Gastroenterology

Gastroenterology

Volume 137, Issue 3, September 2009, Pages 865-872
Gastroenterology

Clinical—Liver, Pancreas, and Biliary Tract
Prediction of Non-Alcoholic Fatty Liver Disease and Liver Fat Using Metabolic and Genetic Factors

https://doi.org/10.1053/j.gastro.2009.06.005Get rights and content

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.

Section snippets

Subjects and Study Design

All subjects (359 non-diabetic and 111 type 2 diabetic Finnish individuals) were recruited for metabolic studies designed to include either non-diabetic subjects12, 13, 14, 15, 16, 17 or type 2 diabetic patients18, 19, 20, 21 mainly by newspaper advertisements, by contacting occupational health services, or among subjects referred to the Department of Gastroenterology because of chronically elevated serum transaminase concentrations using the following inclusion criteria: (1) age 18–75 years;

Univariate Analyses of Determinants of Liver Fat in NAFLD

Of the study subjects, 51% had NAFLD (liver fat content ≥5.56%29), 57% had the metabolic syndrome, and 24% had type 2 diabetes. In univariate logistic regression analyses, increased liver fat content was associated with increased prevalence of the metabolic syndrome and type 2 diabetes, age, BMI, waist circumference, systolic and diastolic BP, fP-glucose, fS-triglyceride, fS-insulin, fS-ALT and fS-AST concentrations, and a decreased fS-HDL cholesterol concentration and AST/ALT ratio (Table 2).

Discussion

We have developed an NAFLD liver fat score, which allows identification of NAFLD using easily available clinical and laboratory data. Our cohort included 470 well-characterized Finnish individuals in whom liver fat content was measured using state-of-the-art 1H-MRS methodology.7 Knowledge of the metabolic syndrome; type 2 diabetes; and serum insulin, AST, and ALT concentrations allowed prediction of NAFLD with a sensitivity of 86% and a specificity of 71%. The score gave high values also in

Acknowledgments

The authors thank Anja Cornér, Juha Halavaara, Anna-Maija Häkkinen, Leena Juurinen, Jaakko Kaprio, Jesper Lundbom, Janne Makkonen, Sari Mäkimattila, Kirsi H. Pietiläinen, Leena Ryysy, Anneli Seppälä-Lindroos, Anssi Sovijärvi, Jussi Sutinen, Marjo Tamminen, Kari Teramo, Mirja Tiikkainen, Satu Vehkavaara, and Jukka Westerbacka for their contributions and Mia Urjansson, Katja Sohlo, Kaisa Makkonen, Tuija Mård, and Pentti Pölönen for excellent technical assistance.

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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).

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