Causal Gut Microbiota-Bone Links: Pleiotropic Effects and Stearidonate Mediation

Causal Gut Microbiota-Bone Links: Pleiotropic Effects and Stearidonate Mediation | 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 Article Causal Gut Microbiota-Bone Links: Pleiotropic Effects and Stearidonate Mediation Hou-Feng Zheng, Peng-Lin Guan, Cheng-Da Yuan, Guangfei Li, Ming-Yu Han, and 12 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6281295/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 28 Nov, 2025 Read the published version in Nature Communications → Version 1 posted You are reading this latest preprint version Abstract Accumulating evidence implicates gut microbiota play a pivotal role in influencing bone metabolism and contribute to the development of osteoporosis (OP). This study aimed to comprehensively investigate the pleiotropic effects between the gut microbiota taxa and bone density, with consideration of shared genetic factors, causal relationships, and the involvement of blood metabolites stearidonate in this complex interplay. We estimate the polygenic SNP heritability (h 2 SNP) for 1104 gut microbiota (GM) taxa GWASs, and identify 97 unique GM taxa with a significant polygenic heritability for further investigation. We identified 14 distinct GM taxa with horizontal pleiotropic effects on heel bone mineral density (eBMD), 11 of them were found to have a causal association with eBMD. GM taxa family Bifidobacteriaceae and its child taxa, genus Bifidobacterium and species Bifidobacterium adolescentis exert causal effects leading to decreased bone mineral density. The mediating effect of these three gut taxa on eBMD was traced back to their influence on blood stearidonate (18:4n3) levels. These findings enhance our understanding of stearidonate's role as a modifiable link in the multifaceted relationship between gut microbiota and bone health. Health sciences/Risk factors Biological sciences/Microbiology/Policy and public health in microbiology Gut microbiota Bone mineral density Causal relationship Pleiotropic Mendelian randomization Bifidobacterium Stearidonate Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Osteoporosis is a bone disease characterized by decreased bone mineral density (BMD) and the occurrence of bone microstructural damage. The evaluation of this condition is primarily measured using dual energy X-ray absorptiometry scans (DXA), with osteoporotic fractures serving as the main clinical outcome [ 1 ]. In the United States, over 2 million osteoporosis-related fractures occurred in 2005, resulting in a treatment cost of $ 17 billion [ 2 ]. BMD, which has a high heritability estimate ranging from 50–85% in family and twin studies, is recognized as a strong predictor of osteoporosis [ 3 , 4 ]. Over the past decade, genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with BMD, osteoporosis, and osteoporotic fractures [ 5 ]. The host gut microbiota, a complex community of microbes inhabiting the gastrointestinal tract, has recently been recognized for its potential role in bone regulation [ 6 ]. Yan et al demonstrated that colonization of the gut microbiota in mice promotes skeletal growth and remodeling by stimulating the hormone insulin-like growth factor 1 (IGF-1), as compared to germ-free mice [ 7 ]. Li et al also found that gut microbiota could influence bone loss associated with sex steroid deficiency in mice [ 8 ]. Certain microbiota taxa, such as Bifidobacterium longum , were shown to affect mineral absorption, including calcium, magnesium, and phosphate [ 9 ], and may also play a crucial role in synthesizing vitamins B and K [ 10 ]. Furthermore, gut microbiota has been implicated in regulating bone overgrowth [ 11 – 13 ] and modulating serotonin synthesis, whose receptors are found in both osteoblasts and osteocytes in the nervous system [ 14 , 15 ]. Studies have also shown that gut microbiota may influence bone development by altering levels of metabolic hormones and calcium absorption [ 16 – 18 ]; producing short-chain fatty acids (such as butyrate) [ 19 ], and affecting peptide like glucagon-like peptide 1 which are related to bone metabolism [ 20 ]. Previous studies have explored the relationship between gut microbiota and BMD using the Mendelian randomization approaches [ 21 , 22 ]. However, these studies primarily examined bacterial taxa at a broader taxonomic level, such as order or family, rather than at a more specific level like genus. The summary datasets were derived from the TwinsUK GWAS for gut microbiota [ 23 ]. It should be noted that the sample sizes in microbiota GWAS were relatively small, and only significant SNPs were used in subsequent analyses. The reliability of genetic associations depends heavily on the selection of instrumental variables, which requires large-scale GWAS summary data that offer robust SNP-trait associations [ 24 – 26 ]. In this analysis, we incorporated 1,104 publicly available GWAS summary statistics for gut microbiota taxa, spanning five taxonomic levels from phylum to species. These data were derived from four recent studies. Notably, Qin et al. identified independent SNPs associated with gut taxonomies within a Finnish cohort [ 27 ]. Another study in a Dutch cohort confirmed these associations near the LCT and ABO genes [ 28 ]. A separate investigation in five German cohorts involving nearly 9,000 individuals also revealed a significant effect of host blood type genes on gut microbiota composition [ 29 ]. These findings shed new light on the complex relationship between bacterial composition and host phenotypes, particularly in the context of host genetic expression. Finally, the MiBioGen consortium undertook a comprehensive analysis that integrated genome-wide genotyping and 16S fecal microbiome data from 18,340 individuals across 24 cohorts to further understand the relationship between host genetics and microbiota composition [ 30 ]. The inclusion of large publicly available genetic summary statistics on gut microbiota, featuring the largest sample size to date, has significantly enhanced our ability to investigate the complex relationship between gut microbiota and diseases. By leveraging these novel datasets during discovery and replication phases, we investigated the genetic influence of gut microbiota on BMD. This exploration was conducted through an assessment of the polygenic SNP heritability ( \(\:{h}_{SNP}^{2}\) ) employing linkage disequilibrium score regression (LDSC) at three genetic levels including genome-wide, gene expression and LD-independent loci. Furthermore, we employed MR to evaluate the causal relationship (vertical pleiotropy) between bacterial taxa showing horizontal pleiotropic genetic effects on BMD traits. In sum, our results underscore the significant role of gut microbiota in bone development, supporting previous studies, and suggest that genetically predicted abundance of specific bacterial taxa may be associated with bone mass variation and influence BMD. Methods Gut microbiota taxa and bone traits GWAS summary statistics We collected GWAS summary statistics for 1,104 gut microbiota taxa abundance quantitative trait loci (mbQTLs) from four studies conducted between January 2021 and February 2022. [ 27 – 30 ]. The majority of participants in these studies were of European ancestry. However, it should be noted that there are about 2900 individuals were included in both two meta-analyses [ 29 , 30 ]. The SNPs information from the human genome build 37 (hg19) was utilized to annotate the GWAS summary statistics, addressing missing rsIDs information. For BMD trait, we sourced GWAS summary data from the Genetic Factors for Osteoporosis (GEFOS) Consortium, a large-scale international collaboration involving multiple research groups ( http://www.gefos.org ). This study included estimated heel quantitative ultrasound bone mineral density (eBMD) data from the UK Biobank collected in 2018 [ 31 ]. The eBMD summary-statistic data was derived from the UK10K/1000G combined imputation panel (hg19) and included 14 million SNPs with a Minor Allele Frequency (MAF) ≥ 0.05%, involving up to 426,824 participants ( Supplementary Table 1 ). Estimated SNP heritability and filtered gut microbiota taxa GWASs We calculated the polygenic SNP heritability ( \(\:{h}_{SNP}^{2}\) ) of the 1104 GM taxa and eBMD GWAS datasets using linkage disequilibrium score regression software ((LDSC, https://data.broadinstitute.org/alkesgroup/LDSCORE ) [ 32 ]. SNPs from approximately 1.2 million common SNPs in European populations from the HapMap3 reference panel (excluding the HLA region) were used. The LD scores of these SNPs referenced the European 1000 Genomes Project phase 3. To filter the GM taxa GWAS datasets, we defined filtering criteria based on the Z score of \(\:{h}_{SNP}^{2}\) is > 1.64 ( \(\:{P}_{{h}_{SNP}^{2}}\) 1 and \(\:{h}_{SNP}^{2}\) < 0 is not meaningful). Pearson correlation for LD-independent SNPs between gut taxa and BMD We employed a genome-wide pleiotropy approach to estimate overall concordant or discordant genetic effects, following the approach used by Nyholt et al [ 33 ]. The Z scores of the LD-independent SNPs derived from GM taxa and eBMD were used to calculate the Pearson correlation ( r ) for trait pairs, including 97 unique GM taxa and eBMD. We retained independent SNPs shared between the gut taxon and eBMD. These SNPs were then used for the subsequent Pearson correlation analysis. To identify LD-independent SNPs, we employed the P-value-informed LD-clumping method using PLINK 1.9 software with --clump-kb 10000, --clump-p1 0.05, --clump-r2 0.1 flags, along with the European 1000 Genome Project reference panel for each gut taxon GWAS. The Pearson correlation coefficients were computed after ensuring the harmonization of the effect alleles among these independent SNPs between the gut taxon and BMD traits. To address the multiple testing problem, we applied False Discovery Rate (FDR) correction (Benjamini-Hochberg method) to adjust P-values for four different studies and each gut microbiome level separately. Pairwise GWAS analysis for LD-independent loci between gut taxa and BMD We performed the pairwise GWAS (GWAS-PW) analysis [ 34 ] involving the GM taxa GWASs and eBMD. The goal was to identify shared genetic variants affecting both gut taxon GWAS and eBMD within any of the 1,703 LD-independent regions (GRCh37) [ 35 ]. For each of the 1,703 loci, we calculated four posterior probabilities (PPA) using Bayesian analysis via GWAS-PW software: PPA1: The probability of containing a genetic variant which was only associated to BMD; PPA2: The probability of containing a genetic variant which was only associated to gut taxon; PPA3: The probability of sharing a genetic variant which was both associated to BMD and gut taxon; PPA4: The probability of containing two distinct associations which were associated to BMD and gut taxon respectively. When either PPA3 or PPA4 exceeded 0.9 for a locus, it was defined as a pleiotropic-associated locus. If a gut taxon had at least one pleiotropic-associated locus, it was identified as demonstrating horizontal pleiotropy with BMD at the genetic variant level. Summary-based Mendelian randomization for gene expression level between gut taxa and BMD To identify genetic factors influencing gene expression, we obtained expression quantitative trait loci (eQTL) summary data from the eQTLGen consortium and Genotype-Tissue Expression (GTEx) consortium. We then employed summary-based Mendelian randomization (SMR) analyses [ 36 , 37 ]. The eQTLGen consortium integrates 37 expression datasets, encompassing both array- and sequencing-based methodologies, derived from whole blood samples involving 31,684 individuals. This analysis includes ~ 17,000 genes and nearly 11 million SNPs in cis-eQTL analyses. The GTEx consortium provided data from artery tibial tissue, based on version 7, involving 308 individuals, forming a vital component of this analysis. The SMR method used eQTL datasets and GWAS summary data to assess gene expression levels associated with bacterial taxa and BMD [ 38 ]. In this process, we specifically selected cis-eQTL SNPs with a P-value < = 5×10 − 8 within the context of whole blood tissue, utilizing them as instrumental variables. Following the SMR linkage clumping protocol (--ld-upper-limit 0.9 --ld-lower-limit 0.05 --peqtl-heidi 1.57e-3 --heidi-min-m 3 --heidi-max-m 20 --cis-wind 2000), we identified associated genes using a Bonferroni corrected P-value threshold (P 0.05. Mendelian randomization analysis We evaluated the association between these instrumental variables and outcomes through two-sample MR analyses. GM taxa summary-statistic data and eBMD. To investigate the causality between GM taxa and bone health, we employed three complementary MR methods including inverse variance-weighted (IVW) test; MR-Egger and the weighted median method. IVW Test: The IVW test was prioritized for GM taxa screening results due to its increased power under specific conditions, where the intercept is set to zero in the linear regression between exposure and outcome effects [ 39 ]. The MR-Egger Regression was utilized to examine directional (unbalanced) pleiotropy [ 40 ], adding an additional layer of analysis to test potential biases. The weighted Median Method was employed to enhance the robustness of the results, contributing to the overall reliability of the findings [ 41 ]. Together, these MR methods provide complementary insights into the causality between GM taxa and bone health. To investigate the causal relationship between gut taxa and metabolites, we selected GM taxa associated with eBMD in both discovery and replication stages for further MR analysis. We collected GWAS summary statistics for 453 metabolites in human blood from 7,824 adults in two European population studies [ 42 ]. We performed two-sample MR analyses to explore whether metabolites could causally affect BMD. For each outcome trait, we selected instrumental variants with a significance level at P < = 5×10 − 8 for the MR analysis. In cases where two significant SNPs within a distance of 500 kb had a linkage disequilibrium score (r 2 ) greater than 0.1, we selected the independent SNP with the most statistically significant association, as indicated by the lowest p-value. If a GM taxon contained only one instrumental variable (IV), we used the Wald ratio test to estimate the causal effect, as an alternative to the Inverse Variance-Weighted (IVW) test. All analyses, including sensitivity and MR analyses, were conducted in R version 4.0.3, using the R package "MendelianRandomization." Multivariable Mendelian randomization analysis We then conducted multivariable MR analyses to determine the mediation effect of specific metabolite on the relationship between the GM taxon and eBMD[ 43 ]. The specific metabolite was found to be potentially causally affected by the GM taxon and were also identified as factors that could affect eBMD in MR analysis (IVW-P < 0.05/N; N, the number of all GM taxa). Specifically, we began by extracting the genetic association estimates of instrumental variables for both the gut taxon and the metabolite. Subsequently, we estimated the effect of the GM taxon on the specific metabolite (β 1 ) based on generalized IVW method. We then estimated the effect of the metabolite on eBMD while adjusting for the effects of the gut taxon (β 2 ). Additionally, we estimated the effect of the gut taxon on eBMD with adjustment for the metabolite, employing the multivariable MR approach. In this analysis, genetic instrumental variables for each of the exposure [i.e., genetic instrumental variables for 1st exposure: the specific GM taxon, and genetic instrumental variables for 2nd exposure: all independent genome-wide significant genetic variants for the specific metabolite (r 2 < 0.001 and P -value < 5×10 − 8 )] are used together with the corresponding association of SNPs with each exposure and outcome (eBMD). The indirect mediation effect of the GM taxon on eBMD was estimated by β 1 × β 2 . Therefore, the proportion of the total effect mediated by each cardiometabolic factor can be estimated by dividing the indirect effect of the exposure (i.e., β 1 × β 2 ) by the total effect (i.e., univariable MR of the GM taxon on eBMD) [ 44 ]. Results The selection of heritable GM taxa An overview of the study design was depicted in Fig. 1 . A total of 1104 GM taxa GWAS summary data were obtained from four recent studies [ 27 – 30 ], and the studies encompassed a sample size ranging from 5959 to 18340 participants ( Supplementary Table 1 ). We first estimated the SNP heritability (h 2 SNP ) for all GM taxa using linkage disequilibrium score regression method (LDSC), and found that most of the GM taxa showed low heritability, with the gut taxon species Bifidobacterium catenulatum exhibiting the highest SNP-based heritability ( \(\:{h}_{SNP}^{2}\) = 0.9845) ( Supplementary Table 2 ). The Z scores of \(\:{h}_{SNP}^{2}\) in all GM taxa exhibited a significant pearson correlation both with the number of SNPs in GWASs ( r = 0.112, P = 0.000185) and the number of sample size ( r = 0.116, P = 0.00011) ( Supplementary Fig. 1 ). This implies that the heritability of gut taxa could be attributed to genome-wide polygenicity and larger participant numbers in GM GWAS. To filter the heritable GM taxa, we selected 108 GM taxa which possessed a Z score of \(\:{h}_{SNP}^{2}\) great than 1.64 ( \(\:{P}_{{h}_{SNP}^{2}}\) <0.05; one-side), accounting for approximately 9.78% of the total (108/1104) (Fig. 2 ). These selected GM taxa exhibited significant polygenicity, and their SNP-based heritability values were both statistically significant and meaningful ( \(\:{h}_{SNP}^{2}\) ≥ 0.0445). Among the 1104 GM taxa GWASs, the gut taxon species Bifidobacterium catenulatum exhibited the highest SNP-based heritability ( \(\:{h}_{SNP}^{2}\) = 0.9845). Additionally, when there were multiple datasets for a single gut taxon, we opted for the one with the higher Z score of \(\:{h}_{SNP}^{2}\) for subsequent analyses. As a result, we ultimately selected 97 unique GM taxa summary data for further analysis ( Supplementary Table 3 ). The name of included gut taxon for further analysis was reported by the lowest bacteria taxa level name for consistency. The estimated median \(\:{h}_{SNP}^{2}\) of those 97 unique GM taxa from the four studies distributed from 0.072 to 0.1735 (Table 1 ). These taxa are categorized into 1 phylum, 4 classes, 4 orders, 11 families, 33 genera, and 44 species ( Supplementary Fig. 2 ). Additionally, we observed that eBMD GWAS exhibited a Z score for \(\:{h}_{SNP}^{2}\) of 14.96 ( Supplementary Table 3 ). Genome-wide pleiotropic association between GM taxa and BMD We employed an approach to estimate the similarity in SNP effects at the genome-wide level, similar to a previous study [ 33 ]. Specifically, we selected gut taxa that exhibited a concordant genetic effect across the entire genome (genome-wide pleiotropic) with BMD trait based on a significant correlation Z score of the LD-independent SNPs. The LD-independent SNPs from the eBMD GWAS were selected and matched with the 97 unique GM taxa GWASs, leaving us with a range of 31,712 to 58,953 SNPs for estimating genome-wide effect similarity. The pearson correlation coefficients ( r ) were calculated using the Z scores of those SNPs, which were harmonized by the effect allele. Further details of this analysis can be found in the Methods section. Among these results, two GM taxa displayed significant negative SNP effects correlations with eBMD at a false discovery rate (FDR) less than 0.1 (Fig. 3 A), including Haloplasmatales ( r = -0.00896; P = 0.02965) and Bifidobacterium adolescentis ( r = − 0.0153; P = 0.0055) ( Supplementary Table 4 ). Pleiotropic SNPs and genes influencing association between GM taxa and BMD Using the pairwise GWAS (GWAS-PW) method, we have identified independent genetic loci which were associated with both BMD and GM taxa by a shared SNP. The independent loci with third posterior probability (PPA3) ≥ 0.9 was suggested the pleiotropic associated SNP between BMD and GM taxa in this analysis. In this study, we have identified five pleiotropic genetic loci that are jointly associated with estimated heel quantitative ultrasound bone mineral density (eBMD) and 13 distinct GM taxa, all through the influence of shared Single Nucleotide Polymorphisms (SNPs) ( Supplementary Table 5 ). We assessed the proportion of pleiotropic LD-independent loci that influence both traits, BMD and gut taxon, via a shared SNP among all loci associated with gut taxon. This proportion exhibited a range from 0.5 to 1 ( Supplementary Table 5 ). Among the identified pleiotropic loci influencing both estimated heel quantitative ultrasound bone mineral density (eBMD) and seven GM taxa, two specific GM taxa stand out: the order Bifidobacteriales (comprising Bifidobacterium pseudocatenulatum and Bifidobacterium adolescentis ) and the phylum Bacillota (consisting of Negativibacillus sp000435195 and Turicibacter ). These loci are located was on chromosome 2 135.1-137.1 Mb, with the lead SNP rs2090660 positioned near the CXCR4 gene (Fig. 3 B). Additionally, we uncovered two pleiotropic loci associated with eBMD and two gut taxa, Faecalicatena torques and Faecalibacterium , situated on chromosome 9 135.3–137 Mb with the lead SNP rs635634 near the ABO gene (Fig. 3 C). Furthermore, the association extends to Clostridiales bacterium CHKCI006 sp900018345 and Merdibacter massiliensis at chromosome 12 0.17–1.08 Mb, with the lead SNP rs215226 located within the B4GALNT3 gene (Fig. 3 D). Interestingly, SMR analysis result uncovered a significant association between the expression level of the B4GALNT3 gene and eBMD (P smr = 8.011×10 − 07 ). The GM species Clostridiales bacterium CHKCI006 sp900018345 (P smr = 5.324×10 − 07 ) and Merdibacter massiliensis (P smr = 5.321×10 − 07 ) were also found to be significantly associated with the expression level of the B4GALNT3 gene in artery tibial tissue (Fig. 3 E). This further confirms the results obtained from the GWAS-PW analysis. The expression level of the ABO gene was also found to be associated with the GM taxon Faecalicatena torques, as determined through the integration of the eQTL dataset. This finding corroborates the results obtained from the GWAS-PW analysis. Additionally, we identified significant associations between the expression of the LCT and MCM6 genes and multiple GM taxa, in both artery tibial tissue and the eQTLgen dataset ( Supplementary Table 6 ). Candidate GM taxa with a causal effect on BMD Our cross-trait analyses identified several gut microbiota (GM) taxa that exhibited pleiotropy with bone mineral density (BMD) at multiple levels, including genome-wide, single nucleotide polymorphism (SNP), and gene expression levels. These GM taxa were selected for further analysis as candidate gut taxa. In total, we identified 14 GM taxa out of 97 unique GM taxa that exhibited horizontal pleiotropic effects on BMD. To further investigate the causal relationships, we employed Mendelian randomization (MR) analysis, using the inverse variance-weighted (IVW) method to estimate the causal relationship (vertical pleiotropic association). Additionally, we utilized the weighted median method to enhance the robustness of our results and the MR-Egger regression method to assess directional (unbalanced) pleiotropy. The detailed information of the MR analysis is presented in the Methods section. In this study, we have identified the 11 specific GM taxa abundances with a causal relationship with eBMD, including Bifidobacterium adolescentis ( β IVW = -0.03142, p = 3.585 x 10 − 5 ); Bifidobacterium pseudocatenulatum ( β IVW = -0.02584, p = 0.00301); Bifidobacteriales ( β IVW = -0.02922, p = 0.000981); Bifidobacteriaceae ( β IVW = -0.02921, p = 0.000981); Bifidobacterium ( β IVW = -0.02921, p = 0.000981); Clostridiales CHKCI006 sp900018345 ( β IVW = 0.4172, p = 1.317 x 10 − 31 ); Merdibacter massiliensis ( β IVW = 0.3241, p = 4.036 x 10 − 20 ); Negativibacillus sp000435195 ( β IVW = 0.0542, p = 9.944 x 10 − 5 ); Turicibacter ( β IVW = 0.3241, p = 4.036 x 10 − 20 ); Faecalibacterium ( β IVW = -0.1692, p = 1.305 x 10 − 19 ); Haloplasmatales ( β IVW = 0.04885, p = 0.00138) ( Supplementary Table 7 ). Notably, we excluded candidate bacteria lacking the SNPs required for instrumental variables in the MR analysis (P < 5 × 10^-8) in the further analysis. The specific gut microbiota taxon associated with eBMD in replication sample Furthermore, we verified the association between specific GM taxa and BMD, accounting for both vertical and horizontal pleiotropy, in the replication sample using publicly available GM abundance GWAS summary statistics from four recent studies. Additionally, we restricted the inclusion of GM GWASs in the replication sample to those with \(\:{h}_{SNP}^{2}\) values between 0 and 1. This study aimed to replicate the associations between five GM taxa ( Bifidobacterium adolescentis , Bifidobacteriales , Bifidobacteriaceae , Bifidobacterium and Faecalibacterium ) and BMD in the replication sample. Significantly, our MR analysis indicated that the abundance of the GM taxa family Bifidobacteriaceae ( β IVW = − 0.021512, p = 0.0221) and its child taxa, including the genus Bifidobacterium ( β IVW = -0.0194, p = 0.01543) and the species Bifidobacterium adolescentis ( β IVW = − 0.0174, p = 0.0082), was causally associated with a decrease in eBMD in replication sample. Importantly, this association was observed in both the discovery and replication samples, enhancing the reliability of this finding. Additionally, our GWAS-PW analysis revealed that specific loci on chromosome 2 135.1-137.1 Mb with lead SNP rs2090660 near CXCR4 gene exhibited horizontal pleiotropy, influencing both eBMD and these GM taxa. This pleiotropic effect was consistent in both the discovery and replication samples, further supporting the robustness of this association ( Table 2 ). The Mediation analysis result between the specific gut microbiota taxon on BMD through the metabolite Here, we conducted Multivariable Mendelian randomization analysis to investigate how the species Bifidobacterium adolescentis may influence eBMD through metabolites. Initially, we identified 41 metabolites that could be causally affected by the species Bifidobacterium adolescentis, with a Bonferroni-corrected p-value from IVW analysis < 0.05 (i.e., P IVW <0.05/453) ( Supplementary Table 8 ). Subsequently, we performed a two-sample MR analysis between those metabolites w that were causally associated with the species Bifidobacterium adolescentis and eBMD. We found the stearidonate (18:4n3) were causal associated with eBMD ( β IVW = -0.3924, p = 3.808e-12) at significant level ( p < 0.05/43) ( Supplementary Table 9 ). The species Bifidobacterium adolescentis was causally associated with an increase in blood stearidonate level ( β IVW = 0.0621, p = 1.92e-05) (Fig. 4 C). Based on the multivariable MR analysis, we observed that the direct effect of the species Bifidobacterium adolescentis on eBMD disappeared after adjusting stearidonate (Fig. 4 A). Moreover, stearidonate (18:4n3) showed a negative causal association with eBMD after adjusting the species Bifidobacterium adolescentis (Fig. 4 B). Mediation analysis showed the indirect effect of the species Bifidobacterium adolescentis on eBMD through stearidonate was − 0.02432 (95% CI: -0.038, -0.0106), with a mediation proportion of 77.41% ( Table 3 ). Also, we found the similarity results for the family Bifidobacteriaceae and genus Bifidobacterium (Fig. 3 ; Table 3 ). The overall Mendelian Randomization results between the family Bifidobacteriaceae or genus Bifidobacterium and 453 metabolites were also listed in Supplementary Table 8. Discussion The gut microbiota is a complex group colonized in the human gut, in adults, the gut bacteria were mainly consisting of Bacteroidetes and Firmicutes , whereas Actinobacteria and Proteobacteria were secondary components [45]. In our investigation, our primary objective was to delve into the genetic relationships, encompassing both vertical and horizontal pleiotropic associations, between bone mineral density (BMD) and the abundance of gut microbiota primarily inhabiting the human gastrointestinal tract. Furthermore, we sought to elucidate the influence of blood metabolites on the gut-bone pathway. In contrast, a previous study revealed that the majority of human gut microbiota taxa exhibited no significant associations with host genetics [46]. Hence, we opted to focus on gut taxa with a significant polygenicity, encompassing genome-wide association signals. The SNP-based heritability of these gut taxa, as estimated by LDSC, consistently met the criteria for statistical significance (\(\:{Z}_{{h}_{SNP}^{2}}\)> 1.64) and biological relevance (0 < \(\:{h}_{SNP}^{2}\) < 1). Consequently, we narrowed our analysis to 97 unique GM taxa from the original 1104, facilitating more precise genetic association investigations. To investigate the relationship between host genetic derived GM taxa abundance and BMD, our study provides evidence of both vertical and horizontal pleiotropic genetic associations between specific GM taxa and BMD. We identified the 14 candidate GM taxa had horizontal pleiotropic effects at three different levels of genome-wide, colocalization SNPs and gene expression level in 97 unique GM taxa. Furthermore, we have identified the causal effects of 11 specific GM taxa on eBMD through MR analysis. Specifically, the GM species Bifidobacterium adolescentis, along with its parent taxon family Bifidobacteriaceae and genus Bifidobacterium , exhibit both vertical and horizontal pleiotropic genetic associations with eBMD in both the discovery and replication samples. Lastly, we identified the mediator effect on these three gut taxa on eBMD through the stearidonate (18:4n3) level in blood. The heritability results for the 1104 GM taxa indicate that including a larger number of individuals and employing deeper sequencing methods, such as metagenomics, can help identify more GM taxa with higher polygenicity in GM GWAS. Notably, the GM taxa demonstrated higher polygenicity compared to the blood proteome in the previous study [33]. The significant association between the SNP heritability of the 1104 GM taxa and the number of included SNPs suggests that the heritability of gut taxa can be attributed to genome-wide polygenicity and is enhanced by larger participant numbers in GM GWAS. Our results suggest that certain GM taxa exhibit relatively high heritability, even though environmental factors also play a significant role in shaping the human GM. Our multiple horizontal pleiotropies genetically association results revealed 11 unique GM taxa associated with eBMD. Significantly, the GM taxon Bifidobacterium adolescentis exhibited two lines of evidence for horizontal pleiotropy with eBMD, at both the genome-wide and SNP level. Additionally, GM taxon Clostridiales bacterium CHKCI006 sp900018345 and Merdibacter massiliensis showed horizontal pleiotropy with eBMD at genome-wide and gene expression levels. Pleiotropy at the genome-wide level provides the direction of the relationship between GM taxa and BMD, contingent upon the presence of sufficient polygenic signals and consistent SNP effect directions. Nevertheless, pleiotropy at gene expression and SNP levels furnishes evidence of shared genetic signals evidences between GM taxa and BMD, although it does not provide information about the direction of the relationships. Therefore, horizontal pleiotropy findings at these three levels complemented each other, identifying in 14 unique GM taxa with horizontal pleiotropic effects on eBMD. These 14 GM taxa are potential candidates associated with BMD and were subsequently subjected to further vertical pleiotropy analysis. Regarding these candidate GM taxa, we conducted MR analyses to unveil their potential causal links with eBMD. Our study identified several GM taxa with significant genetic causality in relation to eBMD. Specifically, we discovered that a group of GM taxa belonging to the order Bifidobacteriales ( Bifidobacterium pseudocatenulatum , Bifidobacteriales , Bifidobacteriaceae , Bifidobacterium , Bifidobacterium adolescentis ) exhibited both the horizontal and vertical pleiotropy association with eBMD, implying their potential impact on lower BMD levels. This finding suggests that these GM taxa could play a role in the regulation of bone mass variation and influence bone development. We also noted that Clostridiales bacterium CHKCI006 sp900018345 , which was the sub-category of the order Clostridiales , had a causal effect on higher eBMD, demonstrating both horizontal and vertical pleiotropic associations, as reported in previous studies [21, 47, 48]. The genus Turicibacter exhibited horizontal and vertical pleiotropy associations with eBMD, potentially contributing to increased BMD as indicated in our results, and this finding was substantiated by mouse experiments [49]. Moreover, the several GM taxa in family Oscillospiraceae ( Faecalibacterium , Faecalibacterium sp. UBA7177 sp002491225 ) was found associated with BMD with both horizontal and vertical pleiotropic associations. Prior research has shown that Oscillospiraceae is capable of producing butyrate, a type of short-chain fatty acid (SCFA) [49]. SCFA has been associated with the inhibition of osteoclast differentiation and bone resorption, both in vitro and in vivo. Compounds like propionate and butyrate are recognized as potent regulators of osteoclast metabolism and bone health [19]. Xu et al. also observed an enrichment of the genus Faecalibacterium in primary osteoporosis patient group, indicating its potential involvement in bone metabolism [50]. Similarly, another study found associations between Clostridiaceae and Faecalibacterium with bone metabolism [51]. In both GWAS-PW and SMR analysis, we identified that the gene B4GALNT3 is associated with both eBMD and two GM taxa ( Clostridiales bacterium CHKCI006 sp900018345 , Merdibacter massiliensis ). Notably, prior studies had already reported an association between gene B4GALNT3 and BMD [52, 53]. This suggests that the expression level of the B4GALNT3 gene could play a role in the pleiotropic association between these GM taxa and BMD. Intriguingly, we also observed that the expression level of gene LCT and MCM6 were significant associated with a series of GM taxa in order Bifidobacteriales ( Bifidobacteriaceae , Bifidobacterium , Bifidobacterium adolescentis ). Additionally, the ABO gene was linked to species Faecalicatena torques , as previously reported in extensive microbiota GWAS studies [27–30, 54]. In our study, our GWAS-PW and MR analyses consistently verified the vertical and horizontal pleiotropic genetic associations of three GM taxa ( Bifidobacteriaceae, Bifidobacterium and Bifidobacterium adolescentis ) with eBMD in both the discovery and replication samples from two independent cohorts. It's worth noting that species Bifidobacterium adolescentis is a sub-category of genus Bifidobacterium , and genus Bifidobacterium belongs to the family Bifidobacteriaceae . The abundance of the GM species Bifidobacterium adolescentis was found to have a potential causal effect in decreasing BMD which contrasts with a previous study suggesting that Bifidobacterium adolescentis supplementation could strengthen skeletal protection following fractures [55]. Additionally, some strains of Bifidobacterium , when used as probiotics, have been shown to have beneficial effects on bone health, as indicated in a prior review [56]. It's important to highlight that the negative causal association between Bifidobacteriaceae and BMD in our study contradicts findings from a previous observational study [57]. This discrepancy may be attributed to variations in sample sizes between the two studies. Nevertheless, it's worth noting that the human gut microbiota generates a diverse array of molecules, and certain components from this microbial community enter the bloodstream, where they can significantly impact overall health [58]. In recent years, there has been some progress in the field of metabolomics research related to BMD [59]. To further investigate how the GM taxa affect BMD through blood metabolites, our mediation analysis revealed that species Bifidobacterium adolescentis might potentially decrease BMD by elevating blood stearidonate levels. Even more noteworthy is the fact that the direct effect of the species Bifidobacterium adolescentis on eBMD vanished when stearidonate was taken into account. This indicates that the impact of gut microbiota on bone density is likely linked to the metabolites it affects. In a separate cross-sectional study involving a Swedish cohort [58], an association was established between Bifidobacterium adolescentis and elevated stearidonate levels (Spearman's rho = 0.03; P = 0.0202). Similarly, we observed a consistent outcome in two other GM categories family Bifidobacteriaceae and genus Bifidobacterium , which also potentially impact bone density by elevating blood stearidonate levels. Stearidonate is one of the multiple omega-3 fatty acids. Animal experiments have demonstrated that omega-3 fatty acids made a complex effect in skeletal development [60]. Although omega-3 fatty acids are generally considered beneficial for bone health [61], a recent study found that omega-3 fatty acid supplementation had no impact on fractures [62]. However, a recent meta-analysis has indicated that supplemental omega-3 fatty acids significantly increased blood omega-3 levels but had no significant effects on bone mineral density (BMD)[63]. Another research showed that polyunsaturated fatty acids (PUFA) (including omega-3 fatty acids and omega-6 fatty acids) was significantly inversely correlated with both BMD[64]. Stearidonate and eicosapentaenoic acid (EPA) are important components of omega-3 polyunsaturated fatty acids. Dietary intake of stearidonate may serve as a precursor to enhance the EPA content in human lipids[65, 66]. EPA may generate resolvins to mitigate inflammation, which can otherwise lead to bone loss and pose significant risks to human health[67]. Additionally, EPA may inhibit NF-κB to mitigate bone loss associated with spaceflight[68]. In animal experiments, high-dose EPA supplementation promotes osteoblastogenesis and upregulates the expression of osteoblast-specific proteins and genes[69]. Nevertheless, there is no direct evidence to demonstrate how stearidonate influences bone mineral density. We propose that elevated blood stearidonate levels may indicate a diminished capacity to synthesize EPA, potentially leading to a reduction in bone density, as reflected in the results of the Mendelian randomization analysis. Furthermore, stearidonate, which is efficiently metabolized into EPA, may inhibit arterial calcification via modulation of the Wnt signaling pathway, thereby potentially affecting osteoblast differentiation, osteogenesis and BMD [70]. Our research offers a fresh perspective on the gut microbiota-metabolite-bone axis within Bifidobacterium adolescentis ( Bifidobacterium and Bifidobacteriaceae ), indicating their role in regulating bone mass and influencing bone development through stearidonate. These findings should be further validated through additional animal experiments and observational studies. Recently, Cheng et al. conducted a weighted genetic risk score (wGRS) analysis using the UK Biobank dataset and found a weak association between GM and pelvis BMD [22]. Additionally, they utilized a GM polygenic risk score to identify environmental interactions within the UKB dataset, revealing several genes that interact with GM and BMD [71]. Ni et al. conducted a two-sample MR analysis by integrating genetic data, and found that the order Clostridiales and family Lachnospiraceae were associated with bone development in both discovery and replication sample [21]. However, it is important to note that these studies had certain limitations. The gut microbiota GWAS they conducted were relatively limited, and only a few genetic instruments were included. Furthermore, they did not consider the horizontal pleiotropy, which is an important factor in the relationship between GM taxa and BMD. Therefore, we employed various cross-trait approaches at several levels to detect the potential pleiotropic effects. Unlike previous studies that mainly examined bacterial taxa at a higher taxonomic level, we investigated them at a more specialized level, including genus and species, to provide a more detailed understanding of their relationships with BMD. Our study performed different analyses to identify the potential association relationship between 1104 bacteria taxa from phylum to species level in four different GM GWAS studies, increasing the reliability of the relationship results. Moreover, we unveiled the critical role of metabolites in mediating the influence of GM on BMD. However, it's essential to acknowledge some limitations in our study. Firstly, the GM and BMD GWASs predominantly utilized data from European populations. Given the substantial variations in GM composition across populations with diverse ancestries, our findings may not be readily applicable to other ancestral groups. Secondly, the potential presence of sample overlaps between the two GM GWAS datasets used in our study might have a minor influence on our findings, which could, in turn, affect our conclusions. Thirdly, it's important to note that our study specifically concentrated on the 8.8% (97 out of 1104) of GM taxa that exhibited a significant genome-wide heritability estimated via LDSC. Nevertheless, there may be other GM taxa that can influence host BMD without a clear genetic association, which were beyond the scope of our study. Fourthly, it's worth noting that GM taxa typically impact host phenotypes through intricate networks of interactions between microbes and host genes, which weren't directly examined in our study. Finally, some potential confounders such as environmental variables and protein could potentially influence the microbiome, which might influence our results. Indeed, observational studies and subsequent animal experiments are essential for validating the mechanisms by which metabolites are involved in the interplay between GM and BMD. In conclusion, our systematic investigation provided assess of pleiotropy relationship between BMD traits and 97 unique GM taxa with significant polygenic SNP heritability, implicates 14 unique GM taxa and eBMD by shared genetic effect, 11 of 14 unique GM taxa was found the causal association with eBMD. Specifically, three GM taxa including Bifidobacteriaceae , Bifidobacterium and Bifidobacterium adolescentis were found to have a causal effect on decreasing BMD due to both vertical and horizontal pleiotropic genetic influences, likely through the increase in blood stearidonate levels. Our study could be helpful to comprehend how gut microbiota can potentially regulate bone mass variation and impact bone development through the mediation of metabolites. Table 1 Summary of polygenic SNP heritability for the 97 unique gut microbiota taxa GWASs (with a significant SNP heritability) analyzed in this study. GWASs study Number of GM taxa sample size h2SNP range h2SNP SE range h2SNP median h2SNP SE median Dutch 21 7,738 0.1024–0.9845 0.0596–0.3944 0.1378 0.0755 FINRISK 54 5,959 0.1252–0.349 0.0702–0.1603 0.1735 0.0811 German 11 8,956 0.0875–0.1213 0.0495–0.0573 0.1131 0.0535 Large 22 18,340 0.0445–0.0942 0.0223–0.0481 0.072 0.0326 Abbreviation: GWASs study, article name for short ( FINRISK, Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort; Dutch, Effect of host genetics on the gut microbiome in 7,738 participants of the Dutch Microbiome Project; German, Genome-wide association study in 8,956 German individuals identifies influence of ABO histo-blood groups on gut microbiome; Large, Large-scale association analyses identify host factors influencing human gut microbiome composition); sample_size, reported sample size of each gut microbiota GWAS; h2SNP, SNP heritability, SE Standard error of SNP heritability. Declarations Acknowledgments We thank the UK Biobank database, the GEnetic Factors for OSteoporosis (GEFOS) Consortium and Microbial composition. We also thank the Westlake University Supercomputer Center for the facility support and technical assistance. Author contributions H.-F.Z. conceptualized and designed the study. P.-L.G., Y.Q., C.-D.Y. and Y.-H.F. conducted the data analysis. M.-Y.H., C.-F.Y., P.-P.Z., J.-W.X., P.W., C.-R.L., M.-Y.Y., W.X., and L.B. contributed to the data collection, processing and preliminary data analysis. P.-L.G. drafted the manuscript, H.-F.Z. reviewed and edited manuscript. All authors contributed, discussed and approved manuscript. Competing Interests None declared. References Zhu X, Zheng H. Factors influencing peak bone mass gain. Front Med. 2021;15(1):53-69. Epub 2020/06/11. doi: 10.1007/s11684-020-0748-y. PubMed PMID: 32519297. Burge R, Dawson-Hughes B, Solomon DH, Wong JB, King A, Tosteson A. 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Panahi N, Arjmand B, Ostovar A, Kouhestani E, Heshmat R, Soltani A, et al. Metabolomic biomarkers of low BMD: a systematic review. Osteoporos Int. 2021;32(12):2407-31. Epub 20210726. doi: 10.1007/s00198-021-06037-8. PubMed PMID: 34309694. Rozner R, Vernikov J, Griess-Fishheimer S, Travinsky T, Penn S, Schwartz B, et al. The Role of Omega-3 Polyunsaturated Fatty Acids from Different Sources in Bone Development. Nutrients. 2020;12(11). Epub 20201113. doi: 10.3390/nu12113494. PubMed PMID: 33202985; PubMed Central PMCID: PMCPMC7697266. Saini RK, Keum YS. Omega-3 and omega-6 polyunsaturated fatty acids: Dietary sources, metabolism, and significance - A review. Life Sci. 2018;203:255-67. Epub 20180430. doi: 10.1016/j.lfs.2018.04.049. PubMed PMID: 29715470. Bischoff-Ferrari HA, Vellas B, Rizzoli R, Kressig RW, da Silva JAP, Blauth M, et al. Effect of Vitamin D Supplementation, Omega-3 Fatty Acid Supplementation, or a Strength-Training Exercise Program on Clinical Outcomes in Older Adults: The DO-HEALTH Randomized Clinical Trial. JAMA. 2020;324(18):1855-68. doi: 10.1001/jama.2020.16909. PubMed PMID: 33170239; PubMed Central PMCID: PMCPMC7656284. Gao J, Xie C, Yang J, Tian C, Zhang M, Lu Z, et al. The Effects of n-3 PUFA Supplementation on Bone Metabolism Markers and Body Bone Mineral Density in Adults: A Systematic Review and Meta-Analysis of RCTs. Nutrients. 2023;15(12). Epub 20230619. doi: 10.3390/nu15122806. PubMed PMID: 37375709; PubMed Central PMCID: PMCPMC10303698. Wang ZG, Fang ZB, Xie XL. Association between fatty acids intake and bone mineral density in adolescents aged 12-19: NHANES 2011-2018. Front Endocrinol (Lausanne). 2024;15:1402937. Epub 20240709. doi: 10.3389/fendo.2024.1402937. PubMed PMID: 39045274; PubMed Central PMCID: PMCPMC11263022. Miles EA, Banerjee T, Calder PC. 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Capacity of omega-3 fatty acids or eicosapentaenoic acid to counteract weightlessness-induced bone loss by inhibiting NF-kappaB activation: from cells to bed rest to astronauts. J Bone Miner Res. 2010;25(5):1049-57. doi: 10.1359/jbmr.091041. PubMed PMID: 19874203. Wang Z, Wu J, Li L, Wang K, Wu X, Chen H, et al. Eicosapentaenoic acid supplementation modulates the osteoblast/osteoclast balance in inflammatory environments and protects against estrogen deficiency-induced bone loss in mice. Clin Nutr. 2023;42(9):1715-27. Epub 20230728. doi: 10.1016/j.clnu.2023.07.022. PubMed PMID: 37542949. Saito Y, Nakamura K, Ito H. Effects of Eicosapentaenoic Acid on Arterial Calcification. Int J Mol Sci. 2020;21(15). Epub 20200730. doi: 10.3390/ijms21155455. PubMed PMID: 32751754; PubMed Central PMCID: PMCPMC7432365. Cheng B, Wen Y, Yang X, Cheng S, Liu L, Chu X, et al. Gut microbiota is associated with bone mineral density : an observational and genome-wide environmental interaction analysis in the UK Biobank cohort. Bone Joint Res. 2021;10(11):734-41. Epub 2021/11/16. doi: 10.1302/2046-3758.1011.BJR-2021-0181.R1. PubMed PMID: 34779240; PubMed Central PMCID: PMCPMC8636179. Additional Declarations There is NO Competing Interest. Supplementary Files Supplementary20241218.xlsx Supplenmentary table Supplenmentaryfigure20241218.docx Supplenmentary figure Cite Share Download PDF Status: Published Journal Publication published 28 Nov, 2025 Read the published version in Nature Communications → Version 1 posted 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-6281295","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":435528289,"identity":"405d7873-89c0-4963-acd4-dff76cac8387","order_by":0,"name":"Hou-Feng Zheng","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-5681-8598","institution":"The Second Affiliated Hospital of Soochow University","correspondingAuthor":true,"prefix":"","firstName":"Hou-Feng","middleName":"","lastName":"Zheng","suffix":""},{"id":435528290,"identity":"02e2c2de-4076-412a-813a-a001c7592c6a","order_by":1,"name":"Peng-Lin Guan","email":"","orcid":"","institution":"Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Peng-Lin","middleName":"","lastName":"Guan","suffix":""},{"id":435528291,"identity":"592ce9ea-6ad6-44e6-bc63-43c6725d3d56","order_by":2,"name":"Cheng-Da Yuan","email":"","orcid":"","institution":"Hangzhou Hospital of Traditional Chinese Medicine","correspondingAuthor":false,"prefix":"","firstName":"Cheng-Da","middleName":"","lastName":"Yuan","suffix":""},{"id":435528292,"identity":"2792f4c5-b819-42b7-aaae-d3d36622cad1","order_by":3,"name":"Guangfei Li","email":"","orcid":"","institution":"Second Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Guangfei","middleName":"","lastName":"Li","suffix":""},{"id":435528293,"identity":"79f03388-44a7-4d03-92ae-debcac29526d","order_by":4,"name":"Ming-Yu Han","email":"","orcid":"","institution":"Institute for immunity, Transplantation and Infection, Stanford Medicine, Stanford University","correspondingAuthor":false,"prefix":"","firstName":"Ming-Yu","middleName":"","lastName":"Han","suffix":""},{"id":435528294,"identity":"22221b3f-8da9-4be3-a4f5-327d635108ec","order_by":5,"name":"Chun-Fu Yu","email":"","orcid":"","institution":"Shangrao Municipal Hospital","correspondingAuthor":false,"prefix":"","firstName":"Chun-Fu","middleName":"","lastName":"Yu","suffix":""},{"id":435528295,"identity":"d8379cd3-e1ee-499f-8208-d25ec2d2e432","order_by":6,"name":"Pianpian Zhao","email":"","orcid":"https://orcid.org/0009-0009-1676-1748","institution":"Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Pianpian","middleName":"","lastName":"Zhao","suffix":""},{"id":435528296,"identity":"7c7b7fcc-f552-4654-82d6-9844efba27c1","order_by":7,"name":"Yu Qian","email":"","orcid":"","institution":"Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Yu","middleName":"","lastName":"Qian","suffix":""},{"id":435528297,"identity":"1bf16262-9337-461b-9523-bc0bebdc5790","order_by":8,"name":"Jiangwei Xia","email":"","orcid":"","institution":"Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Jiangwei","middleName":"","lastName":"Xia","suffix":""},{"id":435528298,"identity":"02e3379e-7563-4113-9724-e6929787b0e1","order_by":9,"name":"Peng Wei","email":"","orcid":"","institution":"Center for Health and Data Science (CHDS), the Second Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Peng","middleName":"","lastName":"Wei","suffix":""},{"id":435528299,"identity":"263484f8-a466-4845-a33e-e0b9ebe276c0","order_by":10,"name":"Cai-Rui Liu","email":"","orcid":"","institution":"Center for Health and Data Science (CHDS), the Second Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Cai-Rui","middleName":"","lastName":"Liu","suffix":""},{"id":435528300,"identity":"0fcd413e-765e-4334-8fd1-86584dfb8e36","order_by":11,"name":"Mengyuan Yang","email":"","orcid":"","institution":"Westlake University","correspondingAuthor":false,"prefix":"","firstName":"Mengyuan","middleName":"","lastName":"Yang","suffix":""},{"id":435528301,"identity":"83449294-eeba-4fb2-a994-40b1e570b8c3","order_by":12,"name":"Wei Xu","email":"","orcid":"","institution":"Center for Health and Data Science (CHDS), the Second Affiliated Hospital of Soochow University","correspondingAuthor":false,"prefix":"","firstName":"Wei","middleName":"","lastName":"Xu","suffix":""},{"id":435528302,"identity":"4d3734c0-3a91-45c4-822d-51e2db408304","order_by":13,"name":"Shu-Yang Xie","email":"","orcid":"https://orcid.org/0000-0002-8090-2180","institution":"Binzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shu-Yang","middleName":"","lastName":"Xie","suffix":""},{"id":435528303,"identity":"4a98e6e0-f561-4f08-9fa3-fb70342d3227","order_by":14,"name":"Ching Lung Cheung","email":"","orcid":"https://orcid.org/0000-0002-6233-9144","institution":"The University of Hong Kong","correspondingAuthor":false,"prefix":"","firstName":"Ching","middleName":"Lung","lastName":"Cheung","suffix":""},{"id":435528304,"identity":"dcf8826b-9d8d-4d59-8b08-7bd2ca391657","order_by":15,"name":"FuSheng Zhou","email":"","orcid":"https://orcid.org/0000-0003-4195-2801","institution":"Department of Dermatology, the First Affiliated Hospital, Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"FuSheng","middleName":"","lastName":"Zhou","suffix":""},{"id":435528305,"identity":"68eec333-680a-4c64-a3f8-4bfa2f04f923","order_by":16,"name":"Xiaoli Rong","email":"","orcid":"","institution":"The Johns Hopkins University School of Medicine","correspondingAuthor":false,"prefix":"","firstName":"Xiaoli","middleName":"","lastName":"Rong","suffix":""}],"badges":[],"createdAt":"2025-03-22 04:15:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6281295/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6281295/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41467-025-66881-8","type":"published","date":"2025-11-28T05:00:00+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":79678179,"identity":"df38b75a-b055-4b42-901c-054038841608","added_by":"auto","created_at":"2025-04-01 12:25:25","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":723239,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e. Step 1, 1,104 publicly available GWAS summary statistics for abundance of gut microbiota (GM) taxa were used from four studies published between January 2021 and February 2022, and most of the participants were of European ancestry. 97 unique GM taxa and the estimated by heel quantitative ultrasound BMD (eBMD) GWAS were selected for further analyses. \u0026nbsp;Step 2, exploring the horizontal pleiotropy genetic effect between 97 unique GM taxa and eBMD at three levels, [i] genome-wide (by estimating Pearson correlation between LD-independent SNP effects), [ii] SNPs level within LD-independent loci (using GWAS-PW), and [iii] gene-level (using the summary-based Mendelian randomization (SMR) method with the eQTL datasets). The causal influence of the candidate GM taxa on BMD was estimated by implementing Mendelian randomization analyses. Step 3, replicated previous analyses in discovery stage for validation test of horizontal and vertical pleiotropic association between candidate gut microbiota taxa and BMD. Step 4, the mediation analysis result showed the indirect effect between three gut taxa (\u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e; \u003cem\u003eBifidobacteriaceae\u003c/em\u003e and \u003cem\u003eBifidobacterium\u003c/em\u003e)and eBMD through stearidonate level.\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-6281295/v1/69789d859fca1e62e523eeff.png"},{"id":79676815,"identity":"d6148480-c70a-419c-9758-157c6a08a351","added_by":"auto","created_at":"2025-04-01 12:17:25","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":109667,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe proportion of selected GM taxa exhibiting significant polygenicity.\u003c/strong\u003e The bar graph presents the GM taxa with significant SNP-heritability polygenicity, relative to the proportion of GM taxa within each taxonomic classification level.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-6281295/v1/c0ca1eee0c708048bff7e079.png"},{"id":79676824,"identity":"7f3d7d65-05b0-452e-87e0-8a684f3967e8","added_by":"auto","created_at":"2025-04-01 12:17:25","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":2617303,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe pleiotropic effects result between the GM taxa and eBMD.\u003c/strong\u003e \u003cstrong\u003eA\u003c/strong\u003e. The volcano plot of pearson correlation results between the SNP Z-scores from the eBMD GWASs and gut microbiota taxa GWASs. The gut microbiota taxa with P values after FDR correction ≤ 0.1 are shown in red. \u0026nbsp;\u003cstrong\u003eB, C, D.\u003c/strong\u003e Locuszoom plots of UK Biobank bone mineral density as estimated by heel quantitative ultrasound (eBMD) GWAS for three pleiotropic loci that affect BMD and multiple proteins via shared SNPs are shown on left. Association effect sizes and their 95% confidence intervals of the shared SNP in each locus for BMD and identified gut microbiota are shown on right. Unadjusted\u0026nbsp;\u003cem\u003eP\u003c/em\u003e-values for the associations from the eBMD and gut microbiota abundance GWASs are shown in red (\u003cem\u003eP\u003c/em\u003e \u0026lt; 5 × 10\u003csup\u003e–8\u003c/sup\u003e), blue (\u003cem\u003eP\u003c/em\u003e \u0026lt; 1 × 10\u003csup\u003e–5\u003c/sup\u003e) and black (\u003cem\u003eP\u003c/em\u003e \u0026lt; 1 × 10\u003csup\u003e–3\u003c/sup\u003e)\u003cstrong\u003e. B\u003c/strong\u003e\u0026nbsp;Chromosome 2 135.1-137.1 Mb affects eBMD and 7 gut microbiota taxa via rs2090660 (position, 2:136818719; effect allele, T).\u0026nbsp;\u003cstrong\u003eC\u003c/strong\u003e\u0026nbsp;Chromosome 9 135.3–137 Mb affects eBMD and 2 gut microbiota taxa via rs635634 (position, 9:136155000; effect allele, G).\u0026nbsp;\u003cstrong\u003eD\u003c/strong\u003e\u0026nbsp;Chromosome 12 0.17-1.08 Mb affects eBMD and 2 gut microbiota taxa via rs215226 (position, 12:591300; effect allele, T). \u003cstrong\u003eE. \u003c/strong\u003eThe forest plot of summary-based Mendelian randomization (SMR) results for the expression level of the B4GALNT3 gene and its association with both gut taxa and eBMD.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-6281295/v1/50b0a3a1eb325737f6fe34cb.png"},{"id":79676813,"identity":"ba593a50-ceea-437f-8066-9ed027a4a744","added_by":"auto","created_at":"2025-04-01 12:17:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":174240,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eBlood stearidonate (18:4n3) mediates GM taxa effects on eBMD. A\u003c/strong\u003e. The forest plot of the MR analysis result for three gut taxa on eBMD including three methods (Inverse-variance weighted; weighted median and multivariable mendelian randomization with adjusting stearidonate). \u003cstrong\u003eB \u003c/strong\u003eThe forest plot of the MR analysis result for stearidonate on eBMD including four methods (Inverse-variance weighted and multivariable mendelian randomization with adjusting three gut taxon) \u003cstrong\u003eC\u003c/strong\u003e. The forest plot of the MR analysis result for three gut taxa on stearidonate including two methods (Inverse-variance weighted and weighted median).\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-6281295/v1/cdd67d5c2a0ee60ef6c193b6.png"},{"id":99212508,"identity":"db82d2b6-1940-4c1a-a26c-0d56826138a9","added_by":"auto","created_at":"2025-12-30 08:24:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4441756,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6281295/v1/d706192a-3898-4882-a15e-57b5ca106861.pdf"},{"id":79676818,"identity":"879f9a86-5469-4973-8fc2-1e92cbce20af","added_by":"auto","created_at":"2025-04-01 12:17:25","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":641796,"visible":true,"origin":"","legend":"Supplenmentary table","description":"","filename":"Supplementary20241218.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6281295/v1/1009be9c2fe06986984d46bf.xlsx"},{"id":79676817,"identity":"8607a07d-759a-4a1a-9c17-238b2f213b7b","added_by":"auto","created_at":"2025-04-01 12:17:25","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":354449,"visible":true,"origin":"","legend":"Supplenmentary figure","description":"","filename":"Supplenmentaryfigure20241218.docx","url":"https://assets-eu.researchsquare.com/files/rs-6281295/v1/720612fc2664e6e8b4d955f4.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Causal Gut Microbiota-Bone Links: Pleiotropic Effects and Stearidonate Mediation","fulltext":[{"header":"Introduction","content":"\u003cp\u003e Osteoporosis is a bone disease characterized by decreased bone mineral density (BMD) and the occurrence of bone microstructural damage. The evaluation of this condition is primarily measured using dual energy X-ray absorptiometry scans (DXA), with osteoporotic fractures serving as the main clinical outcome [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In the United States, over 2\u0026nbsp;million osteoporosis-related fractures occurred in 2005, resulting in a treatment cost of \u003cspan\u003e$\u003c/span\u003e17\u0026nbsp;billion [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. BMD, which has a high heritability estimate ranging from 50\u0026ndash;85% in family and twin studies, is recognized as a strong predictor of osteoporosis [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Over the past decade, genome-wide association studies (GWAS) have identified hundreds of genetic loci associated with BMD, osteoporosis, and osteoporotic fractures [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe host gut microbiota, a complex community of microbes inhabiting the gastrointestinal tract, has recently been recognized for its potential role in bone regulation [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Yan et al demonstrated that colonization of the gut microbiota in mice promotes skeletal growth and remodeling by stimulating the hormone insulin-like growth factor 1 (IGF-1), as compared to germ-free mice [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Li et al also found that gut microbiota could influence bone loss associated with sex steroid deficiency in mice [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Certain microbiota taxa, such as \u003cem\u003eBifidobacterium longum\u003c/em\u003e, were shown to affect mineral absorption, including calcium, magnesium, and phosphate [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and may also play a crucial role in synthesizing vitamins B and K [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Furthermore, gut microbiota has been implicated in regulating bone overgrowth [\u003cspan additionalcitationids=\"CR12\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and modulating serotonin synthesis, whose receptors are found in both osteoblasts and osteocytes in the nervous system [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Studies have also shown that gut microbiota may influence bone development by altering levels of metabolic hormones and calcium absorption [\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]; producing short-chain fatty acids (such as butyrate) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], and affecting peptide like glucagon-like peptide 1 which are related to bone metabolism [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious studies have explored the relationship between gut microbiota and BMD using the Mendelian randomization approaches [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. However, these studies primarily examined bacterial taxa at a broader taxonomic level, such as order or family, rather than at a more specific level like genus. The summary datasets were derived from the TwinsUK GWAS for gut microbiota [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. It should be noted that the sample sizes in microbiota GWAS were relatively small, and only significant SNPs were used in subsequent analyses. The reliability of genetic associations depends heavily on the selection of instrumental variables, which requires large-scale GWAS summary data that offer robust SNP-trait associations [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this analysis, we incorporated 1,104 publicly available GWAS summary statistics for gut microbiota taxa, spanning five taxonomic levels from phylum to species. These data were derived from four recent studies. Notably, Qin et al. identified independent SNPs associated with gut taxonomies within a Finnish cohort [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Another study in a Dutch cohort confirmed these associations near the \u003cem\u003eLCT\u003c/em\u003e and \u003cem\u003eABO\u003c/em\u003e genes [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. A separate investigation in five German cohorts involving nearly 9,000 individuals also revealed a significant effect of host blood type genes on gut microbiota composition [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. These findings shed new light on the complex relationship between bacterial composition and host phenotypes, particularly in the context of host genetic expression. Finally, the MiBioGen consortium undertook a comprehensive analysis that integrated genome-wide genotyping and 16S fecal microbiome data from 18,340 individuals across 24 cohorts to further understand the relationship between host genetics and microbiota composition [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe inclusion of large publicly available genetic summary statistics on gut microbiota, featuring the largest sample size to date, has significantly enhanced our ability to investigate the complex relationship between gut microbiota and diseases. By leveraging these novel datasets during discovery and replication phases, we investigated the genetic influence of gut microbiota on BMD. This exploration was conducted through an assessment of the polygenic SNP heritability (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e) employing linkage disequilibrium score regression (LDSC) at three genetic levels including genome-wide, gene expression and LD-independent loci. Furthermore, we employed MR to evaluate the causal relationship (vertical pleiotropy) between bacterial taxa showing horizontal pleiotropic genetic effects on BMD traits. In sum, our results underscore the significant role of gut microbiota in bone development, supporting previous studies, and suggest that genetically predicted abundance of specific bacterial taxa may be associated with bone mass variation and influence BMD.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eGut microbiota taxa and bone traits GWAS summary statistics\u003c/p\u003e \u003cp\u003eWe collected GWAS summary statistics for 1,104 gut microbiota taxa abundance quantitative trait loci (mbQTLs) from four studies conducted between January 2021 and February 2022. [\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The majority of participants in these studies were of European ancestry. However, it should be noted that there are about 2900 individuals were included in both two meta-analyses [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The SNPs information from the human genome build 37 (hg19) was utilized to annotate the GWAS summary statistics, addressing missing rsIDs information.\u003c/p\u003e \u003cp\u003eFor BMD trait, we sourced GWAS summary data from the Genetic Factors for Osteoporosis (GEFOS) Consortium, a large-scale international collaboration involving multiple research groups (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.gefos.org\u003c/span\u003e\u003cspan address=\"http://www.gefos.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). This study included estimated heel quantitative ultrasound bone mineral density (eBMD) data from the UK Biobank collected in 2018 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The eBMD summary-statistic data was derived from the UK10K/1000G combined imputation panel (hg19) and included 14\u0026nbsp;million SNPs with a Minor Allele Frequency (MAF)\u0026thinsp;\u0026ge;\u0026thinsp;0.05%, involving up to 426,824 participants (\u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eEstimated SNP heritability and filtered gut microbiota taxa GWASs\u003c/p\u003e \u003cp\u003eWe calculated the polygenic SNP heritability (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e) of the 1104 GM taxa and eBMD GWAS datasets using linkage disequilibrium score regression software ((LDSC, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://data.broadinstitute.org/alkesgroup/LDSCORE\u003c/span\u003e\u003cspan address=\"https://data.broadinstitute.org/alkesgroup/LDSCORE\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. SNPs from approximately 1.2\u0026nbsp;million common SNPs in European populations from the HapMap3 reference panel (excluding the HLA region) were used. The LD scores of these SNPs referenced the European 1000 Genomes Project phase 3. To filter the GM taxa GWAS datasets, we defined filtering criteria based on the Z score of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e is \u0026gt;\u0026thinsp;1.64 (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{P}_{{h}_{SNP}^{2}}\\)\u003c/span\u003e\u003c/span\u003e\u0026lt;0.05; one-side). Additionally, we limited the GWAS datasets with\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e between 0 and 1 for further analysis in this study (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e \u0026gt; 1 and \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e \u0026lt; 0 is not meaningful).\u003c/p\u003e \u003cp\u003ePearson correlation for LD-independent SNPs between gut taxa and BMD\u003c/p\u003e \u003cp\u003eWe employed a genome-wide pleiotropy approach to estimate overall concordant or discordant genetic effects, following the approach used by Nyholt et al [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. The Z scores of the LD-independent SNPs derived from GM taxa and eBMD were used to calculate the Pearson correlation (\u003cem\u003er\u003c/em\u003e) for trait pairs, including 97 unique GM taxa and eBMD. We retained independent SNPs shared between the gut taxon and eBMD. These SNPs were then used for the subsequent Pearson correlation analysis. To identify LD-independent SNPs, we employed the P-value-informed LD-clumping method using PLINK 1.9 software with --clump-kb 10000, --clump-p1 0.05, --clump-r2 0.1 flags, along with the European 1000 Genome Project reference panel for each gut taxon GWAS. The Pearson correlation coefficients were computed after ensuring the harmonization of the effect alleles among these independent SNPs between the gut taxon and BMD traits. To address the multiple testing problem, we applied False Discovery Rate (FDR) correction (Benjamini-Hochberg method) to adjust P-values for four different studies and each gut microbiome level separately.\u003c/p\u003e \u003cp\u003ePairwise GWAS analysis for LD-independent loci between gut taxa and BMD\u003c/p\u003e \u003cp\u003eWe performed the pairwise GWAS (GWAS-PW) analysis [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] involving the GM taxa GWASs and eBMD. The goal was to identify shared genetic variants affecting both gut taxon GWAS and eBMD within any of the 1,703 LD-independent regions (GRCh37) [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. For each of the 1,703 loci, we calculated four posterior probabilities (PPA) using Bayesian analysis via GWAS-PW software: PPA1: The probability of containing a genetic variant which was only associated to BMD; PPA2: The probability of containing a genetic variant which was only associated to gut taxon; PPA3: The probability of sharing a genetic variant which was both associated to BMD and gut taxon; PPA4: The probability of containing two distinct associations which were associated to BMD and gut taxon respectively. When either PPA3 or PPA4 exceeded 0.9 for a locus, it was defined as a pleiotropic-associated locus. If a gut taxon had at least one pleiotropic-associated locus, it was identified as demonstrating horizontal pleiotropy with BMD at the genetic variant level.\u003c/p\u003e \u003cp\u003eSummary-based Mendelian randomization for gene expression level between gut taxa and BMD\u003c/p\u003e \u003cp\u003eTo identify genetic factors influencing gene expression, we obtained expression quantitative trait loci (eQTL) summary data from the eQTLGen consortium and Genotype-Tissue Expression (GTEx) consortium. We then employed summary-based Mendelian randomization (SMR) analyses [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. The eQTLGen consortium integrates 37 expression datasets, encompassing both array- and sequencing-based methodologies, derived from whole blood samples involving 31,684 individuals. This analysis includes\u0026thinsp;~\u0026thinsp;17,000 genes and nearly 11\u0026nbsp;million SNPs in cis-eQTL analyses. The GTEx consortium provided data from artery tibial tissue, based on version 7, involving 308 individuals, forming a vital component of this analysis.\u003c/p\u003e \u003cp\u003eThe SMR method used eQTL datasets and GWAS summary data to assess gene expression levels associated with bacterial taxa and BMD [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. In this process, we specifically selected cis-eQTL SNPs with a P-value\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e within the context of whole blood tissue, utilizing them as instrumental variables. Following the SMR linkage clumping protocol (--ld-upper-limit 0.9 --ld-lower-limit 0.05 --peqtl-heidi 1.57e-3 --heidi-min-m 3 --heidi-max-m 20 --cis-wind 2000), we identified associated genes using a Bonferroni corrected P-value threshold (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05/number of genes). We also conducted a heterogeneity test using the PHEIDI statistic, with a threshold of P\u0026thinsp;\u0026gt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eMendelian randomization analysis\u003c/p\u003e \u003cp\u003eWe evaluated the association between these instrumental variables and outcomes through two-sample MR analyses. GM taxa summary-statistic data and eBMD. To investigate the causality between GM taxa and bone health, we employed three complementary MR methods including inverse variance-weighted (IVW) test; MR-Egger and the weighted median method. IVW Test: The IVW test was prioritized for GM taxa screening results due to its increased power under specific conditions, where the intercept is set to zero in the linear regression between exposure and outcome effects [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. The MR-Egger Regression was utilized to examine directional (unbalanced) pleiotropy [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], adding an additional layer of analysis to test potential biases. The weighted Median Method was employed to enhance the robustness of the results, contributing to the overall reliability of the findings [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Together, these MR methods provide complementary insights into the causality between GM taxa and bone health.\u003c/p\u003e \u003cp\u003eTo investigate the causal relationship between gut taxa and metabolites, we selected GM taxa associated with eBMD in both discovery and replication stages for further MR analysis. We collected GWAS summary statistics for 453 metabolites in human blood from 7,824 adults in two European population studies [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. We performed two-sample MR analyses to explore whether metabolites could causally affect BMD.\u003c/p\u003e \u003cp\u003eFor each outcome trait, we selected instrumental variants with a significance level at P\u0026thinsp;\u0026lt;\u0026thinsp;=\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e for the MR analysis. In cases where two significant SNPs within a distance of 500 kb had a linkage disequilibrium score (r\u003csup\u003e2\u003c/sup\u003e) greater than 0.1, we selected the independent SNP with the most statistically significant association, as indicated by the lowest p-value. If a GM taxon contained only one instrumental variable (IV), we used the Wald ratio test to estimate the causal effect, as an alternative to the Inverse Variance-Weighted (IVW) test. All analyses, including sensitivity and MR analyses, were conducted in R version 4.0.3, using the R package \"MendelianRandomization.\"\u003c/p\u003e \u003cp\u003eMultivariable Mendelian randomization analysis\u003c/p\u003e \u003cp\u003eWe then conducted multivariable MR analyses to determine the mediation effect of specific metabolite on the relationship between the GM taxon and eBMD[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The specific metabolite was found to be potentially causally affected by the GM taxon and were also identified as factors that could affect eBMD in MR analysis (IVW-P\u0026thinsp;\u0026lt;\u0026thinsp;0.05/N; N, the number of all GM taxa). Specifically, we began by extracting the genetic association estimates of instrumental variables for both the gut taxon and the metabolite. Subsequently, we estimated the effect of the GM taxon on the specific metabolite (β\u003csub\u003e1\u003c/sub\u003e) based on generalized IVW method. We then estimated the effect of the metabolite on eBMD while adjusting for the effects of the gut taxon (β\u003csub\u003e2\u003c/sub\u003e). Additionally, we estimated the effect of the gut taxon on eBMD with adjustment for the metabolite, employing the multivariable MR approach. In this analysis, genetic instrumental variables for each of the exposure [i.e., genetic instrumental variables for 1st exposure: the specific GM taxon, and genetic instrumental variables for 2nd exposure: all independent genome-wide significant genetic variants for the specific metabolite (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and \u003cem\u003eP\u003c/em\u003e-value\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e)] are used together with the corresponding association of SNPs with each exposure and outcome (eBMD). The indirect mediation effect of the GM taxon on eBMD was estimated by β\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;\u0026times;\u0026thinsp;β\u003csub\u003e2\u003c/sub\u003e. Therefore, the proportion of the total effect mediated by each cardiometabolic factor can be estimated by dividing the indirect effect of the exposure (i.e., β\u003csub\u003e1\u003c/sub\u003e\u0026thinsp;\u0026times;\u0026thinsp;β\u003csub\u003e2\u003c/sub\u003e) by the total effect (i.e., univariable MR of the GM taxon on eBMD) [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThe selection of heritable GM taxa\u003c/p\u003e \u003cp\u003eAn overview of the study design was depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. A total of 1104 GM taxa GWAS summary data were obtained from four recent studies [\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e], and the studies encompassed a sample size ranging from 5959 to 18340 participants (\u003cb\u003eSupplementary Table\u0026nbsp;1\u003c/b\u003e). We first estimated the SNP heritability (h\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eSNP\u003c/sub\u003e) for all GM taxa using linkage disequilibrium score regression method (LDSC), and found that most of the GM taxa showed low heritability, with the gut taxon species \u003cem\u003eBifidobacterium catenulatum\u003c/em\u003e exhibiting the highest SNP-based heritability (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e = 0.9845) (\u003cb\u003eSupplementary Table\u0026nbsp;2\u003c/b\u003e). The Z scores of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e in all GM taxa exhibited a significant pearson correlation both with the number of SNPs in GWASs (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.112, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000185) and the number of sample size (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.116, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.00011) (\u003cb\u003eSupplementary Fig.\u0026nbsp;1\u003c/b\u003e). This implies that the heritability of gut taxa could be attributed to genome-wide polygenicity and larger participant numbers in GM GWAS. To filter the heritable GM taxa, we selected 108 GM taxa which possessed a Z score of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e great than 1.64 (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{P}_{{h}_{SNP}^{2}}\\)\u003c/span\u003e\u003c/span\u003e\u0026lt;0.05; one-side), accounting for approximately 9.78% of the total (108/1104) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). These selected GM taxa exhibited significant polygenicity, and their SNP-based heritability values were both statistically significant and meaningful (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e \u0026ge; 0.0445). Among the 1104 GM taxa GWASs, the gut taxon species \u003cem\u003eBifidobacterium catenulatum\u003c/em\u003e exhibited the highest SNP-based heritability (\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e = 0.9845). Additionally, when there were multiple datasets for a single gut taxon, we opted for the one with the higher Z score of \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e for subsequent analyses.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs a result, we ultimately selected 97 unique GM taxa summary data for further analysis (\u003cb\u003eSupplementary Table\u0026nbsp;3\u003c/b\u003e). The name of included gut taxon for further analysis was reported by the lowest bacteria taxa level name for consistency. The estimated median \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e of those 97 unique GM taxa from the four studies distributed from 0.072 to 0.1735 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These taxa are categorized into 1 phylum, 4 classes, 4 orders, 11 families, 33 genera, and 44 species (\u003cb\u003eSupplementary Fig.\u0026nbsp;2\u003c/b\u003e). Additionally, we observed that eBMD GWAS exhibited a Z score for \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e of 14.96 (\u003cb\u003eSupplementary Table\u0026nbsp;3\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eGenome-wide pleiotropic association between GM taxa and BMD\u003c/p\u003e \u003cp\u003eWe employed an approach to estimate the similarity in SNP effects at the genome-wide level, similar to a previous study [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Specifically, we selected gut taxa that exhibited a concordant genetic effect across the entire genome (genome-wide pleiotropic) with BMD trait based on a significant correlation Z score of the LD-independent SNPs. The LD-independent SNPs from the eBMD GWAS were selected and matched with the 97 unique GM taxa GWASs, leaving us with a range of 31,712 to 58,953 SNPs for estimating genome-wide effect similarity. The pearson correlation coefficients (\u003cem\u003er\u003c/em\u003e) were calculated using the Z scores of those SNPs, which were harmonized by the effect allele. Further details of this analysis can be found in the Methods section. Among these results, two GM taxa displayed significant negative SNP effects correlations with eBMD at a false discovery rate (FDR) less than 0.1 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA), including \u003cem\u003eHaloplasmatales\u003c/em\u003e (\u003cem\u003er\u003c/em\u003e = -0.00896; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02965) and \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.0153; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0055) (\u003cb\u003eSupplementary Table\u0026nbsp;4\u003c/b\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003ePleiotropic SNPs and genes influencing association between GM taxa and BMD\u003c/p\u003e \u003cp\u003eUsing the pairwise GWAS (GWAS-PW) method, we have identified independent genetic loci which were associated with both BMD and GM taxa by a shared SNP. The independent loci with third posterior probability (PPA3)\u0026thinsp;\u0026ge;\u0026thinsp;0.9 was suggested the pleiotropic associated SNP between BMD and GM taxa in this analysis. In this study, we have identified five pleiotropic genetic loci that are jointly associated with estimated heel quantitative ultrasound bone mineral density (eBMD) and 13 distinct GM taxa, all through the influence of shared Single Nucleotide Polymorphisms (SNPs) (\u003cb\u003eSupplementary Table\u0026nbsp;5\u003c/b\u003e). We assessed the proportion of pleiotropic LD-independent loci that influence both traits, BMD and gut taxon, via a shared SNP among all loci associated with gut taxon. This proportion exhibited a range from 0.5 to 1 (\u003cb\u003eSupplementary Table\u0026nbsp;5\u003c/b\u003e). Among the identified pleiotropic loci influencing both estimated heel quantitative ultrasound bone mineral density (eBMD) and seven GM taxa, two specific GM taxa stand out: the order \u003cem\u003eBifidobacteriales\u003c/em\u003e (comprising \u003cem\u003eBifidobacterium pseudocatenulatum\u003c/em\u003e and \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e) and the phylum Bacillota (consisting of \u003cem\u003eNegativibacillus sp000435195\u003c/em\u003e and \u003cem\u003eTuricibacter\u003c/em\u003e). These loci are located was on chromosome 2 135.1-137.1 Mb, with the lead SNP rs2090660 positioned near the CXCR4 gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB). Additionally, we uncovered two pleiotropic loci associated with eBMD and two gut taxa, \u003cem\u003eFaecalicatena torques\u003c/em\u003e and \u003cem\u003eFaecalibacterium\u003c/em\u003e, situated on chromosome 9 135.3\u0026ndash;137 Mb with the lead SNP rs635634 near the ABO gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Furthermore, the association extends to \u003cem\u003eClostridiales bacterium CHKCI006 sp900018345\u003c/em\u003e and \u003cem\u003eMerdibacter massiliensis\u003c/em\u003e at chromosome 12 0.17\u0026ndash;1.08 Mb, with the lead SNP rs215226 located within the B4GALNT3 gene (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003eInterestingly, SMR analysis result uncovered a significant association between the expression level of the \u003cem\u003eB4GALNT3\u003c/em\u003e gene and eBMD (P\u003csub\u003esmr\u003c/sub\u003e = 8.011\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;07\u003c/sup\u003e). The GM species \u003cem\u003eClostridiales bacterium CHKCI006 sp900018345\u003c/em\u003e (P\u003csub\u003esmr\u003c/sub\u003e = 5.324\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;07\u003c/sup\u003e) and \u003cem\u003eMerdibacter massiliensis\u003c/em\u003e (P\u003csub\u003esmr\u003c/sub\u003e = 5.321\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;07\u003c/sup\u003e) were also found to be significantly associated with the expression level of the \u003cem\u003eB4GALNT3\u003c/em\u003e gene in artery tibial tissue (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). This further confirms the results obtained from the GWAS-PW analysis. The expression level of the ABO gene was also found to be associated with the GM taxon Faecalicatena torques, as determined through the integration of the eQTL dataset. This finding corroborates the results obtained from the GWAS-PW analysis. Additionally, we identified significant associations between the expression of the LCT and MCM6 genes and multiple GM taxa, in both artery tibial tissue and the eQTLgen dataset (\u003cb\u003eSupplementary Table\u0026nbsp;6\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eCandidate GM taxa with a causal effect on BMD\u003c/p\u003e \u003cp\u003eOur cross-trait analyses identified several gut microbiota (GM) taxa that exhibited pleiotropy with bone mineral density (BMD) at multiple levels, including genome-wide, single nucleotide polymorphism (SNP), and gene expression levels. These GM taxa were selected for further analysis as candidate gut taxa. In total, we identified 14 GM taxa out of 97 unique GM taxa that exhibited horizontal pleiotropic effects on BMD. To further investigate the causal relationships, we employed Mendelian randomization (MR) analysis, using the inverse variance-weighted (IVW) method to estimate the causal relationship (vertical pleiotropic association). Additionally, we utilized the weighted median method to enhance the robustness of our results and the MR-Egger regression method to assess directional (unbalanced) pleiotropy. The detailed information of the MR analysis is presented in the Methods section.\u003c/p\u003e \u003cp\u003eIn this study, we have identified the 11 specific GM taxa abundances with a causal relationship with eBMD, including \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e = -0.03142, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.585 x 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e); \u003cem\u003eBifidobacterium pseudocatenulatum\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e = -0.02584, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.00301); \u003cem\u003eBifidobacteriales\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e = -0.02922, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000981); \u003cem\u003eBifidobacteriaceae\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e = -0.02921, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000981); \u003cem\u003eBifidobacterium\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e = -0.02921, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.000981); \u003cem\u003eClostridiales CHKCI006 sp900018345\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.4172, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.317 x 10\u003csup\u003e\u0026minus;\u0026thinsp;31\u003c/sup\u003e); \u003cem\u003eMerdibacter massiliensis\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.3241, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.036 x 10\u003csup\u003e\u0026minus;\u0026thinsp;20\u003c/sup\u003e); \u003cem\u003eNegativibacillus sp000435195\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0542, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.944 x 10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e); \u003cem\u003eTuricibacter\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.3241, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.036 x 10\u003csup\u003e\u0026minus;\u0026thinsp;20\u003c/sup\u003e); \u003cem\u003eFaecalibacterium\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e = -0.1692, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.305 x 10\u003csup\u003e\u0026minus;\u0026thinsp;19\u003c/sup\u003e); \u003cem\u003eHaloplasmatales\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.04885, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.00138) (\u003cb\u003eSupplementary Table\u0026nbsp;7\u003c/b\u003e). Notably, we excluded candidate bacteria lacking the SNPs required for instrumental variables in the MR analysis (P\u0026thinsp;\u0026lt;\u0026thinsp;5 \u0026times; 10^-8) in the further analysis.\u003c/p\u003e \u003cp\u003eThe specific gut microbiota taxon associated with eBMD in replication sample\u003c/p\u003e \u003cp\u003eFurthermore, we verified the association between specific GM taxa and BMD, accounting for both vertical and horizontal pleiotropy, in the replication sample using publicly available GM abundance GWAS summary statistics from four recent studies. Additionally, we restricted the inclusion of GM GWASs in the replication sample to those with \u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:{h}_{SNP}^{2}\\)\u003c/span\u003e\u003c/span\u003e values between 0 and 1. This study aimed to replicate the associations between five GM taxa (\u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e, \u003cem\u003eBifidobacteriales\u003c/em\u003e, \u003cem\u003eBifidobacteriaceae\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eFaecalibacterium\u003c/em\u003e) and BMD in the replication sample.\u003c/p\u003e \u003cp\u003eSignificantly, our MR analysis indicated that the abundance of the GM taxa family \u003cem\u003eBifidobacteriaceae\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.021512, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0221) and its child taxa, including the genus \u003cem\u003eBifidobacterium\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e = -0.0194, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01543) and the species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.0174, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0082), was causally associated with a decrease in eBMD in replication sample. Importantly, this association was observed in both the discovery and replication samples, enhancing the reliability of this finding. Additionally, our GWAS-PW analysis revealed that specific loci on chromosome 2 135.1-137.1 Mb with lead SNP rs2090660 near CXCR4 gene exhibited horizontal pleiotropy, influencing both eBMD and these GM taxa. This pleiotropic effect was consistent in both the discovery and replication samples, further supporting the robustness of this association (\u003cb\u003eTable\u0026nbsp;2\u003c/b\u003e).\u003c/p\u003e \u003cp\u003eThe Mediation analysis result between the specific gut microbiota taxon on BMD through the metabolite\u003c/p\u003e \u003cp\u003eHere, we conducted Multivariable Mendelian randomization analysis to investigate how the species Bifidobacterium adolescentis may influence eBMD through metabolites. Initially, we identified 41 metabolites that could be causally affected by the species Bifidobacterium adolescentis, with a Bonferroni-corrected p-value from IVW analysis\u0026thinsp;\u0026lt;\u0026thinsp;0.05 (i.e., \u003cem\u003eP\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e \u0026lt;0.05/453) (\u003cb\u003eSupplementary Table\u0026nbsp;8\u003c/b\u003e). Subsequently, we performed a two-sample MR analysis between those metabolites w that were causally associated with the species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e and eBMD. We found the stearidonate (18:4n3) were causal associated with eBMD (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e = -0.3924, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.808e-12) at significant level (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05/43) (\u003cb\u003eSupplementary Table\u0026nbsp;9\u003c/b\u003e). The species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e was causally associated with an increase in blood stearidonate level (\u003cem\u003eβ\u003c/em\u003e\u003csub\u003eIVW\u003c/sub\u003e\u0026thinsp;=\u0026thinsp;0.0621, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.92e-05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eC). Based on the multivariable MR analysis, we observed that the direct effect of the species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e on eBMD disappeared after adjusting stearidonate (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Moreover, stearidonate (18:4n3) showed a negative causal association with eBMD after adjusting the species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB). Mediation analysis showed the indirect effect of the species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e on eBMD through stearidonate was \u0026minus;\u0026thinsp;0.02432 (95% CI: -0.038, -0.0106), with a mediation proportion of 77.41% (\u003cb\u003eTable\u0026nbsp;3\u003c/b\u003e). Also, we found the similarity results for the family \u003cem\u003eBifidobacteriaceae\u003c/em\u003e and genus \u003cem\u003eBifidobacterium\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; \u003cb\u003eTable\u0026nbsp;3\u003c/b\u003e). The overall Mendelian Randomization results between the family \u003cem\u003eBifidobacteriaceae\u003c/em\u003e or genus \u003cem\u003eBifidobacterium\u003c/em\u003e and 453 metabolites were also listed in Supplementary Table\u0026nbsp;8.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe gut microbiota is a complex group colonized in the human gut, in adults, the gut bacteria were mainly consisting of \u003cem\u003eBacteroidetes\u003c/em\u003e and \u003cem\u003eFirmicutes\u003c/em\u003e, whereas \u003cem\u003eActinobacteria\u003c/em\u003e and \u003cem\u003eProteobacteria\u003c/em\u003e were secondary components [45]. In our investigation, our primary objective was to delve into the genetic relationships, encompassing both vertical and horizontal pleiotropic associations, between bone mineral density (BMD) and the abundance of gut microbiota primarily inhabiting the human gastrointestinal tract. Furthermore, we sought to elucidate the influence of blood metabolites on the gut-bone pathway. In contrast, a previous study revealed that the majority of human gut microbiota taxa exhibited no significant associations with host genetics [46]. Hence, we opted to focus on gut taxa with a significant polygenicity, encompassing genome-wide association signals. The SNP-based heritability of these gut taxa, as estimated by LDSC, consistently met the criteria for statistical significance (\\(\\:{Z}_{{h}_{SNP}^{2}}\\)\u0026gt; 1.64) and biological relevance (0 \u0026lt; \\(\\:{h}_{SNP}^{2}\\) \u0026lt; 1). Consequently, we narrowed our analysis to 97 unique GM taxa from the original 1104, facilitating more precise genetic association investigations. To investigate the relationship between host genetic derived GM taxa abundance and BMD, our study provides evidence of both vertical and horizontal pleiotropic genetic associations between specific GM taxa and BMD. We identified the 14 candidate GM taxa had horizontal pleiotropic effects at three different levels of genome-wide, colocalization SNPs and gene expression level in 97 unique GM taxa. Furthermore, we have identified the causal effects of 11 specific GM taxa on eBMD through MR analysis. Specifically, the GM species Bifidobacterium adolescentis, along with its parent taxon family \u003cem\u003eBifidobacteriaceae\u003c/em\u003e and genus \u003cem\u003eBifidobacterium\u003c/em\u003e, exhibit both vertical and horizontal pleiotropic genetic associations with eBMD in both the discovery and replication samples. Lastly, we identified the mediator effect on these three gut taxa on eBMD through the stearidonate (18:4n3) level in blood.\u003c/p\u003e\n\u003cp\u003eThe heritability results for the 1104 GM taxa indicate that including a larger number of individuals and employing deeper sequencing methods, such as metagenomics, can help identify more GM taxa with higher polygenicity in GM GWAS. Notably, the GM taxa demonstrated higher polygenicity compared to the blood proteome in the previous study [33]. The significant association between the SNP heritability of the 1104 GM taxa and the number of included SNPs suggests that the heritability of gut taxa can be attributed to genome-wide polygenicity and is enhanced by larger participant numbers in GM GWAS. Our results suggest that certain GM taxa exhibit relatively high heritability, even though environmental factors also play a significant role in shaping the human GM.\u003c/p\u003e\n\u003cp\u003eOur multiple horizontal pleiotropies genetically association results revealed 11 unique GM taxa associated with eBMD. Significantly, the GM taxon \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e exhibited two lines of evidence for horizontal pleiotropy with eBMD, at both the genome-wide and SNP level. Additionally, GM taxon \u003cem\u003eClostridiales bacterium CHKCI006 sp900018345\u003c/em\u003e and \u003cem\u003eMerdibacter massiliensis\u003c/em\u003e showed horizontal pleiotropy with eBMD at genome-wide and gene expression levels. Pleiotropy at the genome-wide level provides the direction of the relationship between GM taxa and BMD, contingent upon the presence of sufficient polygenic signals and consistent SNP effect directions. Nevertheless, pleiotropy at gene expression and SNP levels furnishes evidence of shared genetic signals evidences between GM taxa and BMD, although it does not provide information about the direction of the relationships. Therefore, horizontal pleiotropy findings at these three levels complemented each other, identifying in 14 unique GM taxa with horizontal pleiotropic effects on eBMD. These 14 GM taxa are potential candidates associated with BMD and were subsequently subjected to further vertical pleiotropy analysis.\u003c/p\u003e\n\u003cp\u003eRegarding these candidate GM taxa, we conducted MR analyses to unveil their potential causal links with eBMD. Our study identified several GM taxa with significant genetic causality in relation to eBMD. Specifically, we discovered that a group of GM taxa belonging to the order \u003cem\u003eBifidobacteriales\u003c/em\u003e (\u003cem\u003eBifidobacterium pseudocatenulatum\u003c/em\u003e, \u003cem\u003eBifidobacteriales\u003c/em\u003e, \u003cem\u003eBifidobacteriaceae\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e) exhibited both the horizontal and vertical pleiotropy association with eBMD, implying their potential impact on lower BMD levels. This finding suggests that these GM taxa could play a role in the regulation of bone mass variation and influence bone development.\u003c/p\u003e\n\u003cp\u003eWe also noted that \u003cem\u003eClostridiales bacterium CHKCI006 sp900018345\u003c/em\u003e, which was the sub-category of the order \u003cem\u003eClostridiales\u003c/em\u003e, had a causal effect on higher eBMD, demonstrating both horizontal and vertical pleiotropic associations, as reported in previous studies [21, 47, 48]. The genus \u003cem\u003eTuricibacter\u003c/em\u003e exhibited horizontal and vertical pleiotropy associations with eBMD, potentially contributing to increased BMD as indicated in our results, and this finding was substantiated by mouse experiments [49].\u003c/p\u003e\n\u003cp\u003eMoreover, the several GM taxa in family \u003cem\u003eOscillospiraceae\u003c/em\u003e (\u003cem\u003eFaecalibacterium\u003c/em\u003e, \u003cem\u003eFaecalibacterium sp. UBA7177 sp002491225\u003c/em\u003e) was found associated with BMD with both horizontal and vertical pleiotropic associations. Prior research has shown that \u003cem\u003eOscillospiraceae\u003c/em\u003e is capable of producing butyrate, a type of short-chain fatty acid (SCFA) [49]. SCFA has been associated with the inhibition of osteoclast differentiation and bone resorption, both in vitro and in vivo. Compounds like propionate and butyrate are recognized as potent regulators of osteoclast metabolism and bone health [19]. Xu et al. also observed an enrichment of the genus \u003cem\u003eFaecalibacterium\u003c/em\u003e in primary osteoporosis patient group, indicating its potential involvement in bone metabolism [50]. Similarly, another study found associations between \u003cem\u003eClostridiaceae\u003c/em\u003e and \u003cem\u003eFaecalibacterium\u003c/em\u003e with bone metabolism [51]. In both GWAS-PW and SMR analysis, we identified that the gene \u003cem\u003eB4GALNT3\u003c/em\u003e is associated with both eBMD and two GM taxa (\u003cem\u003eClostridiales bacterium CHKCI006 sp900018345\u003c/em\u003e, \u003cem\u003eMerdibacter massiliensis\u003c/em\u003e). Notably, prior studies had already reported an association between gene \u003cem\u003eB4GALNT3\u003c/em\u003e and BMD [52, 53]. This suggests that the expression level of the B4GALNT3 gene could play a role in the pleiotropic association between these GM taxa and BMD. Intriguingly, we also observed that the expression level of gene \u003cem\u003eLCT\u003c/em\u003e and \u003cem\u003eMCM6\u003c/em\u003e were significant associated with a series of GM taxa in order \u003cem\u003eBifidobacteriales\u003c/em\u003e (\u003cem\u003eBifidobacteriaceae\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e, \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e). Additionally, the \u003cem\u003eABO\u003c/em\u003e gene was linked to species \u003cem\u003eFaecalicatena torques\u003c/em\u003e, as previously reported in extensive microbiota GWAS studies [27\u0026ndash;30, 54].\u003c/p\u003e\n\u003cp\u003eIn our study, our GWAS-PW and MR analyses consistently verified the vertical and horizontal pleiotropic genetic associations of three GM taxa (\u003cem\u003eBifidobacteriaceae, Bifidobacterium\u003c/em\u003e and \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e) with eBMD in both the discovery and replication samples from two independent cohorts. It\u0026apos;s worth noting that species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e is a sub-category of genus \u003cem\u003eBifidobacterium\u003c/em\u003e, and genus \u003cem\u003eBifidobacterium\u003c/em\u003e belongs to the family \u003cem\u003eBifidobacteriaceae\u003c/em\u003e. The abundance of the GM species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e was found to have a potential causal effect in decreasing BMD which contrasts with a previous study suggesting that \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e supplementation could strengthen skeletal protection following fractures [55]. Additionally, some strains of \u003cem\u003eBifidobacterium\u003c/em\u003e, when used as probiotics, have been shown to have beneficial effects on bone health, as indicated in a prior review [56]. It\u0026apos;s important to highlight that the negative causal association between \u003cem\u003eBifidobacteriaceae\u003c/em\u003e and BMD in our study contradicts findings from a previous observational study [57]. This discrepancy may be attributed to variations in sample sizes between the two studies.\u003c/p\u003e\n\u003cp\u003eNevertheless, it\u0026apos;s worth noting that the human gut microbiota generates a diverse array of molecules, and certain components from this microbial community enter the bloodstream, where they can significantly impact overall health [58]. In recent years, there has been some progress in the field of metabolomics research related to BMD [59]. To further investigate how the GM taxa affect BMD through blood metabolites, our mediation analysis revealed that species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e might potentially decrease BMD by elevating blood stearidonate levels. Even more noteworthy is the fact that the direct effect of the species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e on eBMD vanished when stearidonate was taken into account. This indicates that the impact of gut microbiota on bone density is likely linked to the metabolites it affects. In a separate cross-sectional study involving a Swedish cohort [58], an association was established between \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e and elevated stearidonate levels (Spearman\u0026apos;s rho\u0026thinsp;=\u0026thinsp;0.03; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0202). Similarly, we observed a consistent outcome in two other GM categories family \u003cem\u003eBifidobacteriaceae\u003c/em\u003e and genus \u003cem\u003eBifidobacterium\u003c/em\u003e, which also potentially impact bone density by elevating blood stearidonate levels.\u003c/p\u003e\n\u003cp\u003eStearidonate is one of the multiple omega-3 fatty acids. Animal experiments have demonstrated that omega-3 fatty acids made a complex effect in skeletal development [60]. Although omega-3 fatty acids are generally considered beneficial for bone health [61], a recent study found that omega-3 fatty acid supplementation had no impact on fractures [62]. However, a recent meta-analysis has indicated that supplemental omega-3 fatty acids significantly increased blood omega-3 levels but had no significant effects on bone mineral density (BMD)[63]. Another research showed that polyunsaturated fatty acids (PUFA) (including omega-3 fatty acids and omega-6 fatty acids) was significantly inversely correlated with both BMD[64]. Stearidonate and eicosapentaenoic acid (EPA) are important components of omega-3 polyunsaturated fatty acids. Dietary intake of stearidonate may serve as a precursor to enhance the EPA content in human lipids[65, 66]. EPA may generate resolvins to mitigate inflammation, which can otherwise lead to bone loss and pose significant risks to human health[67]. Additionally, EPA may inhibit NF-\u0026kappa;B to mitigate bone loss associated with spaceflight[68]. In animal experiments, high-dose EPA supplementation promotes osteoblastogenesis and upregulates the expression of osteoblast-specific proteins and genes[69]. Nevertheless, there is no direct evidence to demonstrate how stearidonate influences bone mineral density. We propose that elevated blood stearidonate levels may indicate a diminished capacity to synthesize EPA, potentially leading to a reduction in bone density, as reflected in the results of the Mendelian randomization analysis. Furthermore, stearidonate, which is efficiently metabolized into EPA, may inhibit arterial calcification via modulation of the Wnt signaling pathway, thereby potentially affecting osteoblast differentiation, osteogenesis and BMD [70]. Our research offers a fresh perspective on the gut microbiota-metabolite-bone axis within \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e (\u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eBifidobacteriaceae\u003c/em\u003e), indicating their role in regulating bone mass and influencing bone development through stearidonate. These findings should be further validated through additional animal experiments and observational studies.\u003c/p\u003e\n\u003cp\u003eRecently, Cheng et al. conducted a weighted genetic risk score (wGRS) analysis using the UK Biobank dataset and found a weak association between GM and pelvis BMD [22]. Additionally, they utilized a GM polygenic risk score to identify environmental interactions within the UKB dataset, revealing several genes that interact with GM and BMD [71]. Ni et al. conducted a two-sample MR analysis by integrating genetic data, and found that the order \u003cem\u003eClostridiales\u003c/em\u003e and family \u003cem\u003eLachnospiraceae\u003c/em\u003e were associated with bone development in both discovery and replication sample [21]. However, it is important to note that these studies had certain limitations. The gut microbiota GWAS they conducted were relatively limited, and only a few genetic instruments were included. Furthermore, they did not consider the horizontal pleiotropy, which is an important factor in the relationship between GM taxa and BMD. Therefore, we employed various cross-trait approaches at several levels to detect the potential pleiotropic effects. Unlike previous studies that mainly examined bacterial taxa at a higher taxonomic level, we investigated them at a more specialized level, including genus and species, to provide a more detailed understanding of their relationships with BMD. Our study performed different analyses to identify the potential association relationship between 1104 bacteria taxa from phylum to species level in four different GM GWAS studies, increasing the reliability of the relationship results. Moreover, we unveiled the critical role of metabolites in mediating the influence of GM on BMD.\u003c/p\u003e\n\u003cp\u003eHowever, it\u0026apos;s essential to acknowledge some limitations in our study. Firstly, the GM and BMD GWASs predominantly utilized data from European populations. Given the substantial variations in GM composition across populations with diverse ancestries, our findings may not be readily applicable to other ancestral groups. Secondly, the potential presence of sample overlaps between the two GM GWAS datasets used in our study might have a minor influence on our findings, which could, in turn, affect our conclusions. Thirdly, it\u0026apos;s important to note that our study specifically concentrated on the 8.8% (97 out of 1104) of GM taxa that exhibited a significant genome-wide heritability estimated via LDSC. Nevertheless, there may be other GM taxa that can influence host BMD without a clear genetic association, which were beyond the scope of our study. Fourthly, it\u0026apos;s worth noting that GM taxa typically impact host phenotypes through intricate networks of interactions between microbes and host genes, which weren\u0026apos;t directly examined in our study. Finally, some potential confounders such as environmental variables and protein could potentially influence the microbiome, which might influence our results. Indeed, observational studies and subsequent animal experiments are essential for validating the mechanisms by which metabolites are involved in the interplay between GM and BMD.\u003c/p\u003e\n\u003cp\u003eIn conclusion, our systematic investigation provided assess of pleiotropy relationship between BMD traits and 97 unique GM taxa with significant polygenic SNP heritability, implicates 14 unique GM taxa and eBMD by shared genetic effect, 11 of 14 unique GM taxa was found the causal association with eBMD. Specifically, three GM taxa including \u003cem\u003eBifidobacteriaceae\u003c/em\u003e, \u003cem\u003eBifidobacterium\u003c/em\u003e and \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003ewere found to have a causal effect on decreasing BMD due to both vertical and horizontal pleiotropic genetic influences, likely through the increase in blood stearidonate levels. Our study could be helpful to comprehend how gut microbiota can potentially regulate bone mass variation and impact bone development through the mediation of metabolites.\u003c/p\u003e\n\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSummary of polygenic SNP heritability for the 97 unique gut microbiota taxa GWASs (with a significant SNP heritability) analyzed in this study.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGWASs study\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNumber of GM taxa\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003esample size\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eh2SNP range\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eh2SNP SE range\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eh2SNP median\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eh2SNP SE median\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDutch\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7,738\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1024\u0026ndash;0.9845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0596\u0026ndash;0.3944\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1378\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0755\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFINRISK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5,959\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1252\u0026ndash;0.349\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0702\u0026ndash;0.1603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0811\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGerman\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8,956\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0875\u0026ndash;0.1213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0495\u0026ndash;0.0573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1131\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0535\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLarge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18,340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0445\u0026ndash;0.0942\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0223\u0026ndash;0.0481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0326\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"7\"\u003e\n \u003cp\u003eAbbreviation: GWASs study, article name for short ( FINRISK, Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort; Dutch, Effect of host genetics on the gut microbiome in 7,738 participants of the Dutch Microbiome Project; German, Genome-wide association study in 8,956 German individuals identifies influence of ABO histo-blood groups on gut microbiome; Large, Large-scale association analyses identify host factors influencing human gut microbiome composition); sample_size, reported sample size of each gut microbiota GWAS; h2SNP, SNP heritability, SE Standard error of SNP heritability.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cimg 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\"\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cdiv 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\"\u003e\u003c/div\u003e\n"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eWe thank the UK Biobank database, the GEnetic Factors for OSteoporosis (GEFOS) Consortium and Microbial composition. We also thank the Westlake University Supercomputer Center for the facility support and technical assistance.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Author contributions\u003c/p\u003e\n\u003cp\u003eH.-F.Z. conceptualized and designed the study. P.-L.G., Y.Q., C.-D.Y. and\u0026nbsp;Y.-H.F.\u0026nbsp;conducted the data analysis.\u0026nbsp;M.-Y.H., C.-F.Y., P.-P.Z., J.-W.X., P.W., C.-R.L.,\u0026nbsp;M.-Y.Y.,\u0026nbsp;W.X., and L.B.\u0026nbsp;contributed to the data collection, processing and preliminary data analysis. P.-L.G. drafted the manuscript, H.-F.Z. reviewed and edited manuscript. All authors contributed, discussed and approved manuscript.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Competing Interests\u003c/p\u003e\n\u003cp\u003eNone declared.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eZhu X, Zheng H. Factors influencing peak bone mass gain. Front Med. 2021;15(1):53-69. Epub 2020/06/11. doi: 10.1007/s11684-020-0748-y. 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PubMed PMID: 34779240; PubMed Central PMCID: PMCPMC8636179.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"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":"nature-portfolio","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"","title":"Nature Portfolio","twitterHandle":"","acdcEnabled":false,"dfaEnabled":false,"editorialSystem":"ejp","reportingPortfolio":"","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Gut microbiota, Bone mineral density, Causal relationship, Pleiotropic, Mendelian randomization, Bifidobacterium, Stearidonate","lastPublishedDoi":"10.21203/rs.3.rs-6281295/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6281295/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAccumulating evidence implicates gut microbiota play a pivotal role in influencing bone metabolism and contribute to the development of osteoporosis (OP). This study aimed to comprehensively investigate the pleiotropic effects between the gut microbiota taxa and bone density, with consideration of shared genetic factors, causal relationships, and the involvement of blood metabolites stearidonate in this complex interplay. We estimate the polygenic SNP heritability (h\u003csup\u003e2\u003c/sup\u003eSNP) for 1104 gut microbiota (GM) taxa GWASs, and identify 97 unique GM taxa with a significant polygenic heritability for further investigation. We identified 14 distinct GM taxa with horizontal pleiotropic effects on heel bone mineral density (eBMD), 11 of them were found to have a causal association with eBMD. GM taxa family \u003cem\u003eBifidobacteriaceae\u003c/em\u003e and its child taxa, genus \u003cem\u003eBifidobacterium\u003c/em\u003e and species \u003cem\u003eBifidobacterium adolescentis\u003c/em\u003e exert causal effects leading to decreased bone mineral density. The mediating effect of these three gut taxa on eBMD was traced back to their influence on blood stearidonate (18:4n3) levels. These findings enhance our understanding of stearidonate's role as a modifiable link in the multifaceted relationship between gut microbiota and bone health.\u003c/p\u003e","manuscriptTitle":"Causal Gut Microbiota-Bone Links: Pleiotropic Effects and Stearidonate Mediation","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-01 12:17:20","doi":"10.21203/rs.3.rs-6281295/v1","editorialEvents":[],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"nature-communications","isNatureJournal":true,"hasQc":false,"allowDirectSubmit":false,"externalIdentity":"NCOMMS","sideBox":"Learn more about [Nature Communications](http://www.nature.com/ncomms/)","snPcode":"","submissionUrl":"https://mts-ncomms.nature.com/","title":"Nature Communications","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"ejp","reportingPortfolio":"Nature Communications","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"40abd18e-8277-45cc-bbb0-af364fe2d6b3","owner":[],"postedDate":"April 1st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":46379446,"name":"Health sciences/Risk factors"},{"id":46379447,"name":"Biological sciences/Microbiology/Policy and public health in microbiology"}],"tags":[],"updatedAt":"2025-12-30T08:24:35+00:00","versionOfRecord":{"articleIdentity":"rs-6281295","link":"https://doi.org/10.1038/s41467-025-66881-8","journal":{"identity":"nature-communications","isVorOnly":false,"title":"Nature Communications"},"publishedOn":"2025-11-28 05:00:00","publishedOnDateReadable":"November 28th, 2025"},"versionCreatedAt":"2025-04-01 12:17:20","video":"","vorDoi":"10.1038/s41467-025-66881-8","vorDoiUrl":"https://doi.org/10.1038/s41467-025-66881-8","workflowStages":[]},"version":"v1","identity":"rs-6281295","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6281295","identity":"rs-6281295","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}