FOLLOWUS
1.Department of Orthopaedics, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei230031, China
2.Graduate School of Anhui University of Chinese Medicine, Hefei230012, China
3.Department of Geriatrics, The Third People's Hospital of Hefei, Hefei230041, China
4.Experimental Center of Clinical Research, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei230031, China
Received:07 March 2024,
Accepted:2024-08-22,
Published Online:14 September 2024,
Published:30 September 2024
Scan QR Code
.Dissecting Causal Relationships Between Plasma Metabolites and Osteoporosis: A Bidirectional Mendelian Randomization Study[J]. 中国医学科学杂志(英文),2024,39(03):182-188.
Lv Hao, Zhang Ge, Hu Zhi-Mu, et al. Dissecting Causal Relationships Between Plasma Metabolites and Osteoporosis: A Bidirectional Mendelian Randomization Study[J]. 中国医学科学杂志(英文);chinese medical sciences journal, 2024, 39(3): 182-188.
.Dissecting Causal Relationships Between Plasma Metabolites and Osteoporosis: A Bidirectional Mendelian Randomization Study[J]. 中国医学科学杂志(英文),2024,39(03):182-188. DOI: 10.24920/004356.
Lv Hao, Zhang Ge, Hu Zhi-Mu, et al. Dissecting Causal Relationships Between Plasma Metabolites and Osteoporosis: A Bidirectional Mendelian Randomization Study[J]. 中国医学科学杂志(英文);chinese medical sciences journal, 2024, 39(3): 182-188. DOI: 10.24920/004356.
目的
2
采用孟德尔随机化分析研究血浆代谢物与骨质疏松症之间的因果关系。
方法
2
采用双向孟德尔随机化方法分析不同全基因组关联研究的汇总数据
研究血浆代谢物与骨质疏松症之间的因果关系。首先
采用逆方差加权法评估血浆代谢物对骨质疏松症的因果效应
从而从不同来源的骨质疏松症相关全基因组关联研究汇总数据中获得具有统计学意义的代谢物交集
并对这些代谢物进行敏感性分析。接着
采用Cochran's Q检验评估单核苷酸多态性之间的异质性。最后
应用MR-Egger截距法和MR-PRESSO法评估水平多效性。同样采用逆方差加权法评估骨质疏松症对血浆代谢物的因果效应。此外
采用通路分析以确定参与骨质疏松症调节的潜在代谢通路。
结果
2
经过初步分析和敏感性分析
从GCST90038656和GCST90044600数据集的全基因组关联研究数据中
我们分别鉴别出77个和61个血浆代谢物与骨质疏松症有因果关系。通过交集确定了5个共同的代谢物。X-13684水平、葡萄糖与麦芽糖比值同骨质疏松症呈负相关
而甘氨脱氧胆酸水平、花生四烯酰肉碱(C20)水平与骨质疏松症呈正相关(P < 0.05)。X-11299水平与骨质疏松症的关系表现出矛盾的结果。通路分析表明:甘氨酸、丝氨酸和苏氨酸代谢
缬氨酸、亮氨酸和异亮氨酸生物合成
半乳糖代谢
精氨酸生物合成以及淀粉和蔗糖代谢通路参与了骨质疏松症的发展。
结论
2
我们发现血浆代谢物与骨质疏松症之间存在因果关系。这些结果为骨质疏松症治疗中针对代谢物的靶向干预提供了新的视角。
Objective
2
To investigate the causal relationships between plasma metabolites and osteoporosis
via
Mendelian randomization (MR) analysis.
Methods
2
Bidirectional MR was used to analyze pooled data from different genome-wide association studies (GWAS). The causal effect of plasma metabolites on osteoporosis was estimated using the inverse variance weighted method
intersections of statistically significant metabolites obtained from different sources of osteoporosis-related GWAS aggregated data was determined
and then sensitivity analysis was performed on these metabolites. Heterogeneity between single nucleotide polymorphisms was evaluated by Cochran's Q test. Horizontal pleiotropy was assessed through the application of the MR-Egger intercept method and the MR-PRESSO method. The causal effect of osteoporosis on plasma metabolites was also evaluated using the inverse variance weighted method. Additionally
pathway analysis was conducted to identify potential metabolic pathways involved in the regulation of osteoporosis.
Results
2
Primary analysis and sensitivity analysis showed that 77 and 61 plasma metabolites had a causal relationship with osteoporosis from the GWAS data in the GCST90038656 and GCST90044600 datasets
respectively. Five common metabolites were identified
via
intersection. X-13684 levels and the glucose-to-maltose ratio were negatively associated with osteoporosis
whereas glycoursodeoxycholate levels and arachidoylcarnitine (C20) levels were positively associated with osteoporosis (all
P
<
0.05). The relationship between
X-11299 levels and osteoporosis showed contradictory results (all
P
<
0.05). Pathway analysis indicated that glycine
serine
and threonine metabolism
valine
leucine
and isoleucine biosynthesis
galactose metabolism
arginine biosynthesis
and starch and sucrose metabolism pathways were participated in the development of osteoporosis.
Conclusion
2
We found a causal relationship between plasma metabolites and osteoporosis. These results offer novel perspectives with important implications for targeted metabolite-focused interventions in the management of osteoporosis.
Gopinath V . Osteoporosis . Med Clin N Am 2023 ; 107 ( 2 ): 213 - 25 . doi: 10.1016/j.mcna.2022.10.013 http://dx.doi.org/10.1016/j.mcna.2022.10.013 .
Trajanoska K , Rivadeneira F . The genetic architecture of osteoporosis and fracture risk . Bone 2019 ; 126 : 2 - 10 . doi: 10.1016/j.bone.2019.04.005 http://dx.doi.org/10.1016/j.bone.2019.04.005 .
Guijas C , Montenegro-Burke JR , Warth B , et al . Metabolomics activity screening for identifying metabolites that modulate phenotype . Nat Biotechnol 2018 ; 36 ( 4 ): 316 - 20 . doi: 10.1038/nbt.4101 http://dx.doi.org/10.1038/nbt.4101 .
Fan J , Jahed V , Klavins K . Metabolomics in bone research . Metabolites 2021 ; 11 ( 7 ): 1 - 17 . doi: 10.3390/metabo11070434 http://dx.doi.org/10.3390/metabo11070434 .
Wang J , Wang Y , Zeng Y , et al . Feature selection approaches identify potential plasma metabolites in postmenopausal osteoporosis patients . Metabolomics 2022 ; 18 ( 11 ): 1 - 12 . doi: 10.1007/s11306-022-01937-0 http://dx.doi.org/10.1007/s11306-022-01937-0 .
He J , Gai J . Genome-wide association studies (GWAS) . Methods Mol Biol 2023 ; 2638 : 123 - 46 . doi: 10.1007/978-1-0716-3024-2_9 http://dx.doi.org/10.1007/978-1-0716-3024-2_9 .
Birney E . Mendelian randomization . Csh Perspect Med 2022 ; 12 ( 4 ): 1 - 4 . doi: 10.1101/cshperspect.a041302 http://dx.doi.org/10.1101/cshperspect.a041302 .
Bowden J , Holmes MV . Meta-analysis and Mendelian randomization: a review . Res Synth Methods 2019 ; 10 ( 4 ): 486 - 96 . doi: 10.1002/jrsm.1346 http://dx.doi.org/10.1002/jrsm.1346 .
Chen Y , Lu T , Pettersson-Kymmer U , et al . Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases . Nat Genet 2023 ; 55 ( 1 ): 44 - 53 . doi: 10.1038/s41588-022-01270-1 http://dx.doi.org/10.1038/s41588-022-01270-1 .
Bowden J , Davey SG , Burgess S . Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression . Int J Epidemiol 2015 ; 44 ( 2 ): 512 - 25 . doi: 10.1093/ije/dyv080 http://dx.doi.org/10.1093/ije/dyv080 .
Pierce BL , Burgess S . Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators . Am J Epidemiol 2013 ; 178 ( 7 ): 1177 - 84 . doi: 10.1093/aje/kwt084 http://dx.doi.org/10.1093/aje/kwt084 .
Broadbent JR , Foley CN , Grant AJ , et al . MendelianRandomization v0.5 . 0 : updates to an R package for performing Mendelian randomization analyses using summarized data. Wellcome Open Res 2020; 5 ( 252 ): 1 - 21 . doi: 10.12688/wellcomeopenres.16374.2 http://dx.doi.org/10.12688/wellcomeopenres.16374.2 .
Verbanck M , Chen CY , Neale B , et al . Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases . Nat Genet 2018 ; 50 ( 5 ): 693 - 8 . doi: 10.1038/s41588-018-0099-7 http://dx.doi.org/10.1038/s41588-018-0099-7 .
Liu H , Gu R , Zhu Y , et al . D-mannose attenuates bone loss in mice via Treg cell proliferation and gut microbiota-dependent anti-inflammatory effects . Ther Adv Chronic Dis 2020 ; 11 : 1 - 17 . doi: 10.1177/2040622320912661 http://dx.doi.org/10.1177/2040622320912661 .
Yang T , Liu S , Ma H , et al . Carnitine functions as an enhancer of NRF2 to inhibit osteoclastogenesis via regulating macrophage polarization in osteoporosis . Free Radical Bio Med 2024 ; 213 : 174 - 89 . doi: 10.1016/j.freeradbiomed.2024.01.017 http://dx.doi.org/10.1016/j.freeradbiomed.2024.01.017 .
Nishihara S , Ikeda M , Ozawa H , et al . Role of cAMP in phenotypic changes of osteoblasts . Biochem Bioph Res Co 2018 ; 495 ( 1 ): 941 - 6 . doi: 10.1016/j.bbrc.2017.11.125 http://dx.doi.org/10.1016/j.bbrc.2017.11.125 .
Wang Y , Deng P , Liu Y , et al . Alpha-ketoglutarate ameliorates age-related osteoporosis via regulating histone methylations . Nat Commun 2020 ; 11 ( 1 ): 1 - 14 . doi: 10.1038/s41467-020-19360-1 http://dx.doi.org/10.1038/s41467-020-19360-1 .
Shen L , Yu Y , Karner CM . SLC38A2 provides proline and alanine to regulate postnatal bone mass accrual in mice . Front Physiol 2022 ; 13 : 1 - 14 . doi: 10.3389/fphys.2022.992679 http://dx.doi.org/10.3389/fphys.2022.992679 .
Lee S , Kim HS , Kim MJ , et al . Glutamine metabolite alpha-ketoglutarate acts as an epigenetic co-factor to interfere with osteoclast differentiation . Bone 2021 ; 145 : 1 - 29 . doi: 10.1016/j.bone.2020.115836 http://dx.doi.org/10.1016/j.bone.2020.115836 .
Cheng C , Xing Z , Hu Q , et al . A bone-targeting near-infrared luminescence nanocarrier facilitates alpha-ketoglutarate efficacy enhancement for osteoporosis therapy . Acta Biomater 2024 ; 173 : 442 - 56 . doi: 10.1016/j.actbio.2023.11.022 http://dx.doi.org/10.1016/j.actbio.2023.11.022 .
Mikkelsen RB , Arora T , Trost K , et al . Type 2 diabetes is associated with increased circulating levels of 3-hydroxydecanoate activating GPR84 and neutrophil migration . Iscience 2022 ; 25 ( 12 ): 1 - 28 . doi: 10.1016/j.isci.2022.105683 http://dx.doi.org/10.1016/j.isci.2022.105683 .
Anaya JM , Bollag WB , Hamrick MW , et al . The role of tryptophan metabolites in musculos21186670 .
Cao S , Li Y , Song R , et al . L-arginine metabolism inhibits arthritis and inflammatory bone loss . Ann Rheum Dis 2024 ; 83 ( 1 ): 72 - 87 . doi: 10.1136/ard-2022-223626 http://dx.doi.org/10.1136/ard-2022-223626 .
Shen L , Yu Y , Zhou Y , et al . SLC38A2 provides proline to fulfill unique synthetic demands arising during osteoblast differentiation and bone formation . Elife 2022 ; 11 : 1 - 64 . doi: 10.7554/eLife.76963 http://dx.doi.org/10.7554/eLife.76963 .
Tousen Y , Matsumoto Y . Skeletal stem cell aging . Int J Mol Sci 2020 ; 21 ( 18 ): 1 - 14 . doi: 10.3390/ijm http://dx.doi.org/10.3390/ijm .
Meng KL , Jiao MZ , Shi XG , et al . A rapid approach to capture the potential bioactive compounds from Rhizoma Drynariae, utilizing disease-associated mutation in calcium sensing receptor to alter the binding affinity for agonists . J Pharmaceut Biomed 2023 ; ( 226 ): 1 - 10 . doi: 10.1016/j.jpba.2023.115253 http://dx.doi.org/10.1016/j.jpba.2023.115253 .
Wang Q , Gao Z , Guo K , et al . Human umbilical cord wharton jelly cells treatment prevents osteoporosis induced by D-galactose . Int J Clin Pract 2022 ; July:1- 10 . doi: 10.1155/2022/4593443 http://dx.doi.org/10.1155/2022/4593443 .
Publicity Resources
Related Articles
Related Author
Related Institution