Why are education, socioeconomic position and intelligence genetically correlated?

Abstract

Genetic associations and correlations are perceived as confirmation that genotype influences one or more phenotypes respectively. However, genetic correlations can arise from non-biological or indirect mechanisms including population stratification, dynastic effects, and assortative mating. In this paper, we outline these mechanisms and demonstrate available tools and analytic methods that can be used to assess their presence in estimates of genetic correlations and genetic associations. Using educational attainment and parental socioeconomic position data as an exemplar, we demonstrate that both heritability and genetic correlation estimates may be inflated by these indirect mechanisms. The results highlight the limitations of between-individual estimates obtained from samples of unrelated individuals and the potential value of family-based studies. Use of the highlighted tools in combination with within-sibling or mother-father-offspring trio data may offer researchers greater opportunity to explore the underlying mechanisms behind genetic associations and correlations and identify the underlying causes of estimate inflation.

Genetic correlates of socio-economic status influence the pattern of shared heritability across mental health traits

“…Our results also suggest a possible violation of an important assumption of Mendelian Randomization (MR) analyses, which states that the genetic variants included in the instrumental variable should be independent of factors (measured and unmeasured) that confound the exposure-outcome relationship 20,59 . SES is likely to be a confounder of MR analyses through its genetic associations with the genetic instruments for mental health phenotypes, which may affect results of MR studies aimed at establishing causal relationships across mental health traits, and other complex traits (e.g., BMI, longevity, and cardiovascular diseases).…”

“…Similar effects likely cause polygenic scores for educational attainment to be twice as predictive in non-adopted children as in adopted children 21 . These results highlight that genotype-phenotype associations based on samples of unrelated individuals may be confounded by external variables, especially by those that reflect complex social phenomena such as educational level 20 and SES.…”

“…Therefore, confounding factors, such as differences in environments, may bias genotype-phenotype associations and may therefore have an impact on estimates of SNP-based h 2 and genetic correlations. For example, recent studies have shown that genetic associations may be inflated by population phenomena, such as population stratification 3,19 , gene-environment correlation 19,20 , and assortative mating 20 . Abdellaoui et al showed significant geographic clustering of complex traits, even after controlling for ancestry 3 .…”

Mendelian Randomization analysis of the causal impact of body mass index and waist-hip ratio on rates of hospital admission

“…Additional sources of bias that should be considered in the context of MR and the UK Biobank data are assortative mating [56][57][58][59], confounding due to population stratification bias [59][60][61][62] and the presence of dynastic effects [59,61,63], which have all be implicated with respect to BMI previously. While we attempted to minimize the impact of population stratification with the inclusion of 40 genetic principle components, latent data structure may still exist for some exposures such as BMI [60].…”

Complexity, Genetic Causation, and Hereditarianism

“…Heritability and the newer polygenic scores say little about how traits would be distributed in different contexts. The effects of genetics on many features in humans are probably overstated because of estimation bias (Feldman and Ramachandran, 2018;Morris et al, 2019).…”