Discussion Of The Relationship Between Iron Overload And The Severity Of Nonalcoholic Fatty Liver Disease With Type 2 Diabetes

Objective:Our research is to discuss the relationship between iron overload and T2 DM with NAFLD(LFC?NASH?liver fibrosis) using case-control study.Analysis the additive interaction between SF and AR in the development of liver fibrosis, and offers a new target and perspective for the treatment of NAFLD. Methods:1400 type 2 diabetes patients were selected in tianjin third center hospital from2012.10 to 2015.10, among which 838 cases have complete important data and the liver ultrasound image quality were better.Calculate the liver fat content using Image J software, and divide them into two group according to the median of liver fat content s: group A( light fat group) and group B(high fat group).We matched the two groups using PSM and finally there are 576 patients successfully matched, namely, group A and group B patients both have 288 patients.According to NASH-PS, we divided the 576 patients into 2 group:group C1(NASH-PS?79,221 cases),group D1(NASH-PS>79,355 cases). In 576 patients,there were 40 patients underwent liver biopsy. We divided them into two groups according to NAS score: group C2(NAS<5,12 cases),group D2(NAS ? 5,28cases). Selected 355 patients whose NASH Predictive Score>79 among 576 patients, and used Fibro Touch detecting liver stiffness. Divided them into two groups according to significant fibrosis:group E1(KPA<7.3,204 cases), group F1(KPA?7.3,151 cases).There were 28 patients underwent liver biopsy in 355 patients and divided them into 2 groups according to significant fibrosis:group E2:(F0-F1,16 cases),group F2(F2-F4,12 cases).Compare SF,SI,hepcidin,HJV and AR between group A and group B,group C and group D,group E1 and group F1,group E2 and group F2,and using Logistic regression analysis the risk factors of LFC,NASH and liver fibrosis.Analysis the addictive interaction between SF and AR in the progressing of fibrosis using additive interaction model.Calculating RERI,AP and S. Results: 1.PSM method is applied to match the patients, including the variables gender, age, duration of diabetes, blood pressure(including systolic and diastolic blood pressure), glycosylated hemoglobin, and fasting and postprandial 2 hours blood glucose levels and insulin use.The results showed that after matching,the above index has no obvious difference, two groups is comparable. After matching, the data distribution, data discrete degree is reduced, simulate the randomization ideal, the research object is close to randomized controlled study. 2.The gender, age, duration of T2 DM and height was comparable between Group A and group B. TG,LDL-c,FFA,FINS,FCP,HOMA-IR,ALT,GGT,visceral fat and CK18-M30,CK18-M65 were significantly higher in group B patients than in Group A(all P<0.05) as well as SF, SI and other iron metabolic variables. AR was no difference between group A and group B(P > 0.05).Logistic regression analysis showed that HOMA IR,LDL- c,SF are the independent risk factors of LFC.BMI,SBP,DBP, LDL-c, FFA, FINS, FCP, HOMA-IR, ALT, AST, NLR and CK18-M30,CK18-M65 were significantly higher in group D1 patients than in group C1 as well as SF,SI,serum levels of saturation,hepcidin and AR(all P < 0.05). HJV,UIBC were significant higher in group C1 patients than in group D1(all P<0.05).Logistic regression analysis showed that HOMA IR,SF are the independent risk factors of NASH.BMI,SBP,DBP, LDL-c, FFA, FINS, FCP2 h, HOMA-IR, ALT, AST, NLR and CK18-M30,CK18-M65 were significantly higher in group D2 patients than in group C2 as well as SF,SI,serum levels of saturation,hepcidin and AR(all P<0.05). HJV,UIBC were significant higher in group C2 patients than in group D2(all P<0.05).Logistic regression analysis showed that HOMA IR,SF,CK18-M30 are the independent risk factors of NASH.Age,FFA,CK18-M30/65,SI,SF,hepcidin and AR were significantly higher in group F1 patients than in group E1 but HJV was lower in group F1 patients than in group E1(all P<0.05). Logistic regression analysis showed that CK18-M65,SF,AR are the independent risk factors of liver fibrosis. Age,SBP,LDL-c,CK18-M30/65,SF,hepcidin and AR were significantly higher in group F2 patients than in group E2 but LFC, HJV was lower in group F2 patients than in group E2(all P<0.05). Logistic regression analysis showed that SF,AR are the independent risk factors of liver fibrosis. SF and AR had addictive interaction in the development of liver fibrosis and RERI,AP,S were 4.020,0.572,3.000,respectively. Conclusion: 1.PSM method can better simulate random controlled study, solving the clinical research of baseline data inconsistency between groups, making the results more reliable. 2.Iron overload can lead to IR and liver fat accumulation, and then promote the formation of fatty liver. 3.SF is one of the independent risk factor which promote NAFLD into NASH in T2 DM patients. 4.SF and AR are the independent risk factors which promote NAFLD into liver fibrosis in T2 DM patients. SF and AR had addictive interaction in the development of liver fibrosis. 5.As a noninvasive method, NASH Predictive Score has higher clinical value in predicting NASH. And should be used as a routine means for clinicians to screen NASH.