SAMM50-rs2073082, -rs738491 and -rs3761472 Interactions Enhancement of Susceptibility to Non-Alcoholic Fatty Liver Disease

Background and aim: Several studies have identified that three SAMM50 polymorphisms (rs2073082, rs738491, rs3761472) are associated with an increased risk of non-alcoholic fatty liver disease (NAFLD). However, the clinical significance of the SAMM50 SNP in relation to NAFLD remains largely unknown. Therefore, we conducted a clinical study and SNP-SNP interaction analysis to further elucidate the effect of the SAMM50 SNP on the progression of NAFLD in the elderly. Methods: A total of 1053 patients over the age of 65 years were recruited. Liver fat and fibrosis were detected by abdominal ultrasound or FibroScan, respectively. Genomic DNA was extracted and then genotyped by Fluidigm 96.96 Dynamic Array. Multivariable logistic regression was used to evaluate the association between NAFLD and SNP. SNP-SNP interactions were analyzed using generalized multivariate dimensionality reduction (GMDR). Results: The risk of NAFLD was substantially higher in people who carried SAMM50-rs2073082 G and -rs738491 T alleles (OR, 1.962; 95% CI, 1.448-2.659; p < 0.001; OR, 1.532; 95% CI, 1.246-1.884; p = 0.021, respectively) compared to noncarriers. Carriers of the rs738491 T and rs3761472 G alleles in the cohort showed a significant increase in liver stiffness measurements (LSM). The combination of the three SNPs showed the highest predictive power for NAFLD. The rs2073082 G allele, rs738491 T allele and rs3761472 G carriers had a two-fold higher risk of NAFLD compared to noncarriers. Conclusions: Our research has demonstrated a strong correlation between the genetic polymorphism of SAMM50 and NAFLD in the elderly, which will contribute to a better understanding of the impact of age and genetics on this condition. Additionally, this study provides a potential predictive model for the early clinical warning of NAFLD.

Automated summary

This study identified a significant correlation between SAMM50 genetic polymorphism and NAFLD in the elderly, contributing to a better understanding of the impact of age and genetics on this condition. Additionally, it provides a potential predictive model for early clinical warning of NAFLD.