Sexual dysfunction during treatment with serotonergic and noradrenergic antidepressants: Clinical description and the role of the 5-HTTLPR

Objectives. Sexual dysfunction (SD) is a frequently reported side-effect of antidepressant treatment, particularly of selective serotonin reuptake inhibitors (SSRIs). In the multicentre clinical and pharmacogenetic GENDEP study (Genome-based Therapeutic Drugs for Depression), the effect of the serotonin transporter gene promoter polymorphism 5-HTTLPR on sexual function was investigated during treatment with escitalopram (SSRI) and nortriptyline (tricyclic antidepressant). Methods. A total of 494 subjects with an episode of DSM-IV major depression were randomly assigned to treatment with escitalopram or nortriptyline. Over 12 weeks, depressive symptoms and SD were measured weekly with the Montgomery-Asberg Depression Rating Scale, the Antidepressant Side-Effect Checklist, the UKU Side Effect Rating Scale, and the Sexual Functioning Questionnaire. Results. The incidence of reported SD after 12 weeks of treatment was relatively low, and did not differ significantly between antidepressants (14.9% escitalopram, 19.7% nortriptyline). There was no significant interaction between the 5-HTTLPR and antidepressant on SD. Improvement in depressive symptoms and younger age were both associated with lower SD. The effect of age on SD may have been moderated by the 5-HTTLPR. Conclusions. In GENDEP, rates of reported SD during treatment were lower than those described in previous reports. There was no apparent effect of the 5-HTTLPR on the observed decline in SD. © 2011 Informa Healthcare.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Neuropsychosocial profiles of current and future adolescent alcohol misusers

A comprehensive account of the causes of alcohol misuse must accommodate individual differences in biology, psychology and environment, and must disentangle cause and effect. Animal models1 can demonstrate the effects of neurotoxic substances; however, they provide limited insight into the psycho-social and higher cognitive factors involved in the initiation of substance use and progression to misuse. One can search for pre-existing risk factors by testing for endophenotypic biomarkers2 in non-using relatives; however, these relatives may have personality or neural resilience factors that protect them from developing dependence3. A longitudinal study has potential to identify predictors of adolescent substance misuse, particularly if it can incorporate a wide range of potential causal factors, both proximal and distal, and their influence on numerous social, psychological and biological mechanisms4. Here we apply machine learning to a wide range of data from a large sample of adolescents (n = 692) to generate models of current and future adolescent alcohol misuse that incorporate brain structure and function, individual personality and cognitive differences, environmental factors (including gestational cigarette and alcohol exposure), life experiences, and candidate genes. These models were accurate and generalized to novel data, and point to life experiences, neurobiological differences and personality as important antecedents of binge drinking. By identifying the vulnerability factors underlying individual differences in alcohol misuse, these models shed light on the aetiology of alcohol misuse and suggest targets for prevention

Genetics of dyslexia: the evolving landscape

Dyslexia is among the most common neurodevelopmental disorders, with a prevalence of 5–12%. At the phenotypic level, various cognitive components that enable reading and spelling and that are disturbed in affected individuals can be distinguished. Depending on the phenotype dimension investigated, inherited factors are estimated to account for up to 80%. Linkage findings in dyslexia are relatively consistent across studies in comparison to findings for other neuropsychiatric disorders. This is particularly true for chromosome regions 1p34–p36, 6p21–p22, 15q21 and 18q11. Four candidate genes have recently been identified through systematic linkage disequilibrium studies in linkage region 6p21–p22, and through cloning approaches at chromosomal breakpoints. Results indicate that a disturbance in neuronal migration is a pathological correlate of dyslexia at the functional level. This review presents a summary of the latest insights into the genetics of dyslexia and an overview of anticipated future developments

The catechol-O-methyl transferase (COMT) gene and its potential association with schizophrenia: Findings from a large German case-control and family-based sample

The aim of the present study was to investigate possible associations between schizophrenia and 13 SNP markers in COMT. No association was observed in 631 cases, 207 nuclear families, and 776 controls. A cognitive performance phenotype (Trail Marking Test) was available for a subgroup of the patients. No association was found between the 13 markers and this phenotype. Four clinically-defined subgroups (early age at onset, negative symptoms, family history of schizophrenia, and life-time major depressive episode) were also investigated. Associations were observed for 3 of these subgroups, although none withstood correction for multiple testing. COMT does not appear to be a risk factor for schizophrenia in this population

G72 and its association with major depression and neuroticism in large population-based groups from Germany

OBJECTIVE: G72 is among the most frequently replicated vulnerability genes for schizophrenia and bipolar disorder. The authors previously found identical haplotypes of markers M23 and M24 to be associated with schizophrenia, bipolar disorder, and panic disorder. Given both the well-recognized familial clustering across these disorders and recent linkage findings implicating the region harboring G72 in the etiology of major depression and panic disorder, we can hypothesize that G72 should also be involved in the etiology of major depression. Neuroticism, measuring trait anxiety, may be the endophenotypic link underlying genetic associations with G72 across diagnostic boundaries. The authors tested whether the previously observed risk haplotypes are also associated with major depression and neuroticism. METHOD: The authors performed a standard haplotype analysis in a group of 500 major depression patients and 1,030 population-based comparison subjects. The authors also performed an exploratory analysis on 10 additional G72 markers using a novel haplotype-sharing approach. They performed a quantitative trait haplotype analysis in an independent group of 907 individuals phenotyped for neuroticism. RESULTS: The previously identified M23-M24 risk haplotype was significantly associated with major depression and high levels of neuroticism. The haplotype-sharing analysis also implicated the same region, whereas more proximal markers showed no association with major depression. CONCLUSIONS: This is the first study to the authors’ knowledge to implicate the G72 locus in the etiology of major depression and neuroticism. The results strengthen the notion of a genetic overlap between diagnoses, commonly conceptualized as distinct entities. Neuroticism may constitute the common underlying endophenotypic link

Variation in GNB3 predicts response and adverse reactions to antidepressants

There is substantial inter-individual variation in response and adverse reactions to antidepressants, and genetic variation may, in part, explain these differences. GNB3 encodes the β3 subunit of the G protein complex, which is involved in the downstream signalling cascade following monoamine receptor activation. A functional polymorphism in this gene (C825T) has been associated with response to antidepressants. Several lines of evidence suggest that GNB3 moderates improvement in the neurovegetative symptoms of depression (such as sleep and appetite) and related adverse reactions independently of change in core mood symptoms. We here report analysis of data from GENDEP, a part-randomized pharmacogenomic trial, on the outcome of 811 subjects with major depression undergoing treatment with either escitalopram or nortriptyline in which the C825T SNP and three further SNPs in GNB3 were genotyped. The TT genotype was significantly associated with a superior response to nortriptyline and these effects were specific to improvements in neurovegetative symptoms. In addition, the same genotype predicted fewer incidents of treatment-emergent insomnia and greater weight gain on the same drug. Our results are consistent with previous associations with GNB3 and emphasize the importance of signalling genes in antidepressant response. © The Author(s) 2011 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Whole-brain gray matter maturation trajectories associated with autistic traits from adolescence to early adulthood

International audienceAbstract A growing number of evidence supports a continued distribution of autistic traits in the general population. However, brain maturation trajectories of autistic traits as well as the influence of sex on these trajectories remain largely unknown. We investigated the association of autistic traits in the general population, with longitudinal gray matter (GM) maturation trajectories during the critical period of adolescence. We assessed 709 community-based adolescents (54.7% women) at age 14 and 22. After testing the effect of sex, we used whole-brain voxel-based morphometry to measure longitudinal GM volumes changes associated with autistic traits measured by the Social Responsiveness Scale (SRS) total and sub-scores. In women, we observed that the SRS was associated with slower GM volume decrease globally and in the left parahippocampus and middle temporal gyrus. The social communication sub-score correlated with slower GM volume decrease in the left parahippocampal, superior temporal gyrus, and pallidum; and the social cognition sub-score correlated with slower GM volume decrease in the left middle temporal gyrus, the right ventromedial prefrontal and orbitofrontal cortex. No longitudinal association was found in men. Autistic traits in young women were found to be associated with specific brain trajectories in regions of the social brain and the reward circuit known to be involved in Autism Spectrum Disorder. These findings support both the hypothesis of an earlier GM maturation associated with autistic traits in adolescence and of protective mechanisms in women. They advocate for further studies on brain trajectories associated with autistic traits in women

Anxiety onset in adolescents: a machine-learning prediction

International audienceAbstract Recent longitudinal studies in youth have reported MRI correlates of prospective anxiety symptoms during adolescence, a vulnerable period for the onset of anxiety disorders. However, their predictive value has not been established. Individual prediction through machine-learning algorithms might help bridge the gap to clinical relevance. A voting classifier with Random Forest, Support Vector Machine and Logistic Regression algorithms was used to evaluate the predictive pertinence of gray matter volumes of interest and psychometric scores in the detection of prospective clinical anxiety. Participants with clinical anxiety at age 18–23 ( N = 156) were investigated at age 14 along with healthy controls ( N = 424). Shapley values were extracted for in-depth interpretation of feature importance. Prospective prediction of pooled anxiety disorders relied mostly on psychometric features and achieved moderate performance (area under the receiver operating curve = 0.68), while generalized anxiety disorder (GAD) prediction achieved similar performance. MRI regional volumes did not improve the prediction performance of prospective pooled anxiety disorders with respect to psychometric features alone, but they improved the prediction performance of GAD, with the caudate and pallidum volumes being among the most contributing features. To conclude, in non-anxious 14 year old adolescents, future clinical anxiety onset 4–8 years later could be individually predicted. Psychometric features such as neuroticism, hopelessness and emotional symptoms were the main contributors to pooled anxiety disorders prediction. Neuroanatomical data, such as caudate and pallidum volume, proved valuable for GAD and should be included in prospective clinical anxiety prediction in adolescents