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Pediatrics

Inter-generational link of obesity in term and preterm births: role of maternal plasma acylcarnitines

International Journal of Obesity volume 43, pages 1967–1977 (2019)Cite this article

Subjects

Abstract

Background/objectives

Acylcarnitines, intermediates of fatty acid oxidation, are known to be involved in obesity and insulin resistance. Since maternal prepregnancy overweight or obesity (OWO) is a recognized major risk factor for offspring OWO, we hypothesized that maternal plasma acylcarnitines may play a role in inter-generational OWO.

Subjects/methods

This study included 1402 mother–child pairs (1043 term, 359 preterm) recruited at birth from 1998–2013 and followed prospectively up to age 18 years at the Boston Medical Center. The primary outcomes were child OWO defined as BMI ≥ 85th percentile for age and sex. The primary exposures were maternal prepregnancy OWO defined as BMI ≥ 25 kg/m2 and maternal acylcarnitine levels measured in plasma samples collected soon after delivery using liquid chromatography–tandem mass spectrometry (LC–MS) in a targeted manner.

Results

Approximately 40% of the children in this study were OWO by age 5. Maternal OWO had a significant association with childhood OWO, both in term and preterm births. β-hydroxybutyryl-carnitine (C4-OH) levels were significantly and positively associated with child OWO among term births after adjustment for potential confounders and multiple-comparisons. Children born to OWO mothers in the top tertile C4-OH levels were at the highest risk of OWO: OR = 3.78 (95%CI: 2.47, 5.79) as compared with those born to non-OWO mothers in the lowest tertile (P for interaction of maternal OWO and C4-OH = 0.035). In a four-way decomposition of mediation/interaction analysis, we estimated that C4-OH levels explained about 27% (se = 0.08) of inter-generational OWO risk (P = 0.001). In contrast, these associations were not observed in preterm births.

Conclusions

In this U.S. urban low-income birth cohort, we provide further evidence of the inter-generational link of OWO and reveal the differential role of C4-OH in explaining the inter-generational obesity between term and preterm births. Further investigations are warranted to better understand and prevent the inter-generational transmission of OWO.

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References

  1. Zylke JW, Bauchner H. The unrelenting challenge of obesity. Jama. 2016;315:2277–8.

    Article  CAS  Google Scholar 

  2. Zylke JW, Bauchner H. Preventing obesity in children: a glimmer of hope. Jama. 2018;320:443–4.

    Article  Google Scholar 

  3. Barkin SL, Heerman WJ, Sommer EC, Martin NC, Buchowski MS, Schlundt D, et al. Effect of a behavioral intervention for underserved preschool-age children on change in body mass index: a randomized clinical trial. Jama. 2018;320:450–60.

    Article  Google Scholar 

  4. Paul IM, Savage JS, Anzman-Frasca S, Marini ME, Beiler JS, Hess LB, et al. Effect of a responsive parenting educational intervention on childhood weight outcomes at 3 years of age: the INSIGHT randomized clinical trial. Jama. 2018;320:461–8.

    Article  Google Scholar 

  5. Gluckman PD, Hanson MA, Cooper C, Thornburg KL. Effect of in utero and early-life conditions on adult health and disease. N Engl J Med. 2008;359:61–73.

    Article  CAS  Google Scholar 

  6. Whitaker RC, Dietz WH. Role of the prenatal environment in the development of obesity. J Pediatr. 1998;132:768–76.

    Article  CAS  Google Scholar 

  7. Levin BE, Govek E. Gestational obesity accentuates obesity in obesity-prone progeny. Am J Physiol. 1998;275(4 Pt 2):R1374–9.

    CAS  PubMed  Google Scholar 

  8. Kral JG, Biron S, Simard S, Hould FS, Lebel S, Marceau S, et al. Large maternal weight loss from obesity surgery prevents transmission of obesity to children who were followed for 2 to 18 years. Pediatrics. 2006;118:e1644–9.

    Article  Google Scholar 

  9. Hochner H, Friedlander Y, Calderon-Margalit R, Meiner V, Sagy Y, Avgil-Tsadok M, et al. Associations of maternal prepregnancy body mass index and gestational weight gain with adult offspring cardiometabolic risk factors: the Jerusalem Perinatal Family Follow-up Study. Circulation. 2012;125:1381–9.

    Article  CAS  Google Scholar 

  10. Lawlor DA, Fraser A, Lindsay RS, Ness A, Dabelea D, Catalano P, et al. Association of existing diabetes, gestational diabetes and glycosuria in pregnancy with macrosomia and offspring body mass index, waist and fat mass in later childhood: findings from a prospective pregnancy cohort. Diabetologia. 2010;53:89–97.

    Article  CAS  Google Scholar 

  11. Wang G, Hu FB, Mistry KB, Zhang C, Ren F, Huo Y, et al. Association between maternal prepregnancy body mass index and plasma folate concentrations with child metabolic health. JAMA pediatrics. 2016;170:e160845.

    Article  Google Scholar 

  12. Lawlor DA, Timpson NJ, Harbord RM, Leary S, Ness A, McCarthy MI, et al. Exploring the developmental overnutrition hypothesis using parental-offspring associations and FTO as an instrumental variable. PLoS Med. 2008;5:e33.

    Article  Google Scholar 

  13. Isganaitis E, Woo M, Ma H, Chen M, Kong W, Lytras A, et al. Developmental programming by maternal insulin resistance: hyperinsulinemia, glucose intolerance, and dysregulated lipid metabolism in male offspring of insulin-resistant mice. Diabetes. 2014;63:688–700.

    Article  CAS  Google Scholar 

  14. Kelley DE, He J, Menshikova EV, Ritov VB. Dysfunction of mitochondria in human skeletal muscle in type 2 diabetes. Diabetes. 2002;51:2944–50.

    Article  CAS  Google Scholar 

  15. Mihalik SJ, Goodpaster BH, Kelley DE, Chace DH, Vockley J, Toledo FG, et al. Increased levels of plasma acylcarnitines in obesity and type 2 diabetes and identification of a marker of glucolipotoxicity. Obesity. 2010;18:1695–700.

    Article  CAS  Google Scholar 

  16. Koves TR, Ussher JR, Noland RC, Slentz D, Mosedale M, Ilkayeva O, et al. Mitochondrial overload and incomplete fatty acid oxidation contribute to skeletal muscle insulin resistance. Cell Metab. 2008;7:45–56.

    Article  CAS  Google Scholar 

  17. Jacob S, Nodzenski M, Reisetter AC, Bain JR, Muehlbauer MJ, Stevens RD, et al. Targeted metabolomics demonstrates distinct and overlapping maternal metabolites associated with BMI, glucose, and insulin sensitivity during pregnancy across four ancestry groups. Diabetes Care. 2017;40:911–9.

    Article  CAS  Google Scholar 

  18. Wang G, Divall S, Radovick S, Paige D, Ning Y, Chen Z, et al. Preterm birth and random plasma insulin levels at birth and in early childhood. Jama. 2014;311:587–96.

    Article  CAS  Google Scholar 

  19. Hong X, Wang G, Liu X, Kumar R, Tsai HJ, Arguelles L, et al. Gene polymorphisms, breast-feeding, and development of food sensitization in early childhood. J Allergy Clin Immunol. 2011;128:374–81 e2.

    Article  CAS  Google Scholar 

  20. Wang X, Zuckerman B, Pearson C, Kaufman G, Chen C, Wang G, et al. Maternal cigarette smoking, metabolic gene polymorphism, and infant birth weight. Jama. 2002;287:195–202.

    Article  CAS  Google Scholar 

  21. National Center for Health Statistics. CDC growth charts. United States. 2000. http://www.cdc.gov/growthcharts/. Accessed 26 Nov 2013.

  22. Zhang S, Liu X, Brickman WJ, Christoffel KK, Zimmerman D, Tsai HJ, et al. Association of plasma leptin concentrations with adiposity measurements in rural Chinese adolescents. J Clin Endocrinol Metab. 2009;94:3497–504.

    Article  CAS  Google Scholar 

  23. Inoue M, Maehata E, Yano M, Taniyama M, Suzuki S. Correlation between the adiponectin-leptin ratio and parameters of insulin resistance in patients with type 2 diabetes. Metabolism. 2005;54:281–6.

    Article  CAS  Google Scholar 

  24. Ruiz-Canela M, Guasch-Ferre M, Toledo E, Clish CB, Razquin C, Liang L, et al. Plasma branched chain/aromatic amino acids, enriched Mediterranean diet and risk of type 2 diabetes: case-cohort study within the PREDIMED Trial. Diabetologia. 2018;61:1560–71.

    Article  CAS  Google Scholar 

  25. VanderWeele TJ. A unification of mediation and interaction: a 4-way decomposition. Epidemiology. 2014;25:749–61.

    Article  Google Scholar 

  26. Austin PC, Stuart EA. Estimating the effect of treatment on binary outcomes using full matching on the propensity score. Stat Methods Med Res. 2017;26:2505–25.

  27. Ryckman KK, Donovan BM, Fleener DK, Bedell B, Borowski KS. Pregnancy-related changes of amino acid and acylcarnitine concentrations: the impact of obesity. AJP Rep. 2016;6:e329–36.

    Article  Google Scholar 

  28. An J, Muoio DM, Shiota M, Fujimoto Y, Cline GW, Shulman GI, et al. Hepatic expression of malonyl-CoA decarboxylase reverses muscle, liver and whole-animal insulin resistance. Nat Med. 2004;10:268–74.

    Article  CAS  Google Scholar 

  29. Boden G, Jadali F, White J, Liang Y, Mozzoli M, Chen X, et al. Effects of fat on insulin-stimulated carbohydrate metabolism in normal men. J Clin Investig. 1991;88:960–6.

    Article  CAS  Google Scholar 

  30. Schooneman MG, Vaz FM, Houten SM, Soeters MR. Acylcarnitines: reflecting or inflicting insulin resistance? Diabetes. 2013;62:1–8.

    Article  CAS  Google Scholar 

  31. Bucci M, Borra R, Nagren K, Maggio R, Tuunanen H, Oikonen V, et al. Human obesity is characterized by defective fat storage and enhanced muscle fatty acid oxidation, and trimetazidine gradually counteracts these abnormalities. Am J Physiol Endocrinol Metab. 2011;301:E105–12.

    Article  CAS  Google Scholar 

  32. Lindsay KL, Hellmuth C, Uhl O, Buss C, Wadhwa PD, Koletzko B, et al. Longitudinal metabolomic profiling of amino acids and lipids across healthy pregnancy. PLoS ONE. 2015;10:e0145794.

    Article  Google Scholar 

  33. Ceners for Disease Contol and Prevention (CDC). Preterm birth. https://www.cdc.gov/reproductivehealth/maternalinfanthealth/pretermbirth.htm. Accessed 30 Aug 2018.

  34. Taveras EM, Gillman MW, Kleinman KP, Rich-Edwards JW, Rifas-Shiman SL. Reducing racial/ethnic disparities in childhood obesity: the role of early life risk factors. JAMA pediatrics. 2013;167:731–8.

    Article  Google Scholar 

  35. Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011-2012. Jama. 2014;311:806–14.

    Article  CAS  Google Scholar 

  36. Wang G, Johnson S, Gong Y, Polk S, Divall S, Radovick S, et al. Weight gain in infancy and overweight or obesity in childhood across the gestational spectrum: a prospective birth cohort study. Sci Rep. 2016;6:29867.

    Article  CAS  Google Scholar 

  37. Mankuta D, Elami-Suzin M, Elhayani A, Vinker S. Lipid profile in consecutive pregnancies. Lipids Health Dis. 2010;9:58.

    Article  Google Scholar 

  38. Pitkin RM, Connor WE, Lin DS. Cholesterol metabolism and placental transfer in the pregnant Rhesus monkey. J Clin Investig. 1972;51:2584–92.

    Article  CAS  Google Scholar 

  39. Lowe WL Jr., Bain JR, Nodzenski M, Reisetter AC, Muehlbauer MJ, Stevens RD, et al. Maternal BMI and glycemia impact the fetal metabolome. Diabetes Care. 2017;40:902–10.

    Article  CAS  Google Scholar 

Download references

Funding

This study is supported in part by the National Institutes of Health (NIH) grants (R01HD086013 and 2R01HD041702). The Boston Birth Cohort (the parent study) is supported in part by the Health Resources and Services Administration (HRSA) of the U.S. Department of Health and Human Services (HHS) under grant number R40MC27443 and UJ2MC31074. XH is partially supported by Hopkins Population Center (NICHD R24HD042854). CZ is supported by the intramural research program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development. The funders had no role in the design or conduct of the study; collection, management, analysis, or interpretation of the data; preparation, review, or approval of the article; or the decision to submit the article for publication. The content and conclusions contained in this article are those of the authors and should not be construed as the official position or policy of, nor should any endorsements be inferred by, HRSA, HHS, or the US Government. XW is the principal investigator of the Boston Birth Cohort, and has full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

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Author notes

  1. These authors contributed equally: Guoying Wang, Qi Sun, Liming Liang

Authors and Affiliations

  1. Department of Population, Family and Reproductive Health, Center on the Early Life Origins of Disease, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA

    Guoying Wang, Cuilin Zhang, Xiumei Hong, Yuelong Ji & Xiaobin Wang

  2. Departments of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Qi Sun

  3. Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA

    Qi Sun & Frank B. Hu

  4. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Liming Liang & Frank B. Hu

  5. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA

    Liming Liang

  6. Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA

    Clary Clash

  7. Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health and Human Development, National Institutes of Health, Bethesda, MD, USA

    Cuilin Zhang

  8. Department of Pediatrics, The Child Health Institute of New Jersey, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, NJ, USA

    Sally Radovick

  9. Department of Pediatrics, Boston University School of Medicine and Boston Medical Center, Boston, MA, USA

    Colleen Pearson & Barry Zuckerman

  10. Mary Ann & J. Milburn Smith Child Health Research, Outreach and Advocacy Center, Stanley Manne Children’s Research Institute, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA

    Tami R. Bartell

  11. Division of General Pediatrics & Adolescent Medicine, Department of Pediatrics, Johns Hopkins University School of Medicine, Baltimore, MD, USA

    Tina L. Cheng & Xiaobin Wang

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  1. Guoying Wang
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Correspondence to Frank B. Hu or Xiaobin Wang.

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Wang, G., Sun, Q., Liang, L. et al. Inter-generational link of obesity in term and preterm births: role of maternal plasma acylcarnitines. Int J Obes 43, 1967–1977 (2019). https://doi.org/10.1038/s41366-019-0417-x

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