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Cited 6 time in webofscience Cited 6 time in scopus
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Genetic Markers for Later Remission in Response to Early Improvement of Antidepressantsopen access

Authors
Kang, Hee-JuKim, Ki taeYoo, Kyung-HunPark, YoomiKim, Ju-WanKim, Sung-WanShin, Il-SeonKim, Ju HanKim, Jae-Min
Issue Date
Jul-2020
Publisher
Multidisciplinary Digital Publishing Institute (MDPI)
Keywords
antidepressant; treatment outcome; remission; improvement; genetic marker; whole-exome sequencing
Citation
International Journal of Molecular Sciences, v.21, no.14
Indexed
SCIE
SCOPUS
Journal Title
International Journal of Molecular Sciences
Volume
21
Number
14
URI
https://scholarworks.korea.ac.kr/kumedicine/handle/2020.sw.kumedicine/33704
DOI
10.3390/ijms21144884
ISSN
1661-6596
1422-0067
Abstract
Planning subsequent treatment strategies based on early responses rather than waiting for delayed antidepressant action can be helpful. We identified genetic markers for later non-remission in patients exhibiting poor early improvement using whole-exome sequencing data of depressive patients treated in a naturalistic manner. Among 1000 patients, early improvement at 2 weeks (reduction in Hamilton Depression Rating Scale [HAM-D] score >= 20%) and remission at 12 weeks (HAM-D score <= 7) were evaluated. Gene- and variant-level analyses were conducted to compare patients who did not exhibit early improvement and did not eventually achieve remission (n= 126) with those who exhibited early improvement and achieved remission (n= 385). Genes predicting final non-remission in patients who exhibited poor early improvement (COMT, PRNP,BRPF3,SLC25A40,andCGREF1in males;PPFIBPI,LZTS3, MEPCE, MAP1A,andPFASin females;ST3GAL5in the total population) were determined. Among the significant genes, variants in thePRNP(rs1800014),COMT(rs6267),BRPF3(rs200565609), andSLC25A40genes (rs3213633) were identified. However, interpretations should be made cautiously, as complex pharmacotherapy involves various genes and pathways. Early detection of poor early improvement and final non-remission based on genetic risk would be helpful for decision-making in a clinical setting.
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