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Cited 57 time in webofscience Cited 58 time in scopus
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Potential peripheral biological predictors of suicidal behavior in major depressive disorder

Authors
Lee, Bun-HeeKim, Yong-Ku
Issue Date
1-Jun-2011
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Keywords
BDNF; Cholesterol; Hypothalamic-pituitary-adrenal; Neurobiology; Serotonin; Suicide
Citation
PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY, v.35, no.4, pp 842 - 847
Pages
6
Indexed
SCI
SCIE
SCOPUS
Journal Title
PROGRESS IN NEURO-PSYCHOPHARMACOLOGY & BIOLOGICAL PSYCHIATRY
Volume
35
Number
4
Start Page
842
End Page
847
URI
https://scholarworks.korea.ac.kr/kumedicine/handle/2020.sw.kumedicine/13367
DOI
10.1016/j.pnpbp.2010.08.001
ISSN
0278-5846
1878-4216
Abstract
Previous studies have shown that dysfunctions in the serotonin system and hypothalamic-pituitary-adrenal axis (HPA) are associated strongly with suicidal behavior and suicide, especially among individuals with major depressive disorder. Suicidal behavior has been explained using both the stress-diathesis model and the state-trait interaction model. Specifically, diatheses, or trait-dependent risk factors, are associated with dysfunctions in the serotonin system; however, stress responses, or state-dependent factors, are associated with HPA hyperactivity. Decreases in cholesterol and brain-derived neurotrophic factor (BDNF) levels have been associated with impaired brain plasticity among individuals with suicidal behavior. Decreased serotonin functioning has been measured using cerebral spinal fluid (CSF) 5-HIAA, fenfluramine challenge studies, and platelet 5-HT2A receptors. HPA axis dysfunction has been evaluated with the dexamethasone suppression test Cholesterol and BDNF levels have been measured in blood serum or plasma. Nevertheless, challenges to finding promising and accessible neurobiological predictors of suicide and suicidal behavior remain. As suicide behavior is a complex phenomenon, a combined or multidimensional approach, including each of the aforementioned methods, may be required to predict suicide risk among individuals with major depressive disorder. (C) 2010 Elsevier Inc. All rights reserved.
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