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Dysregulation of biological stress response, as measured by cortisol output, has been a primary candidate mechanism for how social experiences become biologically embedded. Cortisol is the primary output of the hypothalamic pituitary adrenal (HPA) axis. Cortisol levels vary systematically across the day and change in response to both sudden, acute stress experiences as well as prolonged exposure to environmental stress. Using data from 8- to 15-year-old twins in the Texas Twin Project, we investigate the extent to which genetic influences are shared across different measures of cortisol output: chronic cortisol accumulations in hair (n = 1,104), diurnal variation in salivary output (n = 488), and salivary response to a standardized, acute in-laboratory stressor (n = 537). Multivariate twin models indicate that genetic factors regulating cortisol response to the in-laboratory stressor are separable from those regulating baseline cortisol levels, naturally occurring diurnal variation in cortisol, and hair cortisol levels. These findings illustrate that novel environments can reveal unique genetic variation, reordering people in terms of their observed phenotype rather than only magnifying or mitigating preexisting differences.

Behaviors and disorders related to self-regulation, such as substance use, antisocial behavior and attention-deficit/hyperactivity disorder, are collectively referred to as externalizing and have shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 genetic loci. The loci were enriched for genes expressed in the brain and related to nervous system development. A polygenic score constructed from our results predicts a range of behavioral and medical outcomes that were not part of genome-wide analyses, including traits that until now lacked well-performing polygenic scores, such as opioid use disorder, suicide, HIV infections, criminal convictions and unemployment. Our findings are consistent with the idea that persistent difficulties in self-regulation can be conceptualized as a neurodevelopmental trait with complex and far-reaching social and health correlates.

Exposure to adverse environments during childhood is robustly linked to future aggressive behavior. In this study we tested a model of emotional and neurocognitive mechanisms related to aggressive behavior in the context of childhood adversity. More specifically, we used path analysis to assess the distal contribution of childhood adversity and the more proximal contributions of emotion-related and non-emotion-related forms of impulsivity, and behavioral response inhibition to aggressive behavior. Participants were 180 undergraduates who completed well-validated self-report measures and an emotional version of the Go/No-Go task. The structural equation model was a poor fit for the data (χ2(3) = 23.023, p

We received 23 spirited commentaries on our target article from across the disciplines of philosophy, economics, evolutionary genetics, molecular biology, criminology, epidemiology, and law. We organize our reply around three overarching questions: (1) What is a cause? (2) How are randomized controlled trials (RCTs) and within-family genome-wide association studies (GWASs) alike and unalike? (3) Is behavior genetics a qualitatively different enterprise? Throughout our discussion of these questions, we advocate for the idea that behavior genetics shares many of the same pitfalls and promises as environmentally oriented research, medical genetics, and other arenas of the social and behavioral sciences. [ABSTRACT FROM AUTHOR]

Behavior genetics is a controversial science. For decades, scholars have sought to understand the role of heredity in human behavior and life-course outcomes. Recently, technological advances and the rapid expansion of genomic databases have facilitated the discovery of genes associated with human phenotypes such as educational attainment and substance use disorders. To maximize the potential of this flourishing science, and to minimize potential harms, careful analysis of what it would mean for genes to be causes of human behavior is needed. In this paper, we advance a framework for identifying instances of genetic causes, interpreting those causal relationships, and applying them to advance causal knowledge more generally in the social sciences. Central to thinking about genes as causes is counterfactual reasoning, the cornerstone of causal thinking in statistics, medicine, and philosophy. We argue that within-family genetic effects represent the product of a counterfactual comparison in the same way as average treatment effects (ATEs) from randomized controlled trials (RCTs). Both ATEs from RCTs and within-family genetic effects are shallow causes: They operate within intricate causal systems (non-unitary), produce heterogeneous effects across individuals (non-uniform), and are not mechanistically informative (non-explanatory). Despite these limitations, shallow causal knowledge can be used to improve understanding of the etiology of human behavior and to explore sources of heterogeneity and fade-out in treatment effects. [ABSTRACT FROM AUTHOR]