Correlation of Hypoxia-inducible facto-1α and C-reactive protein with disease evaluation in patients with ulcerative colitis.

OBJECTIVE To investigate the expression levels of hypoxia-inducible factor-1α (HIF-1α) and C-reactive protein (CRP) in patients with ulcerative colitis and correlations of HIF-1α and CRP levels with disease severity. METHODS A total of 82 patients with confirmed ulcerative colitis were enrolled in this study and according to the disease severity grading, these patients were assigned into three groups: mild group (n=25), moderate group (n=31) and severe group (n=26). And other 30 patients without ulcerative colitis as demonstrated by colonoscopy examination were enrolled in control group in the same period. HIF-1α and CRP levels were detected by ELISA and Real-time PCR and compared among different groups. Pearson's correlation analysis was performed to evaluate the correlations of HIF-1α and CRP levels with disease severity. Logistic regression analysis was used to explore risk factors of disease severity in patients with ulcerative colitis. RESULTS The expression levels of HIF-1α and CRP in ulcerative colitis group were significantly higher than those in control group (all P<0.001). The levels of HIF-1α and CRP in patients with ulcerative colitis increased remarkably with the increase of disease severity. Patients in mild group had the lowest levels of HIF-1α and CRP, while patients in severe group had the highest levels of HIF-1α and CRP. Logistic regression analysis showed that the expression of HIF-1α and CRP were the risk factors for disease severity of ulcerative colitis (all P<0.001). And Pearson correlation analysis showed that HIF-1α and CRP levels were significantly associated with Rachmilewitz score and disease activity index (DAI), respectively (all P<0.001). CONCLUSION The levels of HIF-1α and CRP were up-regulated in patients with ulcerative colitis and positively correlated with the progression of ulcerative colitis, indicating that the detection of HIF-1α and CRP expression could be used for predicting the disease severity.