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Integrated transcriptomic analysis identifies an AKT1-associated metabolic-inflammatory signature in osteoporosis
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DOI：10.1007/s10238-026-02263-8.png)
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Abstract
En 中文
Osteoporosis is a significant global health challenge, and low bone mineral density (Low-BMD) is a major clinical feature and risk indicator of osteoporosis. Fatty acid metabolism has been increasingly implicated in bone remodeling and inflammatory regulation, but the transcriptomic links between fatty acid metabolism and immune-inflammatory alterations in Low-BMD remain unclear. We integrated three GEO datasets, including 60 High-BMD controls and 59 Low-BMD subjects. Differential expression analysis, immune infiltration analysis, NMF clustering, WGCNA, pseudotime analysis, and machine learning were performed to identify fatty acid metabolism-related genes associated with Low-BMD. AKT1 knockdown was used to evaluate its potential role in regulating inflammatory mediators. Eighteen fatty acid metabolism-related differentially expressed genes were identified between High-BMD and Low-BMD samples and were enriched in inflammatory, immune, and osteoclast-related pathways. NMF clustering revealed two Low-BMD molecular subtypes with distinct metabolic and immune-inflammatory features. Machine learning identified an AKT1-containing diagnostic signature with good predictive performance, and AKT1 was positively correlated with inflammatory response scores and inflammatory markers. Quantitative Real-time PCR confirmed Akt1 knockdown, and ELISA showed reduced IL-6, TNF-α, and IL-1β secretion in MC3T3-E1 cells. AKT1 may serve as a fatty acid metabolism-related candidate gene associated with immune-inflammatory remodeling and inflammatory mediator regulation in Low-BMD. These findings suggest a potential AKT1-associated metabolic-inflammatory regulatory relationship and provide candidate biomarkers for future validation in osteoporosis-related bone loss.
Keywords:
Osteoporosis
Low-BMD
Fatty acid metabolism
AKT1
Inflammation
Immune microenvironment
Machine learning
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