Alexithymia traits outweigh autism traits in the explanation of depression in adults with autism

Carola Bloch,Lana Burghof,Fritz-Georg Lehnhardt,Christine Falter-Wagner,Kai Vogeley

doi:10.1038/s41598-021-81696-5

Abstract

When contemplating the alarming depression rates in adults with autism spectrum disorder (ASD), there is a need to find factors explaining heightened symptoms of depression. Beyond the impact of autism traits, markedly increased levels of alexithymia traits should be considered as a candidate for explaining why individuals with ASD report higher levels of depressive symptoms. Here, we aim to identify the extent to which autism or alexithymia traits indicate depressive symptoms in ASD and whether the pattern of association are specific to ASD. Data of a large (N = 400) representative clinical population of adults referred to autism diagnostics have been investigated and split by cases with a confirmed ASD diagnosis (N = 281) and cases with a ruled out ASD diagnosis (N = 119). Dominance analysis revealed the alexithymia factor, difficulties in identifying feelings, as the strongest predictor for depressive symptomatology in ASD, outweighing autism traits and other alexithymia factors. This pattern of prediction was not specific to ASD and was shared by clinical controls from the referral population with a ruled out ASD diagnosis. Thus, the association of alexithymia traits with depression is not unique to ASD and may constitute a general psychopathological mechanism in clinical samples.

Highlights

When contemplating the alarming depression rates in adults with autism spectrum disorder (ASD), there is a need to find factors explaining heightened symptoms of depression
Regarding correlations with depressive symptoms in the ASD + sample, Beck Depression Inventory (BDI) scores significantly increased with Autism-Spectrum Quotient (AQ) (r = 0.25, p < 0.001, 95% CI [0.13, 0.35]), Difficulties in Identifying Feelings (DIF) (r = 0.41, p < 0.001, 95% CI [0.31, 0.51]), and Difficulties Describing Feelings (DDF) (r = 0.26, p < 0.001, 95% CI [0.15, 0.37]), but not with Externally-Oriented Thinking (EOT) (r = − 0.03, p = 0.643, 95% CI [ − 0.14, 0.09])
Considering correlations of autism and alexithymia traits in the ASD + sample, DIF significantly increased with AQ (r = 0.52, p < 0.001, 95% CI [0.43, 0.60]) and DDF (r = 0.47, p < 0.001, 95% CI [0.38, 0.56])

Summary

Introduction

When contemplating the alarming depression rates in adults with autism spectrum disorder (ASD), there is a need to find factors explaining heightened symptoms of depression. By observing ASD and alexithymia as parallel factors for depression, Fietz and colleagues applied structural equation models on data from an online study addressed to participants from the general population[25] They showed that autism and alexithymia traits had medium-sized effects on depression. The aims of the current study are to (a) clarify whether autism traits or alexithymia traits better explain depressive symptoms in adults with ASD, (b) establish whether there is a differential predictive power of the three alexithymia traits, and (c) determine whether such predictive associations with depression are specific to ASD For this purpose, we analyzed data of a representative clinical population of adults referred to outpatient clinics for autism diagnostics.

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Conclusion