Qingqing Zhang1, Qidi Zhang2, Binghang Li2, Ying Qu2, Zhenghong Li2, Lungen Lu2, Rongzhou Li1, Xiaobo Cai2. 1. Department of Gastroenterology, Ruian People's Hospital, Wenzhou, Zhejiang Province 325200, China. 2. Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China.
Abstract
METHODS: Differential expression of five selected miRNAs (hsa-mir-1225-3p, hsa-mir-1238, hsa-miR-3162-3P, hsa-miR-4721, and hsa-miR-H7) was verified by qRT-PCR in the plasma of 83 patients and 20 healthy controls. The relative expression of these miRNAs was analyzed in different groups to screen target miRNA. A logistic regression analysis was performed to assess factors associated with fibrosis progression. The receiver operating characteristic (ROC) curve and discriminant analyses validated the ability of these predicted variables to discriminate the nonsignificant liver fibrosis group from the significant liver fibrosis group. Furthermore, the established models were compared with other prediction models to evaluate the diagnostic efficiency. RESULTS: These five tested miRNAs all had signature correlations with hepatic fibrotic level (p < 0.05), and the upregulation trends were consistent with miRNA microarray analysis previously. The multivariate logistic regression analysis identified that a model of five miRNAs (miR-5) had a high diagnostic accuracy in discrimination of different stages of liver fibrosis. The ROC showed that the miR-5 has excellent value in diagnosis of fibrosis, even better than the Forns score, FIB-4, S index, and APRI. GO functions of different miRNAs mainly involved in various biological processes were markedly involved in HBV and revealed signaling pathways dysregulated in liver fibrosis of CHB patients. CONCLUSIONS: It was validated that the combination of these five miRNAs was a new set of promising molecular diagnostic markers for liver fibrosis. The diagnosis model (miR-5) can distinguish significant and nonsignificant liver fibrosis with high sensitivity and specificity.
METHODS: Differential expression of five selected miRNAs (hsa-mir-1225-3p, hsa-mir-1238, hsa-miR-3162-3P, hsa-miR-4721, and hsa-miR-H7) was verified by qRT-PCR in the plasma of 83 patients and 20 healthy controls. The relative expression of these miRNAs was analyzed in different groups to screen target miRNA. A logistic regression analysis was performed to assess factors associated with fibrosis progression. The receiver operating characteristic (ROC) curve and discriminant analyses validated the ability of these predicted variables to discriminate the nonsignificant liver fibrosis group from the significant liver fibrosis group. Furthermore, the established models were compared with other prediction models to evaluate the diagnostic efficiency. RESULTS: These five tested miRNAs all had signature correlations with hepatic fibrotic level (p < 0.05), and the upregulation trends were consistent with miRNA microarray analysis previously. The multivariate logistic regression analysis identified that a model of five miRNAs (miR-5) had a high diagnostic accuracy in discrimination of different stages of liver fibrosis. The ROC showed that the miR-5 has excellent value in diagnosis of fibrosis, even better than the Forns score, FIB-4, S index, and APRI. GO functions of different miRNAs mainly involved in various biological processes were markedly involved in HBV and revealed signaling pathways dysregulated in liver fibrosis of CHB patients. CONCLUSIONS: It was validated that the combination of these five miRNAs was a new set of promising molecular diagnostic markers for liver fibrosis. The diagnosis model (miR-5) can distinguish significant and nonsignificant liver fibrosis with high sensitivity and specificity.
Authors: Patrick S Mitchell; Rachael K Parkin; Evan M Kroh; Brian R Fritz; Stacia K Wyman; Era L Pogosova-Agadjanyan; Amelia Peterson; Jennifer Noteboom; Kathy C O'Briant; April Allen; Daniel W Lin; Nicole Urban; Charles W Drescher; Beatrice S Knudsen; Derek L Stirewalt; Robert Gentleman; Robert L Vessella; Peter S Nelson; Daniel B Martin; Muneesh Tewari Journal: Proc Natl Acad Sci U S A Date: 2008-07-28 Impact factor: 11.205