Evaluating potential risk factors linked to endometriosis: Evidence from a Mendelian randomization study

1. Introduction Endometriosis (EMT) is a common yet intricate disorder that affects roughly 10% of women of reproductive age across the globe. It constitutes a systemic condition that is long-lasting, inflammatory in character, and dependent on hormonal regulation. Its defining features are the development of glandular and stromal tissue beyond the uterine cavity, together with an abnormal expansion of endometrial tissue. Such a state gives rise to pain, difficulty conceiving, fatigue, and a heightened probability of surgery as well as of developing ovarian cancer and immune-associated disorders.[,] At present, both the causes and the disease mechanisms underlying EMT are still poorly understood. Prevailing hypotheses in the field encompass retrograde menstrual flow, coelomic (luminal) metaplasia, and residual mullerian duct tissue.[] Diagnosis of EMT is frequently postponed, a delay that worsens the disorder and in turn influences how it is treated, its outlook, and the chance of relapse. Pursuing etiological research on EMT is thus of considerable value, since it helps clarify how the disease develops and progresses while enabling earlier detection, intervention, and treatment. A wide array of risk factors connected to EMT has been documented in earlier research. Reproductive and menstrual features rank among the major contributors tightly bound to EMT, including an early onset of menarche, briefer menstrual cycles, and prior infertility.[,] In addition, a slender physique, uterine fibroids, eating habits, and contact with harmful metals have each been shown to bear particular links to EMT.[,] Environmental exposure to poisonous metals such as arsenic, cadmium, lead, and mercury, whether alone or in combination, correlates with a greater likelihood of EMT.[] Beyond this, disturbances during early-life development may further raise the chance of the condition arising.[] Nevertheless, the bulk of the studies noted above are largely observational, which leaves them prone to a range of confounding influences. Moreover, although such work can demonstrate a link between risk factors and disease outcomes, it cannot conclusively confirm whether the causation runs in the reverse direction. As a result, exactly what part these recognized risk factors play in the disease is still undetermined. Mendelian randomization (MR) is a novel method that uses genetic variants as instrumental variables (IVs) to reveal causal links. Because alleles are assigned at random within this framework, it is less susceptible to the confounding and reverse-causation problems that typically beset conventional epidemiological research, thereby curbing bias effectively. Earlier MR analyses have tied leukocyte telomere length (LTL),[] obesity,[] and macrophage colony-stimulating factor[] to a raised risk of EMT. In addition, particular members of the gut microbiome have been flagged as possible causal contributors to EMT.[,] Even so, MR-based investigation of EMT is still fairly sparse. For this reason, the present study sets out to appraise 108 traits related to EMT in a systematic fashion. 2. Materials and methods 2.1. Data sources The dataset consisted of people of both sexes with European or mixed heritage. A previously established technique was followed.[] While the majority of exposure GWASs originated from the UK Biobank (refer to Table S1, Supplemental Digital Content 1), the EMT data were derived from FinnGen. This study was designed and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology using Mendelian Randomization (STROBE-MR) guideline. Because the present MR analysis was based exclusively on publicly available, de-identified, summary-level statistics from previously published genome-wide association studies (GWAS), no additional ethical approval or informed consent was required for this study. Ethical approval and participant informed consent had already been obtained in each of the original GWAS. The exposure summary statistics for the 108 candidate traits were obtained from the IEU OpenGWAS database (https://gwas.mrcieu.ac.uk/), and the detailed GWAS identifiers for every trait are provided in Table S1, Supplemental Digital Content 1. The outcome data for endometriosis (EMT) were derived from the FinnGen consortium data freeze release 9 (https://www.finngen.fi/), which comprised 15,088 EMT cases and 107,564 female controls of European ancestry. All exposure and outcome datasets were accessed and downloaded in July 2023. 2.2. Selection of IVs By GWAS data, we have pinpointed single nucleotide polymorphisms (SNPs) that are linked to 108 different exposure traits. The SNPs were then utilized as IVs. IVs were chosen according to predetermined standards. One of the criteria was the presence of an association (P-value < 5 × 10−8) between IVs and the exposure. To identify independent IVs, clumps were detected within a 10 Mb segment by applying a clumping approach, which considered the linkage disequilibrium with an R2 threshold of less than 0.001. Consistent with previous studies, we restricted the inclusion of IVs in our research to those with a minor allele frequency exceeding 0.01. SNPs with palindromic alleles were not included in the analysis when their allele frequencies were found to be at an intermediate level.[] F-statistics were generated to evaluate IVs, with a value >10 indicating a lower likelihood of weak instrument bias. For additional details, please consult Table S2, Supplemental Digital Content 2.[] 2.3. MR analysis and sensitivity analysis The primary methodology was the inverse-variance weighted (IVW) method. In addition to the IVW method, the analysis also incorporated the weighted median (WN) and the MR-Egger methodologies, as previously reported.[,] To assess the presence of horizontal pleiotropy, the MR-Egger intercept test was performed. To address pleiotropy and account for any outliers, the study incorporated the Mendelian Randomization Pleiotropy RESidual Sum and Outlier (MR-PRESSO) method to detect and adjust for pleiotropy. Cochran’s Q statistic was used to quantify the level of heterogeneity among the IVs. In order to assess the reliability of the results and examine the impact of each IV on the causal relationships, a leave-one-out sensitivity analysis was conducted, as previously described.[] Causal effects were computed using odds ratios (ORs) along with their 95% confidence intervals (CIs). The false discovery rate for multiple comparisons was set at 5 percent. All MR analyses were employed using the R package TwoSampleMR. To ensure the validity of the causal inference, the IVs were required to satisfy the three core assumptions of MR analysis: the relevance assumption, that the IVs are strongly associated with the exposure, the independence assumption, that the IVs are independent of any confounding factors that may influence the relationship between the exposure and the outcome, and the exclusion-restriction assumption, that the IVs affect the outcome only through the exposure and not through any alternative pathway. The IVW method was applied as the primary analysis. It combines the Wald ratio estimates of all IVs to achieve the greatest statistical efficiency in estimating the causal effect, provided that all instruments are valid. Two complementary methods were used to evaluate the robustness of the IVW estimates under different assumptions: the WM method, which provides a consistent causal estimate when at least half of the genetic information is contributed by valid instruments, and the MR-Egger method, which allows for the presence of directional (horizontal) pleiotropy. Heterogeneity among the individual IV estimates was quantified using Cochran’s Q statistic. A larger Q value with a corresponding P-value < .05 indicates greater heterogeneity, suggesting that the causal estimates of the individual SNPs are inconsistent and that potential horizontal pleiotropy or differences in the underlying causal pathways may exist among the instruments. When substantial heterogeneity was identified, a random-effects IVW model was adopted. Horizontal pleiotropy was further assessed using the MR-Egger intercept test, in which an intercept deviating from 0 with a P-value < .05 was regarded as evidence of directional pleiotropy. Potential outlier variants were detected and corrected using the MR-PRESSO method, and corrected causal estimates were obtained after the removal of the identified outliers. For both the heterogeneity (Cochran’s Q) test and the pleiotropy (MR-Egger intercept) test, a P-value < .05 was considered statistically significant. 3. Results By employing preset inclusion and exclusion criteria, a total of 108 variables were assessed to identify SNPs as IVs for potential risk factors. We observed statistically suggestive associations (P < .05) for 12 genetic risk factors in the MR analysis employing the IVW method, such as “telomere length” (OR = 1.29; 95% CI: 1.13–1.47), “triglycerides (TG)” (OR = 1.13; 95% CI: 1.05–1.21), “high-density lipoprotein (HDL) cholesterol” (OR = 0.89; 95% CI: 0.83–0.95), “Neuroticism score” (OR = 1.11; 95% CI: 1.02–1.20), “Fluid intelligence score” (OR = 0.90; 95% CI: 0.81–1.00), and “Drive faster than motorway speed limit” (OR = 0.50; 95% CI: 0.26–0.97), with EMT (Figs. 1 and 2; Table S3, Supplemental Digital Content 3). The F-statistics of the IVs associated with the 12 risk factors ranged from 29.73 to 20,664.41, as shown in Table S2, Supplemental Digital Content 2, indicating strong instrument strength. Furthermore, strong correlations between telomere length and TG, as well as HDL cholesterol and EMT, persisted even after adjusting for multiple comparisons. Except for glucose, neuroticism score, and usual walking pace, we observed a consistent and significant association in the same direction between 9 risk factors and EMT when analyzed applying WM and MR-Egger methods, as detailed in Table S3, Supplemental Digital Content 3. Figure 3 presents the scatter plot illustrating the causal associations between each of the 12 traits and EMT. Furthermore, potential heterogeneity was assessed, as shown in Table S4, Supplemental Digital Content 4 and Figure S1, Supplemental Digital Content 5. The MR-Egger approach did not reveal any evidence of horizontal pleiotropy, as shown in Table S5, Supplemental Digital Content 6. After correction, the results of the MR-PRESSO analysis remained largely unchanged, except for phosphate (Table S6, Supplemental Digital Content 7). Despite the identification of multiple outliers in the data, the overall impact on the results was minimal. Based on the data presented in Figure S2, Supplemental Digital Content 8, it can be observed that the majority of single SNPs had no significant impact on the outcomes of the leave-one-out study. 4. Discussion Drawing on data obtained from a GWAS, this work assessed how 108 traits relate to the occurrence of EMT. The analysis pinpointed 12 traits that are linked to EMT. Among them are telomere length, HDL cholesterol, TG, glucose, cystatin C, neuroticism score, habitual walking pace, apolipoprotein A, driving above the motorway speed limit, phosphate, hematocrit percentage, and fluid intelligence score. In particular, telomere length, TG, and HDL cholesterol displayed notable associations with the onset of EMT. 4.1. Telomere length Observational research to date has produced conflicting findings on how LTL and EMT are related. One case-control study supported a possible connection between shorter LTL and a greater chance of EMT, particularly among women with moderate-to-severe dysmenorrhea.[] A separate report likewise found that women given an EMT diagnosis tend to show, on average, shorter telomeres.[] By contrast, a prospective study observed that EMT patients had markedly longer mean telomere length within their endometrial tissue.[] Whether LTL and EMT are causally related therefore continues to be contested. A recent 2-directional MR study established that extended LTL corresponds to a higher EMT risk, whereas EMT itself has no causal effect on LTL.[] Consistent with this, our own results lend weight to the notion that greater LTL accompanies an elevated risk of EMT. Two considerations may account for this relationship: experimental data reveal that longer telomeres go hand in hand with enhanced cell multiplication, repair ability, and suppression of apoptosis, and are moreover closely tied to the division, expansion, and upkeep of stem cells.[,,] As a result, by hindering apoptosis in endometrial cells and encouraging stem-cell differentiation, it may promote the invasion and growth of endometrial cells beyond the uterus. Furthermore, because longer telomeres are positively associated with estrogen (E2) concentrations,[] they might drive the growth and division of ectopic endometrial cells by prompting a rise in E2. 4.2. Dyslipidemia: TG, HDL cholesterol, and apolipoprotein A Lipid metabolism is intimately bound up with both the emergence and the progression of EMT. Although the conclusions have not been uniform, prior studies have reported a meaningful correlation between the blood lipid profile and EMT. Pertinent investigations indicate that women affected by EMT display lower HDL cholesterol together with raised TG, total cholesterol, and apolipoprotein A.[] Our own data showed that higher TG, and diminished HDL cholesterol and apolipoprotein A are each associated with a raised risk of EMT. It is broadly accepted that disordered lipid metabolism may drive the onset and advancement of EMT through its influence on oxidative stress, E2, and inflammatory signaling.[] Beyond this, studies have detected elevated apolipoprotein E (ApoE) protein, a central mediator of lipid metabolism, in the follicular fluid of EMT patients, and this increase is strongly connected to the appearance of EMT.[,] 4.3. Psychological factor and behavior: neuroticism score and driving faster than the motorway speed limit The present work clarified the causal ties linking neuroticism scores and driving above the highway speed limit to EMT. A higher neuroticism score was associated with an increased risk of endometriosis, whereas a greater genetically predicted tendency to drive faster than the motorway speed limit was associated with a lower risk. Neuroticism is a heritable personality trait and an important genetic risk factor for psychiatric conditions such as depression and anxiety.[] Endometriosis is itself associated, both epidemiologically and genetically, with depression and anxiety.[] A trait that predisposes to these disorders could therefore plausibly raise the measured risk of endometriosis, so we regard neuroticism as a marker of vulnerability. The protective direction for speeding fits with this same affective pathway. A genetically predicted tendency to drive faster than the speed limit has been causally linked to a lower liability to depression, probably because people who exceed the speed limit tend to be bold and impulsive rather than depressive.[] Because depression is associated with endometriosis, this lower liability to depression offers one plausible route by which the behavior could accompany a reduced risk of EMT. Speeding is nonetheless only a marker of a broader heritable risk-taking disposition,[] so the finding should be confirmed in future studies. 4.4. Glucose Research has recorded diminished blood glucose in EMT patients,[,] a pattern that agrees with what we observed. These same studies additionally noted raised insulin concentrations in EMT patients, a change that may be related to their reduced blood glucose.[] The fall in blood glucose among EMT patients might stem from heightened glycolysis,[] which offers insight into the mechanisms at work. One study detected increased glycolysis alongside reduced mitochondrial respiration impairment in human peritoneal mesothelial cells taken from the pelvic peritoneum of EMT patients.[] These cellular alterations could foster the buildup of reactive oxygen species inside cells and thereby aid the development of EMT. Follow-up experiments showed that administering a glycolysis inhibitor by mouth shrank endometriotic lesions in a mouse model.[] Taken together, these results imply that glucose may act as a protective factor against EMT. 4.5. Usual walking pace Walking speed is regarded as an objective gauge of physical capability that may signal disease and general health.[,] Earlier work has connected a slower walking pace with an increased risk of stroke and death. Our findings indicate that reduced walking speed may likewise accompany a greater risk of EMT.[] Walking pace reflects physical function and is often shaped by muscular strength. Raised concentrations of inflammatory markers, namely C-reactive protein (CRP) and interleukin-6, show an inverse relationship with physical function and muscle strength. Persistent inflammation hastens functional decline and aging, and elevated proinflammatory cytokines such as tumor necrosis factor-α (TNF-α) and interleukin-6 can drive the loss of skeletal muscle strength and mass by promoting muscle catabolism.[] Ongoing inflammation is a major contributor to the pathogenesis of EMT. Accordingly, walking speed could function as a marker of risk for this disease. 4.6. Cystatin C Cystatin C, an endogenously produced marker, inhibits lysosomal cysteine proteases and consequently mirrors variation in the glomerular filtration rate.[] Recent evidence points to a substantial role for cystatin C in the development of several disorders, including cardiovascular disease and tumors,[] establishing it as a rising biomarker. Our MR analysis demonstrated an inverse causal association between cystatin C levels and EMT risk, suggesting a protective role. This finding contrasts with a previous observational study that reported elevated cystatin C in EMT patients.[] The discrepancy may arise from confounding or reverse causation in the observational design. Mechanistically, cystatin C inhibits cathepsins, which are involved in extracellular matrix degradation and angiogenesis, processes critical for ectopic endometrial cell invasion.[] By suppressing these proteolytic activities, higher cystatin C may limit lesion progression. These results warrant further mechanistic exploration. 4.7. Phosphate Phosphates are indispensable components of the body that take part in numerous physiological processes, among them energy metabolism, intracellular signaling, bone integrity, and transport across membranes.[,] Such processes are crucial for sustaining normal physiological operation and metabolism throughout many bodily systems. That said, consuming too much phosphate can likewise prove harmful. A shortage of phosphate frequently brings about rickets, whereas an excess may raise the frequency of cardiovascular disease, renal disease, tumors, and the chance of death.[,] For this reason, preserving phosphate equilibrium is of great consequence for the body’s systems. Phosphate balance in the body is kept under tight control, with fibroblast growth factor 23 (FGF23), vitamin D, and parathyroid hormone serving prominent regulatory roles.[] Our results indicate that a drop in phosphate concentrations may raise vulnerability to EMT. Few previous studies have examined this relationship, and the mechanism behind it is still obscure. Previous studies have confirmed that E2 can reduce phosphate and induce hypophosphatemia by suppressing the renal sodium-dependent phosphate cotransporter type IIa (NaPi-IIa) protein.[,] It is broadly recognized that EMT is E2-dependent. We therefore propose that declining phosphate levels are tied to a heightened risk of EMT. This could arise because an E2-rich milieu blocks apoptosis of ectopic endometrial cells while encouraging their growth and multiplication.[] 4.8. Hematocrit percentage Our analysis uncovered a possible link between a lowered hematocrit percentage and a greater risk of EMT. Several plausible mechanisms may illuminate it. Anemia usually presents as a diminished hematocrit percentage and, in chronic disease, is generally triggered by cellular immune processes, proinflammatory cytokines, and hepcidin.[] Endometriosis is characterized by chronic inflammation and dysregulated iron metabolism.[] Retrograde menstruation transports erythrocytes into the peritoneal cavity, where they undergo lysis and degradation.[] This process releases hemoglobin and iron into the peritoneal environment.[] Although anemia reduces the number of circulating erythrocytes, the persistent degradation of erythrocytes that have entered the pelvic cavity via retrograde menstruation remains an ongoing source of local iron release.[] Iron overload in the pelvic cavity can induce oxidative stress through the production of reactive oxygen species.[] Oxidative stress, in turn, promotes the proliferation, adhesion, and survival of ectopic endometrial cells, thereby fostering the development of EMT.[] 4.9. Fluid intelligence score Fluid intelligence denotes the mental capacity to work through complex and unfamiliar problems. Differences in fluid intelligence are thought to track with the regulatory capacity of the frontoparietal cortical network.[] Weaker fluid intelligence scores may reflect poorer working memory, slower processing, and diminished cognitive segmentation. Research on the behavioral variant of frontotemporal dementia disclosed a marked tie between blunted baseline autonomic nervous system activity and atrophy of the left frontotemporal lobe.[] The nervous system plays a considerable part in the pathogenesis of chronic inflammatory autoimmune diseases. By releasing neurotransmitters, sympathetic and sensory nerves interact with local inflammation and immune dysregulation in endometriotic lesions, and this nerve-inflammation interaction may promote the development of EMT and contribute to its associated pain.[] 4.10. Strengths and limitations The strength of this work rests on its use of GWAS data together with MR analysis to thoroughly probe the possible risk factors linked to EMT. It also succeeded in revealing the exposure-outcome relationships of this disease. The investigation nonetheless carries several shortcomings: pleiotropy of genetic variants is pervasive and cannot be ignored within the MR framework. Even after applying various techniques, the existence of this bias must still be acknowledged; it is likewise important to recognize that the GWAS database used here consists chiefly of data from people of European descent. Because relevant data from other racial populations remain scarce, further research is needed to establish whether the present findings extend to other cultural groups. 5. Conclusion To sum up, this study systematically surveyed 108 candidate risk and protective factors connected to EMT using a two-sample MR approach, and the analysis brought to light both positive and negative causal associations linking 12 phenotypes to EMT, spanning telomere length, lipid, metabolic, hematological, and neuropsychological traits. By relying on genetic instruments, these estimates are less susceptible to the confounding and reverse causation that limit conventional observational studies. These findings may help accelerate the identification of new biomarkers and assessment methods, thereby strengthening strategies for the early prevention and treatment of EMT. Given that the present analyses were based on summary-level data from predominantly European populations, further studies in more diverse populations are warranted to validate these causal relationships. Author contributions Writing – original draft: Zhiwei Zheng, Peipei Hong, Rumeng Chen, Li Han, Shuling Xu, Yining Ding, Menghua Liu, Mengling Zhang. Writing – review & editing: Meihua Bao, Binsheng He, Sen Li. confidence interval estrogen endometriosis genome-wide association study high-density lipoprotein instrumental variable inverse-variance weighted leukocyte telomere length Mendelian randomization Mendelian Randomization Pleiotropy RESidual Sum and Outlier odds ratio single nucleotide polymorphism triglycerides weighted medianAbbreviations: References [1] Vercellini P, Viganò P, Somigliana E, Fedele L. Endometriosis: pathogenesis and treatment. Nat Rev Endocrinol. 2014;10:261–75.[2] Taylor HS, Kotlyar AM, Flores VA. Endometriosis is a chronic systemic disease: clinical challenges and novel innovations. Lancet. 2021;397:839–52.[3] As-Sanie S, Mackenzie SC, Morrison L, et al. Endometriosis: a review. 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