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Prenatal environmental exposures that may influence β-cell function or insulin sensitivity in middle age

Published online by Cambridge University Press:  20 September 2010

H. S. Kahn ,
A. D. Stein  and
L. H. Lumey
H. S. Kahn*
Affiliation:
Division of Diabetes Translation, Centers for Disease Control and Prevention, Atlanta, Georgia, USA
A. D. Stein
Affiliation:
Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
L. H. Lumey
Affiliation:
Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
*
*Address for correspondence: Dr H. S. Kahn, Centers for Disease Control & Prevention – Division of Diabetes Translation, MS K-10, NCCDPHP 4770 Buford Highway, Atlanta, Georgia 30341, USA. (Email [email protected])
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Abstract

The associations between fetal environment and diabetes risk are likely mediated by the offspring’s diminished pancreatic β-cell function or reduced insulin sensitivity. Our ability to distinguish between these mechanisms is impeded by the lack of markers describing an individual’s gestational environment. Fingerprints, however, are permanently fixed in the first half of gestation, and increased values of a dermatoglyphic marker that contrasts fingerprint ridge counts between the thumbs and fifth fingers (Md15) have been linked to type 2 diabetes. Among 763 adults without known diabetes from the Dutch Hunger Winter Families Study, we tested the associations of Md15 with homeostatic assessment indices of β-cell function (HOMA-b) and insulin sensitivity (QUICKI). For either outcome index, linear regression models included terms for Md15 tertiles and for maternal history of diabetes as reported by each participant. All models were corrected for sibling pairs and adjusted for age, sex and famine exposures. Increased Md15 was associated with decreased HOMA-b (P = 0.03 for Md15 tertile 3 v. 1) but not with QUICKI. In contrast, maternal history of diabetes was associated with decreased QUICKI (P < 0.001) but not with HOMA-b. Birth weight (available for 520 participants) was positively associated with increased QUICKI (P = 0.04 for birth weight tertile 3 v. 1) but not with HOMA-b. Fingerprint Md15, maternal history of diabetes and birth weight may help to identify specific defects in the control of adult glucose metabolism. Research into the environment associated with Md15 variation may suggest prenatal strategies for optimizing β-cell function in adult life.

Keywords

dermatoglyphicsfetal programminghyperglycemiainsulin sensitivitypancreatic β cells
Type
Original Articles
Information
Journal of Developmental Origins of Health and Disease , Volume 1 , Issue 5 , October 2010 , pp. 300 - 309
Copyright
Copyright © Cambridge University Press and the International Society for Developmental Origins of Health and Disease 2010 This is the work of the U.S. Government and is not subject to copyright protection in the United States

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References

1. Kahn, HS, Graff, M, Stein, AD, Lumey, LH. A fingerprint marker from early gestation associated with diabetes in middle age: The Dutch Hunger Winter Families Study. Int J Epidemiol. 2009; 38, 101–109.CrossRefGoogle ScholarPubMed
2. Benazet, J-D, Zeller, R. Vertebrate limb development: moving from classical morphogen gradients to an integrated 4-dimensional patterning system. Cold Spring Harb Perspect Biol. 2009; 1, a001339.CrossRefGoogle Scholar
3. Kahn, HS, Graff, M, Stein, AD, et al. A fingerprint characteristic associated with the early prenatal environment. Am J Hum Biol. 2008; 20, 59–65.Google Scholar
4. Babler, WJ. Embryologic development of epidermal ridges and their configurations. Birth Defects. 1991; 27, 95–112.Google ScholarPubMed
5. King, PJ, Guasti, L, Laufer, E. Hedgehog signalling in endocrine development and disease. J Endocrinol. 2008; 198, 439–450.CrossRefGoogle ScholarPubMed
6. Oliver-Krasinski, JM, Stoffers, DA. On the origin of the beta cell. Genes Dev. 2008; 22, 1998–2021.CrossRefGoogle ScholarPubMed
7. Lau, J, Hebrok, M. Hedgehog signaling in pancreas epithelium regulates embryonic organ formation and adult β-cell function. Diabetes. 2010; 59, 1211–1221.CrossRefGoogle ScholarPubMed
8. Kahn, SE, Zraika, S, Utzschneider, KM, Hull, RL. The beta cell lesion in type 2 diabetes: there has to be a primary functional abnormality. Diabetologia. 2009; 52, 1003–1012.CrossRefGoogle ScholarPubMed
9. Fonseca, VA. Defining and characterizing the progression of type 2 diabetes. Diabetes Care. 2009; 32, S151–S156.CrossRefGoogle ScholarPubMed
10. Lorenzo, C, Wagenknecht, LE, D’Agostino, RB Jr, et al. Insulin resistance, beta-cell dysfunction, and conversion to type 2 diabetes in a multiethnic population: the insulin resistance atherosclerosis study. Diabetes Care. 2010; 33, 67–72.CrossRefGoogle Scholar
11. Dabelea, D, Hanson, RL, Lindsay, RS, et al. Intrauterine exposure to diabetes conveys risks for type 2 diabetes and obesity: a study of discordant sibships. Diabetes. 2000; 49, 2208–2211.CrossRefGoogle ScholarPubMed
12. Pettitt, DJ, Lawrence, JM, Beyer, J, et al. Association between maternal diabetes in utero and age at offspring’s diagnosis of type 2 diabetes. Diabetes Care. 2008; 31, 2126–2130.CrossRefGoogle ScholarPubMed
13. Carr, DB, Newton, KM, Utzschneider, KM, et al. Modestly elevated glucose levels during pregnancy are associated with a higher risk of future diabetes among women without gestational diabetes mellitus. Diabetes Care. 2008; 31, 1037–1039.CrossRefGoogle ScholarPubMed
14. Golden, SH, Bennett, WL, Baptist-Roberts, K, et al. Antepartum glucose tolerance test results as predictors of type 2 diabetes mellitus in women with a history of gestational diabetes mellitus: a systematic review. Gend Med. 2009; 6(Suppl. 1), 109–122.CrossRefGoogle ScholarPubMed
15. Lumey, LH, Stein, AD, Kahn, HS, et al. Cohort profile: The Dutch Hunger Winter Families Study. Int J Epidemiol. 2007; 36, 1196–1204.CrossRefGoogle ScholarPubMed
16. Penrose, LS. Memorandum on dermatoglyphic nomenclature. Birth Defects. 1968; 4, 1–13.Google Scholar
17. Loesch, DZ. Quantitative Dermatoglyphics: Classification, Genetics, and Pathology (Series eds. Roberts JAF, Carter CO, Motulsky AG), 1983; Oxford University Press, Oxford.Google Scholar
18. Stein, AD, Kahn, HS, Rundle, A, et al. Anthropometric measures in middle age after exposure to famine during gestation: evidence from the Dutch famine. Am J Clin Nutr. 2007; 85, 869–876.CrossRefGoogle ScholarPubMed
19. Chen, H, Sullivan, G, Quon, MJ. Assessing the predictive accuracy of QUICKI as a surrogate index for insulin sensitivity using a calibration model. Diabetes. 2005; 54, 1914–1925.CrossRefGoogle ScholarPubMed
20. Matthews, DR, Hosker, JP, Rudenski, AS, et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia. 1985; 28, 412–419.CrossRefGoogle ScholarPubMed
21. American Diabetes Association. Diagnosis and classification of diabetes mellitus. Diabetes Care. 2010; 33, S62–S69.CrossRefGoogle Scholar
22. Levy, JC, Matthews, DR, Hermans, MP. Correct homeostasis model assessment (HOMA) evaluation uses the computer program. Diabetes Care. 1998; 21, 2191–2192.Google Scholar
23. Wallace, TM, Levy, JC, Matthews, DR. Use and abuse of HOMA modeling. Diabetes Care. 2004; 27, 1487–1495.CrossRefGoogle ScholarPubMed
24. Lumey, LH, Van Poppel, FW. The Dutch famine of 1944-45: mortality and morbidity in past and present generations. Soc Hist Med. 1994; 7, 229–246.Google Scholar
25. Ravelli, GP, Stein, ZA, Susser, MW. Obesity in young men after famine exposure in utero and early infancy. New Engl J Med. 1976; 295, 349–353.CrossRefGoogle ScholarPubMed
26. Roseboom, TJ, van der Meulen, JH, Ravelli, AC, et al. Effects of prenatal exposure to the Dutch famine on adult disease in later life: an overview. Twin Res. 2001; 4, 293–298.CrossRefGoogle Scholar
27. Kucken, M, Newell, AC. Fingerprint formation. J Theoret Biol. 2005; 235, 71–83.Google Scholar
28. Florez, J. Newly identified loci highlight beta cell dysfunction as a key cause of type 2 diabetes: where are the insulin resistance genes? Diabetologia. 2008; 51, 1100–1110.CrossRefGoogle ScholarPubMed
29. Medland, SE, Loesch, DZ, Mdzewski, B, et al. Linkage analysis of a model quantitative trait in humans: finger ridge count shows significant multivariate linkage to 5q14.1. PLoS Genet. 2007; 3, 1736–1744.CrossRefGoogle Scholar
30. Vaiserman, AM, Carstensen, B, Voitenko, VP, et al. Seasonality of birth in children and young adults (0-29 years) with type 1 diabetes in Ukraine. Diabetologia. 2007; 50, 32–35.CrossRefGoogle Scholar
31. Kahn, HS, Morgan, TM, Case, LD, et al. Association of type 1 diabetes with month of birth among U.S. youth: The SEARCH for Diabetes in Youth Study. Diabetes Care. 2009; 32, 2010–2015.CrossRefGoogle ScholarPubMed
32. Vaiserman, A, Khalangot, M, Carstensen, B, et al. Seasonality of birth in adult type 2 diabetic patients in three Ukrainian regions. Diabetologia. 2009; 52, 2665–2667.CrossRefGoogle ScholarPubMed
33. Willis, JA, Scott, RS, Darlow, BA, et al. Seasonality of birth and onset of clinical disease in children and adolescents (0-19 years) with type 1 diabetes mellitus in Canterbury, New Zealand. J Pediatr Endocrinol Metab. 2002; 15, 645–647.CrossRefGoogle ScholarPubMed
34. Stein, AD, Zybert, PA, van de Bor, M, Lumey, LH. Intrauterine famine exposure and body proportions at birth: the Dutch Hunger Winter. Int J Epidemiol. 2004; 33, 831–836.CrossRefGoogle ScholarPubMed
35. Jensen, CB, Storgaard, H, Dela, F, et al. Early differential defects of insulin secretion and action in 19-year-old Caucasian men who had low birth weight. Diabetes. 2002; 51, 1271–1280.CrossRefGoogle ScholarPubMed
36. de Rooij, SR, Painter, RC, Phillips, DIW, et al. Impaired insulin secretion after prenatal exposure to the Dutch famine. Diabetes Care. 2006; 29, 1897–1901.Google Scholar
37. Kahn, HS, Cheng, YJ, Thompson, TJ, Imperatore, G, Gregg, EW. Two risk-scoring systems for predicting incident diabetes mellitus in U.S. adults age 45 to 64 years. Ann Intern Med. 2009; 150, 741–751.Google Scholar
38. van ‘t Riet, E, Dekker, JM, Sun, Q, et al. Role of adiposity and lifestyle in the relationship between family history of diabetes and 20-year incidence of type 2 diabetes in U.S. women. Diabetes Care. 2010; 33, 763–767.CrossRefGoogle ScholarPubMed
39. Kong, A, Steinthorsdottir, V, Masson, G, et al. Parental origin of sequence variants associated with complex diseases. Nature. 2009; 462, 868–874.CrossRefGoogle ScholarPubMed
40. Lampl, M, Jeanty, P. Exposure to maternal diabetes is associated with altered fetal growth patterns: a hypothesis regarding metabolic allocation to growth under hyperglycemic-hypoxemic conditions. Am J Hum Biol. 2004; 16, 237–263.CrossRefGoogle ScholarPubMed
41. Vaarasmaki, M, Pouta, A, Elliot, P, et al. Adolescent manifestations of metabolic syndrome among children born to women with gestational diabetes in a general-population birth cohort. Am J Epidemiol. 2009; 169, 1209–1215.CrossRefGoogle Scholar
42. Riskin-Mashiah, S, Younes, G, Damti, A, Auslander, R. First trimester fasting hyperglycemia and adverse pregnancy outcomes. Diabetes Care. 2009; 32, 1639–1643.CrossRefGoogle ScholarPubMed
43. The HAPO Study Cooperative Research Group. Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study: associations with neonatal anthropometrics. Diabetes. 2009; 58, 453–459.CrossRefGoogle Scholar
44. Lawlor, DA, Fraser, A, Lindsay, RS, 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.CrossRefGoogle ScholarPubMed
45. McKeigue, PM, Lithell, HO, Leon, DA. Glucose tolerance and resistance to insulin-stimulated glucose uptake in men aged 70 years in relation to size at birth. Diabetologia. 1998; 41, 1133–1138.CrossRefGoogle ScholarPubMed
46. Bouhours-Nouet, N, Dufresne, S, de Casson, FB, et al. High birth weight and early postnatal weight gain protect obese children and adolescents from truncal adiposity and insulin resistance: metabolically healthy but obese subjects? Diabetes Care. 2008; 31, 1031–1036.CrossRefGoogle ScholarPubMed
47. Monrad, RN, Grunnet, LG, Rasmussen, EL, et al. Age-dependent nongenetic influences of birth weight and adult body fat on insulin sensitivity in twins. J Clin Endocrinol Metab. 2009; 94, 2394–2399.Google Scholar
48. Gillman, MW. Epidemiological challenges in studying the fetal origins of adult chronic disease. Int J Epidemiol. 2002; 31, 294–299.CrossRefGoogle ScholarPubMed
49. Wells, J. Commentary: games people play--birthweight. Int J Epidemiol. 2006; 35, 277–279.CrossRefGoogle ScholarPubMed
50. Staten, MA, Stern, MP, Miller, WG, Steffes, MW, Campbell, SE. Insulin assay standardization: leading to measures of insulin sensitivity and secretion for practical clinical care. Diabetes Care. 2010; 33, 205–206.CrossRefGoogle ScholarPubMed
51. Smith, RJ, Nathan, DM, Arslanian, SA, et al. Individualizing therapies in type 2 diabetes mellitus based on patient characteristics: what we know and what we need to know. J Clin Endocrinol Metab. 2010; 95, 1566–1574.CrossRefGoogle ScholarPubMed