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Genetic predictors of response to treatment with citalopram in depression secondary to traumatic brain injury.

ABSTRACT: To determine which serotonergic system-related single nucleotide polymorphisms (SNPs) predicted variation in treatment response to citalopram in depression following a traumatic brain injury (TBI).Ninety (50 M/40 F, aged 39.9, SD = 18.0 years) post-TBI patients with a major depressive episode (MDE) were recruited into a 6-week open-label study of citalopram (20 mg/day). Six functional SNPs in genes related to the serotonergic system were examined: serotonin transporter (5HTTLPR including rs25531), 5HT1A C-(1019)G and 5HT2A T-(102)C, methylene tetrahydrofolate reductase (MTHFR) C-(677)T, brain-derived neurotrophic factor (BDNF) val66met and tryptophan hydroxylase-2 (TPH2) G-(703)T. Regression analyses were performed using the six SNPs as independent variables: Model 1 with response (percentage Hamilton Depression (HAMD) change from baseline to endpoint) as the dependent variable and Model 2 with adverse event index as the dependent variable (Bonferroni corrected p-value < 0.025).MTHFR and BDNF SNPs predicted greater treatment response (R(2)= 0.098, F = 4.65, p = 0.013). The 5HTTLPR predicted greater occurrence of adverse events (R(2)= 0.069, F = 5.72, p = 0.020).Results suggest that polymorphisms in genes related to the serotonergic system may help predict short-term response to citalopram and tolerability to the medication in patients with MDE following a TBI.

SUBMITTER: Lanctot KL

PROVIDER: S-EPMC3142269 | biostudies-literature | 2010

REPOSITORIES: biostudies-literature

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Genetic predictors of response to treatment with citalopram in depression secondary to traumatic brain injury.

Lanctôt Krista L KL Rapoport Mark J MJ Chan Florance F Rajaram Ryan D RD Strauss John J Sicard Tricia T McCullagh Scott S Feinstein Anthony A Kiss Alex A Kennedy James L JL Bassett Anne S AS Herrmann Nathan N

Brain injury 20100101 7-8

<h4>Objectives</h4>To determine which serotonergic system-related single nucleotide polymorphisms (SNPs) predicted variation in treatment response to citalopram in depression following a traumatic brain injury (TBI).<h4>Methods</h4>Ninety (50 M/40 F, aged 39.9, SD = 18.0 years) post-TBI patients with a major depressive episode (MDE) were recruited into a 6-week open-label study of citalopram (20 mg/day). Six functional SNPs in genes related to the serotonergic system were examined: serotonin tra ...[more]

PMID: 20515362

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Project description:Cross-sectional approaches to outcome assessment may not adequately capture heterogeneity in recovery after traumatic brain injury (TBI). Using latent class mixed models (LCMM), a data-driven analytic that identifies groups of patients with similar trajectories, we identified distinct 6 month functional recovery trajectories in a large cohort (n = 1046) of adults 18-70 years of age with complicated mild to severe TBI who participated in the Citicoline Brain Injury Treatment Trial (COBRIT). We used multinomial logistic fixed effect models and backward elimination, forward selection, and forward stepwise selection with several stopping rules to explore baseline predictors of functional recovery trajectory. Based on statistical and clinical considerations, the seven-class model was deemed superior. Visualization of these seven functional recovery trajectories revealed that each trajectory class started at one of three recovery levels at 1 month, which, for ease of reference we labeled groups A-C: Group A, good recovery (two classes; A1 and A2); Group B, moderate disability (two classes; B1 and B2); and Group C, severe disability (three classes; C1, C2, and C3). By 6 months, these three groups experienced dramatically divergent trajectories. Group A experienced stable good recovery (A1, n = 115) or dramatic decline (A2, n = 4); Group B experienced rapid complete recovery (B1, n = 71) or gradual recovery (B2, n = 742); Group C experienced dramatic rapid recovery (C1, n = 12), no recovery (C2, n = 91), or death (C3, n = 11). Trajectory class membership was not predicted by citicoline treatment (p = 0.57). The models identified demographic, pre-injury, and injury-related predictors of functional recovery trajectory, including: age, race, education, pre-injury employment, pre-injury diabetes, pre-injury psychiatric disorder, site, Glasgow Coma Scale (GCS) score, post-traumatic amnesia, TBI mechanism, major extracranial injury, hemoglobin, and acute computed tomographic (CT) findings. GCS was the most consistently selected predictor across all models. All models also selected at least one demographic or pre-injury medical predictor. LCMM successfully identified dramatically divergent, clinically meaningful 6 month recovery trajectories with utility to inform clinical trial design.

Dataset Information

Genetic predictors of response to treatment with citalopram in depression secondary to traumatic brain injury.

Publications

Genetic predictors of response to treatment with citalopram in depression secondary to traumatic brain injury.

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