PMID- 33123000
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20210507
IS  - 1662-5188 (Print)
IS  - 1662-5188 (Electronic)
IS  - 1662-5188 (Linking)
VI  - 14
DP  - 2020
TI  - Predicting Antidepressant Citalopram Treatment Response via Changes in Brain 
      Functional Connectivity After Acute Intravenous Challenge.
PG  - 554186
LID - 10.3389/fncom.2020.554186 [doi]
LID - 554186
AB  - Introduction: The early and therapy-specific prediction of treatment success in 
      major depressive disorder is of paramount importance due to high lifetime 
      prevalence, and heterogeneity of response to standard medication and symptom 
      expression. Hence, this study assessed the predictability of long-term 
      antidepressant effects of escitalopram based on the short-term influence of 
      citalopram on functional connectivity. Methods: Twenty nine subjects suffering 
      from major depression were scanned twice with resting-state functional magnetic 
      resonance imaging under the influence of intravenous citalopram and placebo in a 
      randomized, double-blinded cross-over fashion. Symptom factors were identified 
      for the Hamilton depression rating scale (HAM-D) and Beck's depression inventory 
      (BDI) taken before and after a median of seven weeks of escitalopram therapy. 
      Predictors were calculated from whole-brain functional connectivity, fed into 
      robust regression models, and cross-validated. Results: Significant predictive 
      power could be demonstrated for one HAM-D factor describing insomnia and the 
      total score (r = 0.45-0.55). Remission and response could furthermore be 
      predicted with an area under the receiver operating characteristic curve of 0.73 
      and 0.68, respectively. Functional regions with high influence on the predictor 
      were located especially in the ventral attention, fronto-parietal, and default 
      mode networks. Conclusion: It was shown that medication-specific antidepressant 
      symptom improvements can be predicted using functional connectivity measured 
      during acute pharmacological challenge as an easily assessable imaging marker. 
      The regions with high influence have previously been related to major depression 
      as well as the response to selective serotonin reuptake inhibitors, corroborating 
      the advantages of the current approach of focusing on treatment-specific symptom 
      improvements.
CI  - Copyright (c) 2020 Klobl, Gryglewski, Rischka, Godbersen, Unterholzner, Reed, 
      Michenthaler, Vanicek, Winkler-Pjrek, Hahn, Kasper and Lanzenberger.
FAU - Klobl, Manfred
AU  - Klobl M
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Gryglewski, Gregor
AU  - Gryglewski G
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Rischka, Lucas
AU  - Rischka L
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Godbersen, Godber Mathis
AU  - Godbersen GM
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Unterholzner, Jakob
AU  - Unterholzner J
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Reed, Murray Bruce
AU  - Reed MB
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Michenthaler, Paul
AU  - Michenthaler P
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Vanicek, Thomas
AU  - Vanicek T
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Winkler-Pjrek, Edda
AU  - Winkler-Pjrek E
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Hahn, Andreas
AU  - Hahn A
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Kasper, Siegfried
AU  - Kasper S
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
FAU - Lanzenberger, Rupert
AU  - Lanzenberger R
AD  - Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, 
      Austria.
LA  - eng
GR  - KLI 516/FWF_/Austrian Science Fund FWF/Austria
PT  - Journal Article
DEP - 20201006
PL  - Switzerland
TA  - Front Comput Neurosci
JT  - Frontiers in computational neuroscience
JID - 101477956
PMC - PMC7573155
OTO - NOTNLM
OT  - functional connectivity
OT  - functional magnetic resonance imaging
OT  - major depressive disorder
OT  - resting-state
OT  - selective serotonin reuptake inhibitors
OT  - treatment response prediction
EDAT- 2020/10/31 06:00
MHDA- 2020/10/31 06:01
PMCR- 2020/01/01
CRDT- 2020/10/30 05:53
PHST- 2020/04/21 00:00 [received]
PHST- 2020/08/31 00:00 [accepted]
PHST- 2020/10/30 05:53 [entrez]
PHST- 2020/10/31 06:00 [pubmed]
PHST- 2020/10/31 06:01 [medline]
PHST- 2020/01/01 00:00 [pmc-release]
AID - 10.3389/fncom.2020.554186 [doi]
PST - epublish
SO  - Front Comput Neurosci. 2020 Oct 6;14:554186. doi: 10.3389/fncom.2020.554186. 
      eCollection 2020.