Pharmacopsychiatry 2007; 40 - A037
DOI: 10.1055/s-2007-991712

Whole genome analysis reveals new potential drug targets as predictors of antidepressant treatment response

S Lucae 1, I Marcus 1, P Saemann 1, T Bettecken 1, M Uhr 1, S Ripke 1, M Kohli 1, S Kloiber 1, B Bondy 2, R Rupprecht 2, K Domschke 3, V Arolt 3, P Lichtner 4, F Holsboer 1, B Müller-Myhsok 1
  • 1Max Planck Institute of Psychiatry, Munich, Germany
  • 2Department of Psychiatry, Ludwig Maximilians University, Munich, Germany
  • 3Department of Psychiatry, University of Münster, Münster, Germany
  • 4Institute for Human Genetics, Technical University and GSF-National Research Centre for Environment and Health, Neuherberg, Germany

Pharmacogenetic studies so far focused on candidate genes implicated in mechanisms of antidepressant drug action. Since the mechanisms by which antidepressants exert their clinical effects are not yet fully known, association studies identifying gene variants distributed over the whole genome, and not restricted to candidate genes therefore are more straightforward in detecting clinical outcome predictors and uncovering yet unknown pathways involved in drug action. We performed a genome-wide pharmacogenetic association study in 412 patients suffering from depression. As antidepressant response phenotypes we measured early partial response after two weeks as well as response and remission after five weeks. We found one SNP in the region of CNS-relevant genes to be associated with treatment response and remission, which was significant after correction for multiple testing. Analysis in a second independent patient sample also gave evidence for involvement of this SNP and neighboring SNPs in remission and response. We also found genotype-dependent differences both in mRNA levels of the gene in peripheral blood monocytes, and in the volumes of anterior cingulate and medial prefrontal cortex of depressed patients. These findings suggest that a genome-wide search for gene variants predicting treatment response provides insight into possible mechanisms of action involved in antidepressant-induced clinical changes.