They meta-analyze whether race or ethnicity moderate the heritability of intelligence in the US; find moderate to high heritabilities that do not substantially differ by race or ethnicity

Racial and ethnic group differences in the heritability of intelligence: A systematic review and meta-analysis. Bryan J.Pesta et al. Intelligence, Volume 78, January–February 2020, 101408. https://doi.org/10.1016/j.intell.2019.101408

Highlights
•    We meta-analyze whether race or ethnicity moderate the heritability of intelligence.
•    The main sample (k = 16) was comprised of Whites Blacks, and Hispanics from the USA.
•    We found moderate to high heritabilities for both groups.
•    Heritabilities, however, did not substantially differ by race or ethnicity.
•    Results are largely inconsistent with predictions from the Scarr-Rowe hypothesis.

Abstract: Via meta-analysis, we examined whether the heritability of intelligence varies across racial or ethnic groups. Specifically, we tested a hypothesis predicting an interaction whereby those racial and ethnic groups living in relatively disadvantaged environments display lower heritability and higher environmentality. The reasoning behind this prediction is that people (or groups of people) raised in poor environments may not be able to realize their full genetic potentials. Our sample (k = 16) comprised 84,897 Whites, 37,160 Blacks, and 17,678 Hispanics residing in the United States. We found that White, Black, and Hispanic heritabilities were consistently moderate to high, and that these heritabilities did not differ across groups. At least in the United States, Race/Ethnicity × Heritability interactions likely do not exist.


1. Introduction

In behavioral genetic research, individual variance in cognitive ability is commonly partitioned into three components. The first is the additive genetic component (a2, also known as h2), which refers to genetic effects on a trait that act additively. This component is called (narrow) “heritability.” The second component is the common or shared environment (c2), which denotes environmental effects that make family members more similar. The third component is the unshared environment (e2), which consists of non-genetic effects (plus measurement error) that are not shared between family members, but which instead differentiate them from each other. Collectively, the last two components are known as “environmentality” (Plomin, DeFries, Knopik, & Neiderhiser, 2014).

These three components together comprise the “ACE” model of behavioral genetics. The model represents one basic, biometric framework behavioral geneticists may use when studying the heritability of human traits, including intelligence. The ACE model assumes that environmental and genetic influences are additive, but allows that interactions (e.g., A × E) may also exist between components; these can be estimated as well (Plomin et al., 2014; Vinkhuyzen, van der Sluis, Maes, & Posthuma, 2012). Moreover, the model is useful in intelligence research because the behavioral genetic architecture of the trait is “surprisingly simple” (Plomin et al., 2014, p. 200). Finally, the ACE model nicely fits IQ data, and ACE estimates do not require the use of cumbersome kinship designs.

The relative importance of genetic and environmental sources of individual differences in cognitive ability has been extensively studied. Results for the general population show that the proportion of variance in IQ explained by genes increases with age (Plomin et al., 2014). Specifically, in early childhood, genetic effects explain less than 50% of IQ variance, and the effect of the shared environment is relatively strong. As children age, though, genetic effects become increasingly prominent, and the environmental variance due to factors common to siblings decreases. In adults, the heritability of intelligence is 60–80%, while the effect of common environment is small, if not zero (Plomin et al., 2014). The unshared environment explains the rest.

The degree to which one can generalize heritability estimates to other populations has been debated (see, e.g., Sesardic, 2005). It is clear, though, that some variables (e.g., age; Plomin et al., 2014) moderate the heritability of cognitive ability. One putative moderator is the quality of one’s environment. Poorer (richer) environments supposedly correspond to lower (higher) heritability, to a presumably measurable degree. Said differently, “natural potentials for adaptive functioning are more fully expressed in the context of more nourishing environmental experiences” (Tucker-Drob & Bates, 2016, p. 1). This prediction is known as the Scarr-Rowe hypothesis (Scarr-Salapatek, 1971; Turkheimer, Harden, D’onofrio, & Gottesman, 2011).

The Scarr-Rowe hypothesis predicts lower heritabilities for lower performing social classes and racial/ethnic groups (Scarr-Salapatek, 1971, p. 1286). Scarr-Salapatek’s (1971) original hypothesis and related ones – examples include the “Threshold Hypothesis” (Jensen, 1968), the “Bio-ecological Model” (Bronfenbrenner & Ceci, 1994), and the “Gene–Gini Hypothesis” (Selita & Kovas, 2019) – predict that Scarr-Rowe interactions will result when there are environmental differences. Assuming that social class and racial/ethnic differences are largely environmental in origin, Scarr-Salapatek (1971) and others have predicted lower heritabilities for the lower scoring groups.

Does the heritability of human intelligence differ by either social class or race/ethnicity? The answer is complicated because variables like age and the country sampled can moderate the effects. For example, a meta-analysis by Tucker-Drob and Bates (2016) found greater heritability with higher socioeconomic status, but these effects existed only with participants from the United States. Regarding age, recent data from Germany suggest the existence of a Scarr-Rowe interaction, but one which declines with increasing age (Gottschling et al., 2019).

While Scarr-Rowe interactions for social class are relatively well-studied, interactions for race or ethnicity are less so. Hence, whether Scarr-Rowe interactions for race or ethnicity exist is unclear. Some reviews suggest that the heritability of intelligence is similar across cultures (Plomin et al., 2014) and ethnic groups (Jensen, 1998; Rushton & Jensen, 2005). Others suggest differently (Turkheimer, Harden, & Nisbett, 2017).

The issue is relevant for several reasons, including evaluating the trans-ethnic validity of polygenic scores. Recently, Lee et al. (2018) developed polygenic scores for both intelligence and educational levels. These scores were derived from European samples and they showed lower predictive accuracy in non-European groups such as African Americans. The typical explanation offered for attenuated predictive accuracy is decay of linkage disequilibrium (LD) which results in differences in the correlations between SNPs across different ancestry groups (Zanetti & Weale, 2018). Another hypothesis appeals to lower within-group heritability in non-White groups (see, e.g., Rabinowitz et al., 2019). Both explanations are plausible since the predictive accuracy of polygenic scores is a joint function of (1) the validity of the scores as predictors of the traits, and (2) the within-group heritability of the traits in question (i.e., the association between the genotype and the phenotype; Daetwyler, Villanueva, & Woolliams, 2008). While LD decay might be a theoretically adequate explanation for attenuated predictive accuracy of PGS (Zanetti & Weale, 2018), whether it is the actual explanation can only be properly evaluated when the heritabilities of the trait within the different subgroups are known.

Our aim is to shed light on these matters by conducting a systematic review and meta-analysis. The goal is to test for the presence of Scarr-Rowe interactions with respect to race/ethnicity. Our specific research question is whether the heritability of intelligence differs across racial/ethnic groups residing in the United States (we searched for studies worldwide but found only samples from this country).