Genome-wide association study of facial emotion recognition in children and association with polygenic risk for mental health disorders

Jonathan R.I. Coleman, Kathryn J. Lester, Robert Keers, Marcus R. Munafò, Gerome Breen, Thalia C. Eley*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

17 Citations (Scopus)
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Emotion recognition is disrupted in many mental health disorders, which may reflect shared genetic aetiology between this trait and these disorders. We explored genetic influences on emotion recognition and the relationship between these influences and mental health phenotypes. Eight-year-old participants (n=4,097) from the Avon Longitudinal Study of Parents and Children (ALSPAC) completed the Diagnostic Analysis of Non-Verbal Accuracy (DANVA) faces test. Genome-wide genotype data was available from the Illumina HumanHap550 Quad microarray. Genome-wide association studies were performed to assess associations with recognition of individual emotions and emotion in general. Exploratory polygenic risk scoring was performed using published genomic data for schizophrenia, bipolar disorder, depression, autism spectrum disorder, anorexia, and anxiety disorders. No individual genetic variants were identified at conventional levels of significance in any analysis although several loci were associated at a level suggestive of significance. SNP-chip heritability analyses did not identify a heritable component of variance for any phenotype. Polygenic scores were not associated with any phenotype. The effect sizes of variants influencing emotion recognition are likely to be small. Previous studies of emotion identification have yielded non-zero estimates of SNP-heritability. This discrepancy is likely due to differences in the measurement and analysis of the phenotype.
Original languageEnglish
Number of pages11
JournalAmerican Journal of Medical Genetics, Part B: Neuropsychiatric Genetics
Early online date13 Jun 2017
Publication statusE-pub ahead of print - 13 Jun 2017

Structured keywords

  • Brain and Behaviour
  • Tobacco and Alcohol


  • Faces
  • Genetics
  • Genomics
  • Polygenic risk scores


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