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Altered global brain network topology as a trait marker in patients with anorexia nervosa

Published online by Cambridge University Press:  09 January 2019

Daniel Geisler Open the ORCID record for Daniel Geisler [Opens in a new window] ,
Viola Borchardt Open the ORCID record for Viola Borchardt [Opens in a new window] ,
Ilka Boehm Open the ORCID record for Ilka Boehm [Opens in a new window] ,
Joseph A. King Open the ORCID record for Joseph A. King [Opens in a new window] ,
Friederike I. Tam Open the ORCID record for Friederike I. Tam [Opens in a new window] ,
Michael Marxen Open the ORCID record for Michael Marxen [Opens in a new window] ,
Ronald Biemann Open the ORCID record for Ronald Biemann [Opens in a new window] ,
Veit Roessner Open the ORCID record for Veit Roessner [Opens in a new window] ,
Martin Walter  and
Stefan Ehrlich Open the ORCID record for Stefan Ehrlich [Opens in a new window]
Daniel Geisler
Affiliation:
Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
Viola Borchardt
Affiliation:
Clinical Affective Neuroimaging Laboratory, Magdeburg, Germany Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany
Ilka Boehm
Affiliation:
Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
Joseph A. King
Affiliation:
Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
Friederike I. Tam
Affiliation:
Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany Department of Child and Adolescent Psychiatry, Eating Disorder Treatment and Research Center, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
Michael Marxen
Affiliation:
Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
Ronald Biemann
Affiliation:
Institute of Clinical Chemistry and Pathobiochemistry, Otto-von-Guericke University, Magdeburg, Germany
Veit Roessner
Affiliation:
Department of Child and Adolescent Psychiatry, Eating Disorder Treatment and Research Center, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
Martin Walter
Affiliation:
Clinical Affective Neuroimaging Laboratory, Magdeburg, Germany Department of Behavioral Neurology, Leibniz Institute for Neurobiology, Magdeburg, Germany Clinic for Psychiatry and Psychotherapy, Eberhard-Karls University, Tuebingen, Germany Center for Behavioral Brain Sciences (CBBS), Magdeburg, Germany
Stefan Ehrlich*
Affiliation:
Division of Psychological and Social Medicine and Developmental Neuroscience, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany Department of Child and Adolescent Psychiatry, Eating Disorder Treatment and Research Center, Faculty of Medicine, Technische Universität Dresden, Dresden, Germany
*
Author for correspondence: Stefan Ehrlich, E-mail: transden.lab@uniklinikum-dresden.de
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Abstract

Background

Resting state functional magnetic resonance imaging studies have identified functional connectivity patterns associated with acute undernutrition in anorexia nervosa (AN), but few have investigated recovered patients. Thus, a trait connectivity profile characteristic of the disorder remains elusive. Using state-of-the-art graph–theoretic methods in acute AN, the authors previously found abnormal global brain network architecture, possibly driven by local network alterations. To disentangle trait from starvation effects, the present study examines network organization in recovered patients.

Methods

Graph–theoretic metrics were used to assess resting-state network properties in a large sample of female patients recovered from AN (recAN, n = 55) compared with pairwise age-matched healthy controls (HC, n = 55).

Results

Indicative of an altered global network structure, recAN showed increased assortativity and reduced global clustering as well as small-worldness compared with HC, while no group differences at an intermediate or local network level were evident. However, using support-vector classifier on local metrics, recAN and HC could be separated with an accuracy of 70.4%.

Conclusions

This pattern of results suggests that long-term recovered patients have an aberrant global brain network configuration, similar to acutely underweight patients. While the finding of increased assortativity may represent a trait marker of AN, the remaining findings could be seen as a scar following prolonged undernutrition.

Keywords

Anorexia nervosaconnectivitygraph theorymachine learningresting statetrait marker
Type
Original Articles
Information
Psychological Medicine , Volume 50 , Issue 1 , January 2020 , pp. 107 - 115
Copyright
Copyright © Cambridge University Press 2019 

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