“Polygenic Influences Associated With Adolescent Cognitive Skills”, Brittany L. Mitchell, Narelle K. Hansell, Kerrie McAloney, Nicholas G. Martin, Margaret J. Wright, Miguel E. Renteria, Katrina L. Grasby2022-09 (, , , , , )⁠:

Genes play an important role in children’s cognitive ability through adolescence and into adulthood. Recent advances in genomics have enabled us to test the effect of various genetic predispositions on measured cognitive outcomes.

Here, we leveraged summary statistics from the most recent genome-wide association studies of 11 cognitive and mental health traits to build polygenic prediction models of measured intelligence and academic skills in a cohort of Australian adolescent twins (n = 2,335, 57% female).

We show that polygenic risk scores for educational attainment, intelligence, and cognitive performance explained up to 10% of the variance in academic skills and 7% in intelligence test scores in our cohort [using Lee et al 2018 EDU, Savage et al 2018 IQ, Demange et al 2020 cognitive/non-cognitive skills]. Additionally, we found that a genetic predisposition for ADHD was negatively associated with all cognitive measures and a genetic predisposition for schizophrenia was negatively associated with performance IQ but no other cognitive measure.

In this study, we provide evidence that a genetic vulnerability to some mental health disorders is associated with poorer performance on a variety of cognitive and academic tests, regardless of whether the individual has developed the disorder.

[Keywords: polygenic risk scores, education, cognition, mental health, genetics, adolescence, intelligence]

Figure 1: Genetic correlations between cognitive and psychiatric traits reveals highly heterogeneous genetic associations between mental health disorders and cognitive phenotypes.
Figure 2: Barplot depicting percentage variance explained in total QCST, full IQ (FIQ), performance IQ (PIQ) and verbal IQ (VIQ) scores by the respective PRSs. PRS were constructed for educational attainment, intelligence, cognitive skills and non-cognitive skills. Error bars represent 95% Confidence Intervals.
Table 2: Traits and their sources used for PRS construction using SBayesR. ✱ Sample sizes for the cognitive and non-cognitive skill factors are estimates using the output of genomic SEM. The traits themselves were not measured. † QIMR samples removed from GWAS summary statistics.
Trait Source N cases N controls SNP-based heritability (SE) Phenotypic Variance explained (%) in source study
Depression† Howard et al 2019 246,819 561,485 0.09 (0.003) 1.5–3.2
Anxiety Purves et al 2020 25,453 58,113 0.26 (0.011) 0.5
bipolar disorder† Mullins et al 2021; Purves et al 2020 41,917 371,549 0.19 (0.006) 4.6
Schizophrenia Pardĩnas et al 2018 40,675 64,643 0.25 (0.007) 5.7
ADHD Demontis et al 2019 20,183 35,191 0.22 (0.014) 5.5
Anorexia Nervosa† Watson et al 2019 16,992 55,525 0.17 (0.01) 1.7
Autism Grove et al 2019 18,381 27,969 0.12 (0.01) 2.5
Educational Attainment† Lee et al 2018 1,100,000 NA 0.15 (0.009) 11–13
Intelligence† Savage et al 2018 269,867 NA 0.19 (0.01) 5.2
Cognitive skills Demange et al 2021 ✱ 510,795 NA 0.19 (0.006) Not reported
Non-Cognitive skills Demange et al 2021 ✱ 257,700 NA 0.06 (0.002) Not reported

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Polygenic Influences Associated With Adolescent Cognitive Skills