{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T07:26:47Z","timestamp":1791271607763,"version":"4.1.0"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2020,9,24]],"date-time":"2020-09-24T00:00:00Z","timestamp":1600905600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2020,9,24]],"date-time":"2020-09-24T00:00:00Z","timestamp":1600905600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/100008982","name":"Qatar National Research Fund","doi-asserted-by":"publisher","award":["NPRP10-1205-160010"],"award-info":[{"award-number":["NPRP10-1205-160010"]}],"id":[{"id":"10.13039\/100008982","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Transl Med"],"published-print":{"date-parts":[[2020,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Background<\/jats:title><jats:p>Pregnant women with gestational diabetes mellitus (GDM) or type 2 diabetes mellitus (T2DM) are at increased risks of pre-term labor, hypertension and preeclampsia. In this study, metabolic profiling of blood samples collected from GDM, T2DM and control pregnant women was undertaken to identify potential diagnostic biomarkers in GDM\/T2DM and compared to pregnancy outcome.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>Sixty-seven pregnant women (21 controls, 32 GDM, 14 T2DM) in their second trimester underwent targeted metabolomics of plasma samples using tandem mass spectrometry with the Biocrates MxP<jats:sup>\u00ae<\/jats:sup>Quant 500 Kit. Linear regression models were used to identify the metabolic signature of GDM and T2DM, followed by generalized linear model (GLMNET) and Receiver Operating Characteristic (ROC) analysis to determine best predictors of GDM, T2DM and pre-term labor.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The gestational age at delivery was 2\u00a0weeks earlier in T2DM compared to GDM and controls and correlated negatively with maternal HbA1C and systolic blood pressure and positively with serum albumin. Linear regression models revealed elevated glutamate and branched chain amino acids in GDM\u2009+\u2009T2DM group compared to controls. Regression models also revealed association of lower levels of triacylglycerols and diacylglycerols containing oleic and linoleic fatty acids with pre-term delivery. A generalized linear model ROC analyses revealed that that glutamate is the best predictors of GDM compared to controls (area under curve; AUC\u2009=\u20090.81). The model also revealed that phosphatidylcholine diacyl C40:2, arachidonic acid, glycochenodeoxycholic acid, and phosphatidylcholine acyl-alkyl C34:3 are the best predictors of GDM\u2009+\u2009T2DM compared to controls (AUC\u2009=\u20090.90). The model also revealed that the triacylglycerols C17:2\/36:4 and C18:1\/34:1 are the best predictors of pre-term delivery (\u2264\u200937\u00a0weeks) (AUC\u2009=\u20090.84).<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions<\/jats:title><jats:p>This study highlights the metabolite alterations in women in their second trimester with diabetes mellitus and identifies predictive indicators of pre-term delivery. Future studies to confirm these associations in other cohorts and investigate their functional relevance and potential utilization for targeted therapies are warranted.<\/jats:p><\/jats:sec>","DOI":"10.1186\/s12967-020-02531-5","type":"journal-article","created":{"date-parts":[[2020,9,24]],"date-time":"2020-09-24T12:02:47Z","timestamp":1600948967000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":21,"title":["Metabolic profiling of pre-gestational and gestational diabetes mellitus identifies novel predictors of pre-term delivery"],"prefix":"10.1186","volume":"18","author":[{"given":"Ilhame","family":"Diboun","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Manjunath","family":"Ramanjaneya","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yasser","family":"Majeed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lina","family":"Ahmed","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed","family":"Bashir","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alexandra E.","family":"Butler","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdul Badi","family":"Abou-Samra","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Stephen L.","family":"Atkin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nayef A.","family":"Mazloum","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3803-4604","authenticated-orcid":false,"given":"Mohamed A.","family":"Elrayess","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2020,9,24]]},"reference":[{"issue":"Suppl 1","key":"2531_CR1","doi-asserted-by":"crossref","first-page":"S103","DOI":"10.2337\/diacare.26.2007.S103","volume":"26","author":"A American Diabetes","year":"2003","unstructured":"American Diabetes A. Gestational diabetes mellitus. Diabetes Care. 2003;26(Suppl 1):S103\u20135.","journal-title":"Diabetes Care"},{"key":"2531_CR2","first-page":"389","volume":"20","author":"H Abdi","year":"2017","unstructured":"Abdi H, Hosseinpanah F, Azizi F, Hadaegh F, Amouzegar A. Screening for dysglycemia: a comment on classification and diagnosis of diabetes in american diabetes association standards of medical care in diabetes-2016. Arch Iran Med. 2017;20:389.","journal-title":"Arch Iran Med"},{"key":"2531_CR3","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1007\/s11892-015-0699-x","volume":"16","author":"Y Zhu","year":"2016","unstructured":"Zhu Y, Zhang C. Prevalence of gestational diabetes and risk of progression to type 2 diabetes: a global perspective. Curr Diab Rep. 2016;16:7.","journal-title":"Curr Diab Rep"},{"key":"2531_CR4","doi-asserted-by":"publisher","first-page":"e0201247","DOI":"10.1371\/journal.pone.0201247","volume":"13","author":"M Bashir","year":"2018","unstructured":"Bashir M, Abdel-Rahman EM, Aboulfotouh M, Eltaher F, Omar K, Babarinsa I, Appiah-Sakyi K, Sharaf T, Azzam E, Abukhalil M, Boumedjane M. Prevalence of newly detected diabetes in pregnancy in Qatar, using universal screening. PLoS ONE. 2018;13:e0201247.","journal-title":"PLoS ONE"},{"key":"2531_CR5","doi-asserted-by":"publisher","first-page":"e49","DOI":"10.1097\/AOG.0000000000002501","volume":"131","author":"ACOG Practice Bulletin No. 190","year":"2018","unstructured":"ACOG Practice Bulletin No. 190. Gestational diabetes mellitus. Obstet Gynecol. 2018;131:e49\u201364.","journal-title":"Obstet Gynecol"},{"key":"2531_CR6","doi-asserted-by":"publisher","first-page":"1053","DOI":"10.2337\/diacare.22.7.1053","volume":"22","author":"F Pallardo","year":"1999","unstructured":"Pallardo F, Herranz L, Garcia-Ingelmo T, Grande C, Martin-Vaquero P, Janez M, Gonzalez A. Early postpartum metabolic assessment in women with prior gestational diabetes. Diabetes Care. 1999;22:1053\u20138.","journal-title":"Diabetes Care"},{"key":"2531_CR7","doi-asserted-by":"publisher","first-page":"E1","DOI":"10.1530\/EC-18-0130","volume":"7","author":"AM Patti","year":"2018","unstructured":"Patti AM, Pafili K, Papanas N, Rizzo M. Metabolic disorders during pregnancy and postpartum cardiometabolic risk. Endocr Connect. 2018;7:E1\u20134.","journal-title":"Endocr Connect"},{"key":"2531_CR8","doi-asserted-by":"publisher","first-page":"134","DOI":"10.1159\/000337734","volume":"2","author":"L Garcia-Vargas","year":"2012","unstructured":"Garcia-Vargas L, Addison SS, Nistala R, Kurukulasuriya D, Sowers JR. Gestational diabetes and the offspring: implications in the development of the cardiorenal metabolic syndrome in offspring. Cardiorenal Med. 2012;2:134\u201342.","journal-title":"Cardiorenal Med"},{"key":"2531_CR9","first-page":"850","volume":"102","author":"MM Hedderson","year":"2003","unstructured":"Hedderson MM, Ferrara A, Sacks DA. Gestational diabetes mellitus and lesser degrees of pregnancy hyperglycemia: association with increased risk of spontaneous preterm birth. Obstet Gynecol. 2003;102:850\u20136.","journal-title":"Obstet Gynecol"},{"key":"2531_CR10","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1007\/s00404-007-0359-8","volume":"276","author":"Y Yogev","year":"2007","unstructured":"Yogev Y, Langer O. Spontaneous preterm delivery and gestational diabetes: the impact of glycemic control. Arch Gynecol Obstet. 2007;276:361\u20135.","journal-title":"Arch Gynecol Obstet"},{"key":"2531_CR11","doi-asserted-by":"publisher","first-page":"2824","DOI":"10.2337\/diacare.27.12.2824","volume":"27","author":"J Lepercq","year":"2004","unstructured":"Lepercq J, Coste J, Theau A, Dubois-Laforgue D, Timsit J. Factors associated with preterm delivery in women with type 1 diabetes: a cohort study. Diabetes Care. 2004;27:2824\u20138.","journal-title":"Diabetes Care"},{"key":"2531_CR12","doi-asserted-by":"publisher","first-page":"1004","DOI":"10.3109\/14767050903551392","volume":"23","author":"K Kock","year":"2010","unstructured":"Kock K, Kock F, Klein K, Bancher-Todesca D, Helmer H. Diabetes mellitus and the risk of preterm birth with regard to the risk of spontaneous preterm birth. J Matern Fetal Neonatal Med. 2010;23:1004\u20138.","journal-title":"J Matern Fetal Neonatal Med"},{"key":"2531_CR13","doi-asserted-by":"publisher","first-page":"420","DOI":"10.5144\/0256-4947.2017.420","volume":"37","author":"H Al-Wassia","year":"2017","unstructured":"Al-Wassia H, Saber M. Admission of term infants to the neonatal intensive care unit in a Saudi tertiary teaching hospital: cumulative incidence and risk factors. Ann Saudi Med. 2017;37:420\u20134.","journal-title":"Ann Saudi Med"},{"key":"2531_CR14","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.pedneo.2017.07.007","volume":"59","author":"YT Huang","year":"2018","unstructured":"Huang YT, Lin HY, Wang CH, Su BH, Lin CC. Association of preterm birth and small for gestational age with metabolic outcomes in children and adolescents: a population-based cohort study from Taiwan. Pediatr Neonatol. 2018;59:147\u201353.","journal-title":"Pediatr Neonatol"},{"key":"2531_CR15","doi-asserted-by":"publisher","first-page":"275","DOI":"10.2217\/clp.12.32","volume":"7","author":"T Louise","year":"2012","unstructured":"Louise T, Nauf Bendar AS, Durighel G, Frost G, Bell J. The effect of preterm birth on adiposity and metabolic pathways and the implications for later life. Clin Lipidol. 2012;7:275\u201388.","journal-title":"Clin Lipidol"},{"key":"2531_CR16","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.jacc.2020.04.072","volume":"76","author":"C Crump","year":"2020","unstructured":"Crump C, Sundquist J, Howell EA, McLaughlin MA, Stroustrup A, Sundquist K. Pre-term delivery and risk of ischemic heart disease in women. J Am Coll Cardiol. 2020;76:57\u201367.","journal-title":"J Am Coll Cardiol"},{"key":"2531_CR17","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1177\/1753495X13513577","volume":"7","author":"H Berger","year":"2014","unstructured":"Berger H, Melamed N. Timing of delivery in women with diabetes in pregnancy. Obstet Med. 2014;7:8\u201316.","journal-title":"Obstet Med"},{"issue":"243","key":"2531_CR18","first-page":"e241","volume":"215","author":"MN Feghali","year":"2016","unstructured":"Feghali MN, Caritis SN, Catov JM, Scifres CM. Timing of delivery and pregnancy outcomes in women with gestational diabetes. Am J Obstet Gynecol. 2016;215(243):e241\u20137.","journal-title":"Am J Obstet Gynecol"},{"key":"2531_CR19","doi-asserted-by":"publisher","first-page":"1078","DOI":"10.1001\/jama.1997.03550130052036","volume":"278","author":"CG Solomon","year":"1997","unstructured":"Solomon CG, Willett WC, Carey VJ, Rich-Edwards J, Hunter DJ, Colditz GA, Stampfer MJ, Speizer FE, Spiegelman D, Manson JE. A prospective study of pregravid determinants of gestational diabetes mellitus. JAMA. 1997;278:1078\u201383.","journal-title":"JAMA"},{"key":"2531_CR20","doi-asserted-by":"publisher","first-page":"833","DOI":"10.2337\/dc15-2251","volume":"39","author":"M Guasch-Ferre","year":"2016","unstructured":"Guasch-Ferre M, Hruby A, Toledo E, Clish CB, Martinez-Gonzalez MA, Salas-Salvado J, Hu FB. Metabolomics in prediabetes and diabetes: a systematic review and meta-analysis. Diabetes Care. 2016;39:833\u201346.","journal-title":"Diabetes Care"},{"key":"2531_CR21","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1186\/s12967-018-1548-x","volume":"16","author":"H Al-Sulaiti","year":"2018","unstructured":"Al-Sulaiti H, Diboun I, Banu S, Al-Emadi M, Amani P, Harvey TM, Domling AS, Latiff A, Elrayess MA. Triglyceride profiling in adipose tissues from obese insulin sensitive, insulin resistant and type 2 diabetes mellitus individuals. J Transl Med. 2018;16:175.","journal-title":"J Transl Med"},{"key":"2531_CR22","doi-asserted-by":"publisher","first-page":"348","DOI":"10.1186\/s12967-019-2096-8","volume":"17","author":"H Al-Sulaiti","year":"2019","unstructured":"Al-Sulaiti H, Diboun I, Agha MV, Mohamed FFS, Atkin S, Domling AS, Elrayess MA, Mazloum NA. Metabolic signature of obesity-associated insulin resistance and type 2 diabetes. J Transl Med. 2019;17:348.","journal-title":"J Transl Med"},{"key":"2531_CR23","doi-asserted-by":"publisher","first-page":"3342","DOI":"10.3390\/ijms19113342","volume":"19","author":"JF Plows","year":"2018","unstructured":"Plows JF, Stanley JL, Baker PN, Reynolds CM, Vickers MH. The pathophysiology of gestational diabetes mellitus. Int J Mol Sci. 2018;19:3342.","journal-title":"Int J Mol Sci."},{"key":"2531_CR24","doi-asserted-by":"publisher","first-page":"2453","DOI":"10.1007\/s00125-014-3371-0","volume":"57","author":"J Huynh","year":"2014","unstructured":"Huynh J, Xiong G, Bentley-Lewis R. A systematic review of metabolite profiling in gestational diabetes mellitus. Diabetologia. 2014;57:2453\u201364.","journal-title":"Diabetologia"},{"key":"2531_CR25","doi-asserted-by":"publisher","first-page":"7154216","DOI":"10.1155\/2018\/7154216","volume":"2018","author":"R Mierzy\u0144ski","year":"2018","unstructured":"Mierzy\u0144ski R, D\u0142uski D, Nowakowski \u0141, Poniedzia\u0142ek-Czajkowska E, Leszczy\u0144ska-Gorzelak B. Adiponectin and omentin levels as predictive biomarkers of preterm birth in patients with gestational diabetes mellitus. Biomed Res Int. 2018;2018:7154216.","journal-title":"Biomed Res Int"},{"key":"2531_CR26","doi-asserted-by":"publisher","first-page":"1324","DOI":"10.3390\/ijms21041324","volume":"21","author":"UV Mahajan","year":"2020","unstructured":"Mahajan UV, Varma VR, Huang CW, An Y, Tanaka T, Ferrucci L, Takebayashi T, Harada S, Iida M, Legido-Quigley C, Thambisetty M. Blood metabolite signatures of metabolic syndrome in two cross-cultural older adult cohorts. Int J Mol Sci. 2020;21:1324.","journal-title":"Int J Mol Sci."},{"key":"2531_CR27","first-page":"105","volume":"26","author":"C Feng","year":"2014","unstructured":"Feng C, Wang H, Lu N, Chen T, He H, Lu Y, Tu XM. Log-transformation and its implications for data analysis. Shanghai Arch Psychiatry. 2014;26:105\u20139.","journal-title":"Shanghai Arch Psychiatry"},{"key":"2531_CR28","doi-asserted-by":"publisher","first-page":"D521","DOI":"10.1093\/nar\/gkl923","volume":"35","author":"DS Wishart","year":"2007","unstructured":"Wishart DS, Tzur D, Knox C, Eisner R, Guo AC, Young N, Cheng D, Jewell K, Arndt D, Sawhney S, et al. HMDB: the human metabolome database. Nucleic Acids Res. 2007;35:D521\u20136.","journal-title":"Nucleic Acids Res"},{"key":"2531_CR29","unstructured":"Mohamed E, Ilhame D, Manjunath R, Yasser M, Lina A, Mohammed B, Alexandra EB, Abdul-Badi A-S, Stephen LA, Nayef AM, Mohamed AE. Metabolic profiling of pre-gestational and gestational diabetes mellitus identifies novel predictors of pre-term labor: Supplementary tables S1\u2013S5. 2020."},{"key":"2531_CR30","doi-asserted-by":"publisher","first-page":"140","DOI":"10.1186\/s12967-016-0897-6","volume":"14","author":"A Halama","year":"2016","unstructured":"Halama A, Kulinski M, Kader SA, Satheesh NJ, Abou-Samra AB, Suhre K, Mohammad RM. Measurement of 1,5-anhydroglucitol in blood and saliva: from non-targeted metabolomics to biochemical assay. J Transl Med. 2016;14:140.","journal-title":"J Transl Med"},{"key":"2531_CR31","doi-asserted-by":"publisher","first-page":"615","DOI":"10.1038\/msb.2012.43","volume":"8","author":"R Wang-Sattler","year":"2012","unstructured":"Wang-Sattler R, Yu Z, Herder C, Messias AC, Floegel A, He Y, Heim K, Campillos M, Holzapfel C, Thorand B, et al. Novel biomarkers for pre-diabetes identified by metabolomics. Mol Syst Biol. 2012;8:615.","journal-title":"Mol Syst Biol"},{"key":"2531_CR32","doi-asserted-by":"publisher","first-page":"2467","DOI":"10.3390\/ijms20102467","volume":"20","author":"B Arneth","year":"2019","unstructured":"Arneth B, Arneth R, Shams M. Metabolomics of type 1 and type 2 diabetes. Int J Mol Sci. 2019;20:2467.","journal-title":"Int J Mol Sci"},{"key":"2531_CR33","doi-asserted-by":"publisher","first-page":"610","DOI":"10.1016\/j.ajog.2004.08.011","volume":"192","author":"I Cetin","year":"2005","unstructured":"Cetin I, de Santis MS, Taricco E, Radaelli T, Teng C, Ronzoni S, Spada E, Milani S, Pardi G. Maternal and fetal amino acid concentrations in normal pregnancies and in pregnancies with gestational diabetes mellitus. Am J Obstet Gynecol. 2005;192:610\u20137.","journal-title":"Am J Obstet Gynecol"},{"key":"2531_CR34","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1186\/s40200-016-0283-1","volume":"16","author":"N Rahimi","year":"2017","unstructured":"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.","journal-title":"J Diabetes Metab Disord"},{"key":"2531_CR35","doi-asserted-by":"publisher","first-page":"44120","DOI":"10.1038\/srep44120","volume":"7","author":"XT Huang","year":"2017","unstructured":"Huang XT, Li C, Peng XP, Guo J, Yue SJ, Liu W, Zhao FY, Han JZ, Huang YH, Yang L, et al. An excessive increase in glutamate contributes to glucose-toxicity in beta-cells via activation of pancreatic NMDA receptors in rodent diabetes. Sci Rep. 2017;7:44120.","journal-title":"Sci Rep"},{"key":"2531_CR36","doi-asserted-by":"publisher","first-page":"7010","DOI":"10.1038\/s41598-019-43431-z","volume":"9","author":"S Chen","year":"2019","unstructured":"Chen S, Akter S, Kuwahara K, Matsushita Y, Nakagawa T, Konishi M, Honda T, Yamamoto S, Hayashi T, Noda M, Mizoue T. Serum amino acid profiles and risk of type 2 diabetes among Japanese adults in the Hitachi Health Study. Sci Rep. 2019;9:7010.","journal-title":"Sci Rep"},{"key":"2531_CR37","doi-asserted-by":"publisher","first-page":"1098","DOI":"10.1093\/ajcn\/nqz191","volume":"110","author":"Y Karusheva","year":"2019","unstructured":"Karusheva Y, Koessler T, Strassburger K, Markgraf D, Mastrototaro L, Jelenik T, Simon MC, Pesta D, Zaharia OP, Bodis K, et al. Short-term dietary reduction of branched-chain amino acids reduces meal-induced insulin secretion and modifies microbiome composition in type 2 diabetes: a randomized controlled crossover trial. Am J Clin Nutr. 2019;110:1098\u2013107.","journal-title":"Am J Clin Nutr"},{"key":"2531_CR38","doi-asserted-by":"publisher","first-page":"513","DOI":"10.3390\/jcm7120513","volume":"7","author":"JL Flores-Guerrero","year":"2018","unstructured":"Flores-Guerrero JL, Ost\u00e9 MC, Kieneker LM, Gruppen EG, Wolak-Dinsmore J, Otvos JD, Connelly MA, Bakker SJ, Dullaart RP. Plasma branched-chain amino acids and risk of incident type 2 diabetes: results from the PREVEND prospective cohort study. J Clin Med. 2018;7:513.","journal-title":"J Clin Med."},{"key":"2531_CR39","doi-asserted-by":"publisher","first-page":"2565","DOI":"10.1007\/s00125-012-2644-8","volume":"55","author":"KD Copps","year":"2012","unstructured":"Copps KD, White MF. Regulation of insulin sensitivity by serine\/threonine phosphorylation of insulin receptor substrate proteins IRS1 and IRS2. Diabetologia. 2012;55:2565\u201382.","journal-title":"Diabetologia"},{"key":"2531_CR40","doi-asserted-by":"publisher","first-page":"606","DOI":"10.1016\/j.cmet.2012.01.024","volume":"15","author":"CB Newgard","year":"2012","unstructured":"Newgard CB. Interplay between lipids and branched-chain amino acids in development of insulin resistance. Cell Metab. 2012;15:606\u201314.","journal-title":"Cell Metab"},{"key":"2531_CR41","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1016\/j.chemphyslip.2011.06.008","volume":"164","author":"S Wallner","year":"2011","unstructured":"Wallner S, Schmitz G. Plasmalogens the neglected regulatory and scavenging lipid species. Chem Phys Lipids. 2011;164:573\u201389.","journal-title":"Chem Phys Lipids"},{"key":"2531_CR42","doi-asserted-by":"publisher","first-page":"197","DOI":"10.2337\/db06-0490","volume":"56","author":"SJ Persaud","year":"2007","unstructured":"Persaud SJ, Muller D, Belin VD, Kitsou-Mylona I, Asare-Anane H, Papadimitriou A, Burns CJ, Huang GC, Amiel SA, Jones PM. The role of arachidonic acid and its metabolites in insulin secretion from human islets of langerhans. Diabetes. 2007;56:197\u2013203.","journal-title":"Diabetes"},{"key":"2531_CR43","doi-asserted-by":"publisher","first-page":"257","DOI":"10.4093\/dmj.2019.0043","volume":"43","author":"JM Ferrell","year":"2019","unstructured":"Ferrell JM, Chiang JYL. Understanding bile acid signaling in diabetes: from pathophysiology to therapeutic targets. Diabetes Metab J. 2019;43:257\u201372.","journal-title":"Diabetes Metab J"},{"key":"2531_CR44","doi-asserted-by":"publisher","first-page":"158","DOI":"10.1002\/ijgo.12794","volume":"145","author":"N Arbib","year":"2019","unstructured":"Arbib N, Shmueli A, Salman L, Krispin E, Toledano Y, Hadar E. First trimester glycosylated hemoglobin as a predictor of gestational diabetes mellitus. Int J Gynaecol Obstet. 2019;145:158\u201363.","journal-title":"Int J Gynaecol Obstet"},{"issue":"162","key":"2531_CR45","first-page":"e161","volume":"197","author":"J Zhang","year":"2007","unstructured":"Zhang J, Villar J, Sun W, Merialdi M, Abdel-Aleem H, Mathai M, Ali M, Yu KF, Zavaleta N, Purwar M, et al. Blood pressure dynamics during pregnancy and spontaneous preterm birth. Am J Obstet Gynecol. 2007;197(162):e161\u20136.","journal-title":"Am J Obstet Gynecol"},{"key":"2531_CR46","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1161\/HYPERTENSIONAHA.113.01276","volume":"63","author":"MR Sutherland","year":"2014","unstructured":"Sutherland MR, Bertagnolli M, Lukaszewski MA, Huyard F, Yzydorczyk C, Luu TM, Nuyt AM. Preterm birth and hypertension risk: the oxidative stress paradigm. Hypertension. 2014;63:12\u20138.","journal-title":"Hypertension"},{"key":"2531_CR47","doi-asserted-by":"publisher","first-page":"563","DOI":"10.1016\/S0009-9120(96)00101-4","volume":"29","author":"JC Forest","year":"1996","unstructured":"Forest JC, Masse J, Moutquin JM. Maternal hematocrit and albumin as predictors of intrauterine growth retardation and preterm delivery. Clin Biochem. 1996;29:563\u20136.","journal-title":"Clin Biochem"},{"key":"2531_CR48","doi-asserted-by":"publisher","first-page":"1567467","DOI":"10.1155\/2017\/1567467","volume":"2017","author":"C Fujii","year":"2017","unstructured":"Fujii C, Kawai T, Azuma K, Oguma Y, Katsukawa F, Hirose H, Tanaka K, Meguro S, Matsumoto H, Itoh H. Relationships between composition of major fatty acids and fat distribution and insulin resistance in Japanese. J Diabetes Res. 2017;2017:1567467.","journal-title":"J Diabetes Res"},{"key":"2531_CR49","doi-asserted-by":"publisher","first-page":"366","DOI":"10.1159\/000077967","volume":"19","author":"E Sheiner","year":"2004","unstructured":"Sheiner E, Levy A, Katz M, Hershkovitz R, Leron E, Mazor M. Gender does matter in perinatal medicine. Fetal Diagn Ther. 2004;19:366\u20139.","journal-title":"Fetal Diagn Ther"},{"key":"2531_CR50","doi-asserted-by":"publisher","first-page":"e273","DOI":"10.1111\/j.1464-5491.2012.03663.x","volume":"29","author":"SF Ehrlich","year":"2012","unstructured":"Ehrlich SF, Eskenazi B, Hedderson MM, Ferrara A. Sex ratio variations among the offspring of women with diabetes in pregnancy. Diabet Med. 2012;29:e273\u20138.","journal-title":"Diabet Med"},{"key":"2531_CR51","doi-asserted-by":"publisher","first-page":"e0179647","DOI":"10.1371\/journal.pone.0179647","volume":"12","author":"H Herath","year":"2017","unstructured":"Herath H, Herath R, Wickremasinghe R. Gestational diabetes mellitus and risk of type 2 diabetes 10\u00a0years after the index pregnancy in Sri Lankan women-A community based retrospective cohort study. PLoS ONE. 2017;12:e0179647.","journal-title":"PLoS ONE"}],"container-title":["Journal of Translational Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12967-020-02531-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1186\/s12967-020-02531-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/s12967-020-02531-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,11,20]],"date-time":"2022-11-20T07:21:06Z","timestamp":1668928866000},"score":1,"resource":{"primary":{"URL":"https:\/\/translational-medicine.biomedcentral.com\/articles\/10.1186\/s12967-020-02531-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,24]]},"references-count":51,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,12]]}},"alternative-id":["2531"],"URL":"https:\/\/doi.org\/10.1186\/s12967-020-02531-5","relation":{},"ISSN":["1479-5876"],"issn-type":[{"value":"1479-5876","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,9,24]]},"assertion":[{"value":"24 June 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"15 September 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 September 2020","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"All participants provided informed consent. Protocols were approved by Institutional Review Boards of the Hamad Medical Corporation (15101\/15) and Weill Cornell Medical College in Qatar (15-00016).","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Not applicable.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare that they have no competing interests.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"366"}}