Variation in the gene encoding the serotonin 2A receptor is associated with outcome of antidepressant treatment

Abstract

Depressive disorders account for a large and increasing global burden of disease. Although the condition of many patients improves with medication, only a minority experience full remission, and patients whose condition responds to one medication may not have a response to others. Individual variation in antidepressant treatment outcome is, at present, unpredictable but may have a partial genetic basis. We searched for genetic predictors of treatment outcome in 1,953 patients with major depressive disorder who were treated with the antidepressant citalopram in the Sequenced Treatment Alternatives for Depression (STAR*D) study and were prospectively assessed. In a split-sample design, a selection of 68 candidate genes was genotyped, with 768 single-nucleotide-polymorphism markers chosen to detect common genetic variation. We detected significant and reproducible association between treatment outcome and a marker in HTR2A (P range 1 x 10(-6) to 3.7 x 10(-5) in the total sample). Other markers in HTR2A also showed evidence of association with treatment outcome in the total sample. HTR2A encodes the serotonin 2A receptor, which is downregulated by citalopram. Participants who were homozygous for the A allele had an 18% reduction in absolute risk of having no response to treatment, compared with those homozygous for the other allele. The A allele was over six times more frequent in white than in black participants, and treatment was less effective among black participants. The A allele may contribute to racial differences in outcomes of antidepressant treatment. Taken together with prior neurobiological findings, these new genetic data make a compelling case for a key role of HTR2A in the mechanism of antidepressant action.

Figures

Figure 1

CONSORT chart of genotyping and analysis of STAR*D sample. Samples dropped from analysis comprised 34 subjects who were noncompliant with medications, 19 with initial QIDS-C16 <10 or missing, 5 with missing clinical data, 4 whose molecular and recorded sex did not match, and 3 duplicate samples.

Figure 2

Treatment-outcome phenotypes. Subjects who completed at least 6 wk of treatment with citalopram were assigned a remission and response phenotype that was based on the QIDS-C16 score at the last treatment visit. Those who met score criteria for remission or response after 3–6 wk of treatment were grouped with probable remitters or probable responders, respectively.

Figure 3

Allelic association between treatment outcome and each of 768 SNPs representing 68 candidate genes. Allelic association P values were ranked in the discovery and replication samples, then the ranks were summed across samples. For visual clarity, the inverse of the sum of ranks is shown on the Y-axis. The remission phenotype is indicated by the unblackened circles, the response phenotype by the blackened circles. Only rs7997012 met the a priori P value thresholds in both samples. Another SNP, rs2178865, ranked highly in both samples but fell short of the a priori significance level in the replication sample.

Figure 4

Physical positions and LD relationships among SNP markers genotyped in the STAR*D sample. This figure shows the Refseq gene model for HTR2A taken from the UCSC Genome Browser (build 43), juxtaposed on a graphical representation of intermarker r2 values produced by Haploview 3.2.