A Novel Risk Prediction Model for Chronic Atrophic Gastritis Based on Traditional Chinese Medicine Spleen Deficiency and Blood Stasis Syndromes and Gastric Stem Cell Dynamics
10.13422/j.cnki.syfjx.20251411
- VernacularTitle:基于中医脾虚、血瘀证和胃干细胞动力学构建慢性萎缩性胃炎新型风险预测模型
- Author:
Qingqing ZHANG
1
;
Di WU
2
;
Fengyun GUO
1
;
Shengnan YANG
3
;
Ruiying ZHANG
3
;
Lijing BAO
1
;
Ping WANG
1
Author Information
1. Xiyuan Hospital of China Academy of Chinese Medical Sciences， Beijing 100091，China
2. The First Hospital of Heilongjiang University of Traditional Chinese Medicine， Harbin 150040，China
3. Graduate School， Beijing University of Chinese Medicine， Beijing 100029，China
- Publication Type:Journal Article
- Keywords:
chronic atrophic gastritis;
risk prediction model;
spleen deficiency syndrome;
blood stasis syndrome;
gastric stem cells
- From:
Chinese Journal of Experimental Traditional Medical Formulae
2026;32(20):191-200
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveTo construct a risk prediction model for chronic atrophic gastritis （CAG） that combines disease and syndrome by integrating spleen deficiency and blood stasis syndrome scores， gastric stem cell marker analysis， and network pharmacology and to elucidate the mechanism link between spleen deficiency， blood stasis， and gastric stem cell dysregulation. MethodsA total of 60 patients were stratified into high-risk CAG， low-risk CAG， and non-atrophic groups based on the operative link for gastritis assessment （OLGA）/operative link for gastric intestinal metaplasia assessment （OLGIM） stages. General data and syndrome scores of the patients were collected. Immunohistochemistry was employed to measure the protein levels of leucine-rich repeat-containing G protein-coupled receptor 5 （LGR5）， trefoil factor 2 （TFF2）， and β-catenin in gastric mucosa across groups. Transcriptomic data （GSE130823） from the Gene Expression Omnibus （GEO） database were analyzed to validate the expression of these molecular markers at the gene level. A Firth penalized maximum likelihood logistic regression model was employed to integrate clinical， molecular， and TCM syndrome data to develop a CAG risk prediction model. Finally， network pharmacology analysis was conducted on spleen-invigorating herbs （Astragali Radix， Atractylodis Macrocephalae Rhizoma， and Dioscorea Rhizoma） and blood-activating herbs （Hedyotis diffusa， Salviae Miltiorrhizae Radix et Rhizoma， and Curcumae Rhizoma） to identify overlapping targets between these herbs and differentially expressed genes between low-grade intraepithelial neoplasia （LGIN） and gastritis， thereby clarifying the role of spleen deficiency and blood stasis in CAG progression from a pharmacological perspective. ResultsHigh-risk CAG patients exhibited higher blood stasis scores （4.60±1.50，2.62±1.32， P<0.01）， progressive nuclear accumulation of β-catenin （A 0.28-0.53， P<0.01）， and an increased LGR5+/TFF2+ ratio （A 1.02-1.92， P<0.01）. Blood stasis scores were correlated with LGR5/TFF2 imbalance （P=0.03） and activation of the Wnt/β-catenin signaling pathway （CTNNB1 increase， log2=0.78）. The integrated prediction model （blood stasis score≥5 + β-catenin>0.38 + LGR5/TFF2>1.5） outperformed a pure biomarker approach ［Area Under the Curve （AUC） 0.92，0.89， ΔAUC=0.03， P=0.02］. Moreover， network pharmacology revealed 66 overlapping targets between spleen-invigorating/blood-activating herbs and LGIN， which were functionally enriched in mucosal repair and anti-oxidative stress， and negatively correlated with the Wnt/β-catenin signaling pathway （P<0.01）. ConclusionThis study developed an integrated risk prediction model for CAG by combining TCM spleen deficiency and blood stasis syndromes with gastric stem cell molecular markers. Furthermore， it proposed for the first time the "blood stasis-Wnt/β-catenin-stem cell axis" hypothesis， preliminarily elucidating that spleen deficiency and blood stasis may exacerbate gastric stem cell dysregulation and promote malignant transformation of CAG through hypoxia-induced Wnt activation. This provides a theoretical foundation and a translational tool for risk stratification and multi-target TCM intervention in CAG.
