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Polygenic Scores for Cognitive Abilities and Their Association with Different Aspects of General Intelligence-A Deep Phenotyping Approach.

Authors
  • Genç, Erhan1, 2
  • Schlüter, Caroline3
  • Fraenz, Christoph4, 3
  • Arning, Larissa5
  • Metzen, Dorothea3
  • Nguyen, Huu Phuc5
  • Voelkle, Manuel C6
  • Streit, Fabian7
  • Güntürkün, Onur3
  • Kumsta, Robert8
  • Ocklenburg, Sebastian3
  • 1 Department of Psychology and Neurosciences, Neuroimaging and Interindividual Differences, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany. [email protected] , (Germany)
  • 2 Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany. [email protected] , (Germany)
  • 3 Department of Biopsychology, Institute of Cognitive Neuroscience, Ruhr University Bochum, Bochum, Germany. , (Germany)
  • 4 Department of Psychology and Neurosciences, Neuroimaging and Interindividual Differences, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Dortmund, Germany. , (Germany)
  • 5 Department of Human Genetics, Ruhr University Bochum, Bochum, Germany. , (Germany)
  • 6 Department of Psychological Research Methods, Institute of Psychology, Humboldt University Berlin, Berlin, Germany. , (Germany)
  • 7 Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany. , (Germany)
  • 8 Department of Genetic Psychology, Ruhr University Bochum, Bochum, Germany. , (Germany)
Type
Published Article
Journal
Molecular neurobiology
Publication Date
Aug 01, 2021
Volume
58
Issue
8
Pages
4145–4156
Identifiers
DOI: 10.1007/s12035-021-02398-7
PMID: 33954905
Source
Medline
Keywords
Language
English
License
Unknown

Abstract

Intelligence is a highly polygenic trait and genome-wide association studies (GWAS) have identified thousands of DNA variants contributing with small effects. Polygenic scores (PGS) can aggregate those effects for trait prediction in independent samples. As large-scale light-phenotyping GWAS operationalized intelligence as performance in rather superficial tests, the question arises which intelligence facets are actually captured. We used deep-phenotyping to investigate the molecular determinants of individual differences in cognitive ability. We, therefore, studied the association between PGS of intelligence (IQ-PGS), cognitive performance (CP-PGS), and educational attainment (EA-PGS) with a wide range of intelligence facets in a sample of 557 healthy adults. IQ-PGS, CP-PGS, and EA-PGS had the highest incremental R2s for general (2.71%; 4.27%; 2.06%), verbal (3.30%; 4.64%; 1.61%), and numerical intelligence (3.06%; 3.24%; 1.26%) and the weakest for non-verbal intelligence (0.89%; 1.47%; 0.70%) and memory (0.80%; 1.06%; 0.67%). These results indicate that PGS derived from light-phenotyping GWAS do not reflect different facets of intelligence equally well, and thus should not be interpreted as genetic indicators of intelligence per se. The findings refine our understanding of how PGS are related to other traits or life outcomes. © 2021. The Author(s).

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