{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T01:07:38Z","timestamp":1792026458176,"version":"4.4.0"},"reference-count":82,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T00:00:00Z","timestamp":1758844800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T00:00:00Z","timestamp":1758844800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"UCLA Technology and Development Group"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Metabolomics"],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>Gestational diabetes mellitus (GDM) is generally identified by measuring elevated maternal glycemic responses to an oral glucose load in late pregnancy (&gt;\u20090.6 term). However, our preliminary study suggests that GDM could be identified with a high predictive accuracy (96%) in the first trimester (&lt;\u20090.35 term) by characteristic changes in the metabolite profile of maternal urine. (Koos and Gornbein, American Journal of Obstetrics and Gynecology 224:215.e1\u2013215.e7, 2021). The gestational decrease in insulin sensitivity and the accompanying perturbations of the maternal metabolome suggest that a distinguishing urinary metabolite algorithm could differ in later gestation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objectives<\/jats:title>\n                    <jats:p>This study was carried out (1) to identify the metabolites of late-pregnancy urine that are independently associated with GDM, (2) to select a metabolite subgroup for a predictive model for the disorder, (3) to compare the predictive accuracy of this late pregnancy algorithm with the model previously established for early pregnancy, and (4) to determine whether the late urinary markers of GDM likely contribute to the late pregnancy decline in insulin sensitivity.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This observational nested case\u2013control study comprised a cohort of 46 GDM patients matched with 46 control subjects (CON). Random urine samples were collected at\u2009\u2265\u200924\u00a0weeks\u2019 gestation and were analyzed by a global metabolomics platform. A consensus of three multivariate criteria was used to distinguish GDM from CON subjects, and a classification tree of selected metabolites was utilized to compute a model that separated GDM vs CON.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The GDM and CON groups were similar with respect to maternal age, pre-pregnancy BMI and gestational age at urine collection [GDM 30.8\u00a0\n                      <jats:inline-formula>\n                        <jats:tex-math>$$\\pm $$<\/jats:tex-math>\n                      <\/jats:inline-formula>\n                      \u00a03.6(SD); CON [30.5\u2009\u00b1\u20093.6] weeks as they were matched by these variables. Three multivariate criteria identified eight metabolites simultaneously separating GDM from CON subjects, comprising five markers of mitochondrial dysfunction and three of inflammation\/oxidative stress. A five-level classification tree incorporating four of the eight metabolites predicted GDM with an unweighted accuracy of 89%. The model derived from early pregnancy urine also had a high predictive accuracy (85.9%).\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The late pregnancy urine metabolites independently linked to GDM were markers for diminished insulin sensitivity and glucose-stimulated insulin release. The high predictive accuracy of the models in both early and late pregnancy in this cohort supports the notion that a urinary metabolite phenotype may separate GDM vs CON across both early and late gestation. A large validation study should be conducted to affirm the accuracy of this noninvasive and time-efficient technology in identifying GDM.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1007\/s11306-025-02314-3","type":"journal-article","created":{"date-parts":[[2025,9,26]],"date-time":"2025-09-26T12:00:14Z","timestamp":1758888014000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Gestational age and models for predicting gestational diabetes mellitus"],"prefix":"10.1007","volume":"21","author":[{"given":"Aisling","family":"Murphy","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jeffrey","family":"Gornbein","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ophelia","family":"Yin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Brian","family":"Koos","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,26]]},"reference":[{"key":"2314_CR1","doi-asserted-by":"publisher","unstructured":"(2018). ACOG Practice Bulletin No. 190: Gestational Diabetes Mellitus. Obstetrics Gynecology, 131(2), e49\u2013e64. https:\/\/doi.org\/10.1097\/AOG.0000000000002501. PMID: 29370047.","DOI":"10.1097\/AOG.0000000000002501"},{"key":"2314_CR2","doi-asserted-by":"publisher","DOI":"10.5339\/imjs22115512","author":"S Alesi","year":"2021","unstructured":"Alesi, S., Ghelani, D., Rassle, K., & Mousa, A. (2021). Metabolomic biomarkers in gestational diabetes: a review of the evidence. International Journal of Molecular Sciences. https:\/\/doi.org\/10.5339\/imjs22115512.","journal-title":"International Journal of Molecular Sciences"},{"key":"2314_CR3","doi-asserted-by":"crossref","first-page":"5269","DOI":"10.3390\/nu14245269","volume":"14","author":"T Bankole","year":"2022","unstructured":"Bankole, T., Winn, H., & Li, Y. (2022). Dietary impacts on gestational diabetes: Connection between gut microbiome and epigenetic mechanisms. Nutrients, 14, 5269.","journal-title":"Nutrients"},{"issue":"5","key":"2314_CR4","doi-asserted-by":"publisher","first-page":"885","DOI":"10.2337\/db17-1150","volume":"67","author":"B Batchuluum","year":"2018","unstructured":"Batchuluun, B., Al Rijjal, D., Prentice, K. J., Eversley, J. A., Burdett, E., Mohan, H., Bhattacharjee, A., Gunderson, E. P., Liu, Y., & Wheeler, M. B. (2018). Elevated medium-chain acylcarnitines are associated with gestational diabetes mellitus and early progression to type 2 diabetes and induce pancreatic-cell dysfunction. Diabetes, 67(5), 885\u2013897. https:\/\/doi.org\/10.2337\/db17-1150.","journal-title":"Diabetes"},{"issue":"11","key":"2314_CR5","doi-asserted-by":"publisher","first-page":"2118","DOI":"10.1007\/s00125-019-4961-7","volume":"62","author":"K Benhalima","year":"2019","unstructured":"Benhalima, K., Van Crombrugge, P., Moyson, C., Verhaeghe, J., Vandeginste, S., Verlaenen, H., Vercammen, C., Maes, T., Dufraimont, E., De Block, C., Jacquemyn, Y., Mekahli, F., De Clippel, K., Van Den Bruel, A., Loccufier, A., Laenen, A., Minschart, C., Devlieger, R., & Mathieu C.  (2019). Characteristics and pregnancy outcomes across gestational diabetes mellitus subtypes based on insulin resistance. Diabetologia, 62(11), 2118\u20132128. https:\/\/doi.org\/10.1007\/s00125-019-4961-7.","journal-title":"Diabetologia"},{"key":"2314_CR6","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1111\/dme.12381","volume":"31","author":"PM Catalano","year":"2014","unstructured":"Catalano, P. M. (2014). Trying to understand gestational diabetes. Diabetic Medicine, 31, 273\u2013281.","journal-title":"Diabetic Medicine"},{"issue":"6 pt 1","key":"2314_CR7","doi-asserted-by":"crossref","first-page":"1667","DOI":"10.1016\/0002-9378(91)90012-G","volume":"165","author":"PM Catalano","year":"1991","unstructured":"Catalano, P. M., Tybir, E. D., Roman, N. M., Amini, S. B., & Sims, E. A. (1991). Longitudinal changes in insulin release and insulin resistance in non-obese pregnant women. American Journal of Obstetrics and Gynecology, 165(6 pt 1), 1667\u20131672.","journal-title":"American Journal of Obstetrics and Gynecology"},{"issue":"1 Pt 1","key":"2314_CR8","doi-asserted-by":"publisher","first-page":"E60","DOI":"10.1152\/ajpendo.1993.264.1.E60","volume":"264","author":"PM Catalano","year":"1993","unstructured":"Catalano, P. M., Tyzbir, E. D., Wolfe, R. R., Calles, J., Roman, N. M., Amini, S. B., & Sims, E. A. (1993). Carbohydrate metabolism during pregnancy in control subjects and women with gestational diabetes. American Journal of Physiology, 264(1 Pt 1), E60\u2013E67. https:\/\/doi.org\/10.1152\/ajpendo.1993.264.1.E60. PMID: 8430789.","journal-title":"American Journal of Physiology"},{"key":"2314_CR9","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1016\/j.jdiacomp.2018.01.007","volume":"32","author":"Q Chen","year":"2018","unstructured":"Chen, Q., Francis, E., Hu, G., & Chen, L. (2018). Metabolomic profiling of women with gestational diabetes and their offspring: Review of metabolomics studies. Journal of Diabetes and Its Complications, 32, 512\u2013523.","journal-title":"Journal of Diabetes and Its Complications"},{"key":"2314_CR10","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1111\/joim.13006","volume":"287","author":"MA Cox","year":"2020","unstructured":"Cox, M. A., Bassi, C., Saunders, M. E., Necharitzky, R., Morgado-Palacin, I., Zheng, C., & Mak, T. W. (2020). Beyond neurotransmission: Acetylcholine in immunity and inflammation. Journal of Internal Medicine, 287, 120\u2013133. https:\/\/doi.org\/10.1111\/joim.13006.","journal-title":"Journal of Internal Medicine"},{"key":"2314_CR11","doi-asserted-by":"crossref","first-page":"2217","DOI":"10.3390\/microorganisms11092217","volume":"11","author":"S Dias","year":"2023","unstructured":"Dias, S., Pheiffer, C., & Adam, S. (2023). The maternal microbiome and gestational diabetes mellitus: Cause and effect. Microorganisms, 11, 2217.","journal-title":"Microorganisms"},{"issue":"2","key":"2314_CR12","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1111\/j.1464-5491.2005.01752.x","volume":"23","author":"M Dworacka","year":"2006","unstructured":"Dworacka, M., Wender-Ozegowska, E., Winiarska, H., Borowska, M., Pietryga, M., Brazert, J., Szczawinska, K., & Bobkiewicz-Koz\u0142owska, T. (2006). Plasma anhydro-D-glucitol (1,5-AG) as an indicator of hyperglycemic excursions in pregnant women with diabetes. Diabetic Medicine, 23(2), 171\u2013175. https:\/\/doi.org\/10.1111\/j.1464-5491.2005.01752.x.","journal-title":"Diabetic Medicine"},{"issue":"1","key":"2314_CR13","doi-asserted-by":"crossref","first-page":"238","DOI":"10.2527\/jas.2011-5070","volume":"91","author":"SK Gatrell","year":"2013","unstructured":"Gatrell, S. K., Berg, L. E., Barnard, J. T., Grimmett, J. G., Barnes, K. M., & Blemings, K. P. (2013). Tissue distribution of indices of lysine metabolism in growing swine. Journal of Animal Science, 91(1), 238\u2013247.","journal-title":"Journal of Animal Science"},{"key":"2314_CR14","doi-asserted-by":"crossref","first-page":"1630","DOI":"10.1016\/j.cmet.2023.07.003","volume":"36","author":"M Gonzalez-Rellan","year":"2023","unstructured":"Gonzalez-Rellan, M., Fernandez, U., Parracho, T., Bravo, S. B., Martinez-Chantar, M. L., & Nogueiras, R. (2023). Neddylation of photoenolpyruvate carboxykinase 1 controls glucose metabolism. Cell Metabolism, 36, 1630\u20131645.","journal-title":"Cell Metabolism"},{"key":"2314_CR15","doi-asserted-by":"publisher","first-page":"431","DOI":"10.1074\/mcp.RA117.000121","volume":"17","author":"W Hou","year":"2018","unstructured":"Hou, W., Meng, X., Zhao, A., Zhao, W., Pan, J., Tang, J., Huang, Y., Li, H., Jia, W., Liu, F., & Jia, W. (2018). Development of multimarker diagnostic models from metabolomics analysis for gestational diabetes mellitus (GDM). Molecular & Cellular Proteomics, 17, 431\u2013441. https:\/\/doi.org\/10.1074\/mcp.RA117.000121.","journal-title":"Molecular & Cellular Proteomics"},{"key":"2314_CR16","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1146\/annurev-physiol-021115-105045","volume":"78","author":"SM Houten","year":"2016","unstructured":"Houten, S. M., Violante, S., Ventura, F. V., & Wanders, R. I. A. (2016). The biochemistry and physiology of mitochondrial fatty acid \u03b2-oxidation and its genetic disorders. Annual Review of Physiology, 78, 23\u201344.","journal-title":"Annual Review of Physiology"},{"issue":"Pt A","key":"2314_CR17","doi-asserted-by":"publisher","first-page":"357","DOI":"10.1016\/j.ijbiomac.2018.06.032","volume":"118","author":"J Huang","year":"2018","unstructured":"Huang, J., Wang, T., Yu, D., Fang, X., Fan, H., Lin, Q. (2018). l-Homocarnosine attenuates inflammation in cerebral ischemia-reperfusion injury through inhibition of nod-like receptor protein s inflammasome. International Journal of Biological Macromolecules, 118(Pt A), 357\u2013364. https:\/\/doi.org\/10.1016\/j.ijbiomac.2018.06.032.","journal-title":"International Journal of Biological Macromolecules"},{"key":"2314_CR18","doi-asserted-by":"crossref","first-page":"E578","DOI":"10.1152\/ajpendo.00093.2009","volume":"297","author":"L Hue","year":"2009","unstructured":"Hue, L., & Taegtmeyer, H. (2009). The Randle cycle revisited: A new head for an old hat. American Journal of Physiology Endocrinology and Metabolism, 297, E578\u2013E591.","journal-title":"American Journal of Physiology Endocrinology and Metabolism"},{"key":"2314_CR19","doi-asserted-by":"crossref","first-page":"696","DOI":"10.3389\/fendo.2018.00696","volume":"9","author":"EA Huhn","year":"2018","unstructured":"Huhn, E. A., Rossi, S. W., Hoesli, L., & Gobl, C. S. (2018). Controversies in screening and diagnostic criteria for gestational diabetes in early and late pregnancy. Frontiers in Endocrinology, 9, 696.","journal-title":"Frontiers in Endocrinology"},{"key":"2314_CR20","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.clinbiochem.2022.10.002","volume":"115","author":"E Jamieson","year":"2023","unstructured":"Jamieson, E. L., Dimeski, G., Flatman, R., Hickman, P. E., Ross Dallas Jones, G., V Marley, J., David McIntyre, H., McNeil, A. R., Nolan, C. J., Potter, J. M., Sweeting, A., Ward, P., Williams, P., & Rita Horvath, A.  (2023). Oral glucose tolerance test to diagnose gestational diabetes mellitus: Impact of variations in specimen handling. Clinical Biochemistry, 115, 33\u201348. https:\/\/doi.org\/10.1016\/j.clinbiochem.2022.10.002.","journal-title":"Clinical Biochemistry"},{"key":"2314_CR21","doi-asserted-by":"crossref","first-page":"e245","DOI":"10.1038\/emm.2016.81","volume":"48","author":"S-M Jeon","year":"2016","unstructured":"Jeon, S.-M. (2016). Regulation and function of AMPK in physiology and diseases. Experimental & Molecular Medicine, 48, e245.","journal-title":"Experimental & Molecular Medicine"},{"key":"2314_CR22","doi-asserted-by":"crossref","first-page":"5320156","DOI":"10.1155\/2019\/5320156","volume":"2019","author":"U Kampmann","year":"2019","unstructured":"Kampmann, U., Knorr, S., Fuglsang, J., & Ovesen, P. (2019). Determinants of maternal insulin resistance during pregnancy: An updated review. Journal of Diabetes Research, 2019, 5320156.","journal-title":"Journal of Diabetes Research"},{"issue":"Suppl 1","key":"2314_CR23","doi-asserted-by":"publisher","first-page":"115","DOI":"10.1007\/s00508-023-02181-9","volume":"135","author":"A Kautzky-Willer","year":"2023","unstructured":"Kautzky-Willer, A., Winhofer, Y., Kiss, H., Falcones, V., Berger, A., Lechleitner, M., Weitgasser, R., & Harreiter, J. (2023). Gestational diabetes mellitus (Update 2023). Wiener Klinische Wochenschrift, 135(Suppl 1), 115\u2013128. https:\/\/doi.org\/10.1007\/s00508-023-02181-9.","journal-title":"Wiener Klinische Wochenschrift"},{"key":"2314_CR24","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1007\/s12020-012-9760-6","volume":"43","author":"WJ Kim","year":"2013","unstructured":"Kim, W. J., & Park, C.-Y. (2013). 1,5-Anhydroglucitol in diabetes mellitus. Endocrine, 43, 33\u201340.","journal-title":"Endocrine"},{"issue":"4","key":"2314_CR25","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1071\/rd9910405","volume":"3","author":"RG King","year":"1991","unstructured":"King, R. G., Gude, N. M., Krishna, B. R., Chen, S., Brennecke, S. P., Boura, A. L., & Rook, T. J. (1991). Human placental acetylcholine. Reproduction, Fertility, and Development, 3(4), 405\u2013411424. https:\/\/doi.org\/10.1071\/rd9910405.","journal-title":"Reproduction, Fertility, and Development"},{"key":"2314_CR26","doi-asserted-by":"crossref","first-page":"2207","DOI":"10.2337\/diabetes.51.7.2207","volume":"51","author":"JP Kirwan","year":"2002","unstructured":"Kirwan, J. P., Hauguel-De Mouzon, S., Lepercq, J., Challier, J. C., Huston-Presley, L., Friedman, J. E., Kalhan, S. C., & Catalano, P. M. (2002). TNF-alpha is a predictor of insulin resistance in human pregnancy. Diabetes, 51, 2207\u20132213.","journal-title":"Diabetes"},{"issue":"2","key":"2314_CR27","doi-asserted-by":"publisher","first-page":"215.e1","DOI":"10.1016\/j.ajog.2020.07.050","volume":"224","author":"BJ Koos","year":"2021","unstructured":"Koos, B. J., & Gornbein, J. A. (2021). Early pregnancy metabolites predict gestational diabetes mellitus: Implications for fetal programming. American Journal of Obstetrics and Gynecology, 224(2), 215.e1-215.e7. https:\/\/doi.org\/10.1016\/j.ajog.2020.07.050. Epub 2020 Jul 31 PMID: 32739399.","journal-title":"American Journal of Obstetrics and Gynecology"},{"issue":"9","key":"2314_CR28","doi-asserted-by":"publisher","first-page":"e1","DOI":"10.1111\/eci.13628","volume":"51","author":"G Kotzaeridi","year":"2021","unstructured":"Kotzaeridi, G., Blatter, J., Eppel, D., Rosicky, I., Linder, T., Geissler, F., Huhn, E. A., H\u00f6sli, I., Tura, A., & G\u00f6bl, C. S. (2021). Characteristics of gestational diabetes subtypes classified by oral glucose tolerance test values. European Journal of Clinical Investigation, 51(9), e13628. https:\/\/doi.org\/10.1111\/eci.13628.","journal-title":"European Journal of Clinical Investigation"},{"key":"2314_CR29","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.cca.2017.02.018","volume":"468","author":"KP Law","year":"2017","unstructured":"Law, K. P., Han, T. L., Mao, X., & Zhang, H. (2017). Tryptophan and purine metabolites are consistently upregulated in the urinary metabolome of patients diagnosed with gestational diabetes throughout pregnancy: A longitudinal metabolomics study of Chinese pregnant women part 2. Clinica Chimica Acta, 468, 126\u2013139.","journal-title":"Clinica Chimica Acta"},{"key":"2314_CR30","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1016\/j.diabres.2018.03.028","volume":"140","author":"S-G Lee","year":"2018","unstructured":"Lee, S.-G., Yim, Y. S., Lee, Y.-H., Lee, B.-W., Kim, H.-S., Kim, K.-S., Lee, Y. W, Kim, J. H. (2018). Fasting serum amino acid concentration is associated with insulin resistance and pro-inflammatory cytokines. Diabetes Research and Clinical Practice, 140, 107\u2013117. https:\/\/doi.org\/10.1016\/j.diabres.2018.03.028.","journal-title":"Diabetes Research and Clinical Practice"},{"key":"2314_CR31","doi-asserted-by":"publisher","first-page":"1680","DOI":"10.1016\/j.cell.2020.05.002","volume":"181","author":"L Liang","year":"2020","unstructured":"Liang, L., Rasmussen, M.-L.H., Pieniing, B., Shen, X., R\u00f6st, H., Snyder, J. K., Tibshirani, R., Skotte, L., Lee, N. C., Contrepois, K., Feenstra, B., Zackriah, H., Snyder, M., & Melbye M. (2020). Metabolic dynamics and prediction of gestational age and time of delivery in pregnant women. Cell, 181, 1680\u20131692. https:\/\/doi.org\/10.1016\/j.cell.2020.05.002.","journal-title":"Cell"},{"issue":"Suppl 3","key":"2314_CR32","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1159\/000448357","volume":"68","author":"GD Lopaschuk","year":"2016","unstructured":"Lopaschuk, G. D. (2016). Fatty acid oxidation and its relation with insulin resistance and associated disorders. Annals of Nutrition & Metabolism, 68(Suppl 3), 15\u201320.","journal-title":"Annals of Nutrition & Metabolism"},{"key":"2314_CR33","doi-asserted-by":"publisher","first-page":"1186","DOI":"10.3390\/ijms20051186","volume":"20","author":"Y Lopez-Hernandez","year":"2019","unstructured":"Lopez-Hernandez, Y., Herrera Van Oostdam, A. S., Torro-Ortiz, J. C., Lopez, J. A., Salgado-Bustamante, M., Murgu, M., Torres-Torres, L. M. (2019). Urinary metabolites altered during the third trimester in pregnancies complicated by gestational diabetes mellitus: Relationship with potential upcoming metabolic disorders. International Journal of Molecular Sciences, 20, 1186. https:\/\/doi.org\/10.3390\/ijms20051186.","journal-title":"International Journal of Molecular Sciences"},{"issue":"16","key":"2314_CR34","doi-asserted-by":"crossref","first-page":"1940","DOI":"10.1097\/CM9.0000000000002160","volume":"135","author":"W Lu","year":"2022","unstructured":"Lu, W., & Hu, C. (2022). Molecular biomarkers for gestational diabetes mellitus and postpartum diabetes. Chinese Medical Journal, 135(16), 1940\u20131951.","journal-title":"Chinese Medical Journal"},{"key":"2314_CR35","doi-asserted-by":"publisher","DOI":"10.26402\/jpp.2019.600","author":"K Luc","year":"2019","unstructured":"Luc, K., Schramm-Luc, A., Ghuzik, T. J., & Mikolajczyk, T. P. (2019). Oxidative stress and inflammatory markers in prediabetes and diabetes. Journal of Physiology & Pharmacology. https:\/\/doi.org\/10.26402\/jpp.2019.600.","journal-title":"Journal of Physiology & Pharmacology"},{"key":"2314_CR36","doi-asserted-by":"crossref","first-page":"44291","DOI":"10.1038\/srep44291","volume":"10","author":"C Ma","year":"2017","unstructured":"Ma, C., Sheng, J., Liu, Z., & Guo, M. (2017). Excretion rates of 1,5-anhydro-D-glucitol, uric acid and microalbuminuria as glycemic control indexes in patients with type 2 diabetes. Science and Reports, 10, 44291.","journal-title":"Science and Reports"},{"key":"2314_CR37","unstructured":"Mahalanobis, P.C. (1936). On the Generalised distance in statistics. [Reprinted in Sankhya A, 2018, 80(1), 1\u20137]."},{"issue":"2","key":"2314_CR38","first-page":"43","volume":"19","author":"R Mallik","year":"2023","unstructured":"Mallik, R., & Huda, M. S. B. (2023). Current practice and controversies in screening for gestational diabetes. Current Diabetes Review, 19(2), 43\u201349.","journal-title":"Current Diabetes Review"},{"key":"2314_CR39","doi-asserted-by":"crossref","first-page":"116","DOI":"10.1016\/j.cca.2017.10.019","volume":"475","author":"X Mao","year":"2017","unstructured":"Mao, X., Chen, X., Chen, C., Zhang, H., & Law, K. P. (2017). Metabolomics in gestational diabetes. Clinica Chimica Acta, 475, 116\u2013127.","journal-title":"Clinica Chimica Acta"},{"issue":"3","key":"2314_CR40","doi-asserted-by":"crossref","first-page":"753","DOI":"10.1002\/nau.24620","volume":"40","author":"L McLatchie","year":"2021","unstructured":"McLatchie, L., Sahai, A., Caldwell, A., Dasgupta, P., & Fry, C. (2021). ATP shows more potential as a urinary biomarker than acetylcholine and PGE2, but its concentration in urine is not a simple function of dilution. Neurourology and Urodynamics, 40(3), 753\u2013762.","journal-title":"Neurourology and Urodynamics"},{"key":"2314_CR41","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.3389\/fphys.2018.01091","volume":"9","author":"T Napso","year":"2018","unstructured":"Napso, T., Yong, H. E. J., Lopez-Tello, J., & Sferuzzi-Perri, A. N. (2018). The role of placental hormones in mediating maternal adaptations to support pregnancy and lactation. Frontiers in Physiology, 9, 1091.","journal-title":"Frontiers in Physiology"},{"key":"2314_CR42","first-page":"4068","volume":"13","author":"X Pan","year":"2021","unstructured":"Pan, X., Jin, X., Wang, J., Hu, Q., & Dai, B. (2021). Placental inflammation is closely associated with gestational diabetes mellitus. American Journal of Translational Research, 13, 4068\u20134079.","journal-title":"American Journal of Translational Research"},{"key":"2314_CR43","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1016\/j.niox.2022.11.006","volume":"131","author":"G Pappas","year":"2023","unstructured":"Pappas, G., Wilkinson, M. L., & Gow, A. I. (2023). Nitric oxide regulation of cellular metabolism: Adaptive tuning of cellular energy. Nitric Oxide, 131, 8\u201317.","journal-title":"Nitric Oxide"},{"issue":"2","key":"2314_CR44","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1089\/met.2014.0113","volume":"13","author":"S Park","year":"2015","unstructured":"Park, S., Park, J. Y., Lee, J. H., & Kim, S. H. (2015). Plasma levels of lysine, tyrosine, and valine during pregnancy are independent risk factors of insulin resistance and gestational diabetes. Metabolic Syndrome and Related Disorders, 13(2), 64\u201370.","journal-title":"Metabolic Syndrome and Related Disorders"},{"issue":"4","key":"2314_CR45","doi-asserted-by":"publisher","first-page":"745","DOI":"10.1016\/j.cell.2015.01.012","volume":"160","author":"RJ Perry","year":"2015","unstructured":"Perry, R. J., Camparoz, J.-P., Kursawe, R., Titchenell, P. M., Zhang, D., Perry, C. J., Jurczak, M. J., Abudukadier, A., Han, M. S., Zhang, X. M., Ruan, H. B., Yang, X., Caprio, S., Kaech, S. M., Sul, H. S., Birnbaum, M. J., Davis, R. J., Cline, G. W., Petersen, K. F., Shulman, G. I. (2015). Hepatic acetyl CoA links adipose tissue inflammation to hepatic insulin resistance and type 2 diabetes. Cell, 160(4), 745\u2013758. https:\/\/doi.org\/10.1016\/j.cell.2015.01.012.","journal-title":"Cell"},{"issue":"11","key":"2314_CR46","doi-asserted-by":"crossref","first-page":"2367","DOI":"10.1007\/s00726-015-2024-z","volume":"47","author":"V Peters","year":"2015","unstructured":"Peters, V., Lanthaler, B., Amberger, A., Fleming, T., Forsberg, E., Hecker, M., Wagner, A. H., Yue, W. W., Hoffmann, G. F., Nawroth, P., Zschocke, J., & Schmitt, C. P. (2015). Carnosine metabolism in diabetes is altered by reactive metabolites. Amino Acids, 47(11), 2367\u20132376.","journal-title":"Amino Acids"},{"key":"2314_CR47","doi-asserted-by":"publisher","first-page":"1503","DOI":"10.1530\/EC-19-0436","volume":"11","author":"C Piao","year":"2019","unstructured":"Piao, C., Wang, X., Peng, S., Guo, X., Zhao, H., He, L., Zeng, Y., Zhang, F., Zhu, K., & Wang, Y. (2019). IL-34 causes inflammation and beta cell apoptosis and dysfunction in gestational diabetes mellitus. Endocrine Connections, 11, 1503\u20131512. https:\/\/doi.org\/10.1530\/EC-19-0436.","journal-title":"Endocrine Connections"},{"key":"2314_CR48","doi-asserted-by":"publisher","first-page":"918","DOI":"10.1136\/gutjnl-2022-328406","volume":"72","author":"Y Pinto","year":"2023","unstructured":"Pinto, Y., Frishman, S., Turjeman, S., Eshel, A., Nuriel-Ohayon, M., Shrossel, O., Ziv, O., Walters, W., Parsonnet, J., Ley C., Johnson, E. L., Kumar, K., Schweitzer, R., Khatib, S., Magzal, F., Muller, E., Tamir, S., Tenenbaum-Gavish, K., Rautava, S., Salminen, S., Isolauri, E., Yariv, O., Peled, Y., Poran, E., Pardo, J., Chen, R., Hod, M., Borenstein E, Ley, R. E., Schwartz, B., Louzoun, Y., Hadar, E., & Koren O (2023). Gestational diabetes is driven by microbiota-induced inflammation months before diagnosis. Gut, 72, 918\u2013928. https:\/\/doi.org\/10.1136\/gutjnl-2022-328406.","journal-title":"Gut"},{"key":"2314_CR49","doi-asserted-by":"publisher","first-page":"8275","DOI":"10.1080\/14767058.2021","volume":"35","author":"C Piras","year":"2022","unstructured":"Piras, C., Neri, I., Pintus, R., Noto, A., Petrella, E., Monari, F., Dess\u00ec, A., Fanos, V., Atzori, L., & Facchinetti, F.  (2022). First-trimester metabolites 1H-NMR study of the urinary profile predicts gestational diabetes mellitus development in obese women. The Journal of Maternal-Fetal & Neonatal Medicine, 35, 8275\u20138283. https:\/\/doi.org\/10.1080\/14767058.2021.","journal-title":"The Journal of Maternal-Fetal & Neonatal Medicine"},{"key":"2314_CR50","doi-asserted-by":"crossref","first-page":"3342","DOI":"10.3390\/ijms19113342","volume":"19","author":"JF Plows","year":"2018","unstructured":"Plows, J. F., Stanley, J. L., Baker, P. N., Reynolds, C. M., & Vickers, M. H. (2018). The pathophysiology of gestational diabetes mellitus. International Journal of Molecular Sciences, 19, 3342.","journal-title":"International Journal of Molecular Sciences"},{"issue":"7","key":"2314_CR51","doi-asserted-by":"crossref","first-page":"1438","DOI":"10.2337\/dc20-0304","volume":"43","author":"JM Potter","year":"2020","unstructured":"Potter, J. M., Hickman, P. E., Oakman, C., Woods, C., & Nolan, C. J. (2020). Strict preanalytic oral tolerance test blood sample handling is essential for diagnosing gestational diabetes mellitus. Diabetes Care, 43(7), 1438\u20131441.","journal-title":"Diabetes Care"},{"issue":"3","key":"2314_CR52","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1016\/j.jdiacomp.2018.11.010","volume":"33","author":"TA Pramodkumar","year":"2019","unstructured":"Pramodkumar, T. A., Jayashri, R., Gokulakrishnan, K., Velmurugan, K., Pradeepa, R., Venkatesan, U., Saravanan, P., Uma, R., Anjana, R. M., & Mohan, V. (2019). 1,5 Anhydroglucitol in gestational diabetes mellitus. Journal of Diabetes and Its Complications, 33(3), 231\u2013235.","journal-title":"Journal of Diabetes and Its Complications"},{"key":"2314_CR53","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1016\/S0140-6736(63)91500-9","volume":"1","author":"PJ Randle","year":"1963","unstructured":"Randle, P. J., Garland, P. B., Hales, C. N., & Newsholme, E. A. (1963). The glucose fatty-acid cycle. Its role in insulin sensitivity and the metabolic disturbance of diabetes mellitus. Lancet, 1, 785\u2013789.","journal-title":"Lancet"},{"issue":"9","key":"2314_CR54","doi-asserted-by":"publisher","first-page":"553","DOI":"10.1007\/BF03261931","volume":"51","author":"SE Reuter","year":"2012","unstructured":"Reuter, S. E., & Evans, A. M. (2012). Carnitine and acylcarnitines: Pharmacokinetic, pharmacological and clinical aspects. Clinical Pharmacokinetics, 51(9), 553\u2013572. https:\/\/doi.org\/10.1007\/BF03261931. PMID: 22804748.","journal-title":"Clinical Pharmacokinetics"},{"key":"2314_CR55","doi-asserted-by":"publisher","first-page":"183","DOI":"10.1016\/j.diabres.2018.03.058","volume":"140","author":"C Roy","year":"2018","unstructured":"Roy, C., Tremblay, P. Y., Anassour-Laouan-Sidi, L. M., Forest, I. C., Giguere, Y., & Ayotte, P. (2018). Risk of gestational diabetes in relation to plasma concentrations of amino acids and acylcarnitines: a nested case-control study. Diabetes Research and Clinical Practice, 140, 183\u2013190. https:\/\/doi.org\/10.1016\/j.diabres.2018.03.058.","journal-title":"Diabetes Research and Clinical Practice"},{"issue":"2","key":"2314_CR56","doi-asserted-by":"publisher","first-page":"130282","DOI":"10.1016\/j.bbagen.2022.130282","volume":"1867","author":"MVC Rudge","year":"2023","unstructured":"Rudge, M. V. C., Alves, F. C. H., Hallur, R. L. S., Oliveira, R., Vega, S., Reyes, D. R., Floriano, J. F., Prudencio, C. B., Garcia, G. A., Reis, F. V. D. S, Emanueli, C., Fuentes, G., Cornejo, M., Toledo, F., Valenzuela-Hinrichsen, A., Guerra, C., Grismaldo, A., Valero, P., Barbosa, A. M. P., & Sobrevia, L. (2023). Consequences of the exposure to gestational diabetes. Biochimica Et Biophysica Acta (BBA) - General Subjects, 1867(2), 130282. https:\/\/doi.org\/10.1016\/j.bbagen.2022.130282.","journal-title":"Biochimica Et Biophysica Acta (BBA) - General Subjects"},{"key":"2314_CR57","doi-asserted-by":"crossref","first-page":"887","DOI":"10.1042\/bj3000887","volume":"300","author":"PWD Scislowski","year":"1994","unstructured":"Scislowski, P. W. D., Foster, A. R., & Fuller, M. F. (1994). Regulation of oxidative degradation of L-lysine in rat liver mitochondria. The Biochemical Journal, 300, 887\u2013891.","journal-title":"The Biochemical Journal"},{"issue":"2","key":"2314_CR58","doi-asserted-by":"publisher","first-page":"241.e1","DOI":"10.1016\/j.ajog.2021.08.016","volume":"226","author":"DJ Selen","year":"2022","unstructured":"Selen, D. J., Edelson, P. K., James, K., Corelli, K., Hivert, M. F., Meigs, J. B., Thadhani, R., Ecker, J., & Powe, C. E. (2022). Physiological subtypes of gestational glucose intolerance and risk of adverse pregnancy outcomes. American Journal of Obstetrics and Gynecology, 226(2), 241.e1\u201324. https:\/\/doi.org\/10.1016\/j.ajog.2021.08.016.","journal-title":"American Journal of Obstetrics and Gynecology"},{"key":"2314_CR59","doi-asserted-by":"publisher","first-page":"2672","DOI":"10.3390\/cells11172672","volume":"11","author":"AK Sharma","year":"2022","unstructured":"Sharma, A. K., Singh, S., Singh, H., Mahajan, D., Kolli, P., Mandadapu, G., Kumar, B., Kumar, D., Kumar, S., & Jena, M. K.  (2022). Deep insight of the pathophysiology of gestational diabetes mellitus. Cells, 11, 2672. https:\/\/doi.org\/10.3390\/cells11172672.","journal-title":"Cells"},{"issue":"5","key":"2314_CR60","doi-asserted-by":"crossref","first-page":"763","DOI":"10.1210\/endrev\/bnac003","volume":"43","author":"A Sweeting","year":"2022","unstructured":"Sweeting, A., Wong, J., Murphy, H. R., & Ross, G. P. (2022). A clinical update on gestational diabetes mellitus. Endocrine Reviews, 43(5), 763\u2013793.","journal-title":"Endocrine Reviews"},{"issue":"7","key":"2314_CR61","doi-asserted-by":"publisher","first-page":"e2906","DOI":"10.1210\/clinem\/dgac181","volume":"107","author":"FR Tehrani","year":"2022","unstructured":"Tehrani, F. R., Behboudi-Gandevani, S., Farzadfar, F., Hosseinpanah, F., Hadaegh, F., Khalili, D., Soleymani-Dodaran, M., Valizadeh, M., Abedini, M., Rahmati, M., Bidhendi Yarandi, R., Torkestani, F., Abdollahi, Z., Bakhshandeh, M., Zokaee, M., Amiri, M., Bidarpour, F., Javanbakht, M., Nabipour, I., Nasli Esfahani, E., Ostovar, A., & Azizi, F. A. (2022). A cluster randomized noninferiority field trial of gestational diabetes mellitus screening. Journal of Clinical Endocrinology and Metabolism, 107(7), e2906\u2013e2920. https:\/\/doi.org\/10.1210\/clinem\/dgac181.","journal-title":"Journal of Clinical Endocrinology and Metabolism"},{"key":"2314_CR62","doi-asserted-by":"publisher","first-page":"1749","DOI":"10.3390\/microorganisms11071749","volume":"11","author":"RA Teixeira","year":"2023","unstructured":"Teixeira, R. A., Silva, C., Ferreira, A. C., Martins, D., Leite-Moreivo, A., Miranda, I. M., & Barros, A. S. (2023). The association between gestational diabetes and the microbiome: A systematic review and meta-analysis. Microorganisms, 11, 1749. https:\/\/doi.org\/10.3390\/microorganisms11071749.","journal-title":"Microorganisms"},{"issue":"8","key":"2314_CR63","doi-asserted-by":"publisher","first-page":"6521","DOI":"10.1074\/jbc.M209764200","volume":"278","author":"M Teufel","year":"2003","unstructured":"Teufel, M., Saudek, V., Ledig, J.-P., Bernhardt, A., Boularand, S., Carreau, A., Cairns, N. J., Carter, C., Cowley, D. J., Duverger, D., Ganzhorn, A. J., Guenet, C., Heintzelmann, B., Laucher, V., Sauvage, C., & Smirnova, T. (2003). Sequence identification and characterization of human carosinase and a closely related non-specific dipeptidase. Journal of Biological Chemistry, 278(8), 6521\u20136531. https:\/\/doi.org\/10.1074\/jbc.M209764200.","journal-title":"Journal of Biological Chemistry"},{"key":"2314_CR64","doi-asserted-by":"publisher","first-page":"8885954","DOI":"10.1155\/2021\/8885954","volume":"2021","author":"M Tian","year":"2021","unstructured":"Tian, M., Ma, S., You, Y., Long, S., Zhang, J., Guo, C., Wang, X., & Tan, H. (2021). Serum metabolites as an indicator of developing gestational diabetes mellitus later in pregnancy: A prospective cohort of a Chinese population. Journal of Diabetes Research, 2021, 8885954. https:\/\/doi.org\/10.1155\/2021\/8885954.","journal-title":"Journal of Diabetes Research"},{"issue":"2","key":"2314_CR65","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/0300-9629(95)00099-2","volume":"112","author":"NJ Tillakaratne","year":"1995","unstructured":"Tillakaratne, N. J., Medina-Kauwe, L., & Gibson, K. M. (1995). Gamma-Aminobutryic acid (GABA) metabolism in mammalian neural and nonneural tissues. Comparative Biochemistry and Physiology Part a, Physiology, 112(2), 247\u2013263.","journal-title":"Comparative Biochemistry and Physiology Part a, Physiology"},{"issue":"6","key":"2314_CR66","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1097\/OGX.0000000000000899","volume":"76","author":"I Tsakiridis","year":"2021","unstructured":"Tsakiridis, I., Giouleka, S., Mamopoulos, A., Kourtis, A., Athanasiadis, A., Filopoulous, D. & Dagklis T. (2021). Diagnosis and management of gestational diabetes mellitus: An overview of national and international guidelines. Obstetrical & Gynecological Survey, 76(6), 367\u2013381. https:\/\/doi.org\/10.1097\/OGX.0000000000000899.","journal-title":"Obstetrical & Gynecological Survey"},{"key":"2314_CR67","doi-asserted-by":"publisher","first-page":"531","DOI":"10.1001\/jama.2021.14807","volume":"326","author":"KW Davidson","year":"2021","unstructured":"US Preventive Services Task Force, Davidson, K. W., Barry, M. J., Mangione, C. M., Cabana, M., Caughey, A. B., Davis, E. M., Donahue, K. E., Doubeni, C. A., Kubik, M., Li, L., Ogedegbe, G., Pbert, L., Silverstein, M., Stevermer, J., Tseng, C. W., & Wong, J. B. (2021). Screening for gestational diabetes: US Preventive Services Taskforce recommendation statement. JAMA, 326, 531\u2013538. https:\/\/doi.org\/10.1001\/jama.2021.14807.","journal-title":"JAMA"},{"issue":"12","key":"2314_CR68","doi-asserted-by":"crossref","first-page":"105405","DOI":"10.1016\/j.jbc.2023.105405","volume":"299","author":"TO Usman","year":"2023","unstructured":"Usman, T. O., Chhetri, G., Yeh, H., & Dong, H. H. (2023). Beta-cell compensation and gestational diabetes. Journal of Biological Chemistry, 299(12), 105405.","journal-title":"Journal of Biological Chemistry"},{"issue":"3","key":"2314_CR69","doi-asserted-by":"crossref","first-page":"197","DOI":"10.1159\/000123456","volume":"36","author":"SR Vincent","year":"1983","unstructured":"Vincent, S. R., Hokfelt, T., Wu, J. Y., Elde, R. P., Morgan, L. M., & Kimmel, J. R. (1983). Immunohistochemical studies of the GABA system in the pancreas. Neuroendocrinology, 36(3), 197\u2013204.","journal-title":"Neuroendocrinology"},{"key":"2314_CR70","doi-asserted-by":"publisher","first-page":"350","DOI":"10.3390\/metabo10090350","volume":"10","author":"JM Walejko","year":"2020","unstructured":"Walejko, J. M., Chelliah, A., Keller-Wood, M., Wasserfall, C., Atkinson, M., Gregg, A., & Edison, A. S. (2020). Diabetes leads to alterations in normal metabolic transitions of pregnancy as revealed by time-course metabolomics. Metabolites, 10, 350. https:\/\/doi.org\/10.3390\/metabo10090350.","journal-title":"Metabolites"},{"issue":"10","key":"2314_CR71","doi-asserted-by":"publisher","first-page":"4309","DOI":"10.1172\/JCI64801","volume":"123","author":"TJ Wang","year":"2013","unstructured":"Wang, T. J., Ngo, D., Psychogios, N., Dejam, A., Larson, M. G., Vasan, R. S., Ghorbani, A., O'Sullivan, J., Cheng, S., Rhee, E. P., Sinha, S., McCabe, E., Fox, C. S., O'Donnell, C. J., Ho, J. E., Florez, J. C., Magnusson, M., Pierce, K. A., Souza, A. L., Yu, Y., Carter, C., Light, P. E., Melander, O., Clish, C. B., & Gerszten, R. E. (2013). 2-aminoadipic acid is a biomarker for diabetes risk. The Journal of Clinical Investigation, 123(10), 4309\u20134317. https:\/\/doi.org\/10.1172\/JCI64801.","journal-title":"The Journal of Clinical Investigation"},{"key":"2314_CR72","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.cca.2022.11.010","volume":"538","author":"Y Wang","year":"2023","unstructured":"Wang, Y., Li, L., & Li, P. (2023). Novel single nucleotide polymorphisms in gestational diabetes. Clinica Chimica Acta, 538, 60\u201364.","journal-title":"Clinica Chimica Acta"},{"key":"2314_CR73","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1152\/physiol.00034.2021","volume":"37","author":"DH Wasserman","year":"2022","unstructured":"Wasserman, D. H. (2022). Insulin, muscle glucose uptake, and hexokinase: Revisiting the road not taken. Physiology, 37, 115\u2013127.","journal-title":"Physiology"},{"issue":"18\u201319","key":"2314_CR74","doi-asserted-by":"crossref","first-page":"2055","DOI":"10.1016\/S0024-3205(03)00083-3","volume":"72","author":"I Wessler","year":"2003","unstructured":"Wessler, I., Kilhinger, H., Bittinger, F., Ungar, R., & Kirkpatrick, C. J. (2003). The non-neuronal cholinergic system in humans: Expression, function and pathophysiology. Life Sciences, 72(18\u201319), 2055\u20132061.","journal-title":"Life Sciences"},{"issue":"3","key":"2314_CR75","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/s002100100445","volume":"364","author":"I Wessler","year":"2001","unstructured":"Wessler, I., Roth, E., Schwarze, S., Weikel, W., Bittinger, F., Kirkpatrick, C. J., & Kilbinger H. (2001). Release of non-neuronal acetylcholine from the human placenta: Difference to neuronal acetylcholine. Naunyn-Schmiedeberg\u2019s Archives of Pharmacology, 364(3), 205\u2013212. https:\/\/doi.org\/10.1007\/s002100100445.","journal-title":"Naunyn-Schmiedeberg\u2019s Archives of Pharmacology"},{"issue":"3","key":"2314_CR76","doi-asserted-by":"crossref","first-page":"333","DOI":"10.4093\/dmj.2022.0348","volume":"47","author":"B Wicklow","year":"2023","unstructured":"Wicklow, B., & Retnakaran, R. (2023). Gestational diabetes mellitus and its implications across the lifespan. Diabetes & Metabolism Journal, 47(3), 333\u2013344.","journal-title":"Diabetes & Metabolism Journal"},{"key":"2314_CR77","doi-asserted-by":"crossref","first-page":"134","DOI":"10.1016\/j.cca.2022.12.005","volume":"539","author":"J Xie","year":"2023","unstructured":"Xie, J., Li, L., & Xing, H. (2023). Metabolomics in gestational diabetes mellitus: A review. Clinica Chimica Acta, 539, 134\u2013143.","journal-title":"Clinica Chimica Acta"},{"key":"2314_CR78","doi-asserted-by":"crossref","first-page":"e070244","DOI":"10.1136\/bmj-2022-070244","volume":"378","author":"W Xie","year":"2022","unstructured":"Xie, W., Wang, Y., Xiao, S., Chiu, L., Yu, L., & Zhang, Z. (2022). Association of gestational diabetes mellitus with overall and type specific cardiovascular and cerebrovascular diseases: Systematic review and meta-analysis. BMJ, 378, e070244.","journal-title":"BMJ"},{"issue":"10","key":"2314_CR79","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1038\/s41580-018-0044-8","volume":"19","author":"Q Yang","year":"2018","unstructured":"Yang, Q., Vijayakumar, A., & Kahn, B. B. (2018). Metabolites as regulators of insulin sensitivity and metabolism. Nature Reviews Molecular Cell Biology, 19(10), 654\u2013672.","journal-title":"Nature Reviews Molecular Cell Biology"},{"issue":"1","key":"2314_CR80","doi-asserted-by":"publisher","first-page":"2154552","DOI":"10.1080\/19490976.2022.2154552","volume":"15","author":"D Ye","year":"2023","unstructured":"Ye, D., Huang, J., Wu, J., Kie, K., Gao, X., Yan, K., Zhang, P., Tao, Y., Li, Y., Zang, S., Rong, X., Li, J., & Guo, J. (2023). Integrative metagenomic and metabolomic analysis reveal gut microbiota-derived multiple hits connected to development of gestational diabetes mellitus in humans. Gut Microbes, 15(1), 2154552. https:\/\/doi.org\/10.1080\/19490976.2022.2154552.","journal-title":"Gut Microbes"},{"key":"2314_CR81","doi-asserted-by":"crossref","first-page":"e067946","DOI":"10.1136\/bmj-2021-067946","volume":"377","author":"W Ye","year":"2022","unstructured":"Ye, W., Cong, L., Huang, J., Li, C., Liu, Z., & Liu, F. (2022). Gestational diabetes mellitus and adverse pregnancy outcomes: Systematic review and meta-analysis. BMJ, 377, e067946.","journal-title":"BMJ"},{"key":"2314_CR82","doi-asserted-by":"publisher","first-page":"292","DOI":"10.1021\/acs.jproteome.8b00602","volume":"18","author":"H Zhao","year":"2019","unstructured":"Zhao, H., Li, H., Chung, A. C. K., Xiang, L., Li, X., Zheng, Y., Luan, H., Zhu, L., Liu, W., Peng, Y., Zhao, Y., Xu, S., Li, Y., & Cai, Z. (2019). Large-scale longitudinal metabolomics study reveals different trimester-specific alterations of metabolites in relation to gestational diabetes. Journal of Proteome Research, 18, 292\u2013300. https:\/\/doi.org\/10.1021\/acs.jproteome.8b00602.","journal-title":"Journal of Proteome Research"}],"container-title":["Metabolomics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11306-025-02314-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11306-025-02314-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11306-025-02314-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,30]],"date-time":"2025-10-30T23:42:04Z","timestamp":1761867724000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11306-025-02314-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,26]]},"references-count":82,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2025,10]]}},"alternative-id":["2314"],"URL":"https:\/\/doi.org\/10.1007\/s11306-025-02314-3","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-5050182\/v1","asserted-by":"object"}]},"ISSN":["1573-3890"],"issn-type":[{"value":"1573-3890","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,26]]},"assertion":[{"value":"7 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 July 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 September 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human and\/or animal participants performed by any of the authors. Specimens were obtained from a de-identified biobank as part of the GAPPS (Global Alliance to Prevent Prematurity and Stillbirth) repository, Seattle, WA. Informed consent was obtained from participating subjects under protocols approved by the Institutional review board of the University of Washington Medical Center, Seattle, WA; Swedish Medical Center, Seattle, WA; Yakima Valley Memorial Hospital, Yakima, WA; and Seattle Children\u2019s Hospital, Seattle, WA.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}],"article-number":"140"}}