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Pharmacogenetics Studies in STAR*D: Strengths, Limitations, and Results Export

Psychiatr Serv, Vol. 60, No. 11. (1 November 2009), pp. 1446-1457.

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adverse_events depression depressive_disorder genes genetic_contribution major_depression suicidal_ideation therapeutic_response treatment_outcome

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Several lines of evidence support an important genetic contribution to the wide individual variation in therapeutic response to antidepressant medications. The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study provided the largest cohort assembled to date of DNA from patients with nonpsychotic major depressive disorder, uniformly treated with citalopram and followed prospectively for up to 12 weeks. This pivotal study changed the face of pharmacogenetics research by increasing the sample size by an order of magnitude as well as by providing detailed prospective information about antidepressant response and tolerability. Several groups have identified markers in genes and tested the replication of previous findings of genes associated with outcome and side effects of antidepressant treatment. Variants in HTR2A, GRIK4, and KCNK2 were associated with citalopram treatment outcome. Replication was achieved in markers in the FKBP5 gene. Other findings in PDE11A and BDNF were not successfully replicated, and reports of potential confounders in previous associations with serotonin transporter variation (SLC6A4) were identified. Polymorphisms in pharmacokinetic genes involved in metabolism and transmembrane transport were also not associated with antidepressant response. Adverse events were also tested. Treatment-emergent suicidal ideation was associated with GRIK2, GRIA3, PAPLN, IL28RA, and CREB1. Sexual dysfunction was linked with variation in GRIN3A, GRIA1 GRIA3, and GRIK2. Reported and future findings of pharmacogenetics studies in STAR*D could help elucidate pathways involved in major depression and those pertinent to antidepressant outcome and side effects. Replication of these findings in independent samples could lead to the development of new treatments and to optimization of available treatments. 10.1176/appi.ps.60.11.1446


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