{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T18:28:47Z","timestamp":1765477727613,"version":"3.48.0"},"reference-count":28,"publisher":"Public Library of Science (PLoS)","issue":"12","license":[{"start":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T00:00:00Z","timestamp":1765411200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Liu Zhou Science and Technology Development Project","award":["2023YRQ0101"],"award-info":[{"award-number":["2023YRQ0101"]}]},{"name":"Lianyungang Science and Technology Bureau 2023 Municipal Key Research and Development Project","award":["SF2321"],"award-info":[{"award-number":["SF2321"]}]},{"name":"Lianyungang Anti-Cancer Association 2023 Tumor Prevention and Treatment Science and Technology Development Plan Surface Project","award":["MS202308"],"award-info":[{"award-number":["MS202308"]}]},{"name":"Nanjing Medical University Kangda College 2023 Key Research and Development Fund Project","award":["KD2023KYJJ045"],"award-info":[{"award-number":["KD2023KYJJ045"]}]},{"name":"Lianyungang 2024 Hygiene and Health Surface Science and Technology Project","award":["202422"],"award-info":[{"award-number":["202422"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"\n Objective<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n 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.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n In the initial model, Osteoporosis was significantly associated with stroke risk (OR=1.78, 95% CI: 1.14\u20132.78,\n p<\/jats:italic>\n \u2009<\u20090.01). This association was still significant after adjusting for factors such as age, gender, race, and BMI (OR=1.84, 95% CI: 1.18\u20132.89,\n p<\/jats:italic>\n \u2009=\u20090.007). Bioinformatics analysis identified\n LILRA5<\/jats:italic>\n ,\n HNRNPL<\/jats:italic>\n and\n AGBL3<\/jats:italic>\n 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.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusion<\/jats:title>\n \n There is a significant positive correlation between Osteoporosis and stroke risk.\n LILRA5<\/jats:italic>\n ,\n HNRNPL<\/jats:italic>\n and\n AGBL3<\/jats:italic>\n could be key genes common to both diseases, and Cyclopenthiazide, Neostigmine bromide, and R-atenolol could be potential drugs for intervention.\n <\/jats:p>\n <\/jats:sec>","DOI":"10.1371\/journal.pone.0337460","type":"journal-article","created":{"date-parts":[[2025,12,11]],"date-time":"2025-12-11T18:25:19Z","timestamp":1765477519000},"page":"e0337460","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Exploring the link between osteoporosis and stroke risk: An exploratory study based on 2017\u20132018 NHANES clinical data and 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