Affective dysfunction in a mouse model of Rett syndrome: therapeutic effects of environmental stimulation and physical activity

Rett syndrome (RTT) is a neurodevelopmental disorder associated with mutations in the X-linked gene encoding methyl-CpG-binding protein 2 (MeCP2) and consequent dysregulation of brain maturation. Patients suffer from a range of debilitating physical symptoms, however, behavioral and emotional symptoms also severely affect their quality of life. Here, we present previously unreported and clinically relevant affective dysfunction in the female heterozygous Mecp2tm1Tam mouse model of RTT (129sv and C57BL6 mixed background). The affective dysfunction and aberrant anxiety-related behavior of the Mecp2+ / - mice were found to be reversible with environmental enrichment (EE) from 4 weeks of age. The effect of exercise alone (via wheel running) was also explored, providing the first evidence that increased voluntary physical activity in an animal model of RTT is beneficial for some phenotypes. Mecp2+ / - mutants displayed elevated corticosterone despite decreased Crh expression, demonstrating hypothalamic-pituitary-adrenal axis dysregulation. EE of Mecp2+ / - mice normalized basal serum corticosterone and hippocampal BDNF protein levels. The enrichment-induced rescue appears independent of the transcriptional regulation of the MeCP2 targets Bdnf exon 4 and Crh. These findings provide new insight into the neurodevelopmental role of MeCP2 and pathogenesis of RTT, in particular the affective dysfunction. The positive outcomes of environmental stimulation and physical exercise have implications for the development of therapies targeting the affective symptoms, as well as behavioral and cognitive dimensions, of this devastating neurodevelopmental disorder.

Investigating the affective core of SWB: the circular way

 This thesis builds on premises from the subjective wellbeing homeostasis theoretical framework, and applies constructs from circumplex theories of affect. The findings inform basic affective science by using circumplex modeling and curve-fitting to identify the set-point core affective state associated with normal self-perceptions, and overall life satisfaction.

Effects of affective and anxiety disorders on outcome in problem gamblers attending routine cognitive-behavioural treatment in South Australia

This study evaluated the influence of 12-month affective and anxiety disorders on treatment outcomes for adult problem gamblers in routine cognitive–behavioural therapy. A cohort study at a state-wide gambling therapy service in South Australia. Primary outcome measure was rated by participants using victorian gambling screen (VGS) ‘harm to self’ sub-scale with validated cut score 21? (score range 0–60) indicative of problem gambling behaviour. Secondary outcome measure was Work and Social Adjustment Scale (WSAS). Independent variable was severity of affective and anxiety disorders based on Kessler 10 scale. We used propensity score adjusted random-effects models to estimate treatment outcomes for sub-populations of individuals from baseline to 12 month follow-up. Between July, 2010 and December, 2012, 380 participants were eligible for inclusion in the final analysis. Mean age was 44.1 (SD = 13.6) years and 211 (56 %) were males. At baseline, 353 (92.9 %) were diagnosed with a gambling disorder using VGS. For exposure, 175 (46 %) had a very high probability of a 12-month affective or anxiety disorder, 103 (27 %) in the high range and 102 (27 %) in the low to moderate range. For the main analysis, individuals experienced similar clinically significant reductions (improvement) in gambling related outcomes across time (p\0.001). Individuals with co-varying patterns of problem gambling and 12 month affective and anxiety disorders who present to a gambling help service for treatment in metropolitan South Australia

Discovering latent affective dynamics among individuals in online mental health-related communities

Discovering dynamics of emotion and mood changes for individuals has the potential to enhance the diagnosis and treatment of mental disorders. In this paper we study affective transitions and dynamics among individuals in online mental health communities. Using social media as form of 'sensor', we crawl a large dataset of blogs posted by online communities whose descriptions declared to be associated with affective disorder conditions such as depression, anxiety, or autism. We then apply nonnegative matrix factorization model to extract the common and individual factors of affective transitions across groups of individuals in different levels of affective disorders. We examine the latent patterns of emotional transitions and investigate the effects of emotional transitions across the cohorts. Our framework is novel as it utilizes social media as an online sensing platform of mood and emotional dynamics. Hence, our work has implication in constructing systems to screen individuals and communities at high risks of mental health problems in online settings.