A Pathophysiologic Approach Combining Genetics and Insulin Resistance to Predict the Severity of Nonalcoholic Fatty Liver Disease.
Nonalcoholic fatty liver disease (NAFLD) is a complex disease dictated by both genetic and environmental factors. While insulin resistance (IR) is a key pathogenic driver, two common genetic variants in patatin-like phospholipase domain containing 3 (PNPLA3) and transmembrane 6 superfamily member 2 (TM6SF2) also impart significant risk for disease progression. Traditional approaches to NAFLD risk stratification rely on biomarkers of fibrosis, an end result of disease progression. We hypothesized that by combining genetics and a novel measurement for IR we could predict disease progression by the NAFLD activity score (NAS) and histologic presence of significant fibrosis. A total of 177 patients with biopsy-proven NAFLD were enrolled in this cross-sectional study. PNPLA3 I148M and TM6SF2 E167K genotypes were determined by TaqMan assays. The enhanced lipoprotein IR index (eLP-IR) was calculated from serum biomarkers using nuclear magnetic resonance (NMR) spectroscopy. Multivariate regression models were used to study the relationships between genetics, IR, and histologic features of NAFLD. In the multivariate analysis, the eLP-IR was strongly associated with histologic features of NAFLD activity and hepatic fibrosis (P < 0.001 to 0.02) after adjustment for potential confounders. PNPLA3 148M and TM6SF2 E167K genotypes were significantly associated with steatosis (P = 0.003 and P = 0.02, respectively). A combination of the eLP-IR and genetic score was able to predict the presence of NAS ≥3 with an area under the receiver operating characteristic curve (AUROC) of 0.74. Adding age to this model predicted stages 3-4 liver fibrosis with an AUROC of 0.82. Conclusion: This proof-of-concept study supports the hypothesis that genetics and IR are major determinants of NAFLD severity and demonstrates the feasibility of a new risk stratification paradigm using exclusively pathogenic factors.
Danford, CJ; Connelly, MA; Shalaurova, I; Kim, M; Herman, MA; Nasser, I; Otvos, JD; Afdhal, NH; Jiang, ZG; Lai, M
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