We argue that Madole & Harden's distinction between shallow versus deep genetic causes can bring some clarity to causal claims arising from genome-wide association studies (GWASs). However, the authors argue that GWAS only finds shallow genetic causes, making GWAS commensurate with the environmental studies they hope to supplant. We also assess whether their distinction applies best to explanations or causes.

Behavior genetics often emphasizes methods over the underlying quality of the psychological information to which the methods are applied. A core aspect of this quality is the demographic diversity of the samples. Building causal genetic models based only on European-ancestry samples compromises their generalizability. Behavior genetics researchers must spend additional time and resources diversifying their samples before emphasizing causation.

The overarching theme of causality in behavioral genetics is discussed on epistemological grounds. Evidence is offered in favor of a continuum spectrum in causality, in contrast to discrimination between causal factors and associations. The risk of invalidating exploratory studies in behavior genetics is discussed, especially for the potential impact on those fields of medicine interested in complex behaviors.

The view advanced by Madole & Harden falls back on the dogma of a gene as a DNA sequence that codes for a fixed product with an invariant function regardless of temporal and spatial contexts. This outdated perspective entrenches the metaphor of genes as static units of information and glosses over developmental complexities.

The methodological shift from twin studies to genome-wide association studies (GWASs) diminished estimates of true genetic causation underlying statistical heritability of behavioral differences. The sum total of causal genetic influence on behavior is not zero, but, (a) no one cited in the target article ever thought this was the case, and (b) there is still little known about concrete instances of genetic causation.

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.

The sociogenomics revolution is upon us, we are told. Whether revolutionary or not, sociogenomics is poised to flourish given the ease of incorporating polygenic scores (or PGSs) as “genetic propensities” for complex traits into social science research. Pointing to evidence of ubiquitous heritability and the accessibility of genetic data, scholars have argued that social scientists not only have an opportunity but a duty to add PGSs to social science research. Social science research that ignores genetics is, some proponents argue, at best partial and likely scientifically flawed, misleading, and wasteful. Here, I challenge arguments about the value of genetics for social science and with it the claimed necessity of incorporating PGSs into social science models as measures of genetic influences. In so doing, I discuss the impracticability of distinguishing genetic influences from environmental influences because of non-causal gene–environment correlations, especially population stratification, familial confounding, and downward causation. I explain how environmental effects masquerade as genetic influences in PGSs, which undermines their raison d’être as measures of genetic propensity, especially for complex socially contingent behaviors that are the subject of sociogenomics. Additionally, I draw attention to the partial, unknown biology, while highlighting the persistence of an implicit, unavoidable reductionist genes versus environments approach. Leaving sociopolitical and ethical concerns aside, I argue that the potential scientific rewards of adding PGSs to social science are few and greatly overstated and the scientific costs, which include obscuring structural disadvantages and cultural influences, outweigh these meager benefits for most social science applications.

In her target article, Burt revives a by now ancient debate on nature and nurture, and the ways to measure, disentangle, and ultimately trust one or the other of these forces. Unfortunately, she largely dismisses recent advances in behavior genetics and its huge potential in contributing to a better prediction and understanding of complex traits in social sciences.

“Challenging the utility of polygenic scores for social science” is a compelling but limited critique. Phenotypic development is sensitive to both initial conditions and all subsequent states – from conception to senescence. Thus, gene-centric analyses are misleading (and often meaningless) because gene products are transformed, and their phenotypic ‘effects' combined and attenuated with successive propagations from molecular and cellular contexts to organismal and social environments.

Although Burt clearly explains how modern genomic techniques work, and describes their limitations, her conclusion that they are therefore not valuable additions to understanding social outcomes is unwarranted. Understanding the causes of complex social outcomes depends on understanding how social, individual, and genetic factors complexly interact with each other. None can be understood without reference to the others.

In discussing the relationship between genetically influenced differences and educational attainment (EA), Burt employs the concept of downward causation. I note the similarities between Burt's concept of downward causation and the sociogenomics concept of vertical pleiotropy and argue that her discussion of downward causation introduces an unnecessary normative component. The core problem concerns not the appropriateness of phenotypes that influence EA but mistaken assumptions about which phenotypes are being predicted.

The problems with polygenic scores (PGSs) have been understated. The fact that they are ancestry-specific means that biases related to sociodemographic factors would be impossible to avoid. Additionally, the requirement to obtain DNA would have profound impacts on study design and required resources, as well as likely introducing recruitment bias. PGSs are unhelpful for social science research.

This commentary seeks to briefly outline a clear-eyed middle ground between Burt's claims that the inclusion of polygenic scores (PGSs) is essentially useless for social science and proponents' vast overstatements and over-interpretations of these scores. Current practice of including PGSs in social science is often wrong but sometimes useful.

Polygenic scores (PGSs) have several limitations. They are confounded with environmental effects on behavior and cannot be used to study how mutations affect brain function and behavior. For this, mutations with large effects, which often arise in only one geographical population are needed. Genome-wide association studies (GWASs), commonly used for identifying mutations, have difficulty detecting these mutations. A strategy that overcomes this challenge is discussed.

This commentary is a call to action for researchers to create and use genome-wide association studies (GWASs) with previously missed age groups (e.g., infancy, elderly), which will improve our ability to ask important developmental questions using genetic data to trace pathways across the lifespan.

We generally agree with Burt's thesis. However, we note that the author did not discuss epigenetics, the study of how the environment can alter gene structure and function. Given epigenetic mechanisms, the utility of polygenic risk scores (PRS) is limited in studies of development and mental illness. Finally, in this commentary we expand upon the risks of reliance upon PRSs.

Burt's target article oddly misses the important intellectual contribution of sociogenomics to our understanding of genetic evolution in contemporary human populations. Although social scientists' immediate research agendas are often not evolutionary in nature, I call for a better appreciation of the role of sociogenomics in answering important evolutionary questions.

Influences on social traits involve a tangled interplay of genetic, social, and environmental factors. Moreover, there is increasing awareness that gene–environment correlations are real and potentially measurable. Such gene–environment correlations can mislead if they are uncontrolled and genetic associations are interpreted as being purely because of direct genetic effects. This complexity is cause for more and better investigation, not a reason to refrain from researching one of the potentially important factors (genetics) influencing trait variation.

This commentary expands on Burt's concept of downward causation to include any association between genomic variants and a given outcome that is forged through social practices rather than biochemical pathways. It proposes the social stratification of population, through which endogamy over a period of generations produces allele frequency differences between socioeconomic strata, as a mechanism of downward causation.

Polygenic scores cannot elucidate the mechanisms that produce behavioral phenotypes (including “intelligence”). Therefore, they are unlikely to yield helpful interventions. Moreover, they are poor predictors of individuals' developmental outcomes. Burt's critique is well-supported by the details of molecular biology. Specifically, experiences affect epigenetic factors that influence phenotypes via how the genome functions, a fact that lends support to Burt's conclusions.