[en] We here address the causal relationship between the maternal genetic risk for depression and child human capital using UK birth-cohort data. We find that an increase of one standard deviation (SD) in the maternal polygenic risk score for depression reduces their children’s cognitive and non-cognitive skill scores by 5 to 7% of a SD throughout adolescence. Our results are robust to a battery of sensitivity tests addressing, among others, concerns about pleiotropy and dynastic effects. Our Gelbach decomposition analysis suggests that the strongest mediator is genetic nurture (through maternal depression itself), with genetic inheritance playing only a marginal role.
Special economic topics (health, labor, transportation...)
Author, co-author :
Menta, Giorgia; Luxembourg Institute of Socio-Economic Research (LISER), Luxembourg
Lepinteur, Anthony ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS)
Clark, Andrew; Paris School of Economics - CNRS, France and University of Luxembourg
Ghislandi, Simone; Bocconi University, Italy
d'Ambrosio, Conchita ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS)
External co-authors :
Maternal genetic risk for depression and child human capital
Abdellaoui, A., Hugh-Jones, D., Yengo, L., Kemper, K.E., Nivard, M.G., Veul, L., Visscher, P.M., Genetic correlates of social stratification in Great Britain. Nat. Hum. Behav. 3 (2019), 1332–1342.
Amare, A.T., Schubert, K.O., Hou, L., Clark, S.R., Papiol, S., Cearns, M., Baune, B.T., Association of polygenic score for major depression with response to lithium in patients with bipolar disorder. Mol. Psychiatry 26 (2021), 2457–2470.
Assari, S., Social determinants of depression: the intersections of race, gender, and socioeconomic status. Brain Sci. 7 (2017), 1–12.
Atkinson, A.B., Inequality: What Can Be Done?. 2015, Harvard University Press.
Banerjee, S., Chatterji, P., Lahiri, K., Effects of psychiatric disorders on labor market outcomes: a latent variable approach using multiple clinical indicators. Health Econ. 26 (2017), 184–205.
Becker, J., Burik, C.A., Goldman, G., Wang, N., Jayashankar, H., Bennett, M., Okbay, A., Resource profile and user guide of the Polygenic Index Repository. Nat. Hum. Behav. 5 (2021), 1744–1758.
Benke, K.S., Nivard, M.G., Velders, F.P., Walters, R.K., Pappa, I., Scheet, P.A., Verhulst, F.C., A genome-wide association meta-analysis of preschool internalizing problems. J. Am. Acad. Child Adolesc. Psychiatry 53 (2014), 667–676.
Boef, A.G., Dekkers, O.M., Le Cessie, S., Mendelian randomization studies: a review of the approaches used and the quality of reporting. Int. J. Epidemiol. 44 (2015), 496–511.
Boyd, A., Macleod, J., Henderson, J., Molloy, L., Ring, S., Golding, J., Ness, A., “Cohort profile: the “Children of the 90s”-the index offspring of the Avon longitudinal study of parents and children. Int. J. Epidemiol. 42 (2013), 111–127.
Briole, S., Le Forner, H., Lepinteur, A., Children's socio-emotional skills: is there a quantity–quality trade-off?. Labour Econ., 64, 2020, 101811.
Bubonya, M., Cobb-Clark, D.A., Wooden, M., Mental health and productivity at work: does what you do matter?. Labour Econ. 46 (2017), 150–165.
Campbell, D., Green, M.J., Davies, N., Demou, E., Howe, L.D., Harrison, S., Smith, D.J., Howard, D.M., McIntosh, A.M., Munafo, M., Katikireddi, S.V., Effects of depression on employment and social outcomes: a mendelian randomisation study. J. Epidemioly Community Health 76 (2022), 563–571.
Clark, A.E., D'Ambrosio, C., Barazzetta, M., Childhood circumstances and young adult outcomes: the role of mothers’ financial problems”. Health Econ. 30 (2021), 342–357.
Clark, A.E., Flèche, S., Layard, R., Powdthavee, N., Ward, G., The Origins of Happiness: The Science of Well-being over the Life Course. 2018, Princeton University Press.
Clark, A.E., Lepinteur, A., The causes and consequences of early-adult unemployment: evidence from cohort data. J. Econ. Behav. Organ. 166 (2019), 107–124.
Clark, D.M., Realizing the mass public benefit of evidence-based psychological therapies: the IAPT program. Annu. Rev. Clin. Psychol. 14 (2018), 159–183.
Cunha, F., Heckman, J.J., Formulating, identifying and estimating the technology of cognitive and noncognitive skill formation. J. Hum. Resour. 43 (2008), 738–782.
Dahlen, H.M., The impact of maternal depression on child academic and socioemotional outcomes. Econ. Educ. Rev. 52 (2016), 77–90.
Davies, N.M., von Hinke Kessler Scholder, S., Farbmacher, H., Burgess, S., Windmeijer, F., Smith, G.D, The many weak instruments problem and Mendelian randomization. Stat. Med. 34 (2015), 454–468.
de Geus, E.J., Mendelian randomization supports a causal effect of depression on cardiovascular disease as the main source of their comorbidity. J. Am. Heart Assoc., 10, 2021, e019861.
Del Bono, E., Kinsler, J., and Pavan, R. (2020). Skill Formation and the Trouble with Child Non-Cognitive Skill Measures. IZA Discussion Paper No. 13713.
Demange, P.A., Malanchini, M., Mallard, T.T., Biroli, P., Cox, S.R., Grotzinger, A.D., Corcoran, D., Investigating the genetic architecture of non-cognitive skills using GWAS-by-subtraction. Nat. Genet. 53 (2021), 35–44.
DiPrete, T.A., Burik, C.A., Koellinger, P.D., Genetic instrumental variable regression: explaining socioeconomic and health outcomes in nonexperimental data. Proc. Natl. Acad. Sci. 115 (2018), 4970–4979.
Flèche, S. (2017). Teacher quality, test-scores and non-cognitive skills: evidence from primary school teachers in the UK. CEP Discussion Paper No. 1472.
Fletcher, J., Adolescent depression and adult labor market outcomes. South. Econ. J. 80 (2013), 26–49.
Fraser, A., Macdonald-Wallis, C., Tilling, K., Boyd, A., Golding, J., Davey Smith, G., Ring, S., Cohort profile: the Avon longitudinal study of parents and children: ALSPAC mothers cohort. Int. J. Epidemiol. 42 (2013), 97–110.
Gelbach, J.B., When do covariates matter? And which ones, and how much?. J. Labor Econ. 34 (2016), 509–543.
Goodman, R., The strengths and difficulties questionnaire: a research note. J. Child Psychol. Psychiatry 38 (1997), 581–586.
Goodman, A., Lamping, D.L., Ploubidis, G.B., When to use broader internalising and externalising subscales instead of the hypothesised five subscales on the strengths and difficulties questionnaire (SDQ): data from British parents, teachers and children. J. Abnorm. Child Psychol. 38 (2010), 1179–1191.
Goodman, S.H., Rouse, M.H., Connell, A.M., Broth, M.R., Hall, C.M., Heyward, D., Maternal depression and child psychopathology: a meta-analytic review. Clin. Child Fam. Psychol. Rev. 14 (2011), 1–27.
Gotlib, I., Goodman, S., Humphreys, K., Studying the intergenerational transmission of risk for depression: current status and future directions. Curr. Dir. Psychol. Sci. 29 (2020), 174–179.
Gotlib, I.H., Lewinsohn, P.M., Seeley, J.R., Consequences of depression during adolescence: marital status and marital functioning in early adulthood. J. Abnorm. Psychol. 107 (1998), 686–690.
Hakulinen, C., Elovainio, M., Arffman, M., Lumme, S., Pirkola, S., Keskimäki, I., Böckerman, P., Mental disorders and long-term labour market outcomes: nationwide cohort study of 2,055,720 individuals. Acta Psychiatr. Scand. 140 (2019), 371–381.
Harden, K.P., Koellinger, P.D., Using genetics for social science. Nat. Hum. Behav. 4 (2020), 567–576.
Heckman, J.J., Stixrud, J., Urzua, S., The effects of cognitive and noncognitive abilities on labor market outcomes and social behavior. J. Labor Econ. 24 (2006), 411–482.
Heckman, J.J., Humphries, J.E., Veramendi, G., Returns to education: the causal effects of education on earnings, health, and smoking. J. Polit. Econ. 126 (2018), 197–246.
Hemani, G., Bowden, J., Davey Smith, G., Evaluating the potential role of pleiotropy in Mendelian randomization studies. Hum. Mol. Genet. 27 (2018), 195–208.
Howe, L.J., Nivard, M.G., Morris, T.T., Hansen, A.F., Rasheed, H., Cho, Y., Davies, N.M., Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects. Nat. Genet. 54 (2022), 581–592.
InStansfeld, S., Clark, C., Bebbington, P., King, M., Jenkins, R., Hinchliffe, S., McManus, S., Bebbington, P., Jenkins, R., Brugha, T., Chapter 2: common mental disorders. Mental Health and Wellbeing in England: Adult Psychiatric Morbidity Survey 2014, 2016, NHS Digital, Leeds, 37–68.
Joint Research Centre F7 - Knowledge Health and Consumer Safety, 2019. Genome-wide association studies, polygenic scores and social science genetics. JRC Technical Report, 117414. Luxembourg: European Commission.
Karlsson Linnér, R., Biroli, P., Kong, E., Meddens, S.F.W., Wedow, R., Fontana, M.A., Nivard, M.G., Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences. Nat. Genet. 51 (2019), 245–257.
Kiernan, K.E., Huerta, M.C., Economic deprivation, maternal depression, parenting and children's cognitive and emotional development in early childhood. Br. J. Sociol. 59 (2008), 783–806.
Koellinger, P.D., De Vlaming, R., Mendelian randomization: the challenge of unobserved environmental confounds. Int. J. Epidemiol. 48 (2019), 665–671.
Kong, A., Thorleifsson, G., Frigge, M.L., Vilhjalmsson, B.J., Young, A.I., Thorgeirsson, T.E., Gudbjartsson, D.F., The nature of nurture: effects of parental genotypes. Science 359 (2018), 424–428.
Lee, J.J., Wedow, R., Okbay, A., Kong, E., Maghzian, O., Zacher, M., Fontana, M.A., Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat. Genet. 50 (2018), 1112–1121.
Middeldorp, C.M., Hammerschlag, A.R., Ouwens, K.G., Groen-Blokhuis, M.M., Pourcain, B.S., Greven, C.U., Vilor-Tejedor, N., A genome-wide association meta-analysis of attention-deficit/hyperactivity disorder symptoms in population-based pediatric cohorts. J. Am. Acad. Child Adolesc. Psychiatry 55 (2016), 896–905.
Mulugeta, A., Lumsden, A., Hyppönen, E., Relationship between serum 25 (OH) D and depression: causal evidence from a bi-directional Mendelian randomization study. Nutrients, 13, 2020, 109 1-13.
O'Hara, M.W., McCabe, J.E., Postpartum depression: current status and future directions. Annu. Rev. Clin. Psychol. 9 (2013), 379–407.
Okbay, A., Baselmans, B.M., De Neve, J.E., Turley, P., Nivard, M.G., Fontana, M.A., Gratten, J., Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat. Genet. 48 (2016), 624–633.
Pappa, I., St Pourcain, B., Benke, K., Cavadino, A., Hakulinen, C., Nivard, M.G., Evans, D.M., A genome-wide approach to children's aggressive behavior: the EAGLE consortium. Am. J. Med. Genet. B: Neuropsychiatr. Genet. 171 (2016), 562–572.
Perry, C.D., Does treating maternal depression improve child health management? The case of pediatric asthma. J. Health Econ. 27 (2008), 157–173.
Prince, M., Patel, V., Saxena, S., Maj, M., Maselko, J., Phillips, M.R., Rahman, A., No health without mental health. Lancet 370 (2007), 859–877.
Reed, Z.E., Morris, T.T., Davis, O.S., Smith, G.D., Munafo, M.R., and Griffith, G.J. (2022). “Examining the association between genetic risk for depression, wellbeing and schizophrenia, and proximity to greenspace”. medRxiv, 10.1101/2022.04.21.22274122.
Roemer, J.E., Theories of Distributive Justice. 1998, Harvard University Press.
Sealock, J.M., Lee, Y.H., Moscati, A., Venkatesh, S., Voloudakis, G., Straub, P., Davis, L.K., Use of the PsycheMERGE network to investigate the association between depression polygenic scores and white blood cell count. JAMA Psychiatry 78 (2021), 1365–1374.
Smith, G.D., Lawlor, D.A., Harbord, R., Timpson, N., Day, I., Ebrahim, S., Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology. PLoS Med. 4 (2007), 1985–1992.
Taylor, A.E., Jones, H.J., Sallis, H., Euesden, J., Stergiakouli, E., Davies, N.M., Tilling, K., Exploring the association of genetic factors with participation in the Avon longitudinal study of parents and children. Int. J. Epidemiol. 47 (2018), 1207–1216.
Turley, P., Walters, R.K., Maghzian, O., Okbay, A., Lee, J.J., Fontana, M.A., Magnusson, P., Multi-trait analysis of genome-wide association summary statistics using MTAG. Nat. Genet. 50 (2018), 229–237.
Von Hinke, S., Rice, N., Tominey, E., Mental health around pregnancy and child development from early childhood to adolescence. Labour Econ., 78, 2022, 102245.
Von Hinke, S., Smith, G.D., Lawlor, D.A., Propper, C., Windmeijer, F., Genetic markers as instrumental variables. J. Health Econ. 45 (2016), 131–148.
Zimmerman, F., Katon, W., Socioeconomic status, depression disparities, and financial strain: what lies behind the income-depression relationship?. Health Econ. 14 (2005), 1197–1215.