基于铁代谢相关基因评分的"气血-脏腑"证候量化模型探索OA

Objective To explore the application value of iron metabolism-related gene scores in the quantitative assessment of"Qi-Blood"and"Zang-Fu"patterns in traditional Chinese medicine(TCM)by comparing the differences between global iron metabolism gene scores and disease-specific intersection gene scores across six diseases.Methods Transcriptomic data for breast cancer,pancreatic cancer,Alzheimer's disease(AD),major depressive disorder(MDD),acute kidney injury(AKI),and meningitis were obtained from the GEO database.A total of 775 iron metabolism-related genes were compiled.Differential expression analysis was performed using limma,and gene scores were calculated separately using the global gene set and the disease-specific intersect gene sets via ssGSEA.The discriminative performance of the two scoring strategies was compared,and enrichment analyses were conducted using clusterProfiler.Results The global iron metabolism gene score showed a significant difference only in breast cancer(P<0.01),with no statistical significance in the other five diseases.In contrast,the disease-specific intersect gene score significantly distinguished disease from control groups in breast cancer(P=4.75×10-17),pancreatic cancer(P<0.001),AD(P=2.73×10-11),MDD(P<0.001),and meningitis(P<0.01),but not in AKI.Breast cancer was enriched in the HIF-1 pathway,pancreatic cancer in ferroptosis,AD in oxidative phosphorylation,MDD in cytochrome P450,AKI in IL-17,and meningitis in mTOR signaling.Conclusion The global iron metabolism gene score reflects the overall"Qi-Blood"background of the body with relatively low sensitivity,whereas the disease-specific intersect gene score reflects local iron metabolic dysregulation in specific"Zang-Fu"organs under disease conditions,exhibiting higher sensitivity.The differential performance of these two scoring approaches suggests that iron metabolism-related gene scores may serve as a quantitative bridge linking the macro-level theory of Qi-Blood and Zang-Fu to micro-level molecular evidence,offering new insights for the objective evaluation of TCM patterns.