Liver Enzyme Biomarkers Before or in Early Pregnancy as Predictors for Gestational Diabetes Mellitus
A Systematic Review and Meta-Analysis
DOI:
https://doi.org/10.15605/jafes.041.01.5807Keywords:
liver enzymes, gestational diabetes mellitus, pregnancy, meta-analysis, odds ratioAbstract
Background. Liver enzymes may reflect early metabolic disturbances and insulin resistance preceding gestational diabetes mellitus (GDM). This systematic review and meta-analysis evaluated whether liver enzyme biomarkers measured before or in early pregnancy are associated with subsequent development of GDM.
Methodology. PubMed, Cochrane, EBSCOHost, and SCOPUS databases were searched through May 2025 for observational studies or trials assessing pre- or early pregnancy liver enzymes in relation to GDM development. Pooled mean differences (MD) and odds ratios (OR) with 95% confidence intervals (CI) were calculated using a random-effects model. Risk of bias was assessed using RoB 2.0 and ROBINS-E; certainty of evidence was evaluated using GRADE.
Results. Twenty-seven studies were included in the analyses. GDM was associated with higher AST (MD 0.97 U/L; OR 1.42), ALT (MD 2.38 U/L; OR 1.69), GGT (MD 3.77 U/L; OR 2.57), and hepatic steatosis index (HSI) (MD 2.82; OR 2.19). ALP showed no significant mean difference but an elevated GDM risk (OR 1.47). Substantial heterogeneity was observed with very low certainty of evidence across outcomes.
Conclusion. Elevated liver enzymes, especially GGT and HSI, are associated with increased GDM risk at a population level. However, high heterogeneity and very low certainty of evidence limit current clinical applicability, warranting further prospective validation.
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References
ElSayed NA, Aleppo G, Aroda VR, Bannuru RR, Brown FM, Bruemmer D et al. Classification and diagnosis of diabetes: Standards of care in diabetes-2023. Diabetes Care. 2023;46(Suppl 1):S19-40. https://pubmed.ncbi.nlm.nih.gov/36507649/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9810477/ https://doi.org/10.2337/dc23-S002 DOI: https://doi.org/10.2337/dc23-S002
Li LJ, Huang L, Tobias DK, Zhang C. Gestational diabetes mellitus among Asians - A systematic review from a population health perspective. Front Endocrinol (Lausanne). 2022;13:840331. https://pubmed.ncbi.nlm.nih.gov/35784581/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9245567/ https://doi.org/10.3389/fendo.2022.840331 DOI: https://doi.org/10.3389/fendo.2022.840331
Kattini R, Hummelen R, Kelly L. Early gestational diabetes mellitus screening with glycated hemoglobin: A systematic review. J Obstet Gynaecol Can. 2020;42(11):1379-84. https://pubmed.ncbi.nlm.nih.gov/32268994/ https://doi.org/10.1016/j.jogc.2019.12.015 DOI: https://doi.org/10.1016/j.jogc.2019.12.015
Dong L, Zhong W, Qiao T, Wang Z, Liang Y, Zhao DQ. Investigation and study on the epidemiology of gestational diabetes mellitus in Guizhou. World J Diabetes. 2025;16(2):98438. https://pubmed.ncbi.nlm.nih.gov/39959259/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11718487/ https://doi.org/10.4239/wjd.v16.i2.98438 DOI: https://doi.org/10.4239/wjd.v16.i2.98438
Luo J, Tong L, Xu A, et al. Gestational diabetes mellitus: New thinking on diagnostic criteria. Life (Basel). 2024;14(12):1665. https://pubmed.ncbi.nlm.nih.gov/39768372/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11679338/ https://doi.org/10.3390/life14121665 DOI: https://doi.org/10.3390/life14121665
Perkumpulan Endokrinologi Indonesia. Pedoman Diagnosis dan Penatalaksanaan Hiperglikemia dalam Kehamilan 2021. 1st ed. Indonesia: PB PERKENI; 2021. https://pbperkeni.or.id/catalog-buku/pedoman-diaknosis-dan-penatalaksanaan-hiperglikemia-dalamkehamilan-2021
Pramodkumar TA, Hannah W, Anjana RM, et al. Biomarkers of gestational diabetes mellitus: Mechanisms, advances, and clinical utility. J Assoc Physicians India. 2025;73(2):56-67. https://pubmed.ncbi.nlm.nih.gov/39928001/ https://doi.org/10.59556/japi.73.0849 DOI: https://doi.org/10.59556/japi.73.0849
Zheng D, Zhang X, You L, et al. The association of liver enzymes with diabetes mellitus risk in different obesity subgroups: A population-based study. Front Endocrinol (Lausanne). 2022;13:961762. https://pubmed.ncbi.nlm.nih.gov/36313767/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9608349/ https://doi.org/10.3389/fendo.2022.961762 DOI: https://doi.org/10.3389/fendo.2022.961762
Park JY, Kim WJ, Chung YH, et al. Association between pregravid liver enzyme levels and gestational diabetes in twin pregnancies: A secondary analysis of national cohort study. Sci Rep. 2021;11(1):18695. https://pubmed.ncbi.nlm.nih.gov/34548558/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8455664/ https://doi.org/10.1038/s41598-021-98180-9 DOI: https://doi.org/10.1038/s41598-021-98180-9
Priego-Parra BA, Triana-Romero A, Martínez-Pérez GP, et al. Hepatic steatosis index (HSI): A valuable biomarker in subjects with metabolic dysfunction-associated fatty liver disease (MAFLD). Ann Hepatol. 2024;29:101391. https://doi.org/10.1016/j.aohep.2024.101391 DOI: https://doi.org/10.1016/j.aohep.2024.101391
Higgins JP, Morgan RL, Rooney AA, et al. A tool to assess risk of bias in non-randomized follow-up studies of exposure effects (ROBINS-E). Environ Int. 2024:186:108602. https://pubmed.ncbi.nlm.nih.gov/38555664/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11098530/ https://doi.org/10.1016/j.envint.2024.108602 DOI: https://doi.org/10.1016/j.envint.2024.108602
Sterne JAC, Savović J, Page MJ, et al. RoB 2: A revised tool for assessing risk of bias in randomised trials. BMJ. 2019:366:l4898. https://pubmed.ncbi.nlm.nih.gov/31462531/ https://doi.org/10.1136/bmj.l4898 DOI: https://doi.org/10.1136/bmj.l4898
McGuinness LA, Higgins JPT. Risk-of-bias VISualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res Synth Methods. 2021:12(1):55-61. https://pubmed.ncbi.nlm.nih.gov/32336025/ https://doi.org/10.1002/jrsm.1411 DOI: https://doi.org/10.1002/jrsm.1411
Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. Int J Surg. 2021;88:105906. https://pubmed.ncbi.nlm.nih.gov/33789826/ https://doi.org/10.1016/j.ijsu.2021.105906 DOI: https://doi.org/10.1016/j.ijsu.2021.105906
Prasad M. Introduction to the GRADE tool for rating certainty in evidence and recommendations. Clinical Epidemiology and Global Health. 2024;25:101484. https://doi.org/10.1016/j.cegh.2023.101484 DOI: https://doi.org/10.1016/j.cegh.2023.101484
Maitland RA, Seed PT, Briley AL, et al. Prediction of gestational diabetes in obese pregnant women from the UK pregnancies better eating and activity (UPBEAT) pilot trial. Diabet Med. 2014;31(8):963-70. https://pubmed.ncbi.nlm.nih.gov/24798080/
https://doi.org/10.1111/dme.12482 DOI: https://doi.org/10.1111/dme.12482
Sridhar SB, Xu F, Darbinian J, Quesenberry CP, Ferrara A, Hedderson MM. Pregravid liver enzyme levels and risk of gestational diabetes mellitus during a subsequent pregnancy. Diabetes Care. 2014;37(7):1878-84. https://pubmed.ncbi.nlm.nih.gov/24795397/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4067389/ https://doi.org/10.2337/dc13-2229 DOI: https://doi.org/10.2337/dc13-2229
Zhao LL, Li W, Ping, Ma LK, Nie M. Associations of white blood cell count, alanine aminotransferase, and aspartate aminotransferase in the first trimester with gestational diabetes mellitus. Zhongguo Yi Xue Ke Xue Yuan Xue Bao. 2016;38(3):283-7 https://pubmed.ncbi.nlm.nih.gov/27469912/ https://doi.org/10.3881/j.issn.1000-503X.2016.03.007
White SL, Lawlor DA, Briley AL, et al; UPBEAT Consortium. Early antenatal prediction of gestational diabetes in obese women: Development of prediction tools for targeted intervention. PLoS One. 2016;11(12):e0167846. https://pubmed.ncbi.nlm.nih.gov/27930697/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5145208/ https://doi.org/10.1371/journal.pone.0167846 DOI: https://doi.org/10.1371/journal.pone.0167846
Leng J, Zhang C, Wang P, et al. Plasma levels of alanine aminotransferase in the first trimester identify high risk Chinese women for gestational diabetes. Sci Rep. 2016;6:27291 https://pubmed.ncbi.nlm.nih.gov/27264612/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4893691/ https://doi.org/10.1038/srep27291 Yarrington CD, Cantonwine DE, Seely EW, McElrath TF, Zera CA. The association of alanine aminotransferase in early pregnancy with gestational diabetes. Metab Syndr Relat Disord. 2016;14(5):254-8. https://pubmed.ncbi.nlm.nih.gov/26959309/ https://doi.org/10.1089/met.2015.0106 DOI: https://doi.org/10.1089/met.2015.0106
Kong M, Liu C, Guo Y, et al. Higher level of GGT during midpregnancy is associated with increased risk of gestational diabetes mellitus. Clin Endocrinol (Oxf). 2018;88(5):700-5 https://pubmed.ncbi.nlm.nih.gov/29385633/ https://doi.org/10.1111/cen.13558 DOI: https://doi.org/10.1111/cen.13558
Zhu Y, Hedderson MM, Quesenberry CP, et al. Liver enzymes in early to mid-pregnancy, insulin resistance, and gestational diabetes risk: A longitudinal analysis. Front Endocrinol (Lausanne). 2018;9:581 https://pubmed.ncbi.nlm.nih.gov/30333792/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6176077/ https://doi.org/10.3389/fendo.2018.00581 DOI: https://doi.org/10.3389/fendo.2018.00581
Xiong T, Zhong C, Sun G, et al. Early maternal circulating alkaline phosphatase with subsequent gestational diabetes mellitus and glucose regulation: a prospective cohort study in China. Endocrine. 2019;65(2):295-303. https://pubmed.ncbi.nlm.nih.gov/31115769/ https://doi.org/10.1007/s12020-019-01954-5 DOI: https://doi.org/10.1007/s12020-019-01954-5
Correa PJ, Venegas P, Palmeiro Y, et al. First trimester prediction of gestational diabetes mellitus using plasma biomarkers: a case-control study. J Perinat Med. 2019;47(2):161-8 https://pubmed.ncbi.nlm.nih.gov/30205647/ https://doi.org/10.1515/jpm-2018-0120 DOI: https://doi.org/10.1515/jpm-2018-0120
Lee SM, Kwak SH, Koo JN, et al. Non-alcoholic fatty liver disease in the first trimester and subsequent development of gestational diabetes mellitus. Diabetologia. 2019;62(2):238-48. https://pubmed.ncbi.nlm.nih.gov/30470912/ https://doi.org/10.1007/s00125-018-4779-8 DOI: https://doi.org/10.1007/s00125-018-4779-8
Gao S, Leng J, Liu H, et al. Development and validation of an early pregnancy risk score for the prediction of gestational diabetes mellitus in Chinese pregnant women. BMJ Open Diabetes Res Care. 2020;8(1):e000909. https://pubmed.ncbi.nlm.nih.gov/32327440/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202751/ https://doi.org/10.1136/bmjdrc-2019-000909 DOI: https://doi.org/10.1136/bmjdrc-2019-000909
Lee SM, Park JS, Han YJ, et al. Elevated alanine aminotransferase in early pregnancy and subsequent development of gestational diabetes and preeclampsia. J Korean Med Sci. 2020;35(26):e198 https://pubmed.ncbi.nlm.nih.gov/32627436/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338210/ https://doi.org/10.3346/jkms.2020.35.e198 DOI: https://doi.org/10.3346/jkms.2020.35.e198
Zhao M, Yang S, Hung TC, et al. Association of pre- and early-pregnancy factors with the risk for gestational diabetes mellitus in a large Chinese population. Sci Rep. 2021;11(1):7335. https://pubmed.ncbi.nlm.nih.gov/33795771/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8016847/ https://doi.org/10.1038/s41598-021-86818-7 DOI: https://doi.org/10.1038/s41598-021-86818-7
Kim WJ, Chung Y, Park J, et al. Influences of pregravid liver enzyme levels on the development of gestational diabetes mellitus. Liver Int. 2021;41(4):743-53. https://pubmed.ncbi.nlm.nih.gov/33314623/ https://doi.org/10.1111/liv.14759 DOI: https://doi.org/10.1111/liv.14759
You SY, Han K, Lee SH, Kim MK. Nonalcoholic fatty liver disease and the risk of insulin-requiring gestational diabetes. Diabetol Metab Syndr. 2021;13(1):90. https://pubmed.ncbi.nlm.nih.gov/34446090/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8393465/
https://doi.org/10.1186/s13098-021-00710-y DOI: https://doi.org/10.1186/s13098-021-00710-y
Wang N, Peng Y, Wang L, et al. Risk factors screening for gestational diabetes mellitus heterogeneity in Chinese pregnant women: A case-control study. Diabetes Metab Syndr Obes. 2021;14:951-61. https://pubmed.ncbi.nlm.nih.gov/33688229/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7936674/ https://doi.org/10.2147/DMSO.S295071 DOI: https://doi.org/10.2147/DMSO.S295071
Song S, Duo Y, Zhang Y, et al. The predictive ability of hepatic steatosis index for gestational diabetes mellitus and large for gestational age infant compared with other noninvasive indices among Chinese pregnancies: A preliminary double-center cohort study. Diabetes Metab Syndr Obes. 2021;14:4791-800. https://pubmed.ncbi.nlm.nih.gov/34938090/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8687517/ https://doi.org/10.2147/DMSO.S335364 DOI: https://doi.org/10.2147/DMSO.S335364
Song S, Zhang Y, Qiao X, et al. ALT/AST as an independent risk factor of gestational diabetes mellitus compared with TG/HDL-C. Int J Gen Med. 2022;15:115-21. https://pubmed.ncbi.nlm.nih.gov/35023950/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8743491/
https://doi.org/10.2147/IJGM.S332946 DOI: https://doi.org/10.2147/IJGM.S332946
An R, Ma S, Zhang N, et al. AST-to-ALT ratio in the first trimester and the risk of gestational diabetes mellitus. Front Endocrinol (Lausanne). 2022;13:1017448. https://pubmed.ncbi.nlm.nih.gov/36246899/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9558287/
https://doi.org/10.3389/fendo.2022.1017448 DOI: https://doi.org/10.3389/fendo.2022.1017448
Quotah OF, Poston L, Flynn AC, White SL. Metabolic profiling of pregnant women with obesity: an exploratory study in women at greater risk of gestational diabetes. Metabolites. 2022;12(10):922.. https://pubmed.ncbi.nlm.nih.gov/36295825/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9612230/
https://doi.org/10.3390/metabo12100922 DOI: https://doi.org/10.3390/metabo12100922
Duo Y, Song S, Qiao X, et al. A simplified screening model to predict the risk of gestational diabetes mellitus in pregnant Chinese women. Diabetes Ther. 2023;14(12):2143-57. https://pubmed.ncbi.nlm.nih.gov/37843770/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10597926/ https://doi.org/10.1007/s13300-023-01480-8 DOI: https://doi.org/10.1007/s13300-023-01480-8
Wu P, Wang Y, Ye Y, et al. Liver biomarkers, lipid metabolites, and risk of gestational diabetes mellitus in a prospective study among Chinese pregnant women. BMC Med. 2023;21(1):150. https://pubmed.ncbi.nlm.nih.gov/37069659/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10111672/ https://doi.org/10.1186/s12916-023-02818-6 DOI: https://doi.org/10.1186/s12916-023-02818-6
Lee SH, Yu J, Han K, et al. Predicting the risk of insulin-requiring gestational diabetes before pregnancy: A model generated from a nationwide population-based cohort study in Korea. Endocrinol Metab (Seoul). 2023;38(1):129-38. https://pubmed.ncbi.nlm.nih.gov/36702473/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10008663/
https://doi.org/10.3803/EnM.2022.1609 DOI: https://doi.org/10.3803/EnM.2022.1609
An Z, Niu T, Lu Y, et al. Nonlinear association between alanine aminotransferase to high-density lipoprotein cholesterol ratio and risk of gestational diabetes mellitus. Sci Rep. 2024;14(1):24872. https://pubmed.ncbi.nlm.nih.gov/39438670/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11496691/ https://doi.org/10.1038/s41598-024-76656-8 DOI: https://doi.org/10.1038/s41598-024-76656-8
Liu H, Zhang L, Cheng H, et al. The associations of maternal liver biomarkers in early pregnancy with the risk of gestational diabetes mellitus: a prospective cohort study and Mendelian randomization analysis. Front Endocrinol (Lausanne). 2024;15:1396347. https://pubmed.ncbi.nlm.nih.gov/38836232/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11148214/
https://doi.org/10.3389/fendo.2024.1396347 DOI: https://doi.org/10.3389/fendo.2024.1396347
Sonagra AD, Biradar SM, Dattatreya K, Murthy JDS. Normal pregnancy—a state of insulin resistance. J Clin Diagn Res. 2014;8(11):CC01-3. https://pubmed.ncbi.nlm.nih.gov/25584208/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4290225/ https://doi.org/10.7860/JCDR/2014/10068.5081 DOI: https://doi.org/10.7860/JCDR/2014/10068.5081
Purnamasari D, Waspadji S, Adam JMF, Rudijanto A, Tahapary D. Indonesian clinical practice guidelines for diabetes in pregnancy. J ASEAN Fed Endocr Soc. 2013;28(1):9-13. DOI: https://doi.org/10.15605/jafes.028.01.02
Rafaqat S, Sattar A, Khalid A, Rafaqat S. Role of liver parameters in diabetes mellitus - A narrative review. Endocr Regul. 2023;57(1):200-20. https://pubmed.ncbi.nlm.nih.gov/37715985/ https://doi.org/10.2478/enr-2023-0024 DOI: https://doi.org/10.2478/enr-2023-0024
Zhao W, Zhang L, Zhang G, et al. The association of plasma levels of liver enzymes and risk of gestational diabetes mellitus: A systematic review and dose-response meta-analysis of observational studies. Acta Diabetol. 2020;57(6):635-44 https://pubmed.ncbi.nlm.nih.gov/31781958/ https://doi.org/10.1007/s00592-019-01458-8 DOI: https://doi.org/10.1007/s00592-019-01458-8
Nogueira JP, Cusi K. Role of insulin resistance in the development of nonalcoholic fatty liver disease in people with type 2 diabetes: From bench to patient care. Diabetes Spectr. 2024;37(1):20-28 https://pubmed.ncbi.nlm.nih.gov/38385099/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10877218/ https://doi.org/10.2337/dsi23-0013 DOI: https://doi.org/10.2337/dsi23-0013
Lozo S, Atabeygi A, Healey M. Extreme elevation of alkaline phosphatase in a pregnancy complicated by gestational diabetes and infant with neonatal alloimmune thrombocytopenia. Case Rep Obstet Gynecol. 2016;2016:4896487. https://pubmed.ncbi.nlm.nih.gov/27610256/ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5005538/ https://doi.org/10.1155/2016/4896487 DOI: https://doi.org/10.1155/2016/4896487
Sheiner E. Gestational diabetes mellitus: long-term consequences for the mother and child grand challenge: how to move on towards secondary prevention? Front Clin Diabetes Healthc. 2020;1:546256. https://pubmed.ncbi.nlm.nih.gov/36993989/
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10041873/ https://doi.org/10.3389/fcdhc.2020.546256 DOI: https://doi.org/10.3389/fcdhc.2020.546256
Perämäki R, Gissler M, Ollila MM, et al. The risk of developing type 2 diabetes after gestational diabetes: A registry study from Finland. Diabetes Metab Syndr. 2022;100124. https://doi.org/10.1016/j.deman.2022.100124 DOI: https://doi.org/10.1016/j.deman.2022.100124
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