Serum biomarkers predictive of depressive episodes in panic disorder. (February 2016)
- Record Type:
- Journal Article
- Title:
- Serum biomarkers predictive of depressive episodes in panic disorder. (February 2016)
- Main Title:
- Serum biomarkers predictive of depressive episodes in panic disorder
- Authors:
- Gottschalk, M.G.
Cooper, J.D.
Chan, M.K.
Bot, M.
Penninx, B.W.J.H.
Bahn, S. - Abstract:
- Abstract: Panic disorder with or without comorbid agoraphobia (PD/PDA) has been linked to an increased risk to develop subsequent depressive episodes, yet the underlying pathophysiology of these disorders remains poorly understood. We aimed to identify a biomarker panel predictive for the development of a depressive disorder (major depressive disorder and/or dysthymia) within a 2-year-follow-up period. Blood serum concentrations of 165 analytes were evaluated in 120 PD/PDA patients without depressive disorder baseline diagnosis (6-month-recency) in the Netherlands Study of Depression and Anxiety (NESDA). We assessed the predictive performance of serum biomarkers, clinical, and self-report variables using receiver operating characteristics curves (ROC) and the area under the ROC curve (AUC). False-discovery-rate corrected logistic regression model selection of serum analytes and covariates identified an optimal predictive panel comprised of tetranectin and creatine kinase MB along with patient gender and scores from the Inventory of Depressive Symptomatology (IDS) rating scale. Combined, an AUC of 0.87 was reached for identifying the PD/PDA patients who developed a depressive disorder within 2 years (n = 44). The addition of biomarkers represented a significant (p = 0.010) improvement over using gender and IDS alone as predictors (AUC = 0.78). For the first time, we report on a combination of biological serum markers, clinical variables and self-report inventories that canAbstract: Panic disorder with or without comorbid agoraphobia (PD/PDA) has been linked to an increased risk to develop subsequent depressive episodes, yet the underlying pathophysiology of these disorders remains poorly understood. We aimed to identify a biomarker panel predictive for the development of a depressive disorder (major depressive disorder and/or dysthymia) within a 2-year-follow-up period. Blood serum concentrations of 165 analytes were evaluated in 120 PD/PDA patients without depressive disorder baseline diagnosis (6-month-recency) in the Netherlands Study of Depression and Anxiety (NESDA). We assessed the predictive performance of serum biomarkers, clinical, and self-report variables using receiver operating characteristics curves (ROC) and the area under the ROC curve (AUC). False-discovery-rate corrected logistic regression model selection of serum analytes and covariates identified an optimal predictive panel comprised of tetranectin and creatine kinase MB along with patient gender and scores from the Inventory of Depressive Symptomatology (IDS) rating scale. Combined, an AUC of 0.87 was reached for identifying the PD/PDA patients who developed a depressive disorder within 2 years (n = 44). The addition of biomarkers represented a significant (p = 0.010) improvement over using gender and IDS alone as predictors (AUC = 0.78). For the first time, we report on a combination of biological serum markers, clinical variables and self-report inventories that can detect PD/PDA patients at increased risk of developing subsequent depressive disorders with good predictive performance in a naturalistic cohort design. After an independent validation our proposed biomarkers could prove useful in the detection of at-risk PD/PDA patients, allowing for early therapeutic interventions and improving clinical outcome. Graphical abstract: Highlights: We describe biological depression risk factors in panic disorder ± agoraphobia (PD/PDA). Serum markers and clinical variables were considered in a naturalistic cohort design. Depressive episodes were predicted in 120 PD/PDA patients over a 2-year follow-up. Serum markers included tetranectin and CK-MB and significantly improved prediction. In combination with gender and IDS a predictive performance of AUC = 0.87 was reached. … (more)
- Is Part Of:
- Journal of psychiatric research. Volume 73(2016:Feb.)
- Journal:
- Journal of psychiatric research
- Issue:
- Volume 73(2016:Feb.)
- Issue Display:
- Volume 73 (2016)
- Year:
- 2016
- Volume:
- 73
- Issue Sort Value:
- 2016-0073-0000-0000
- Page Start:
- 53
- Page End:
- 62
- Publication Date:
- 2016-02
- Subjects:
- Panic disorder -- Major depressive episode -- Prediction -- Risk factor -- Prognosis -- Secondary depression
Psychiatry -- Periodicals
Mental Disorders -- Periodicals
Maladies mentales -- Périodiques
Psychiatry
Electronic journals
Periodicals
616.89005 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00223956 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jpsychires.2015.11.012 ↗
- Languages:
- English
- ISSNs:
- 0022-3956
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5043.250000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 1336.xml