The Journal of Practical Medicine >
Causal association of 35 biomarkers, including apolipoprotein B, serum phosphate, and calcium, with bone mineral density: A Mendelian randomization analysis
Received date: 2025-07-24
Online published: 2025-12-25
Objective To investigate the potential causal relationship between 35 blood and urine markers and bone mineral density (BMD) at different skeletal sites using a two-sample Mendelian randomization design. Methods Genetic instruments (single-nucleotide polymorphisms, SNPs) associated with the 35 biomarkers were selected from the UK Biobank (UKB). GWAS aggregate data for bone mineral density were obtained from the Osteoporosis Genetic Factors Consortium (GEFOS). The inverse-variance weighted (IVW) method served as the primary analysis, supplemented by the weighted median, simple median, and MR-Egger methods. Sensitivity analyses, including tests for pleiotropy and heterogeneity, were performed to ensure robustness. Furthermore, the significant findings were validated in independent European GWAS datasets. Results IVW results showed that apolipoprotein B was negatively associated with heel BMD (OR = 0.98, 95%CI: 0.97 ~ 1.00, P = 0.027). There may be a causal relationship between blood phosphorus and bone mineral density of femoral neck (OR = 1.09,95%CI: 1.03 ~ 1.15, P = 0.003); Elevated blood calcium levels were potentially causally linked to reduced BMD in the skull (OR = 0.90, 95% CI: 0.85 ~ 0.95, P = 1.75 × 10??) and lumbar spine (OR = 0.92, 95% CI: 0.86 ~ 0.98, P = 0.007). We also found blood urea nitrogen, glomerular filtration rate, apolipoprotein B, triglycerides, and total protein also have potential correlations with bone mineral density, and the P-values are all less than 0.05. MR-Egger regression suggests that the above causal association is not affected by horizontal pleiotropy, and weighted median method and simple median method can obtain results similar to IVW. All these biomarker-BMD associations were replicated in the validation cohort. Conclusions This large-scale two-sample MR study systematically identifies potential causal effects of specific biomarkers on site-specific BMD. The findings suggest that higher apolipoprotein B may reduce heel BMD, elevated blood phosphorus might help maintain femoral neck BMD, and increased blood calcium could be associated with lower BMD in the skull and lumbar spine.
Jianxiong ZHUANG , Rong CHEN , Jian TU , Zhengran YU , Xiaoqing ZHENG , Yunbing CHANG , Honglin. GU . Causal association of 35 biomarkers, including apolipoprotein B, serum phosphate, and calcium, with bone mineral density: A Mendelian randomization analysis[J]. The Journal of Practical Medicine, 2025 , 41(24) : 3947 -3958 . DOI: 10.3969/j.issn.1006-5725.2025.24.020
| [1] | ZHANG J, DENNISON E, PRIETO-ALHAMBRA D. Osteoporosis epidemiology using international cohorts[J]. Curr Opin Rheumatol,2020,32(4):387-393. doi:10.1097/bor.0000000000000722 |
| [2] | BOUVARD B, ANNWEILER C, LEGRAND E. Osteoporosis in older adults[J]. Joint Bone Spine,2021,88(3):105135. doi:10.1016/j.jbspin.2021.105135 |
| [3] | WANG J, SHU B, TANG D Z, et al. The prevalence of osteoporosis in China, a community based cohort study of osteoporosis[J]. Front Public Health, 2023, 11: 1084005. doi:10.3389/fpubh.2023.1084005 |
| [4] | SLART R, PUNDA M, ALI D S, et al. Updated practice guideline for dual-energy X-ray absorptiometry (DXA)[J]. Eur J Nucl Med Mol Imaging, 2025, 52(2): 539-563. doi:10.1007/s00259-024-06912-6 |
| [5] | 李小海,谢光友,梁力嵩,等. 贵州中老年人腰椎QCT骨密度及脊柱脆性骨折的骨密度分析[J]. 实用医学杂志,2023,39(1):60-65. |
| [6] | NISSINEN T, SUORANTA S, SAAVALAINEN T, et al. Detecting pathological features and predicting fracture risk from dual-energy X-ray absorptiometry images using deep learning[J]. Bone Rep, 2021, 14: 101070. doi:10.1016/j.bonr.2021.101070 |
| [7] | STUURSMA A, STROOT I, VERMEULEN K M, et al. Reliability, costs, and radiation dose of dual-energy X-ray absorptiometry in diagnosis of radiologic sarcopenia in surgically menopausal women[J]. Insights Imaging, 2024, 15(1): 104. doi:10.1186/s13244-024-01677-w |
| [8] | PANAHI N, ARJMAND B, OSTOVAR A, et al. Metabolomic biomarkers of low BMD: A systematic review[J]. Osteoporos Int,2021,32(12):2407-2431. doi:10.1007/s00198-021-06037-8 |
| [9] | FUJIYOSHI A, POLGREEN L E, HURLEY D L, et al. A cross-sectional association between bone mineral density and parathyroid hormone and other biomarkers in community-dwelling young adults: The CARDIA study[J]. J Clin Endocrinol Metab, 2013, 98(10): 4038-4046. doi:10.1210/jc.2013-2198 |
| [10] | BARBOUR K E, BOUDREAU R, DANIELSON M E, et al. Inflammatory markers and the risk of hip fracture: The Women's Health Initiative[J]. J Bone Miner Res, 2012, 27(5): 1167-1176. doi:10.1002/jbmr.1559 |
| [11] | SKRIVANKOVA V W, RICHMOND R C, WOOLF B, et al. Strengthening the Reporting of Observational Studies in Epidemiology Using Mendelian Randomization: The STROBE-MR Statement[J]. JAMA,2021,326(16):1614-1621. doi:10.1001/jama.2021.18236 |
| [12] | BURGESS S, SMALL D S, THOMPSON S G. A review of instrumental variable estimators for Mendelian randomization[J]. Stat Methods Med Res, 2017,26(5): 2333-2355. doi:10.1177/0962280215597579 |
| [13] | SINNOTT-ARMSTRONG N, TANIGAWA Y, AMAR D, et al. Genetics of 35 blood and urine biomarkers in the UK Biobank[J]. Nat Genet, 2021, 53(2): 185-194. doi:10.1038/s41588-020-00757-z |
| [14] | MEDINA-GOMEZ C, KEMP J P, TRAJANOSKA K, et al. Life-Course Genome-wide Association Study Meta-analysis of Total Body BMD and Assessment of Age-Specific Effects[J]. Am J Hum Genet, 2018, 102(1): 88-102. |
| [15] | MORRIS J A, KEMP J P, YOULTEN S E, et al. An atlas of genetic influences on osteoporosis in humans and mice[J]. Nat Genet, 2019, 51(2): 258-266. doi:10.1038/s41588-018-0302-x |
| [16] | ZHENG H F, FORGETTA V, HSU Y H, et al. Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture[J]. Nature, 2015, 526(7571): 112-117. |
| [17] | MIAO J, WU Y, SUN Z, et al. Valid inference for machine learning-assisted genome-wide association studies[J]. Nat Genet, 2024, 56(11): 2361-2369. doi:10.1038/s41588-024-01934-0 |
| [18] | LOH P R, KICHAEV G, GAZAL S, et al. Mixed-model association for biobank-scale datasets[J]. Nat Genet,2018,50(7):906-908. doi:10.1038/s41588-018-0144-6 |
| [19] | SURAKKA I, FRITSCHE L G, ZHOU W, et al. MEPE loss-of-function variant associates with decreased bone mineral density and increased fracture risk[J]. Nat Commun,2020,11(1):4093. doi:10.1038/s41467-020-17315-0 |
| [20] | BOWDEN J, DAVEY S G, HAYCOCK P C, et al. Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator[J]. Genet Epidemiol, 2016, 40(4): 304-314. doi:10.1002/gepi.21965 |
| [21] | BOWDEN J, DEL G M F, MINELLI C, et al. A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization[J]. Stat Med,2017, 36(11): 1783-1802. doi:10.1002/sim.7221 |
| [22] | VERBANCK M, CHEN C Y, NEALE B, et al. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases[J]. Nat Genet,2018,50(5):693-698. doi:10.1038/s41588-018-0099-7 |
| [23] | PIERCE B L, BURGESS S. Efficient design for Mendelian randomization studies: Subsample and 2-sample instrumental variable estimators[J]. Am J Epidemiol, 2013, 178(7): 1177-1184. doi:10.1093/aje/kwt084 |
| [24] | TANG G, FENG L, PEI Y, et al. Low BMI, blood calcium and vitamin D, kyphosis time, and outdoor activity time are independent risk factors for osteoporosis in postmenopausal women[J]. Front Endocrinol (Lausanne), 2023, 14: 1154927. doi:10.3389/fendo.2023.1154927 |
| [25] | STROMSNES K, FAJARDO C M, SOTO-RODRIGUEZ S, et al. Osteoporosis: Causes, Mechanisms, Treatment and Prevention: Role of Dietary Compounds[J]. Pharmaceuticals (Basel), 2024, 17(12): 1697. doi:10.3390/ph17121697 |
| [26] | HASSANEIN M M, HURI H Z, BAIG K, et al. Determinants and Effects of Vitamin D Supplementation in Postmenopausal Women: A Systematic Review[J]. Nutrients, 2023, 15(3): 685. doi:10.3390/nu15030685 |
| [27] | FATIMA K, RAZZAK M A, LATIF A, et al. Relationship between Renal Function and Bone Mineral Density in Postmenopausal Women[J]. Mymensingh Med J,2023,32(1):144-152. |
| [28] | KANG D H, PARK C H, KIM H W, et al. Kidney function and bone mineral density in chronic kidney disease patients[J]. Clin Kidney J,2024,17(9):sfae248. doi:10.1093/ckj/sfae248 |
| [29] | CANNATA-ANDIA J B, MARTIN-CARRO B, MARTIN-VIRGALA J, et al. Chronic Kidney Disease-Mineral and Bone Disorders: Pathogenesis and Management[J]. Calcif Tissue Int,2021,108(4):410-422. doi:10.1007/s00223-020-00777-1 |
| [30] | STEHMAN-BREEN C. Bone mineral density measurements in dialysis patients[J]. Semin Dial,2001,14(3):228-229. doi:10.1046/j.1525-139x.2001.00057-2.x |
| [31] | SHU J, TAN A, LI Y, et al. The correlation between serum total alkaline phosphatase and bone mineral density in young adults[J]. BMC Musculoskelet Disord, 2022, 23(1): 467. doi:10.1186/s12891-022-05438-y |
| [32] | BROWN J P, DON-WAUCHOPE A, DOUVILLE P, et al. Current use of bone turnover markers in the management of osteoporosis[J]. Clin Biochem, 2022, 109-110: 1-10. doi:10.1016/j.clinbiochem.2022.09.002 |
| [33] | KAN B, ZHAO Q, WANG L, et al. Association between lipid biomarkers and osteoporosis: A cross-sectional study[J]. BMC Musculoskelet Disord, 2021, 22(1): 759. doi:10.1186/s12891-021-04643-5 |
| [34] | ZHAO X, TAN N, ZHANG Y, et al. Associations between apolipoprotein B and bone mineral density: A population-based study[J]. BMC Musculoskelet Disord, 2023, 24(1): 861. doi:10.1186/s12891-023-06990-x |
| [35] | SNIDERMAN A, LANGLOIS M, COBBAERT C. Update on apolipoprotein B[J]. Curr Opin Lipidol,2021,32(4):226-230. doi:10.1097/mol.0000000000000754 |
| [36] | WANG T, HE C. TNF-alpha and IL-6: The Link between Immune and Bone System[J]. Curr Drug Targets,2020,21(3):213-227. doi:10.2174/1389450120666190821161259 |
| [37] | FISCHER V, HAFFNER-LUNTZER M. Interaction between bone and immune cells: Implications for postmenopausal osteoporosis[J]. Semin Cell Dev Biol,2022,123:14-21. doi:10.1016/j.semcdb.2021.05.014 |
| [38] | 陈帅,金杰,韩化伟,等. 两样本孟德尔随机化分析循环炎症细胞因子与骨密度的因果关联[J]. 中国组织工程研究, 2025, 29(8): 1556-1564. |
| [39] | YANG X L, CUI Z Z, ZHANG H, et al. Causal link between lipid profile and bone mineral density: A Mendelian randomization study[J]. Bone, 2019, 127: 37-43. doi:10.1016/j.bone.2019.05.037 |
/
| 〈 |
|
〉 |