Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.
Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, China.
Front Public Health. 2022 Aug 25;10:905178. doi: 10.3389/fpubh.2022.905178. eCollection 2022.
Osteoporosis is associated with metabolic alterations, but the causal roles of serum metabolites on osteoporosis have not been identified.
Based on the large individual-level datasets from UK Biobank as well as GWAS summary datasets, we first constructed genetic risk scores (GRSs) for 308 of 486 human serum metabolites and evaluated the effect of each GRS on 2 major osteoporosis phenotypes, i.e., estimated bone miner density (eBMD) and fracture, respectively. Then, two-sample Mendelian Randomization (MR) was performed to validate the casual metabolites on osteoporosis. Multivariable MR analysis tested whether the effects of metabolites on osteoporosis are independent of possible confounders. Finally, we conducted metabolic pathway analysis for the metabolites involved in bone metabolism.
We identified causal effects of 18 metabolites on eBMD and 1 metabolite on fracture with the GRS method after adjusting for multiple tests. Then, 9 of them were further validated with MR as replication, where comprehensive sensitive analyses proved robust of the causal associations. Although not identified in GRS, 3 metabolites were associated with at least three osteoporosis traits in MR results. Multivariable MR analysis determined the independent causal effect of several metabolites on osteoporosis. Besides, 23 bone metabolic pathways were detected, such as valine, leucine, isoleucine biosynthesis ( = 0.053), and Aminoacyl-tRNA biosynthesis ( = 0.076), and D-glutamine and D-glutamate metabolism ( = 0.004).
The systematic causal analyses strongly suggested that blood metabolites have causal effects on osteoporosis risk.
骨质疏松症与代谢改变有关,但血清代谢物对骨质疏松症的因果作用尚未确定。
基于英国生物库的大型个体水平数据集以及 GWAS 汇总数据集,我们首先构建了 486 个人类血清代谢物中的 308 个代谢物的遗传风险评分(GRS),并评估了每个 GRS 对 2 种主要骨质疏松表型(即估计骨矿物质密度[eBMD]和骨折)的影响。然后,进行两样本 Mendelian Randomization(MR)以验证代谢物对骨质疏松症的因果关系。多变量 MR 分析测试了代谢物对骨质疏松症的影响是否独立于可能的混杂因素。最后,我们对参与骨代谢的代谢物进行了代谢途径分析。
我们使用 GRS 方法在调整了多重检验后,确定了 18 种代谢物对 eBMD 和 1 种代谢物对骨折的因果影响。然后,通过 MR 进一步验证了 9 种代谢物,综合敏感分析证明了因果关系的稳健性。尽管在 GRS 中未被识别,但在 MR 结果中,有 3 种代谢物与至少 3 种骨质疏松症特征相关。多变量 MR 分析确定了几种代谢物对骨质疏松症的独立因果作用。此外,还检测到 23 个骨代谢途径,例如缬氨酸、亮氨酸、异亮氨酸生物合成( = 0.053)和氨酰-tRNA 生物合成( = 0.076),以及 D-谷氨酰胺和 D-谷氨酸代谢( = 0.004)。
系统的因果分析强烈表明血液代谢物对骨质疏松症风险有因果作用。