Objective
Osteoporosis (OP) is a prevalent systemic metabolic disorder characterized by a reduction in total bone mass and a deterioration of bone microarchitecture. These changes result in significantly increased bone fragility, which predisposes patients to a higher risk of fractures. As a consequence, OP severely impacts patients' quality of life and imposes a considerable economic burden on society. With the ongoing global demographic shift towards an aging population, it is crucial to gain a deeper understanding of the pathogenesis of OP and to develop effective therapeutic strategies. This study aims to identify potential causal risk factors associated with OP by examining genetic variations, with the goal of providing new insights for the prevention and management of the disease.
Methods
We commenced our investigation by developing a comprehensive search protocol. Subsequently, we conducted a systematic search across several Chinese databases, including the China National Knowledge Infrastructure (CNKI), the Chinese Biomedical Literature Database (CBM), the Wanfang Database, and VIP Information (CSTJ), as well as international databases such as The Cochrane Library, PubMed, Embase, and Web of Science. This thorough search was executed electronically to ensure a complete collection of the most current literature and data related to OP, thereby minimizing the risk of oversights. Following this, we established rigorous inclusion and exclusion criteria for literature selection, which was followed by a meticulous review and synthesis of the existing literature. This process enabled us to accurately identify a range of potential etiological risk factors associated with OP. To substantiate the association between these factors and the disease, we incorporated extensive outcome data from the Finnish database, which included 3,203 OP cases and 209,575 controls, as well as the UK Biobank database, which comprised 5,266 cases and 331,893 controls.The inclusion of these robust datasets enhances the statistical rigor and reliability of our findings. We employed a two-sample bidirectional Mendelian randomization(MR) approach, utilizing genetic variation as an instrumental variable. This method mitigates the influence of confounding factors and reverse causality, thus enabling a more thorough exploration of the genetic relationship between hypothesized risk factors and OP risk. To assess heterogeneity in our results, we applied Cochran's Q test and employed the MR-Egger and MR-PRESSO regression techniques to investigate the potential for pleiotropy. To ensure the homogeneity of our research data and guard against pleiotropy, we calculated the impact quantification index (ORSD) for each risk factor's effect on OP risk across varying degrees of genetic variation. This calculation offers substantial evidence for a deeper understanding of the disease's etiology. Furthermore, to rigorously control the accuracy of our research outcomes, we implemented the False Discovery Rate (FDR) correction and the Bonferroni correction methods. These approaches mitigate the risk of false positives in multiple hypothesis testing, thereby preserving the scientific integrity and credibility of our conclusions.
Results
Through rigorous analysis, we identified several factors associated with OP in the Finnish database. Notably, primary biliary cholangitis, type 1 diabetes, seropositive rheumatoid arthritis, and seronegative rheumatoid arthritis exhibited positive correlations with OP. In contrast, type 2 diabetes demonstrated an inverse relationship with the condition. Biochemical indicators, including Dickkopf-related protein 1 and sex hormone-binding globulin levels, were positively associated with OP. Socioeconomic factors, such as higher education levels and years of schooling, showed negative correlations with OP. Lifestyle habits, including drinking frequency, as well as biochemical indicators like oxalate levels, also displayed negative associations. Furthermore, specific population characteristics, such as the relative body size of 10-year-old male children, along with physical indicators like body mass index and systolic blood pressure, were inversely related to OP risk.In the UK Biobank data, factors such as menopausal status, celiac disease, irritable bowel syndrome, systemic lupus erythematosus, education level, and environmental exposures like PM2.5 exhibited positive correlations with OP. Conversely, menopausal age, dietary factors including non-oily fish consumption, and pulse pressure were found to be negatively associated with the disease. Post-hoc corrections employing the Bonferroni method revealed significant positive correlations between seropositive rheumatoid arthritis and type 1 diabetes with OP in the Finnish database, along with negative correlations for menopausal age and pulse pressure in the UK Biobank. Following the application of the False Discovery Rate (FDR) correction, the Finnish database indicated additional positive associations with OP for primary biliary cholangitis, irritable bowel syndrome, type 1 diabetes, seropositive rheumatoid arthritis, and sex hormone-binding globulin levels. Furthermore, type 2 diabetes and systolic blood pressure were confirmed to have negative correlations with OP. In the UK Biobank, the negative associations for menopausal age and pulse pressure remained consistent.
Conclusion
These findings, derived from a genetic variation perspective, effectively exclude certain previously implicated pathogenic risk factors for OP while highlighting others. This distinction is pivotal as it enhances our understanding of the disease's etiology. The implications of our study are profound, providing valuable insights that could significantly inform the development of preventive and therapeutic strategies for OP.
