THE FIRST NINE MONTHS AND CHILDHOOD OBESITY. Deborah A Lawlor MRC Integrative Epidemiology Unit

Transcription

1 THE FIRST NINE MONTHS AND CHILDHOOD OBESITY Deborah A Lawlor MRC Integrative Epidemiology Unit d.a.lawlor@bristol.ac.uk

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3 Sample size (N of children) <1000 (N=12) (N=28) ,999 (N=13) 20, ,000 (N=3) Number: Cohorts (%) Number: Participants (%) Participants / Cohort West 15 (25) 93,914 (16.2) 6,262 North 25 (42) 424,702 (73.4) 16,988 [9,769] South 11 (18) 15,105 (2.6) 1,373 East 7 (12) 42,229 (7.3) 6,032 Mixed 2 (3) 3,000 (0.5) 1,500 Total ,950

4 risk of HDP Delayed / poorer ANC Obesity /overweight in Pregnancy risk of GDM risk of still birth / miscarriage risk of congenital anomalies risk of LGA, greater fatness at birth, shoulder dystocia, difficult labour difficulty breast feeding risk of later overweight and obesity risk of later CVD, T2DM, etc.

5 Intergenerational cycling of obesity and diabetes

6 Mendelian randomization study of causal effects of maternal exposures on birthweight PRELIMINARY FINDINGS; NOT FOR CITATION OR CIRCULATION Tyrell J, Freathy R, Frayling T, Lawlor DA, EAGLE 2014

7 Association of gestational diabetes with offspring adiposity Evidence from Pima Indians Gestational diabetes associated with increased mean BMI and odds of obesity in offspring at least up to age 20s Sibling and parental comparison study suggests intrauterine effects play some part Evidence from non-pima populations Few studies Inconsistent results

8 Mean BMI (kg/m2) Pima-Indians: mean BMI in siblings by exposure to diabetic intrauterine environment Siblings not exposed to diabetes in utero Siblings exposed to diabetes in utero Age Mean sibling BMI difference by parental diabetes status at time of pregnancy: Mothers: 2.6 (95%CI: 0.9, 4.3) kg/m 2, P = N = 52 families & 183 siblings Dabelea et al. Diabetes 2000; 49: 2208-

9 Mean BMI (kg/m2) Pima-Indians: mean BMI in siblings by exposure to diabetic intrauterine environment Siblings not exposed to diabetes in utero Siblings exposed to diabetes in utero Age Mean sibling BMI difference by parental diabetes status at time of pregnancy: Mothers: 2.6 (95%CI: 0.9, 4.3) kg/m 2, P = Fathers: 0.4 (95%CI: -0.9, +1.7) kg/m 2, P = 0.50 N = 52 families & 183 siblings Dabelea et al. Diabetes 2000; 49: 2208-

10 OR obesity US population: Odds of obesity by maternal gestational diabetes Without adjustment for maternal BMI With adjustment for maternal BMI N = maternal-offspring pairs, with 465 cases gestational diabetes Gillman et al., Pediatrics 2003;111:e221-e226

11 OR obesity UK population: odds of offspring obesity by maternal gestational diabetes and glycosuria 3.0 No maternal BMI adjust. With maternal BMI adjust. No maternal BMI adjust. With maternal BMI adjust Gestational diabetes N = 40/6854 Gestational glycosuria N = 232/6854 Lawlor et al. Diabetologia 2009

12 Mean difference in BMI at age 18 years by maternal pregnancy exposures: sibling study of 280,866 singleton born Swedish men from 248, 293 families Within brothers Between unrelated men P-value for difference Maternal diabetes in pregnancy (yes versus no) 0.94 (0.35, 1.52) 0.87 (0.68, 1.07) 0.87 Lawlor DA, Lichtenstein P, Långström N. Circulation 2011

13 Exposure to extreme obese intrauterine environment and offspring obesity: sibling comparison N = 172 children from 133 families. Age offspring 2-18yrs P = Kral et al. Pediatrics 2006;118:e1644-

14 Age- and sex-adjusted offspring BMI Age- and sex-adjusted offspring BMI Offspring BMI according to deciles of maternal and paternal BMI (N = 12,183). Offspring age = 6 years Age-adjusted maternal BMI deciles Patel R, et al. PLoS One Age-adjusted paternal BMI deciles

15 Mendelian randomisation & parental comparisons (negative control study). Offspring Age = 12 Maternal adiposity Maternal FTO Offspring FTO Offspring adiposity Confounders, e.g social class, diet, physical activity Paternal FTO Paternal adiposity Lawlor et al. PLoS Med 2008

16 Results: Parental comparison Difference in outcome per SD parental BMI (95%CI) P Mother s Father s Fat mass (z-score) 0.25 (0.22, 0.27) 0.13 (0.11, 0.15) < Lean mass (z-score) 0.10 (0.08, 0.12) 0.08 (0.06, 0.10) 0.31 Adjusted for offspring sex, age, height & puberty; parental SEP, education, smoking & maternal parity & mutually adjusted for each parents BMI

17 Results: Sensitivity analyses for non-paternity Assumed nonpaternity (%) Coefficient for mother s BMI Coefficient for father s BMI P for difference in coefficients < < <

18 Results: IV analyses Change in total offspring fat mass per SD mothers BMI (95%CI) P OLS IV Fat mass (z-score) 0.26 (0.23, 0.29) (-0.56, 0.41) 0.17 OLS: Ordinary Least Squares (conventional) regression; IV: Instrumental variable analysis, instrumental variable = mothers FTO controlling for offspring FTO NB: OLS adjusted as in results 1, but slightly fewer participants included here

19 Median total fat mass at age 9 (grams) Results: graphical representation of IV analyses Offspring FTO genotype 9000 TT AT AA TT AT TT AT AA AT AA Maternal FTO genotype

20 Results: MV and IV analyses, using 32 SNPs in weighted allele score. Preliminary results (NOT FOR CITATION OR CIRCULATION) THANKS to Rebecca Richmond Offspring outcome Mean difference in outcome (z-score) per 1SD greater maternal BMI MV analyses IV analyses BMI age (0.28, 0.33) 0.01 (-0.23, 0.25) 0.01 DXA fat age (0.23, 0.27) 0.09 (-0.12, 0.31) 0.1 BMI age (0.32, 0.37) 0.00 (-0.25, 0.24) DXA fat age (0.27, 0.31) 0.00 (-0.23, 0.22) BMI age (0.33, 0.38) (-0.29, 0.21) DXA fat age (0.28, 0.33) 0.04 (-0.19, 0.28) 0.03 BMI age (0.34, 0.40) (-0.34, 0.19) DXA fat age (0.27, 0.33) (-0.36, 0.20) P-difference IV versus MV result

21 Mean difference in BMI at age 18 years by maternal pregnancy exposures: sibling study of 280,866 singleton born Swedish men from 248, 293 families Within brothers Between unrelated men P-value for difference Maternal diabetes in pregnancy (yes versus no) Maternal prepregnancy BMI (per 1kg) 0.94 (0.35, 1.52) 0.87 (0.68, 1.07) (-0.07, -0.01) 0.32 (0.31, 0.32) < Lawlor DA, Lichtenstein P, Långström N. Circulation 2011

22 Gestational weight gain and offspring adiposity At least 20 studies Mostly in European origin populations 19 show positive association; 1 null Most use IOM categories of GWG Most have relatively crude measurements of GWG two measures, with one or both self-report

23 ALSPAC Mothers and offspring enrolled in the Avon Longitudinal Study of Parents and Children, a population-based birth cohort study that recruited 14,541 pregnant women resident in Avon, UK with expected dates of delivery 1 st April 1991 to 31 st December 1992 Gestational weight available for 12,484 mothers; of whom12,449 had a term pregnancy and offspring who survived 1 year.

24 Statistical methods 1. Categorise women according to IOM categories; using pre-pregnancy weight and highest gestational weight 2. Use all of the available repeat ANC weight measurements Median (IQR): 10 (8, 11) MLwiN - linear spline random effects model with two knots (fractional polynomials to identify position of knots)

25 IoM recommendations Pre-pregnancy BMI Underweight (< 18.5kg/m 2 ) Normal weight ( kg/m 2 ) Overweight ( kg/m 2 ) Obese ( 30kg/m 2 ) IoM recommendations Actual results from a UK pregnancy cohort who were pregnant between 1991 and 1993* Recommende Predicted mean Mean (SD) Mean rate (SD) of Prevalence Prevalence d weight gain rate of weight absolute weight gain in above below per BMI gain in 2 nd and weight gain 2 nd and 3 rd recommended recommended category (kg) 3 rd trimester for trimesters (%) (%) these (kg/week) recommendation s (kg/week) (4.1) 0.54 (0.14) (4.3) 0.53 (0.14) (5.1) 0.49 (0.17) (5.5) 0.41 (0.20)

26 Patterns of change IOM categories Less than recommended: 35% Recommended: 38% More than recommended: 27% age fractional polynomial weight spline weight weeks weeks

27 weight (kg) Negative control to test causality Expected associations Negative control

28 weight (kg) Results Fraser A, et al. Circulation 2010 Linear increase in offspring BMI, fat, waist, adverse lipids, BP at age 10 Morales E, et al. BMC Research Notes Differential DNA m in CpG sites of MMP7, KCNK4, TRPM5, NFKB1, in cord-blood white cells

29 Mean difference in BMI at age 18 years by maternal pregnancy exposures: Swedish sibs Maternal diabetes in pregnancy (yes versus no) Maternal prepregnancy BMI (per 1kg) Weight retention (per 1kg) in normal weight mums Weight retention (per 1kg) in overweight /obese mums Within brothers Between unrelated men P-value for difference 0.94 (0.35, 1.52) 0.87 (0.68, 1.07) (-0.07, -0.01) 0.32 (0.31, 0.32) < (-0.02, 0.02) 0.07 (0.06, 0.07) < (0.01, 0.12) 0.02 (0.01, 0.03) 0.13 Lawlor DA, Lichtenstein P, Långström N. Circulation 2011 & AJCN 2011

30 Maternal BMI offspring DNA Methylation later offspring BMI (Causal approaches) PRELIMINARY FINDINGS; NOT FOR CITATION OR CIRCULATION THANKS TO G SHARPE

31 Negative control: maternal versus paternal Mendelian randomization: cg at USP18 (Hypomethylated in cord-blood of offspring of underweight women) causally related to greater offspring adiposity in childhood & adolescence cg at RGS1 (Hypermethylated in cord-blood of offspring of obese women) causally related to greater offspring birthweight Consistency with gene expression PRELIMINARY FINDINGS; NOT FOR CITATION OR CIRCULATION THANKS TO G SHARPE

32 Future research Large collaboration Further assess causality Explore role of multiple metabolites Maternal circulating nutrients Fetal metabolic response Explore role of epigenetics Cross-generational impact ALSPAC-G2, b1000/mandela, Pelotas Better measures continuous glucose monitoring, physical activity, diet, USS maternal and fetal fat & lean

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34 Conclusions Research Greater maternal adiposity, GDM, greater FPG cause greater birthweight GDM, extreme maternal adiposity cause greater subsequent offspring adiposity? GWG, role of other metabolites, role of epigenome For future birth cohorts Large studies Measurements on fathers Multi- omic s data Repeat measurements Long term follow-up (into next generation) Novel methods of collecting data USS Modern technology for diet, PA Novel methods for data storage, sharing & analyses New forms of collaboration chemists, bioinformaticians, engineers.

35 Acknowledgements Jodie Dodd Rachel Freathy Scott Nelson Julie Owens Lucilla Poston Caroline Relton Gemma Sharpe Rebecca Richmond Naveed Sattar Kate Tilling John Wright Ian Beesley BiB photo gallery