Polygenic indexes (PGIs) are DNA-based predictors. Their value for research in many scientific disciplines is rapidly growing. As a resource for researchers, we used a consistent methodology to construct PGIs for 47 phenotypes in 11 datasets. To maximize the PGIs' prediction accuracies, we constructed them using genome-wide association studies - some of which are novel - from multiple data sources, including 23andMe and UK Biobank. We present a theoretical framework to help interpret analyses involving PGIs. A key insight is that a PGI can be understood as an unbiased but noisy measure of a latent variable we call the "additive SNP factor." Regressions in which the true regressor is the additive SNP factor but the PGI is used as its proxy therefore suffer from errors-in-variables bias. We derive an estimator that corrects for the bias, illustrate the correction, and make a Python tool for implementing it publicly available.

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Polygenic scores offer developmental psychologists new methods for integrating genetic information into research on how people change and develop across the life span. Indeed, polygenic scores have correlations with developmental outcomes that rival correlations with traditional developmental psychology variables, such as family income. Yet linking people's genetics with differences between them in socially valued developmental outcomes, such as educational attainment, has historically been used to justify acts of state-sponsored violence. In this review, we emphasize that an interdisciplinary understanding of the environmental and structural determinants of social inequality, in conjunction with a transactional developmental perspective on how people interact with their environments, is critical to interpreting associations between polygenic measures and phenotypes. While there is a risk of misuse, early applications of polygenic scores to developmental psychology have already provided novel findings that identify environmental mechanisms of life course processes that can be used to diagnose inequalities in social opportunity. Expected final online publication date for the Annual Review of Developmental Psychology, Volume 2 is December 15, 2020. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Personality is not the most popular subfield of psychology. But, in one way or another, personality psychologists have played an outsized role in the ongoing “credibility revolution” in psychology. Not only have individual personality psychologists taken on visible roles in the movement, but our field’s practices and norms have now become models for other fields to emulate (or, for those who share Baumeister’s (2016, https://doi.org/10.1016/j.jesp.2016.02.003) skeptical view of the consequences of increasing rigor, a model for what to avoid). In this article we discuss some unique features of our field that may have placed us in an ideal position to be leaders in this movement. We do so from a subjective perspective, describing our impressions and opinions about possible explanations for personality psychology’s disproportionate role in the credibility revolution. We also discuss some ways in which personality psychology remains less-than-optimal, and how we can address these flaws.

Background: More highly educated parents tend to raise children who go on to complete more education themselves. Strong evidence for environmental transmission arises from the fact that offspring outcomes correlate to parental genotypes even when controlling for the offspring genotype. The process that gives rise to an environmentally mediated correlation between parental genotype and offspring education (“indirect genetic effects”) remains poorly understood. A key question is whether intergenerational transmission reflects within-family processes, such as parenting behaviors (i.e. “Genetic nurture”), or social inheritance that could reflect either genetic ancestry or social stratification (i.e. “Dynastic effects”). Methods: We analyzed data from N = 25,215 genotyped parent-offspring trios participating in the Norwegian Mother, Father, and Child Cohort Study (MoBa), where many of the participants in the parental generation are siblings (N = 3,500 sibling pairs). We correlate genetic differences within the parental family, conditional on offspring genetics to offspring’s educational outcomes. The strategy isolates indirect genetic effects that play out in the nuclear family from indirect genetic effects that arise through social or ancestral genetic stratification. We additionally partition genetic variants associated with EA into those associated with cognitive versus non-cognitive skills. Results: We find that children’s genetics, measured using polygenic indices (PGIs) for cognitive and non-cognitive components of EA, are associated with their educational performance. Parents’ genetics are also associated with their children’s educational performance, over and above the child’s own genetics. However, we find no evidence that parents’ PGI are specifically related to offspring academic achievement over and above the average PGI of the siblings in the parental generation. Conclusions: Our result suggests that the effects of the environmental processes captured by genome-wide association studies of EA and characterized as “nurture” are explained less by parents’ specific behaviors and more by dynastic stratification in environments relevant to success in school.