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Hum Mol Genet. 2018 Jun 15;27(12):2214-2223. doi: 10.1093/hmg/ddy124.

NAFLD risk alleles in PNPLA3, TM6SF2, GCKR and LYPLAL1 show divergent metabolic effects.

Author information

1
Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.
2
Biocenter Oulu, University of Oulu, Oulu, Finland.
3
Department of Genomics of Complex Diseases, School of Public Health, Imperial College London, London, UK.
4
Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland.
5
Nightingale Health Ltd., Helsinki, Finland.
6
NMR Metabolomics Laboratory, School of Pharmacy, Faculty of Health Sciences, University of Eastern Finland, Kuopio, Finland.
7
Fimlab Laboratories, Department of Clinical Chemistry, Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.
8
Department of Clinical Physiology, Tampere University Hospital and Faculty of Medicine and Life Sciences, University of Tampere, Tampere, Finland.
9
Division of Medicine, Department of Medicine, University of Turku, Turku University Hospital, Turku, Finland.
10
Northern Finland Birth Cohorts, Faculty of Medicine, University of Oulu, Oulu, Finland.
11
Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland.
12
Population Health Science, Bristol Medical School, University of Bristol and Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
13
Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, VIC, Australia.
14
Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Faculty of Medicine, Nursing and Health Sciences, The Alfred Hospital, Monash University, Melbourne, VIC, Australia.
15
Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
16
Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland.

Abstract

Fatty liver has been associated with unfavourable metabolic changes in circulation. To provide insights in fatty liver-related metabolic deviations, we compared metabolic association profile of fatty liver versus metabolic association profiles of genotypes increasing the risk of non-alcoholic fatty liver disease (NAFLD). The cross-sectional associations of ultrasound-ascertained fatty liver with 123 metabolic measures were determined in 1810 (Nfatty liver = 338) individuals aged 34-49 years from The Cardiovascular Risk in Young Finns Study. The association profiles of NAFLD-risk alleles in PNPLA3, TM6SF2, GCKR, and LYPLAL1 with the corresponding metabolic measures were obtained from a publicly available metabolomics GWAS including up to 24 925 Europeans. The risk alleles showed different metabolic effects: PNPLA3 rs738409-G, the strongest genetic NAFLD risk factor, did not associate with metabolic changes. Metabolic effects of GCKR rs1260326-T were comparable in many respects to the fatty liver associations. Metabolic effects of LYPLAL1 rs12137855-C were similar, but statistically less robust, to the effects of GCKR rs1260326-T. TM6SF2 rs58542926-T displayed opposite metabolic effects when compared with the fatty liver associations. The metabolic effects of the risk alleles highlight heterogeneity of the molecular pathways leading to fatty liver and suggest that the fatty liver-related changes in the circulating lipids and metabolites may vary depending on the underlying pathophysiological mechanism. Despite the robust cross-sectional associations on population level, the present results showing neutral or cardioprotective metabolic effects for some of the NAFLD risk alleles advocate that hepatic lipid accumulation by itself may not increase the level of circulating lipids or other metabolites.

PMID:
29648650
PMCID:
PMC5985737
DOI:
10.1093/hmg/ddy124
[Indexed for MEDLINE]
Free PMC Article

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