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Autistic individuals experience significantly elevated rates of childhood trauma, self-harm and suicidal behaviour and ideation (SSBI). Is this purely the result of negative environmental experiences, or does this interact with genetic predisposition? In this study we investigated if a genetic predisposition for autism is associated with childhood trauma using polygenic scores (PGS) and genetic correlations in the UK Biobank (105,222 < N < 105,638), and tested potential mediators and moderators of the association between autism, childhood trauma and SSBI. Autism PGS were significantly associated with childhood trauma (max R2 = 0.096%, P < 2 × 10-16), self-harm ideation (max R2 = 0.108%, P < 2 × 10-16), and self-harm (max R2 = 0.13%, P < 2 × 10-16). Supporting this, we identified significant genetic correlations between autism and childhood trauma (rg = 0.36 ± 0.05, P = 8.13 × 10-11), self-harm ideation (rg = 0.49 ± 0.05, P = 4.17 × 10-21) and self-harm (rg = 0.48 ± 0.05, P = 4.58 × 10-21), and an over-transmission of PGS for the two SSBI phenotypes from parents to autistic probands. Male sex negatively moderated the effect of autism PGS on childhood trauma (β = -0.023 ± 0.005, P = 6.74 × 10-5). Further, childhood trauma positively moderated the effect of autism PGS on self-harm score (β = 8.37 × 10-3 ± 2.76 × 10-3, P = 2.42 × 10-3) and self-harm ideation (β = 7.47 × 10-3 ± 2.76 × 10-3, P = 6.71 × 10-3). Finally, depressive symptoms, quality and frequency of social interactions, and educational attainment were significant mediators of the effect of autism PGS on SSBI, with the proportion of effect mediated ranging from 0.23 (95% CI: 0.09-0.32) for depression to 0.008 (95% CI: 0.004-0.01) for educational attainment. Our findings identify that a genetic predisposition for autism is associated with adverse life-time outcomes, which represent complex gene-environment interactions, and prioritizes potential mediators and moderators of this shared biology. It is important to identify sources of trauma for autistic individuals in order to reduce their occurrence and impact.
Pubmed ID: 31659270
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Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.
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