Biosocial Surveys (2008) / Chapter Skim
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15 Genoeconomics--Daniel J. Benjamin, Christopher F. Chabris, Edward L. Glaeser, Vilmundur Gudnason, Tamara B. Harris, David I. Laibson, Lenore J. Launer, and Shaun Purcell
15 Genoeconomics--Daniel J. Benjamin, Christopher F. Chabris, Edward L. Glaeser, Vilmundur Gudnason, Tamara B. Harris, David I. Laibson, Lenore J. Launer, and Shaun Purcell
Pages 304-335
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From page 304... ...
. The primary contribution of genoeconomics is likely to be identifying the many ways in which individual behavior and social institutions moderate or amplify genetic differences.
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From page 305... ...
address the causal effect of health on educational outcomes, using genetic predictors of health to ameliorate confounding by third factors potentially correlated with both health and educational outcomes. More generally, cognition-linked alleles will contribute to understanding of the cognitive factors that influence income, or the extent to which cognitive factors influence decision making about savings and wealth.
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These problems are multiplied when genetic research is done carelessly. Historically, there have been many cases of false positives in which early genetic claims have evaporated under subsequent attempts at replication.
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Proximal behavioral phenotypes, such as impatience or risk aversion, are probably more directly related to genetic propensities than more distal economic phenotypes, such as wealth accumulation or labor force participation. Proximal phenotypes have typically been measured with personality tests.
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Correlated Genes and Environments Genes and environments are, for various reasons, often not independent factors. This has implications for statistical designs attempting to uncover genetic influences, environmental influences, and the interactions of genes and environments.
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causal mechanism: gene X Measuring Genetic Variation The typical "gene by environment" association study should really be called an "allele by environment" study because, very often, only a single variant within a gene is studied.
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From page 310... ...
For example, phenylketonuria is a Mendelian human disorder, but the gene acts to produce the severe symptoms of mental retardation only in the presence of dietary phenylalanine. Research in Drosophila melanogaster has found evidence for G×E in quantitative traits including bristle number, longevity, and wing shape (Mackay, 2001; Clare and Luckinbill, 1985)
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Assuming an additive model implies that the joint effect (without an interaction effect) is g + e – 1, whereas a multiplicative model implies that the joint effect (without an interaction effect)
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There can be no guarantee that the effects of G and E should necessarily display an additive relationship at this level, considering the various neurochemical cascades and reciprocal feedback loops that are presumably involved in a system as complex as the human brain. Or the measured phenotype may be even further downstream -- a clinical diagnosis based on behavioral symptoms, or a 25-item self-report questionnaire measure, log-transformed to approximate normality.
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Efforts to detect G×E magnify these concerns. AGES-Reykjavik Study collaboration Currently, the main obstacle to bringing genetic research into economics is the fact that few data sets combine economic measures with biosamples that can be genotyped.
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In addition to these distal phenotypes, we plan to study proximal phenotypes -- such as impulsiveness, risk aversion, and cognition -- that may be more closely related to underlying genetic propensities. A measure of late-life general cognitive function can be constructed from existing data on memory, speed of processing, and working memory.
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For the next wave of the AGES-Reykjavik study, we plan to add additional distal phenotypes (wealth and income) and proximal phenotypes (experimental measures of impulsivity and risk aversion)
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as labor supply and wealth accumulation, will be related to proximal phenotypes that matter for decision making, such as impulsiveness, risk aversion, and cognitive function (Barsky et al., 1997; Benjamin, Brown, and Shapiro, 2006; Dohmen et al., 2005)
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By contrast, the cortical system is active for all decisions (whether or not immediate rewards are among the choices) , and its activity increases in trials when sub jects choose more delayed rewards.
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Second, we selected genes that have been associated or implicated in phenotypes related to cognitive functions: memory (e.g., de Quervain and Papassotiropoulos, 2006) ; schizophrenia, which involves neurocognitive dysfunction (Hallmayer et al., 2005)
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System TH 11p15.5 Tyrosine hydroxylase DDC 7p12.2 Dopa decarboxylase VMAT1 8p21.3 Vesicular monoamine transporter 1 VMAT2 10q25.3 Vesicular monoamine transporter 2 DRD1 5q35.1 Dopamine receptor 1 ADHD (Bobb et al., 2005) DRD2 11q23 Dopamine receptor 2 Neural activation during working memory (Jacobsen et al., 2006)
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Under selection in CEU and ASN populations (Voight et al., 2006) Genes Reported to Be Associated with General Cognitive Ability (reviewed by Payton, 2006; Plomin et al., in press)
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Candidate Genes Near Linkage Peaks in Studies of IQ (Posthuma et al., 2005; Luciano et al., 2006; Hallmayer et al., 2005; Dick et al., 2006b) NR4A2 2q24.1 Nuclear receptor subfamily 4, group A, member 2 SLC25A12 2q31.1 Solute carrier family 25, member 12 SCN1A 2q24.3 Sodium channel, neuronal type 1, alpha subunit SCN2A 2q24.3 Sodium channel, neuronal type 2, alpha subunit TBR1 2q24.2 T-box, brain, 1 SCN3A 2q24.3 Sodium channel, neuronal type 3, alpha subunit KCNH7 2q24.2 Potassium channel, voltage-gated, subfamily H, member 7 GAD1 2q31.1 Gluatamate decarboxylase 1 HOXD1 2q31.1 Homeobox D1 CHN1 2q31.1 Chimerin 1 RAPGEF4 2q31.1 RAP guanine nucleotide exchange factor NOSTRIN 2q24.3 Nitric oxide synthase trafficker BBS5 2q31.1 BBS5 gene DLX1 2q31.1 Distal-less homeobox 1 DLX2 2q31.1 Distal-less homeobox 2 KIF13A 6p22.3 Kinesin family member 13A NQO2 6p25.2 NAD(P)
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Genes Associated with Alzheimer Disease (AD) (reviewed by Bertram et al., 2007; Bertram and Tanzi, 2004)
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CDK5RAP2 9q33.2 CDK5 regulatory subunit associated protein 2 ���������������������������������������������� Brain size (Woods et al., 2005; Evans et al., 2006) Reverse association w/ verbal IQ (Luciano et al., 2006)
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CHRNA4 20q13.2 Neuronal nicotinic cholinergic receptor alpha polypeptide 4 Attentional function (Greenwood et al., 2005; Parasuraman et al., 2005) CHRNA7 15q13.3 Neuronal nicotinic cholinergic receptor alpha polypeptide 7 Schizophrenia and auditory processing (Leonard et al., 2002)
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We plan to examine direct associations between the genes in our SNP panel and the distal economic outcomes measured in the AGES-RS data -- for instance, labor force participation and housing wealth. We will also investigate whether these associations are mediated by proximal variables like cognitive function, brain morphology, and impatience.
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From page 326... ...
We think that there is potential for productive collaboration between economists, cognitive scientists, epidemiologists, and genetic researchers. Indeed, we end by summarizing a study that is currently under way, which uses a SNP panel to analyze associations between candidate cognitive genes and economic phenotypes.
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. Genetic variation in DTNBP1 influences general cognitive ability.
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. Nicastrin gene polymorphisms, cognitive ability level and cognitive ageing.
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American Journal of Medical Genetics Part B: Neuropsychiatric Genetics, 134(1)
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Human Molecular Genetics, 8(5)
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. Cognitive functioning and sex steroid hormone gene polymorphisms in women at midlife.
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. Candidate genes for human brain evolution: Do they relate to head size and cognitive ability?
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gene is associated with cognitive ability. Molecular Psychiatry, 9(6)
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: A review of clinical, molecular, and evolutionary findings. American Journal of Human Genetics, 76, 717-728.
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Human Molecular Genetics, 15(12)
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