Validation of genetic variants associated with metabolic dysfunction-associated fatty liver disease in an ethnic Chinese population

Abstract

BACKGROUND Genetic factors play an important role in the pathogenesis and development of metabolic dysfunction-associated fatty liver disease (MAFLD). AIM To study the association of single nucleotide polymorphisms (SNPs), previously identified in Western populations, with the risk of MAFLD in a Singapore Chinese population and their interactions with environmental and medical risk factors. METHODS A retrospective case-control study was conducted with 72 MAFLD cases and 72 controls with no hepatic steatosis on computed tomography, magnetic resonance imaging, or controlled attenuation parameter score. Subjects were recruited from two tertiary hospitals. Genetic alleles such as NCAN, GCKR, LYPLAL1, PNPLA3, PPP1R3B, FDFT1, COL13A1, EFCAB4B, PZP, and TM6SF2 were genotyped using the TaqMan® Predesigned SNP Genotyping Assay. RESULTS Weight and body mass index (BMI) were 1.2-times higher in patients (70.6 kg, 95% confidence interval [CI]: 57.1-84.1 vs 60.8 kg, 95%CI: 48.5-73.1, P < 0.001 and 26.9 kg, 95%CI: 23-40.8 vs 23.3 kg 95%CI: 19-27.6, P < 0.001 respectively). The prevalence of diabetes mellitus in patients was 40.3% and 20.8% in controls (P = 0.011). Patients had higher mean triglycerides than controls (P < 0.001). PNPLA3 GG was more likely to be associated with MAFLD (43.4% CC vs 69.7% GG, P = 0.017, and 44.8% CG vs 69.7% GG, P = 0.022). In multivariable analysis, hypertriglyceridemia (odds ratio [OR]: 2.04 95%CI: 1.3-3.1, P = 0.001), BMI (OR: 1.2 95%CI: 1.1-1.4, P < 0.001) and PNPLA3 GG (OR: 3.4 95%CI: 1.3-9.2, P = 0.014) were associated with MAFLD (area under the receiver operating characteristic curve of 0.823). CONCLUSION Among the Chinese population of Singapore, PNPLA3 homozygous GG allele is a strong predictor of MAFLD, whereas LYPLAL1, GCKR, FDFT1, COL13A1, PZP, and TM6SF2 are not significantly associated. Hypertriglyceridemia, high BMI, and PNPLA3 GG are independent predictors of MAFLD. © 2020. Published by Baishideng Publishing Group Inc. All Rights Reserved.