ArticleBMC public health2024
An analysis of the potential association between obstructive sleep apnea and osteoporosis from the perspective of transcriptomics and NHANES.
Article in BMC public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Integrating epidemiological and transcriptomic data reveals novel lipid metabolic drivers of obstructive sleep apnea.Nutrition & metabolism · 2026Article
- Caffeine intake is inversely associated with osteoporosis risk based on cross-sectional and genetic evidence.Scientific reports · 2025Article
- Exploring the potential biomarkers between stroke and obstructive sleep apnea by WGCNA and machine learning.Sleep & breathing = Schlaf & Atmung · 2025Article
- Association between body roundness index and obstructive sleep apnea: a cross-sectional study from the NHANES (2005-2008 to 2015-2020).BMC oral health · 2025Article
- Associations of fat, bone, and muscle indices with disease severity in patients with obstructive sleep apnea hypopnea syndrome.Sleep & breathing = Schlaf & Atmung · 2025Article
- AI-driven bone mineral density prediction from chest x-rays and its association with obstructive sleep apnea.PloS one · 2025Article
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Authors and funding
8 authors.
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Abstract
backgroundObstructive sleep apnea (OSA) and osteoporosis (OP) are prevalent diseases in the elderly. This study aims to reveal the clinical association between OSA and OP and explore potential crosstalk gene targets.
methodsParticipants diagnosed with OSA in the National Health and Nutrition Examination Survey (NHANES) database (2015-2020) were included, and OP was diagnosed based on bone mineral density (BMD). We explored the association between OSA and OP, and utilized multivariate logistic regression analysis and machine learning algorithms to explore the risk factors for OP in OSA patients. Overlapping genes of comorbidity were explored using differential expression analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Random Forest (RF) methods.
resultsIn the OSA population, the weighted prevalence of OP was 7.0%. The OP group had more females, lower body mass index (BMI), and more low/middle-income individuals compared to the non-OP group. Female gender and lower BMI were identified as independent risk factors for OP in OSA patients. Gene expression profiling revealed 8 overlapping differentially expressed genes in OP and OSA patients. KCNJ1, NPR3 and WT1-AS were identified as shared diagnostic biomarkers or OSA and OP, all of which are associated with immune cell infiltration.
conclusionThis study pinpointed female gender and lower BMI as OP risk factors in OSA patients, and uncovered three pivotal genes linked to OSA and OP comorbidity, offering fresh perspectives and research targets.
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