Potential corporate uses of polygenic indexes: Starting a conversation about the associated ethics and policy issues.

Some commercial firms currently sell polygenic indexes (PGIs) to individual consumers, despite their relatively low predictive power. It might be tempting to assume that because the predictive power of many PGIs is so modest, other sorts of firms-such as those selling insurance and financial services-will not be interested in using PGIs for their own purposes. We argue to the contrary. We build this argument in two ways. First, we offer a very simple model, rooted in economic theory, of a profit-maximizing firm that can gain information about a single consumer's genome. We use the model to show that, depending on the specific economic environment, a firm would be willing to pay for statistically noisy PGIs, even if they allow for only a small reduction in uncertainty. Second, we describe two plausible scenarios in which these different kinds of firms could conceivably use PGIs to maximize profits. Finally, we briefly discuss some of the associated ethics and policy issues. They deserve more attention, which is unlikely to be given until it is first recognized that firms whose services affect a large swath of the public will indeed have incentives to use PGIs.

Challenges in studying the interplay of genes and environment. A study of childhood financial distress moderating genetic predisposition for peak smoking.

Smoking is one of the leading causes of preventable disease and death in the U.S., and it is strongly influenced both by genetic predisposition and childhood adversity. Using polygenic indices (PGIs) of predisposition to smoking, we evaluate whether childhood financial distress (CFD; a composite measure of financial adversity) moderates genetic risk in explaining peak-cigarette consumption in adulthood. Using the Health and Retirement Study (HRS), we find a substantial reduction in the relationship between genetic risk and peak smoking for those who did not suffer financial adversity in childhood. Among adult smokers who grew up in high-CFD households, a one standard deviation higher PGI is associated with 2.9 more cigarettes smoked per day at peak. By contrast, among smokers who grew up in low-CFD households, this gradient is reduced by 37 percent (or 1.1 fewer). These results are robust to controlling for a host of prime confounders. By contrast, we find no evidence of interactions between the PGI and typical measures of childhood SES such as parental education - a null result that we replicate in the Wisconsin Longitudinal Study (WLS) and the English Longitudinal Study of Aging (ELSA). This suggests the role of childhood financial distress in the relationship with peak smoking is distinct from that of low childhood SES, with high CFD potentially reflecting more acute distress than do measures of low childhood SES. Our evidence also suggests low childhood SES is a weaker proxy for acute distress, providing an alternative explanation for the childhood SES null result.

Genetic Endowments and Wealth Inequality.

We show that genetic endowments linked to educational attainment strongly and robustly predict wealth at retirement. The estimated relationship is not fully explained by flexibly controlling for education and labor income. We therefore investigate a host of additional mechanisms that could account for the gene-wealth gradient, including inheritances, mortality, risk preferences, portfolio decisions, beliefs about the probabilities of macroeconomic events, and planning horizons. We provide evidence that genetic endowments related to human capital accumulation are associated with wealth not only through educational attainment and labor income, but also through a facility with complex financial decision-making.

Genes, Education, and Labor Market Outcomes: Evidence from the Health and Retirement Study.

Recent advances have led to the discovery of specific genetic variants that predict educational attainment. We study how these variants, summarized as a linear index-known as a polygenic score-are associated with human capital accumulation and labor market outcomes in the Health and Retirement Study (HRS). We present two main sets of results. First, we find evidence that the genetic factors measured by this score interact strongly with childhood socioeconomic status in determining educational outcomes. In particular, although the polygenic score predicts higher rates of college graduation on average, this relationship is substantially stronger for individuals who grew up in households with higher socioeconomic status relative to those who grew up in poorer households. Second, the polygenic score predicts labor earnings even after adjusting for completed education, with larger returns in more recent decades. These patterns suggest that the genetic traits that promote education might allow workers to better accommodate ongoing skill biased technological change. Consistent with this interpretation, we find a positive association between the polygenic score and nonroutine analytic tasks that have benefited from the introduction of new technologies. Nonetheless, the college premium remains a dominant determinant of earnings differences at all levels of the polygenic score. Given the role of childhood SES in predicting college attainment, this raises concerns about wasted potential arising from limited household resources.

Genome-wide association study identifies 74 loci associated with educational attainment.

Educational attainment is strongly influenced by social and other environmental factors, but genetic factors are estimated to account for at least 20% of the variation across individuals. Here we report the results of a genome-wide association study (GWAS) for educational attainment that extends our earlier discovery sample of 101,069 individuals to 293,723 individuals, and a replication study in an independent sample of 111,349 individuals from the UK Biobank. We identify 74 genome-wide significant loci associated with the number of years of schooling completed. Single-nucleotide polymorphisms associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioural phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because educational attainment is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric diseases.