Anna Placentino

Neurofunctional correlates of vulnerability to psychosis: a systematic review and meta-analysis.

An understanding of the neurobiological correlates of vulnerability to psychosis is fundamental to research on schizophrenia. We systematically reviewed data from studies published from 1992 to 2006 on the neurocognitive correlates (as measured by fMRI) of increased vulnerability to psychosis. We also conducted a meta-analysis of abnormalities of activation in the prefrontal cortex (PFC) in high-risk and first episode subjects, and reviewed neuroimaging studies of high-risk subjects that used PET, SPECT and MRS. Twenty-four original fMRI papers were identified, most of which involved tasks that engaged the PFC. In fMRI studies, vulnerability to psychosis was associated with medium to large effect sizes when prefrontal activation was contrasted with that in controls. Relatives of patients affected with psychosis, the co-twins of patients and subjects with an At Risk Mental State (ARMS) appear to share similar neurocognitive abnormalities. Furthermore, these are qualitatively similar but less severe than those observed in the first episode of illness. These abnormalities have mainly been described in the prefrontal and anterior cingulated cortex, the basal ganglia, hippocampus and cerebellum.

Serum and plasma BDNF levels in major depression: A replication study and meta-analyses

Abstract Objectives. Alterations of BDNF signalling in major depression (MD) are supported by studies demonstrating decreased levels of the neurotrophin serum and plasma content in MD patients. We conducted a replication study and we performed two meta-analyses on studies analysing serum and plasma BDNF levels in MD patients. Methods. The samples were composed by 489 patients/483 controls for the meta-analysis on serum and by 161 patients/211 controls for that on plasma levels. We performed also subgroup analyses to examine whether the decrease in BDNF levels in MD was influenced by gender. Results. In the replication study we found decreased serum BDNF levels in MD patients (P<0.01) and we demonstrated that is down-regulated the mature form of the neurotrophin (mBDNF). No significant difference was evidenced for plasma BDNF levels. The meta-analyses showed a reduction of both BDNF serum (P<0.0001) and plasma levels (P=0.02) in MD. No difference in the effect size on serum BDNF was observed between males and females (P=0.18). Conclusions. In conclusion, our results provide evidence of peripheral BDNF alteration in MD and support the rationale for further investigation aiming to the identification of biomarkers for differential diagnosis and personalization of therapies in this disorder.

Genetic predictors of response to antidepressants in the GENDEP project.

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=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.

Differential efficacy of escitalopram and nortriptyline on dimensional measures of depression

BACKGROUND Tricyclic antidepressants and serotonin reuptake inhibitors are considered to be equally effective, but differences may have been obscured by internally inconsistent measurement scales and inefficient statistical analyses. AIMS To test the hypothesis that escitalopram and nortriptyline differ in their effects on observed mood, cognitive and neurovegetative symptoms of depression. METHOD In a multicentre part-randomised open-label design (the Genome Based Therapeutic Drugs for Depression (GENDEP) study) 811 adults with moderate to severe unipolar depression were allocated to flexible dosage escitalopram or nortriptyline for 12 weeks. The weekly Montgomery-Asberg Depression Rating Scale, Hamilton Rating Scale for Depression, and Beck Depression Inventory were scored both conventionally and in a more novel way according to dimensions of observed mood, cognitive symptoms and neurovegetative symptoms. RESULTS Mixed-effect linear regression showed no difference between escitalopram and nortriptyline on the three original scales, but symptom dimensions revealed drug-specific advantages. Observed mood and cognitive symptoms improved more with escitalopram than with nortriptyline. Neurovegetative symptoms improved more with nortriptyline than with escitalopram. CONCLUSIONS The three symptom dimensions provided sensitive descriptors of differential antidepressant response and enabled identification of drug-specific effects.

Common genetic variation and antidepressant efficacy in major depressive disorder: a meta-analysis of three genome-wide pharmacogenetic studies.

OBJECTIVE Indirect evidence suggests that common genetic variation contributes to individual differences in antidepressant efficacy among individuals with major depressive disorder, but previous studies may have been underpowered to detect these effects. METHOD A meta-analysis was performed on data from three genome-wide pharmacogenetic studies (the Genome-Based Therapeutic Drugs for Depression [GENDEP] project, the Munich Antidepressant Response Signature [MARS] project, and the Sequenced Treatment Alternatives to Relieve Depression [STAR*D] study), which included 2,256 individuals of Northern European descent with major depressive disorder, and antidepressant treatment outcomes were prospectively collected. After imputation, 1.2 million single-nucleotide polymorphisms were tested, capturing common variation for association with symptomatic improvement and remission after up to 12 weeks of antidepressant treatment. RESULTS No individual association met a genome-wide threshold for statistical significance in the primary analyses. A polygenic score derived from a meta-analysis of GENDEP and MARS participants accounted for up to approximately 1.2% of the variance in outcomes in STAR*D, suggesting a weakly concordant signal distributed over many polymorphisms. An analysis restricted to 1,354 individuals treated with citalopram (STAR*D) or escitalopram (GENDEP) identified an intergenic region on chromosome 5 associated with early improvement after 2 weeks of treatment. CONCLUSIONS Despite increased statistical power accorded by meta-analysis, the authors identified no reliable predictors of antidepressant treatment outcome, although they did identify modest, direct evidence that common genetic variation contributes to individual differences in antidepressant response.

Laterality effect on emotional faces processing: ALE meta-analysis of evidence

Recognizing emotion from facial expressions draws on diverse psychological processes implemented in a large array of neural structures. Two major theories of cerebral lateralization of emotional perception have been proposed: (i) the Right-Hemisphere Hypothesis (RHH) and (ii) the Valence-Specific Hypothesis (VSH). To test these lateralization models we conducted a large voxel-based meta-analysis of current functional magnetic resonance imaging (fMRI) studies employing emotional faces paradigms in healthy volunteers. Two independent researchers conducted separate comprehensive PUBMED (1990-May 2008) searches to find all functional magnetic resonance imaging studies using a variant of the emotional faces paradigm in healthy subjects. Out of the 551 originally identified studies, 105 studies met inclusion criteria. The overall database consisted of 1785 brain coordinates which yield an overall sample of 1600 healthy subjects. We found no support for the hypothesis of overall right-lateralization of emotional processing. Conversely, across all emotional conditions the parahippocampal gyrus and amygdala, fusiform gyrus, lingual gyrus, precuneus, inferior and middle occipital gyrus, posterior cingulated, middle temporal gyrus, inferior frontal and superior frontal gyri were activated bilaterally (p=0.001). There was a valence-specific lateralization of brain response during negative emotions processing in the left amygdala (p=0.001). Significant interactions between the approach and avoidance dimensions and prefrontal response were observed (p=0.001).

Genetic Predictors of Increase in Suicidal Ideation During Antidepressant Treatment in the GENDEP Project

The aim of this study was to investigate genetic predictors of an increase in suicidal ideation during treatment with a selective serotonin reuptake inhibitor or a tricyclic antidepressant. A total of 796 adult patients with major depressive disorder who were treated with a flexible dosage of escitalopram or nortriptyline in Genome-based Therapeutic Drugs for Depression (GENDEP) were included in the sample and provided data on suicidal ideation. Nine candidate genes involved in neurotrophic, serotonergic, and noradrenergic pathways were selected based on previous association studies with suicidal ideation or behavior. Using a logistic regression model, 123 polymorphisms in these genes were compared between subjects with an increase in suicidal ideation and those without any increase in suicidal ideation. Polymorphisms in BDNF, the gene encoding the brain-derived neurotrophic factor, were significantly associated with an increase in suicidal ideation. The strongest association was observed for rs962369 in BDNF (p=0.0015). Moreover, a significant interaction was found between variants in BDNF and NTRK2, the gene encoding the BNDF receptor (p=0.0003). Among men taking nortriptyline, suicidality was also associated with rs11195419 SNP in the alpha2A-adrenergic receptor gene (ADRA2A) (p=0.007). The associations observed with polymorphisms in BDNF suggest the involvement of the neurotrophic system in vulnerability to suicidality. Epistasis between BDNF and NTRK2 suggests that genetic variations in the two genes are involved in the same causal mechanisms leading to suicidality during antidepressant treatment. Among men, genetic variation in noradrenergic signaling may interact with norepinephrine reuptake-inhibiting antidepressants, thereby contributing to suicidality.

Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis

Testing whether genetic information could inform the selection of the best drug for patients with depression, Rudolf Uher and colleagues searched for genetic variants that could predict clinically meaningful responses to two major groups of antidepressants.

Trajectories of change in depression severity during treatment with antidepressants

BACKGROUND Response and remission defined by cut-off values on the last observed depression severity score are commonly used as outcome criteria in clinical trials, but ignore the time course of symptomatic change and may lead to inefficient analyses. We explore alternative categorization of outcome by naturally occurring trajectories of symptom change. METHOD Growth mixture models were applied to repeated measurements of depression severity in 807 participants with major depression treated for 12 weeks with escitalopram or nortriptyline in the part-randomized Genome-based Therapeutic Drugs for Depression study. Latent trajectory classes were validated as outcomes in drug efficacy comparison and pharmacogenetic analyses. RESULTS The final two-piece growth mixture model categorized participants into a majority (75%) following a gradual improvement trajectory and the remainder following a trajectory with rapid initial improvement. The rapid improvement trajectory was over-represented among nortriptyline-treated participants and showed an antidepressant-specific pattern of pharmacogenetic associations. In contrast, conventional response and remission favoured escitalopram and produced chance results in pharmacogenetic analyses. Controlling for drop-out reduced drug differences on response and remission but did not affect latent trajectory results. CONCLUSIONS Latent trajectory mixture models capture heterogeneity in the development of clinical response after the initiation of antidepressants and provide an outcome that is distinct from traditional endpoint measures. It differentiates between antidepressants with different modes of action and is robust against bias due to differential discontinuation.

Interaction between serotonin transporter gene variants and life events predicts response to antidepressants in the GENDEP project

There is substantial inter-individual variation in response to antidepressants, and genetic variation may, in part, explain these differences. For example, there is evidence to suggest that variation in the serotonin transporter gene (SLC6A4) predicts response to selective serotonin reuptake inhibitors (SSRIs). Environmental factors such as the occurrence of stressful life events before treatment may also be important. One prior report suggests that both factors interact in predicting response to antidepressants. GENDEP, a prospective part-randomized pharmacogenomics trial, collected longitudinal data on the outcome of 811 patients with major depression undergoing treatment with either an SSRI (escitalopram) or a tricyclic antidepressant (nortriptyline). Life events experienced over 6 months preceding treatment were measured using a List of Threatening Experiences Questionnaire, and several polymorphisms in the serotonin transporter gene (SLC6A4) have been genotyped including the serotonin transporter-linked polymorphic region (5-HTTLPR). Stressful life events were shown to predict a significantly better response to escitalopram but had no effect on response to nortriptyline. Variation in the 5-HTTLPR and another polymorphism in the gene, STin4, significantly modified these effects. Gene–environment interactions including life events may therefore be important not only in the aetiology of depression, but also in predicting response to antidepressant medication.