An easily accessible peripheral blood biomarker may contribute to improvement in outcomes of major depressive disorder by personalizing treatment choice.

Background Symptom dimensions have not yet been comprehensively tested as predictors of the substantial heterogeneity in outcomes of antidepressant treatment in major depressive disorder. Method We tested nine symptom dimensions derived from a previously published factor analysis of depression rating scales as predictors of outcome in 811 adults with moderate to severe depression treated with flexibly dosed escitalopram or nortriptyline in Genome-based Therapeutic Drugs for Depression (GENDEP). The effects of symptom dimensions were tested in mixed-effect regression models that controlled for overall initial depression severity, age, sex and recruitment centre. Significant results were tested for replicability in 3637 adult out-patients with non-psychotic major depression treated with citalopram in level I of Sequenced Treatment Alternatives to Relieve Depression (STAR*D). Results The interest-activity symptom dimension (reflecting low interest, reduced activity, indecisiveness and lack of enjoyment) at baseline strongly predicted poor treatment outcome in GENDEP, irrespective of overall depression severity, antidepressant type and outcome measure used. The prediction of poor treatment outcome by the interest-activity dimension was robustly replicated in STAR*D, independent of a comprehensive list of baseline covariates. Conclusions Loss of interest, diminished activity and inability to make decisions predict poor outcome of antidepressant treatment even after adjustment for overall depression severity and other clinical covariates. The prominence of such symptoms may require additional treatment strategies and should be accounted for in future investigations of antidepressant response.

While limited statistical power means that a number of true associations may have been missed, these results suggest that efficacy of antidepressants may be predicted by genetic markers other than traditional candidates. Genome-wide studies, if properly replicated, may thus be important steps in the elucidation of the genetic basis of pharmacological response.

The MADRS and the BDI can be recommended as complementary measures of depression severity. The three factor scores are proposed for external validation.

Adverse reactions to antidepressants can be reliably assessed by self-report. Attention to specific adverse reactions may improve adherence to antidepressant treatment.

The three symptom dimensions provided sensitive descriptors of differential antidepressant response and enabled identification of drug-specific effects.

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The objective of the Genome-based Therapeutic Drugs for Depression study is to investigate the function of variations in genes encoding key proteins in serotonin, norepinephrine, neurotrophic and glucocorticoid signaling in determining the response to serotonin-reuptake-inhibiting and norepinephrine-reuptake-inhibiting antidepressants. A total of 116 single nucleotide polymorphisms in 10 candidate genes were genotyped in 760 adult patients with moderate-to-severe depression, treated with escitalopram (a serotonin reuptake inhibitor) or nortriptyline (a norepinephrine reuptake inhibitor) for 12 weeks in an open-label part-randomized multicenter study. The effect of genetic variants on change in depressive symptoms was evaluated using mixed linear models. Several variants in a serotonin receptor gene (HTR2A) predicted response to escitalopram with one marker (rs9316233) explaining 1.1% of variance (P ¼ 0.0016). Variants in the norepinephrine transporter gene (SLC6A2) predicted response to nortriptyline, and variants in the glucocorticoid receptor gene (NR3C1) predicted response to both antidepressants. Two HTR2A markers remained significant after hypothesis-wide correction for multiple testing. A false discovery rate of 0.106 for the three strongest associations indicated that the multiple findings are unlikely to be false positives. The pattern of associations indicated a degree of specificity with variants in genes encoding proteins in serotonin signaling influencing response to the serotonin-reuptake-inhibiting escitalopram, genes encoding proteins in norepinephrine signaling influencing response to the norepinephrine-reuptake-inhibiting nortriptyline and a common pathway gene influencing response to both antidepressants. The single marker associations explained only a small proportion of variance in response to antidepressants, indicating a need for a multivariate approach to prediction.