Prediction of Non-Alcoholic Fatty Liver Disease and Liver Fat Using Metabolic and Genetic Factors
Background & Aims
Our aims were to develop a method to accurately predict non-alcoholic fatty liver disease (NAFLD) and liver fat content based on routinely available clinical and laboratory data and to test whether knowledge of the recently discovered genetic variant in the PNPLA3 gene (rs738409) increases accuracy of the prediction.
Methods
Liver fat content was measured using proton magnetic resonance spectroscopy in 470 subjects, who were randomly divided into estimation (two thirds of the subjects, n = 313) and validation (one third of the subjects, n = 157) groups. Multivariate logistic and linear regression analyses were used to create an NAFLD liver fat score to diagnose NAFLD and liver fat equation to estimate liver fat percentage in each individual.
Results
The presence of the metabolic syndrome and type 2 diabetes, fasting serum (fS) insulin, fS-aspartate aminotransferase (AST), and the AST/alanine aminotransferase ratio were independent predictors of NAFLD. The score had an area under the receiver operating characteristic curve of 0.87 in the estimation and 0.86 in the validation group. The optimal cut-off point of −0.640 predicted increased liver fat content with sensitivity of 86% and specificity of 71%. Addition of the genetic information to the score improved the accuracy of the prediction by only <1%. Using the same variables, we developed a liver fat equation from which liver fat percentage of each individual could be estimated.
Conclusions
The NAFLD liver fat score and liver fat equation provide simple and noninvasive tools to predict NAFLD and liver fat content.
Abbreviations used in this paper: 1H-MRS, proton magnetic resonance spectroscopy, AROC, area under the ROC curve, BP, blood pressure, BMI, body mass index, fP, fasting plasma, fS, fasting serum, HBV, hepatitis B virus, HCV, hepatitis C virus, HDL, high-density lipoprotein, LDL, low-density lipoprotein, NAFLD, non-alcoholic fatty liver disease, PNPLA3, adiponutrin, ROC, receiver operating characteristic, SNP, single nucleotide polymorphism
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Conflicts of interest The authors disclose no conflicts.
Funding Supported by research grants from the Academy of Finland (to H.Y.-J.); the Sigrid Juselius Foundation (to H.Y.-J.); the Novo Nordisk Foundation (to H.Y.-J., M.R.); the Biomedicum Helsinki Foundation (to A.K.); the Paulo Foundation (to A.K.); the Wallenberg Foundation (to L.G.); a Nordic Centre of Excellence in Disease Genetics grant by the Nordic Research Councils (to L.G.); the Swedish Research Council, Region Skåne (to M.R.); Påhlsson Foundation (to M.R.); the UMAS Foundation (to M.R.); the Swedish Diabetes Foundation (to M.R.); the Crafoord Foundation (to M.R.); the Lundgren Foundation (to M.R.); the Bergvall Foundation (to M.R.); and the European Commission as an Integrated Project under the 6th Framework Programme (contract LSHM-CT-2005-018734) (to H.Y.-J.) as part of the project “Hepatic and adipose tissue and functions in the metabolic syndrome (www.hepadip.org).
PII: S0016-5085(09)00913-5
doi:10.1053/j.gastro.2009.06.005
© 2009 AGA Institute. Published by Elsevier Inc. All rights reserved.
Refers to article:
- Nonalcoholic Fatty Liver Disease Liver Fat Score and Fat Equation to Predict and Quantitate Hepatic Steatosis: Promising But Not Prime Time! , 27 July 2009
