Joanna Hauser

The DTNBP1 (Dysbindin) Gene Contributes to Schizophrenia, Depending on Family History of the Disease

We have investigated the gene for dystrobrevin-binding protein 1 (DTNBP1), or dysbindin, which has been strongly suggested as a positional candidate gene for schizophrenia, in three samples of subjects with schizophrenia and unaffected control subjects of German (418 cases, 285 controls), Polish (294 cases, 113 controls), and Swedish (142 cases, 272 controls) descent. We analyzed five single-nucleotide polymorphisms (P1635, P1325, P1320, P1757, and P1578) and identified significant evidence of association in the Swedish sample but not in those from Germany or Poland. The results in the Swedish sample became even more significant after a separate analysis of those cases with a positive family history of schizophrenia, in whom the five-marker haplotype A-C-A-T-T showed a P value of.00009 (3.1% in controls, 17.8% in cases; OR 6.75; P=.00153 after Bonferroni correction). Our results suggest that genetic variation in the dysbindin gene is particularly involved in the development of schizophrenia in cases with a familial loading of the disease. This would also explain the difficulty of replicating this association in consecutively ascertained case-control samples, which usually comprise only a small proportion of subjects with a family history of disease.

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.

Genome-wide association study reveals two new risk loci for bipolar disorder

Bipolar disorder (BD) is a common and highly heritable mental illness and genome-wide association studies (GWAS) have robustly identified the first common genetic variants involved in disease aetiology. The data also provide strong evidence for the presence of multiple additional risk loci, each contributing a relatively small effect to BD susceptibility. Large samples are necessary to detect these risk loci. Here we present results from the largest BD GWAS to date by investigating 2.3 million single-nucleotide polymorphisms (SNPs) in a sample of 24,025 patients and controls. We detect 56 genome-wide significant SNPs in five chromosomal regions including previously reported risk loci ANK3, ODZ4 and TRANK1, as well as the risk locus ADCY2 (5p15.31) and a region between MIR2113 and POU3F2 (6q16.1). ADCY2 is a key enzyme in cAMP signalling and our finding provides new insights into the biological mechanisms involved in the development of BD.

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.

An Inflammatory Biomarker as a Differential Predictor of Outcome of Depression Treatment With Escitalopram and Nortriptyline

OBJECTIVE Major depressive disorder has been linked with inflammatory processes, but it is unclear whether individual differences in levels of inflammatory biomarkers could help match patients to treatments that are most likely to be beneficial. The authors tested the hypothesis that C-reactive protein (CRP), a commonly available marker of systemic inflammation, predicts differential response to escitalopram (a serotonin reuptake inhibitor) and nortriptyline (a norepinephrine reuptake inhibitor). METHOD The hypothesis was tested in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study, a multicenter open-label randomized clinical trial. CRP was measured with a high-sensitivity method in serum samples from 241 adult men and women with major depressive disorder randomly allocated to 12-week treatment with escitalopram (N=115) or nortriptyline (N=126). The primary outcome measure was the score on the Montgomery-Åsberg Depression Rating Scale (MADRS), administered weekly. RESULTS CRP level at baseline differentially predicted treatment outcome with the two antidepressants (CRP-drug interaction: β=3.27, 95% CI=1.65, 4.89). For patients with low levels of CRP (<1 mg/L), improvement on the MADRS score was 3 points higher with escitalopram than with nortriptyline. For patients with higher CRP levels, improvement on the MADRS score was 3 points higher with nortriptyline than with escitalopram. CRP and its interaction with medication explained more than 10% of individual-level variance in treatment outcome. CONCLUSIONS An easily accessible peripheral blood biomarker may contribute to improvement in outcomes of major depressive disorder by personalizing treatment choice.

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.

Depression symptom dimensions as predictors of antidepressant treatment outcome: replicable evidence for interest-activity symptoms

BACKGROUND Symptom dimensions have not yet been comprehensively tested as predictors of the substantial heterogeneity in outcomes of antidepressant treatment in major depressive disorder. METHOD We tested nine symptom dimensions derived from a previously published factor analysis of depression rating scales as predictors of outcome in 811 adults with moderate to severe depression treated with flexibly dosed escitalopram or nortriptyline in Genome-based Therapeutic Drugs for Depression (GENDEP). The effects of symptom dimensions were tested in mixed-effect regression models that controlled for overall initial depression severity, age, sex and recruitment centre. Significant results were tested for replicability in 3637 adult out-patients with non-psychotic major depression treated with citalopram in level I of Sequenced Treatment Alternatives to Relieve Depression (STAR*D). RESULTS The interest-activity symptom dimension (reflecting low interest, reduced activity, indecisiveness and lack of enjoyment) at baseline strongly predicted poor treatment outcome in GENDEP, irrespective of overall depression severity, antidepressant type and outcome measure used. The prediction of poor treatment outcome by the interest-activity dimension was robustly replicated in STAR*D, independent of a comprehensive list of baseline covariates. CONCLUSIONS Loss of interest, diminished activity and inability to make decisions predict poor outcome of antidepressant treatment even after adjustment for overall depression severity and other clinical covariates. The prominence of such symptoms may require additional treatment strategies and should be accounted for in future investigations of antidepressant response.

Prefrontal cognition in schizophrenia and bipolar illness in relation to Val66Met polymorphism of the brain-derived neurotrophic factor gene

Abstract  The measures of prefrontal cognition have been used as endophenotype in molecular‐genetic studies. Brain‐derived neurotrophic factor (BDNF) has been implicated in cognitive functions and in the pathogenesis of major psychoses. This study investigates the relationship between Val66Met polymorphisms of the BDNF gene and prefrontal cognitive function in 129 patients with schizophrenia and 111 patients with bipolar mood disorder. Cognitive tests included the Wisconsin Card Sorting Test (WCST), with such domains as number of perseverative errors, non‐perseverative errors, completed corrected categories, conceptual level responses, and set to the first category, and the N‐back test, where mean reaction time and percent of correct reactions were measured. Genotyping for Val66Met BDNF polymorphism was done by polymerase chain reaction method. In schizophrenia, no relationship between Val66Met polymorphism of the BDNF gene and the results of the WCST was observed. Patients with Val/Val genotype had a higher percentage of correct reactions in the N‐back test than those with the remaining genotypes. Bipolar patients with Val/Val genotype obtained significantly better results on three of five domains of the WCST. No relationship between BDNF polymorphism and the results of the N‐back test was found in this group. A limitation to the results could be variable psychopathological state and medication during cognitive testing and lack of Hardy–Weinberg equilibrium in schizophrenia group. Val66Met polymorphism of the BDNF gene may be associated with cognitive performance on the WCST in bipolar mood disorder but not in schizophrenia. An association of this polymorphism with performance on the N‐back test in schizophrenia and not in bipolar illness may suggest that in schizophrenia, the BDNF system may be connected with early phases of information processing.

Illness-specific association of val66met BDNF polymorphism with performance on Wisconsin Card Sorting Test in bipolar mood disorder

Illness-specific association of val66met BDNF polymorphism with performance on Wisconsin Card Sorting Test in bipolar mood disorder

Association analysis of brain-derived neurotrophic factor (BDNF) gene Val66Met polymorphism in schizophrenia and bipolar affective disorder

Summary Brain-derived neurotrophic factor (BDNF) has been implicated in the pathogenesis of schizophrenia and bipolar disorder. A functional polymorphism Val66Met of BDNF gene was studied in patients with schizophrenia (n=336), bipolar affective disorder (n=352) and healthy controls (n=375). Consensus diagnosis by at least two psychiatrists, according to DSM-IV and ICD-10 criteria, was made for each patient using a structured clinical interview for DSM-IV Axis I disorders (SCID). No association was found between the studied polymorphism and schizophrenia or bipolar affective disorder either for genotype or allele distribution (for genotype: p=0.210 in schizophrenia, p=0.400 in bipolar disorder; for alleles: p=0.260 in schizophrenia, p=0.406 in bipolar disorder). Results were also not significant when analysed by gender. For males genotype distribution and allele frequency were (respectively): p=0.480 and p=0.312 in schizophrenia, p=0.819 and p=0.673 in bipolar affective disorder. Genotype distribution and allele frequency observed in the female group were: p=0.258 for genotypes, p=0.482 for alleles in schizophrenia; p=0.432 for genotypes, p=0.464 for alleles in bipolar affective disorder. A subgroup of schizophrenic (n=62) and bipolar affective patients (n=28) with early age at onset (18 years or younger) was analysed (p=0.328 for genotypes, p=0.253 for alleles in schizophrenia; p=0.032 for genotypes, p=0.858 for alleles in bipolar affective disorder).