Abstract
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.
Highlights
We investigated the association between polygenic risk scores derived from genome-wide association studies (GWAS) of these disorders and facial emotion recognition phenotypes to assess whether genetic correlations mirror reported comorbidities
The unbiased hit rate represents the proportion of correct responses for a given emotion, weighted by the number of times the participant gave that response for the wrong face (Eq 2)
Multiple analyses were performed across five Diagnostic Analysis of Non-Verbal Accuracy (DANVA) phenotypes, using results from seven external GWAS studies
Summary
Disorders, including autism (Harms, Martin, & Wallace, 2010), schizophrenia (Kohler, Walker, Martin, Healey, & Moberg, 2010), Emotion permeates everyday social interaction and represents a depression (Bourke, Douglas, & Porter, 2010; Kohler, Hoffman, central component of human (and other primate) societies (Brothers, Eastman, Healey, & Moberg, 2011), bipolar disorder (Kohler et al., 1990; Ekman, 2007; Salovey & Mayer, 1989). There has been a considerable literature linking 5HTTLPR to amygdala activation, including in response to emotional faces (Canli & Lesch, 2007) These studies use a candidate gene approach, which is limited by focusing on a few regions of assumed relevance, and usually relies on small sample sizes that are underpowered to detect likely effect sizes (Dick et al, 2015; Ioannidis, 2003). Large GWAS of these disorders exist, and may predict variance in emotion recognition in the present cohort (Otowa et al, 2016; Ripke et al, 2013; Schizophrenia Working Group of the Psychiatric Genomics C, 2014; Sklar et al, 2011). We used polygenic risk score analysis to predict individual differences in emotion recognition within this cohort, using polygenic risk scores from studies of psychiatric disorders in which emotion recognition is impaired
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Schedule a callMore From: American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics
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