Key result
GCKR NAFLD risk allele shares ~77% of metabolic traits with observational fatty liver, unlike PNPLA3.
Why the study?
Fatty liver is associated with unfavorable metabolic changes and cardiometabolic risk, but the metabolic effects of NAFLD risk alleles are heterogeneous and not fully understood.
Do NAFLD risk alleles in PNPLA3, TM6SF2, GCKR, and LYPLAL1 have similar metabolic effects to observational fatty liver associations?
Cross-Sectional (n=26,735)
Yes
Do NAFLD risk alleles in PNPLA3, TM6SF2, GCKR, and LYPLAL1 have similar metabolic effects to observational fatty liver associations?
Different NAFLD risk alleles have divergent effects on circulating lipids and metabolites, suggesting pathogenically different subtypes of NAFLD with alternate metabolic consequences.
Divergent metabolic effects of NAFLD risk alleles support distinct subtypes; hypothesis-generating and should not yet change practice.
Fatty liver has been associated with unfavourable metabolic changes in circulation and is considered as a risk factor for cardiometabolic complications such as type 2 diabetes and cardiovascular disease. We aimed to provide insights in fatty liver related metabolic deviations by studying the resemblance between the metabolic profile associated with fatty liver observationally and metabolic profiles of non-alcoholic fatty liver disease (NAFLD) risk increasing genotypes. We determined cross-sectional associations of ultrasound-ascertained fatty liver status with 123 metabolic traits in 1,810 individuals aged 34-49 years from The Cardiovascular Risk in Young Finns Study. The cross-sectional associations were compared with the association profiles of NAFLD risk alleles in PNPLA3 , TM6SF2 , GCKR , and LYPLAL1 with the corresponding metabolic traits obtained from a publicly available genome-wide association study including up to 24,925 European individuals. The analysis revealed substantially different metabolic effects of the risk alleles. PNPLA3 rs738409-G, the strongest genetic risk factor to NAFLD, did not associate with metabolic changes. GCKR rs1260326-T resulted in an association profile similar to the observational fatty liver associations. Metabolic effects of LYPLAL1 rs12137855-C were similar, but statistically less robust, to the effects of GCKR rs1260326-T. In contrast, NAFLD risk allele TM6SF2 rs58542926-T displayed opposite metabolic associations when compared with the observational association pattern. Conclusion The divergent effects of the risk alleles on circulating lipids and metabolites underline involvement of several metabolic pathways in NAFLD and suggest that there are pathogenically different subtypes of NAFLD with alternate metabolic consequences. NAFLD risk alleles may have neutral or even cardioprotective effect on circulating lipids and metabolites providing evidence that hepatic lipid accumulation by itself would not necessarily cause the metabolic deviations associated observationally with fatty liver.
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Sliz et al. (2017) conducted a cross-sectional in Non-alcoholic fatty liver disease (NAFLD) (n=26,735). NAFLD risk alleles (PNPLA3, TM6SF2, GCKR, LYPLAL1) and fatty liver vs. Non-risk alleles and no fatty liver was evaluated on Resemblance between metabolic effects of NAFLD risk alleles and observational fatty liver across 123 metabolic traits (measured by R-squared). NAFLD risk alleles displayed divergent effects on circulating metabolic traits, with GCKR rs1260326-T mimicking observational fatty liver (R2=0.77) while PNPLA3 rs738409-G showed no association.
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