Causal relationship between key genes and metabolic dysfunction-associated fatty liver disease risk mediated by immune cells: A Mendelian randomization and mediation analysis

被引:1
作者
Feng, Gong [1 ,2 ]
He, Na [3 ]
Gao, Jing [4 ,5 ]
Li, Xiao-Cheng [2 ]
Zhang, Fen-Na [3 ]
Liu, Cheng-Cheng [2 ]
Targher, Giovanni [6 ,7 ]
Byrne, Christopher D. [8 ,9 ]
Mi, Man [2 ]
Zheng, Ming-Hua [10 ,11 ]
Ye, Feng [1 ]
机构
[1] Xi An Jiao Tong Univ, Affiliated Hosp 1, Dept Infect Dis, Xian, Peoples R China
[2] Xian Med Univ, Inst Gen Practice, Xian, Peoples R China
[3] Xian Med Univ, Affiliated Hosp 1, Dept Gastroenterol, Xian, Peoples R China
[4] Xiamen Univ, Sch Med, Xiamen, Peoples R China
[5] Xizang Minzu Univ, Affiliated Hosp, Dept Emergency Med, Xianyang, Peoples R China
[6] Univ Verona, Dept Med, Verona, Italy
[7] IRCCS Sacro Cuore Don Calabria Hosp, Metab Dis Res Unit, Negrar Di Valpolicella, Italy
[8] Univ Hosp Southampton, Southampton Natl Inst Hlth & Care, Res Biomed Res Ctr, Southampton, England
[9] Univ Southampton, Southampton Gen Hosp, Southampton, England
[10] Wenzhou Med Univ, Affiliated Hosp 1, NAFLD Res Ctr, Dept Hepatol, Wenzhou, Peoples R China
[11] Key Lab Diag & Treatment Dev Chron Liver Dis Zheji, Wenzhou, Peoples R China
关键词
diagnostic markers; mediation analysis; Mendelian randomization; metabolic dysfunction-associated fatty liver disease; STEATOHEPATITIS; PATHOGENESIS; DIAGNOSIS; BIOPSY;
D O I
10.1111/dom.15925
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
AimNon-invasive diagnostics for metabolic dysfunction-associated fatty liver disease (MAFLD) remain challenging. We aimed to identify novel key genes as non-invasive biomarkers for MAFLD, elucidate causal relationships between biomarkers and MAFLD and determine the role of immune cells as potential mediators.Materials and MethodsUtilizing published transcriptome data of patients with biopsy-proven MAFLD, we applied linear models for microarray data, least absolute shrinkage and selector operation (LASSO) regressions and receiver operating characteristic (ROC) curve analyses to identify and validate biomarkers for MAFLD. Using the expression quantitative trait loci database and a cohort of 778 614 Europeans, we used Mendelian randomization to analyse the causal relationships between key biomarkers and MAFLD. Additionally, mediation analysis was performed to examine the involvement of 731 immunophenotypes in these relationships.ResultsWe identified 31 differentially expressed genes, and LASSO regression showed three hub genes, IGFBP2, PEG10, and P4HA1, with area under the receiver operating characteristic (AUROC) curve of 0.807, 0.772 and 0.791, respectively, for identifying MAFLD. The model of these three genes had an AUROC of 0.959 and 0.800 in the development and validation data sets, respectively. This model was also validated using serum-based enzyme-linked immunosorbent assay data from MAFLD patients and control subjects (AUROC: 0.819, 95% confidence interval: 0.736-0.902). PEG10 was associated with an increased MAFLD risk (odds ratio = 1.106, p = 0.032) via inverse variance-weighted analysis, and about 30% of this risk was mediated by the percentage of CD11c + CD62L- monocytes.ConclusionsThe MAFLD panels have good diagnostic accuracy, and the causal link between PEG10 and MAFLD was mediated by the percentage of CD11c + CD62L- monocytes.
引用
收藏
页码:5590 / 5599
页数:10
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