gut microbiota significantly influences the onset and progression of juvenile idiopathic arthritis (JIA) and associated uveitis (JIAU); however, the causality remains unclear. This study aims to establish a causal link between gut microbiota and JIA or JIAU.

Methods

Using publicly available genome-wide association studies (GAWS) summary data, we conducted a two-sample Mendelian randomisation (MR) analysis employing various methods, namely inverse variance weighted (IVW), simple mode, weighted mode, weighted median and MR-Egger regression methods, to assess the causal association between JIA or JIAU and gut microbiota. Sensitivity analyses, including Cochrane's Q test, MR-Egger intercept test, leave-one-out analysis and MR-PRESSO, were performed to evaluate the robustness of the MR results. Subsequently, reverse MR analysis was conducted to determine causality between gene-predicted gut microbiota abundance and JIA or JIAU.

Results

The MR analysis revealed a causal association between gut microbiota abundance variations and JIA or JIAU risk. Specifically, the increased abundance of genus Ruminococcaceae UCG013 (OR: 0.055, 95%CI: 0.006-0.103, p = 0.026) and genus Ruminococcaceae UCG003 (β: 0.06, 95%CI: 0.003-0.117, p = 0.041) correlated with an increased risk of JIA, while genus Lachnospiraceae UCG001 (OR: 0.833, 95%CI: 0.699~0.993, p = 0.042) was associated with a reduced risk of JIA, among others. Sensitivity analysis confirmed MR analysis robustness.

Conclusions

This study provides substantial evidence supporting a causal association between genetically predicted gut microbiota and JIA or JIAU. It highlights the significant role of intestinal flora in JIA or JIAU development, suggesting their potential as novel biomarkers for diagnosis and prevention. These findings offer valuable insights to mitigate the impact of JIA or JIAU.

Exploring Causal Links Between Gut Microbiota and Geriatric Syndromes: A Two-Sample Mendelian Randomization Analysis

Background: Both observational studies and clinical trials have demonstrated a link between the gut microbiota and the geriatric syndrome. Nevertheless, the exact nature of this relationship, particularly concerning causality, remains elusive. Mendelian randomization (MR) is a method of inference based on genetic variation to assess the causal relationship between an exposure and an outcome. In this study, we conducted a two-sample Mendelian randomization (TSMR) study to fully reveal the potential genetic causal effects of gut microbiota on geriatric syndromes. Methods: This study used data from genome wide association studies (GWAS) to investigate causal relationships between the gut microbiota and geriatric syndromes, including frailty, Parkinson's disease (PD), delirium, insomnia, and depression. The primary causal relationships were evaluated using the inverse-variance weighted method, MR Egger, simple mode, weighted mode and weighted median. To assess the robustness of the results, horizontal pleiotropy was examined through MR-Egger intercept and MR-presso methods. Heterogeneity was assessed using Cochran's Q test, and sensitivity was evaluated via the leave-one-out method. Results: We identified 41 probable causal relationships between gut microbiota and five geriatric syndrome-associated illnesses using the inverse-variance weighted method. Frailty showed five positive and two negative causal relationships, while PD revealed three positive and four negative causal connections. Delirium showed three positive and two negative causal relationships. Similarly, insomnia demonstrated nine positive and two negative causal connections, while depression presented nine positive and two negative causal relationships. Conclusions: Using the TSMR method and data from the public GWAS database and, we observed associations between specific microbiota groups and geriatric syndromes. These findings suggest a potential role of gut microbiota in the development of geriatric syndromes, providing valuable insights for further research into the causal relationship between gut microbiota and these syndromes.

Causal associations between gut microbiota with intervertebral disk degeneration, low back pain, and sciatica: a Mendelian randomization study

PURPOSE

Although studies have suggested that gut microbiota may be associated with intervertebral disk disease, their causal relationship is unclear. This study aimed to investigate the causal relationship between the gut microbiota and its metabolic pathways with the risk of intervertebral disk degeneration (IVDD), low back pain (LBP), and sciatica.

METHODS

Genetic variation data for 211 gut microbiota taxa at the phylum to genus level were obtained from the MiBioGen consortium. Genetic variation data for 105 taxa at the species level and 205 metabolic pathways were obtained from the Dutch Microbiome Project. Genetic variation data for disease outcomes were obtained from the FinnGen consortium. The causal relationships between the gut microbiota and its metabolic pathways and the risk of IVDD, LBP, and sciatica were evaluated via Mendelian randomization (MR). The robustness of the results was assessed through sensitivity analysis.

RESULTS

Inverse variance weighting identified 46 taxa and 33 metabolic pathways that were causally related to IVDD, LBP, and sciatica. After correction by weighted median and MR-PRESSO, 15 taxa and nine pathways remained stable. After FDR correction, only the effect of the genus_Eubacterium coprostanoligenes group on IVDD remained stable. Sensitivity analyses showed no evidence of horizontal pleiotropy, heterogeneity, or reverse causation.

CONCLUSION

Some microbial taxa and their metabolic pathways are causally related to IVDD, LBP, and sciatica and may serve as potential intervention targets. This study provides new insights into the mechanisms of gut microbiota-mediated development of intervertebral disk disease.

Microbiota during pregnancy and early life: role in maternal-neonatal outcomes based on human evidence

Here, we explored the vast potential of microbiome-based interventions in preventing and managing non-communicable diseases including obesity, diabetes, allergies, celiac disease, inflammatory bowel diseases, malnutrition, and cardiovascular diseases across different life stages. We discuss the intricate relationship between microbiome and non-communicable diseases, emphasizing on the "window of opportunity" for microbe-host interactions during the first years after birth. Specific biotics and also live biotherapeutics including fecal microbiota transplantation emerge as pivotal tools for precision medicine, acknowledging the "one size doesn't' fit all" aspect. Challenges in implementation underscore the need for advanced technologies, scientific transparency, and public engagement. Future perspectives advocate for understanding maternal-neonatal microbiome, exploring the maternal exposome and delving into human milk's role in the establishment and restoration of the infant microbiome and its influence over health and disease. An integrated scientific approach, employing multi-omics and accounting for inter-individual variance in microbiome composition and function appears central to unleash the full potential of early-life microbiome interventions in revolutionizing healthcare.