Authors:	Neyer, Sabrina Elisabeth
Title:	Psychophysiological correlates of treatment effects – in search of potential biomarkers for the course of major depressive disorder
Online publication date:	1-Dec-2022
Year of first publication:	2022
Language:	english
Abstract:	Major depressive disorder (MDD) is still one of the most common and highly debili-tating mental disorders. Although there are several treatment possibilities, the relapse rate is still high and some patients even suffer from treatment-resistant depression. First research re-sults suggest that the measurement of psychophysiological correlates (“biomarkers”) of MDD might be promising as a means to identify high-risk subgroups for poor outcomes in respect of MDD treatment. However, findings about the association between these correlates and MDD are still inconsistent, especially in naturalistic settings. To address this research gap, this dissertation focusses on assessing the explanatory value of psychophysiological correlates of depression to predict the course of MDD after inpa-tient treatment. This research employs two psychophysiological correlates of MDD that are typically used: Heart Rate Variability (HRV) and Cortisol Awakening Response (CAR). The overarching methodological goal that guided the studies within this dissertation is to use mul-tiple measurement designs to increase the robustness of psychophysiological data in naturalistic settings. Vagally-mediated HRV is seen as a psychophysiological marker for mental health and MDD. However, up to now, little has been known about the association between HRV and the severity of depression and whether this association mirrors treatment effects following in-patient psychotherapy. Therefore a multiple measurement study was conducted to assess the association between the severity of MDD symptoms and HRV before and after therapy. The sample consisted of 50 patients suffering from moderate to severe MDD. HRV was assessed three times at the beginning of, and three times at discharge from, inpatient psychotherapy. Depressive symptoms were assessed by self-reports (Beck Depression Inventory, BDI-II) and a third-party questionnaire (Hamilton rating scale for depression, HRSD) at the beginning of psychotherapy and at discharge. Results confirm an expected negative correlation between HRV and depressive symptoms at the beginning of the inpatient treatment. At discharge, results show a de-coupling between HRV and symptom severity: Depressive symptoms improve sig-nificantly (d=0.84) without corresponding changes in HRV as a psychophysiological indicator. CAR reflects a dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis which is associated with MDD. Initial research results suggest that CAR resembles the accumulated effects of MDD and therefore might be a predictor for the course of depression after discharge. Therefore CAR was measured at intake to inpatient psychotherapy. The BDI was assessed at IX four time-points (intake, discharge, 6 weeks after discharge and 6 months after discharge). The sample included 123 inpatients diagnosed with MDD. The results show that a blunted CAR at intake predicts mood deterioration six weeks and six months following discharge. Due to a lack of comparative data, and to verify these initial results regarding the association of CAR and MDD, a replication study was conducted. The replication study used an improved methodology with stricter assessment protocols and monitoring. The sample in-cluded 122 inpatients diagnosed with moderate to severe MDD. CAR and self-ratings were assessed at the same measurement points as in the original study. Results could be replicated in terms of nearly identical effect sizes but do not reach statistical significance (p=.054). The rep-lication of effect sizes with a concurrent lack of statistical significance may well inform re-search on psycho-endocrinological predictors for treatment success, but raises the question of practical relevance for CAR as a predictor for the further course of MDD. Results are discussed for each study individually and on an aggregate level with respect to the overarching research question. Taken together, they show that the associations between biological and psychological aspects are very complex and are influenced by many factors. Robust measurement designs are required to improve scientific understanding. However, when measured strictly, additional information regarding the association between biomarkers and the course of depression can be gathered. However, the explanatory power of a single biomarker seems to be too small to have clinical impact. Therefore biomarkers can be viewed only as an additional source of information to predict treatment effects.
DDC:	150 Psychologie 150 Psychology 610 Medizin 610 Medical sciences
Institution:	Johannes Gutenberg-Universität Mainz
Department:	FB 02 Sozialwiss., Medien u. Sport
Place:	Mainz
ROR:	https://ror.org/023b0x485
DOI:	http://doi.org/10.25358/openscience-8120
URN:	urn:nbn:de:hebis:77-openscience-0e2b2a3f-9feb-442b-8494-8fb90605ba539
Version:	Original work
Publication type:	Dissertation
License:	CC BY
Information on rights of use:	https://creativecommons.org/licenses/by/4.0/
Extent:	IX, 122 Seiten
Appears in collections:	JGU-Publikationen