摘要
Objective To investigate the causal relationships between plasma metabolites and osteoporosis via Mendelian randomization(MR) analysis.Methods 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 MRPRESSO 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 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 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.
目的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。结果经过初步分析和一系列敏感性分析,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(GCST90038656:OR=0.999,95%CI,0.998~1.000,P=0.004;GCST90044600:OR=0.834,95%CI,0.700~0.993,P=0.042)、葡萄糖与麦芽糖比值(GCST90038656:OR=0.998,95%CI,0.997~1.000,P=0.025;GCST90044600:OR=0.752,95%CI,0.576~0.981,P=0.036)同骨质疏松症呈负相关,而甘氨脱氧胆酸水平(GCST90038656:OR=1.002,95%CI,1.000~1.003,P=0.032;GCST90044600:OR=1.331,95%CI,1.036~1.709,P=0.025)、花生四烯酰肉碱(C20)水平(GCST90038656:OR=1.001,95%CI,1.000~1.003,P=0.039;GCST90044600:OR=1.237,95%CI,1.008~1.518,P=0.042)与骨质疏松症呈正相关。X-11299水平与骨质疏松症的关系表现出矛盾的结果(GCST90038656:OR=0.998,95%CI,0.997~1.000,P=0.026;GCST90044600:OR=1.402,95%CI,1.071~1.834,P=0.014)。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。
基金
安徽省自然科学基金项目(2308085MH294)
安徽省高校自然科学研究项目(2022AH050510)
安徽省重点研发项目(202104j07020010)
安徽中医药大学自然科学基金项目(2020yfyzc27)。
