Exploring the molecular intersections of osteoporosis and sarcopenia: An integrated bioinformatics and experimental validation

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Authors: Yan Lv, Yongjun Du, Peng Lin, Jiamian Liu, Silin Pu, Sheng Lu
Cited by: 2
References: 44

Abstract

Osteoporosis and sarcopenia are age-related degenerative diseases that frequently co-occur in the older adults, yet their shared molecular mechanisms remain poorly understood. This study aimed to identify common biomarkers. By utilizing the GEO database, differential and enrichment analyses were conducted to identify genes that are commonly expressed in both diseases. Subsequently, key genes were identified through four types of machine learning and six types of immune infiltration analyses. Finally, the Dual Condition Sarcopenia and Osteoporosis (DSO) model was established by combining bilateral ovariectomy with natural aging to validate the key genes. A total of 577 and 625 genes were identified in the osteoporosis (GSE156508) and sarcopenia (GSE226151), respectively. GO, KEGG, and GSEA analyses revealed that osteoporosis-related genes were enriched in muscle development and myogenesis pathways, while sarcopenia-related genes were linked to osteoclast differentiation and inflammatory responses. Venn analysis identified 20 genes shared by both diseases. Four machine learning algorithms identified five key genes: APOC1, ENPP5, FBXL22, IRS1, and PAQR4. Among them, PAQR4 showed the highest predictive value in ROC analysis and was consistently downregulated in both training and validation datasets. Immune infiltration analysis indicated altered neutrophil levels, notably reduced in osteoporotic skeletal muscle. Experimental validation confirmed decreased PAQR4 expression in both bone and muscle tissues of the DSO model. These findings highlight PAQR4 as a potential biomarker and a candidate molecule of interest for osteosarcopenia. • Integrated bioinformatics and animal validation reveal PAQR4 as a key osteosarcopenia gene. • Machine learning identifies PAQR4 as the top predictive marker for bone–muscle comorbidity. • PAQR4 downregulation links osteoporosis and sarcopenia via lipid metabolism and immunity. • Immune infiltration analysis suggests neutrophil involvement in osteosarcopenia pathogenesis. • Study provides novel molecular insights into bone–muscle crosstalk and potential biomarkers.

Fields of Study & Subjects

Bone Metabolism and Diseases Bone health and osteoporosis research GDF15 and Related Biomarkers

Publication details

Journal / source
Experimental Gerontology
Publisher
Elsevier BV
Volume
214
Pages
113033–113033
Publication date
12 January 2026
Language
EN