The Impact of Poor Health on Education: New Evidence Using Genetic Markers

Ding, Weili; Lehrer, Steven F.; Rosenquist, J. Niels; Audrain-McGovern, Janet

doi:10.3386/w12304

Cited by 49 publications

(58 citation statements)

References 74 publications

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“…Another potential contribution to social science, already being actively pursued (e.g., 5,6), is the use of genetic markers as instrumental variables in (nongenetic) empirical work. In order for the gene-as-instrument to be valid, not only must the marker be robustly associated with the "endogenous regressor," but all of the behaviors associated with that marker must be understood.…”

Section: Discussionmentioning

confidence: 99%

“…For example, if specific genetic markers can be identified that are associated with a behavioral trait, then such predictive markers may shed light on the biological pathways underlying that trait (3,4). If a set of genetic markers is sufficiently predictive, then these markers could be used in social science research as control variables, as instrumental variables (5,6; for critical perspectives, see refs. 7,8) or, under certain conditions, as factors for identifying at-risk individuals (1)(2)(3).…”

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confidence: 99%

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The genetic architecture of economic and political preferences

Benjamin

Cesarini

Loos

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

233

166

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Preferences are fundamental building blocks in all models of economic and political behavior. We study a new sample of comprehensively genotyped subjects with data on economic and political preferences and educational attainment. We use dense single nucleotide polymorphism (SNP) data to estimate the proportion of variation in these traits explained by common SNPs and to conduct genome-wide association study (GWAS) and prediction analyses. The pattern of results is consistent with findings for other complex traits. First, the estimated fraction of phenotypic variation that could, in principle, be explained by dense SNP arrays is around one-half of the narrow heritability estimated using twin and family samples. The molecular-genetic-based heritability estimates, therefore, partially corroborate evidence of significant heritability from behavior genetic studies. Second, our analyses suggest that these traits have a polygenic architecture, with the heritable variation explained by many genes with small effects. Our results suggest that most published genetic association studies with economic and political traits are dramatically underpowered, which implies a high false discovery rate. These results convey a cautionary message for whether, how, and how soon molecular genetic data can contribute to, and potentially transform, research in social science. We propose some constructive responses to the inferential challenges posed by the small explanatory power of individual SNPs.genoeconomics | genopolitics | GCTA T here has been growing enthusiasm for the use of molecular genetic data in social science research. This enthusiasm is based on a number of potential contributions that such research could make to social science (1-3). For example, if specific genetic markers can be identified that are associated with a behavioral trait, then such predictive markers may shed light on the biological pathways underlying that trait (3, 4). If a set of genetic markers is sufficiently predictive, then these markers could be used in social science research as control variables, as instrumental variables (5, 6; for critical perspectives, see refs. 7, 8) or, under certain conditions, as factors for identifying at-risk individuals (1-3).The extent to which this potential of molecular genetic data will be fulfilled for a given trait hinges on the trait's "molecular genetic architecture," i.e., the joint distribution of effect sizes and allele frequencies of the causal genetic variants (9). The architecture-which is the result of evolutionary forces, including mutation, drift, and selection-determines the difficulty with which the genetic variants associated with a trait can be identified and what sample sizes will be required for gene discovery. It also determines the out-of-sample aggregate predictability that can be derived from a set of genetic markers considered jointly.Existing studies claiming to have established genetic associations with economic and political traits typically use samples of several hundred individuals, and no...

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

The genetic architecture of economic and political preferences

Benjamin

Cesarini

Loos

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

233

166

View full text Add to dashboard Cite

show abstract

“…The three economic studies cited above do not appear to have taken this approach (Lawlor, Windmeijer and Davey Smith, 2008). Rather than basing their selection of genetic variants on associations that are robustly shown in the literature, their choice of instruments seems rather ad hoc: using either forward stepwise estimation (Ding et al, 2009) or selecting those SNPs that have statistically significant sample correlations in the first stage (Fletcher and Lehrer, 2008). In fact, both Ding et al (2009) given that the evidence of a robust association for these variants is lacking, this is not surprising (Lawlor, Windmeijer and Davey Smith, 2008).…”

Section: The Empirical Evidence Using Genetic Variantsmentioning

confidence: 99%

“…Finally, Norton and Han (2008) use several variants as additional controls rather than instruments, as they fail the over-identification tests (SLC6A4, MAOA, DRD2 and CYP2A6). Fletcher and Lehrer (2008) and Ding et al (2009) use several of these as their instruments.…”

Section: The Empirical Evidence Using Genetic Variantsmentioning

confidence: 99%

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Genetic markers as instrumental variables: an application to child fat mass and academic achievement

Hinke¹,

Propper²,

Lawlor³

et al. 2010

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The use of genetic markers as instrumental variables (IV) is receiving increasing attention from economists. This paper examines the conditions that need to be met for genetic variants to be used as instruments. We combine the IV literature with that from genetic epidemiology, with an application to child adiposity (fat mass, determined by a dual-energy X-ray absorptiometry (DXA) scan) and academic performance. OLS results indicate that leaner children perform slightly better in school tests compared to their more adipose counterparts, but the IV findings show no evidence that fat mass affects academic outcomes. Acknowledgements:We thank John Cawley, George Leckie, Owen O'Donnell, Jennifer Roberts, Sarah Smith, Nicholas Timpson, and Gerard van den Berg for helpful suggestions. We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists and nurses. The UK Medical Research Council (MRC), the Wellcome Trust and the University of Bristol provide core support for ALSPAC. This publication is the work of the authors, who will serve as guarantors for the contents of this paper.

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Adolescent depression: diagnosis, treatment, and educational attainment

2007

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In this paper, I use nationally representative longitudinal data to examine adolescent depression and educational attainment. First, I examine the individual, family, and community-level determinants of adolescent depression, diagnosis, and treatment. I find that male and minority adolescents who score high on depression scales are less likely to be diagnosed as depressed or receive treatment than female and non-Hispanic white adolescents. Additionally, I find several community-level variables to be important determinants of depression, diagnosis, and treatment. Second, I examine the importance of adolescent depression for educational attainment. Although it is uncontroversial to expect a negative relationship, most previous research uses cross-sectional data, making it difficult to adequately determine the magnitude of the effect. I find that depressive symptoms are related to educational attainment along multiple margins: dropping out of high school, college enrollment, and college type. These relationships are only found for adolescent females, and there are several interesting results across income groups. Overall, these findings suggest that further attempts to diagnose and treat adolescents with depressive symptoms are needed and that additional treatment options may be required to combat the important relationship between adolescent depression and human capital accumulation for females.

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The Impact of Poor Health on Education: New Evidence Using Genetic Markers

Cited by 49 publications

References 74 publications

The genetic architecture of economic and political preferences

The genetic architecture of economic and political preferences

Genetic markers as instrumental variables: an application to child fat mass and academic achievement

Adolescent depression: diagnosis, treatment, and educational attainment

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