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Combined cognitive, psychomotor and electrophysiological biomarkers in major depressive disorder

Ping Chai Koo, Christoph Berger, Golo Kronenberg, Julia Bartz, Peter Wybitul, Olaf Reis, Jacqueline Hoeppner*

*Korrespondierende/r Autor/-in für diese Arbeit

Abstract

The diagnosis of major depressive disorder (MDD) should be based on multimodal evidence, because MDD not only affects mood, but also psychomotor and cognitive functions. Clinical markers such as executive dysfunctions and a reduction in daily motor activity have been observed in MDD. Neurophysiological biomarkers have also been described. In this study, we investigate the utility of combining biomarkers related to executive dysfunctions, motor activity, neurophysiological patterns (i.e. alpha power asymmetry and EEG-vigilance as indicators of brain arousal), and the interaction of these parameters in the diagnosis of MDD. Twenty (female: 11) patients with MDD (age: 51.05 ± 10.50) and 20 (female: 13) healthy controls (HC; age: 47.15 ± 12.57) underwent a 10-min resting EEG. Executive dysfunctions were assessed using the Trail Making Test B (TMT B). Motor activity was analysed by actigraphy measurements. MDD patients displayed significant impairments in executive functions and reduced daily motor activity. In the EEG, MDD patients showed more right than left frontal activity and lower brain arousal relative to HC. TMT B and asymmetrical frontal alpha power alone discriminated between MDD patients and HC with an accuracy of 78%. The interaction of motor activity and the EEG-vigilance stage alongside TMT B increased the accuracy of the discrimination test to 81%. This improved accuracy suggests that the combination of these biomarkers in a discriminant analysis resulted in a more reliable identification of MDD patients.

OriginalspracheEnglisch
ZeitschriftEuropean Archives of Psychiatry and Clinical Neuroscience
Jahrgang269
Ausgabenummer7
Seiten (von - bis)823-832
Seitenumfang10
ISSN0940-1334
DOIs
PublikationsstatusVeröffentlicht - 01.10.2019

UN SDGs

Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung

  1. SDG 3 – Gesundheit und Wohlergehen
    SDG 3 – Gesundheit und Wohlergehen

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