Mendelian randomization supports causality between maternal hyperglycemia and epigenetic regulation of leptin gene in newborns

Epigenetics

Volumn 10, Issue 4, 2015, Pages 342-351

  Allard, C ^a   Desgagne V ^b,d   Patenaude, J ^a   Lacroix, M ^a   Guillemette, L ^a   Battista, M C ^a,c   Doyon, M ^c   Menard J ^c   Ardilouze, J L ^a,c   Perron, P ^a,c   Bouchard, L ^b,c,d   Hivert, M F ^a,c,e,f  

^a UNIVERSITÉ DE SHERBROOKE   (Canada)

^b UNIVERSITY OF SHERBROOKE   (Canada)

^c CENTRE HOSPITALIER UNIVERSITAIRE DE SHERBROOKE   (Canada)

^d CHICOUTIMI HOSPITAL   (Canada)

^e HARVARD MEDICAL SCHOOL   (United States)

^f MASSACHUSETTS GENERAL HOSPITAL   (United States)

Author keywords

: DNA methylation; Fetal programming; Gestational diabetes; Glycemia; Leptin; Mendelian randomization; Obesity; Pregnancy

Indexed keywords

LEPTIN; GLUCOSE;

ADULT; ALLELE; ARTICLE; BLOOD PRESSURE; COHORT ANALYSIS; CPG ISLAND; DISEASE ASSOCIATION; DNA METHYLATION; EPIGENETIC REGULATION; EPIGENETICS; FEMALE; GENETIC RISK; GENOTYPING TECHNIQUE; GLUCOSE BLOOD LEVEL; HUMAN; HYPERGLYCEMIA; MATERNAL DISEASE; MATERNAL HYPERGLYCEMIA; MATRIX ASSISTED LASER DESORPTION IONIZATION TIME OF FLIGHT MASS SPECTROMETRY; MENDELIAN RANDOMIZATION ANALYSIS; MULTIDIMENSIONAL SCALING; OBESITY; ORAL GLUCOSE TOLERANCE TEST; POLYMERASE CHAIN REACTION; PROGENY; PROSPECTIVE STUDY; FETOMATERNAL TRANSFUSION; GENE EXPRESSION REGULATION; GENETIC EPIGENESIS; GENETICS; MALE; METABOLISM; NEWBORN; PREGNANCY; PROCEDURES;

ANIMALIA;

ADULT; COHORT STUDIES; DNA METHYLATION; EPIGENESIS, GENETIC; FEMALE; GENE EXPRESSION REGULATION; GLUCOSE; HUMANS; HYPERGLYCEMIA; INFANT, NEWBORN; LEPTIN; MALE; MATERNAL-FETAL EXCHANGE; MENDELIAN RANDOMIZATION ANALYSIS; PREGNANCY;

EID: 84927740135     PISSN: 15592294     EISSN: 15592308     Source Type: Journal    
DOI: 10.1080/15592294.2015.1029700     Document Type: Article

References (57)

1. HAPO Study Cooperative Research Group. Hyperglycemia and adverse pregnancy outcomes. N Engl J Med 2008; 358:1991-2002; PMID:18463375; http://dx.doi.org/10.1056/NEJMoa0707943
2. Wright CS, Rifas-Shiman SL, Rich-Edwards JW, Taveras EM, Gillman MW, Oken E. Intrauterine exposure to gestational diabetes, child adiposity, and blood pressure. Am J Hypertens 2009; 22:215-20; PMID:19023272; http://dx.doi.org/10.1038/ajh.2008.326
3. Franks PW, Looker HC, Kobes S, Touger L, Tataranni PA, Hanson RL, KnowlerWC. Gestational glucose tolerance and risk of type 2 diabetes in young Pima Indian offspring. Diabetes 2006; 55:460-5; PMID:16443781; http://dx.doi.org/10.2337/diabetes.55.02.06.db05-0823
4. Catalano PM, McIntyre HD, Cruickshank JK, McCance DR, Dyer AR, Metzger BE, Lowe LP, Trimble ER, Coustan DR, Hadden DR, et al. The hyperglycemia and adverse pregnancy outcome study: associations of GDM and obesity with pregnancy outcomes. Diabetes Care 2012; 35:780-6; PMID:22357187; http://dx.doi.org/10.2337/dc11-1790
5. Dabelea D, Mayer-Davis EJ, Lamichhane AP, D’Agostino Jr RB, Liese AD, Vehik KS, Narayan KM, Zeitler P, Hamman RF. Association of intrauterine exposure to maternal diabetes and obesity with type 2 diabetes in youth: the SEARCH Case-Control Study. Diabetes Care 2008; 31:1422-6; PMID:18375420; http://dx.doi.org/10.2337/dc07-2417
6. Hillier TA, Pedula KL, Schmidt MM, Mullen JA, Charles MA, Pettitt DJ. Childhood obesity and metabolic imprinting: the ongoing effects of maternal hyperglycemia. Diabetes Care 2007; 30:2287-92; PMID:17519427; http://dx.doi.org/10.2337/dc06-2361
7. Tam WH, Ma RC, Yang X, Li AM, Ko GT, Kong AP, Lao TT, Chan MH, Lam CW, Chan JC. Glucose intolerance and cardiometabolic risk in adolescents exposed to maternal gestational diabetes: a 15-year follow-up study. Diabetes Care 2010; 33:1382-4; PMID:20215448; http://dx.doi.org/10.2337/dc09-2343
8. Dabelea D, Hanson RL, Lindsay RS, Pettitt DJ, Imperatore G, Gabir MM, Roumain J, Bennett PH, Knowler WC. Intrauterine exposure to diabetes conveys risks for type 2 diabetes and obesity: a study of discordant sibships. Diabetes 2000; 49:2208-11; PMID:11118027; http://dx.doi.org/10.2337/diabetes.49.12.2208
9. Cedar H, Bergman Y. Linking DNA methylation and histone modification: patterns and paradigms. Nat Rev Genet 2009; 10:295-304; PMID:19308066; http://dx.doi.org/10.1038/nrg2540
10. Barker DJP. Intrauterine programming of adult disease. Mol Med Today 1995; 1:418-23; PMID:9415190; http://dx.doi.org/10.1016/S1357-4310(95)90793-9
11. Hales CN, Barker DJ. The thrifty phenotype hypothesis. Br Med Bull 2001; 60:5-20; PMID:11809615; http://dx.doi.org/10.1093/bmb/60.1.5
12. O’Rahilly S. 20 Years of leptin: what we know and what the future holds. J Endocrinol 2014; 223:E1-3; PMID:25143632; http://dx.doi.org/10.1530/JOE-14-
13. Melzner I, Scott V, Dorsch K, Fischer P, Wabitsch M, Bruderlein S, Hasel C, Moller P. Leptin gene expression in human preadipocytes is switched on by maturationinduced demethylation of distinct CpGs in its proximal promoter. J Biol Chem 2002; 277:45420-7; PMID:12213831; http://dx.doi.org/10.1074/jbc.M208511200
14. Bouyer K, Simerly RB. Neonatal leptin exposure specifies innervation of presympathetic hypothalamic neurons and improves the metabolic status of leptindeficient mice. J Neurosci 2013; 33:840-51; PMID:23303959; http://dx.doi.org/10.1523/JNEUROSCI.3215-12.2013
15. Itoh H, Yura S, Sagawa N, Kanayama N, Konihi I. Neonatal exposure to leptin reduces glucose tolerance in adult mice. Acta Physiol 2011; 202:159-64; PMID:21352506; http://dx.doi.org/10.1111/j.1748-1716.2011.02268.x
16. Li G, Zhang W, Baker MS, Laritsky E, Mattan-Hung N, Yu D, Kunde-Ramamoorthy G, Simerly RB, Chen R, Shen L, et al. Major epigenetic development distinguishing neuronal and non-Neuronal cells occurs postnatally in the murine hypothalamus. Hum Mol Genet 2014; 23:1579-90; PMID:24186871; http://dx.doi.org/10.1093/hmg/ddt548
17. Mantzoros CS, Rifas-Shiman SL, Williams CJ, Fargnoli JL, Kelesidis T, Gillman MW. Cord blood leptin and adiponectin as predictors of adiposity in children at 3 years of age: a prospective cohort study. Pediatrics 2009; 123:682-9; PMID:19171638; http://dx.doi.org/10.1542/peds.2008-0343
18. Bouchard L, Thibault S, Guay SP, Santure M, Monpetit A, St-Pierre J, Perron P, Brisson D. Leptin gene epigenetic adaptation to impaired glucose metabolism during pregnancy. Diabetes Care 2010; 33:2436-41; PMID:20724651; http://dx.doi.org/10.2337/dc10-1024;10.2337/dc10-1024
19. Lesseur C, Armstrong DA, Paquette AG, Li Z, Padbury JF,Marsit CJ. Maternal obesity and gestational diabetes are associated with placental leptin DNA methylation. Am J Obstet Gynecol 2014; 211:654.e1-9; PMID:24954653; http://dx.doi.org/10.1016/j.ajog.2014.06.037
20. Relton CL, Davey Smith G. Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease. Int J Epidemiol 2012; 41:161-76; PMID:22422451; http://dx.doi.org/10.1093/ije/dyr233
21. Palmer TM, Lawlor DA, Harbord RM, Sheehan NA, Tobias JH, Timpson NJ, Davey Smith G, Sterne JA. Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res 2012; 21:223-42; PMID:21216802; http://dx.doi.org/10.1177/0962280210394459
22. Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, Jackson AU, Wheeler E, Glazer NL, Bouatia-Naji N, Gloyn AL, et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet 2010; 42:105-16; PMID:20081858; http://dx.doi.org/10.1038/ng.520
23. Hayes MG, Urbanek M, Hivert MF, Armstrong LL, Morrison J, Guo C, Lowe LP, Scheftner DA, Pluzhnikov A, Levine DM, et al. Identification of HKDC1 and BACE2 as genes influencing glycemic traits during pregnancy through genome-wide association studies. Diabetes 2013; 62:3282-91; PMID:23903356; http://dx.doi.org/10.2337/db12-1692
24. Manning AK, Hivert MF, Scott RA, Grimsby JL, Bouatia-Naji N, Chen H, Rybin D, Liu C-T, Bielak LF, Prokopenko I, et al. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat Genet 2012; 44:659-69; PMID:22581228; http://dx.doi.org/10.1038/ng.2274
25. Scott RA, Lagou V, Welch RP, Wheeler E, Montasser ME, Luan J, Mägi R, Strawbridge RJ, Rehnberg E, Gustafsson S, et al. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet 2012; 44:991-1005; PMID:22885924; http://dx.doi.org/10.1038/ng.2385
26. Kang H, Zhang A, Cai TT, Small DS. Instrumental variables estimation with some invalid instruments and its application to Mendelian randomization. J Am Statist Assoc 2015; in press.
27. Jahan S, Ahmed CM, Zinnat R, Hasan Z, Habib SH, Saha S, Ali L. Influence of maternal diabetes on serum leptinemic and insulinemic status of the offspring: a case study of selected patients in a tertiary care hospital in Bangladesh. Diabetes Metab Syndr Clin Res Rev 2011; 5:33-7; PMID:22814839; http://dx.doi.org/10.1016/j.dsx.2010.10.001
28. Lawlor DA, West J, Fairley L, Nelson SM, Bhopal RS, Tuffnell D, Freeman DJ, Wright J, Whitelaw DC, Sattar N. Pregnancy glycaemia and cord-blood levels of insulin and leptin in Pakistani and white British mother–offspring pairs: findings from a prospective pregnancy cohort. Diabetologia 2014; 57:2492-500; PMID:25273345; http://dx.doi.org/10.1007/s00125-014-3386-6
29. Luo Z-C, Nuyt A-M, Delvin E, Fraser WD, Julien P, Audibert F, Girard I, Shatenstein B, Deal C, Grenier E, et al. Maternal and fetal leptin, adiponectin levels and associations with fetal insulin sensitivity. Obesity 2013; 21:210-6; PMID:23505188; http://dx.doi.org/10.1002/oby.20250
30. Willer CJ, Sanna S, Jackson AU, Scuteri A, Bonnycastle LL, Clarke R, Heath SC, Timpson NJ, Najjar SS, Stringham HM. Newly identified loci that influence lipid concentrations and risk of coronary artery disease. Nat Genet 2008; 40:161-9; PMID:18193043; http://dx.doi.org/10.1038/ng.76
31. Saxena R, Hivert M-F, Langenberg C, Tanaka T, Pankow JS, Vollenweider P, Lyssenko V, Bouatia-Naji N, Dupuis J, Jackson AU. Genetic variation in GIPR influences the glucose and insulin responses to an oral glucose challenge. Nat Genet 2010; 42:142-8; PMID:20081857; http://dx.doi.org/10.1038/ng.521
32. Armstrong DA, Lesseur C, Conradt E, Lester BM, Marsit CJ. Global and gene-specific DNA methylation across multiple tissues in early infancy: implications for children’s health research. FASEB J 2014; 28:2088-97; PMID:24478308; http://dx.doi.org/10.1096/fj.13-238402
33. Houde AA, Ruchat SM, Allard C, Perron P, Baillargeon JP, St-Pierre J, Gaudet D, Brisson D, Hivert MF, Bouchard L. Epigenomic fetal programming: identifying genomic sites differentially methylated after exposure to maternal gestational diabetes and responsive to its treatment. Poster session presented at: 63rd Annual Meeting of the American Society of Human Genetics; 2013 Oct 22–26; Boston, MA
34. Lesseur C, Armstrong DA, Paquette AG, Koestler DC, Padbury JF, Marsit CJ. Tissue-specific Leptin promoter DNA methylation is associated with maternal and infant perinatal factors. Mol Cell Endocrinol 2013; 381:160-7; PMID:23911897; http://dx.doi.org/10.1016/j.mce.2013.07.024
35. Lillycrop KA, Burdge GC. Epigenetic changes in early life and future risk of obesity. Int J Obes 2010; 35:72-83; PMID:20548303; http://dx.doi.org/10.1038/ijo.2010.122
36. Saffery R, Novakovic B. Epigenetics as the mediator of fetal programming of adult onset disease: what is the evidence? Acta Obstet Gynecol Scand 2014; 93:1090-8; PMID:24835110; http://dx.doi.org/10.1111/aogs.12431
37. Tobi EW, Lumey LH, Talens RP, Kremer D, Putter H, Stein AD, Slagboom PE, Heijmans BT. DNA methylation differences after exposure to prenatal famine are common and timing-and sex-specific. Hum Mol Genet 2009; 18:4046-53; PMID:19656776; http://dx.doi.org/10.1093/hmg/ddp353
38. Obermann-Borst SA, Eilers PHC, Tobi EW, de Jong FH, Slagboom PE, Heijmans BT, Steegers-Theunissen RPM. Duration of breastfeeding and gender are associated with methylation of the LEPTIN gene in very young children. Pediatr Res 2013; 74:344-9; PMID:23884163; http://dx.doi.org/10.1038/pr.2013.95
39. García-Cardona MC, Huang F, García-Vivas JM, Lopez-Camarillo C, Del Rio Navarro BE, Olivos EN, Hong-Chong E, Bolaños-Jiménez F, Marchat LA. DNA methylation of leptin and adiponectin promoters in children is reduced by the combined presence of obesity and insulin resistance. Int J Obes 2014; 38:1457-65; PMID:24549138; http://dx.doi.org/10.1038/ijo.2014.30
40. Bouret SG, Draper SJ, Simerly RB. Trophic action of leptin on hypothalamic neurons that regulate feeding. Science 2004; 304:108-10; PMID:15064420; http://dx.doi.org/10.1126/science.1095004
41. Li M, Sloboda DM, Vickers MH. Maternal obesity and developmental programming of metabolic disorders in offspring: evidence from animal models. Exp Diabetes Res 2011; 2011:592408; PMID:21969822; http://dx.doi.org/10.1155/2011/592408
42. Khulan B, Cooper WN, Skinner BM, Bauer J, Owens S, Prentice AM, Belteki G, Constancia M, Dunger D, Affara NA. Periconceptional maternal micronutrient supplementation is associated with widespread gender related changes in the epigenome: a study of a unique resource in the Gambia. Hum Mol Genet 2012; 21:2086-101; PMID:22307237; http://dx.doi.org/10.1093/hmg/dds026
43. Voight BF, Peloso GM, Orho-Melander M, Frikke-Schmidt R, Barbalic M, Jensen MK, Hindy G, H_olm H, Ding EL, Johnson T, et al. Plasma HDL cholesterol and risk of myocardial infarction: a mendelian randomisation study. Lancet 2012; 380:572-80; PMID:22607825; http://dx.doi.org/10.1016/S0140-6736(12)60312-2
44. International Association of Diabetes and Pregnancy Study Groups Consensus Panel, Metzger BE, Gabbe SG, Persson B, Buchanan TA, Catalano PM, Damm P, Dyer AR, de Leiva A, Hod M, et al. International association of diabetes and pregnancy study groups recommendations on the diagnosis and classification of hyperglycemia in pregnancy. Diabetes Care 2010; 33:676-82; PMID:20190296; http://dx.doi.org/10.2337/dc09-1848
45. El Hajj N, Pliushch G, Schneider E, Dittrich M, Muller T, Korenkov M, Aretz M, Zechner U, Lehnen H, Haaf T. Metabolic programming of MEST DNA methylation by intrauterine exposure to gestational diabetes mellitus. Diabetes 2013; 62:1320-8; PMID:23209187; http://dx.doi.org/10.2337/db12-0289
46. Canadian Diabetes Association Clinical Practice Guidelines Expert Committee. Canadian Diabetes Association 2008 clinical practice guidelines for the prevention and management of diabetes in Canada. CanJDiabetes 2008; 32:S1-201
47. Ehrich M, Bocker S, van den Boom D. Multiplexed discovery of sequence polymorphisms using base-specific cleavage and MALDI-TOF MS. Nucleic Acids Res 2005; 33:e38; PMID:15731331; http://dx.doi.org/10.1093/nar/gni038
48. Chen Y, Lemire M, Choufani S, Butcher DT, Grafodatskaya D, Zanke BW, Gallinger S, Hudson TJ, Weksberg R. Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray. Epigenetics 2013; 8:203-9; PMID:23314698; http://dx.doi.org/10.4161/epi.23470
49. Vaškú JAB, Vaškú A, Dostálová Z, Bienert P. Association of leptin genetic polymorphism -2548 G/A with gestational diabetes mellitus. Genes Nutr 2006; 1:117-23; PMID:18850205; http://dx.doi.org/10.1007/BF02829953
50. Lawlor DA, Harbord RM, Sterne JAC, Timpson N, Davey Smith G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med 2008; 27:1133-63; PMID:17886233; http://dx.doi.org/10.1002/sim.3034
51. Angrist JD, Imbens GW. Two-stage least squares estimation of average causal effects in models with variable treatment intensity. J Am Stat Assoc 1995; 90:431-42; http://dx.doi.org/10.1080/01621459.1995.10476535
52. R Core Team. R: A language and environment for statistical computing. Version 3.1.2. Vienna, Austria: R Foundation for Statistical Computing; 2014.
53. Fox J, Nie Z, Byrnes J. Sem: structural equation models. R package version 3.1-5. 2014.
54. Hastie T, Efron B. lars: Least angle regression, lasso and forward stagewise. R package version 1.2. 2013.
55. Kang H. sisVIVE: Some invalid some valid instrumental variables estimator. R package version 1.0. 2014; http://CRAN.R-project.org/package=sisVIVE
56. Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, Irizarry RA. Minfi: a flexible and comprehensive Bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics 2014; 30:1363-9; PMID:24478339; http://dx.doi.org/10.1093/bioinformatics/btu049
57. Pidsley R, Wong CC, Volta M, Lunnon K, Mill J, Schalkwyk LC. A data-driven approach to preprocessing Illumina 450K methylation array data. BMC genomics 2013; 14:293; PMID:23631413; http://dx.doi.org/10.1186/1471-2164-14-293