Assessing the causal relationship between plasma proteins and osteoporosis: novel insights into pathological mechanisms and therapeutic implications

• Published in: Osteoporosis international Vol. 35; no. 11; pp. 1973 - 1987
• Main Authors: Wang, Liang, Guo, Xiangyun, Qin, Jinran, Jin, Zikai, Liu, Qingqing, Sun, Chuanrui, Sun, Kai, Li, Linghui, Wei, Xu, Zhang, Yili
• Format: Journal Article
• Language: English
• Published: London Springer London 01-11-2024; Springer Nature B.V
• Subjects: Bone mineral density; Clinical outcomes; Clinical trials; Disease prevention; Drug development; Drug therapy; Endocrinology; ErbB-3 protein; Immune response; Immunosuppressive agents; Medical treatment; Medicine; Medicine & Public Health; Original Article; Orthopedics; Osteoporosis; Plasma proteins; Proteins; Rheumatology; Statistical analysis; Therapeutic targets; Osteoporosis; Plasma proteins; Mendelian randomization; Drug targets
• ISSN: 0937-941X; 1433-2965; 1433-2965
• DOI: 10.1007/s00198-024-07225-y

Summary
Identifying dysregulated plasma proteins in osteoporosis (OP) progression offers insights into prevention and treatment. This study found 8 such proteins associated with OP, suggesting them as therapy targets. This discovery may cut drug development costs and improve personalized treatments.
Purpose
This study aims to identify potential therapeutic targets for OP using summary data-based Mendelian randomization (SMR) and colocalization analysis methods. Furthermore, we seek to explore the biological significance and pharmacological value of these drug targets.
Methods
To identify potential therapeutic targets for OP, we conducted SMR and colocalization analysis. Plasma protein (pQTL, exposure) data were sourced from the study by Ferkingstad et al. (
n
 = 35,559). Summary statistics for bone mineral density (BMD, outcome) were obtained from the GWAS Catalog (
n
 = 56,284). Additionally, we utilized enrichment analysis, protein–protein interaction (PPI) network analysis, drug prediction, and molecular docking to further analyze the biological significance and pharmacological value of these drug targets.
Results
In the SMR analysis, while 20 proteins showed significance, only 8 potential drug targets (GCKR, ERBB3, CFHR1, GPN1, SDF2, VTN, BET1L, and SERPING1) received support from colocalization (PP.H4 > 0.8). These proteins are closely associated with immune function in terms of biological significance. Molecular docking also demonstrated favorable binding of drugs to proteins, consistent with existing structural data, further substantiating the pharmacological value of these targets.
Conclusions
The study identified 8 potential drug targets for OP. These prospective targets are believed to have a higher chance of success in clinical trials, thus aiding in prioritizing OP drug development and reducing development costs.