Predicting antidepressant treatment outcome based on socioeconomic status and citalopram dose.

Selective serotonin reuptake inhibitors (SSRIs), the most prescribed antidepressant drugs, have incomplete efficacy and no clear mechanism of action. In addition, no reliable methods to identify patients who will benefit from treatment is available. In this study, we show that citalopram, a commonly used SSRI, produces a dose-dependent amplification of the influence of the environment on mood, making the severity of symptoms dependent on the level of socioeconomic status (SES). As a consequence, based on SES, we were able to predict which patients would show remission following 12 weeks of treatment in the high, but not the low dose group. Our findings support a novel mechanism of action for SSRIs, which calls for a permissive rather than an instructive role of these drugs, and indicate that treatment outcome can be predicted based on SES and dose. Finally, our findings suggest that the patient's social and economic conditions should be considered in setting up personalized strategies aimed at enhancing SSRI efficacy.