No abstract

BackgroundNonalcoholic fatty liver disease (NAFLD) includes a broad range of liver pathologies from simple steatosis to cirrhosis and fibrosis, in which a subtype accompanying hepatocyte degeneration and fibrosis is classified as nonalcoholic steatohepatitis (NASH). NASH accounts for approximately 10–30% of NAFLD and causes a higher frequency of liver-related death, and its progression of NASH has been considered to be complex involving multiple genetic factors interacting with the environment and lifestyle.Principal FindingsTo identify genetic factors related to NAFLD in the Japanese, we performed a genome-wide association study recruiting 529 histologically diagnosed NAFLD patients and 932 population controls. A significant association was observed for a cluster of SNPs in PNPLA3 on chromosome 22q13 with the strongest p-value of 1.4×10−10 (OR = 1.66, 95%CI: 1.43–1.94) for rs738409. Rs738409 also showed the strongest association (p = 3.6×10−6) with the histological classifications proposed by Matteoni and colleagues based on the degree of inflammation, ballooning degeneration, fibrosis and Mallory-Denk body. In addition, there were marked differences in rs738409 genotype distributions between type4 subgroup corresponding to NASH and the other three subgroups (p = 4.8×10−6, OR = 1.96, 95%CI: 1.47–2.62). Moreover, a subgroup analysis of NAFLD patients against controls showed a significant association of rs738409 with type4 (p = 1.7×10−16, OR = 2.18, 95%CI: 1.81–2.63) whereas no association was obtained for type1 to type3 (p = 0.41). Rs738409 also showed strong associations with three clinical traits related to the prognosis of NAFLD, namely, levels of hyaluronic acid (p = 4.6×10−4), HbA1c (p = 0.0011) and iron deposition in the liver (p = 5.6×10−4).ConclusionsWith these results we clearly demonstrated that Matteoni type4 NAFLD is both a genetically and clinically different subset from the other spectrums of the disease and that the PNPLA3 gene is strongly associated with the progression of NASH in Japanese population.

The genetic factors affecting the natural history of nonalcoholic fatty liver disease (NAFLD), including the development of nonalcoholic steatohepatitis (NASH) and NASH-derived hepatocellular carcinoma (NASH-HCC), are still unknown. In the current study, we sought to identify genetic factors related to the development of NAFLD, NASH, and NASH-HCC, and to establish risk-estimation models for them. For these purposes, 936 histologically proven NAFLD patients were recruited, and genome-wide association (GWA) studies were conducted for 902, including 476 NASH and 58 NASH-HCC patients, against 7,672 general-population controls. Risk estimations for NAFLD and NASH were then performed using the SNPs identified as having significant associations in the GWA studies. We found that rs2896019 in PNPLA3 [p = 2.3x10-31, OR (95%CI) = 1.85 (1.67–2.05)], rs1260326 in GCKR [p = 9.6x10-10, OR (95%CI) = 1.38(1.25–1.53)], and rs4808199 in GATAD2A [p = 2.3x10-8, OR (95%CI) = 1.37 (1.23–1.53)] were significantly associated with NAFLD. Notably, the number of risk alleles in PNPLA3 and GATAD2A was much higher in Matteoni type 4 (NASH) patients than in type 1, type 2, and type 3 NAFLD patients. In addition, we newly identified rs17007417 in DYSF [p = 5.2x10-7, OR (95%CI) = 2.74 (1.84–4.06)] as a SNP associated with NASH-HCC. Rs641738 in TMC4, which showed association with NAFLD in patients of European descent, was not replicated in our study (p = 0.73), although the complicated LD pattern in the region suggests the necessity for further investigation. The genetic variants of PNPLA3, GCKR, and GATAD2A were then used to estimate the risk for NAFLD. The obtained Polygenic Risk Scores showed that the risk for NAFLD increased with the accumulation of risk alleles [AUC (95%CI) = 0.65 (0.63–0.67)]. Conclusions: We demonstrated that NASH is genetically and clinically different from the other NAFLD subgroups. We also established risk-estimation models for NAFLD and NASH using multiple genetic markers. These models can be used to improve the accuracy of NAFLD diagnosis and to guide treatment decisions for patients.