Common mental disorders, like major depressive disorder (MDD) and post-traumatic stress disorder(PTSD) cause a significant part of the global burden of disease and exhibit a growing prevalence in thegeneral population. Second generation antidepressants are the first-line medications for PTSD and MDD.Although these medications have demonstrated better results compared to placebo, almost 50 percent ofpatients do not achieve remission and more than 30 percent do not respond during the first 6-12 weeksof treatment. There is no evidence to guide the choice of antidepressants. Thus, the process of finding aneffective treatment can be long for the non-responding patient and delaying recovery impose a heavy bur-den for the individual and to the society. Therefore, we need to learn more about the factors influencingtreatment response to move towards more personalized treatment options. Through three papers thisjoint industry-academia thesis sought to identify biological and clinical factors affecting antidepressanttreatment response in patients with MDD or PTSD.The first paper examined demographic and clinical predictors and latent classes of antidepressant treat-ment (sertraline or paroxetine) response in patients with PTSD from a clinical trial. Using growth mixturemodeling three classes with similar response trajectories were identified: fast responders, responders withlow pretreatment symptom severity and responders with high pretreatment symptom severity. Classmembership was predicted by time since index trauma, severity of depression, and severity of anxiety.The paper demonstrated, that higher baseline depression, anxiety and PTSD symptom severity does notresult in worse treatment response. Furthermore, patients with longer time since index trauma might par-ticularly benefit from treatment with sertraline or paroxetine as they are more likely to be fast responders.The second paper investigated changes and sources of variability in gene expression in peripheral bloodrelated to antidepressant treatment (vortioxetine) and treatment response for patients suffering fromrecurrent MDD. At the point of publication, the paper contained the largest dataset with both geneexpression in blood and placebo-controlled treatment response measured by a clinical scale in a rando-mized clinical trial. The paper revealed three novel genes whose gene expression at baseline and week 8were associated with treatment response after 8 weeks of treatment. No genes were differentially expres-sed between placebo and vortioxetine. Nor did the study replicate any genes identified in previous bloodgene expression studies of treatment response. Analysis of genome-wide expression variability showedthat type of treatment (median < 0.0001 %) and treatment response (median < 0.05 %) explain a lowproportion of the gene expression variance across all genes.The third paper examined whether polygenic risk scores (PRS) for relevant complex traits were as-sociated with antidepressant treatment response (vortioxetine) and placebo response. This was exploredin a clinical test sample, where placebo and treatment response were measured by clinical scales and sub-scales in MDD patients, as well as a web-based survey study of vortioxetine treated participants withself-reported response. In the clinical test sample, clinically assessed treatment response PRS was nomi-nally associated with vortioxetine treatment and placebo response given by several secondary outcomescales (improvement on HAM-A, HAM-A Psychic Anxiety sub-scale, CPFQ and PDQ). Further, we foundthat higher subjective well-being PRS and lower depression PRS were nominally significant associationswith higher placebo-response. In the self-reported test sample, higher schizophrenia PRS was associatedwith poorer self-reported response. Finally, the variance in vortioxetine and placebo response explainedby the PRSs was low (1.2 % - 5.3 %).Together, these papers viewed antidepressant treatment response from three different perspectives. Theyreveled heterogenisity of treatment response trajectories and showed that clinical, transcriptomic andpolygenic factors are associated med response to antidepressant treatment. However, the effect sizes ex-plained by the identified factors were limited which contribute to the evidence that treatment response isa complex trait influenced by various factors with small effect sizes. Thus, the findings so far have little tono clinical utility and limited interpretation on the individual’s level. Methodological improvements, datastandardization and larger sample sizes have the potential to provide a better insight into the differentfactors underlying antidepressant treatment response.