Candidate drug predicted using DSigDB.

Objective
This study aims to explore the correlation between Osteoporosis and stroke risk, and find potential common key genes and drugs for intervention through bioinformatics methods.
Methods
This study used clinical data to assess the relationship between Osteoporosis and stroke risk through univariate and multivariate logistic regression analyses. Additionally, blood sequencing data from patients with Osteoporosis and stroke were obtained from the GEO database, and common key genes were identified using differential analysis, LASSO regression, and ROC curve methods. Potential interventional drugs were predicted using the DSigDB database.
Results
In the initial model, Osteoporosis was significantly associated with stroke risk (OR=1.78, 95% CI: 1.14–2.78, p < 0.01). This association was still significant after adjusting for factors such as age, gender, race, and BMI (OR=1.84, 95% CI: 1.18–2.89, p = 0.007). Bioinformatics analysis identified LILRA5, HNRNPL and AGBL3 as common key genes for Osteoporosis and stroke, and these genes were highly effective in diagnosing both diseases. The DSigDB database predicted that Cyclopenthiazide, Neostigmine bromide, and R-atenolol could potentially intervene with these three genes.
Conclusion
There is a significant positive correlation between Osteoporosis and stroke risk. LILRA5, HNRNPL and AGBL3 could be key genes common to both diseases, and Cyclopenthiazide, Neostigmine bromide, and R-atenolol could be potential drugs for intervention.

研究目的
本研究旨在探讨骨质疏松症与卒中风险的相关性，并通过生物信息学方法挖掘二者潜在的共同关键基因及干预药物。

研究方法
本研究首先利用临床数据，通过单因素及多因素logistic回归分析评估骨质疏松症与卒中风险之间的关联。此外，从基因表达综合数据库（Gene Expression Omnibus，简称GEO）获取骨质疏松症及卒中患者的血液测序数据，采用差异分析、最小绝对收缩和选择算子（LASSO）回归及受试者工作特征（Receiver Operating Characteristic，简称ROC）曲线法筛选共同关键基因。利用DSigDB数据库预测潜在的干预药物。

研究结果
初始模型中，骨质疏松症与卒中风险呈显著关联（OR=1.78，95%CI：1.14~2.78，p<0.01）。在校正年龄、性别、种族、体质量指数（Body Mass Index，简称BMI）等混杂因素后，该关联仍具有统计学意义（OR=1.84，95%CI：1.18~2.89，p=0.007）。生物信息学分析筛选出LILRA5、HNRNPL及AGBL3作为骨质疏松症与卒中的共同关键基因，上述基因对两种疾病均具有良好的诊断效能。通过DSigDB数据库预测得到环戊噻嗪（Cyclopenthiazide）、溴新斯的明（Neostigmine bromide）及R-阿替洛尔（R-atenolol）可靶向干预上述三个关键基因。

研究结论
本研究证实骨质疏松症与卒中风险存在显著正相关。LILRA5、HNRNPL及AGBL3可作为二者的共同关键基因，环戊噻嗪、溴新斯的明及R-阿替洛尔或可作为潜在的干预药物。