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Behavior Genetics

, Volume 46, Issue 3, pp 315–328 | Cite as

Translational Epidemiologic Approaches to Understanding the Consequences of Early-Life Exposures

  • Brian M. D’OnofrioEmail author
  • Quetzal A. Class
  • Martin E. Rickert
  • Ayesha C. Sujan
  • Henrik Larsson
  • Ralf Kuja-Halkola
  • Arvid Sjölander
  • Catarina Almqvist
  • Paul Lichtenstein
  • A. Sara Oberg
Review

Abstract

Prominent developmental theories posit a causal link between early-life exposures and later functioning. Yet, observed associations with early exposures may not reflect causal effects because of genetic and environmental confounding. The current manuscript describes how a systematic series of epidemiologic analyses that combine several genetically-informative designs and statistical approaches can help distinguish between competing theories. In particular, the manuscript details how combining the use of measured covariates with sibling-comparisons, cousin-comparisons, and additional designs can help elucidate the sources of covariation between early-life exposures and later outcomes, including the roles of (a) factors that are not shared in families, including a potential causal effect of the exposure; (b) carryover effects from the exposure of one child to the next; and (c) familial confounding. We also describe key assumptions and how they can be critically evaluated. Furthermore, we outline how subsequent analyses, including effect decomposition with respect to measured, plausible mediators, and quantitative genetic models can help further specify the underlying processes that account for the associations between early-life exposures and offspring outcomes.

Keywords

Causal inference Genetically-informed designs Sibling comparisons Cousin comparisons Developmental origins of health and disease Pregnancy Fetal growth 

Notes

Acknowledgments

We acknowledge financial support from the Swedish Research Council through the Swedish Initiative for Research on Microdata in the Social and Medical Sciences (SIMSAM, Grant No. 340-2013-5867), NICHD (HD061817 and HD061384), and NIMH (MH094011 and MH102221).

References

  1. Academy of Medical Sciences Working Group (2007) Identifying the environmental causes of disease: how should we decide what to believe and when to take action? Academy of Medical Sciences, LondonGoogle Scholar
  2. Allison PD (2009) Fixed effects regression models. Sage, Washington, DCGoogle Scholar
  3. Baker P, Mott FL (1989) NLSY child handbook. Center for Human Resource Research, ColumbusGoogle Scholar
  4. Barker DJP (1998) Mothers, babies and health in later life, 2nd edn. Churchill Livingstone, EdinburghGoogle Scholar
  5. Byrne N, Regan C, Howard L (2005) Administrative registers in psychiatric research: a systematic review of validity studies. Acta Psychiatr Scand 112:409–414CrossRefPubMedGoogle Scholar
  6. Caspi A, Moffitt TE, Morgan J, Rutter M, Taylor A, Arseneault L, Tully L, Jacobs C, Kim-Cohen J, Polo-Tomas M (2004) Maternal expressed emotion predicts children’s antisocial behavior problems: using monozygotic-twin differences to identify environmental effects on behavioral development. Dev Psychol 40:149–161CrossRefPubMedGoogle Scholar
  7. Chang Z, Lichtenstein P, D’Onofrio BM, Almqvist C, Kuja-Halkola R, Sjolander A, Larsson H (2014) Maternal age at childbirth and risk for ADHD in offspring: a population-based cohort study. Int J Epidemiol 43(6):1815–1824CrossRefPubMedCentralPubMedGoogle Scholar
  8. Cicchetti D (1993) Developmental psychopathology: reactions reflections projections. Dev Rev 13:471–502CrossRefGoogle Scholar
  9. Coie JD, Watt NF, West SG, Hawkins JD, Asarnow JR, Markman HJ, Long B (1993) The science of prevention: a conceptual-framework and some directions for a national research-program. Am Psychol 48:1013–1022CrossRefPubMedGoogle Scholar
  10. Coie JD, Miller-Jackson S, Bagwell C (2000) Prevention science. In: Sameroff AJ, Lewis M, Miller SM (eds) Handbook of developmental psychopathology, vol 2. Springer, New York, pp 94–114Google Scholar
  11. Cole SR, Hernan MA (2002) Fallibility in estimating direct effects. Int J Epidemiol 31(1):163–165CrossRefPubMedGoogle Scholar
  12. Coley RL, Chase-Lansdale L (1998) Adolescent pregnancy and parenthood: recent evidence and future directions. Am Psychol 53(2):152–166CrossRefPubMedGoogle Scholar
  13. Coyne CA, D’Onofrio BM (2012) Some (but not much) progress toward understanding teenage childbearing: a review of research in the past 10 years. Adv Child Dev Behav 42:113–152CrossRefPubMedCentralPubMedGoogle Scholar
  14. Coyne CA, Långström N, Rickert ME, Lichtenstein P, D’Onofrio BM (2013) Maternal age at first birth and offspring criminality: using the children-of-twins design to test causal hypotheses. Dev Psychopathol 25:17–35CrossRefPubMedCentralPubMedGoogle Scholar
  15. D’Onofrio BM, Turkheimer E, Eaves LJ, Corey LA, Berg K, Solaas MH, Emery RE (2003) The role of the children of twins design in elucidating causal relations between parent characteristics and child outcomes. J Child Psychol Psychiatry 44:1130–1144CrossRefPubMedGoogle Scholar
  16. D’Onofrio BM, Van Hulle CA, Waldman ID, Rodgers JL, Harden KP, Rathouz PJ, Lahey BB (2008) Smoking during pregnancy and offspring externalizing problems: an exploration of genetic and environmental confounds. Dev Psychopathol 20:139–164PubMedCentralPubMedGoogle Scholar
  17. D’Onofrio BM, Lahey BB, Turkheimer E, Lichtenstein P (2013a) The critical need for family-based, quasi-experimental research in integrating genetic and social science research. Am J Public Health 103:S46–S55CrossRefPubMedCentralPubMedGoogle Scholar
  18. D’Onofrio BM, Class QA, Rickert ME, Larsson H, Langstrom N, Lichtenstein P (2013b) Preterm birth and mortality and morbidity: a population-based quasi-experimental study. JAMA Psychiatry 70:1231–1240CrossRefPubMedGoogle Scholar
  19. D’Onofrio BM, Class Q, Lahey B, Larsson H (2014) Testing the developmental origins of health and disease hypothesis for psychopathology using family-based, quasi-experimental designs. Child Dev Perspect 8(3):151–157. doi: 10.1111/cdep.12078 CrossRefPubMedCentralPubMedGoogle Scholar
  20. Dick DM (2011) Gene-environment interaction in psychological traits and disorders. Annu Rev Clin Psychol 7:383–409CrossRefPubMedCentralPubMedGoogle Scholar
  21. Donovan SJ, Susser E (2011) Commentary: advent of sibling designs. Int J Epidemiol 40:345–349CrossRefPubMedCentralPubMedGoogle Scholar
  22. Eaves LJ, Silberg JL, Maes HH (2005) Revisiting the children of twins: can they be used to resolve the environmental effects of dyadic parental treatment on child behavior? Twin Res 8:283–290Google Scholar
  23. Eaves LJ, Pourcain BS, Smith GD, York TP, Evans DM (2014) Resolving the effects of maternal and offspring genotype on dyadic outcomes in genome wide complex trait analysis (“M-GCTA”). Behav Genet 44(5):445–455. doi: 10.1007/s10519-014-9666-6 CrossRefPubMedCentralPubMedGoogle Scholar
  24. Fernando ABP, Robbins TW (2011) Animal models of neuropsychiatrics disorders. Annu Rev Clin Psychol 7:39–61CrossRefPubMedGoogle Scholar
  25. Frisell T, Oberg S, Kuja-Halkola R, Sjolander A (2012) Sibling comparison designs: bias from non-shared confounders and measurement error. Epidemiology 23:713–720CrossRefPubMedGoogle Scholar
  26. Ganzel BL, Morris PA (2011) Allostasis and the developing human brain: explicit considering of implicit models. Dev Psychopathol 23(4):955–974CrossRefPubMedGoogle Scholar
  27. Gaziano JM (2010) The evolution of population science. JAMA 304(20):2288–2289. doi: 10.1001/jama.2010.1691 CrossRefPubMedGoogle Scholar
  28. Greenland S, Pearl J, Robins JM (1999) Causal diagrams for epidemiologic research. Epidemiology 10(1):37–48CrossRefPubMedGoogle Scholar
  29. Harden KP, Lynch SK, Turkheimer E, Emery RE, D’Onofrio BM, Slutske WS, Martin NG (2007) A behavior genetic investigation of adolescent motherhood and offspring mental health problems. J Abnorm Psychol 116:667–683CrossRefPubMedCentralPubMedGoogle Scholar
  30. Heath AC, Kendler KS, Eaves LJ, Markell D (1985) The resolution of cultural and biological inheritance: informativeness of different relationships. Behav Genet 15:439–465CrossRefPubMedGoogle Scholar
  31. Heckman JJ (2012) The developmental origins of health. Health Econ 21:24–29CrossRefPubMedCentralPubMedGoogle Scholar
  32. Hiatt RA (2010) Invited commentary: the epicenter of translational science. Am J Epidemiol 172(5):525–527. doi: 10.1093/aje/kwq212 CrossRefPubMedGoogle Scholar
  33. Jaffee S, Caspi A, Moffitt TE, Belsky JAY, Silva P (2001) Why are children born to teen mothers at risk for adverse outcomes in young adulthood? Results from a 20-year longitudinal study. Dev Psychopathol 13:377–397CrossRefPubMedGoogle Scholar
  34. Jaffee SR, Price TS (2012) The implications of genotype–environment correlation for establishing causal processes in psychopathology. Dev Psychopathol 24((Special Issue 04)):1253–1264. doi: 10.1017/S0954579412000685 CrossRefPubMedGoogle Scholar
  35. Kaufman JS, Maclehose RF, Kaufman S (2004) A further critique of the analytic strategy of adjusting for covariates to identify biologic mediation. Epidemiol Perspect Innov 1(1):4. doi: 10.1186/1742-5573-1-4 CrossRefPubMedCentralPubMedGoogle Scholar
  36. Kendler KS, Baker JH (2007) Genetic influences on measures of the environment: a systematic review. Psychol Med 37:615–626CrossRefPubMedGoogle Scholar
  37. Khoury MJ, Gwinn M, Ioannidis JPA (2010) The emergence of translational epidemiology: from scientific discovery to population health impact. Am J Epidemiol 172(5):517–524. doi: 10.1093/aje/kwq211 CrossRefPubMedCentralPubMedGoogle Scholar
  38. Knopik VS (2009) Maternal smoking during pregnancy and child outcomes: real or spurious effect? Dev Neuropsychol 34:1–36CrossRefPubMedCentralPubMedGoogle Scholar
  39. Knopik VS, Heath AC, Marceau K, Palmer RHC, McGeary JE, Todorov A, Evans AS (2015) Missouri Mothers and Their Children: a family study of the effects of genetics and the prenatal environment. Twin Res Hum Genet 18(05):485–496. doi: 10.1017/thg.2015.46 CrossRefPubMedCentralPubMedGoogle Scholar
  40. Knudsen EI (2004) Sensitive periods in the development of the brain and behavior. J Cogn Neurosci 16(8):1412–1425CrossRefPubMedGoogle Scholar
  41. Kuja-Halkola R, D’Onofrio BM, Illiadou A, Pawitan Y, Langstrom N, Lichtenstein P (2010) Prenatal smoking exposure and stress coping in late adolescence: no causal link. Int J Epidemiol 39:1531–1540CrossRefPubMedCentralPubMedGoogle Scholar
  42. Kuja-Halkola R, D’Onofrio BM, Larsson H, Lichtenstein P (2014) Maternal smoking during pregnancy and adverse outcomes in offspring: genetic and environmental sources of covariance. Behav Genet 44(5):456–467. doi: 10.1007/s10519-014-9668-4 CrossRefPubMedCentralPubMedGoogle Scholar
  43. Lahey BB, D’Onofrio BM (2010) All in the family: comparing siblings to test causal hypotheses regarding environmental influences on behavior. Curr Dir Psychol Sci 19:319–323CrossRefPubMedCentralPubMedGoogle Scholar
  44. Lawlor DA, Mishra GD (2009) Family matters: designing, analysing, and understanding family-based studies in life course epidemiology. Oxford University Press, OxfordCrossRefGoogle Scholar
  45. Leve LD, Neiderhiser JM, Scaramella LV, Reiss D (2010) The early growth and development study: using the prospective adoption design to examine genotype-environment interplay. Behav Genet 40:306–314CrossRefPubMedGoogle Scholar
  46. Light IJ (1973) The collaborative perinatal study of the national institute of neurological diseases and stroke: the women and their pregnancies. Am J Dis Child 125(1):146. doi: 10.1001/archpedi.1973.04160010106025 Google Scholar
  47. McAdams TA, Neiderhiser JM, Rijsdijk FV, Narusyte J, Lichtenstein P, Eley TC (2014) Accounting for genetic and environmental confounds in associations between parent and child characteristics: a systematic review of children-of-twins studies. Psychol Bull 140(4):1138–1173. doi: 10.1037/a0036416 CrossRefPubMedGoogle Scholar
  48. McGue M, Osler M, Christensen K (2010) Causal inference and observational research: the utility of twins. Perspect Psychol Sci 5:546–556CrossRefPubMedCentralPubMedGoogle Scholar
  49. Meyer KA, Williams P, Hernandez-Diaz S, Cnattingius S (2004) Smoking and risk of oral clefts: exploring the impact of study designs. Epidemiology 15:671–678CrossRefPubMedGoogle Scholar
  50. Miettunen J, Suvisaari J, Haukka J, Isohanni M (2011) Use of register data for psychiatric epidemiology in the Nordic countries. In: Tsuang MT, Tohen M, Jones P (eds) Textbook of psychiatric epidemiology, 3rd edn. Wiley, Chichester, pp 117–131CrossRefGoogle Scholar
  51. Moffitt TE, Caspi A, Rutter M (2005) Strategy for investigating interactions between measured genes and measured environments. Arch Gen Psychiatry 62:473–481CrossRefPubMedGoogle Scholar
  52. Neiderhiser JM, Reiss D, Hetherington EM (2007) The Nonshared Environment in Adolescent Development (NEAD) project: a longitudinal family study of twins and siblings from adolescence to young adulthood. Twin Res Hum Genet 10(1):74–83CrossRefPubMedGoogle Scholar
  53. Nestler EJ, Hyman SE (2010) Animal models of neuropsychiatric disorders. Nat Neurosci 13:1161–1169CrossRefPubMedCentralPubMedGoogle Scholar
  54. Parisi MA, Spong CY, Zajicek A, Guttmacher AE (2011) We don’t know what we don’t study: the case for research on medication effects in pregnancy. Am J Med Genet Part C 157(3):247–250. doi: 10.1002/ajmg.c.30309 CrossRefPubMedCentralGoogle Scholar
  55. Pearl J (2000) Causality: models, reasoning and inference. Cambridge University Press, CambridgeGoogle Scholar
  56. Pearl J (2001) Direct and indirect effects. In: Proceedings of the seventeenth conference on the uncertainty and artificial intelligence, Morgan Kaufman, San Fransisco, pp 411–420Google Scholar
  57. Pechtel P, Pizzagalli D (2011) Effects of early life stress on cognitive and affective function: an integrated review of human literature. Psychopharmacology 214(1):55–70. doi: 10.1007/s00213-010-2009-2 CrossRefPubMedCentralPubMedGoogle Scholar
  58. Petersen L, Mortensen PB, Pedersen CB (2011) Paternal age at birth of first child and risk of schizophrenia. Am J Psychiatry 168:82–88CrossRefPubMedGoogle Scholar
  59. Plomin R, Bergeman CS (1991) The nature of nurture: genetic influences on “environmental” measures. Behav Brain Sci 10:1–15CrossRefGoogle Scholar
  60. Plomin R, Daniels D (1987) Why are children in the same family so different from each other? Behav Brain Sci 10:1–16CrossRefGoogle Scholar
  61. Rice D, Barone S (2000) Critical periods of vulnerability for the developing nervous system: evidence from humans and animal models. Environ Health Perspect 108(3):511–533CrossRefPubMedCentralPubMedGoogle Scholar
  62. Robins JM (2001) Data, design, and background knowledge in etiologic inference. Epidemiology 12(3):313–320CrossRefPubMedGoogle Scholar
  63. Robins JM, Greenland S (1992) Identifiability and exchangeability for direct and indirect effects. Epidemiology 3(2):143–155CrossRefPubMedGoogle Scholar
  64. Rutter M (2000) Psychosocial influences: critiques, findings, and research needs. Dev Psychopathol 12:375–405CrossRefPubMedGoogle Scholar
  65. Rutter M (2007) Proceeding from observed correlation to causal inference: the use of natural experiments. Perspect Psychol Sci 2:377–395CrossRefPubMedGoogle Scholar
  66. Rutter M, Silberg J, Simonoff E (1993) Whither behavior genetics? A developmental psychopathology perspective. In: Plomin R, McClearn GE (eds) Nature, nurture, and psychology. American Psychological Association, Washington, DC, pp 433–456CrossRefGoogle Scholar
  67. Rutter M, Pickles A, Murray R, Eaves LJ (2001) Testing hypotheses on specific environmental causal effects on behavior. Psychol Bull 127:291–324CrossRefPubMedGoogle Scholar
  68. Shadish WR, Cook TD, Campbell DT (2002) Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin, New YorkGoogle Scholar
  69. Silberg JL, Eaves LJ (2004) Analyzing the contribution of genes and parent-child interaction to childhood behavioral and emotional problems: a model for the children of twins. Psychol Med 34:347–356CrossRefPubMedGoogle Scholar
  70. Sjolander A (2013) Reducing mean squared error in the analysis of binary paired data. Epidemiol Methods 2(1):33–47Google Scholar
  71. Sjölander A, Greenland S (2013) Ignoring the matching variables in cohort studies—when is it valid and why? Stat Med 32(27):4696–4708. doi: 10.1002/sim.5879 CrossRefPubMedGoogle Scholar
  72. Sjolander A, Johansson ALV, Lundholm C, Altman D, Almqvist C, Pawitan Y (2012) Analysis of 1:1 matched cohort studies and twin studies, with binary exposures and binary outcomes. Stat Sci 27:395–411. doi: 10.1214/12-STS390 CrossRefGoogle Scholar
  73. Smith GD, Ebrahim S (2005) What can Mendelian randomization tell us about modifiable behavioural and environmental exposures? Br Med J 330:1076–1079CrossRefGoogle Scholar
  74. Susser E, Eide MG, Begg M (2010) Invited commentary: the use of sibship studies to detect familial confounding. Am J Epidemiol 172(5):537–539. doi: 10.1093/aje/kwq196 CrossRefPubMedGoogle Scholar
  75. Thapar A, Rutter M (2009) Do prenatal risk factors cause psychiatric disorder? Be wary of causal claims. Br J Psychiatry 195:100–101CrossRefPubMedGoogle Scholar
  76. Thapar A, Harold G, Rice F, Ge X, Boivin J, Hay D, Lewis A (2007) Do intrauterine or genetic influences explain the foetal origins of chronic disease? A novel experimental method for disentangling effects. BMC Med Res Methodol 7:25CrossRefPubMedCentralPubMedGoogle Scholar
  77. Turkheimer E, Harden KP (2014) Behavior genetic research methods: testing quasi-causal hypotheses using multivariate twin data. In: Reis HT, Judd CM (eds) Handbook of research methods in personality and social psychology, 2nd edn. Cambridge University Press, CambridgeGoogle Scholar
  78. Turkheimer E, Waldron M (2000) Nonshared environment: a theoretical, methodological, and quantitative review. Psychol Bull 126(1):78–108CrossRefPubMedGoogle Scholar
  79. Turley RNL (2003) Are children of young mothers disadvantaged because of their mother’s age or family background? Child Dev 74:465–474CrossRefPubMedGoogle Scholar
  80. VanderWeele TJ (2009) Marginal structural models for the estimation of direct and indirect effects. Epidemiology 20(1):18–26. doi: 10.1097/EDE.0b013e31818f69ce CrossRefPubMedGoogle Scholar
  81. VanderWeele TJ (2010) Bias formulas for sensitivity analysis for direct and indirect effects. Epidemiology 21(4):540–551. doi: 10.1097/EDE.0b013e3181df191c CrossRefPubMedCentralPubMedGoogle Scholar
  82. VanderWeele TJ, Hernandez-Diaz S (2011) Is there a direct effect of pre-eclampsia on cerebral palsy not through preterm birth? Paediatr Perinat Epidemiol 25(2):111–115. doi: 10.1111/j.1365-3016.2010.01175.x CrossRefPubMedGoogle Scholar
  83. Vrieze SI, Iacono WG, McGue M (2012) Confluence of genes, environment, development, and behavior in a post Genome-Wide Association Study world. Dev Psychopathol 24:1195–1214CrossRefPubMedCentralPubMedGoogle Scholar
  84. Weissman MM, Brown AS, Talati A (2011) Translational epidemiology in psychiatry: linking population to clinical and basic sciences. Arch Gen Psychiatry 68(6):600–608. doi: 10.1001/archgenpsychiatry.2011.47 CrossRefPubMedCentralPubMedGoogle Scholar
  85. Zeanah CH, Gunnar MR, McCall RB, Kreppner JM, Fox NA (2011) Sensitive periods. Monogr Soc Res Child Dev 76(4):147–162CrossRefPubMedCentralPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • Brian M. D’Onofrio
    • 1
    Email author return OK on get
  • Quetzal A. Class
    • 1
  • Martin E. Rickert
    • 1
  • Ayesha C. Sujan
    • 1
  • Henrik Larsson
    • 2
  • Ralf Kuja-Halkola
    • 2
  • Arvid Sjölander
    • 2
  • Catarina Almqvist
    • 2
  • Paul Lichtenstein
    • 2
  • A. Sara Oberg
    • 2
    • 3
  1. 1.Department of Psychological and Brain SciencesIndiana UniversityBloomingtonUSA
  2. 2.Karolinska InstitutetStockholmSweden
  3. 3.Harvard T.H. Chan School of Public HealthBostonUSA

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