1. CHL1, ITGB3 and SLC6A4 gene expression and antidepressant drug response: results from the Munich Antidepressant Response Signature (MARS) study.
- Author
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Probst-Schendzielorz K, Scholl C, Efimkina O, Ersfeld E, Viviani R, Serretti A, Fabbri C, Gurwitz D, Lucae S, Ising M, Paul AM, Lehmann ML, Steffens M, Crisafulli C, Calabrò M, Holsboer F, and Stingl J
- Subjects
- Adult, Biomarkers, Pharmacological metabolism, Cell Adhesion Molecules biosynthesis, Depressive Disorder, Major epidemiology, Dose-Response Relationship, Drug, Female, Gene Expression Regulation, Germany epidemiology, Humans, Integrin beta3 biosynthesis, Male, Middle Aged, Polymorphism, Single Nucleotide genetics, Serotonin Plasma Membrane Transport Proteins biosynthesis, Switzerland epidemiology, Treatment Outcome, Antidepressive Agents therapeutic use, Cell Adhesion Molecules genetics, Depressive Disorder, Major drug therapy, Depressive Disorder, Major genetics, Integrin beta3 genetics, Serotonin Plasma Membrane Transport Proteins genetics
- Abstract
Aim: The identification of antidepressant drugs (ADs) response biomarkers in depression is of high clinical importance. We explored CHL1 and ITGB3 expression as tentative response biomarkers., Materials & Methods: In vitro sensitivity to ADs, as well as gene expression and genetic variants of the candidate genes CHL1, ITGB3 and SLC6A4 were measured in lymphoblastoid cell lines (LCLs) of 58 depressed patients., Results: An association between the clinical remission of depression and the basal expression of CHL1 and ITGB3 was discovered. Individuals whose LCLs expressed higher levels of CHL1 or ITGB3 showed a significantly better remission upon AD treatment. In addition individuals with the CHL1 rs1516338 TT genotype showed a significantly better remission after 5 weeks AD treatment than those carrying a CC genotype. No association between the in vitro sensitivity of LCLs toward AD and the clinical remission could be detected., Conclusion: CHL1 expression in patient-derived LCLs correlated with the clinical outcome. Thus, it could be a valid biomarker to predict the success of an antidepressant therapy. Original submitted 8 December 2014; Revision submitted 2 March 2015.
- Published
- 2015
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