Abstract
This study employs Mendelian randomization (MR) approach to investigate the potential causal association between genetic variants associated with gut microbiota, inflammatory factors, and the risk of uterine fibroids development. We extracted data on 211 types of gut microbiota, 91 inflammatory factors, and uterine fibroids occurrence from genome-wide association studies and applied the inverse-variance weighted (IVW) method for analysis. To further assess the robustness of our MR analysis, we conducted sensitivity tests including Cochrane’s Q test, the MR-Egger intercept test, the MR-PRESSO global test, and a leave-one-out analysis. IVW analysis identified a potential causal association between 14 types of gut microbiota and 8 inflammatory factors with the risk of uterine fibroids. When using 91 inflammation-related proteins as the outcome variable, 13 proteins demonstrated a potential causal association with uterine fibroids risk (IVW, all P < .05). Additionally, the MR-Egger intercept and MR-PRESSO global tests indicated no evidence of horizontal pleiotropy (P > .05), and the leave-one-out analysis confirmed the robustness of the results. This MR approach suggests that specific gut microbiota and inflammatory factors may have a causal association with the development of uterine fibroids, shedding light on the pathogenesis of uterine fibroids and potentially identifying targets for future therapeutic interventions.
Keywords: gut microbiota, inflammation factors, inverse-variance weighted, Mendelian randomization, uterine fibroids
1. Introduction
Uterine fibroids are the most common type of benign tumor in the female reproductive system, arising from the proliferation of uterine smooth muscle cells and affecting up to 80% of premenopausal women. These tumors can result in significant health issues, including heavy menstrual bleeding, pelvic pain, and infertility.[1] Recent research has highlighted the involvement of growth factors, genetic predispositions, estrogenic isoflavones, cytokines, inflammatory chemokines, and extracellular matrix remodeling in the pathogenesis of uterine fibroids. However, the association between gut microbiota, inflammatory factors, and uterine fibroids remains underexplored.[2,3]
The human gut contains approximately 100 trillion bacteria, which not only aid in the digestion and absorption of nutrients but also play a critical role in infection prevention, immune regulation, inflammation modulation, and hormonal balance.[4–6] Uterine fibroids are hormone-dependent tumors, predominantly influenced by estrogen and progesterone.[7,8] Several studies have suggested that gut microbiota are involved in estrogen metabolism via the enterohepatic circulation. Disruptions in gut microbiota composition may influence hormone levels, thereby impacting the development and growth of uterine fibroids.[9,10] Alterations in the gut microbiome can modify the reabsorption and excretion of estrogen, which may affect estrogen-dependent conditions like uterine fibroids.[11,12]
Chronic inflammation is considered to be one of the causative factors in the development of a number of tumors, including uterine fibroids. Dysbiosis of the gut microbiota has been associated with systemic inflammation and immune dysregulation, which may increase the risk of developing uterine fibroids.[13,14] Some studies have reported that the gut microbiota may influence intestinal inflammation in several ways, including through microbial metabolites, immune modulation, and intestinal barrier function.[14,15] Therefore, there is a need to explore in depth the influence of the gut microbiome in hormone metabolism and inflammatory response on the pathogenesis of uterine fibroids.[16]
Mendelian randomization (MR) studies utilize single nucleotide polymorphisms (SNPs) as instrumental variables (IVs) for exposure factors. The random assortment of these SNPs mimics the random allocation in clinical trials, allowing MR studies to function as a natural experiment to investigate causal associations between exposures and outcomes.[17] This study employs MR to explore the potential causal association between gut microbiota, inflammatory factors, and uterine fibroids, offering new insights for future clinical diagnosis and treatment strategies for uterine fibroids.
2. Methods
2.1. Study design
The MR studies are employed to investigate the causal association between gut microbiota, inflammatory factors, and uterine fibroids (Fig. 1A). The MR design is based on 3 core assumptions. First, the SNPs used as instrumental variables must have a strong association with the exposure of interest. Second, these SNPs should not be related to the outcome through confounding factors. Third, the SNPs should not have a direct effect on the outcome, except through the exposure being studied (Fig. 1B). Previous research has extensively described this methodology in the context of published studies and publicly available summary data, thus negating the need for additional ethical approval or informed consent from participants.
Figure 1.
(A) Diagram for MR study. MR is based on 3 hypotheses. First of all, SNPs identified as IVs should be strongly associated with exposure; secondly, selected SNPs must be independent of confounders; and finally, IVs are associated with outcome only via exposure, rather than through a direct association. (B) Three core assumptions of MR. GWAS = genome-wide association study, IVs = instrumental variables, IVW = inverse variance-weighted, MR = Mendelian randomization, SNP = single nucleotide polymorphism.
2.2. Data sources for gut microbiota and screening criteria for IVs
Gut microbiota data were obtained from the MiBioGen consortium (Table 1). The dataset includes 16S rRNA gene sequencing profiles and genotyping data from 18,340 individuals across 11 countries, including regions in Asia and Europe. This data was used to identify genetic loci influencing the relative abundance or presence of microbial taxa. A total of 211 traits across 35 families, 20 orders, 16 phyla, 9 classes, and 131 genera were represented in the gut microbiota dataset. Given the limited availability of SNP loci with P values < 1 × 10−8 for gut microbiota traits, SNPs with P values < 1 × 10−5 were selected instead. The loci identified through this screening process were then used as instrumental variables to represent gut microbiota, a clinical risk exposure factor, in the analysis.[18,19] Data from SNPs with linked or unbalanced aggregates were subsequently excluded, with removal based on linkage disequilibrium criteria (r² < 0.001, distance = 10,000 kb). Additionally, SNPs that were not associated with a specific bacterial trait were excluded from the analysis.
Table 1.
Details of the genome wide association studies and datasets used in this study.
| Exposure/outcome | Year | Author | Participants | Number of SNPs | Web source if publicly |
|---|---|---|---|---|---|
| Uterine fibroids (ebi-a-GCST90018934) (PMID:34594039) | 2021 | Sakaue S | 258,718 individuals (21,024 cases and 237,694 controls) of European ancestry | 24,129,853 | https://gwas.mrcieu.ac.uk/datasets/ebi-a-GCST90018934/ (Access time: December 29, 2023) |
| Human gut microbiome (PMID:33462485) | 2021 | Kurilshikov | 18,340 individuals of Asian and European ancestry | NA | https://mibiogen.gcc.rug.nl (Access time: December 29, 2023) |
| 91 circulating inflammation-related proteins (PMID:37563310) | 2023 | Zhao JH | 14,824 individuals of European ancestry | NA | https://www.eqtlgen.org/cis-eqtls.html (Access time:December 29, 2023) |
SNP = single nucleotide polymorphism.
2.3. Data sources for 91 inflammatory factors and screening criteria for IVs
The genetic predictors for 91 inflammatory regulatory factors were derived from the largest cytokine-related Genome Wide Association Study (GWAS) meta-analysis to date, which included 11 independent cohorts comprising a total of 14,824 participants of European descent (Table 1).[20] SNPs were selected based on the following criteria: P value < 1 × 10−5, linkage disequilibrium r² < 0.001, and a distance of < 10,000 kb.
2.4. Data sources of uterine fibroids
Data on uterine fibroids (ebi-a-GCST90018934), comprising 21,024 cases and 237,694 controls, were obtained from the GWAS, which includes a total of 24,129,853 SNPs. All participants in this dataset are of European descent.
2.5. Statistical methods
The inverse variance weighting (IVW) method from the TwoSampleMR package was used for the analyses. Phenotype scanning of the screened SNPs was also performed in this study. All data analyses were conducted using R software (version 4.3.1) and the “TwoSampleMR” package (version 0.5.6, Mount Sinai, New York). Differences were considered statistically significant if the P value < .05.[21]
2.6. Sensitivity analysis
Heterogeneity was assessed using the P value from Cochran’s Q test. The pleiotropy test was conducted to verify the reliability of the MR analysis results, with the MR-Egger intercept used to assess pleiotropy. The intercept P value > .05 indicates the absence of horizontal pleiotropy.
3. Result
3.1. Screening SNPs to analyze causal associations between gut microbiome, inflammatory factors and uterine fibroids
Using the screening criteria for IVs, this study identified 2201 SNPs from the gut microbiome dataset to analyze their potential causal association with uterine fibroids. From the inflammatory factor dataset, 2743 SNPs were selected for the analysis of causal associations with uterine fibroids. When uterine fibroids were treated as the exposure factor, 111 SNPs were screened for possible causal associations (Tables S1–S3, Supplemental Digital Content, http://links.lww.com/MD/N985).
3.2. Fourteen gut microbiotas might be potentially causally associated with the risk of developing uterine fibroids
IVW analysis showed that 7 species, including Paraprevotella genus id.962 (odds ratio [OR] = 0.92, 95% confidence interval [CI]: 0.87–0.97, P = .006), Lachnoclostridium genus id.11308 (OR = 0.89, 95% CI: 0.81–0.98, P = .016) and other gut microbiota was negatively associated with uterine fibroids. In contrast, 7 gut microbiotas including Lachnospiraceae UCG010 id.11330 (OR = 1.15, 95% CI: 1.00–1.33, P = .049) were positively associated with uterine fibroids (Fig. 2A).
Figure 2.
Causal association between gut microbiota and inflammatory factors and uterine fibroids. (A) 14 gut microbiota that may be causally associated with the risk of developing uterine fibroids were demonstrated using forest plots and bubble diagrams. (B) 8 inflammatory factors that may be causally associated with the risk of developing uterine fibroids were demonstrated using forest plots and bubble diagrams. (C) Forest plots and bubble plots were used to demonstrate the changes in the expression of 13 inflammatory factors that may to affect uterine fibroids.
3.3. Eight inflammatory factors might be potentially causally related to the risk of developing uterine fibroids
IVW analysis showed that 4 inflammatory factors including Fms-related tyrosine kinase 3 ligand levels (OR = 0.91, 95% CI: 0.83–0.98, P = .023) may be negatively associated with uterine fibroids. Meanwhile, IVW analysis showed that 4 inflammatory factors, including interleukin-4 levels (OR = 1.08, 95% CI: 1.00–1.16, P = .034) may be positively associated with uterine fibroids (Fig. 2B).
3.4. Uterine fibroids might be potentially causally related to changes in 12 inflammatory factors
At the same time, this study conducted a reverse study on inflammatory factors and uterine fibroids. The IVW analysis results show that only Osteoprotegerin levels may be negatively correlated with uterine fibroids (OR = 0.95, 95% CI: 0.91–0.99, P = .030). Meanwhile, IVW analysis showed that 12 inflammatory factors including T cell surface glycoprotein CD5 levels (OR = 1.07, 95% CI: 1.02–1.11, P = .001) and natural killer cell receptor 2B4 level (OR = 1.07, 95% CI: 1.02–1.11, P = .001) would have an elevated expression following the presence of uterine fibroids (Fig. 2C).
3.5. Sensitivity analysis
The results of the heterogeneity test showed that there was no heterogeneity among the SNPs (P > .05). The results of the MR Egger regression intercept showed that there was no horizontal multiplicity in the correlation between intestinal flora and aneurysms. The results of leave-one-out analysis showed that there were no SNPs that had a significant impact on the effect estimate. In summary, the results of this study were relatively stable (Table S4, Supplemental Digital Content, http://links.lww.com/MD/N985). Phenotype scanning results can be found in Table S5, Supplemental Digital Content, http://links.lww.com/MD/N985.
4. Discussion
This study employed the MR approach to investigate the potential causal association between genetic variations related to gut microbiota, inflammatory factors, and the risk of developing uterine fibroids. We identified a potential causal association between 14 types of gut microbiota and 8 inflammatory factors with the risk of uterine fibroids. These findings offer new insights into the pathogenesis of uterine fibroids and underscore the potentially significant role of gut microbiota in women’s reproductive health.
Fourteen gut microbiotas obtained from the MR analysis can be divided into 2 main categories, “phylum” and “order.” Among them, the gut microbiota belonging to the “phylum” include Firmicutes, Proteobacteria and Actinobacteria. The groups in this phylum mainly include Lachnoclostridium, Ruminococcaceae UCG-003, Lachnospiraceae NC2004 group, Eubacterium hallii group, Clostridium innocuum group, Lachnospiraceae UCG-010, and Tyzzerella 3. These bacteria are commonly associated with the synthesis of short-chain fatty acids, which can potentially influence the immune status of the host by modulating the intestinal environment and reducing inflammatory responses. Short-chain fatty acids contribute to the maintenance of intestinal health and reduce chronic inflammation, thereby potentially reducing the risk of uterine fibroids.[22,23] Alphaproteobacteria in the phylum Proteobacteria also play an important role in host metabolism and immune regulation, and these bacteria may have an impact on uterine health by influencing the balance of intestinal microecology and modulating the host’s inflammatory response. Meanwhile, the Actinomycetaceae family of bacteria belonging to the phylum Actinobacteria also have important functions in metabolism, and can influence host health through immunomodulation and the promotion of intestinal health, which may have an impact on the risk of uterine fibroids. In terms of “orders,” bacteria in the order Lactobacillales are widely regarded as probiotics that maintain gut health by inhibiting the growth of pathogenic bacteria and enhancing immune function, which may reduce the risk of uterine fibroids. We also found that Lachnoclostridium and E Eubacterium hallii group are both anaerobic bacteria which produce short-chain fatty acids such as butyric acid, which suppresses inflammation and promotes the development of regulatory T-cells, thereby maintaining immune tolerance, suggesting that the gut microbiota may influence uterine fibroids formation through immune modulation. Bacteria in the order Actinomycetales, on the other hand, play a key role in maintaining gut microecological stability and promoting host health.
Our study also explored the causal association between 91 recently published inflammatory factors and uterine fibroids, identifying 3 inflammatory factors (C–C motif chemokine 19, fibroblast growth factor 19, and TNF-beta) that may be closely associated with the risk of developing uterine fibroids. C–C motif chemokine 19 is a chemokine that attracts and activates specific types of white blood cells, such as T and B cells.[24,25] Based on existing research, we hypothesize that elevated levels of C–C motif chemokine 19 may direct immune cells to accumulate in uterine fibroids tissues, triggering an inflammatory response and promoting fibroid growth. However, it remains unclear whether C–C motif chemokine 19 might also affect hormone levels and, in turn, influence fibroid development. Fibroblast growth factor 19 (FGF19) is involved in regulating bile acid and energy metabolism and has been linked to metabolic diseases.[26,27] Additionally, studies suggest that FGF19 may have anti-inflammatory and anti-proliferative effects. Our findings, which show a negative correlation between FGF19 levels and uterine fibroids risk, suggest that elevated FGF19 may suppress inflammation and cell proliferation, thereby inhibiting fibroid growth and reducing the risk of fibroid development. We also found that TNF-beta levels may be negatively associated with the risk of uterine fibroids. TNF-beta is a cytokine that plays a critical role in the proliferation, differentiation, and activation of immune cells, contributing to the normal functioning of the immune system. Additionally, TNF-beta may regulate apoptosis, helping to eliminate abnormal cells that could potentially form fibroids. Therefore, we hypothesize that TNF-beta may reduce the risk of uterine fibroids by alleviating chronic inflammation and clearing abnormal cells that might otherwise develop into fibroids.[28,29]
In the reverse MR analysis, we identified 13 inflammatory factors potentially related to uterine fibroids. However, none of these matched the inflammatory factors identified in the initial analysis. Among them, only Osteoprotegerin levels were negatively correlated with the risk of developing uterine fibroids. Osteoprotegerin is a member of the tumor necrosis factor receptor superfamily and primarily influences inflammatory responses through its interactions with its ligand, RANKL, and receptor, RANK.[30]
This study has several notable strengths. First, it utilized a comprehensive and large-scale dataset, analyzing 211 types of gut microbiota and 91 inflammatory factors. The extensive scope of the data enhances the robustness and reliability of the findings, providing a solid basis for exploring the potential causal associations between these variables and uterine fibroids risk. Second, the use of MR is a key strength, as this approach helps mitigate confounding factors and reverse causality by mimicking a randomized control trial. This method strengthens the causal inferences drawn from the analysis. Finally, the study provides novel insights into the pathogenesis of uterine fibroids, identifying specific gut microbiota and inflammatory factors that may play a role in fibroid development. These findings could offer new directions for the development of biomarkers and therapeutic targets, contributing to more personalized treatment strategies in clinical practice.
Despite these strengths, the study has some limitations. First, all data were derived from participants of European descent, limiting the generalizability of the findings to other populations. Further research including diverse ethnic groups is needed to validate these results. Second, due to the limited availability of strong SNP associations (P < 1 × 10−8) for gut microbiota traits, the study used SNPs with a less stringent threshold (P < 1 × 10−5), which may introduce weaker associations and affect the robustness of the findings related to gut microbiota. Third, while the study identified potential causal associations, it did not investigate the underlying biological mechanisms. Future studies should focus on elucidating the specific molecular pathways through which gut microbiota and inflammatory factors influence the development of uterine fibroids.
5. Conclusion
This study identified potential causal links between specific gut microbiota, inflammatory factors, and the development of uterine fibroids using the MR approach. These findings offer new insights into the pathogenesis of uterine fibroids, with gut microbiota and inflammation emerging as possible therapeutic targets. However, the study’s limitations include its focus on a specific population and the need for further investigation into the underlying biological mechanisms. Future research should validate these findings in more diverse populations and explore the molecular pathways involved.
Author contributions
Conceptualization: Shaoyi Peng, Miao Liu, Yuhao Zeng, Lei Wang.
Data curation: Shaoyi Peng, Miao Liu.
Formal analysis: Miao Liu.
Methodology: Shaoyi Peng.
Project administration: Yilong Man.
Supervision: Lei Wang.
Validation: Lei Wang.
Visualization: Yilong Man.
Writing – original draft: Shaoyi Peng, Miao Liu, Yuhao Zeng.
Writing – review & editing: Lei Wang, Yilong Man.
Supplementary Material
Abbreviations:
- CI
- confidence interval
- GWAS
- Genome Wide Association Study
- IVs
- instrumental variables
- IVW
- inverse variance weighted
- MR
- Mendelian randomization
- OR
- odds ratio
- SNPs
- single nucleotide polymorphisms
The authors have no funding and conflicts of interest to disclose.
All data generated or analyzed during this study are included in this published article [and its supplementary information files].
Supplemental Digital Content is available for this article.
How to cite this article: Peng S, Liu M, Zeng Y, Wang L, Man Y. Exploring the gut-inflammation connection: A Mendelian randomization study on gut microbiota, inflammatory factors, and uterine fibroids risk. Medicine 2024;103:47(e40514).
SP, ML and, YZ contributed to this article equally.
Contributor Information
Shaoyi Peng, Email: 1239852850@qq.com.
Miao Liu, Email: 836518522@qq.com.
Yuhao Zeng, Email: zengyuhao17@163.com.
Yilong Man, Email: 1036474530@qq.com.
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