Identification of genetic risk variants of non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is an increasingly relevant public health issue, being part of the obesity epidemic. NAFLD is emerging as the most common cause of chronic liver disease in the Western world [1]. Prevalence of NAFLD is approximately 20-30% in Europe and is 22% in the Lifelines cohort [2]. The spectrum of NAFLD ranges from simple steatosis to non-alcoholic steatohepatitis (NASH) and may lead to fibrosis, cirrhosis and hepatocellular carcinoma [3]. As NAFLD is becoming increasingly common, NASH is projected to become the leading cause of liver transplantation in the near future [4]. NAFLD is comorbid with an extended number of metabolic and inflammatory associated disorders. It coexists frequently with obesity, dyslipidemia, metabolic syndrome, insulin resistance, type 2 diabetes mellitus [3-7] and cardiovascular disease, which is the leading cause of death in NAFLD [4,8].

NAFLD is characterized by a considerable inter patient variability in terms of severity and progression rate to NASH and fibrosis. NAFLD is a complex disease resulting from environmental exposures acting on a susceptible polygenic background and comprising multiple independent modifiers. The development of obesity and NAFLD is determined by dietary factors, lack of physical exercise, the microbiome and host genetics. Ongoing research is focused on identifying genetic factors that contribute to NAFLD pathogenesis. Evidence indicative of a genetic component to NAFLD are familial aggregation, twin studies and interethnic differences in susceptibility. In genome-wide association studies (GWAS) ethnic differences in the prevalence of NAFLD were found. A variant in PNPLA3 has been identified as the major common genetic determinant of NAFLD and other genetic variants with smaller effect size are located in vicinity of TM6SF2, MBOAT7 and GCKR loci [9-11].

If we want to implement effective preventive measures in the future to overcome the rising incidence of NAFLD, we need to take a collective unbiased multidisciplinary approach to identify major determinants of NAFLD including its causal genetic variants. 

In this proposal, we aim to perform analyses of genetic data in Lifelines-UGLI samples. We can identify the association of genome and disease with following functional explanation, which provides further insight into the genetic architecture of NAFLD.