Genetic factors contribute to the phenotype of drug response. We systematically analyzed all available pharmacogenetic data from Medline databases on the impact that genetic polymorphisms have on positive and adverse reactions to antidepressants and antipsychotics. Additionally, dose adjustments that would compensate for genetically caused differences in blood concentrations were calculated. To study pharmacokinetic effects, data for 36 antidepressants were screened. We found that for 20 of those, data on polymorphic CYP2D6 or CYP2C19 were found and that in 14 drugs such genetic variation would require at least doubling of the dose in extensive metabolizers in comparison to poor metabolizers. Data for 38 antipsychotics were examined: for 13 of those CYP2D6 and CYP2C19 genotype was of relevance. To study the effects of genetic variability on pharmacodynamic pathways, we reviewed 80 clinical studies on polymorphisms in candidate genes, but those did not for the most part reveal significant associations between neurotransmitter receptor and transporter genotypes and therapy response or adverse drug reactions. In addition associations found in one study could not be replicated in other studies. For this reason, it is not yet possible to translate pharmacogenetic parameters fully into therapeutic recommendations. At present, antidepressant and antipsychotic drug responses can best be explained as the combinatorial outcome of complex systems that interact at multiple levels. In spite of these limitations, combinations of polymorphisms in pharmacokinetic and pharmacodynamic pathways of relevance might contribute to identify genotypes associated with best and worst responders and they may also identify susceptibility to adverse drug reactions.

Finding predictors of the response to antidepressant therapy is a major goal of molecular psychiatry. The genes encoding the serotonin (SERT) and dopamine (DAT1) transporters are among the possible candidate genes modulating an individual's antidepressant response. In a naturalistic prospective cohort study with a total of 190 fully assessed patients, improvement of depression symptoms during the 3 weeks following initiation of antidepressant therapy was recorded using the 21-item Hamilton Depression Rating Scale (HDRS). The SLC6A3 3 0 UTR 40-bp variable number of tandem repeats (VNTR) and the SLC6A4 5 0 44-bp insertion/deletion polymorphism were analyzed by polymerase chain reaction. There was a significantly smaller number of rapid responders among homozygous carriers of the DAT1 9-repeat allele (9/9) than among heterozygous (9/10) and homozygous (10/10) carriers of the 10-repeat allele (19 versus 37 versus 52%, respectively, P ¼ 0.0037). Median decline in HDRS score was 35, 40, and 52% in patients with the 9/9, 9/10, and 10/10 genotypes, respectively (P ¼ 0.013). The effect was found in all classes of medications (selective serotonin reuptake inhibitors (SSRIs), tricyclics, mirtazapine, venlafaxine) and statistically significant also within the subgroup of patients having received SSRIs. The serotonin promoter insertion/deletion genotype had no effect in the entire study group, but there was an insignificant trend of better response in the l/l and l/s carriers who received SSRIs or mirtazapine. In conclusion, the dopamine transporter VNTR polymorphism influenced rapid response to antidepressant therapy. Compared with homozygous carriers of the 10-repeat allele, carriers of the 9/10 genotype had an odds ratio (OR) calculated by logistic regression analysis of 1.6 (95% CI 0.8-3.2) and carriers of the 9/9 genotype had an OR of 6.0 (1.5-24.4) for no or poor response. Further studies are required to confirm this clinical association and to elucidate the underlying mechanisms.

Huntington's disease (HD) is an autosomal dominant neurodegenerative condition characterized by a triad of movement disorder, neuropsychiatric symptoms and cognitive deficits. The striatum is particularly vulnerable to the effects of mutant huntingtin, and cell loss can already be found in presymptomatic stages. Since the striatum is well known for its role in reinforcement learning, we hypothesized to find altered behavioral and neural responses in HD patients in a probabilistic reinforcement learning task performed during functional magnetic resonance imaging. We studied 24 HD patients without central nervous system (CNS)-active medication and 25 healthy controls. Twenty HD patients and 24 healthy controls were able to complete the task. Computational modeling was used to calculate prediction error values and estimate individual parameters. We observed that gray matter density and prediction error signals during the learning task were related to disease stage. HD patients in advanced disease stages appear to use a less complex strategy in the reversal learning task. In contrast, HD patients in early disease stages show intact encoding of learning signals in the degenerating left ventral striatum. This effect appears to be lost with disease progression.

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