Association of pre-pregnancy body mass index with offspring metabolic profile: Analyses of 3 European prospective birth cohorts

1. Kanagalingam MG, Forouhi NG, Greer IA, Sattar N. Changes in booking body mass index over a decade: retrospective analysis from a Glasgow Maternity Hospital. Bjog. 2005;112(10):1431–3. doi: 10.1111/j.1471-0528.2005.00685.x 16167951.

2. Heslehurst N, Ells LJ, Simpson H, Batterham A, Wilkinson J, Summerbell CD. Trends in maternal obesity incidence rates, demographic predictors, and health inequalities in 36,821 women over a 15-year period. Bjog. 2007;114(2):187–94. 17305899.

3. Lawlor DA, Davey Smith G, O'Callaghan M, Alati R, Mamun AA, Williams GM, et al. Epidemiologic evidence for the fetal overnutrition hypothesis: findings from the mater-university study of pregnancy and its outcomes. Am J Epidemiol. 2007;165(4):418–24. doi: 10.1093/aje/kwk030 17158475.

4. Lawlor DA. The Society for Social Medicine John Pemberton Lecture 2011. Developmental overnutrition-an old hypothesis with new importance?*. Int J Epidemiol. 2013;42(1):7–29. doi: 10.1093/ije/dys209 23508404

5. Farrar D, Simmonds M, Bryant M, Sheldon TA, Tuffnell D, Golder S, et al. Hyperglycaemia and risk of adverse perinatal outcomes: systematic review and meta-analysis. BMJ (Clinical research ed). 2016;354:i4694. doi: 10.1136/bmj.i4694 27624087.

6. Tyrrell J, Richmond RC, Palmer TM, Feenstra B, Rangarajan J, Metrustry S, et al. Genetic Evidence for Causal Relationships Between Maternal Obesity-Related Traits and Birth Weight. JAMA. 2016;315(11):1129–40. doi: 10.1001/jama.2016.1975 26978208;

7. Ojha S, Saroha V, Symonds ME, Budge H. Excess nutrient supply in early life and its later metabolic consequences. Clin Exp Pharmacol Physiol. 2013;40(11):817–23. doi: 10.1111/1440-1681.12061 23350968.

8. Lawlor DA, Lichtenstein P, Langstrom N. Association of maternal diabetes mellitus in pregnancy with offspring adiposity into early adulthood sibling study in a prospective cohort of 280,866 men from 248,293 families. Circulation. 2011;123(3):258–U67. doi: 10.1161/CIRCULATIONAHA.110.980169 21220735

9. Richmond RC, Timpson NJ, Felix JF, Palmer T, Gaillard R, McMahon G, et al. Using Genetic Variation to Explore the Causal Effect of Maternal Pregnancy Adiposity on Future Offspring Adiposity: A Mendelian Randomisation Study. PLoS Med. 2017;14(1):e1002221. doi: 10.1371/journal.pmed.1002221 28118352;

10. Smith GD, Lawlor DA, Harbord R, Timpson N, Day I, Ebrahim S. Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology. PLoS Med. 2007;4(12):e352. doi: 10.1371/journal.pmed.0040352 18076282.

11. Lawlor DA, Tilling K, Davey Smith G. Triangulation in aetiological epidemiology. Int J Epidemiol. 2017. doi: 10.1093/ije/dyw314 28108528.

12. Boyd A, Golding J, Macleod J, Lawlor DA, Fraser A, Henderson J, et al. Cohort Profile: The 'Children of the 90s'-the index offspring of the Avon Longitudinal Study of Parents and Children. Int J Epidemiol. 2013;42(1):111–27. doi: 10.1093/ije/dys064 22507743

13. Fraser A, Macdonald-Wallis C, Tilling K, Boyd A, Golding J, Davey Smith G, et al. Cohort Profile: The Avon Longitudinal Study of Parents and Children: ALSPAC mothers cohort. Int J Epidemiol. 2013;42(1):97–110. doi: 10.1093/ije/dys066 22507742

14. Rantakallio P. The longitudinal study of the northern Finland birth cohort of 1966. Paediatr Perinat Epidemiol. 1988;2(1):59–88. 2976931.

15. Northern Finland Birth Cohorts Studies (NFBC). Retrieved from http://www.oulu.fi/nfbc 2016. Cited 3 Aug 2016.

16. Riley RD, Lambert PC, Abo-Zaid G. Meta-analysis of individual participant data: rationale, conduct, and reporting. BMJ. 2010;340:c221. doi: 10.1136/bmj.c221 20139215.

17. Simmonds MC, Higgins JPT, Stewart LA, Tierney JF, Clarke MJ, Thompson SG. Meta-analysis of individual patient data from randomized trials: a review of methods used in practice. Clin Trials. 2005;2(3):209–17. doi: 10.1191/1740774505cn087oa 16279144.

18. Oxman AD, Clarke MJ, Stewart LA. From science to practice. Meta-analyses using individual patient data are needed. JAMA. 1995;274(10):845–6. 7650811.

19. Lawlor DA, Ben-Shlomo Y, Leon DA. Pre-adult influences on cardiovascular disease. In: Kuh D, Ben-Shlomo Y, editors. A life course approach to chronic disease epidemiology 2ed. Oxford: Oxford University Press; 2004. p. 41–76.

20. Soininen P, Kangas AJ, Wurtz P, Suna T, Ala-Korpela M. Quantitative serum nuclear magnetic resonance metabolomics in cardiovascular epidemiology and genetics. Circ Cardiovasc Genet. 2015;8(1):192–206. doi: 10.1161/CIRCGENETICS.114.000216 25691689.

21. Soininen P, Kangas AJ, Wurtz P, Tukiainen T, Tynkkynen T, Laatikainen R, et al. High-throughput serum NMR metabonomics for cost-effective holistic studies on systemic metabolism. Analyst. 2009;134(9):1781–5. doi: 10.1039/b910205a 19684899

22. Wurtz P, Havulinna AS, Soininen P, Tynkkynen T, Prieto-Merino D, Tillin T, et al. Metabolite profiling and cardiovascular event risk: a prospective study of 3 population-based cohorts. Circulation. 2015;131(9):774–85. doi: 10.1161/CIRCULATIONAHA.114.013116 25573147;

23. Fischer K, Kettunen J, Wurtz P, Haller T, Havulinna AS, Kangas AJ, et al. Biomarker profiling by nuclear magnetic resonance spectroscopy for the prediction of all-cause mortality: an observational study of 17,345 persons. PLoS Med. 2014;11(2):e1001606. doi: 10.1371/journal.pmed.1001606 24586121;

24. Kettunen J, Tukiainen T, Sarin AP, Ortega-Alonso A, Tikkanen E, Lyytikainen LP, et al. Genome-wide association study identifies multiple loci influencing human serum metabolite levels. Nat Genet. 2012;44(3):269–76. doi: 10.1038/ng.1073 22286219;

25. Kujala UM, Makinen VP, Heinonen I, Soininen P, Kangas AJ, Leskinen TH, et al. Long-term leisure-time physical activity and serum metabolome. Circulation. 2013;127(3):340–8. doi: 10.1161/CIRCULATIONAHA.112.105551 23258601.

26. Inouye M, Kettunen J, Soininen P, Silander K, Ripatti S, Kumpula LS, et al. Metabonomic, transcriptomic, and genomic variation of a population cohort. Mol Syst Biol. 2010;6:441. doi: 10.1038/msb.2010.93 21179014;

27. Higgins JP, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327(7414):557–60. doi: 10.1136/bmj.327.7414.557 12958120;

28. Nakagawa S, Schielzeth H. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol Evol. 2013;4(2):133–42. doi: 10.1111/j.2041-210x.2012.00261.x

29. Gao X, Starmer J, Martin ER. A multiple testing correction method for genetic association studies using correlated single nucleotide polymorphisms. Genet Epidemiol. 2008;32(4):361–9. doi: 10.1002/gepi.20310 18271029.

30. Wang Q, Kangas AJ, Soininen P, Tiainen M, Tynkkynen T, Puukka K, et al. Sex hormone-binding globulin associations with circulating lipids and metabolites and the risk for type 2 diabetes: observational and causal effect estimates. Int J Epidemiol. 2015;44(2):623–37. doi: 10.1093/ije/dyv093 26050255.

31. Gaillard R, Steegers EAP, Duijts L, Felix JF, Hofman A, Franco OH, et al. Childhood Cardiometabolic Outcomes of Maternal Obesity During Pregnancy The Generation R Study. Hypertension. 2014;63(4):683–91. doi: 10.1161/HYPERTENSIONAHA.113.02671 24379180

32. Daraki V, Georgiou V, Papavasiliou S, Chalkiadaki G, Karahaliou M, Koinaki S, et al. Metabolic Profile in Early Pregnancy Is Associated with Offspring Adiposity at 4 Years of Age: The Rhea Pregnancy Cohort Crete, Greece. PLoS ONE. 2015;10(5). doi: 10.1371/journal.pone.0126327 25970502

33. Oostvogels AJJM, Stronks K, Roseboom TJ, van der Post JAM, van Eijsden M, Vrijkotte TGM. Maternal Prepregnancy BMI, Offspring's Early Postnatal Growth, and Metabolic Profile at Age 5–6 Years: the ABCD Study. J Clin Endocrinol Metab. 2014;99(10):3845–54. doi: 10.1210/jc.2014-1561 24955609

34. 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(12):e1001765. doi: 10.1371/journal.pmed.1001765 25490400;

35. Brion MJA. Commentary: Can maternal-paternal comparisons contribute to our understanding of maternal pre-pregnancy obesity and its association with offspring cognitive outcomes? Int J Epidemiol. 2013;42(2):518–9. doi: 10.1093/ije/dyt041 23569192

36. Katzmarzyk PT, Perusse L, Rao DC, Bouchard C. Spousal resemblance and risk of 7-year increases in obesity and central adiposity in the Canadian population. Obes Res. 1999;7(6):545–51. 10574512.

37. Knuiman MW, Divitini ML, Bartholomew HC, Welborn TA. Spouse correlations in cardiovascular risk factors and the effect of marriage duration. Am J Epidemiol. 1996;143(1):48–53. 8533746.

38. Jeffery RW, Rick AM. Cross-sectional and longitudinal associations between body mass index and marriage-related factors. Obes Res. 2002;10(8):809–15. doi: 10.1038/oby.2002.109 12181390.

39. Silventoinen K, Kaprio J, Lahelma E, Viken RJ, Rose RJ. Assortative mating by body height and BMI: Finnish twins and their spouses. Am J Hum Biol. 2003;15(5):620–7. doi: 10.1002/ajhb.10183 12953173.

40. Stewart LA, Parmar MKB. Metaanalysis of the Literature or of Individual Patient Data—Is There a Difference. Lancet. 1993;341(8842):418–22. doi: 10.1016/0140-6736(93)93004-K 8094183