Gut microbiota and intervertebral disc degeneration: A Bidirectional Two-Sample Mendelian Randomization Study

Gut microbiota and intervertebral disc degeneration: A Bidirectional Two-Sample Mendelian Randomization Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Gut microbiota and intervertebral disc degeneration: A Bidirectional Two-Sample Mendelian Randomization Study Ziming Geng, Jian Wang, Guangdong Chen, Jianchao Liu, Jie Lan, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3088048/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Aug, 2023 Read the published version in Journal of Orthopaedic Surgery and Research → Version 1 posted 7 You are reading this latest preprint version Abstract BACKGROUND Although previous studies have suggested a close association between gut microbiota(GM) and intervertebral disc degeneration(IVDD), the causal relationship between them remains unclear.Hence,we thoroughly investigate their causal relationship by means of a two-sample mendelian randomization (MR) study, aiming to determine the impact of gut microbiota on the risk of developing intervertebral disc degeneration. METHODS Summary data from genome-wide association studies (GWAS) of GM (the MiBioGen) and IVDD (the FinnGen biobank) have been acquired.The inverse variance weighted (IVW) method was utilized as the primary MR analysis approach. Weighted median (WME), MR-Egger regression, weighted mode, and simple mode were used as supplements. The mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger regression were performed to assess horizontal pleiotropy. Cochran's Q test evaluated heterogeneity.Leave-one-out sensitivity analysis was further conducted to determine the reliability of the causal relationship. A reverse MR analysis was conducted to assess potential reverse causation. RESULTS We identified nine gut microbial taxa that were causally associated with IVDD( P < 0.05).Following the Benjamini-Hochberg corrected test, the association between the phylum Bacteroidetes and a higher risk of IVDD remained significant(IVW FDR-corrected P = 0.0365). The results of the Cochrane Q test did not indicate heterogeneity ( P > 0.05). Additionally, both the MR-Egger intercept test and the MR-PRESSO global test revealed that our results were not influenced by horizontal pleiotropy ( P > 0.05). Furthermore, the leave-one-out analysis substantiated the reliability of the causal relationship.In the reverse analysis, no evidence was found to suggest that IVDD has an impact on the gut microbiota. CONCLUSION Our results validate the potential causal impact of particular GM taxa on IVDD, thus providing fresh insights into the gut microbiota-mediated mechanism of IVDD and laying the groundwork for further research into targeted preventive measures. gut microbiota intervertebral disc degeneration low back pain causal relationship mendelian randomization MiBioGen FinnGen Figures Figure 1 Figure 2 1. Introduction Low back pain (LBP), which affects a staggering 70–85% of individuals at some point in their lives, presents a significant global public health challenge, resulting in a considerable financial burden on healthcare and social systems[1–3]. In general, LBP refers to discomfort, tension or inflexibility that is felt in the region of the body situated beneath the ribcage and above the inferior gluteal folds, often accompanied by leg pain (sciatica) and other neurological issues affecting the lower extremities[1, 4].While various factors can play a role in the development of LBP, intervertebral disc degeneration (IVDD) stands out as one of the primary causes[4, 5].IVDD serves as the pathological foundation for various spinal degenerative disorders and is a prevalent orthopedic condition that contributes to a reduced quality of life[6]. The intervertebral disc(IVD) consists of the nucleus pulposus(NP), annulus fibrosus, and the cartilage endplate, which are primarily composed of collagen and proteoglycan, imparting crucial properties to the disc.The NP is a critical component of the IVD,primarily made up of NP cells and the extracellular matrix (ECM).Intervertebral disc degeneration (IVDD) is a prevalent degenerative condition that is distinguished by the gradual reduction of proteoglycans and water content within NP[7]. As the disease progresses, the discs between the vertebrae may break down, rendering them more susceptible to herniation, which can cause compression of the spinal nerves and nerve roots.The irritation of nerves in the lower back as a result of IVDD is known as lumbar radiculopathy.If this occurs in the nerve roots of L4-S2, it commonly results in a distinct type of pain known as sciatica[8, 9]. The gut microbiota(GM) refers to the distinct microbial populations that inhabit the intestinal tract and coexist in a mutually beneficial relationship with the host organism, including bacteria, protozoa, fungi, archaea, and viruses[10].It has the potential to influence multiple physiological processes, including metabolism, inflammation, and immune responses[11–14].The identification of gut microbiota taxonomic characteristics and their potential role is mainly based on the utilization of 16S rRNA and metagenomic sequencing methods, which are commonly employed techniques[15].In a recent study by Rajasekaran et al.[16], a total of 24 lumbar intervertebral discs (IVDs) were analyzed, revealing that the microbial makeup present in healthy IVDs contrasted with that of degenerated and herniated IVDs.Changes in the composition of the microbiome and the way hosts respond to microbiota, which can cause abnormal bone growth and resorption[17, 18], gave rise to the idea of the gut-bone marrow axis[19, 20] and the gut-bone axis[18]. Subsequent to the study conducted by Rajasekaran et al., a comparable gut-disc axis concept has emerged that could have significant implications in intervertebral disc degeneration and low back pain[16, 21]. As a result, the regulation of gut microbiota could potentially impact the diversity and quantity of microbiota within the intervertebral disc, ultimately helping to regulate intervertebral disc degeneration. However, additional investigation is required to further explore the distinct role of various gut microbiota taxa in the development of intervertebral disc degeneration.Akin to randomized controlled trials (RCT), the mendelian randomization (MR) study is a recent research approach that investigates the causal relationship between exposure and outcome[22]. Mendelian randomization is a genetic epidemiology technique that uses single nucleotide polymorphisms (SNPs) that are known to affect modifiable exposures as instrumental variables (IVs) to deduce the causal effect of an exposure on an outcome. This approach is advantageous because it can eliminate confounding bias and can help to distinguish between the causal pathways of phenotypically grouped risk variables that are difficult to randomize or that are prone to measurement error[23]. In this study, we utilized GWAS summary statistics of GM and IVDD to perform MR analysis, with the aim of identifying GM taxa that may have a significant impact.This approach can help to confirm existing evidence and offer fresh perspectives on the management and prevention of intervertebral disc degeneration. 2. Materials and methods 2.1 Study design: The overall flowchart of this study is shown in Fig. 1 . MR studies require three assumptions to be met: (i) a strong correlation between the instrumental variable (IV) and the exposure, (ii)IVs are unrelated to confounding factors, and (iii)IVs are only related to the outcome through the exposure[24, 25]. Specifically, we determined the gut microbiota taxa that had a causal effect on intervertebral disc degeneration (IVDD) through bidirectional two-sample mendelian randomization.Our results were reported according to the STROBE-MR guidelines[26].We utilized GWAS data that had previously been obtained with informed consent and ethical approval for public release. 2.2. Data sources for exposure and outcome: The MiBioGen consortium conducted a study analyzing the genotypes of hosts and the sequencing profiles of 16S fecal microbiomes rRNA gene of 18,340 participants, as reported by Kurilshikov et al[27]. The GWAS study examined 211 GM taxa ranging from genus to phylum level and discovered genetic variants associated with 9 phyla, 16 classes, 20 orders, 35 families, and 131 genera. We obtained summary statistics of GWAS for IVDD from the FinnGen Consortium R8 release, which included 29,508 cases and 227,388 controls. [28].The diagnosis of IVDD was based on ICD-10 M51,ICD-9 722,and ICD-8 275.Table 1 presents detailed information on the exposure and outcome analyzed in this MR study. The details of the exposure and outcome are shown in TABLE1. Table 1 Details of the exposure and outcome Trait Consortium Samples Case Control Exposure 211 GM taxa MiBioGen 18340 / / Outcome Intervertebral disc degeneration FinnGen (R8) 256896 20001 164682 2.3. Identification of IVs SNPs closely associated with each GM taxon were used as instrumental variables (IVs) in this MR study. Due to the limited number of IVs obtained at a strict threshold ( P < 5×10 − 8), a more comprehensive threshold ( P < 1×10 − 5) was utilized to obtain a relatively higher number of IVs, thus resulting in more robust results[29]. In addition, to ensure the independence of each IV, SNPs within a 10,000 kb window size with a threshold of r 2 < 0.001 were pruned to mitigate linkage disequilibrium (LD). Subsequently, we eliminated palindromic SNPs and SNPs that did not appear in the outcome from the IVs. Ultimately, we computed the F statistic for the IVs to evaluate the degree of bias due to weak instruments.The calculation formula is as follows: F = \(\frac{N-K-1}{K}\times \frac{{R}^{2}}{1- {R}^{2}}\) ; \({R}^{2}\) represents the proportion of variance in the exposure that is explained by genetic variants.N=sample size;K=the number of IV.If the F statistic > 10, weak IVs were deemed not to have caused bias [30]. 2.4. Statistical methods For each GM taxon, the inverse variance weighted(IVW)method was used as the primary analysis method to determine causal associations ( P < 0.05), with four additional methods (MR-Egger, weighted median, simple mode, and weighted mode) employed as supplementary measures[31, 32].This study conducted sensitivity analyses in order to eliminate potential bias and examine the robustness of the IVW results. The Cochran Q test was utilized to assess heterogeneity among SNPs, and a P -value greater than 0.05 indicates a lower likelihood of heterogeneity among the SNPs, in which case the IVW fixed-effect model was employed for analysis. Conversely, if the P-value was less than or equal to 0.05, the IVW random-effects model was used[33]. In IVW regression, the intercept term is not considered and the reciprocal of the outcome variance (se 2 ) is used as weights for fitting[31]. The weighted median method is defined as the median of the weighted empirical density function of the ratio estimates, and causal relationships can be consistently estimated if at least 50% of the information in the analysis comes from valid instruments[31]. In MR-Egger regression, the intercept term is considered, and the reciprocal of the outcome variance (se 2 ) is also used as weights for fitting, with the resulting intercept used to assess horizontal pleiotropy[34]. MR-PRESSO global test was also utilized to achieve the same objective, which eliminated the influence of pleiotropy by removing outliers[35]. In addition, funnel plots and forest plots were constructed to visualize and ensure the reliability of the results.Finally, we converted the effect estimates to odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) to more intuitively display the causal associations between each GATA taxon and outcomes. A significance level of P < 0.05 indicated the presence of a causal relationship between the exposure and outcome.To account for multiple testing (multiple exposures), the significance of the MR effect estimates was controlled using a Benjamini-Hochberg false discovery rate (FDR) of < 5% at a specific level.Additionally, we performed reverse causal analysis to examine the reverse causality relationship.To meet the core assumptions of MR, the selected SNPs were further filtered in the Phenoscanner database to ensure that the included instrumental variables were not correlated with known confounding factors[36],including dried fruit intake[37],diabetes[38], insomnia[39], plasma omega-3 levels[40],obesity[41], smoking.The replicated MR analyses were performed after excluding instrumental variables associated with confounding factors mentioned earlier.All statistical analyses were performed using the "TwoSampleMR" package and the "MRPRESSO" package in R language (version 4.3.0). 3. Results 3.1. Selection of instrumental variables : After excluding three unknown families and twelve unknown genera from a pool of 211 gut microbiota(GM) taxa, a total of 196 GM taxa were included as exposure.There are 2103 SNPs were selected as instrumental variables,which can be categorized according to five levels: 185 SNPs in 16 classes, 353 SNPs in 32 families, 1232 SNPs in 119 genera, 227 SNPs in 20 orders, and 106 SNPs in 9 phyla. All instrumental variables showed F-values greater than 10, indicating their resilience to weak instrumental variables. Detailed information regarding the instrumental variables can be found in the Supplementary table1. 3.2. Causal effects of gut microbiota on intervertebral disc degeneration Causal Associations from 9 GM taxa(2 Families, 6 Genera, and 1 Phylum) to IVDD were identified through mendelian randomization analysis evaluating the causal link between microbiota taxa at five Levels and IVDD(Supplementary table2). As shown in Fig. 2 , the IVW analysis revealed that the genus Escherichia Shigella (OR: 1.163, 95% CI: 1.025–1.319, P = 0.019), genus Marvinbryantia (OR: 1.176, 95% CI: 1.039–1.330, P = 0.010), and phylum Bacteroidetes (OR: 1.218, 95% CI: 1.065–1.392, P = 0.004) were associated with an increased risk of IVDD. On the other hand, the family Rikenellaceae (OR: 0.893, 95% CI: 0.803–0.993, P = 0.037), family Ruminococcaceae (OR: 0.845, 95% CI: 0.740–0.964, P = 0.005), genus Eubacterium coprostanoligenes group (OR: 0.801, 95% CI: 0.704–0.912, P < 0.001), genus Gordonibacter (OR: 0.933, 95% CI: 0.877–0.993, P = 0.028), genus Lachnoclostridium (OR: 0.876, 95% CI: 0.774–0.991, P = 0.035), and genus Oscillospira (OR: 0.834, 95% CI: 0.721–0.966, P = 0.016) were associated with a reduced risk of IVDD. In addition, we performed four supplementary analysis methods to complement the IVW analysis, and the results were consistent with the direction of the IVW method (Fig. 2 ). This indicates the robustness of the IVW results. 3.3. Benjamini–Hochberg corrected test, sensitivity analysis and reverse analysis After conducting the Benjamini-Hochberg corrected test, it was found that the phylum Bacteroidetes remained associated with a higher risk of IVDD (IVW FDR-corrected p = 0.037)(Supplementary table 2). No heterogeneity was observed according to the Cochrane Q and MR-Egger tests, and the analysis results of MR-Egger and MRPRESSO global tests indicated the absence of horizontal pleiotropy (Table 2 ). Table 2 Horizontal pleiotropy analysis for IVs of 9 GM taxa associated with IVDD Exposure Heterogeneity test MR-Egger intercept test MR-PRESSO global test MR-IVW MR-Egger Egger_intercept SE p RSS obs p Family family Rikenellaceae id.967 Q = 14.471 Q = 14.289 -0.005 0.012 0.676 16.364 0.565 P = 0.564 P = 0.504 family Ruminococcaceae id.2050 Q = 6.676 Q = 6.189 -0.010 0.014 0.508 8.5467 0.623 P = 0.572 P = 0.518 Genus genus Escherichia Shigella id.3504 Q = 7.955 Q = 7.645 -0.008 0.015 0.593 9.708 0.542 P = 0.539 P = 0.469 genus Eubacterium coprostanoligenes group id.11375 Q = 7.735 Q = 6.683 0.016 0.016 0.327 9.066 0.761 P = 0.806 P = 0.824 genus Gordonibacter id.821 Q = 6.773 Q = 6.740 0.004 0.020 0.858 8.198 0.775 P = 0.817 P = 0.750 genus Lachnoclostridium id.11308 Q = 11.166 Q = 10.808 -0.009 0.014 0.562 12.955 0.517 P = 0.515 P = 0.460 genus Marvinbryantia id.2005 Q = 6.462 Q = 6.409 -0.005 0.021 0.824 8.243 0.716 genus Oscillospira id.2064 P = 0.693 P = 0.602 0.034 0.030 0.292 13.456 0.155 Phylum phylum Bacteroidetes id.905 Q = 8.994 Q = 8.994 0.000 0.011 0.991 10.871 0.564 P = 0.533 P = 0.438 The leave-one-out sensitivity analysis showed that the IVW analysis results remained similar when any SNP was removed as instrumental variable(Supplementary Fig. 1). In the reverse MR analysis, we found no significant causal effect of IVDD on gut microbiota(Supplementary Table 3). 3.4. Further Analysis for Removing Potential Confounding Factors Among the instrumental variables (IVs) associated with the 9 microbial taxa causally linked to intervertebral disc degeneration (IVDD),rs55793120, rs72829893, rs12925026, and rs62532512 were found to be associated with obesity. Furthermore, rs62532512 was also found to be associated with smoking. After excluding these IVs and conducting the analysis again, it was observed that three GM taxa, including family Rikenellaceae ( P = 0.0687), genus Lachnoclostridium ( P = 0.0751), and genus Oscillospira ( P = 0.0582), were no longer causally associated with IVDD. However, the causal associations between the remaining GM taxa and IVDD remained robust. Table 3 Replicated MR analysis by IVW method after removing confounders-related IVs Exposure Outcome P -value OR(95%CI) Family IVDD family Rikenellaceae id.967 0.069 0.903(0.809–1.008) Family Ruminococcaceae id.2050 0.005 0.813(0.705–0.939) Genus genus Escherichia Shigella id.3504 0.019 1.163(1.025–1.319) genus Eubacterium coprostanoligenes group id.11375 0.001 0.801(0.704–0.912) genus Gordonibacter id.821 0.028 0.933(0.877–0.993) genus Lachnoclostridium id.11308 0.075 0.885(0.774–1.012) genus Marvinbryantia id.2005 0.010 1.176(1.039–1.330) genus Oscillospira id.2064 0.058 0.885(0.779–1.004) Phylum phylum Bacteroidetes id.905 0.004 1.218(1.065–1.392) 4. Discussion To the best of our knowledge, this is the first mendelian randomization study investigating the causal relationship between gut microbiota (GM) and intervertebral disc degeneration (IVDD). In this study, we utilized GM data derived from a GWAS meta-analysis conducted by the MiBioGen consortium and IVDD data from the R8 release of the FinnGen consortium. The causal effects of gut microbiota taxa (from phylum to genus level) on intervertebral disc degeneration were investigated, and nine gut microbiota taxa were identified to have a causal association with IVDD.Additionally, we performed reverse analysis to demonstrate the unidirectionality of the causal relationships and found no evidence of IVDD affecting the gut microbiota. There is a growing interest in understanding the pathogenic impact of the microbiome in numerous human diseases.Dysbiosis of the gut microbiota can potentially impair the normal functioning of the gut microbial community in maintaining host health. It may also lead to the selective enrichment of certain microbial members, including pathogenic bacteria, resulting in a dysregulated production of microbial-derived products or metabolites that can be harmful to the host.This dysregulation can contribute to the development of various diseases in local, systemic, or distant organs[42].Similarly,it has been established that alterations in the composition of the gastrointestinal, skin, and oral microbiota are associated with various musculoskeletal diseases, such as rheumatoid arthritis [43–45],osteoarthritis [46, 47],ankylosing spondylitis [45],spondyloarthritis[48]. As one of the most common complaints in orthopedic clinics, low back pain is a prevalent public health issue worldwide,causing severe lifelong disability and imposing significant economic burdens on both patients and society[49]. Although the etiology of LBP is diverse[50–52],IVDD is widely acknowledged as a prominent factor among the various causes[4, 53],which is responsible for approximately 40% of symptomatic LBP[54].In the past, the intervertebral discs in healthy individuals were believed to be sterile.However,Rajasekaran et al.[16] conducted a comprehensive metagenomic analysis of lumbar intervertebral discs, revealing the presence of a human intervertebral disc microbiome, and documenting the existence of "dysbiosis". Furthermore, it was discovered that the gut and intervertebral disc microbiomes share a total of 58 bacterial species.In addition, the intervertebral disc (IVD) is a complex fibrocartilaginous joint and is often referred to as the largest avascular structure in the human body. Blood vessels in the IVD are only present in the longitudinal ligaments and the outer layers of the annulus fibrosis. However, the formation of new blood vessels can occur when the following conditions arise: intervertebral disc herniation into the extradural space, physical injury and fractures, or local inflammation on the intervertebral disc and vertebral endplates[55]. In the mouse model of IVDD, the abundance of Muribaculaceae and Lactobacillus increased, while the abundance of Clostridia_UCG-014 decreased. Furthermore, fecal microbiota transplantation further increased the abundance of Lactobacillus and reduced the abundance of Clostridia_UCG-014[56]. Su et al. [57]conducted a mendelian randomization study on the potential causal effects of specific gut microbiota and gut microbiota metabolites on low back pain (LBP). Similar to our findings, they observed that the abundance of the genus Marvinbryantia is a potential risk factor for LBP, while the abundance of the family Rikenellaceae and family Ruminococcaceae is a potential protective factor for LBP.These studies provide evidence for the association between gut microbiota and intervertebral disc degeneration (IVDD). The pathogenic mechanisms underlying the role of gut microbiota in IVDD have been widely discussed in previous studies, involving various aspects such as inflammatory response, gut barrier function, and nutrient metabolism.These mechanisms intersect and collectively contribute to the overall impact of gut microbiota in IVDD.The Escherichia Shigella is a group of bacteria capable of producing lipopolysaccharide (LPS). LPS is a glycolipid component found in the outer membrane of gram-negative bacteria[58].LPS can activate the TLR4/MyD88/NF-κB signaling pathway, leading to the release of pro-inflammatory mediators such as IL-6, IL-1β, and TNF-α. This cascade of events triggers a series of inflammatory processes, ultimately resulting in chronic low-grade inflammation[59].A significant decrease in the abundance of a short chain fatty acids-producer, Marvinbryantia spp, was observed in the low muscle mass elders[60]. Sarcopenia is postulated to be an influential factor in chronic low back pain[61, 62].The GM taxon may potentially impact intervertebral disc degeneration and trigger lower back pain by regulating nutrient absorption in the intestinal epithelium, thereby affecting muscle mass. Ruminococcus , originally classified as a member of the core phylum Firmicutes in the human gut microbiota, accounting for approximately 30% of the total gut microbial population[63],has been recently reclassified as Blautia [64]. Blautia is a genus of anaerobic bacteria that exhibits probiotic characteristics. It has the potential to reduce the production of local inflammatory factors and alleviate inflammatory responses in the gut. In normal intervertebral disc (IVD) samples, Firmicutes are abundantly present, and their abundance is associated with intestinal barrier function and antimicrobial protection[16].Both Firmicutes and Bacteroidetes are capable of fermenting dietary fiber to produce short-chain fatty acids (SCFAs), which then act on G-protein-coupled receptors,such as GPR43, GPR41, and GPR109a,to regulate immune responses[65].This leads to an increase in regulatory T cells (Tregs) and dendritic cell precursors, improvement in epithelial barrier function, and an upregulation of anti-inflammatory cytokines such as IL-10[66].The ratio of Firmicutes and Bacteroidetes has been implicated that some diseases like T2DM, hyperlipidemia[67], obesity[68], and non-alcoholic fatty liver disease(NAFLD)[69] are associated with elevated Firmicutes to Bacteroidetes ratio (F/B) in the gut microbiota. Our research, along with previous studies, demonstrates a strong association between Firmicutes, Bacteroidetes and intervertebral disc degeneration (IVDD). Thus, the F/B ratio could potentially be utilized as an evaluative indicator for assessing the association with IVDD. In mouse models of lumbar disc herniation, the gut was found to have a higher abundance of Ruminococcaceae[70], which can alleviate chronic inflammation through the production of butyrate[71]. However, it contradicts our study results to some extent, which suggest that this bacterium acts as a protective factor against IVDD. The reason for this discrepancy may be attributed to the complex interactions that exist among gut microbiota. Further prospective randomized controlled trials may be necessary to validate it. The Gordonibacter , as a probiotic, has been shown to alleviate inflammatory reactions and prevent the occurrence of various diseases[72].It is known to produce anti-inflammatory metabolites, including urolithins. Urolithin A, in particular, has been found to improve mitochondrial health, reduce cartilage degeneration, and alleviate pain in osteoarthritis[73]. Studies have indicated that Urolithin A affects intervertebral discs through mechanisms that include inhibiting the breakdown metabolism of nucleus pulposus cells by TNFα in the body[74].Additionally, it increases mitochondrial autophagy and reduces cell apoptosis in the nucleus pulposus cells[75]. These findings suggest that Gordonibacter may have potential characteristics in regulating intervertebral disc health through the modulation of anti-inflammatory metabolites.Supplementation of vitamin D has been shown to impact the gut microbiota[76].Importantly,vitamin D is closely associated with the gut barrier and can improve barrier function by inducing the expression of E-cadherin and enhancing epithelial cell connections within the intestine[77]. Deficiency in vitamin D can lead to disruption of these connections, resulting in intestinal permeability and facilitating the passage of bacterial components and metabolites. In patients with vitamin D deficiency and osteoarthritis, there is an increase in the abundance of Gordonibacter [78]. This particular microbial group may alter intestinal permeability, thereby creating conditions for the gut microbiota to influence the microecology of intervertebral discs. Yang et al. discovered that Oscillospira sp. constitutes a significant proportion of the gut microbiota. This suggests that Oscillospira sp. may play a crucial role in maintaining microbial balance and human health[79].Importantly, its abundance has been found to be negatively correlated with a range of inflammatory diseases[80]. In the subsequent analysis after removing the instrumental variables associated with confounding factors, the analysis results for Eubacterium coprostanoligenes group , Rikenellaceae , and Lachnoclostridium no longer showed statistical significance.Limited research has been conducted regarding the association between Eubacterium coprostanoligenes group , Rikenellaceae , Lachnoclostridium , and IVDD. Therefore, whether there is a causal relationship between these three microbial taxa and IVDD remains to be debated.In conclusion,our research findings suggest that gut microbiota a dual role, both inducing and protective, in the occurrence and progression of IVDD.The specific mechanisms underlying these effects and the intricate interplay between gut microbial communities require further elucidation. In previous studies, the etiology of intervertebral disc degeneration (IVDD) has mainly focused on various pathological factors, such as aging, inflammation, oxidative stress, mitochondrial dysfunction, and abnormal mechanical load[81–84]. However, there is limited research on the role of gut microbiota in IVDD. To the best of our knowledge, this study represents the first investigation of this topic using a two-sample bidirectional mendelian randomization (MR) approach. MR utilizes genetic variations as instrumental variables to analyze the causal relationship between exposure and disease outcomes. By leveraging the random allocation of genetic variations, which occurs before the onset of disease and is independent of environmental factors, MR overcomes the inherent limitations of traditional observational studies, such as confounding factors and reverse causality. In this study, we employed available exposure and outcome data from genome-wide association studies (GWAS) to obtain precise analytical results.This approach provides an efficient means of harnessing reliable genetic information without the need for additional experimental costs.Furthermore, we meticulously examined the instrumental variables associated with the positive microbial results using the Phenoscanner V2 website to mitigate the influence of confounding factors and applied false discovery rate (FDR) correction to control the occurrence of false positives, thereby enhancing the reliability and reproducibility of the analysis results.Our research results provide the initial evidence of a causal association between the phylum Bacteroidetes and IVDD, thereby further confirming the concept of the gut-disc axis. Nevertheless,the study has several limitations. First, due to the use of a stringent genome-wide significance threshold ( P < 5×10 − 8 ), the number of SNPs available for analysis was limited. Only SNPs meeting the suggestive significance threshold ( P < 1×10 − 5 ) were included, which may reduce the reliability and accuracy of the results.Furthermore, the sample size and strain-level information of gut microbiota GWAS data are still in the early stages.This resulted in the exclusion of certain microbial species from the study, and the limited number of instrumental variables used may lead to a decrease in statistical power and increase the potential impact of weak instrumental variables on reverse mendelian randomization, making it difficult to fully exclude reverse causality. It is essential to acknowledge that the study's data were exclusively obtained from European populations, without considering factors like gender and ethnicity, limiting the generalizability of the findings to other populations. Additionally, it is important to recognize that the study focused solely on bacteria, disregarding the considerable diversity of eukaryotic viruses and prokaryotic phages present in the human microbiota[85].Further investigations are warranted to explore their potential involvement in IVDD.Finally, the association between human microbiota and the host in both healthy and disease states is a complex interplay rather than a simple one-way "causal relationship"[42].Therefore, future studies should consider the intricate coordination and crosstalk between the host and gut microbiota to gain a better understanding of the relationship between gut microbiota and disease. 5. Conclusion Using publicly available GWAS data, we conducted a bidirectional two-sample mendelian randomization analysis on the causal association between 211 gut microbiota taxa and intervertebral disc degeneration(IVDD). Our analysis resulted in the identification of eight nominal causal associations and one strong correlation, further providing a theoretical foundation for the concept of the gut-disc axis. This study was based on a GWAS meta-analysis dataset generated from 16S rRNA sequencing, thus highlighting the need for analyses based on more advanced large-scale studies using metagenomics sequencing. Nevertheless, our research also offers valuable biomarkers for understanding the progression, diagnosis, and potential therapeutic approaches for IVDD. Abbreviations IVDD:intervertebral disc degeneration IVD:intervertebral disc NP:nucleus pulposus ECM:extracellular matrix GM:gut microbiota LBP:low back pain MR:mendelian randomization GWAS:genome-wide association studies IVW:inverse variance weighted WME:Weighted median MR-PRESSO:mendelian randomization pleiotropy residual sum and outlier SNP:single nucleotide polymorphism IV:instrumental variable FDR:false discovery rate Declarations Ethics approval and consent to participate: We utilized GWAS data that had previously been obtained with informed consent and ethical approval for public release. Acknowledgements: Not applicable. Consent for publication: Written informed consent for publication was obtained from all participants. Availability of data and materials: Please contact the corresponding author for data requests. Competing interests: The authors declare that they have no competing interests. Funding: The study is supported by the National Natural Science Foundation of China (81472140)，the Natural Science Foundation of Tianjin City (S20ZDD484) and Health and Technology Project of Tianjin Municipal Commission, Grant No. zc20219. Authors' contributions: Ziming Geng and Jun Miao contributed to conception and design of the study. Ziming Geng,Jian Wang and Guangdong Chen organized the database. Ziming Geng and Jian Wang performed the statistical analysis. Ziming Geng wrote the first draft of the manuscript. Jianchao Liu,Jie Lan and Zepei Zhang wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version. All author(s) read and approved the final manuscript. Jun Miao conceived and designed the study. References Hartvigsen J, Hancock MJ, Kongsted A, Louw Q, Ferreira ML, Genevay S, Hoy D, Karppinen J, Pransky G, Sieper J et al : What low back pain is and why we need to pay attention . 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Asquith M, Sternes PR, Costello ME, Karstens L, Diamond S, Martin TM, Li Z, Marshall MS, Spector TD, le Cao KA et al : HLA Alleles Associated With Risk of Ankylosing Spondylitis and Rheumatoid Arthritis Influence the Gut Microbiome . Arthritis & rheumatology (Hoboken, NJ) 2019, 71 (10):1642-1650. Boer CG, Radjabzadeh D, Medina-Gomez C, Garmaeva S, Schiphof D, Arp P, Koet T, Kurilshikov A, Fu J, Ikram MA et al : Intestinal microbiome composition and its relation to joint pain and inflammation . Nature Communications 2019, 10 (1):4881. Biver E, Berenbaum F, Valdes AM, Araujo de Carvalho I, Bindels LB, Brandi ML, Calder PC, Castronovo V, Cavalier E, Cherubini A et al : Gut microbiota and osteoarthritis management: An expert consensus of the European society for clinical and economic aspects of osteoporosis, osteoarthritis and musculoskeletal diseases (ESCEO) . Ageing Research Reviews 2019, 55 :100946. 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Khan AN, Jacobsen HE, Khan J, Filippi CG, Levine M, Lehman RA, Jr., Riew KD, Lenke LG, Chahine NO: Inflammatory biomarkers of low back pain and disc degeneration: a review . Annals of the New York Academy of Sciences 2017, 1410 (1):68-84. Kamali A, Ziadlou R, Lang G, Pfannkuche J, Cui S, Li Z, Richards RG, Alini M, Grad S: Small molecule-based treatment approaches for intervertebral disc degeneration: Current options and future directions . Theranostics 2021, 11 (1):27-47. Fournier DE, Kiser PK, Shoemaker JK, Battié MC, Séguin CA: Vascularization of the human intervertebral disc: A scoping review . JOR spine 2020, 3 (4):e1123. Yao B, Cai Y, Wang W, Deng J, Zhao L, Han Z, Wan L: The Effect of Gut Microbiota on the Progression of Intervertebral Disc Degeneration . Orthopaedic surgery 2023, 15 (3):858-867. Su M, Tang Y, Kong W, Zhang S, Zhu T: Genetically supported causality between gut microbiota, gut metabolites and low back pain: a two-sample Mendelian randomization study . 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Journal of the American Medical Directors Association 2022, 23 (5):902.e901-902.e920. Ebenbichler G, Habenicht R, Ziegelbecker S, Kollmitzer J, Mair P, Kienbacher T: Age- and sex-specific effects in paravertebral surface electromyographic back extensor muscle fatigue in chronic low back pain . GeroScience 2020, 42 (1):251-269. Biddle A, Stewart L, Blanchard J, Leschine SJD: Untangling the genetic basis of fibrolytic specialization by Lachnospiraceae and Ruminococcaceae in diverse gut communities . 2013, 5 (3):627-640. Liu X, Mao B, Gu J, Wu J, Cui S, Wang G, Zhao J, Zhang H, Chen W: Blautia-a new functional genus with potential probiotic properties? Gut microbes 2021, 13 (1):1-21. Hodgkinson K, El Abbar F, Dobranowski P, Manoogian J, Butcher J, Figeys D, Mack D, Stintzi A: Butyrate's role in human health and the current progress towards its clinical application to treat gastrointestinal disease . Clinical nutrition (Edinburgh, Scotland) 2023, 42 (2):61-75. Liu H, Wang J, He T, Becker S, Zhang G, Li D, Ma X: Butyrate: A Double-Edged Sword for Health? Advances in nutrition (Bethesda, Md) 2018, 9 (1):21-29. Chen M, Liao Z, Lu B, Wang M, Lin L, Zhang S, Li Y, Liu D, Liao Q, Xie Z: Huang-Lian-Jie-Du-Decoction Ameliorates Hyperglycemia and Insulin Resistant in Association With Gut Microbiota Modulation . Frontiers in microbiology 2018, 9 :2380. Ansari A, Bose S, Yadav MK, Wang JH, Song YK, Ko SG, Kim H: CST, an Herbal Formula, Exerts Anti-Obesity Effects through Brain-Gut-Adipose Tissue Axis Modulation in High-Fat Diet Fed Mice . Molecules (Basel, Switzerland) 2016, 21 (11). Zhang L, Wang Y, Wu F, Wang X, Feng Y, Wang Y: MDG, an Ophiopogon japonicus polysaccharide, inhibits non-alcoholic fatty liver disease by regulating the abundance of Akkermansia muciniphila . International journal of biological macromolecules 2022, 196 :23-34. Wang Z, Wu H, Chen Y, Chen H, Wang X, Yuan W: Lactobacillus paracasei S16 Alleviates Lumbar Disc Herniation by Modulating Inflammation Response and Gut Microbiota . Frontiers in nutrition 2021, 8 :701644. Kang C, Wang B, Kaliannan K, Wang X, Lang H, Hui S, Huang L, Zhang Y, Zhou M, Chen M et al : Gut Microbiota Mediates the Protective Effects of Dietary Capsaicin against Chronic Low-Grade Inflammation and Associated Obesity Induced by High-Fat Diet . mBio 2017, 8 (3). D'Amico D, Andreux PA, Valdés P, Singh A, Rinsch C, Auwerx J: Impact of the Natural Compound Urolithin A on Health, Disease, and Aging . Trends in molecular medicine 2021, 27 (7):687-699. D'Amico D, Olmer M, Fouassier AM, Valdés P, Andreux PA, Rinsch C, Lotz M: Urolithin A improves mitochondrial health, reduces cartilage degeneration, and alleviates pain in osteoarthritis . Aging cell 2022, 21 (8):e13662. Liu H, Kang H, Song C, Lei Z, Li L, Guo J, Xu Y, Guan H, Fang Z, Li F: Urolithin A Inhibits the Catabolic Effect of TNFα on Nucleus Pulposus Cell and Alleviates Intervertebral Disc Degeneration in vivo . Frontiers in pharmacology 2018, 9 :1043. Lin J, Zhuge J, Zheng X, Wu Y, Zhang Z, Xu T, Meftah Z, Xu H, Wu Y, Tian N et al : Urolithin A-induced mitophagy suppresses apoptosis and attenuates intervertebral disc degeneration via the AMPK signaling pathway . Free radical biology & medicine 2020, 150 :109-119. Tabatabaeizadeh SA, Fazeli M, Meshkat Z, Khodashenas E, Esmaeili H, Mazloum S, Ferns GA, Abdizadeh MF, Ghayour-Mobarhan M: The effects of high doses of vitamin D on the composition of the gut microbiome of adolescent girls . Clinical nutrition ESPEN 2020, 35 :103-108. Holick MF: High prevalence of vitamin D inadequacy and implications for health . Mayo Clinic proceedings 2006, 81 (3):353-373. Ramasamy B, Magne F, Tripathy SK, Venugopal G, Mukherjee D, Balamurugan R: Association of Gut Microbiome and Vitamin D Deficiency in Knee Osteoarthritis Patients: A Pilot Study . Nutrients 2021, 13 (4). Yang J, Li Y, Wen Z, Liu W, Meng L, Huang H: Oscillospira - a candidate for the next-generation probiotics . Gut microbes 2021, 13 (1):1987783. Del Chierico F, Nobili V, Vernocchi P, Russo A, De Stefanis C, Gnani D, Furlanello C, Zandonà A, Paci P, Capuani G et al : Gut microbiota profiling of pediatric nonalcoholic fatty liver disease and obese patients unveiled by an integrated meta-omics-based approach . Hepatology (Baltimore, Md) 2017, 65 (2):451-464. Silwal P, Nguyen-Thai AM, Mohammad HA, Wang Y, Robbins PD, Lee JY, Vo NV: Cellular Senescence in Intervertebral Disc Aging and Degeneration: Molecular Mechanisms and Potential Therapeutic Opportunities . Biomolecules 2023, 13 (4). 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Supplementary File Supplementary figure and table are not available with this version. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 14 Aug, 2023 Read the published version in Journal of Orthopaedic Surgery and Research → Version 1 posted Editorial decision: Major revision 21 Jul, 2023 Reviews received at journal 16 Jul, 2023 Reviewers agreed at journal 08 Jul, 2023 Reviewers invited by journal 24 Jun, 2023 Editor assigned by journal 20 Jun, 2023 Submission checks completed at journal 20 Jun, 2023 First submitted to journal 20 Jun, 2023 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3088048","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":211722632,"identity":"8210470e-3873-4a25-a38b-72e0535cdb75","order_by":0,"name":"Ziming Geng","email":"","orcid":"","institution":"Tianjin Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Ziming","middleName":"","lastName":"Geng","suffix":""},{"id":211722634,"identity":"fb059b5a-d333-47e0-9d52-8a962c81da9f","order_by":1,"name":"Jian Wang","email":"","orcid":"","institution":"Tianjin Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Wang","suffix":""},{"id":211722636,"identity":"d974bb73-0649-4b62-8ac1-72523d74c0f0","order_by":2,"name":"Guangdong Chen","email":"","orcid":"","institution":"Tianjin University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Guangdong","middleName":"","lastName":"Chen","suffix":""},{"id":211722637,"identity":"9fa79c28-6c6c-4c61-afc4-8b5224a0a7dc","order_by":3,"name":"Jianchao Liu","email":"","orcid":"","institution":"Tianjin Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jianchao","middleName":"","lastName":"Liu","suffix":""},{"id":211722638,"identity":"7867538e-f47f-48ea-963e-793e0e39d1bc","order_by":4,"name":"Jie Lan","email":"","orcid":"","institution":"Tianjin Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jie","middleName":"","lastName":"Lan","suffix":""},{"id":211722640,"identity":"a056bfab-003b-451e-bc20-9c9a7d4c38c8","order_by":5,"name":"Zepei Zhang","email":"","orcid":"","institution":"Tianjin Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zepei","middleName":"","lastName":"Zhang","suffix":""},{"id":211722642,"identity":"0a5a00de-837c-48e4-8c11-2130065417fb","order_by":6,"name":"Jun. 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Introduction","content":"\u003cp\u003eLow back pain (LBP), which affects a staggering 70\u0026ndash;85% of individuals at some point in their lives, presents a significant global public health challenge, resulting in a considerable financial burden on healthcare and social systems[1\u0026ndash;3]. In general, LBP refers to discomfort, tension or inflexibility that is felt in the region of the body situated beneath the ribcage and above the inferior gluteal folds, often accompanied by leg pain (sciatica) and other neurological issues affecting the lower extremities[1, 4].While various factors can play a role in the development of LBP, intervertebral disc degeneration (IVDD) stands out as one of the primary causes[4, 5].IVDD serves as the pathological foundation for various spinal degenerative disorders and is a prevalent orthopedic condition that contributes to a reduced quality of life[6]. The intervertebral disc(IVD) consists of the nucleus pulposus(NP), annulus fibrosus, and the cartilage endplate, which are primarily composed of collagen and proteoglycan, imparting crucial properties to the disc.The NP is a critical component of the IVD,primarily made up of NP cells and the extracellular matrix (ECM).Intervertebral disc degeneration (IVDD) is a prevalent degenerative condition that is distinguished by the gradual reduction of proteoglycans and water content within NP[7]. As the disease progresses, the discs between the vertebrae may break down, rendering them more susceptible to herniation, which can cause compression of the spinal nerves and nerve roots.The irritation of nerves in the lower back as a result of IVDD is known as lumbar radiculopathy.If this occurs in the nerve roots of L4-S2, it commonly results in a distinct type of pain known as sciatica[8, 9].\u003c/p\u003e \u003cp\u003eThe gut microbiota(GM) refers to the distinct microbial populations that inhabit the intestinal tract and coexist in a mutually beneficial relationship with the host organism, including bacteria, protozoa, fungi, archaea, and viruses[10].It has the potential to influence multiple physiological processes, including metabolism, inflammation, and immune responses[11\u0026ndash;14].The identification of gut microbiota taxonomic characteristics and their potential role is mainly based on the utilization of 16S rRNA and metagenomic sequencing methods, which are commonly employed techniques[15].In a recent study by Rajasekaran et al.[16], a total of 24 lumbar intervertebral discs (IVDs) were analyzed, revealing that the microbial makeup present in healthy IVDs contrasted with that of degenerated and herniated IVDs.Changes in the composition of the microbiome and the way hosts respond to microbiota, which can cause abnormal bone growth and resorption[17, 18], gave rise to the idea of the gut-bone marrow axis[19, 20] and the gut-bone axis[18]. Subsequent to the study conducted by Rajasekaran et al., a comparable gut-disc axis concept has emerged that could have significant implications in intervertebral disc degeneration and low back pain[16, 21]. As a result, the regulation of gut microbiota could potentially impact the diversity and quantity of microbiota within the intervertebral disc, ultimately helping to regulate intervertebral disc degeneration.\u003c/p\u003e \u003cp\u003eHowever, additional investigation is required to further explore the distinct role of various gut microbiota taxa in the development of intervertebral disc degeneration.Akin to randomized controlled trials (RCT), the mendelian randomization (MR) study is a recent research approach that investigates the causal relationship between exposure and outcome[22]. Mendelian randomization is a genetic epidemiology technique that uses single nucleotide polymorphisms (SNPs) that are known to affect modifiable exposures as instrumental variables (IVs) to deduce the causal effect of an exposure on an outcome. This approach is advantageous because it can eliminate confounding bias and can help to distinguish between the causal pathways of phenotypically grouped risk variables that are difficult to randomize or that are prone to measurement error[23]. In this study, we utilized GWAS summary statistics of GM and IVDD to perform MR analysis, with the aim of identifying GM taxa that may have a significant impact.This approach can help to confirm existing evidence and offer fresh perspectives on the management and prevention of intervertebral disc degeneration.\u003c/p\u003e"},{"header":"2. Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design:\u003c/h2\u003e \u003cp\u003eThe overall flowchart of this study is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. MR studies require three assumptions to be met: (i) a strong correlation between the instrumental variable (IV) and the exposure, (ii)IVs are unrelated to confounding factors, and (iii)IVs are only related to the outcome through the exposure[24, 25]. Specifically, we determined the gut microbiota taxa that had a causal effect on intervertebral disc degeneration (IVDD) through bidirectional two-sample mendelian randomization.Our results were reported according to the STROBE-MR guidelines[26].We utilized GWAS data that had previously been obtained with informed consent and ethical approval for public release.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2. Data sources for exposure and outcome:\u003c/h2\u003e \u003cp\u003eThe MiBioGen consortium conducted a study analyzing the genotypes of hosts and the sequencing profiles of 16S fecal microbiomes rRNA gene of 18,340 participants, as reported by Kurilshikov et al[27]. The GWAS study examined 211 GM taxa ranging from genus to phylum level and discovered genetic variants associated with 9 phyla, 16 classes, 20 orders, 35 families, and 131 genera.\u003c/p\u003e \u003cp\u003eWe obtained summary statistics of GWAS for IVDD from the FinnGen Consortium R8 release, which included 29,508 cases and 227,388 controls. [28].The diagnosis of IVDD was based on ICD-10 M51,ICD-9 722,and ICD-8 275.Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents detailed information on the exposure and outcome analyzed in this MR study. The details of the exposure and outcome are shown in TABLE1.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetails of the exposure and outcome\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsortium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSamples\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCase\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eControl\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExposure\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e211 GM taxa\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiBioGen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eOutcome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntervertebral disc degeneration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen (R8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e256896\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e164682\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3. Identification of IVs\u003c/h2\u003e \u003cp\u003eSNPs closely associated with each GM taxon were used as instrumental variables (IVs) in this MR study. Due to the limited number of IVs obtained at a strict threshold (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;8), a more comprehensive threshold (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026times;10\u0026thinsp;\u0026minus;\u0026thinsp;5) was utilized to obtain a relatively higher number of IVs, thus resulting in more robust results[29]. In addition, to ensure the independence of each IV, SNPs within a 10,000 kb window size with a threshold of \u003cem\u003er\u003c/em\u003e\u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 were pruned to mitigate linkage disequilibrium (LD). Subsequently, we eliminated palindromic SNPs and SNPs that did not appear in the outcome from the IVs. Ultimately, we computed the F statistic for the IVs to evaluate the degree of bias due to weak instruments.The calculation formula is as follows:\u003cem\u003eF\u003c/em\u003e =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{N-K-1}{K}\\times \\frac{{R}^{2}}{1- {R}^{2}}\\)\u003c/span\u003e\u003c/span\u003e; \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\({R}^{2}\\)\u003c/span\u003e\u003c/span\u003e represents the proportion of variance in the exposure that is explained by genetic variants.N=sample size;K=the number of IV.If the F statistic \u0026gt;\u0026thinsp;10, weak IVs were deemed not to have caused bias [30].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4. Statistical methods\u003c/h2\u003e \u003cp\u003eFor each GM taxon, the inverse variance weighted(IVW)method was used as the primary analysis method to determine causal associations (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), with four additional methods (MR-Egger, weighted median, simple mode, and weighted mode) employed as supplementary measures[31, 32].This study conducted sensitivity analyses in order to eliminate potential bias and examine the robustness of the IVW results. The Cochran Q test was utilized to assess heterogeneity among SNPs, and a \u003cem\u003eP\u003c/em\u003e-value greater than 0.05 indicates a lower likelihood of heterogeneity among the SNPs, in which case the IVW fixed-effect model was employed for analysis. Conversely, if the P-value was less than or equal to 0.05, the IVW random-effects model was used[33].\u003c/p\u003e \u003cp\u003eIn IVW regression, the intercept term is not considered and the reciprocal of the outcome variance (se\u003csup\u003e2\u003c/sup\u003e) is used as weights for fitting[31]. The weighted median method is defined as the median of the weighted empirical density function of the ratio estimates, and causal relationships can be consistently estimated if at least 50% of the information in the analysis comes from valid instruments[31]. In MR-Egger regression, the intercept term is considered, and the reciprocal of the outcome variance (se\u003csup\u003e2\u003c/sup\u003e) is also used as weights for fitting, with the resulting intercept used to assess horizontal pleiotropy[34]. MR-PRESSO global test was also utilized to achieve the same objective, which eliminated the influence of pleiotropy by removing outliers[35]. In addition, funnel plots and forest plots were constructed to visualize and ensure the reliability of the results.Finally, we converted the effect estimates to odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) to more intuitively display the causal associations between each GATA taxon and outcomes.\u003c/p\u003e \u003cp\u003eA significance level of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicated the presence of a causal relationship between the exposure and outcome.To account for multiple testing (multiple exposures), the significance of the MR effect estimates was controlled using a Benjamini-Hochberg false discovery rate (FDR) of \u0026lt;\u0026thinsp;5% at a specific level.Additionally, we performed reverse causal analysis to examine the reverse causality relationship.To meet the core assumptions of MR, the selected SNPs were further filtered in the Phenoscanner database to ensure that the included instrumental variables were not correlated with known confounding factors[36],including dried fruit intake[37],diabetes[38], insomnia[39], plasma omega-3 levels[40],obesity[41], smoking.The replicated MR analyses were performed after excluding instrumental variables associated with confounding factors mentioned earlier.All statistical analyses were performed using the \"TwoSampleMR\" package and the \"MRPRESSO\" package in R language (version 4.3.0).\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1. \u003cb\u003eSelection of instrumental variables\u003c/b\u003e:\u003c/h2\u003e \u003cp\u003eAfter excluding three unknown families and twelve unknown genera from a pool of 211 gut microbiota(GM) taxa, a total of 196 GM taxa were included as exposure.There are 2103 SNPs were selected as instrumental variables,which can be categorized according to five levels: 185 SNPs in 16 classes, 353 SNPs in 32 families, 1232 SNPs in 119 genera, 227 SNPs in 20 orders, and 106 SNPs in 9 phyla. All instrumental variables showed F-values greater than 10, indicating their resilience to weak instrumental variables. Detailed information regarding the instrumental variables can be found in the Supplementary table1.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. \u003cb\u003eCausal effects of gut microbiota on intervertebral disc degeneration\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eCausal Associations from 9 GM taxa(2 Families, 6 Genera, and 1 Phylum) to IVDD were identified through mendelian randomization analysis evaluating the causal link between microbiota taxa at five Levels and IVDD(Supplementary table2).\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the IVW analysis revealed that the \u003cem\u003egenus Escherichia Shigella\u003c/em\u003e (OR: 1.163, 95% CI: 1.025\u0026ndash;1.319, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.019), \u003cem\u003egenus Marvinbryantia\u003c/em\u003e (OR: 1.176, 95% CI: 1.039\u0026ndash;1.330, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.010), and \u003cem\u003ephylum Bacteroidetes\u003c/em\u003e (OR: 1.218, 95% CI: 1.065\u0026ndash;1.392, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) were associated with an increased risk of IVDD. On the other hand, the \u003cem\u003efamily Rikenellaceae\u003c/em\u003e (OR: 0.893, 95% CI: 0.803\u0026ndash;0.993, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037), \u003cem\u003efamily Ruminococcaceae\u003c/em\u003e (OR: 0.845, 95% CI: 0.740\u0026ndash;0.964, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.005), \u003cem\u003egenus Eubacterium coprostanoligenes group\u003c/em\u003e (OR: 0.801, 95% CI: 0.704\u0026ndash;0.912, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), \u003cem\u003egenus Gordonibacter\u003c/em\u003e (OR: 0.933, 95% CI: 0.877\u0026ndash;0.993, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028), \u003cem\u003egenus Lachnoclostridium\u003c/em\u003e (OR: 0.876, 95% CI: 0.774\u0026ndash;0.991, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.035), and \u003cem\u003egenus Oscillospira\u003c/em\u003e (OR: 0.834, 95% CI: 0.721\u0026ndash;0.966, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.016) were associated with a reduced risk of IVDD.\u003c/p\u003e \u003cp\u003eIn addition, we performed four supplementary analysis methods to complement the IVW analysis, and the results were consistent with the direction of the IVW method (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This indicates the robustness of the IVW results.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e3.3. Benjamini\u0026ndash;Hochberg corrected test, sensitivity analysis and reverse analysis\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eAfter conducting the Benjamini-Hochberg corrected test, it was found that the phylum Bacteroidetes remained associated with a higher risk of IVDD (IVW FDR-corrected \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.037)(Supplementary table 2). No heterogeneity was observed according to the Cochrane Q and MR-Egger tests, and the analysis results of MR-Egger and MRPRESSO global tests indicated the absence of horizontal pleiotropy (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHorizontal pleiotropy analysis for IVs of 9 GM taxa associated with IVDD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eHeterogeneity test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e \u003cp\u003eMR-Egger intercept test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eMR-PRESSO global test\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMR-IVW\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMR-Egger\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEgger_intercept\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRSS obs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cem\u003ep\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003efamily Rikenellaceae id.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;14.471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;14.289\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e16.364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003efamily Ruminococcaceae id.2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;6.676\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;6.189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.508\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e8.5467\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.623\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.518\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003egenus Escherichia Shigella id.3504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;7.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;7.645\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.008\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9.708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.469\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003egenus Eubacterium coprostanoligenes group id.11375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;7.735\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;6.683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e9.066\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.806\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003egenus Gordonibacter id.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;6.773\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;6.740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e8.198\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.775\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.750\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003egenus Lachnoclostridium id.11308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;11.166\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;10.808\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e12.955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.517\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.515\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.460\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egenus Marvinbryantia id.2005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;6.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;6.409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.824\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8.243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.716\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egenus Oscillospira id.2064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.693 \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.602\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.034\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13.456\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e0.155\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhylum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ephylum Bacteroidetes id.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;8.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eQ\u0026thinsp;=\u0026thinsp;8.994\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.991\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e10.871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c9\" namest=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.533\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.438\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe leave-one-out sensitivity analysis showed that the IVW analysis results remained similar when any SNP was removed as instrumental variable(Supplementary Fig.\u0026nbsp;1). In the reverse MR analysis, we found no significant causal effect of IVDD on gut microbiota(Supplementary Table\u0026nbsp;3).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Further Analysis for Removing Potential Confounding Factors\u003c/h2\u003e \u003cp\u003eAmong the instrumental variables (IVs) associated with the 9 microbial taxa causally linked to intervertebral disc degeneration (IVDD),rs55793120, rs72829893, rs12925026, and rs62532512 were found to be associated with obesity. Furthermore, rs62532512 was also found to be associated with smoking. After excluding these IVs and conducting the analysis again, it was observed that three GM taxa, including \u003cem\u003efamily Rikenellaceae\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0687), \u003cem\u003egenus Lachnoclostridium\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0751), and \u003cem\u003egenus Oscillospira\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0582), were no longer causally associated with IVDD. However, the causal associations between the remaining GM taxa and IVDD remained robust.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eReplicated MR analysis by IVW method after removing confounders-related IVs\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOutcome\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOR(95%CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"11\" rowspan=\"12\"\u003e \u003cp\u003eIVDD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003efamily Rikenellaceae id.967\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.069\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.903(0.809\u0026ndash;1.008)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily Ruminococcaceae id.2050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.813(0.705\u0026ndash;0.939)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egenus Escherichia Shigella id.3504\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.163(1.025\u0026ndash;1.319)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egenus Eubacterium coprostanoligenes group id.11375\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.801(0.704\u0026ndash;0.912)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egenus Gordonibacter id.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.933(0.877\u0026ndash;0.993)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egenus Lachnoclostridium id.11308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.075\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.885(0.774\u0026ndash;1.012)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egenus Marvinbryantia id.2005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.176(1.039\u0026ndash;1.330)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003egenus Oscillospira id.2064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.885(0.779\u0026ndash;1.004)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhylum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ephylum Bacteroidetes id.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.218(1.065\u0026ndash;1.392)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eTo the best of our knowledge, this is the first mendelian randomization study investigating the causal relationship between gut microbiota (GM) and intervertebral disc degeneration (IVDD). In this study, we utilized GM data derived from a GWAS meta-analysis conducted by the MiBioGen consortium and IVDD data from the R8 release of the FinnGen consortium. The causal effects of gut microbiota taxa (from phylum to genus level) on intervertebral disc degeneration were investigated, and nine gut microbiota taxa were identified to have a causal association with IVDD.Additionally, we performed reverse analysis to demonstrate the unidirectionality of the causal relationships and found no evidence of IVDD affecting the gut microbiota.\u003c/p\u003e \u003cp\u003eThere is a growing interest in understanding the pathogenic impact of the microbiome in numerous human diseases.Dysbiosis of the gut microbiota can potentially impair the normal functioning of the gut microbial community in maintaining host health. It may also lead to the selective enrichment of certain microbial members, including pathogenic bacteria, resulting in a dysregulated production of microbial-derived products or metabolites that can be harmful to the host.This dysregulation can contribute to the development of various diseases in local, systemic, or distant organs[42].Similarly,it has been established that alterations in the composition of the gastrointestinal, skin, and oral microbiota are associated with various musculoskeletal diseases, such as rheumatoid arthritis [43\u0026ndash;45],osteoarthritis [46, 47],ankylosing spondylitis [45],spondyloarthritis[48]. As one of the most common complaints in orthopedic clinics, low back pain is a prevalent public health issue worldwide,causing severe lifelong disability and imposing significant economic burdens on both patients and society[49]. Although the etiology of LBP is diverse[50\u0026ndash;52],IVDD is widely acknowledged as a prominent factor among the various causes[4, 53],which is responsible for approximately 40% of symptomatic LBP[54].In the past, the intervertebral discs in healthy individuals were believed to be sterile.However,Rajasekaran et al.[16] conducted a comprehensive metagenomic analysis of lumbar intervertebral discs, revealing the presence of a human intervertebral disc microbiome, and documenting the existence of \"dysbiosis\". Furthermore, it was discovered that the gut and intervertebral disc microbiomes share a total of 58 bacterial species.In addition, the intervertebral disc (IVD) is a complex fibrocartilaginous joint and is often referred to as the largest avascular structure in the human body. Blood vessels in the IVD are only present in the longitudinal ligaments and the outer layers of the annulus fibrosis. However, the formation of new blood vessels can occur when the following conditions arise: intervertebral disc herniation into the extradural space, physical injury and fractures, or local inflammation on the intervertebral disc and vertebral endplates[55]. In the mouse model of IVDD, the abundance of Muribaculaceae and Lactobacillus increased, while the abundance of Clostridia_UCG-014 decreased. Furthermore, fecal microbiota transplantation further increased the abundance of Lactobacillus and reduced the abundance of Clostridia_UCG-014[56]. Su et al. [57]conducted a mendelian randomization study on the potential causal effects of specific gut microbiota and gut microbiota metabolites on low back pain (LBP). Similar to our findings, they observed that the abundance of the genus Marvinbryantia is a potential risk factor for LBP, while the abundance of the family Rikenellaceae and family Ruminococcaceae is a potential protective factor for LBP.These studies provide evidence for the association between gut microbiota and intervertebral disc degeneration (IVDD).\u003c/p\u003e \u003cp\u003eThe pathogenic mechanisms underlying the role of gut microbiota in IVDD have been widely discussed in previous studies, involving various aspects such as inflammatory response, gut barrier function, and nutrient metabolism.These mechanisms intersect and collectively contribute to the overall impact of gut microbiota in IVDD.The \u003cem\u003eEscherichia Shigella\u003c/em\u003e is a group of bacteria capable of producing lipopolysaccharide (LPS). LPS is a glycolipid component found in the outer membrane of gram-negative bacteria[58].LPS can activate the TLR4/MyD88/NF-κB signaling pathway, leading to the release of pro-inflammatory mediators such as IL-6, IL-1β, and TNF-α. This cascade of events triggers a series of inflammatory processes, ultimately resulting in chronic low-grade inflammation[59].A significant decrease in the abundance of a short chain fatty acids-producer, \u003cem\u003eMarvinbryantia\u003c/em\u003e spp, was observed in the low muscle mass elders[60]. Sarcopenia is postulated to be an influential factor in chronic low back pain[61, 62].The GM taxon may potentially impact intervertebral disc degeneration and trigger lower back pain by regulating nutrient absorption in the intestinal epithelium, thereby affecting muscle mass.\u003cem\u003eRuminococcus\u003c/em\u003e, originally classified as a member of the core phylum \u003cem\u003eFirmicutes\u003c/em\u003e in the human gut microbiota, accounting for approximately 30% of the total gut microbial population[63],has been recently reclassified as \u003cem\u003eBlautia\u003c/em\u003e[64]. \u003cem\u003eBlautia\u003c/em\u003e is a genus of anaerobic bacteria that exhibits probiotic characteristics. It has the potential to reduce the production of local inflammatory factors and alleviate inflammatory responses in the gut. In normal intervertebral disc (IVD) samples, \u003cem\u003eFirmicutes\u003c/em\u003e are abundantly present, and their abundance is associated with intestinal barrier function and antimicrobial protection[16].Both \u003cem\u003eFirmicutes\u003c/em\u003e and \u003cem\u003eBacteroidetes\u003c/em\u003e are capable of fermenting dietary fiber to produce short-chain fatty acids (SCFAs), which then act on G-protein-coupled receptors,such as GPR43, GPR41, and GPR109a,to regulate immune responses[65].This leads to an increase in regulatory T cells (Tregs) and dendritic cell precursors, improvement in epithelial barrier function, and an upregulation of anti-inflammatory cytokines such as IL-10[66].The ratio of \u003cem\u003eFirmicutes\u003c/em\u003e and \u003cem\u003eBacteroidetes\u003c/em\u003e has been implicated that some diseases like T2DM, hyperlipidemia[67], obesity[68], and non-alcoholic fatty liver disease(NAFLD)[69] are associated with elevated \u003cem\u003eFirmicutes\u003c/em\u003e to \u003cem\u003eBacteroidetes\u003c/em\u003e ratio (F/B) in the gut microbiota. Our research, along with previous studies, demonstrates a strong association between Firmicutes, Bacteroidetes and intervertebral disc degeneration (IVDD). Thus, the F/B ratio could potentially be utilized as an evaluative indicator for assessing the association with IVDD. In mouse models of lumbar disc herniation, the gut was found to have a higher abundance of Ruminococcaceae[70], which can alleviate chronic inflammation through the production of butyrate[71]. However, it contradicts our study results to some extent, which suggest that this bacterium acts as a protective factor against IVDD. The reason for this discrepancy may be attributed to the complex interactions that exist among gut microbiota. Further prospective randomized controlled trials may be necessary to validate it. The \u003cem\u003eGordonibacter\u003c/em\u003e, as a probiotic, has been shown to alleviate inflammatory reactions and prevent the occurrence of various diseases[72].It is known to produce anti-inflammatory metabolites, including urolithins. Urolithin A, in particular, has been found to improve mitochondrial health, reduce cartilage degeneration, and alleviate pain in osteoarthritis[73]. Studies have indicated that Urolithin A affects intervertebral discs through mechanisms that include inhibiting the breakdown metabolism of nucleus pulposus cells by TNFα in the body[74].Additionally, it increases mitochondrial autophagy and reduces cell apoptosis in the nucleus pulposus cells[75]. These findings suggest that \u003cem\u003eGordonibacter\u003c/em\u003e may have potential characteristics in regulating intervertebral disc health through the modulation of anti-inflammatory metabolites.Supplementation of vitamin D has been shown to impact the gut microbiota[76].Importantly,vitamin D is closely associated with the gut barrier and can improve barrier function by inducing the expression of E-cadherin and enhancing epithelial cell connections within the intestine[77]. Deficiency in vitamin D can lead to disruption of these connections, resulting in intestinal permeability and facilitating the passage of bacterial components and metabolites. In patients with vitamin D deficiency and osteoarthritis, there is an increase in the abundance of \u003cem\u003eGordonibacter\u003c/em\u003e[78]. This particular microbial group may alter intestinal permeability, thereby creating conditions for the gut microbiota to influence the microecology of intervertebral discs. Yang et al. discovered that Oscillospira sp. constitutes a significant proportion of the gut microbiota. This suggests that Oscillospira sp. may play a crucial role in maintaining microbial balance and human health[79].Importantly, its abundance has been found to be negatively correlated with a range of inflammatory diseases[80].\u003c/p\u003e \u003cp\u003eIn the subsequent analysis after removing the instrumental variables associated with confounding factors, the analysis results for \u003cem\u003eEubacterium coprostanoligenes group\u003c/em\u003e, \u003cem\u003eRikenellaceae\u003c/em\u003e, and \u003cem\u003eLachnoclostridium\u003c/em\u003e no longer showed statistical significance.Limited research has been conducted regarding the association between \u003cem\u003eEubacterium coprostanoligenes group\u003c/em\u003e,\u003cem\u003eRikenellaceae\u003c/em\u003e, \u003cem\u003eLachnoclostridium\u003c/em\u003e, and IVDD. Therefore, whether there is a causal relationship between these three microbial taxa and IVDD remains to be debated.In conclusion,our research findings suggest that gut microbiota a dual role, both inducing and protective, in the occurrence and progression of IVDD.The specific mechanisms underlying these effects and the intricate interplay between gut microbial communities require further elucidation.\u003c/p\u003e \u003cp\u003eIn previous studies, the etiology of intervertebral disc degeneration (IVDD) has mainly focused on various pathological factors, such as aging, inflammation, oxidative stress, mitochondrial dysfunction, and abnormal mechanical load[81\u0026ndash;84]. However, there is limited research on the role of gut microbiota in IVDD. To the best of our knowledge, this study represents the first investigation of this topic using a two-sample bidirectional mendelian randomization (MR) approach. MR utilizes genetic variations as instrumental variables to analyze the causal relationship between exposure and disease outcomes. By leveraging the random allocation of genetic variations, which occurs before the onset of disease and is independent of environmental factors, MR overcomes the inherent limitations of traditional observational studies, such as confounding factors and reverse causality. In this study, we employed available exposure and outcome data from genome-wide association studies (GWAS) to obtain precise analytical results.This approach provides an efficient means of harnessing reliable genetic information without the need for additional experimental costs.Furthermore, we meticulously examined the instrumental variables associated with the positive microbial results using the Phenoscanner V2 website to mitigate the influence of confounding factors and applied false discovery rate (FDR) correction to control the occurrence of false positives, thereby enhancing the reliability and reproducibility of the analysis results.Our research results provide the initial evidence of a causal association between the phylum \u003cem\u003eBacteroidetes\u003c/em\u003e and IVDD, thereby further confirming the concept of the gut-disc axis.\u003c/p\u003e \u003cp\u003eNevertheless,the study has several limitations. First, due to the use of a stringent genome-wide significance threshold (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e), the number of SNPs available for analysis was limited. Only SNPs meeting the suggestive significance threshold (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;1\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e) were included, which may reduce the reliability and accuracy of the results.Furthermore, the sample size and strain-level information of gut microbiota GWAS data are still in the early stages.This resulted in the exclusion of certain microbial species from the study, and the limited number of instrumental variables used may lead to a decrease in statistical power and increase the potential impact of weak instrumental variables on reverse mendelian randomization, making it difficult to fully exclude reverse causality. It is essential to acknowledge that the study's data were exclusively obtained from European populations, without considering factors like gender and ethnicity, limiting the generalizability of the findings to other populations. Additionally, it is important to recognize that the study focused solely on bacteria, disregarding the considerable diversity of eukaryotic viruses and prokaryotic phages present in the human microbiota[85].Further investigations are warranted to explore their potential involvement in IVDD.Finally, the association between human microbiota and the host in both healthy and disease states is a complex interplay rather than a simple one-way \"causal relationship\"[42].Therefore, future studies should consider the intricate coordination and crosstalk between the host and gut microbiota to gain a better understanding of the relationship between gut microbiota and disease.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eUsing publicly available GWAS data, we conducted a bidirectional two-sample mendelian randomization analysis on the causal association between 211 gut microbiota taxa and intervertebral disc degeneration(IVDD). Our analysis resulted in the identification of eight nominal causal associations and one strong correlation, further providing a theoretical foundation for the concept of the gut-disc axis. This study was based on a GWAS meta-analysis dataset generated from 16S rRNA sequencing, thus highlighting the need for analyses based on more advanced large-scale studies using metagenomics sequencing. Nevertheless, our research also offers valuable biomarkers for understanding the progression, diagnosis, and potential therapeutic approaches for IVDD.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eIVDD:intervertebral disc degeneration\u003c/p\u003e\n\u003cp\u003eIVD:intervertebral disc\u003c/p\u003e\n\u003cp\u003eNP:nucleus pulposus\u003c/p\u003e\n\u003cp\u003eECM:extracellular matrix\u003c/p\u003e\n\u003cp\u003eGM:gut microbiota\u003c/p\u003e\n\u003cp\u003eLBP:low back pain\u003c/p\u003e\n\u003cp\u003eMR:mendelian randomization\u003c/p\u003e\n\u003cp\u003eGWAS:genome-wide association studies\u003c/p\u003e\n\u003cp\u003eIVW:inverse variance weighted\u003c/p\u003e\n\u003cp\u003eWME:Weighted median\u003c/p\u003e\n\u003cp\u003eMR-PRESSO:mendelian randomization pleiotropy residual sum and outlier\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSNP:single nucleotide polymorphism\u003c/p\u003e\n\u003cp\u003eIV:instrumental variable\u003c/p\u003e\n\u003cp\u003eFDR:false discovery rate\u0026nbsp;\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate:\u003c/p\u003e\n\u003cp\u003eWe utilized GWAS data that had previously been obtained with informed consent and ethical approval for public release.\u003c/p\u003e\n\u003cp\u003eAcknowledgements:\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eConsent for publication:\u003c/p\u003e\n\u003cp\u003eWritten informed consent for publication was obtained from all participants.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials:\u003c/p\u003e\n\u003cp\u003ePlease contact the corresponding author for data requests.\u003c/p\u003e\n\u003cp\u003eCompeting interests:\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding:\u003c/p\u003e\n\u003cp\u003eThe study is supported by the National Natural Science Foundation of China\u003c/p\u003e\n\u003cp\u003e(81472140)，the Natural Science Foundation of Tianjin City (S20ZDD484) and Health and Technology Project of Tianjin Municipal Commission, Grant No. zc20219.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026apos; contributions:\u003c/p\u003e\n\u003cp\u003eZiming Geng and Jun Miao contributed to conception and design of the study. Ziming Geng,Jian Wang and Guangdong Chen organized the database. Ziming Geng and Jian Wang performed the statistical analysis. Ziming Geng wrote the first draft of the manuscript. Jianchao Liu,Jie Lan and Zepei Zhang wrote sections of the manuscript. All authors contributed to manuscript revision, read, and approved the submitted version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAll author(s) read and approved the final manuscript. Jun Miao conceived and designed the study.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eHartvigsen J, Hancock MJ, Kongsted A, Louw Q, Ferreira ML, Genevay S, Hoy D, Karppinen J, Pransky G, Sieper J\u003cem\u003e et al\u003c/em\u003e: \u003cstrong\u003eWhat low back pain is and why we need to pay attention\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2018, \u003cstrong\u003e391\u003c/strong\u003e(10137):2356-2367.\u003c/li\u003e\n\u003cli\u003eAlonso-Garc\u0026iacute;a M, Sarr\u0026iacute;a-Santamera A: \u003cstrong\u003eThe Economic and Social Burden of Low Back Pain in Spain: A National Assessment of the Economic and Social Impact of Low Back Pain in Spain\u003c/strong\u003e. \u003cem\u003eSpine \u003c/em\u003e2020, \u003cstrong\u003e45\u003c/strong\u003e(16):E1026-e1032.\u003c/li\u003e\n\u003cli\u003eAndersson GB: \u003cstrong\u003eEpidemiological features of chronic low-back pain\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e1999, \u003cstrong\u003e354\u003c/strong\u003e(9178):581-585.\u003c/li\u003e\n\u003cli\u003eKnezevic NN, Candido KD, Vlaeyen JWS, Van Zundert J, Cohen SP: \u003cstrong\u003eLow back pain\u003c/strong\u003e. \u003cem\u003eLancet (London, England) \u003c/em\u003e2021, \u003cstrong\u003e398\u003c/strong\u003e(10294):78-92.\u003c/li\u003e\n\u003cli\u003eZehra U, Tryfonidou M, Iatridis JC, Illien-J\u0026uuml;nger S, Mwale F, Samartzis D: \u003cstrong\u003eMechanisms and clinical implications of intervertebral disc calcification\u003c/strong\u003e. \u003cem\u003eNature reviews Rheumatology \u003c/em\u003e2022, \u003cstrong\u003e18\u003c/strong\u003e(6):352-362.\u003c/li\u003e\n\u003cli\u003eLi Z, Chen X, Xu D, Li S, Chan MTV, Wu WKK: \u003cstrong\u003eCircular RNAs in nucleus pulposus cell function and intervertebral disc degeneration\u003c/strong\u003e. \u003cem\u003eCell proliferation \u003c/em\u003e2019, \u003cstrong\u003e52\u003c/strong\u003e(6):e12704.\u003c/li\u003e\n\u003cli\u003eRaj PP: \u003cstrong\u003eIntervertebral Disc: Anatomy-Physiology-Pathophysiology-Treatment\u003c/strong\u003e. 2008, \u003cstrong\u003e8\u003c/strong\u003e(1):18-44.\u003c/li\u003e\n\u003cli\u003eRopper AH, Zafonte RD: \u003cstrong\u003eSciatica\u003c/strong\u003e. \u003cem\u003eThe New England journal of medicine \u003c/em\u003e2015, \u003cstrong\u003e372\u003c/strong\u003e(13):1240-1248.\u003c/li\u003e\n\u003cli\u003eJensen RK, Kongsted A, Kjaer P, Koes B: \u003cstrong\u003eDiagnosis and treatment of sciatica\u003c/strong\u003e. \u003cem\u003eBMJ (Clinical research ed) \u003c/em\u003e2019, \u003cstrong\u003e367\u003c/strong\u003e:l6273.\u003c/li\u003e\n\u003cli\u003eKrga I, Glibetic M: \u003cstrong\u003e2.16 - Gut Microbiota in Health and Diseases\u003c/strong\u003e. 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prevent extracellular matrix degeneration in intervertebral disc\u003c/strong\u003e. \u003cem\u003eOsteoarthritis and cartilage \u003c/em\u003e2020, \u003cstrong\u003e28\u003c/strong\u003e(8):1121-1132.\u003c/li\u003e\n\u003cli\u003eZhang GZ, Deng YJ, Xie QQ, Ren EH, Ma ZJ, He XG, Gao YC, Kang XW: \u003cstrong\u003eSirtuins and intervertebral disc degeneration: Roles in inflammation, oxidative stress, and mitochondrial function\u003c/strong\u003e. \u003cem\u003eClinica chimica acta; international journal of clinical chemistry \u003c/em\u003e2020, \u003cstrong\u003e508\u003c/strong\u003e:33-42.\u003c/li\u003e\n\u003cli\u003eLiang G, Bushman FD: \u003cstrong\u003eThe human virome: assembly, composition and host interactions\u003c/strong\u003e. \u003cem\u003eNature reviews Microbiology \u003c/em\u003e2021, \u003cstrong\u003e19\u003c/strong\u003e(8):514-527.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Supplementary File","content":"\u003cp\u003eSupplementary figure and table are not available with this version. \u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"gut microbiota, intervertebral disc degeneration, low back pain, causal relationship, mendelian randomization, MiBioGen, FinnGen","lastPublishedDoi":"10.21203/rs.3.rs-3088048/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3088048/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBACKGROUND\u003c/h2\u003e \u003cp\u003eAlthough previous studies have suggested a close association between gut microbiota(GM) and intervertebral disc degeneration(IVDD), the causal relationship between them remains unclear.Hence,we thoroughly investigate their causal relationship by means of a two-sample mendelian randomization (MR) study, aiming to determine the impact of gut microbiota on the risk of developing intervertebral disc degeneration.\u003c/p\u003e\u003ch2\u003eMETHODS\u003c/h2\u003e \u003cp\u003eSummary data from genome-wide association studies (GWAS) of GM (the MiBioGen) and IVDD (the FinnGen biobank) have been acquired.The inverse variance weighted (IVW) method was utilized as the primary MR analysis approach. Weighted median (WME), MR-Egger regression, weighted mode, and simple mode were used as supplements. The mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) and MR-Egger regression were performed to assess horizontal pleiotropy. Cochran's Q test evaluated heterogeneity.Leave-one-out sensitivity analysis was further conducted to determine the reliability of the causal relationship. A reverse MR analysis was conducted to assess potential reverse causation.\u003c/p\u003e\u003ch2\u003eRESULTS\u003c/h2\u003e \u003cp\u003eWe identified nine gut microbial taxa that were causally associated with IVDD(\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).Following the Benjamini-Hochberg corrected test, the association between the phylum \u003cem\u003eBacteroidetes\u003c/em\u003e and a higher risk of IVDD remained significant(IVW FDR-corrected \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0365). The results of the Cochrane Q test did not indicate heterogeneity (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Additionally, both the MR-Egger intercept test and the MR-PRESSO global test revealed that our results were not influenced by horizontal pleiotropy (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Furthermore, the leave-one-out analysis substantiated the reliability of the causal relationship.In the reverse analysis, no evidence was found to suggest that IVDD has an impact on the gut microbiota.\u003c/p\u003e\u003ch2\u003eCONCLUSION\u003c/h2\u003e \u003cp\u003eOur results validate the potential causal impact of particular GM taxa on IVDD, thus providing fresh insights into the gut microbiota-mediated mechanism of IVDD and laying the groundwork for further research into targeted preventive measures.\u003c/p\u003e","manuscriptTitle":"Gut microbiota and intervertebral disc degeneration: A Bidirectional Two-Sample Mendelian Randomization Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-06-27 19:12:04","doi":"10.21203/rs.3.rs-3088048/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2023-07-21T06:47:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2023-07-16T12:36:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6162901c-5205-4b4e-abf7-8ab0771937d1_SNPRID","date":"2023-07-09T02:11:22+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-06-24T10:41:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-06-21T01:39:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2023-06-21T01:00:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Orthopaedic Surgery and Research","date":"2023-06-20T15:01:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-orthopaedic-surgery-and-research","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"josr","sideBox":"Learn more about [Journal of Orthopaedic Surgery and Research](http://josr-online.biomedcentral.com)","snPcode":"13018","submissionUrl":"https://submission.nature.com/new-submission/13018/3","title":"Journal of Orthopaedic Surgery and Research","twitterHandle":"@MSKmedBMC","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a0b53084-357b-4846-a3b8-8a20451f6533","owner":[],"postedDate":"June 27th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2023-10-16T22:13:48+00:00","versionOfRecord":{"articleIdentity":"rs-3088048","link":"https://doi.org/10.1186/s13018-023-04081-0","journal":{"identity":"journal-of-orthopaedic-surgery-and-research","isVorOnly":false,"title":"Journal of Orthopaedic Surgery and Research"},"publishedOn":"2023-08-14 22:00:36","publishedOnDateReadable":"August 14th, 2023"},"versionCreatedAt":"2023-06-27 19:12:04","video":"","vorDoi":"10.1186/s13018-023-04081-0","vorDoiUrl":"https://doi.org/10.1186/s13018-023-04081-0","workflowStages":[]},"version":"v1","identity":"rs-3088048","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3088048","identity":"rs-3088048","version":["v1"]},"buildId":"cBFmMYwuxLRRLfASyISRj","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}