Guoqiang Wang, Jiachen Wang, Dinglong Yang, Lin Liu, Peng Xu
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引用次数: 0
Abstract
Background: The influence of nervous system activity on bone remodeling has been widely reported. Patients with traumatic brain injury (TBI) exhibit a high incidence of osteoporosis (OP). Nevertheless, the relationship between severe TBI (sTBI) and OP remains unclear. We performed Mendelian randomization (MR) analysis to assess the potential causal relationship between sTBI and OP.
Methods: Data on exposure and outcomes were acquired from genome-wide association studies (GWAS). Data on OP was obtained from UK Biobank (5,266 cases of OP and 331,893 controls). Data on sTBI was obtained from FinnGen Consortium (6,687 cases and 370,590 controls). Single nucleotide polymorphisms (SNPs) that underwent strict screening were regarded as instrumental variables. We used the inverse variance weighted (IVW), constrained maximum likelihood and model averaging (CML-MA), MR-Egger, and weighted median methods for causal effect estimation. To test the reliability of the results, sensitivity analysis was performed using Cochran's Q, leave-one-out, MR-Egger intercept, and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) tests.
Results: The IVW analysis indicates that sTBI and OP have a suggestive association (odds ratio [OR] = 1.004, 95% confidence interval [CI] = 1.001,1.007; p = 0.002), and no heterogeneity (Q = 11.536, p = 0.241) or directional pleiotropy was observed (egger_intercept = 7.368 × 10- 5, p = 0.870). The robustness of the results was validated using a leave-one-out sensitivity test.
Conclusion: According to the MR analysis, sTBI and OP are likely suggestively related. This finding contributes to the prevention of OP in patients with sTBI and provides genetic evidence supporting the theory that the nervous system regulates bone remodeling.
期刊介绍:
BMC Medical Genomics is an open access journal publishing original peer-reviewed research articles in all aspects of functional genomics, genome structure, genome-scale population genetics, epigenomics, proteomics, systems analysis, and pharmacogenomics in relation to human health and disease.