Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction

Perline A Demange; Margherita Malanchini; Travis T Mallard; Pietro Biroli; Simon R Cox; Andrew D Grotzinger; Elliot M Tucker-Drob; Abdel Abdellaoui; Louise Arseneault; Elsje van Bergen; Dorret I Boomsma; Avshalom Caspi; David L Corcoran; Benjamin W Domingue; Kathleen Mullan Harris; Hill F Ip; Colter Mitchell; Terrie E Moffitt; Richie Poulton; Joseph A Prinz; Karen Sugden; Jasmin Wertz; Benjamin S Williams; Eveline L de Zeeuw; Daniel W Belsky; K Paige Harden; Michel G Nivard

doi:10.1038/s41588-020-00754-2

Investigating the genetic architecture of noncognitive skills using GWAS-by-subtraction

Nat Genet. 2021 Jan;53(1):35-44. doi: 10.1038/s41588-020-00754-2. Epub 2021 Jan 7.

Authors

Perline A Demange^#^{1

2

3}, Margherita Malanchini^#^{4

5

6}, Travis T Mallard⁶, Pietro Biroli⁷, Simon R Cox⁸, Andrew D Grotzinger⁶, Elliot M Tucker-Drob^{6

9}, Abdel Abdellaoui^{1

10}, Louise Arseneault⁵, Elsje van Bergen^{1

3}, Dorret I Boomsma¹, Avshalom Caspi^{5

11

12

13}, David L Corcoran¹², Benjamin W Domingue¹⁴, Kathleen Mullan Harris¹⁵, Hill F Ip¹, Colter Mitchell¹⁶, Terrie E Moffitt^{5

11

12

13}, Richie Poulton¹⁷, Joseph A Prinz¹², Karen Sugden¹¹, Jasmin Wertz¹¹, Benjamin S Williams¹¹, Eveline L de Zeeuw^{1

3}, Daniel W Belsky^{18

19}, K Paige Harden²⁰, Michel G Nivard²¹

Affiliations

¹ Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
² Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, Amsterdam, the Netherlands.
³ Research Institute LEARN!, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
⁴ Department of Biological and Experimental Psychology, Queen Mary University of London, London, UK.
⁵ Social, Genetic and Developmental Psychiatric Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.
⁶ Department of Psychology, University of Texas at Austin, Austin, TX, USA.
⁷ Department of Economics, University of Zurich, Zurich, Switzerland.
⁸ Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK.
⁹ Population Research Center, University of Texas at Austin, Austin, TX, USA.
¹⁰ Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands.
¹¹ Department of Psychology & Neuroscience, Duke University, Durham, NC, USA.
¹² Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA.
¹³ Center for Genomic and Computational Biology, Duke University, Durham, NC, USA.
¹⁴ Stanford Graduate School of Education, Stanford University, Palo Alto, CA, USA.
¹⁵ Department of Sociology and Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
¹⁶ Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.
¹⁷ Department of Psychology and Dunedin Multidisciplinary Health and Development Research Unit, University of Otago, Dunedin, New Zealand.
¹⁸ Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA. daniel.belsky@columbia.edu.
¹⁹ Robert N. Butler Columbia Aging Center, Columbia University, New York, NY, USA. daniel.belsky@columbia.edu.
²⁰ Department of Psychology, University of Texas at Austin, Austin, TX, USA. harden@utexas.edu.
²¹ Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands. m.g.nivard@vu.nl.

^# Contributed equally.

Abstract

Little is known about the genetic architecture of traits affecting educational attainment other than cognitive ability. We used genomic structural equation modeling and prior genome-wide association studies (GWASs) of educational attainment (n = 1,131,881) and cognitive test performance (n = 257,841) to estimate SNP associations with educational attainment variation that is independent of cognitive ability. We identified 157 genome-wide-significant loci and a polygenic architecture accounting for 57% of genetic variance in educational attainment. Noncognitive genetics were enriched in the same brain tissues and cell types as cognitive performance, but showed different associations with gray-matter brain volumes. Noncognitive genetics were further distinguished by associations with personality traits, less risky behavior and increased risk for certain psychiatric disorders. For socioeconomic success and longevity, noncognitive and cognitive-performance genetics demonstrated associations of similar magnitude. By conducting a GWAS of a phenotype that was not directly measured, we offer a view of genetic architecture of noncognitive skills influencing educational success.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Brain / diagnostic imaging
Cognition*
Decision Making
Educational Status
Fertility
Genome-Wide Association Study*
Humans
Intelligence
Mental Disorders / genetics
Models, Genetic
Molecular Sequence Annotation
Multifactorial Inheritance / genetics
Personality
Phenotype
Polymorphism, Single Nucleotide / genetics
Risk-Taking

Abstract

Publication types

MeSH terms

Grants and funding