A composite biomarker using multiparametric magnetic resonance imaging and blood analytes accurately identifies patients with non-alcoholic steatohepatitis and significant fibrosis.
Biomarkers
/ blood
Biopsy
Cross-Sectional Studies
Elasticity Imaging Techniques
/ methods
Female
Fibrosis
/ blood
Humans
Liver
/ pathology
Liver Cirrhosis
/ blood
Male
Middle Aged
Multiparametric Magnetic Resonance Imaging
/ methods
Non-alcoholic Fatty Liver Disease
/ blood
Prospective Studies
ROC Curve
Retrospective Studies
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
17 09 2020
17 09 2020
Historique:
received:
24
04
2020
accepted:
21
08
2020
entrez:
18
9
2020
pubmed:
19
9
2020
medline:
15
12
2020
Statut:
epublish
Résumé
Non-alcoholic steatohepatitis (NASH) is major health burden lacking effective pharmacological therapies. Clinical trials enrol patients with histologically-defined NAFLD (non-alcoholic fatty liver disease) activity score (NAS) ≥ 4 and Kleiner-Brunt fibrosis stage (F) ≥ 2; however, screen failure rates are often high following biopsy. This study evaluated a non-invasive MRI biomarker, iron-corrected T1 mapping (cT1), as a diagnostic pre-screening biomarker for NASH. In a retrospective analysis of 86 biopsy confirmed NAFLD patients we explored the potential of blood and imaging biomarkers, both in isolation and in combination, to discriminate those who have NAS ≥ 4 and F ≥ 2 from those without. Stepwise logistic regression was performed to select the optimal combination of biomarkers, diagnostic accuracy was determined using area under the receiver operator curve and model validated confirmed with and fivefold cross-validation. Results showed that levels of cT1, AST, GGT and fasting glucose were all good predictors of NAS ≥ 4 and F ≥ 2, and the model identified the combination of cT1-AST-fasting glucose (cTAG) as far superior to any individual biomarker (AUC 0.90 [0.84-0.97]). This highlights the potential utility of the composite cTAG score for screening patients prior to biopsy to identify those suitable for NASH clinical trial enrolment.
Identifiants
pubmed: 32943694
doi: 10.1038/s41598-020-71995-8
pii: 10.1038/s41598-020-71995-8
pmc: PMC7499258
doi:
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
15308Subventions
Organisme : Chief Scientist Office
ID : SCD/20
Pays : United Kingdom
Références
Dai, W. et al. Prevalence of nonalcoholic fatty liver disease in patients with type 2 diabetes mellitus: a meta-analysis. Medicine (Baltimore) 96, e8179 (2017).
Friedman, S. L., Neuschwander-Tetri, B. A., Rinella, M. & Sanyal, A. J. Mechanisms of NAFLD development and therapeutic strategies. Nat. Med. 24, 908–922 (2018).
pubmed: 29967350
pmcid: 6553468
Younossi, Z. et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat. Rev. Gastroenterol. Hepatol. 15, 11–20 (2018).
pubmed: 28930295
Williams, C. D. et al. Prevalence of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis among a largely middle-aged population utilizing ultrasound and liver biopsy: a prospective study. Gastroenterology 140, 124–131 (2011).
pubmed: 20858492
Hyysalo, J. et al. A population-based study on the prevalence of NASH using scores validated against liver histology. J. Hepatol. 60, 839–846 (2014).
pubmed: 24333862
Younossi, Z. M. et al. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: a systematic review and meta-analysis. J. Hepatol. 71, 793–801 (2019).
pubmed: 31279902
Kleiner, D. E. & Makhlouf, H. R. Histology of NAFLD and NASH in adults and children. Clin. Liver Dis. 20, 293–312 (2016).
pubmed: 27063270
Younossi, Z. et al. GS-06-positive results from REGENERATE: a phase 3 international, randomized, placebo-controlled study evaluating obeticholic acid treatment for NASH. J. Hepatol. 70, e5 (2019).
Kleiner, D. et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 41, 1313–1321 (2005).
pubmed: 15915461
Angulo, P. et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology 45, 846–854 (2007).
pubmed: 17393509
Ekstedt, M. et al. Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up. Hepatology 61, 1547–1554 (2015).
pubmed: 25125077
Pioglitazone vs vitamin E vs placebo for treatment of non-diabetic patients with nonalcoholic steatohepatitis (PIVENS). https://clinicaltrials.gov/ct2/show/NCT00063622 .
Friedman, S. L. et al. A randomized, placebo-controlled trial of cenicriviroc for treatment of nonalcoholic steatohepatitis with fibrosis. Hepatology 67, 1754–1767 (2018).
pubmed: 28833331
pmcid: 5947654
Ferreira, V. M. et al. Non-contrast T1-mapping detects acute myocardial edema with high diagnostic accuracy: a comparison to T2-weighted cardiovascular magnetic resonance. J. Cardiovasc. Magn. Reson. 14, 42 (2012).
pubmed: 22720998
pmcid: 3424120
Rial, B., Robson, M. D., Neubauer, S. & Schneider, J. E. Rapid quantification of myocardial lipid content in humans using single breath-hold 1H MRS at 3 Tesla. Magn. Reson. Med. 66, 619–624 (2011).
pubmed: 21721038
pmcid: 3427889
Banerjee, R. et al. Multiparametric magnetic resonance for the non-invasive diagnosis of liver disease. J. Hepatol. 61, 69–77 (2014).
Pavlides, M. et al. Multiparametric magnetic resonance imaging predicts clinical outcomes in patients with chronic liver disease. J. Hepatol. 64, 308–315 (2016).
pubmed: 26471505
pmcid: 4751288
Garg, P., Saunders, L. C., Swift, A. J., Wild, J. M. & Plein, S. Role of cardiac T1 mapping and extracellular volume in the assessment of myocardial infarction. Anatol. J. Cardiol. 19, 404–411 (2018).
pubmed: 29638222
pmcid: 5998858
Wood, J. C. et al. MRI R2 and R2* mapping accurately estimates hepatic iron concentration in transfusion-dependent thalassemia and sickle cell disease patients. Blood 106, 1460–1465 (2005).
pubmed: 15860670
pmcid: 1895207
Tunnicliffe, E. M., Banerjee, R., Pavlides, M., Neubauer, S. & Robson, M. D. A model for hepatic fibrosis: the competing effects of cell loss and iron on shortened modified Look-Locker inversion recovery T1 (shMOLLI-T1) in the liver. J. Magn. Reson. Imaging 45, 450–462 (2017).
pubmed: 27448630
Pavlides, M. et al. Multi-parametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease severity. Liver Int. 37, 1065–1073 (2017).
pubmed: 27778429
pmcid: 5518289
Park, C. C. et al. Magnetic resonance elastography vs transient elastography in detection of fibrosis and noninvasive measurement of steatosis in patients with biopsy-proven nonalcoholic fatty liver disease. Gastroenterology 152, 598-607.e2 (2017).
pubmed: 27911262
Tang, A. et al. Nonalcoholic fatty liver disease: MR imaging of liver proton density fat fraction to assess hepatic steatosis. Radiology 267, 422–431 (2013).
pubmed: 23382291
pmcid: 3632805
Middleton, M. S. et al. Agreement between magnetic resonance imaging proton density fat fraction measurements and pathologist-assigned steatosis grades of liver biopsies from adults with nonalcoholic steatohepatitis michael. Gastroenterology 153, 753–761 (2017).
pubmed: 28624576
pmcid: 5695870
Tang, A. et al. Accuracy of MR imaging-estimated proton density fat fraction for classification of dichotomized histologic steatosis grades in nonalcoholic fatty liver disease. Radiology 274, 416–425 (2015).
pubmed: 25247408
Idilman, I. S. et al. Hepatic steatosis: quantification by proton density fat fraction with MR imaging versus liver biopsy. Radiology 267, 767–775 (2013).
pubmed: 23382293
Wildman-Tobriner, B. et al. Association between magnetic resonance imaging-proton density fat fraction and liver histology features in patients with nonalcoholic fatty liver disease or nonalcoholic steatohepatitis. Gastroenterology 155, 1428-1435.e2 (2018).
pubmed: 30031769
pmcid: 6456892
Jayakumar, S. et al. Longitudinal correlations between MRE, MRI-PDFF, and liver histology in patients with non-alcoholic steatohepatitis: analysis of data from a phase II trial of selonsertib. J. Hepatol. 70, 133–141 (2019).
pubmed: 30291868
Permutt, Z. et al. Correlation between liver histology and novel magnetic resonance imaging in adult patients with non-alcoholic fatty liver disease: MRI accurately quantifies hepatic steatosis in NAFLD. Aliment. Pharmacol. Ther. 36, 22–29 (2012).
pubmed: 22554256
pmcid: 3437221
Loomba, R. et al. Ezetimibe for the treatment of nonalcoholic steatohepatitis: Assessment by novel magnetic resonance imaging and magnetic resonance elastography in a randomized trial (MOZART trial). Hepatology 61, 1239–1250 (2015).
pubmed: 25482832
pmcid: 4407930
Neuschwander-Tetri, B. et al. Farnesoid X nuclear receptor ligand obeticholic acid for non- cirrhotic, non-alcoholic steatohepatitis (FLINT): a multicentre, randomised, placebo-controlled trial. Lancet 14, 956–965 (2015).
Vilar-Gomez, E. & Chalasani, N. Non-invasive assessment of non-alcoholic fatty liver disease: clinical prediction rules and blood-based biomarkers. J. Hepatol. 68, 305–315 (2018).
pubmed: 29154965
McDonald, N. et al. Multiparametric magnetic resonance imaging for quantitation of liver disease: a two-centre cross-sectional observational study. Sci. Rep. 8, 9189 (2018).
pubmed: 29907829
pmcid: 6003924
Pavlides, M. et al. Multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease severity. Liver Int. 37, 1065–1073 (2017).
pubmed: 27778429
pmcid: 5518289
Eddowes, P. et al. Utility and cost evaluation of multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease. Aliment. Pharmacol. Ther. 47, 631–644 (2017).
pubmed: 29271504
Wyatt, J., Hubscher, S. & Bellamy, C. Tissue pathways for liver biopsies for the investigation of medical disease and for focal lesions. https://www.rcpath.org/uploads/assets/2921c666-0f66-4272-820c16db2acaff99/Tissue-pathways-liver-biopsies-Mar-14.pdf (2014).
Bachtiar, V. et al. Repeatability and reproducibility of multiparametric magnetic resonance imaging of the liver. PLoS ONE 14, e0214921 (2019).
pubmed: 30970039
pmcid: 6457552
R Core Team. R: A Language and Environment for Statistical Computing. (2020).
W. N. Venables, B. D. R. Modern Applied Statistics with S. (Springer, 2002).
Cribari-Neto, F. & Zarkos, S. Improved test statistics for multivariate regression. Econ. Lett. 49, 113–120 (1995).
Demler, O. V., Pencina, M. J. & D’Agostino, R. B. Misuse of DeLong test to compare AUCs for nested models. Stat. Med. 31, 2577–2587 (2012).
pubmed: 22415937
pmcid: 3684152
Newsome, P. N. et al. FibroScan-AST (FAST) score for the non-invasive identification of patients with non-alcoholic steatohepatitis with significant activity and fibrosis: a prospective derivation and global validation study. Lancet Gastroenterol Hepatol (2020).
Harrison, S. A. et al. Utility and variability of three non-invasive liver fibrosis imaging modalities to evaluate efficacy of GR-MD-02 in subjects with NASH and bridging fibrosis during a phase-2 randomized clinical trial. PLoS ONE 13, e0203054 (2018).
pubmed: 30192782
pmcid: 6128474
Harrison, S. A. et al. NGM282 improves liver fibrosis and histology in 12 weeks in patients with nonalcoholic steatohepatitis. Hepatology 71, 1198–1212 (2020).
pubmed: 30805949
Marchesini, G., Moscatiello, S., Di Domizio, S. & Forlani, G. Obesity-associated liver disease. J. Clin. Endocrinol. Metab. 93, S74-80 (2008).
pubmed: 18987273
Sorbi, D., Boynton, J. & Lindor, K. D. The ratio of aspartate aminotransferase to alanine aminotransferase: potential value in differentiating nonalcoholic steatohepatitis from alcoholic liver disease. Am. J. Gastroenterol. 94, 1018–1022 (1999).
pubmed: 10201476
Neuschwander-Tetri, B. A. & Caldwell, S. H. Nonalcoholic steatohepatitis: summary of an AASLD single topic conference. Hepatology 37, 1202–1219 (2003).
pubmed: 12717402
Sanyal, A. J. et al. Endpoints and clinical trial design for nonalcoholic steatohepatitis. Hepatology 54, 344–353 (2011).
pubmed: 21520200
pmcid: 4014460
Amarapurkar, D. N. et al. Nonalcoholic steatohepatitis (NASH) with diabetes: predictors of liver fibrosis. Ann. Hepatol. 5, 30–33 (2006).
pubmed: 16531962
Fujii, H. et al. HOMA-IR: An independent predictor of advanced liver fibrosis in nondiabetic non-alcoholic fatty liver disease. J. Gastroenterol. Hepatol. 34, 1390–1395 (2019).
pubmed: 30600551
Gastaldelli, A. & Cusi, K. From NASH to diabetes and from diabetes to NASH: Mechanisms and treatment options. JHEP Rep. 1, 312–328 (2019).
pubmed: 32039382
pmcid: 7001557
Daniels, S. J. et al. ADAPT: an algorithm incorporating PRO-C3 accurately identifies patients with NAFLD and advanced fibrosis. Hepatology 69, 1075–1086 (2019).
pubmed: 30014517
Liang, J. et al. A noninvasive score model for prediction of NASH in patients with chronic hepatitis B and nonalcoholic fatty liver disease. Hindawi BioMed Res. Int. (2017).
Harrison, S. A. Nonalcoholic fatty liver disease and fibrosis progression: the good, the bad, and the unknown. Clin. Gastroenterol. Hepatol. 13, 655–657 (2015).
pubmed: 25478921