Irvine Katharine M, Wockner Leesa F, Hoffmann Isabell, Horsfall Leigh U, Fagan Kevin J, Bijin Veonice, Lee Bernett, Clouston Andrew D, Lampe Guy, Connolly John E, Powell Elizabeth E
Centre for Liver Disease Research, School of Medicine, The University of Queensland, Brisbane, Australia.
Statistics Unit, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
PLoS One. 2016 Nov 18;11(11):e0167001. doi: 10.1371/journal.pone.0167001. eCollection 2016.
Non-invasive markers of liver fibrosis are urgently required, especially for use in non-specialist settings. The aim of this study was to identify novel serum biomarkers of advanced fibrosis.
We performed an unbiased screen of 120 serum analytes including cytokines, chemokines and proteases in 70 patients (35 without fibrosis, 35 with cirrhosis on biopsy), and selected a panel of 44 candidate biomarkers, which were subsequently measured in a mixed-etiology cohort of 432 patients with known serum HA, PIIINP and TIMP1 (which comprise the validated Enhanced Liver Fibrosis (ELF) test). Multivariate logistic regression modelling was used to generate models for the prediction of advanced or significant fibrosis (METAVIR ≥F3 and ≥F2, respectively); in addition to identifying biomarkers of disease activity and steatohepatitis.
Seventeen analytes were significantly differentially expressed between patients with no advanced fibrosis and patients with advanced fibrosis, the most significant being hyaluronic acid (HA) and matrix metalloproteinase (MMP) 7 (p = 2.9E-41 and p = 1.0E-26, respectively). The optimal model for the prediction of advanced fibrosis comprised HA, MMP7, MMP1, alphafetoprotein (AFP) and the AST to platelet ratio index (APRI). We demonstrate enhanced diagnostic accuracy (AUROC = 0.938) compared to a model comprising HA, PIIINP and TIMP1 alone (ELF) (AUROC = 0.898, p<0.0001, De Long's test).
We have identified novel serum biomarkers of advanced liver fibrosis, which have the potential to enhance the diagnostic accuracy of established biomarkers. Our data suggest MMP7 is a valuable indicator of advanced fibrosis and may play a role in liver fibrogenesis.
迫切需要肝脏纤维化的非侵入性标志物,尤其是用于非专科环境。本研究的目的是识别晚期纤维化的新型血清生物标志物。
我们对70例患者(35例无纤维化,35例活检证实为肝硬化)的120种血清分析物进行了无偏筛选,包括细胞因子、趋化因子和蛋白酶,并选择了一组44种候选生物标志物,随后在432例已知血清透明质酸(HA)、III型前胶原氨基端肽(PIIINP)和基质金属蛋白酶组织抑制因子1(TIMP1)(构成经过验证的增强肝纤维化(ELF)检测)的混合病因队列中进行测量。使用多变量逻辑回归模型生成预测晚期或显著纤维化(分别为METAVIR≥F3和≥F2)的模型;此外还识别疾病活动和脂肪性肝炎的生物标志物。
17种分析物在无晚期纤维化患者和晚期纤维化患者之间有显著差异表达,最显著的是透明质酸(HA)和基质金属蛋白酶(MMP)7(分别为p = 2.9E-41和p = 1.0E-26)。预测晚期纤维化的最佳模型包括HA、MMP7、MMP1、甲胎蛋白(AFP)和天冬氨酸氨基转移酶与血小板比值指数(APRI)。与仅包含HA、PIIINP和TIMP1的模型(ELF)(AUROC = 0.898,p<0.0001,De Long检验)相比,我们证明了诊断准确性有所提高(AUROC = 0.938)。
我们识别出了晚期肝纤维化的新型血清生物标志物,其有可能提高现有生物标志物的诊断准确性。我们的数据表明MMP7是晚期纤维化的有价值指标,可能在肝纤维化形成中起作用。