Chinese Medical Sciences Journaldoi: 10.24920/004356

• Research Article • Previous Articles    

Dissecting Causal Relationships Between Plasma Metabolites and Osteoporosis: A Bidirectional Mendelian Randomization Study

Hao Lv1, 2†, Ge Zhang3†, Zhi-Mu Hu2, Qing-Song Chu2, Jiu-Xiang Wang4*, Ting Jiang1*   

  1. 1Department of Orthopaedics, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, 230031 China;
    2Graduate School of Anhui University of Chinese Medicine, Hefei, 230012 China;
    3Department of Geriatrics, The Third People's Hospital of Hefei, Hefei, 230041 China;
    4Experimental Center of Clinical Research, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, 230031 China
  • Received:2024-03-07 Accepted:2024-08-22 Online:2024-09-14
  • Contact: *E-mail: Ting Jiang, jiangting70@163.com; Jiu-Xiang Wang, 1322921327@qq.com
  • About author:Contributed equally as co-first authors.

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) to investigate the causal relationships between plasma metabolites and osteoporosis. 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 After primary analysis and a series of sensitivity analyses, 77 and 61 plasma metabolites were identified as having 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 (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), and the glucose-to-maltose ratio (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) were negatively associated with osteoporosis, whereas glycoursodeoxycholate levels (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) and arachidoylcarnitine (C20) levels (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) were positively associated with osteoporosis. The relationship between X-11299 levels and osteoporosis showed contradictory results (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). 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 that have implications for targeted interventions focused on metabolites in the management of osteoporosis.

Key words: osteoporosis, plasma metabolites, mendelian randomization, bidirectional analysis

Funding:

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