Review Article | Published:

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

Nature Reviews Gastroenterology & Hepatologyvolume 15pages461478 (2018) | Download Citation

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.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Additional information

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

References

  1. 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).

  2. 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).

  3. 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).

  4. 4.

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

  5. 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).

  6. 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).

  7. 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).

  8. 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).

  9. 9.

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

  10. 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).

  11. 11.

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

  12. 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).

  13. 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).

  14. 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).

  15. 15.

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

  16. 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).

  17. 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).

  18. 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).

  19. 19.

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

  20. 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).

  21. 21.

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

  22. 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).

  23. 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).

  24. 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).

  25. 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).

  26. 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).

  27. 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).

  28. 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).

  29. 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).

  30. 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).

  31. 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).

  32. 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).

  33. 33.

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

  34. 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).

  35. 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).

  36. 36.

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

  37. 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).

  38. 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).

  39. 39.

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

  40. 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).

  41. 41.

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

  42. 42.

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

  43. 43.

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

  44. 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).

  45. 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).

  46. 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).

  47. 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).

  48. 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).

  49. 49.

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

  50. 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).

  51. 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).

  52. 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).

  53. 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).

  54. 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).

  55. 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).

  56. 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).

  57. 57.

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

  58. 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).

  59. 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).

  60. 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).

  61. 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).

  62. 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).

  63. 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).

  64. 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).

  65. 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).

  66. 66.

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

  67. 67.

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

  68. 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).

  69. 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).

  70. 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).

  71. 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).

  72. 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).

  73. 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).

  74. 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).

  75. 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).

  76. 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).

  77. 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).

  78. 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).

  79. 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).

  80. 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).

  81. 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).

  82. 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).

  83. 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).

  84. 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).

  85. 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).

  86. 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).

  87. 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).

  88. 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).

  89. 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).

  90. 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).

  91. 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).

  92. 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).

  93. 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).

  94. 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).

  95. 95.

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

  96. 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).

  97. 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).

  98. 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).

  99. 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).

  100. 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).

  101. 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).

  102. 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).

  103. 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).

  104. 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).

  105. 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).

  106. 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).

  107. 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).

  108. 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).

  109. 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).

  110. 110.

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

  111. 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).

  112. 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).

  113. 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).

  114. 114.

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

  115. 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).

  116. 116.

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

  117. 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).

  118. 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).

  119. 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).

  120. 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).

  121. 121.

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

  122. 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).

  123. 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).

  124. 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).

  125. 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).

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

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. Search for Vincent Wai-Sun Wong in:

  2. Search for Leon A. Adams in:

  3. Search for Victor de Lédinghen in:

  4. Search for Grace Lai-Hung Wong in:

  5. Search for Silvia Sookoian in:

Contributions

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

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.

Corresponding author

Correspondence to Vincent Wai-Sun Wong.

About this article

Publication history

Published

DOI

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