INVESTIGATING DISPARITIES IN METABOLITE CONCENTRATIONS USING GAS CHROMATOGRAPHY MASS SPECTROSCOPY AMONG PATIENTS WITH GESTATIONAL DIABETES MELLITUS AND IN HEALTHY CONTROL PARTICIPANTS

SAPNA BHARDWAJ; CHIRAG PASRICHA; PREETPAL SINGH; PRATIMA KUMARI; RUPINDER KAUR; RAVINDER SINGH

doi:10.22159/ajpcr.2025v18i10.55487

Authors

SAPNA BHARDWAJ Department of Pharmacy Practice, Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India.
CHIRAG PASRICHA Department of Pharmacy Practice, Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India. https://orcid.org/0009-0000-2180-3556
PREETPAL SINGH Department of Pharmacy Practice, Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India. https://orcid.org/0000-0002-7357-9207
PRATIMA KUMARI Department of Pharmacy Practice, Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India.
RUPINDER KAUR Department of Pharmacy Practice, Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India.
RAVINDER SINGH Department of Pharmacy Practice, Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab, India.

DOI:

https://doi.org/10.22159/ajpcr.2025v18i10.55487

Keywords:

GDM, metabolomics, HCP, GC-MS, amino acid, biomarker

Abstract

Objective: Metabolomics has been a promising strategy in recent years for understanding the intricate metabolic changes linked to diseases like gestational diabetes mellitus (GDM). Gas chromatography-mass spectrometry (GC-MS) has been used as analytical method in this study to explore the function of metabolomics in comprehending the underlying biochemical alterations in GDM.

Methods: One hundred subjects were enrolled and divided into two groups, Group A with healthy control participants (HCPs) and Group B with GDM patients. Both groups’ plasma samples were taken, and concentrations of amino acid metabolites were evaluated using GC-MS analysis.

Results: Leucine and Tyrosine levels were low in HCP, that is, (1.79±0.15 μM and 0.25±0.06 μM), whereas levels were high in GDM patients, that is, (23.58±1.73 μM and 0.466±0.015 μM), respectively. Similarly, tryptophan and histidine levels were low in HCP, that is, (0.41±0.10 μM and 0.271±0.072 μM), and levels were high in GDM patients, that is, (0.871±0.105 μM and 1.916±0.340 μM), respectively. Methionine and Phenylalanine levels were high in HCP (1.063±0.161 and 0.642±0.035), and levels were low in GDM patients (0.765±0.103 and 0.459±0.056), respectively.

Conclusion: The findings of the current study suggested that GDM is associated with an increase in tyrosine, tryptophan, leucine, and histidine levels and a decrease in methionine and phenylalanine levels. Therefore, these amino acids could serve as a diagnostic biomarker and supplementation tool (methionine and phenylalanine) as a management strategy in GDM.

Downloads

Download data is not yet available.

References

1. Chen Q, Francis E, Hu G, Chen L. Metabolomic profiling of women with gestational diabetes mellitus and their offspring: Review of metabolomics studies. J Diabetes Complications. 2018;32(5):512-23. doi: 10.1016/j.jdiacomp.2018.01.007, PMID 29506818

2. Ye W, Luo C, Huang J, Li C, Liu Z, Liu F. Gestational diabetes mellitus and adverse pregnancy outcomes: Systematic review and meta-analysis. BMJ. 2022;377:e067946. doi: 10.1136/bmj-2021-067946, PMID 35613728

3. Manorma MR, Mazumder R, Rani A, Budhori R, Kaushik A. Current measures against ophthalmic complications of diabetes mellitus-A short review. Int J App Pharm. 2021;13(6):54-65. doi: 10.22159/ ijap.2021v13i6.42876

4. Bommineni SR, Shravani P, Shyam J, Alekhya M, Srikanth B. A comparative study of efficacy on glycemic control by glimepiride versus teneligliptin as an add on to metformin therapy in type 2 diabetes mellitus patients. Int J Curr Pharm Sci. 2022 Mar;14:26-30. doi: 10.22159/ijcpr.2022v14i2.1939

5. Razzaq A, Sadia B, Raza A, Khalid Hameed M, Saleem F. Metabolomics: A way forward for crop improvement. Metabolites. 2019;9(12):303. doi: 10.3390/metabo9120303, PMID 31847393

6. Alesi S, Ghelani D, Rassie K, Mousa A. Metabolomic biomarkers in gestational diabetes mellitus: A review of the evidence. Int J Mol Sci. 2021;22(11):5512. doi: 10.3390/ijms22115512, PMID 34073737

7. Schrimpe-Rutledge AC, Codreanu SG, Sherrod SD, McLean JA. Untargeted metabolomics strategies-challenges and emerging directions. J Am Soc Mass Spectrom. 2016;27(12):1897-905. doi: 10.1007/s13361-016-1469-y, PMID 27624161

8. Jain AS, Soni LK, Sharma RA. Development and validation of stability indicating RP-UHPLC method for the estimation of imeglimin hydrochloride used for the treatment of metabolic disorder diabetes mellitus. Int J App Pharm. 2023;15:211-7. doi: 10.22159/ ijap.2023v15i6.49757

9. Xie J, Li L, Xing H. Metabolomics in gestational diabetes mellitus: A review. Clin Chim Acta. 2023;539:134-43. doi: 10.1016/j. cca.2022.12.005, PMID 36529269

10. Jahic A, Altun B, Noyan S. Alterations in tryptophan metabolism in gestational diabetes mellitus: Potential mechanisms and clinical implications. Diabetes Metab J. 2021;45(6):809-21.

11. Zhao X, Han Q, Liu Y, Sun C, Gang X, Wang G. The relationship between branched-chain amino acid related metabolomic signature and insulin resistance: A systematic review. J Diabetes Res. 2021;2021:9577572.

12. Yin J, Ren W, Chen S, Li Y, Han H, Gao J, et al. Metabolic regulation of methionine restriction in diabetes. Mol Nutr Food Res. 2018;62(10):e1700951. doi: 10.1002/mnfr.201700951, PMID 29603632

13. Rahimi N, Razi F, Nasli-Esfahani E, Qorbani M, Shirzad N, Larijani B. Amino acid profiling in the gestational diabetes mellitus. J Diabetes Metab Disord. 2017;16:13. doi: 10.1186/s40200-016-0283-1, PMID 28367428

14. 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. doi: 10.3390/ijms21217811, PMID 33105558

15. Pappa KI, Vlachos G, Theodora M, Roubelaki M, Angelidou K, Antsaklis A. Intermediate metabolism in association with the amino acid profile during the third trimester of normal pregnancy and diet-controlled gestational diabetes. Am J Obstet Gynecol. 2007;196(1):65. e1-5. doi: 10.1016/j.ajog.2006.06.094, PMID 17240238

16. Nie C, He T, Zhang W, Zhang G, Ma X. Branched chain amino acids: Beyond nutrition metabolism. Int J Mol Sci. 2018;19(4):954. doi: 10.3390/ijms19040954, PMID 29570613

17. Jiang R, Wu S, Fang C, Wang C, Yang Y, Liu C, et al. Amino acids levels in early pregnancy predict subsequent gestational diabetes. J Diabetes. 2020;12(7):503-11. doi: 10.1111/1753-0407.13018, PMID 31883199

18. Mokkala K, Vahlberg T, Pellonperä O, Houttu N, Koivuniemi E, Laitinen K. Distinct metabolic profile in early pregnancy of overweight and obese women developing gestational diabetes. J Nutr. 2020;150(1):31-7. doi: 10.1093/jn/nxz220, PMID 31529056

19. Zhao L, Wang M, Li J, Bi Y, Li M, Yang J. Association of circulating branched-chain amino acids with gestational diabetes mellitus: A meta-analysis. Int J Endocrinol Metab. 2019;17(3):e85413. doi: 10.5812/ ijem.85413, PMID 31497040

20. Spanou L, Dimou A, Kostara CE, Bairaktari E, Anastasiou E, Tsimihodimos V. A study of the metabolic pathways affected by gestational diabetes mellitus: comparison with type 2 diabetes. Diagnostics (Basel). 2022;12(11):2881. doi: 10.3390/ diagnostics12112881, PMID 36428943