Enhancing Clinical Decision-Making in Gestational Diabetes Through Metabolomics: A Pharmacy Practice Outlook
Main Article Content
Keywords
Gestational Diabetes Mellitus, MetaboAnalyst, UHPLC-ESI-QTOF-MS, metabolic pathways, metabolic profiling, metabolites, untargeted metabolomics
Abstract
Gestational diabetes mellitus (GDM) is a pregnancy complication associated with glucose intolerance and an increased risk of type 2 diabetes. Metabolic alterations, including changes in amino acids, fatty acids, and glycolysis, have been linked to GDM. However, comprehensive metabolomics analyses, particularly in Middle Eastern women cohort, are lacking. This study aims to identify unique metabolic pathways to enhance understanding of disease progression and guide diagnosis and targeted therapeutic strategies. Blood samples were collected from 32 women with GDM and 21 healthy pregnant women. Metabolomic analysis was performed using trapped ion mobility spectrometry time-of-flight mass spectrometry. Statistical analysis included a two-tailed independent Student’s t-test, with a significance threshold of p < 0.05. Out of 108 identified metabolites student’s t-test analysis revealed 33 statistically significant metabolites (P < 0.05) in GDM group compared to healthy pregnant women. Of them, citramalic acid, creatinine, D-arginine, and glutamine were significantly reduced in GDM, while 4-aminohippuric acid, homovanillic acid, alpha-aspartyl-lysine, L-aspartyl-L-phenylalanine, L-valine, L-leucine, and normetanephrine were increased. Pathway analysis further highlighted phenylacetate metabolism as a key pathway upregulated in GDM. This underscores the potential significance of phenylacetate metabolism in the metabolic alterations associated with GDM. A comprehensive understanding of metabolic alteration in GDM provides valuable insights into the factors influencing the metabolic environment of pregnant women with GDM. This knowledge not only enhances our understanding of the molecular mechanisms underlying GDM but also paves away for developing diagnostic and targeted therapeutic strategies. By addressing dysregulated metabolomic pathways, these findings hold the potential for improving the management and prevention of GDM.
References
1. Szmuilowicz ED, Josefson JL, Metzger BE. Gestational Diabetes Mellitus. Endocrinol Metab Clin North Am. 2019 Sep;48(3):479–93.
2. Capula C, Chiefari E, Vero A, Foti DP, Brunetti A, Vero R. Prevalence and predictors of postpartum glucose intolerance in Italian women with gestational diabetes mellitus. Diabetes Res Clin Pract. 2014 Aug;105(2):223–30.
3. Boney CM, Verma A, Tucker R, Vohr BR. Metabolic Syndrome in Childhood: Association With Birth Weight, Maternal Obesity, and Gestational Diabetes Mellitus. Pediatrics. 2005 Mar 1;115(3):e290–6.
4. Muche AA, Olayemi OO, Gete YK. Prevalence and determinants of gestational diabetes mellitus in Africa based on the updated international diagnostic criteria: a systematic review and meta-analysis. Archives of Public Health. 2019 Dec 6;77(1):36.
5. TEH WT, TEEDE HJ, PAUL E, HARRISON CL, WALLACE EM, ALLAN C. Risk factors for gestational diabetes mellitus: Implications for the application of screening guidelines. Australian and New Zealand Journal of Obstetrics and Gynaecology. 2011 Feb;51(1):26–30.
6. Kautzky-Willer A, Harreiter J, Winhofer-Stöckl Y, Bancher-Todesca D, Berger A, Repa A, et al. Gestationsdiabetes (GDM) (Update 2019). Wien Klin Wochenschr. 2019 May 12;131(S1):91–102.
7. Thayer SM, Lo JO, Caughey AB. Gestational Diabetes. Obstet Gynecol Clin North Am. 2020 Sep;47(3):383–96.
8. Yamamoto JM, Kellett JE, Balsells M, García-Patterson A, Hadar E, Solà I, et al. Gestational Diabetes Mellitus and Diet: A Systematic Review and Meta-analysis of Randomized Controlled Trials Examining the Impact of Modified Dietary Interventions on Maternal Glucose Control and Neonatal Birth Weight. Diabetes Care. 2018 Jul 1;41(7):1346–61.
9. Al-Daffaie FM, Al-Mudhafar SF, Alhomsi A, Tarazi H, Almehdi AM, El-Huneidi W, et al. Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications. Int J Mol Sci. 2024 May 7;25(10):5071.
10. Johnson CH, Ivanisevic J, Siuzdak G. Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol. 2016 Jul 16;17(7):451–9.
11. Cui L, Lu H, Lee YH. Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases. Mass Spectrom Rev. 2018 Nov 27;37(6):772–92.
12. Ortmayr K, Causon TJ, Hann S, Koellensperger G. Increasing selectivity and coverage in LC-MS based metabolome analysis. TrAC Trends in Analytical Chemistry. 2016 Sep;82:358–66.
13. Abufares HI, Zenati RA, Soares NC, El-Huneidi W, Dahabiyeh LA, Al-Hroub HM, et al. A non-targeted metabolomics comparative study on plasma of pfizer and sinopharm COVID-19 vaccinated individuals, assessed by (TIMS-QTOF) mass spectrometry. Heliyon. 2024 Aug;10(15):e35443.
14. Hassanein MM, Hagyousif YA, Zenati RA, Al-Hroub HM, Khan FM, Abuhelwa AY, et al. Metabolomics insights into doxorubicin and 5-fluorouracil combination therapy in triple-negative breast cancer: a xenograft mouse model study. Front Mol Biosci. 2025 Jan 13;11.
15. Chen P, Wang S, Ji J, Ge A, Chen C, Zhu Y, et al. Risk Factors and Management of Gestational Diabetes. Cell Biochem Biophys. 2015 Mar 1;71(2):689–94.
16. Babes EE, Bustea C, Behl T, Abdel-Daim MM, Nechifor AC, Stoicescu M, et al. Acute coronary syndromes in diabetic patients, outcome, revascularization, and antithrombotic therapy. Biomedicine & Pharmacotherapy. 2022 Apr;148:112772.
17. Feleke BE, Feleke TE, Adane WG, Kassahun MB, Girma A, Alebachew A, et al. Maternal and newborn effects of gestational diabetes mellitus: A prospective cohort study. Prim Care Diabetes. 2022 Feb;16(1):89–95.
18. Yao D, Shen C, Zhang X, Tang J, Yu J, Tu M, et al. Untargeted metabolomics study of mature human milk from women with and without gestational diabetes mellitus. Food Chem. 2024 Dec;460:140663.
19. Miller AJ, Arnold AC. The renin–angiotensin system in cardiovascular autonomic control: recent developments and clinical implications. Clinical Autonomic Research. 2019 Apr 9;29(2):231–43.
20. Qiu G, Lin Y, Ouyang Y, You M, Zhao X, Wang H, et al. Nontargeted Metabolomics Revealed Novel Association Between Serum Metabolites and Incident Acute Coronary Syndrome: A Mendelian Randomization Study. J Am Heart Assoc. 2023 Jul 4;12(13).
21. Altmaier E, Menni C, Heier M, Meisinger C, Thorand B, Quell J, et al. The Pharmacogenetic Footprint of ACE Inhibition: A Population-Based Metabolomics Study. PLoS One. 2016 Apr 27;11(4):e0153163.
22. Altmaier E, Fobo G, Heier M, Thorand B, Meisinger C, Römisch-Margl W, et al. Metabolomics approach reveals effects of antihypertensives and lipid-lowering drugs on the human metabolism. Eur J Epidemiol. 2014 May 10;29(5):325–36.
23. Plaza A, Merino B, Del Olmo N, Ruiz‐Gayo M. The cholecystokinin receptor agonist, CCK‐8, induces adiponectin production in rat white adipose tissue. Br J Pharmacol. 2019 Aug 20;176(15):2678–90.
24. Plaza A, Merino B, Cano V, Domínguez G, Pérez-Castells J, Fernández-Alfonso MS, et al. Cholecystokinin is involved in triglyceride fatty acid uptake by rat adipose tissue. Journal of Endocrinology. 2018 Mar;236(3):137–50.
25. Halland M, Bharucha AE. Relationship Between Control of Glycemia and Gastric Emptying Disturbances in Diabetes Mellitus. Clinical Gastroenterology and Hepatology. 2016 Jul;14(7):929–36.
26. Zhou Q, Sun WW, Chen JC, Zhang HL, Liu J, Lin Y, et al. Phenylalanine impairs insulin signaling and inhibits glucose uptake through modification of IRβ. Nat Commun. 2022 Jul 25;13(1):4291.
27. Ríos H, Brusco A, Saavedra JP. Development of serotoninergic chick retinal neurons. International Journal of Developmental Neuroscience. 1997 Oct 15;15(6):729–38.
28. Chu KO, Chan TI, Chan KP, Yip YW, Bakthavatsalam M, Wang CC, et al. Untargeted metabolomic analysis of aqueous humor in diabetic macular edema. Mol Vis. 2022;28:230–44.
29. Liu T, Li J, Xu F, Wang M, Ding S, Xu H, et al. Comprehensive analysis of serum metabolites in gestational diabetes mellitus by UPLC/Q-TOF-MS. Anal Bioanal Chem. 2016 Feb 16;408(4):1125–35.
30. ŠTOLBA P, OPLTOVÁ H, HUŠEK P, NEDVÍDKOVÁ J, KUNEŠ J, DOBEŠOVÁ Z, et al. Adrenergic Overactivity and Insulin Resistance in Nonobese Hereditary Hypertriglyceridemic Rats a. Ann N Y Acad Sci. 1993 Jun 17;683(1):281–8.
31. Rodríguez-Romero V, González-Villalva KI, Reyes JL, Franco-Bourland RE, Guízar-Sahagún G, Castañeda-Hernández G, et al. A novel, simple and inexpensive procedure for the simultaneous determination of iopamidol and p-aminohippuric acid for renal function assessment from plasma samples in awake rats. J Pharm Biomed Anal. 2015 Mar;107:196–203.
32. Karabacak M, Cinar Z, Cinar M. A structural and spectroscopic study on para-aminohippuric acid with experimental and theoretical approaches. Spectrochim Acta A Mol Biomol Spectrosc. 2012 Jan;85(1):241–50.
33. Raoof JB, Ojani R, Baghayeri M, Ahmadi F. Fabrication of a fast, simple and sensitive voltammetric sensor for the simultaneous determination of 4-aminohippuric acid and uric acid using a functionalized multi-walled carbon nanotube modified glassy carbon electrode. Analytical Methods. 2012;4(6):1825.
34. Chen H, Yuan B, Miao H, Tan Y, Bai X, Zhao YY, et al. Urine metabolomics reveals new insights into hyperlipidemia and the therapeutic effect of rhubarb. Analytical Methods. 2015;7(7):3113–23.
35. Sun R, Zhang J, Xiong M, Chen Y, Yin L, Pu Y. Metabonomics Biomarkers for Subacute Toxicity Screening for Benzene Exposure in Mice. J Toxicol Environ Health A. 2012 Sep 15;75(18):1163–73.
36. Jin W, Huang P, Chen Y, Wu F, Wan Y. Colorimetric detection of Cr3+ using gold nanoparticles functionalized with 4-amino hippuric acid. Journal of Nanoparticle Research. 2015 Sep 8;17(9):358.
37. Agudiez M, Martinez PJ, Martin-Lorenzo M, Heredero A, Santiago-Hernandez A, Molero D, et al. Analysis of urinary exosomal metabolites identifies cardiovascular risk signatures with added value to urine analysis. BMC Biol. 2020 Dec 14;18(1):192.
38. Oeltmann T, Carson R, Shannon JR, Ketch T, Robertson D. Assessment of O-methylated catecholamine levels in plasma and urine for diagnosis of autonomic disorders. Autonomic Neuroscience. 2004 Nov;116(1–2):1–10.
39. Serednytskyy O, Alonso-Fernández A, Ribot C, Herranz A, Álvarez A, Sánchez A, et al. Systemic inflammation and sympathetic activation in gestational diabetes mellitus with obstructive sleep apnea. BMC Pulm Med. 2022 Dec 18;22(1):94.
40. Holeček M. Why Are Branched-Chain Amino Acids Increased in Starvation and Diabetes? Nutrients. 2020 Oct 11;12(10):3087.
41. McCormack SE, Shaham O, McCarthy MA, Deik AA, Wang TJ, Gerszten RE, et al. Circulating branched‐chain amino acid concentrations are associated with obesity and future insulin resistance in children and adolescents. Pediatr Obes. 2013 Feb 7;8(1):52–61.
42. Holeček M. The Role of Skeletal Muscle in The Pathogenesis of Altered Concentrations of Branched-Chain Amino Acids (Valine, Leucine, and Isoleucine) in Liver Cirrhosis, Diabetes, and Other Diseases. Physiol Res. 2021 Jun 30;293–305.
43. Gadgil MD, Ingram KH, Appiah D, Rudd J, Whitaker KM, Bennett WL, et al. Prepregnancy Protein Source and BCAA Intake Are Associated with Gestational Diabetes Mellitus in the CARDIA Study. Int J Environ Res Public Health. 2022 Oct 29;19(21):14142.
44. Avagliano L, Garò C, Marconi AM. Placental Amino Acids Transport in Intrauterine Growth Restriction. J Pregnancy. 2012;2012:1–6.
45. Cleal JK, Lofthouse EM, Sengers BG, Lewis RM. A systems perspective on placental amino acid transport. J Physiol. 2018 Dec 7;596(23):5511–22.
46. Zheng HY, Wang L, Zhang R, Ding R, Yang CX, Du ZQ. Valine induces inflammation and enhanced adipogenesis in lean mice by multi-omics analysis. Front Nutr. 2024 May 13;11.
47. Calvo MJ, Parra H, Santeliz R, Bautista J, Luzardo E, Villasmil N, et al. The Placental Role in Gestational Diabetes Mellitus: A Molecular Perspective. touchREVIEWS in Endocrinology. 2024;20(1).
48. Zhou Y, Zhao R, Lyu Y, Shi H, Ye W, Tan Y, et al. Serum and Amniotic Fluid Metabolic Profile Changes in Response to Gestational Diabetes Mellitus and the Association with Maternal–Fetal Outcomes. Nutrients. 2021 Oct 18;13(10):3644.
49. Zhao H, Li H, Chung ACK, Xiang L, Li X, Zheng Y, et al. Large-Scale Longitudinal Metabolomics Study Reveals Different Trimester-Specific Alterations of Metabolites in Relation to Gestational Diabetes Mellitus. J Proteome Res. 2018 Dec 12;acs.jproteome.8b00602.
50. Meng X, Zhu B, Liu Y, Fang L, Yin B, Sun Y, et al. Unique Biomarker Characteristics in Gestational Diabetes Mellitus Identified by LC-MS-Based Metabolic Profiling. J Diabetes Res. 2021 Jun 9;2021:1–15.
51. Takeda R, Demura M, Sugimura Y, Miyamori I, Konoshita T, Yamamoto H. Pregnancy-associated diabetes insipidus in Japan-a review based on quoting from the literatures reported during the period from 1982 to 2019. Endocr J. 2021 Apr 28;68(4):375–85.
52. Heymsfield S, Arteaga C, McManus C, Smith J, Moffitt S. Measurement of muscle mass in humans: validity of the 24-hour urinary creatinine method. Am J Clin Nutr. 1983 Mar;37(3):478–94.
53. Hu H, Nakagawa T, Honda T, Yamamoto S, Okazaki H, Yamamoto M, et al. Low serum creatinine and risk of diabetes: The Japan Epidemiology Collaboration on Occupational Health Study. J Diabetes Investig. 2019 Sep 2;10(5):1209–14.
54. Chen N, Zeng R, Xu C, Lai F, Chen L, Wang C, et al. Low Serum Creatinine Levels in Early Pregnancy Are Associated with a Higher Incidence of Postpartum Abnormal Glucose Metabolism among Women with Gestational Diabetes Mellitus: A Retrospective Cohort Study. Nutrients. 2023 May 5;15(9):2193.
55. Wu X, Xie C, Zhang Y, Fan Z, Yin Y, Blachier F. Glutamate–glutamine cycle and exchange in the placenta–fetus unit during late pregnancy. Amino Acids. 2015 Jan 16;47(1):45–53.
56. Prada PO, Hirabara SM, Souza CT de, Schenka AA, Zecchin HG, Vassallo J, et al. RETRACTED ARTICLE:l-glutamine supplementation induces insulin resistance in adipose tissue and improves insulin signalling in liver and muscle of rats with diet-induced obesity. Diabetologia. 2007 Sep 29;50(9):1949–59.
57. Deters BJ, Saleem M. The role of glutamine in supporting gut health and neuropsychiatric factors. Food Science and Human Wellness. 2021 Mar;10(2):149–54.
58. McIntyre KR, Vincent KMM, Hayward CE, Li X, Sibley CP, Desforges M, et al. Human placental uptake of glutamine and glutamate is reduced in fetal growth restriction. Sci Rep. 2020 Oct 1;10(1):16197.
59. Ezrokhi M, Luo S, Trubitsyna Y, Cincotta AH. Neuroendocrine and metabolic components of dopamine agonist amelioration of metabolic syndrome in SHR rats. Diabetol Metab Syndr. 2014 Dec 25;6(1):104.
60. Newgard CB, An J, Bain JR, Muehlbauer MJ, Stevens RD, Lien LF, et al. A Branched-Chain Amino Acid-Related Metabolic Signature that Differentiates Obese and Lean Humans and Contributes to Insulin Resistance. Cell Metab. 2009 Apr;9(4):311–26.
61. Landsberg L, Aronne LJ, Beilin LJ, Burke V, Igel LI, Lloyd‐Jones D, et al. Obesity‐Related Hypertension: Pathogenesis, Cardiovascular Risk, and Treatment. The Journal of Clinical Hypertension. 2013 Jan 18;15(1):14–33.
62. Aleidi SM, Al Fahmawi H, AlMalki RH, Al Mogren M, Alwahsh M, Mujammami M, et al. Untargeted metabolomics profiling of gestational diabetes mellitus: insights into early diagnosis and metabolic pathway alterations. Front Mol Biosci. 2024 Dec 23;11.
63. Borges Manna L, Syngelaki A, Würtz P, Koivu A, Sairanen M, Pölönen T, et al. First-trimester nuclear magnetic resonance–based metabolomic profiling increases the prediction of gestational diabetes mellitus. Am J Obstet Gynecol. 2024 Dec.
64. Xu Z, Fang J, Wang Y, Wu X, Liu L, Cui X, et al. Targeted metabolomics reveals novel biomarkers for gestational diabetes mellitus. Diabetes Obes Metab. 2025 Apr 30;27(4):2163–72.
65. Razo-Azamar M, Nambo-Venegas R, Meraz-Cruz N, Guevara-Cruz M, Ibarra-González I, Vela-Amieva M, et al. An early prediction model for gestational diabetes mellitus based on metabolomic biomarkers. Diabetol Metab Syndr. 2023 Jun 1;15(1):116.
66. Burzynska-Pedziwiatr I, Jankowski A, Kowalski K, Sendys P, Zieleniak A, Cypryk K, et al. Associations of Arginine with Gestational Diabetes Mellitus in a Follow-Up Study. Int J Mol Sci. 2020 Oct 22;21(21):7811.
67. Yu J, Ren J, Ren Y, Wu Y, Zeng Y, Zhang Q, et al. Using metabolomics and proteomics to identify the potential urine biomarkers for prediction and diagnosis of gestational diabetes. EBioMedicine. 2024 Mar;101:105008.
68. Dudzik D, Zorawski M, Skotnicki M, Zarzycki W, Kozlowska G, Bibik-Malinowska K, et al. Metabolic fingerprint of Gestational Diabetes Mellitus. J Proteomics. 2014 May;103:57–71.
69. Huynh J, Xiong G, Bentley-Lewis R. A systematic review of metabolite profiling in gestational diabetes mellitus. Diabetologia. 2014 Dec 6;57(12):2453–64.
70. De Las Heras J, Aldámiz-Echevarría L, Martínez-Chantar ML, Delgado TC. An update on the use of benzoate, phenylacetate and phenylbutyrate ammonia scavengers for interrogating and modifying liver nitrogen metabolism and its implications in urea cycle disorders and liver disease. Expert Opin Drug Metab Toxicol. 2017 Apr 3;13(4):439–48.
71. Tian M, Ma S, You Y, Long S, Zhang J, Guo C, et al. Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population. J Diabetes Res. 2021 Feb 5;2021:1–13.
2. Capula C, Chiefari E, Vero A, Foti DP, Brunetti A, Vero R. Prevalence and predictors of postpartum glucose intolerance in Italian women with gestational diabetes mellitus. Diabetes Res Clin Pract. 2014 Aug;105(2):223–30.
3. Boney CM, Verma A, Tucker R, Vohr BR. Metabolic Syndrome in Childhood: Association With Birth Weight, Maternal Obesity, and Gestational Diabetes Mellitus. Pediatrics. 2005 Mar 1;115(3):e290–6.
4. Muche AA, Olayemi OO, Gete YK. Prevalence and determinants of gestational diabetes mellitus in Africa based on the updated international diagnostic criteria: a systematic review and meta-analysis. Archives of Public Health. 2019 Dec 6;77(1):36.
5. TEH WT, TEEDE HJ, PAUL E, HARRISON CL, WALLACE EM, ALLAN C. Risk factors for gestational diabetes mellitus: Implications for the application of screening guidelines. Australian and New Zealand Journal of Obstetrics and Gynaecology. 2011 Feb;51(1):26–30.
6. Kautzky-Willer A, Harreiter J, Winhofer-Stöckl Y, Bancher-Todesca D, Berger A, Repa A, et al. Gestationsdiabetes (GDM) (Update 2019). Wien Klin Wochenschr. 2019 May 12;131(S1):91–102.
7. Thayer SM, Lo JO, Caughey AB. Gestational Diabetes. Obstet Gynecol Clin North Am. 2020 Sep;47(3):383–96.
8. Yamamoto JM, Kellett JE, Balsells M, García-Patterson A, Hadar E, Solà I, et al. Gestational Diabetes Mellitus and Diet: A Systematic Review and Meta-analysis of Randomized Controlled Trials Examining the Impact of Modified Dietary Interventions on Maternal Glucose Control and Neonatal Birth Weight. Diabetes Care. 2018 Jul 1;41(7):1346–61.
9. Al-Daffaie FM, Al-Mudhafar SF, Alhomsi A, Tarazi H, Almehdi AM, El-Huneidi W, et al. Metabolomics and Proteomics in Prostate Cancer Research: Overview, Analytical Techniques, Data Analysis, and Recent Clinical Applications. Int J Mol Sci. 2024 May 7;25(10):5071.
10. Johnson CH, Ivanisevic J, Siuzdak G. Metabolomics: beyond biomarkers and towards mechanisms. Nat Rev Mol Cell Biol. 2016 Jul 16;17(7):451–9.
11. Cui L, Lu H, Lee YH. Challenges and emergent solutions for LC‐MS/MS based untargeted metabolomics in diseases. Mass Spectrom Rev. 2018 Nov 27;37(6):772–92.
12. Ortmayr K, Causon TJ, Hann S, Koellensperger G. Increasing selectivity and coverage in LC-MS based metabolome analysis. TrAC Trends in Analytical Chemistry. 2016 Sep;82:358–66.
13. Abufares HI, Zenati RA, Soares NC, El-Huneidi W, Dahabiyeh LA, Al-Hroub HM, et al. A non-targeted metabolomics comparative study on plasma of pfizer and sinopharm COVID-19 vaccinated individuals, assessed by (TIMS-QTOF) mass spectrometry. Heliyon. 2024 Aug;10(15):e35443.
14. Hassanein MM, Hagyousif YA, Zenati RA, Al-Hroub HM, Khan FM, Abuhelwa AY, et al. Metabolomics insights into doxorubicin and 5-fluorouracil combination therapy in triple-negative breast cancer: a xenograft mouse model study. Front Mol Biosci. 2025 Jan 13;11.
15. Chen P, Wang S, Ji J, Ge A, Chen C, Zhu Y, et al. Risk Factors and Management of Gestational Diabetes. Cell Biochem Biophys. 2015 Mar 1;71(2):689–94.
16. Babes EE, Bustea C, Behl T, Abdel-Daim MM, Nechifor AC, Stoicescu M, et al. Acute coronary syndromes in diabetic patients, outcome, revascularization, and antithrombotic therapy. Biomedicine & Pharmacotherapy. 2022 Apr;148:112772.
17. Feleke BE, Feleke TE, Adane WG, Kassahun MB, Girma A, Alebachew A, et al. Maternal and newborn effects of gestational diabetes mellitus: A prospective cohort study. Prim Care Diabetes. 2022 Feb;16(1):89–95.
18. Yao D, Shen C, Zhang X, Tang J, Yu J, Tu M, et al. Untargeted metabolomics study of mature human milk from women with and without gestational diabetes mellitus. Food Chem. 2024 Dec;460:140663.
19. Miller AJ, Arnold AC. The renin–angiotensin system in cardiovascular autonomic control: recent developments and clinical implications. Clinical Autonomic Research. 2019 Apr 9;29(2):231–43.
20. Qiu G, Lin Y, Ouyang Y, You M, Zhao X, Wang H, et al. Nontargeted Metabolomics Revealed Novel Association Between Serum Metabolites and Incident Acute Coronary Syndrome: A Mendelian Randomization Study. J Am Heart Assoc. 2023 Jul 4;12(13).
21. Altmaier E, Menni C, Heier M, Meisinger C, Thorand B, Quell J, et al. The Pharmacogenetic Footprint of ACE Inhibition: A Population-Based Metabolomics Study. PLoS One. 2016 Apr 27;11(4):e0153163.
22. Altmaier E, Fobo G, Heier M, Thorand B, Meisinger C, Römisch-Margl W, et al. Metabolomics approach reveals effects of antihypertensives and lipid-lowering drugs on the human metabolism. Eur J Epidemiol. 2014 May 10;29(5):325–36.
23. Plaza A, Merino B, Del Olmo N, Ruiz‐Gayo M. The cholecystokinin receptor agonist, CCK‐8, induces adiponectin production in rat white adipose tissue. Br J Pharmacol. 2019 Aug 20;176(15):2678–90.
24. Plaza A, Merino B, Cano V, Domínguez G, Pérez-Castells J, Fernández-Alfonso MS, et al. Cholecystokinin is involved in triglyceride fatty acid uptake by rat adipose tissue. Journal of Endocrinology. 2018 Mar;236(3):137–50.
25. Halland M, Bharucha AE. Relationship Between Control of Glycemia and Gastric Emptying Disturbances in Diabetes Mellitus. Clinical Gastroenterology and Hepatology. 2016 Jul;14(7):929–36.
26. Zhou Q, Sun WW, Chen JC, Zhang HL, Liu J, Lin Y, et al. Phenylalanine impairs insulin signaling and inhibits glucose uptake through modification of IRβ. Nat Commun. 2022 Jul 25;13(1):4291.
27. Ríos H, Brusco A, Saavedra JP. Development of serotoninergic chick retinal neurons. International Journal of Developmental Neuroscience. 1997 Oct 15;15(6):729–38.
28. Chu KO, Chan TI, Chan KP, Yip YW, Bakthavatsalam M, Wang CC, et al. Untargeted metabolomic analysis of aqueous humor in diabetic macular edema. Mol Vis. 2022;28:230–44.
29. Liu T, Li J, Xu F, Wang M, Ding S, Xu H, et al. Comprehensive analysis of serum metabolites in gestational diabetes mellitus by UPLC/Q-TOF-MS. Anal Bioanal Chem. 2016 Feb 16;408(4):1125–35.
30. ŠTOLBA P, OPLTOVÁ H, HUŠEK P, NEDVÍDKOVÁ J, KUNEŠ J, DOBEŠOVÁ Z, et al. Adrenergic Overactivity and Insulin Resistance in Nonobese Hereditary Hypertriglyceridemic Rats a. Ann N Y Acad Sci. 1993 Jun 17;683(1):281–8.
31. Rodríguez-Romero V, González-Villalva KI, Reyes JL, Franco-Bourland RE, Guízar-Sahagún G, Castañeda-Hernández G, et al. A novel, simple and inexpensive procedure for the simultaneous determination of iopamidol and p-aminohippuric acid for renal function assessment from plasma samples in awake rats. J Pharm Biomed Anal. 2015 Mar;107:196–203.
32. Karabacak M, Cinar Z, Cinar M. A structural and spectroscopic study on para-aminohippuric acid with experimental and theoretical approaches. Spectrochim Acta A Mol Biomol Spectrosc. 2012 Jan;85(1):241–50.
33. Raoof JB, Ojani R, Baghayeri M, Ahmadi F. Fabrication of a fast, simple and sensitive voltammetric sensor for the simultaneous determination of 4-aminohippuric acid and uric acid using a functionalized multi-walled carbon nanotube modified glassy carbon electrode. Analytical Methods. 2012;4(6):1825.
34. Chen H, Yuan B, Miao H, Tan Y, Bai X, Zhao YY, et al. Urine metabolomics reveals new insights into hyperlipidemia and the therapeutic effect of rhubarb. Analytical Methods. 2015;7(7):3113–23.
35. Sun R, Zhang J, Xiong M, Chen Y, Yin L, Pu Y. Metabonomics Biomarkers for Subacute Toxicity Screening for Benzene Exposure in Mice. J Toxicol Environ Health A. 2012 Sep 15;75(18):1163–73.
36. Jin W, Huang P, Chen Y, Wu F, Wan Y. Colorimetric detection of Cr3+ using gold nanoparticles functionalized with 4-amino hippuric acid. Journal of Nanoparticle Research. 2015 Sep 8;17(9):358.
37. Agudiez M, Martinez PJ, Martin-Lorenzo M, Heredero A, Santiago-Hernandez A, Molero D, et al. Analysis of urinary exosomal metabolites identifies cardiovascular risk signatures with added value to urine analysis. BMC Biol. 2020 Dec 14;18(1):192.
38. Oeltmann T, Carson R, Shannon JR, Ketch T, Robertson D. Assessment of O-methylated catecholamine levels in plasma and urine for diagnosis of autonomic disorders. Autonomic Neuroscience. 2004 Nov;116(1–2):1–10.
39. Serednytskyy O, Alonso-Fernández A, Ribot C, Herranz A, Álvarez A, Sánchez A, et al. Systemic inflammation and sympathetic activation in gestational diabetes mellitus with obstructive sleep apnea. BMC Pulm Med. 2022 Dec 18;22(1):94.
40. Holeček M. Why Are Branched-Chain Amino Acids Increased in Starvation and Diabetes? Nutrients. 2020 Oct 11;12(10):3087.
41. McCormack SE, Shaham O, McCarthy MA, Deik AA, Wang TJ, Gerszten RE, et al. Circulating branched‐chain amino acid concentrations are associated with obesity and future insulin resistance in children and adolescents. Pediatr Obes. 2013 Feb 7;8(1):52–61.
42. Holeček M. The Role of Skeletal Muscle in The Pathogenesis of Altered Concentrations of Branched-Chain Amino Acids (Valine, Leucine, and Isoleucine) in Liver Cirrhosis, Diabetes, and Other Diseases. Physiol Res. 2021 Jun 30;293–305.
43. Gadgil MD, Ingram KH, Appiah D, Rudd J, Whitaker KM, Bennett WL, et al. Prepregnancy Protein Source and BCAA Intake Are Associated with Gestational Diabetes Mellitus in the CARDIA Study. Int J Environ Res Public Health. 2022 Oct 29;19(21):14142.
44. Avagliano L, Garò C, Marconi AM. Placental Amino Acids Transport in Intrauterine Growth Restriction. J Pregnancy. 2012;2012:1–6.
45. Cleal JK, Lofthouse EM, Sengers BG, Lewis RM. A systems perspective on placental amino acid transport. J Physiol. 2018 Dec 7;596(23):5511–22.
46. Zheng HY, Wang L, Zhang R, Ding R, Yang CX, Du ZQ. Valine induces inflammation and enhanced adipogenesis in lean mice by multi-omics analysis. Front Nutr. 2024 May 13;11.
47. Calvo MJ, Parra H, Santeliz R, Bautista J, Luzardo E, Villasmil N, et al. The Placental Role in Gestational Diabetes Mellitus: A Molecular Perspective. touchREVIEWS in Endocrinology. 2024;20(1).
48. Zhou Y, Zhao R, Lyu Y, Shi H, Ye W, Tan Y, et al. Serum and Amniotic Fluid Metabolic Profile Changes in Response to Gestational Diabetes Mellitus and the Association with Maternal–Fetal Outcomes. Nutrients. 2021 Oct 18;13(10):3644.
49. Zhao H, Li H, Chung ACK, Xiang L, Li X, Zheng Y, et al. Large-Scale Longitudinal Metabolomics Study Reveals Different Trimester-Specific Alterations of Metabolites in Relation to Gestational Diabetes Mellitus. J Proteome Res. 2018 Dec 12;acs.jproteome.8b00602.
50. Meng X, Zhu B, Liu Y, Fang L, Yin B, Sun Y, et al. Unique Biomarker Characteristics in Gestational Diabetes Mellitus Identified by LC-MS-Based Metabolic Profiling. J Diabetes Res. 2021 Jun 9;2021:1–15.
51. Takeda R, Demura M, Sugimura Y, Miyamori I, Konoshita T, Yamamoto H. Pregnancy-associated diabetes insipidus in Japan-a review based on quoting from the literatures reported during the period from 1982 to 2019. Endocr J. 2021 Apr 28;68(4):375–85.
52. Heymsfield S, Arteaga C, McManus C, Smith J, Moffitt S. Measurement of muscle mass in humans: validity of the 24-hour urinary creatinine method. Am J Clin Nutr. 1983 Mar;37(3):478–94.
53. Hu H, Nakagawa T, Honda T, Yamamoto S, Okazaki H, Yamamoto M, et al. Low serum creatinine and risk of diabetes: The Japan Epidemiology Collaboration on Occupational Health Study. J Diabetes Investig. 2019 Sep 2;10(5):1209–14.
54. Chen N, Zeng R, Xu C, Lai F, Chen L, Wang C, et al. Low Serum Creatinine Levels in Early Pregnancy Are Associated with a Higher Incidence of Postpartum Abnormal Glucose Metabolism among Women with Gestational Diabetes Mellitus: A Retrospective Cohort Study. Nutrients. 2023 May 5;15(9):2193.
55. Wu X, Xie C, Zhang Y, Fan Z, Yin Y, Blachier F. Glutamate–glutamine cycle and exchange in the placenta–fetus unit during late pregnancy. Amino Acids. 2015 Jan 16;47(1):45–53.
56. Prada PO, Hirabara SM, Souza CT de, Schenka AA, Zecchin HG, Vassallo J, et al. RETRACTED ARTICLE:l-glutamine supplementation induces insulin resistance in adipose tissue and improves insulin signalling in liver and muscle of rats with diet-induced obesity. Diabetologia. 2007 Sep 29;50(9):1949–59.
57. Deters BJ, Saleem M. The role of glutamine in supporting gut health and neuropsychiatric factors. Food Science and Human Wellness. 2021 Mar;10(2):149–54.
58. McIntyre KR, Vincent KMM, Hayward CE, Li X, Sibley CP, Desforges M, et al. Human placental uptake of glutamine and glutamate is reduced in fetal growth restriction. Sci Rep. 2020 Oct 1;10(1):16197.
59. Ezrokhi M, Luo S, Trubitsyna Y, Cincotta AH. Neuroendocrine and metabolic components of dopamine agonist amelioration of metabolic syndrome in SHR rats. Diabetol Metab Syndr. 2014 Dec 25;6(1):104.
60. Newgard CB, An J, Bain JR, Muehlbauer MJ, Stevens RD, Lien LF, et al. A Branched-Chain Amino Acid-Related Metabolic Signature that Differentiates Obese and Lean Humans and Contributes to Insulin Resistance. Cell Metab. 2009 Apr;9(4):311–26.
61. Landsberg L, Aronne LJ, Beilin LJ, Burke V, Igel LI, Lloyd‐Jones D, et al. Obesity‐Related Hypertension: Pathogenesis, Cardiovascular Risk, and Treatment. The Journal of Clinical Hypertension. 2013 Jan 18;15(1):14–33.
62. Aleidi SM, Al Fahmawi H, AlMalki RH, Al Mogren M, Alwahsh M, Mujammami M, et al. Untargeted metabolomics profiling of gestational diabetes mellitus: insights into early diagnosis and metabolic pathway alterations. Front Mol Biosci. 2024 Dec 23;11.
63. Borges Manna L, Syngelaki A, Würtz P, Koivu A, Sairanen M, Pölönen T, et al. First-trimester nuclear magnetic resonance–based metabolomic profiling increases the prediction of gestational diabetes mellitus. Am J Obstet Gynecol. 2024 Dec.
64. Xu Z, Fang J, Wang Y, Wu X, Liu L, Cui X, et al. Targeted metabolomics reveals novel biomarkers for gestational diabetes mellitus. Diabetes Obes Metab. 2025 Apr 30;27(4):2163–72.
65. Razo-Azamar M, Nambo-Venegas R, Meraz-Cruz N, Guevara-Cruz M, Ibarra-González I, Vela-Amieva M, et al. An early prediction model for gestational diabetes mellitus based on metabolomic biomarkers. Diabetol Metab Syndr. 2023 Jun 1;15(1):116.
66. Burzynska-Pedziwiatr I, Jankowski A, Kowalski K, Sendys P, Zieleniak A, Cypryk K, et al. Associations of Arginine with Gestational Diabetes Mellitus in a Follow-Up Study. Int J Mol Sci. 2020 Oct 22;21(21):7811.
67. Yu J, Ren J, Ren Y, Wu Y, Zeng Y, Zhang Q, et al. Using metabolomics and proteomics to identify the potential urine biomarkers for prediction and diagnosis of gestational diabetes. EBioMedicine. 2024 Mar;101:105008.
68. Dudzik D, Zorawski M, Skotnicki M, Zarzycki W, Kozlowska G, Bibik-Malinowska K, et al. Metabolic fingerprint of Gestational Diabetes Mellitus. J Proteomics. 2014 May;103:57–71.
69. Huynh J, Xiong G, Bentley-Lewis R. A systematic review of metabolite profiling in gestational diabetes mellitus. Diabetologia. 2014 Dec 6;57(12):2453–64.
70. De Las Heras J, Aldámiz-Echevarría L, Martínez-Chantar ML, Delgado TC. An update on the use of benzoate, phenylacetate and phenylbutyrate ammonia scavengers for interrogating and modifying liver nitrogen metabolism and its implications in urea cycle disorders and liver disease. Expert Opin Drug Metab Toxicol. 2017 Apr 3;13(4):439–48.
71. Tian M, Ma S, You Y, Long S, Zhang J, Guo C, et al. Serum Metabolites as an Indicator of Developing Gestational Diabetes Mellitus Later in the Pregnancy: A Prospective Cohort of a Chinese Population. J Diabetes Res. 2021 Feb 5;2021:1–13.
Article Sidebar
Published
Mar 12, 2026
Article Details
How to Cite
1.
Enhancing Clinical Decision-Making in Gestational Diabetes Through Metabolomics: A Pharmacy Practice Outlook. Pharm Pract (Granada) [Internet]. 2026 Mar. 12 [cited 2026 Mar. 29];24(1):1-14. Available from: https://www.pharmacypractice.org/index.php/pp/article/view/3344
Section
Original Research
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Author Biographies
Basma Majed Sharaf, Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272
NA
Sameh Soliman, Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates ; Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272
NA
Karem H. Alzoubi , Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates; Department of Pharmacy Practice and Pharmacotherapeutics, College of Pharmacy, University of Sharjah, Sharjah 27272
NA
Eman Abu-Gharbieh, Department of Clinical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates. Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates, School of Pharmacy, The University of Jordan, Amman 11942
NA
Abla Albsoul, School of Pharmacy, The University of Jordan, Queen Rania Street Amman, 11942
NA
Reem AlQuoqa, School of Pharmacy, The University of Jordan, Queen Rania Street Amman, 11942
NA
Nahla Khawaja, National Center of Diabetes, Endocrinology and Genetic Diseases, Queen Rania Street, Amman
NA
Mousa Abujbara, National Center of Diabetes, Endocrinology and Genetic Diseases, Queen Rania Street, Amman
NA
Asma Basha, School of Medicine, The University of Jordan, Queen Rania Street Amman, 11942
NA
Yasser Bustanji, Department of Basic Medical Sciences, College of Medicine, University of Sharjah, Sharjah 27272, United Arab Emirates and Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272, United Arab Emirates and School of Pharmacy, The University of Jordan, Amman 11942
NA
Mohammad H. Semreen, Department of Medicinal Chemistry, College of Pharmacy, University of Sharjah, Sharjah 27272, United Arab Emirates and Research Institute of Medical and Health Sciences, University of Sharjah, Sharjah 27272
NA
How to Cite
1.
Enhancing Clinical Decision-Making in Gestational Diabetes Through Metabolomics: A Pharmacy Practice Outlook. Pharm Pract (Granada) [Internet]. 2026 Mar. 12 [cited 2026 Mar. 29];24(1):1-14. Available from: https://www.pharmacypractice.org/index.php/pp/article/view/3344