Network Analysis of Behaviors in the Depression and Autism Realms: Inter-Relationships and Clinical Implications

Abstract

Depression-, anxiety-, OCD- and autism-related behaviors were assessed in 118 high-functioning individuals with autism spectrum disorders (ASD) and in 2016 controls. The ASD group had a higher rate of clinical depression and markedly higher “insomnia” and “restlessness” scores. Network analysis and hierarchical cluster analysis in the ASD group revealed that depression and anxiety items clustered together, but separately from autism-related items. Compared to controls, “insomnia” and “restlessness” items in the ASD network of depression items were much more central (higher closeness, and betweenness centrality). Combined networks of depression-, anxiety-, and OCD-related items revealed that the control group depression item module was not preserved in ASD. The results indicate that depression is atypical in autism and suggest specific intervention targets.

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    RCADS Scoring Guideline available at http://www.childfirst.ucla.edu/RCADSUsersGuide20150701.pdf.

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Acknowledgments

We appreciate the help of the developers of WGCNA package (Dr. Steve Horvath and Dr. Peter Langfelder). Dr. Langfelder checked the code of our newly defined function to work with WGCNA’s modulePreservation function and approved its functionality along with supplying us with further useful information regarding the inner working of this package and how it would interact with our function. We also are grateful for the thorough and very helpful comments of two reviewers. The current study is based on data from the Efficacy of Social Skills Training in Autism (ESTIA) study, conducted by Accare Center for Child and Adolescent Psychiatry and financed by the Netherlands Organization for Health Research and Development (ZonMw, nr 157003005). The study also used data from the TRacking Adolescents’ Individual Lives Survey (TRAILS). Participating centers of TRAILS include various departments of the University Medical Center and University of Groningen, the Erasmus University Medical Center Rotterdam, the University of Utrecht, the Radboud Medical Center Nijmegen, and the Parnassia Bavo group, all in the Netherlands. TRAILS has been financially supported by various grants from the Netherlands Organization for Scientific Research (NWO), ZonMW, GB-MaGW, the Dutch Ministry of Justice, the European Science Foundation, BBMRI-NL, the participating universities, and Accare Center for Child and Adolescent Psychiatry. We are grateful to all children, their parents, and teachers who participated in this research, and to everyone who worked on this project and made it possible.

Funding

Supported by the Netherlands Organization for Health Research and Development and the Netherlands Organization for Scientific Research (NWO), the Dutch Ministry of Justice, the European Science Foundation, BBMRI-NL, and the Accare Center for Child and Adolescent Psychiatry.

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GMA oversaw the data analysis and wrote the paper. FM conceived the project, performed data analysis and wrote the paper. AdB oversaw all clinical aspects of the project and contributed to writing of the paper. VD contributed to the patient assessment and methodological aspects of the paper.

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Correspondence to Farhad Montazeri.

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Conflict of interest

Author AdB is first author on the Dutch ADOS manual for which her institution (Accare) receives remuneration. Author GMA has received remuneration from the law firm Pepper Hamilton LLP, Philadelphia, PA, for consultation regarding their representation of the pharmaceutical firm Eli Lilly & Co. The agency had no role in the data analyses, the decision to publish, or the preparation of the manuscript. All other author declare that they no conflict of interest.

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Montazeri, F., de Bildt, A., Dekker, V. et al. Network Analysis of Behaviors in the Depression and Autism Realms: Inter-Relationships and Clinical Implications. J Autism Dev Disord 50, 1580–1595 (2020). https://doi.org/10.1007/s10803-019-03914-4

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Keywords

  • Network analysis
  • Autism spectrum disorder
  • Depression
  • Anxiety
  • Gaussian graphical modeling
  • Module preservation analysis
  • Clustering analysis