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The causal influence of brain size on human intelligence: Evidence from within-family phenotypic associations and GWAS modeling

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  • Lee, James J.
  • McGue, Matt
  • Iacono, William G.
  • Michael, Andrew M.
  • Chabris, Christopher F.

Abstract

There exists a moderate correlation between MRI-measured brain size and the general factor of IQ performance (g), but the question of whether the association reflects a theoretically important causal relationship or spurious confounding remains somewhat open. Previous small studies (n 〈100) looking for the persistence of this correlation within families failed to find a tendency for the sibling with the larger brain to obtain a higher test score. We studied the within-family relationship between brain volume and intelligence in the much larger sample provided by the Human Connectome Project (n = 1022) and found a highly significant correlation (disattenuated ρ = 0.18, p < .001). We replicated this result in the Minnesota Center for Twin and Family Research (n = 2698), finding a highly significant within-family correlation between head circumference and intelligence (disattenuated ρ = 0.19, p < .001). We also employed novel methods of causal inference relying on summary statistics from genome-wide association studies (GWAS) of head size (n ≈ 10,000) and measures of cognition (257,000 < n < 767,000). Using bivariate LD Score regression, we found a genetic correlation between intracranial volume (ICV) and years of education (EduYears) of 0.41 (p < .001). Using the Latent Causal Variable method, we found a genetic causality proportion of 0.72 (p < .001); thus the genetic correlation arises from an asymmetric pattern, extending to sub-significant loci, of genetic variants associated with ICV also being associated with EduYears but many genetic variants associated with EduYears not being associated with ICV. This is the pattern of genetic results expected from a causal effect of brain size on intelligence. These findings give reason to take up the hypothesis that the dramatic increase in brain volume over the course of human evolution has been the result of natural selection favoring general intelligence.

Suggested Citation

  • Lee, James J. & McGue, Matt & Iacono, William G. & Michael, Andrew M. & Chabris, Christopher F., 2019. "The causal influence of brain size on human intelligence: Evidence from within-family phenotypic associations and GWAS modeling," Intelligence, Elsevier, vol. 75(C), pages 48-58.
    • Handle: RePEc:eee:intell:v:75:y:2019:i:c:p:48-58
    DOI: 10.1016/j.intell.2019.01.011
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    References listed on IDEAS

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    1. Chabris, C.F. & Lee, J.J. & Benjamin, D.J. & Beauchamp, J.P. & Glaeser, E.L. & Borst, G. & Pinker, S. & Laibson, D.I., 2013. "Why it is hard to find genes associated with social science traits: Theoretical and empirical considerations," American Journal of Public Health, American Public Health Association, vol. 103(SUPPL.1), pages 152-166.
    2. Aysu Okbay & Jonathan P. Beauchamp & Mark Alan Fontana & James J. Lee & Tune H. Pers & Cornelius A. Rietveld & Patrick Turley & Guo-Bo Chen & Valur Emilsson & S. Fleur W. Meddens & Sven Oskarsson & Jo, 2016. "Genome-wide association study identifies 74 loci associated with educational attainment," Nature, Nature, vol. 533(7604), pages 539-542, May.
    3. Gignac, Gilles E. & Bates, Timothy C., 2017. "Brain volume and intelligence: The moderating role of intelligence measurement quality," Intelligence, Elsevier, vol. 64(C), pages 18-29.
    4. Matthew C Keller & Christine E Garver-Apgar & Margaret J Wright & Nicholas G Martin & Robin P Corley & Michael C Stallings & John K Hewitt & Brendan P Zietsch, 2013. "The Genetic Correlation between Height and IQ: Shared Genes or Assortative Mating?," PLOS Genetics, Public Library of Science, vol. 9(4), pages 1-10, April.
    5. Tune H. Pers & Juha M. Karjalainen & Yingleong Chan & Harm-Jan Westra & Andrew R. Wood & Jian Yang & Julian C. Lui & Sailaja Vedantam & Stefan Gustafsson & Tonu Esko & Tim Frayling & Elizabeth K. Spel, 2015. "Biological interpretation of genome-wide association studies using predicted gene functions," Nature Communications, Nature, vol. 6(1), pages 1-9, May.
    6. Chabris, C. F. & Lee, J. J. & Cesarini, D. & Benjamin, D. J. & Laibson, David I., 2015. "The Fourth Law of Behavior Genetics," Scholarly Articles 30780203, Harvard University Department of Economics.
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    1. Nagel, Mats, 2020. "Changing perspectives: Towards detailed phenotyping in genetics," Thesis Commons a4nz2, Center for Open Science.

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