Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Noninvasive biomarkers in NAFLD and NASH — current progress and future promise

Nature Reviews Gastroenterology & Hepatology volume 15, pages 461–478 (2018)Cite this article

Subjects

Abstract

Nonalcoholic fatty liver disease (NAFLD) affects 25% of the global adult population and is the most common chronic liver disease worldwide. Nonalcoholic steatohepatitis (NASH) is the active form of NAFLD, with hepatic necroinflammation and faster fibrosis progression. With an increasing number of patients developing NASH-related end-stage liver disease and pharmacological treatments on the horizon, there is a pressing need to develop NAFLD and NASH biomarkers for prognostication, selection of patients for treatment and monitoring. This requirement is particularly true as liver biopsy utility is limited by its invasive nature, poor patient acceptability and sampling variability. This article reviews current and potential biomarkers for different features of NAFLD, namely, steatosis, necroinflammation and fibrosis. For each biomarker, we evaluate its accuracy, reproducibility, responsiveness, feasibility and limitations. We cover biochemical, imaging and genetic biomarkers and discuss biomarker discovery in the omics era.

Key points

  • When assessing a patient with nonalcoholic fatty liver disease (NAFLD), the key histological features of interest include the degree of steatosis, necroinflammation and fibrosis.

  • MRI-estimated proton density fat fraction is currently the most accurate test to quantify hepatic steatosis and can be considered the gold standard.

  • Magnetic resonance elastography is the most accurate fibrosis test, yet its use is limited by cost and availability.

  • Controlled attenuation parameter and liver stiffness measurement by transient elastography also enables simultaneous assessment of hepatic steatosis and fibrosis, albeit with lower accuracy and success rates than MRI-based methods.

  • Plasma cytokeratin 18 (CK18) fragment levels are a marker of hepatocyte apoptosis and represent the most extensively evaluated biomarker of steatohepatitis, although the accuracy is modest.

  • A number of gene polymorphisms (such as those in PNPLA3 and TM6SF2) have been shown to correlate with NAFLD and its severity, yet their role in patient assessment remains to be established.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Management of NAFLD according to disease severity.
Fig. 2: Ultrasound-based measurement of liver stiffness or elasticity.
Fig. 3: Noninvasive assessment of NAFLD and NASH.

Similar content being viewed by others

References

  1. Younossi, Z. M. et al. Global epidemiology of nonalcoholic fatty liver disease-meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology 64, 73–84 (2016).

    Article  PubMed  Google Scholar 

  2. Singh, S. et al. Fibrosis progression in nonalcoholic fatty liver versus nonalcoholic steatohepatitis: a systematic review and meta-analysis of paired-biopsy studies. Clin. Gastroenterol. Hepatol. 13, 643–654 (2015).

    Article  PubMed  Google Scholar 

  3. Goldberg, D. et al. Changes in the prevalence of hepatitis C virus infection, nonalcoholic steatohepatitis, and alcoholic liver disease among patients with cirrhosis or liver failure on the waitlist for liver transplantation. Gastroenterology 152, 1090–1099.e1 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  4. Vilar-Gomez, E. et al. Weight loss through lifestyle modification significantly reduces features of nonalcoholic steatohepatitis. Gastroenterology 149, 367–378.e5 (2015).

    Article  PubMed  Google Scholar 

  5. Wong, V. W. et al. Community-based lifestyle modification programme for non-alcoholic fatty liver disease: a randomized controlled trial. J. Hepatol. 59, 536–542 (2013).

    Article  PubMed  Google Scholar 

  6. Chalasani, N. et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology 67, 328–357 (2018).

    Article  PubMed  Google Scholar 

  7. Chitturi, S. et al. The Asia-Pacific Working Party on Nonalcoholic Fatty Liver Disease Guidelines 2017 Part 2: Management and special groups. J. Gastroenterol. Hepatol. 33, 86–98 (2018).

    Article  PubMed  Google Scholar 

  8. European Association for the Study of the Liver, European Association for the Study of Diabetes & European Association for the Study of Obesity. EASL-EASD-EASO Clinical Practice Guidelines for the management of non-alcoholic fatty liver disease. J. Hepatol. 64, 1388–1402 (2016).

    Google Scholar 

  9. Wong, V. W. et al. Pathogenesis and novel treatment options for non-alcoholic steatohepatitis. Lancet Gastroenterol. Hepatol. 1, 56–67 (2016).

    Article  PubMed  Google Scholar 

  10. McGill, D. B., Rakela, J., Zinsmeister, A. R. & Ott, B. J. A. 21-year experience with major hemorrhage after percutaneous liver biopsy. Gastroenterology 99, 1396–1400 (1990).

    Article  PubMed  CAS  Google Scholar 

  11. Ratziu, V. et al. Sampling variability of liver biopsy in nonalcoholic fatty liver disease. Gastroenterology 128, 1898–1906 (2005).

    Article  PubMed  Google Scholar 

  12. Mehta, S. H., Lau, B., Afdhal, N. H. & Thomas, D. L. Exceeding the limits of liver histology markers. J. Hepatol. 50, 36–41 (2009).

    Article  PubMed  Google Scholar 

  13. Wong, V. W. et al. The Asia-Pacific Working Party on Nonalcoholic Fatty Liver Disease Guidelines 2017 Part 1: Definition, risk factors and assessment. J. Gastroenterol. Hepatol. 33, 70–85 (2018).

    Article  PubMed  Google Scholar 

  14. 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).

    Article  PubMed  CAS  Google Scholar 

  15. Caldwell, S. H. et al. Cryptogenic cirrhosis: clinical characterization and risk factors for underlying disease. Hepatology 29, 664–669 (1999).

    Article  PubMed  CAS  Google Scholar 

  16. Bedogni, G. et al. The Fatty Liver Index: a simple and accurate predictor of hepatic steatosis in the general population. BMC Gastroenterol. 6, 33 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  17. Calori, G. et al. Fatty liver index and mortality: the Cremona study in the 15th year of follow-up. Hepatology 54, 145–152 (2011).

    Article  PubMed  CAS  Google Scholar 

  18. Lee, J. H. et al. Hepatic steatosis index: a simple screening tool reflecting nonalcoholic fatty liver disease. Dig. Liver Dis. 42, 503–508 (2010).

    Article  PubMed  CAS  Google Scholar 

  19. Saadeh, S. et al. The utility of radiological imaging in nonalcoholic fatty liver disease. Gastroenterology 123, 745–750 (2002).

    Article  PubMed  Google Scholar 

  20. Kotronen, A. et al. Prediction of non-alcoholic fatty liver disease and liver fat using metabolic and genetic factors. Gastroenterology 137, 865–872 (2009).

    Article  PubMed  CAS  Google Scholar 

  21. Poynard, T. et al. The diagnostic value of biomarkers (SteatoTest) for the prediction of liver steatosis. Comp. Hepatol. 4, 10 (2005).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  22. Yip, T. C. et al. Laboratory parameter-based machine learning model for excluding non-alcoholic fatty liver disease (NAFLD) in the general population. Aliment. Pharmacol. Ther. 46, 447–456 (2017).

    Article  PubMed  CAS  Google Scholar 

  23. Keating, S. E. et al. NAFLD in clinical practice: can simple blood and anthropometric markers be used to detect change in liver fat measured by 1 H-MRS? Liver Int. 37, 1907–1915 (2017).

    Article  PubMed  CAS  Google Scholar 

  24. Hernaez, R. et al. Diagnostic accuracy and reliability of ultrasonography for the detection of fatty liver: a meta-analysis. Hepatology 54, 1082–1090 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  25. Hannah, W. N. Jr & Harrison, S. A. Noninvasive imaging methods to determine severity of nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. Hepatology 64, 2234–2243 (2016).

    Article  PubMed  CAS  Google Scholar 

  26. Karlas, T. et al. Individual patient data meta-analysis of controlled attenuation parameter (CAP) technology for assessing steatosis. J. Hepatol. 66, 1022–1030 (2017).

    Article  PubMed  Google Scholar 

  27. Park, C. C. et al. Magnetic resonance elastography versus 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).

    Article  PubMed  Google Scholar 

  28. Noureddin, M. et al. Utility of magnetic resonance imaging versus histology for quantifying changes in liver fat in nonalcoholic fatty liver disease trials. Hepatology 58, 1930–1940 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  29. European Association for Study of the Liver & Asociacion Latinoamericana para el Estudio del Higado. EASL-ALEH Clinical Practice Guidelines: Non-invasive tests for evaluation of liver disease severity and prognosis. J. Hepatol. 63, 237–264 (2015).

    Article  Google Scholar 

  30. Bedossa, P. & FLIP Pathology Consortium. Utility and appropriateness of the fatty liver inhibition of progression (FLIP) algorithm and steatosis, activity, and fibrosis (SAF) score in the evaluation of biopsies of nonalcoholic fatty liver disease. Hepatology 60, 565–575 (2014).

    Article  PubMed  CAS  Google Scholar 

  31. Maximos, M. et al. The role of liver fat and insulin resistance as determinants of plasma aminotransferase elevation in nonalcoholic fatty liver disease. Hepatology 61, 153–160 (2015).

    Article  PubMed  CAS  Google Scholar 

  32. Verma, S., Jensen, D., Hart, J. & Mohanty, S. R. Predictive value of ALT levels for non-alcoholic steatohepatitis (NASH) and advanced fibrosis in non-alcoholic fatty liver disease (NAFLD). Liver Int. 33, 1398–1405 (2013).

    Article  PubMed  CAS  Google Scholar 

  33. Eguchi, A., Wree, A. & Feldstein, A. E. Biomarkers of liver cell death. J. Hepatol. 60, 1063–1074 (2014).

    Article  PubMed  CAS  Google Scholar 

  34. Vuppalanchi, R. et al. Relationship between changes in serum levels of keratin 18 and changes in liver histology in children and adults with nonalcoholic fatty liver disease. Clin. Gastroenterol. Hepatol. 12, 2121–2130 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Kwok, R. et al. Systematic review with meta-analysis: non-invasive assessment of non-alcoholic fatty liver disease — the role of transient elastography and plasma cytokeratin-18 fragments. Aliment. Pharmacol. Ther. 39, 254–269 (2014).

    Article  PubMed  CAS  Google Scholar 

  36. Tamimi, T. I. et al. An apoptosis panel for nonalcoholic steatohepatitis diagnosis. J. Hepatol. 54, 1224–1229 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Ajmera, V. et al. Novel plasma biomarkers associated with liver disease severity in adults with nonalcoholic fatty liver disease. Hepatology 65, 65–77 (2017).

    Article  PubMed  CAS  Google Scholar 

  38. Roskams, T. et al. Oxidative stress and oval cell accumulation in mice and humans with alcoholic and nonalcoholic fatty liver disease. Am. J. Pathol. 163, 1301–1311 (2003).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  39. Puri, P. et al. The plasma lipidomic signature of nonalcoholic steatohepatitis. Hepatology 50, 1827–1838 (2009).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  40. Feldstein, A. E. et al. Mass spectrometric profiling of oxidized lipid products in human nonalcoholic fatty liver disease and nonalcoholic steatohepatitis. J. Lipid Res. 51, 3046–3054 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Jarrar, M. H. et al. Adipokines and cytokines in non-alcoholic fatty liver disease. Aliment. Pharmacol. Ther. 27, 412–421 (2008).

    Article  PubMed  CAS  Google Scholar 

  42. Shen, J. et al. Non-invasive diagnosis of non-alcoholic steatohepatitis by combined serum biomarkers. J. Hepatol. 56, 1363–1370 (2012).

    Article  PubMed  CAS  Google Scholar 

  43. Polyzos, S. A., Kountouras, J. & Mantzoros, C. S. Adipokines in nonalcoholic fatty liver disease. Metabolism 65, 1062–1079 (2016).

    Article  PubMed  CAS  Google Scholar 

  44. He, L. et al. Diagnostic value of CK-18, FGF-21, and related biomarker panel in nonalcoholic fatty liver disease: a systematic review and meta-analysis. Biomed. Res. Int. 2017, 9729107 (2017).

    PubMed  PubMed Central  Google Scholar 

  45. Kowdley, K. V. et al. Serum ferritin is an independent predictor of histologic severity and advanced fibrosis in patients with nonalcoholic fatty liver disease. Hepatology 55, 77–85 (2012).

    Article  PubMed  CAS  Google Scholar 

  46. Goh, G. B. et al. The development of a non-invasive model to predict the presence of non-alcoholic steatohepatitis in patients with non-alcoholic fatty liver disease. J. Gastroenterol. Hepatol. 31, 995–1000 (2016).

    Article  PubMed  CAS  Google Scholar 

  47. Sumida, Y. et al. A simple clinical scoring system using ferritin, fasting insulin, and type IV collagen 7S for predicting steatohepatitis in nonalcoholic fatty liver disease. J. Gastroenterol. 46, 257–268 (2011).

    Article  PubMed  CAS  Google Scholar 

  48. Poynard, T. et al. Diagnostic value of biochemical markers (NashTest) for the prediction of non alcoholo steato hepatitis in patients with non-alcoholic fatty liver disease. BMC Gastroenterol. 6, 34 (2006).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Younossi, Z. M. et al. A novel diagnostic biomarker panel for obesity-related nonalcoholic steatohepatitis (NASH). Obes. Surg. 18, 1430–1437 (2008).

    Article  PubMed  Google Scholar 

  50. Walenbergh, S. M. et al. Plasma cathepsin D levels: a novel tool to predict pediatric hepatic inflammation. Am. J. Gastroenterol. 110, 462–470 (2015).

    Article  PubMed  CAS  Google Scholar 

  51. Walenbergh, S. M. et al. Plasma cathepsin D correlates with histological classifications of fatty liver disease in adults and responds to intervention. Sci. Rep. 6, 38278 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  52. Smits, L. P. et al. Noninvasive differentiation between hepatic steatosis and steatohepatitis with MR imaging enhanced with USPIOs in patients with nonalcoholic fatty liver disease: a proof-of-concept study. Radiology 278, 782–791 (2016).

    Article  PubMed  Google Scholar 

  53. Bastati, N. et al. Noninvasive differentiation of simple steatosis and steatohepatitis by using gadoxetic acid-enhanced MR imaging in patients with nonalcoholic fatty liver disease: a proof-of-concept study. Radiology 271, 739–747 (2014).

    Article  PubMed  Google Scholar 

  54. Abrigo, J. M. et al. Non-alcoholic fatty liver disease: spectral patterns observed from an in vivo phosphorus magnetic resonance spectroscopy study. J. Hepatol. 60, 809–815 (2014).

    Article  PubMed  CAS  Google Scholar 

  55. Chen, J. et al. Early detection of nonalcoholic steatohepatitis in patients with nonalcoholic fatty liver disease by using MR elastography. Radiology 259, 749–756 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Ratziu, V. et al. A phase 2, randomized, double-blind, placebo-controlled study of GS-9450 in subjects with nonalcoholic steatohepatitis. Hepatology 55, 419–428 (2012).

    Article  PubMed  CAS  Google Scholar 

  57. Ascha, M. S. et al. The incidence and risk factors of hepatocellular carcinoma in patients with nonalcoholic steatohepatitis. Hepatology 51, 1972–1978 (2010).

    Article  PubMed  Google Scholar 

  58. Dulai, P. S. et al. Increased risk of mortality by fibrosis stage in nonalcoholic fatty liver disease: Systematic review and meta-analysis. Hepatology 65, 1557–1565 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Sheth, S. G., Flamm, S. L., Gordon, F. D. & Chopra, S. AST/ALT ratio predicts cirrhosis in patients with chronic hepatitis C virus infection. Am. J. Gastroenterol. 93, 44–48 (1998).

    Article  PubMed  CAS  Google Scholar 

  60. Shaheen, A. A. & Myers, R. P. Diagnostic accuracy of the aspartate aminotransferase-to-platelet ratio index for the prediction of hepatitis C-related fibrosis: a systematic review. Hepatology 46, 912–921 (2007).

    Article  PubMed  Google Scholar 

  61. Sterling, R. K. et al. Development of a simple noninvasive index to predict significant fibrosis in patients with HIV/HCV coinfection. Hepatology 43, 1317–1325 (2006).

    Article  PubMed  CAS  Google Scholar 

  62. Angulo, P. et al. The NAFLD fibrosis score: a noninvasive system that identifies liver fibrosis in patients with NAFLD. Hepatology 45, 846–854 (2007).

    Article  PubMed  CAS  Google Scholar 

  63. Wong, V. W. et al. Validation of the NAFLD fibrosis score in a Chinese population with low prevalence of advanced fibrosis. Am. J. Gastroenterol. 103, 1682–1688 (2008).

    Article  PubMed  Google Scholar 

  64. Angulo, P. et al. Simple noninvasive systems predict long-term outcomes of patients with nonalcoholic fatty liver disease. Gastroenterology 145, 782–789.e4 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  65. Harrison, S. A., Oliver, D., Arnold, H. L., Gogia, S. & Neuschwander-Tetri, B. A. Development and validation of a simple NAFLD clinical scoring system for identifying patients without advanced disease. Gut 57, 1441–1447 (2008).

    Article  PubMed  CAS  Google Scholar 

  66. Unalp-Arida, A. & Ruhl, C. E. Liver fibrosis scores predict liver disease mortality in the United States population. Hepatology 66, 84–95 (2017).

    Article  PubMed  CAS  Google Scholar 

  67. Gudowska, M. et al. Hyaluronic acid concentration in liver diseases. Clin. Exp. Med. 16, 523–528 (2016).

    Article  PubMed  CAS  Google Scholar 

  68. Suzuki, A. et al. Hyaluronic acid, an accurate serum marker for severe hepatic fibrosis in patients with non-alcoholic fatty liver disease. Liver Int. 25, 779–786 (2005).

    Article  PubMed  CAS  Google Scholar 

  69. Monarca, A. et al. Procollagen-type III peptide serum concentrations in alcoholic and non-alcoholic liver disease. Ric Clin. Lab 15, 167–171 (1985).

    PubMed  CAS  Google Scholar 

  70. Nielsen, M. J. et al. The neo-epitope specific PRO-C3 ELISA measures true formation of type III collagen associated with liver and muscle parameters. Am. J. Transl Res. 5, 303–315 (2013).

    PubMed  PubMed Central  CAS  Google Scholar 

  71. Leeming, D. J. et al. Estimation of serum “true collagen type III formation” (Pro-C3) levels as a marker of non-alcoholic steatohepatitis in a prospective cohort. J. Hepatol. 66 (Suppl. 1), S154 (2017).

    Article  Google Scholar 

  72. Hemmann, S., Graf, J., Roderfeld, M. & Roeb, E. Expression of MMPs and TIMPs in liver fibrosis — a systematic review with special emphasis on anti-fibrotic strategies. J. Hepatol. 46, 955–975 (2007).

    Article  PubMed  CAS  Google Scholar 

  73. Abdelaziz, R., Elbasel, M., Esmat, S., Essam, K. & Abdelaaty, S. Tissue inhibitors of metalloproteinase-1 and 2 and obesity related non-alcoholic fatty liver disease: is there a relationship. Digestion 92, 130–137 (2015).

    Article  PubMed  CAS  Google Scholar 

  74. Santos, V. N. et al. Serum laminin, type IV collagen and hyaluronan as fibrosis markers in non-alcoholic fatty liver disease. Braz. J. Med. Biol. Res. 38, 747–753 (2005).

    Article  PubMed  Google Scholar 

  75. Wong, G. L. et al. Non-invasive algorithm of enhanced liver fibrosis and liver stiffness measurement with transient elastography for advanced liver fibrosis in chronic hepatitis B. Aliment. Pharmacol. Ther. 39, 197–208 (2014).

    Article  PubMed  Google Scholar 

  76. Guha, I. N. et al. Noninvasive markers of fibrosis in nonalcoholic fatty liver disease: validating the European Liver Fibrosis Panel and exploring simple markers. Hepatology 47, 455–460 (2008).

    Article  PubMed  Google Scholar 

  77. Nobili, V. et al. Performance of ELF serum markers in predicting fibrosis stage in pediatric non-alcoholic fatty liver disease. Gastroenterology 136, 160–167 (2009).

    Article  PubMed  CAS  Google Scholar 

  78. Imbert-Bismut, F. et al. Biochemical markers of liver fibrosis in patients with hepatitis C virus infection: a prospective study. Lancet 357, 1069–1075 (2001).

    Article  PubMed  CAS  Google Scholar 

  79. Munteanu, M. et al. Diagnostic performance of FibroTest, SteatoTest and ActiTest in patients with NAFLD using the SAF score as histological reference. Aliment. Pharmacol. Ther. 44, 877–889 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  80. Boursier, J. et al. A stepwise algorithm using an at-a-glance first-line test for the non-invasive diagnosis of advanced liver fibrosis and cirrhosis. J. Hepatol. 66, 1158–1165 (2017).

    Article  PubMed  Google Scholar 

  81. Loong, T. C. et al. Application of the combined FibroMeter vibration-controlled transient elastography algorithm in Chinese patients with non-alcoholic fatty liver disease. J. Gastroenterol. Hepatol. 32, 1363–1369 (2017).

    Article  PubMed  CAS  Google Scholar 

  82. Boursier, J. et al. Diagnostic accuracy and prognostic significance of blood fibrosis tests and liver stiffness measurement by FibroScan in non-alcoholic fatty liver disease. J. Hepatol. 65, 570–578 (2016).

    Article  PubMed  Google Scholar 

  83. Xiao, G. et al. Comparison of laboratory tests, ultrasound, or MRE to detect fibrosis in patients with non-alcoholic fatty liver disease: a meta-analysis. Hepatology 66, 1486–1501 (2017).

    Article  PubMed  CAS  Google Scholar 

  84. Wong, V. W. et al. Diagnosis of fibrosis and cirrhosis using liver stiffness measurement in nonalcoholic fatty liver disease. Hepatology 51, 454–462 (2010).

    Article  PubMed  CAS  Google Scholar 

  85. Wong, V. W. et al. Liver stiffness measurement using XL probe in patients with nonalcoholic fatty liver disease. Am. J. Gastroenterol. 107, 1862–1871 (2012).

    Article  PubMed  Google Scholar 

  86. Petta, S. et al. The combination of liver stiffness measurement and NAFLD fibrosis score improves the noninvasive diagnostic accuracy for severe liver fibrosis in patients with nonalcoholic fatty liver disease. Liver Int. 35, 1566–1573 (2015).

    Article  PubMed  Google Scholar 

  87. Tapper, E. B., Sengupta, N., Hunink, M. G., Afdhal, N. H. & Lai, M. Cost-effective evaluation of nonalcoholic fatty liver disease with NAFLD fibrosis score and vibration controlled transient elastography. Am. J. Gastroenterol. 110, 1298–1304 (2015).

    Article  PubMed  Google Scholar 

  88. Chan, W. K., Nik Mustapha, N. R. & Mahadeva, S. A novel 2-step approach combining the NAFLD fibrosis score and liver stiffness measurement for predicting advanced fibrosis. Hepatol. Int. 9, 594–602 (2015).

    Article  PubMed  Google Scholar 

  89. Bamber, J. et al. EFSUMB guidelines and recommendations on the clinical use of ultrasound elastography. Part 1: Basic principles and technology. Ultraschall Med. 34, 169–184 (2013).

    Article  PubMed  CAS  Google Scholar 

  90. Cassinotto, C. et al. Liver stiffness in nonalcoholic fatty liver disease: a comparison of supersonic shear imaging, FibroScan, and ARFI with liver biopsy. Hepatology 63, 1817–1827 (2016).

    Article  PubMed  Google Scholar 

  91. Ferraioli, G. et al. Accuracy of real-time shear wave elastography for assessing liver fibrosis in chronic hepatitis C: a pilot study. Hepatology 56, 2125–2133 (2012).

    Article  PubMed  Google Scholar 

  92. Dulai, P. S., Sirlin, C. B. & Loomba, R. MRI and MRE for non-invasive quantitative assessment of hepatic steatosis and fibrosis in NAFLD and NASH: clinical trials to clinical practice. J. Hepatol. 65, 1006–1016 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  93. Singh, S. et al. Diagnostic performance of magnetic resonance elastography in staging liver fibrosis: a systematic review and meta-analysis of individual participant data. Clin. Gastroenterol. Hepatol. 13, 440–451.e6 (2015).

    Article  PubMed  Google Scholar 

  94. Imajo, K. et al. Magnetic resonance imaging more accurately classifies steatosis and fibrosis in patients with nonalcoholic fatty liver disease than transient elastography. Gastroenterology 150, 626–637.e7 (2016).

    Article  PubMed  Google Scholar 

  95. Banerjee, R. et al. Multiparametric magnetic resonance for the non-invasive diagnosis of liver disease. J. Hepatol. 60, 69–77 (2014).

    Article  PubMed  PubMed Central  Google Scholar 

  96. Pavlides, M. et al. Multiparametric magnetic resonance imaging for the assessment of non-alcoholic fatty liver disease severity. Liver Int. 37, 1065–1073 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  97. Sookoian, S. & Pirola, C. J. Meta-analysis of the influence of I148M variant of patatin-like phospholipase domain containing 3 gene (PNPLA3) on the susceptibility and histological severity of nonalcoholic fatty liver disease. Hepatology 53, 1883–1894 (2011).

    Article  PubMed  CAS  Google Scholar 

  98. Pirola, C. J. & Sookoian, S. The dual and opposite role of the TM6SF2-rs58542926 variant in protecting against cardiovascular disease and conferring risk for nonalcoholic fatty liver: a meta-analysis. Hepatology 62, 1742–1756 (2015).

    Article  PubMed  CAS  Google Scholar 

  99. Zain, S. M., Mohamed, Z. & Mohamed, R. Common variant in the glucokinase regulatory gene rs780094 and risk of nonalcoholic fatty liver disease: a meta-analysis. J. Gastroenterol. Hepatol. 30, 21–27 (2015).

    Article  PubMed  CAS  Google Scholar 

  100. Wood, G. C. et al. A multi-component classifier for nonalcoholic fatty liver disease (NAFLD) based on genomic, proteomic, and phenomic data domains. Sci. Rep. 7, 43238 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  101. Zhou, Y. et al. Noninvasive detection of nonalcoholic steatohepatitis using clinical markers and circulating levels of lipids and metabolites. Clin. Gastroenterol. Hepatol. 14, 1463–1472.e6 (2016).

    Article  PubMed  CAS  Google Scholar 

  102. Nobili, V. et al. A 4-polymorphism risk score predicts steatohepatitis in children with nonalcoholic fatty liver disease. J. Pediatr. Gastroenterol. Nutr. 58, 632–636 (2014).

    Article  PubMed  CAS  Google Scholar 

  103. Sevastianova, K. et al. Genetic variation in PNPLA3 (adiponutrin) confers sensitivity to weight loss-induced decrease in liver fat in humans. Am. J. Clin. Nutr. 94, 104–111 (2011).

    Article  PubMed  CAS  Google Scholar 

  104. Krawczyk, M. et al. PNPLA 3p. I148M variant is associated with greater reduction of liver fat content after bariatric surgery. Surg. Obes. Relat. Dis. 12, 1838–1846 (2016).

    Article  PubMed  Google Scholar 

  105. Tan, Y., Ge, G., Pan, T., Wen, D. & Gan, J. A pilot study of serum microRNAs panel as potential biomarkers for diagnosis of nonalcoholic fatty liver disease. PLoS ONE 9, e105192 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  106. Pirola, C. J. et al. Circulating microRNA signature in non-alcoholic fatty liver disease: from serum non-coding RNAs to liver histology and disease pathogenesis. Gut 64, 800–812 (2015).

    Article  PubMed  CAS  Google Scholar 

  107. Becker, P. P. et al. Performance of serum microRNAs -122, -192 and -21 as biomarkers in patients with non-alcoholic steatohepatitis. PLoS ONE 10, e0142661 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  108. Harrison, S. A. et al. A new non-invasive diagnostic score to monitor change in disease activity and predict fibrosis evolution in patients with NASH. J. Hepatol. 66 (Suppl. 1), S110 (2017).

    Article  Google Scholar 

  109. Hardy, T. et al. Plasma DNA methylation: a potential biomarker for stratification of liver fibrosis in non-alcoholic fatty liver disease. Gut 66, 1321–1328 (2017).

    Article  PubMed  CAS  Google Scholar 

  110. Gorden, D. L. et al. Biomarkers of NAFLD progression: a lipidomics approach to an epidemic. J. Lipid Res. 56, 722–736 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  111. Loomba, R., Quehenberger, O., Armando, A. & Dennis, E. A. Polyunsaturated fatty acid metabolites as novel lipidomic biomarkers for noninvasive diagnosis of nonalcoholic steatohepatitis. J. Lipid Res. 56, 185–192 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  112. Oresic, M. et al. Prediction of non-alcoholic fatty-liver disease and liver fat content by serum molecular lipids. Diabetologia 56, 2266–2274 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  113. Soga, T. et al. Serum metabolomics reveals gamma-glutamyl dipeptides as biomarkers for discrimination among different forms of liver disease. J. Hepatol. 55, 896–905 (2011).

    Article  PubMed  CAS  Google Scholar 

  114. Kalhan, S. C. et al. Plasma metabolomic profile in nonalcoholic fatty liver disease. Metabolism 60, 404–413 (2011).

    Article  PubMed  CAS  Google Scholar 

  115. Mardinoglu, A. et al. Genome-scale metabolic modelling of hepatocytes reveals serine deficiency in patients with non-alcoholic fatty liver disease. Nat. Commun. 5, 3083 (2014).

    Article  PubMed  CAS  Google Scholar 

  116. Alonso, C. et al. Metabolomic identification of subtypes of nonalcoholic steatohepatitis. Gastroenterology 152, 1449–1461.e7 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  117. Raman, M. et al. Fecal microbiome and volatile organic compound metabolome in obese humans with nonalcoholic fatty liver disease. Clin. Gastroenterol. Hepatol. 11, 868–875 (2013).

    Article  PubMed  CAS  Google Scholar 

  118. Wong, V. W. et al. Molecular characterization of the fecal microbiota in patients with nonalcoholic steatohepatitis — a longitudinal study. PLoS ONE 8, e62885 (2013).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  119. Boursier, J. et al. The severity of nonalcoholic fatty liver disease is associated with gut dysbiosis and shift in the metabolic function of the gut microbiota. Hepatology 63, 764–775 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  120. Loomba, R. et al. Gut microbiome-based metagenomic signature for non-invasive detection of advanced fibrosis in human nonalcoholic fatty liver disease. Cell Metab. 25, 1054–1062.e5 (2017).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  121. Verdam, F. J. et al. Non-alcoholic steatohepatitis: a non-invasive diagnosis by analysis of exhaled breath. J. Hepatol. 58, 543–548 (2013).

    Article  PubMed  CAS  Google Scholar 

  122. De Vincentis, A. et al. Breath-print analysis by e-nose for classifying and monitoring chronic liver disease: a proof-of-concept study. Sci. Rep. 6, 25337 (2016).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  123. Kwok, R. et al. Screening diabetic patients for non-alcoholic fatty liver disease with controlled attenuation parameter and liver stiffness measurements: a prospective cohort study. Gut 65, 1359–1368 (2016).

    Article  PubMed  CAS  Google Scholar 

  124. Wong, V. W. et al. Validity criteria for the diagnosis of fatty liver by M probe-based controlled attenuation parameter. J. Hepatol. 67, 577–584 (2017).

    Article  PubMed  Google Scholar 

  125. Shen, J. et al. PNPLA3 gene polymorphism and response to lifestyle modification in patients with nonalcoholic fatty liver disease. J. Gastroenterol. Hepatol. 30, 139–146 (2015).

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgements

The work of the authors was supported partially by grants PICT 2014–543 and PICT 2015–0551 (Agencia Nacional de Promoción Científica y Tecnológica) and the General Research Fund from the Research Grants Council, Hong Kong SAR Government (project reference 14108916). The authors thank C. Cassinotto and N. Frulio for the 2D shear wave elastography and point shear wave elastography images.

Author information

Authors and Affiliations

  1. Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China

    Vincent Wai-Sun Wong & Grace Lai-Hung Wong

  2. State Key Laboratory of Digestive Disease, The Chinese University of Hong Kong, Hong Kong, China

    Vincent Wai-Sun Wong & Grace Lai-Hung Wong

  3. School of Medicine and Pharmacology, The University of Western Australia, Nedlands, Australia

    Leon A. Adams

  4. Hepatology Unit, University Hospital, CHU Bordeaux, Pessac, France

    Victor de Lédinghen

  5. INSERM, University of Bordeaux, UMR1053 Bordeaux Research in Translational Oncology, BaRITOn, F-Bordeaux, France

    Victor de Lédinghen

  6. University of Buenos Aires, Institute of Medical Research A Lanari, Buenos Aires, Argentina

    Silvia Sookoian

  7. Department of Clinical and Molecular Hepatology, Institute of Medical Research (IDIM), National Scientific and Technical Research Council (CONICET)-University of Buenos Aires, Buenos Aires, Argentina

    Silvia Sookoian

Authors
  1. Vincent Wai-Sun Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Leon A. Adams
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Victor de Lédinghen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Grace Lai-Hung Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Silvia Sookoian
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All authors researched data and contributed to writing and reviewing the manuscript.

Corresponding author

Correspondence to Vincent Wai-Sun Wong.

Ethics declarations

Competing interests

V.W.-S.W. served as a consultant for AbbVie, Allergan, Gilead Sciences, Janssen, Perspectum Diagnostics and Pfizer and a speaker for Bristol-Myers Squibb, Echosens, Gilead Sciences and Merck. L.A.A. has received speaking fees from Bayer and holds patents for Hepascore (Quest Diagnostics) for which his employer (University of Western Australia) has received royalties from Quest Diagnostics for its commercialization. V.d.L. has served as a consultant for AbbVie, Bristol-Myers Squibb, Echosens, Gilead Sciences, Merck, Intercept Pharma and Supersonic Imagine and a speaker for AbbVie, Bristol-Myers Squibb, Echosens, Gilead Sciences, Intercept Pharma and Merck. G.L.-H.W. has served as an advisory committee member for Gilead Sciences and a speaker for Abbott, AbbVie, Bristol-Myers Squibb, Echosens, Furui, Gilead Sciences, Janssen and Roche. S.S. declares no competing interests.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wong, V.WS., Adams, L.A., de Lédinghen, V. et al. Noninvasive biomarkers in NAFLD and NASH — current progress and future promise. Nat Rev Gastroenterol Hepatol 15, 461–478 (2018). https://doi.org/10.1038/s41575-018-0014-9

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41575-018-0014-9

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research