Mitochondrial mt12361A>G increased risk of metabolic dysfunctionassociated steatotic liver disease among non-diabetes  

作　　者：Ming-Ying Lu Yu-Ju Wei Chih-Wen Wang Po-Cheng Liang Ming-Lun Yeh Yi-Shan Tsai Pei-Chien Tsai Yu-Min Ko Ching-Chih Lin Kuan-Yu Chen Yi-Hung Lin Tyng-Yuan Jang Ming-Yen Hsieh Zu-Yau Lin Chung-Feng Huang Jee-Fu Huang Chia-Yen Dai Wan-Long Chuang Ming-Lung Yu 

机构地区：[1]Hepatitis Center and Hepatobiliary Division,Department of Internal Medicine,Kaohsiung Medical University Hospital,Kaohsiung 80708,Taiwan [2]School of Medicine and Doctoral Program of Clinical and Experimental Medicine,College of Medicine and Center of Excellence for Metabolic Associated Fatty Liver Disease,National Sun Yat-sen University,Kaohsiung 80708,Taiwan

出　　处：《World Journal of Gastroenterology》2025年第10期38-50,共13页世界胃肠病学杂志(英文)

基　　金：Supported by the“Center of Excellence for Metabolic Associated Fatty Liver Disease,National Sun Yat-sen University,Kaohsiung”,No.NSTC 112-2321-B-001-006;The Featured Areas Research Center Program within the Framework of the Higher Education Sprout Project by the Ministry of Education in Taiwan,No.MOHW112-TDU-B-221-124007.

摘　　要：BACKGROUND Insulin resistance,lipotoxicity,and mitochondrial dysfunction contribute to the pathogenesis of metabolic dysfunction-associated steatotic liver disease(MASLD).Mitochondrial dysfunction impairs oxidative phosphorylation and increases reactive oxygen species production,leading to steatohepatitis and hepatic fibrosis.Artificial intelligence(AI)is a potent tool for disease diagnosis and risk stratification.AIM To investigate mitochondrial DNA polymorphisms in susceptibility to MASLD and establish an AI model for MASLD screening.METHODS Multiplex polymerase chain reaction was performed to comprehensively genotype 82 mitochondrial DNA variants in the screening dataset(n=264).The significant mitochondrial single nucleotide polymorphism was validated in an independent cohort(n=1046)using the Taqman®allelic discrimination assay.Random forest,eXtreme gradient boosting,Naive Bayes,and logistic regression algorithms were employed to construct an AI model for MASLD.RESULTS In the screening dataset,only mt12361A>G was significantly associated with MASLD.mt12361A>G showed borderline significance in MASLD patients with 2-3 cardiometabolic traits compared with controls in the validation dataset(P=0.055).Multivariate regression analysis confirmed that mt12361A>G was an independent risk factor of MASLD[odds ratio(OR)=2.54,95%confidence interval(CI):1.19-5.43,P=0.016].The genetic effect of mt12361A>G was significant in the non-diabetic group but not in the diabetic group.mt12361G carriers had a 2.8-fold higher risk than A carriers in the non-diabetic group(OR=2.80,95%CI:1.22-6.41,P=0.015).By integrating clinical features and mt12361A>G,random forest outperformed other algorithms in detecting MASLD[training area under the receiver operating characteristic curve(AUROC)=1.000,validation AUROC=0.876].CONCLUSION The mt12361A>G variant increased the severity of MASLD in non-diabetic patients.AI supports the screening and management of MASLD in primary care settings.

关 键 词：Metabolic dysfunction-associated steatotic liver disease Mitochondrial DNA Artificial intelligence Machine learning Algorithm 

分 类 号：R73[医药卫生—肿瘤]