Abstract
Background/Objective:
The term macrosomia is used to describe neonates with a birth weight of 4000 g or more. Macrosomia is a potential risk factor for obesity and metabolic syndromes in postnatal and adult life, yet little is known about its associations with metabolic difference in the early age. We performed metabolic profiling of umbilical cord blood to discover differential metabolites of macrosomia.
Methods:
We conducted a case–control study of full-term singletons with normal maternal glucose tolerance [50 cases (macrosomia, birth weight ⩾4000 g); 50 controls (normal weight, birth weight 2500–3999 g)]. Metabolites in umbilical cord blood were detected using an untargeted metabolomic approach based on gas chromatography/mass spectrometry. We performed logistic regression to evaluate the associations between metabolites and macrosomia. We also performed pathway analysis based on KEGG and MBRole.
Results:
Compared with controls, the macrosomia cases had a greater male proportion, gestational age, paternal body mass index (BMI) and maternal pre-pregnancy BMI. Forty-two metabolites differed between the cases and controls. After multivariable adjustment, 2-methylfumarate [adjusted odds ratio (AOR)=1.232, 95% confidence interval (CI): 1.102–1.376], uracil (AOR=38.494, 95% CI: 5.635–262.951), elaidic acid (AOR=0.834, 95% CI: 0.761–0.915), ribose (AOR=0.089, 95% CI: 0.021–0.378), lactulose (AOR=0.815, 95% CI: 0.743–0.894) and 4-aminobutyric acid (AOR=0.835, 95% CI: 0.764–0.912) remained significantly associated with macrosomia. Pyrimidine metabolism and pentose and glucuronate interconversions were the two top-ranking pathways enriched with those metabolites (−log P-value=3.49 and 2.47, respectively).
Conclusion:
Levels of 2-methylfumarate, uracil, ribose, elaidic acid, lactulose and 4-aminobutyric acid were associated with the incidence of macrosomia. The alteration of pathways involving those factors might be linked with the incidence of macrosomia and relevant metabolic syndromes later in life, and further studies are needed to confirm it and verify the mechanisms.
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References
Ng SK, Olog A, Spinks AB, Cameron CM, Searle J, McClure RJ . Risk factors and obstetric complications of large for gestational age births with adjustments for community effects: results from a new cohort study. BMC pub health 2010; 10: 460.
Wang D, Hong Y, Zhu L, Wang X, Lv Q, Zhou Q et al. Risk factors and outcomes of macrosomia in China: a multicentric survey based on birth data. J matern fetal neonatal med 2017; 30: 623–627.
Ren JH, Wang C, Wei YM, Yang HX . Incidence of singleton macrosomia in Beijing and its risk factors. Zhonghua fu chan ke za zhi 2016; 51: 410–414.
Cheng YK, Lao TT, Sahota DS, Leung VK, Leung TY . Use of birth weight threshold for macrosomia to identify fetuses at risk of shoulder dystocia among Chinese populations. Int j gynaecol Obstet 2013; 120: 249–253.
Wang D, Zhu L, Zhang S, Wu X, Wang X, Lv Q et al. Predictive macrosomia birthweight thresholds for adverse maternal and neonatal outcomes. J Matern Fetal Neonatal Med 2016; 29: 3745–3750.
Agbozo F, Abubakari A, Der J, Jahn A . Prevalence of low birth weight, macrosomia and stillbirth and their relationship to associated maternal risk factors in Hohoe Municipality, Ghana. Midwifery 2016; 40: 200–206.
Mohammadbeigi A, Farhadifar F, Soufi Zadeh N, Mohammadsalehi N, Rezaiee M, Aghaei M . Fetal macrosomia: risk factors, maternal, and perinatal outcome. Ann med health sci res 2013; 3: 546–550.
Yang S, Zhou A, Xiong C, Yang R, Bassig BA, Hu R et al. Parental body mass index, gestational weight gain, and risk of macrosomia: a population-based case–control study in China. Paediatr perinat epidemiol 2015; 29: 462–471.
Li G, Kong L, Li Z, Zhang L, Fan L, Zou L et al. Prevalence of macrosomia and its risk factors in china: a multicentre survey based on birth data involving 101,723 singleton term infants. Paediatr Perinat epidemiol 2014; 28: 345–350.
Kerenyi Z, Tamas G, Kivimaki M, Peterfalvi A, Madarasz E, Bosnyak Z et al. Maternal glycemia and risk of large-for-gestational-age babies in a population-based screening. Diabetes care 2009; 32: 2200–2205.
Hehir MP, McHugh AF, Maguire PJ, Mahony R . Extreme macrosomia-obstetric outcomes and complications in birthweights >5000 g. Aust N Z j obstet gynaecol 2015; 55: 42–46.
Swank ML, Caughey AB, Farinelli CK, Main EK, Melsop KA, Gilbert WM et al. The impact of change in pregnancy body mass index on macrosomia. Obesity (Silver Spring, MD) 2014; 22: 1997–2002.
Li Y, Liu QF, Zhang D, Shen Y, Ye K, Lai HL et al. Weight gain in pregnancy, maternal age and gestational age in relation to fetal macrosomia. Clin nutr res 2015; 4: 104–109.
Hermann GM, Dallas LM, Haskell SE, Roghair RD . Neonatal macrosomia is an independent risk factor for adult metabolic syndrome. Neonatology 2010; 98: 238–244.
Wurtz P, Wang Q, Kangas AJ, Richmond RC, Skarp J, Tiainen M et al. Metabolic signatures of adiposity in young adults: mendelian randomization analysis and effects of weight change. PLoS med 2014; 11: e1001765.
Hellmuth C, Kirchberg FF, Lass N, Harder U, Peissner W, Koletzko B et al. Tyrosine is associated with insulin resistance in longitudinal metabolomic profiling of obese children. J diabetes res 2016; 2016: 2108909.
Chen HH, Tseng YJ, Wang SY, Tsai YS, Chang CS, Kuo TC et al. The metabolome profiling and pathway analysis in metabolic healthy and abnormal obesity. Int j obesity 2015; 39: 1241–1248.
Wang TJ, Larson MG, Vasan RS, Cheng S, Rhee EP, McCabe E et al. Metabolite profiles and the risk of developing diabetes. Nat Med 2011; 17: 448–453.
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; 9: 311–326.
Perng W, Gillman MW, Fleisch AF, Michalek RD, Watkins SM, Isganaitis E et al. Metabolomic profiles and childhood obesity. Obesity (Silver Spring, MD) 2014; 22: 2570–2578.
Son HH, Kim SH, Moon JY, Chung BC, Park MJ, Choi MH . Serum sterol profiling reveals increased cholesterol biosynthesis in childhood obesity. J steroid biochem mol biol 2015; 149: 138–145.
Wahl S, Yu Z, Kleber M, Singmann P, Holzapfel C, He Y et al. Childhood obesity is associated with changes in the serum metabolite profile. Obes Facts 2012; 5: 660–670.
Xia J, Sinelnikov IV, Han B, Wishart DS . MetaboAnalyst 3.0-making metabolomics more meaningful. Nucleic Acids Res 2015; 43: W251–W257.
Xia J, Psychogios N, Young N, Wishart DS . MetaboAnalyst: a web server for metabolomic data analysis and interpretation. Nucleic Acids Res 2009; 37 (Web Server issue): W652–W660.
Wardrope C, Mowat CG, Walkinshaw MD, Reid GA, Chapman SK . Fumarate reductase: structural and mechanistic insights from the catalytic reduction of 2-methylfumarate. FEBS Lett 2006; 580: 1677–1680.
Koy A, Waldhaus A, Hammen HW, Wendel U, Mayatepek E, Schadewaldt P . Urinary excretion of pentose phosphate pathway-associated polyols in early postnatal life. Neonatology 2009; 95: 256–261.
Anichini C, Lo Rizzo C, Longini M, Paoli G, di Bartolo RM, Proietti F et al. Beckwith-Wiedemann syndrome: potassium ascorbate with ribose therapy in a syndrome with high neoplastic risk. Anticancer Res 2011; 31: 3973–3976.
Ohmori H, Fujii K, Kadochi Y, Mori S, Nishiguchi Y, Fujiwara R et al. Elaidic acid, a trans-fatty acid, enhances the metastasis of colorectal cancer cells. Pathobiology 2016; 84: 144–151.
Schlormann W, Kramer R, Lochner A, Rohrer C, Schleussner E, Jahreis G et al. Foetal cord blood contains higher portions of n-3 and n-6 long-chain PUFA but lower portions of trans C18:1 isomers than maternal blood. Food Nutr Res 2015; 59: 29348.
De Preter V, Coopmans T, Rutgeerts P, Verbeke K . Influence of long-term administration of lactulose and Saccharomyces boulardii on the colonic generation of phenolic compounds in healthy human subjects. J Am Coll Nutr 2006; 25: 541–549.
Benitez-Paez A, Moreno FJ, Sanz ML, Sanz Y . Genome structure of the symbiont Bifidobacterium pseudocatenulatum CECT 7765 and gene expression profiling in response to lactulose-derived oligosaccharides. Front Microbiol 2016; 7: 624.
Li J, Casteels T, Frogne T, Ingvorsen C, Honore C, Courtney M et al. Artemisinins target GABAA receptor signaling and impair alpha cell identity. Cell 2017; 168: 86–100.e15.
Franklin IK, Wollheim CB . GABA in the endocrine pancreas: its putative role as an islet cell paracrine-signalling molecule. J Gen Physiol 2004; 123: 185–190.
Maruyama H, Hisatomi A, Orci L, Grodsky GM, Unger RH . Insulin within islets is a physiologic glucagon release inhibitor. J Clin Invest 1984; 74: 2296–2299.
Xu E, Kumar M, Zhang Y, Ju W, Obata T, Zhang N et al. Intra-islet insulin suppresses glucagon release via GABA-GABAA receptor system. Cell Metab 2006; 3: 47–58.
van den Oord EJ . Controlling false discoveries in genetic studies. Am J Med Genet Part B, Neuropsychiatr Genet 2008; 147b: 637–644.
Abdullah M, Kornegay JN, Honcoop A, Parry TL, Balog-Alvarez CJ, O'Neal SK et al. Non-targeted metabolomics analysis of golden retriever muscular dystrophy-affected muscles reveals alterations in arginine and proline metabolism, and elevations in glutamic and oleic acid in vivo. Metabolites 2017; 7: 38.
Takahashi S, Izawa Y, Suzuki N . Astroglial pentose phosphate pathway rates in response to high-glucose environments. ASN neuro 2012; 4: e00078.
Gupte SA . Targeting the pentose phosphate pathway in syndrome X-related cardiovascular complications. Drug Dev Res 2010; 71: 161–167.
Lm T, Or T . Pre and post-natal risk and determination of factors for child obesity. J Med Life 2016; 9: 386–391.
Rona G, Scheer I, Nagy K, Palinkas HL, Tihanyi G, Borsos M et al. Detection of uracil within DNA using a sensitive labeling method for in vitro and cellular applications. Nucleic Acids Res 2016; 44: e28.
Luhnsdorf B, Epe B, Khobta A . Excision of uracil from transcribed DNA negatively affects gene expression. J Biol Chem 2014; 289: 22008–22018.
Nielsen HR, Sjolin KE, Nyholm K, Baliga BS, Wong R, Borek E . Beta-aminoisobutyric acid, a new probe for the metabolism of DNA and RNA in normal and tumorous tissue. Cancer Res 1974; 34: 1381–1384.
Acknowledgements
The present study was supported by the National Natural Science Foundation of China (No. 81072378) and the Natural Science Funds of Zhejiang (No. Y2101185). We gratefully acknowledge the Department of Obstetrics, the 2nd Affiliated Hospital of Wenzhou Medical University, for the umbilical cord blood samples. We also thank Wenzhou residents for their support for our epidemiological study.
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Sun, H., Wang, Y., Wang, C. et al. Metabolic profiling of umbilical cord blood in macrosomia. Int J Obes 42, 679–685 (2018). https://doi.org/10.1038/ijo.2017.288
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DOI: https://doi.org/10.1038/ijo.2017.288