Bidirectional two-sample Mendelian randomization investigation of the causal association between liver function indicators and autoimmune liver diseases
-
摘要:
目的 运用双向两样本孟德尔随机化(MR)探究肝功能指标与自身免疫性肝病(AILD)的因果关联。 方法 基于Open GWAS数据库的全基因组关联研究(GWAS)数据，以9项肝功能指标[丙氨酸氨基转移酶(ALT)、天冬氨酸氨基转移酶(AST)、碱性磷酸酶(ALP)、γ-谷氨酰转肽酶(GGT)等]为暴露、3种AILD[自身免疫性肝炎(AIH)、原发性胆汁性胆管炎(PBC)、原发性硬化性胆管炎(PSC)]为结局进行正向MR分析，同时开展逆向MR验证；以逆方差加权法(IVW)为主要分析方法，结合敏感性分析验证结果的稳健性。 结果 正向MR显示, ALT(OR=1.719, 95% CI：1.276~2.316，P＜0.001)、AST(OR=1.358, 95% CI：1.012~1.824，P=0.041)、GGT(OR=1.535, 95% CI：1.255~1.877，P＜0.001)与AIH呈正相关关系，ALP、GGT与PBC(ALP: OR=1.309，P＜0.001；GGT: OR=1.168，P=0.007)及PSC(ALP: OR=1.208，P=0.037；GGT: OR=1.155，P=0.046)均存在正相关关系；逆向MR提示AIH与GGT(OR=1.004，P=0.021)、PBC/PSC与ALP(PBC: OR=1.007，P=0.018；PSC: OR=1.008，P=0.039)及GGT(PBC: OR=1.014，P=0.003；PSC: OR=1.010，P＜0.001)存在因果关联。 结论 基因预测水平上，ALT、AST增加AIH发病风险且AIH可能影响GGT水平，ALP、GGT与PBC、PSC存在双向因果关系，这为AILD的无创诊断及潜在治疗提供新思路。 Abstract:Objective To investigate the causal associations between liver function indices and autoimmune liver diseases (AILD) using a bidirectional two-sample Mendelian randomization (MR) approach. Methods Genome-wide association study (GWAS) data for liver function indices and AILD were obtained from the open GWAS database. Forward MR analysis was performed with 9 liver function indices including alanine transaminase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), γ-glutamyl transferase (GGT): as exposures, while 3 types of AILD autoimmune hepatitis (AIH), primary biliary cholangitis (PBC), and primary sclerosing cholangitis (PSC) were considered as outcomes. Reverse MR analysis was subsequently conducted to validate potential causal effects in the opposite direction. The inverse variance weighted (IVW) method was used as the primary analytical approach. Sensitivity analyses, including weighted median, MR-Egger, MR-PRESSO, horizontal pleiotropy test, and heterogeneity test were conducted to verify result robustness. Results Forward MR analysis showed that ALT (OR=1.719, 95% CI: 1.276-2.316, P < 0.001), AST (OR=1.358, 95% CI: 1.012-1.824, P=0.041), and GGT (OR=1.535, 95% CI: 1.255-1.877, P < 0.001) were positively associated with AIH. ALP and GGT exhibited positive causal relationships with PBC (ALP: OR=1.309, P < 0.001; GGT: OR=1.168, P=0.007) and PSC (ALP: OR=1.208, P=0.037; GGT: OR=1.155, P=0.046). Reverse MR analysis revealed causal associations between AIH and GGT (OR=1.004, P=0.021), PBC/PSC and ALP (PBC: OR=1.007, P=0.018; PSC: OR=1.008, P=0.039), as well as PBC/PSC and GGT (PBC: OR=1.014, P=0.003; PSC: OR=1.010, P < 0.001). Conclusion At the genetically predicted level, elevated ALT, AST, and GGT are associated with an increased risk of AIH, and AIH may, in turn, influence GGT levels. Bidirectional causal relationships were identified between ALP/GGT and PBC/PSC. These findings provide novel insights into the non-invasive diagnosis and potential therapeutic strategies for AILD. -
表 1 本研究中GWAS数据集来源
Table 1. Sources of GWAS datasets used in this study
暴露/结局 GWAS ID SNP数量 样本量/例 种族 年份 PubMed ID 丙氨酸氨基转移酶(ALT) ebi-a-GCST90025979 4 231 965 437 724 欧洲 2021 34226706 天门冬氨酸氨基转移酶(AST) ebi-a-GCST90025980 4 231 525 436 275 欧洲 2021 34226706 碱性磷酸酶(ALP) ebi-a-GCST90025947 4 232 004 437 896 欧洲 2021 34226706 γ-谷氨酰转肽酶(GGT) ebi-a-GCST90025966 4 231 983 437 651 欧洲 2021 34226706 总胆红素水平(Tbil) ebi-a-GCST90018973 19 046 135 342 829 欧洲 2021 34594039 直接胆红素水平(Dbil) ebi-a-GCST90025983 4 206 076 372 420 欧洲 2021 34226706 血清总蛋白(TP) ebi-a-GCST90025995 4 218 824 400 482 欧洲 2021 34226706 血清白蛋白(Alb) ebi-a-GCST90025992 4 219 040 400 938 欧洲 2021 34226706 胆汁酸水平(BA) ebi-a-GCST90060135 614 265 13 814 欧洲 2021 34503513 自身免疫性肝炎(AIH) ebi-a-GCST90018785 24 198 482 485 234 欧洲 2021 34594039 原发性胆汁性胆管炎(PBC) ebi-a-GCST90061440 5 004 018 24 510 欧洲 2021 34033851 原发性硬化性胆管炎(PSC) ieu-a-1112 7 891 603 14 890 欧洲 2017 27992413 
下载: 导出CSV
表 2 肝功能与AILD的正向MR分析
Table 2. Forward Mendelian randomization analysis of liver function and autoimmune liver disease
MR AIH PBC PSC 暴露 OR(95% CI) P值 暴露 OR(95% CI) P值 暴露 OR(95% CI) P值 IVW ALT 1.719(1.276~2.316) ＜0.001 ALT 1.151(0.923~1.437 0.212 ALT 0.866(0.667~1.125) 0.282 Weighted median 1.773(1.025~3.064) 0.040 1.035(0.793~1.350) 0.800 0.796(0.540~1.173) 0.249 MR Egger 2.092(1.205~3.630) 0.009 1.123(0.748~1.687) 0.577 0.914(0.505~1.654) 0.768 Simple mode 0.989(0.291~3.364) 0.986 0.924(0.491~1.739) 0.806 0.943(0.331~2.692) 0.913 Weighted mode 1.554(0.803~3.009) 0.192 1.048(0.795~1.381) 0.741 0.795(0.420~1.507) 0.483 IVW AST 1.358(1.012~1.824) 0.041 AST 1.007(0.838~1.210) 0.941 AST 0.826(0.636~1.072) 0.150 Weighted median 1.172(0.726~1.893) 0.516 1.021(0.788~1.324) 0.875 0.774(0.533~1.125) 0.179 MR Egger 1.261(0.727~2.187) 0.410 0.972(0.650~1.454) 0.892 0.903(0.486~1.679) 0.748 Simple mode 0.781(0.215~2.836) 0.708 0.898(0.501~1.609) 0.719 1.179(0.426~3.261) 0.751 Weighted mode 1.218(0.675~2.199) 0.513 0.991(0.796~1.233) 0.934 1.045(0.474~2.306) 0.913 IVW ALP 0.978(0.795~1.203) 0.835 ALP 1.309(1.121~1.528) 0.001 ALP 1.208(1.012~1.442) 0.037 Weighted median 0.955(0.673~1.355) 0.797 1.201(0.962~1.498) 0.106 1.113(0.841~1.474) 0.454 MR Egger 0.841(0.608~1.164) 0.298 1.126(0.885~1.431) 0.335 1.296(0.971~1.730) 0.080 Simple mode 0.871(0.404~1.878) 0.724 1.359(0.854~2.164) 0.197 1.110(0.561~2.198) 0.765 Weighted mode 0.871(0.606~1.252) 0.455 1.165(0.954~1.424) 0.136 1.054(0.740~1.501) 0.771 IVW GGT 1.535(1.255~1.877) ＜0.001 GGT 1.168(1.044~1.306) 0.007 GGT 1.155(1.002~1.331) 0.046 Weighted median 1.106(0.778~1.571) 0.575 0.997(0.867~1.145) 0.964 1.197(0.915~1.565) 0.189 MR Egger 1.692(1.241~2.308) 0.001 1.077(0.889~1.305) 0.449 1.423(1.138~1.781) 0.002 Simple mode 1.959(0.852~4.504) 0.114 1.130(0.739~1.729) 0.573 0.860(0.497~1.490) 0.591 Weighted mode 1.275(0.937~1.734) 0.123 1.010(0.891~1.145) 0.873 1.228(0.980~1.540) 0.076 IVW Tbil 1.043(0.906~1.201) 0.554 Tbil 1.064(0.985~1.150) 0.117 Tbil 1.009(0.695~1.465) 0.962 Weighted median 1.056(0.919~1.213) 0.443 1.062(0.996~1.132) 0.068 0.827(0.502~1.363) 0.456 MR Egger 1.056(0.907~1.229) 0.482 1.067(0.982~1.160) 0.131 1.060(0.567~1.981) 0.855 Simple mode 1.206(0.418~3.48) 0.729 1.034(0.524~2.042) 0.923 0.780(0.299~2.035) 0.612 Weighted mode 1.018(0.883~1.172) 0.809 1.060(0.988~1.136) 0.108 0.711(0.408~1.237) 0.230 IVW Dbil 1.110(0.929~1.326) 0.252 Dbil 0.892(0.697~1.143) 0.368 Dbil 0.840(0.600~1.177) 0.311 Weighted median 1.091(0.913~1.305) 0.338 0.657(0.480~0.899) 0.009 0.636(0.390~1.038) 0.070 MR Egger 1.110(0.911~1.352) 0.301 0.855(0.594~1.232) 0.404 0.837(0.465~1.508) 0.555 Simple mode 1.588(0.484~5.204) 0.447 0.712(0.332~1.527) 0.386 0.524(0.179~1.535) 0.241 Weighted mode 1.084(0.912~1.288) 0.360 0.712(0.516~0.982) 0.042 0.524(0.265~1.036) 0.066 IVW TP 1.342(0.973~1.852) 0.073 TP 1.244(0.986~1.568) 0.066 TP 0.805(0.628~1.033) 0.089 Weighted median 1.27(0.736~2.192) 0.391 1.169(0.842~1.623) 0.350 0.819(0.551~1.216) 0.322 MR Egger 1.295(0.643~2.607) 0.470 1.177(0.724~1.913) 0.511 0.692(0.413~1.158) 0.163 Simple mode 1.598(0.424~6.027) 0.489 1.714(0.773~3.803) 0.187 1.062(0.448~2.517) 0.892 Weighted mode 1.379(0.561~3.392) 0.484 1.152(0.754~1.761) 0.513 0.899(0.575~1.405) 0.641 IVW Alb 1.028(0.741~1.426) 0.868 Alb 0.969(0.849~1.105) 0.637 Alb 0.780(0.601~1.011) 0.061 Weighted median 1.109(0.668~1.842) 0.688 0.998(0.873~1.140) 0.974 0.916(0.630~1.331) 0.645 MR Egger 0.917(0.497~1.689) 0.780 0.836(0.589~1.188) 0.321 1.102(0.655~1.854) 0.715 Simple mode 1.081(0.318~3.676) 0.900 0.928(0.465~1.853) 0.833 1.570(0.642~3.842) 0.324 Weighted mode 1.024(0.475~2.209) 0.951 0.995(0.865~1.144) 0.941 1.003(0.604~1.666) 0.991 IVW BA 1.523(0.759~3.057) 0.236 BA 0.895(0.674~1.187) 0.441 BA 0.915(0.543~1.544) 0.740 Weighted median 1.913(0.776~4.714) 0.159 1.078(0.740~1.571) 0.696 0.948(0.502~1.790) 0.869 MR Egger 1.325(0.105~16.666) 0.838 0.887(0.382~2.060) 0.786 0.528(0.042~6.694) 0.656 Simple mode 1.968(0.486~7.962) 0.386 1.085(0.580~2.030) 0.804 1.043(0.470~2.313) 0.922 Weighted mode 1.936(0.537~6.983) 0.359 1.098(0.651~1.853) 0.734 0.972(0.477~1.980) 0.942
下载: 导出CSV
表 3 肝功能与AILD的逆向MR分析
Table 3. Reverse Mendelian randomization analysis of liver function and autoimmune liver disease
暴露 结局 nSNP Method方法 OR(95% CI) P值 多效性检验P值 异质性检验P值 AIH ALT 21 IVW 1.001(0.998~1.005) 0.394 0.059 0.463 AST 23 IVW 1.002(0.999~1.006) 0.247 0.277 0.198 ALP 12 IVW 0.998(0.992~1.004) 0.441 0.959 0.063 GGT 23 IVW 1.004(1.001~1.007) 0.021 0.668 0.887 Tbil 97 IVW 1.000(0.999~1.002) 0.641 0.244 0.626 Dbil 24 IVW 1.000(0.996~1.003) 0.819 0.608 0.093 TP 22 IVW 1.002(0.998~1.005) 0.334 0.217 0.299 Alb 22 IVW 1.002(0.998~1.005) 0.381 0.544 0.602 BA 21 IVW 0.983(0.965~1.001) 0.066 0.690 0.933 PBC ALT 23 IVW 1.002(0.995~1.008) 0.633 0.136 0.001 AST 22 IVW 1.003(0.997~1.008) 0.364 0.092 0.014 ALP 18 IVW 1.007(1.001~1.014) 0.018 0.885 0.003 GGT 14 IVW 1.014(1.005~1.023) 0.003 0.472 0.001 Tbil 34 IVW 1.003(0.998~1.008) 0.200 0.283 0.001 Dbil 22 IVW 1.003(0.996~1.010) 0.401 0.281 0.001 TP 13 IVW 1.001(0.993~1.009) 0.735 0.364 0.010 Alb 23 IVW 0.997(0.990~1.003) 0.333 0.746 0.001 BA 27 IVW 0.995(0.976~1.014) 0.606 0.523 0.422 PSC ALT 4 IVW 1.006(0.994~1.017) 0.328 0.370 0.156 AST 4 IVW 0.991(0.979~1.004) 0.166 0.169 0.002 ALP 5 IVW 1.008(1.000~1.015) 0.039 0.657 0.093 GGT 6 IVW 1.010(1.005~1.015) 0.000 0.634 0.352 Tbil 13 IVW 0.996(0.991~1.002) 0.163 0.757 0.753 Dbil 4 IVW 1.009(0.998~1.019) 0.107 0.464 0.226 TP 7 IVW 1.016(0.989~1.044) 0.236 0.584 0.000 Alb 4 IVW 0.996(0.986~1.006) 0.462 0.207 0.291 BA 5 IVW 0.984(0.941~1.028) 0.461 0.582 0.720
下载: 导出CSV
表 4 肝功能与AILD的正向敏感性分析
Table 4. Forward sensitivity analysis of liver function and autoimmune liver disease
暴露 AIH PBC PSC 多效性检验P值 异质性检验P值 多效性检验P值 异质性检验P值 多效性检验P值 异质性检验P值 ALT 0.407 0.317 0.886 < 0.001 0.843 0.006 AST 0.754 0.261 0.849 < 0.001 0.754 0.002 ALP 0.239 0.322 0.110 < 0.001 0.546 0.001 GGT 0.417 0.076 0.313 < 0.001 0.064 0.301 Tbil 0.670 0.063 0.847 0.005 0.848 0.001 Dbil 0.994 0.038 0.755 0.002 0.988 0.081 TP 0.909 0.032 0.801 < 0.001 0.511 0.003 Alb 0.663 0.120 0.378 0.008 0.134 < 0.001 BA 0.916 0.575 0.983 0.345 0.694 0.627
下载: 导出CSV
-
[1] HORST A K, KUMASHIE K G, NEUMANN K, et al. Antigen presentation, autoantibody production, and therapeutic targets in autoimmune liver disease[J]. Cell Mol Immunol, 2021, 18(1): 92-111. doi: 10.1038/s41423-020-00568-6 [2] 郑林华, 韩英. 2024年自身免疫性肝病研究进展[J]. 中华肝脏病杂志, 2025, 33(1): 10-12.ZHENG L H, HAN Y. Research progress in autoimmune liver diseases in 2024[J]. Chinese Journal of Hepatology, 2025, 33(1): 10-12. [3] TRIVEDI P J, HIRSCHFIELD G M, ADAMS D H, et al. Immunopathogenesis of primary biliary cholangitis, primary sclerosing cholangitis and autoimmune hepatitis: themes and concepts[J]. Gastroenterology, 2024, 166(6): 995-1019. doi: 10.1053/j.gastro.2024.01.049 [4] WANG L, HU Y F, YANG A Y, et al. Development and validation of a noninvasive prediction model of autoimmune hepatitis in patients with liver diseases[J]. Scand J Gastroenterol, 2024, 59(1): 62-69. doi: 10.1080/00365521.2023.2249571 [5] ZHANG H. Pros and cons of Mendelian randomization[J]. Fertil Steril, 2023, 119(6): 913-916. doi: 10.1016/j.fertnstert.2023.03.029 [6] LIU Z P, QIN Y M, WU T, et al. Reciprocal causation mixture model for robust Mendelian randomization analysis using genome-scale summary data[J]. Nat Commun, 2023, 14(1): 1131. DOI: 10.1038/s41467-023-36490-4. [7] BYRSKA-BISHOP M, EVANI U S, ZHAO X, et al. High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios[J]. Cell, 2022, 185(18): 3426-3440. e19. doi: 10.1016/j.cell.2022.08.004 [8] SANDERSON E, SPILLER W, BOWDEN J. Testing and correcting for weak and pleiotropic instruments in two-sample multivariable Mendelian randomization[J]. Stat Med, 2021, 40(25): 5434-5452. doi: 10.1002/sim.9133 [9] 张婷婷, 李惠, 张星平. 双向两样本孟德尔随机化探究慢性肾脏病及肾功能相关指标与失眠的因果关联[J]. 中华全科医学, 2025, 23(7): 1152-1156. doi: 10.16766/j.cnki.issn.1674-4152.004086ZHANG T T, LI H, ZHANG X P. Bidirectional two-sample mendelian randomization investigation of the causal association between chronic kidney disease and renal function related indicators with insomnia[J]. Chinese Journal of General Practice, 2025, 23(7): 1152-1156. doi: 10.16766/j.cnki.issn.1674-4152.004086 [10] KHAN M, LUDL A A, BANKIER S, et al. Prediction of causal genes at GWAS loci with pleiotropic gene regulatory effects using sets of correlated instrumental variables[J]. PLoS Genet, 2024, 20(11): e1011473. DOI: 10.1371/journal.pgen.1011473. [11] CHENG Q, ZHANG X, CHEN L S, et al. Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology[J]. Nat Commun, 2022, 13(1): 6490. DOI: 10.1038/s41467-022-34164-1. [12] BOEHM F J, ZHOU X. Statistical methods for Mendelian randomization in genome-wide association studies: a review[J]. Comput Struct Biotechnol J, 2022, 20: 2338-2351. doi: 10.1016/j.csbj.2022.05.015 [13] BURGESS S, DAVEY SMITH G, DAVIES N M, et al. Guidelines for performing Mendelian randomization investigations: update for summer 2023[J]. Wellcome Open Res, 2023, 4: 186. DOI: 10.12688/wellcomeopenres.15555.3. [14] MURATORI L, LOHSE A W, LENZI M. Diagnosis and management of autoimmune hepatitis[J]. BMJ, 2023, 380: e070201. DOI: 10.1136/bmj-2022-070201. [15] YANG H Y, HUANG L Y, XIE Y, et al. A diagnostic model of autoimmune hepatitis in unknown liver injury based on noninvasive clinical data[J]. Sci Rep, 2023, 13(1): 3996. DOI: 10.1038/s41598-023-31167-w. [16] WANG Z, SHENG L, YANG Y, et al. The management of autoimmune hepatitis patients with decompensated cirrhosis: real-world experience and a comprehensive review[J]. Clin Rev Allergy Immunol, 2017, 52(3): 424-435. doi: 10.1007/s12016-016-8583-2 [17] YANG Y S, HE X S, ROJAS M, et al. Mechanism-based target therapy in primary biliary cholangitis: opportunities before liver cirrhosis?[J]. Front Immunol, 2023, 14: 1184252. DOI: 10.3389/fimmu.2023.1184252. [18] WU H M, WANG Y, YAO Q Q, et al. Alkaline phosphatase attenuates LPS-induced liver injury by regulating the miR-146a-related inflammatory pathway[J]. Int Immunopharmacol, 2021, 101(Pt A): 108149. DOI: 10.1016/j.intimp.2021.108149. [19] HU Y F, LI S X, LIU H L, et al. Precirrhotic primary biliary cholangitis with portal hypertension: bile duct injury correlate[J]. Gut Liver, 2024, 18(5): 867-876. doi: 10.5009/gnl230468 [20] ZHU Y J, LI J, LIU Y G, et al. Role of biochemical markers and autoantibodies in diagnosis of early-stage primary biliary cholangitis[J]. World J Gastroenterol, 2023, 29(34): 5075-5081. doi: 10.3748/wjg.v29.i34.5075 [21] MARIA A, SOOD V, KHANNA R, et al. Association of HLA DRB1 allele profile with pediatric autoimmune liver disease in India[J]. J Clin Exp Hepatol, 2023, 13(3): 397-403. doi: 10.1016/j.jceh.2023.01.001 [22] HLADY R A, ZHAO X, EL KHOURY L Y, et al. Epigenetic heterogeneity hotspots in human liver disease progression[J]. Hepatology, 2025, 81(4): 1197-1210. doi: 10.1097/HEP.0000000000001023 -
点击查看大图
图(1) / 表(4)
计量
- 文章访问数: 3
- HTML全文浏览量: 1
- PDF下载量: 0
- 被引次数: 0
