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Non-alcoholic fatty liver disease (NAFLD) is a complex disease associated with premature mortality. Its diagnosis is challenging, and the identification of biomarkers causally influenced by NAFLD may be clinically useful. We aimed at identifying blood metabolites causally impacted by NAFLD using two-sample Mendelian randomization (MR) with validation in a population-based biobank. Our instrument for genetically predicted NAFLD included all independent genetic variants from a recent genome-wide association study. The outcomes included 123 blood metabolites from 24,925 individuals. After correction for multiple testing, a positive effect of NAFLD on plasma tyrosine levels but not on other metabolites was identified. This association was consistent across MR methods and was robust to outliers and pleiotropy. In observational analyses performed in the Estonian Biobank (10,809 individuals including 359 patients with NAFLD), after multivariable adjustment, tyrosine levels were positively associated with the presence of NAFLD (odds ratio per 1 SD increment = 1.23 [95% confidence interval = 1.12–1.36], p = 2.19 × 10−5). In a small proof-of-concept study on bariatric surgery patients, blood tyrosine levels were higher in patients with NAFLD than without. This study revealed a potentially causal effect of NAFLD on blood tyrosine levels, suggesting it may represent a new biomarker of NAFLD.

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Non-alcoholic fatty liver disease (NAFLD) is a complex disease linked with several chronic diseases. We aimed at identifying genetic variants associated with NAFLD as well as blood biomarkers that may be causally impacted by NAFLD. We performed a genome-wide meta-analysis of four cohorts of electronic health record-documented NAFLD (8434 cases and 770,180 controls) and confirmed known susceptibility loci (GCKR, MAU2/TM6SF2, APOE, and PNPLA3). We also identified potentially new loci (LPL, FTO and TR1B1) and report an effect of lower LPL expression in adipose tissue on NAFLD susceptibility. Mendelian randomization analyses identified an effect of NAFLD on tyrosine metabolism and on blood levels of three proteins. Positive genetic correlations between NAFLD and cardiometabolic traits and negative genetic correlations with parental lifespan, socio-economic factors and ketone bodies were observed. Altogether, this analysis revealed novel susceptibility loci for NAFLD and early biomarkers of NAFLD that could be used to identify patients with NAFLD.

Background Observational studies have linked adiposity and especially abdominal adiposity to liver fat accumulation and non-alcoholic fatty liver disease. These traits are also associated with type 2 diabetes and coronary artery disease but the causal factor(s) underlying these associations remain unexplored. Methods We used a multivariable Mendelian randomization study design to determine whether body mass index and waist circumference were causally associated with non-alcoholic fatty liver disease using publicly available genome-wide association study summary statistics of the UK Biobank (n = 461,460) and of non-alcoholic fatty liver disease (8434 cases and 770,180 control). A multivariable Mendelian randomization study design was also used to determine the respective causal contributions of waist circumference and liver fat (n = 32,858) to type 2 diabetes and coronary artery disease. Results Using multivariable Mendelian randomization we show that waist circumference increase non-alcoholic fatty liver disease risk even when accounting for body mass index (odd ratio per 1-standard deviation increase = 2.35 95% CI = 1.31–4.22, p = 4.2e−03), but body mass index does not increase non-alcoholic fatty liver disease risk when accounting for waist circumference (0.86 95% CI = 0.54–1.38, p = 5.4e−01). In multivariable Mendelian randomization analyses accounting for liver fat, waist circumference remains strongly associated with both type 2 diabetes (3.27 95% CI = 2.89–3.69, p = 3.8e−80) and coronary artery disease (1.66 95% CI = 1.54–1.8, p = 3.4e−37). Conclusions These results identify waist circumference as a strong, independent, and causal contributor to non-alcoholic fatty liver disease, type 2 diabetes and coronary artery disease, thereby highlighting the importance of assessing body fat distribution for the prediction and prevention of cardiometabolic diseases.