Open-label add-on treatment trial of minocycline in fragile X syndrome

<p>Abstract</p> <p>Background</p> <p>Fragile X syndrome (FXS) is a disorder characterized by a variety of disabilities, including cognitive deficits, attention-deficit/hyperactivity disorder, autism, and other socio-emotional problems. It is hypothesized that the absence of the fragile X mental retardation protein (FMRP) leads to higher levels of matrix metallo-proteinase-9 activity (MMP-9) in the brain. Minocycline inhibits MMP-9 activity, and alleviates behavioural and synapse abnormalities in <it>fmr1 </it>knockout mice, an established model for FXS. This open-label add-on pilot trial was conducted to evaluate safety and efficacy of minocycline in treating behavioural abnormalities that occur in humans with FXS.</p> <p>Methods</p> <p>Twenty individuals with FXS, ages 13-32, were randomly assigned to receive 100 mg or 200 mg of minocycline daily. Behavioural evaluations were made prior to treatment (baseline) and again 8 weeks after daily minocycline treatment. The primary outcome measure was the Aberrant Behaviour Checklist-Community Edition (ABC-C) Irritability Subscale, and the secondary outcome measures were the other ABC-C subscales, clinical global improvement scale (CGI), and the visual analog scale for behaviour (VAS). Side effects were assessed using an adverse events checklist, a complete blood count (CBC), hepatic and renal function tests, and antinuclear antibody screen (ANA), done at baseline and at 8 weeks.</p> <p>Results</p> <p>The ABC-C Irritability Subscale scores showed significant improvement (p < 0.001), as did the VAS (p = 0.003) and the CGI (p < 0.001). The only significant treatment-related side effects were minor diarrhea (n = 3) and seroconversion to a positive ANA (n = 2).</p> <p>Conclusions</p> <p>Results from this study demonstrate that minocycline provides significant functional benefits to FXS patients and that it is well-tolerated. These findings are consistent with the <it>fmr1 </it>knockout mouse model results, suggesting that minocycline modifies underlying neural defects that account for behavioural abnormalities. A placebo-controlled trial of minocycline in FXS is warranted.</p> <p>Trial registration</p> <p>ClinicalTrials.gov Open-Label Trial NCT00858689.</p

Involvement of Gut Microbiota in Schizophrenia and Treatment Resistance to Antipsychotics

The gut microbiota is constituted by more than 40,000 bacterial species involved in key processes including high order brain functions. Altered composition of gut microbiota has been implicated in psychiatric disorders and in modulating the efficacy and safety of psychotropic medications. In this work we characterized the composition of the gut microbiota in 38 patients with schizophrenia (SCZ) and 20 healthy controls (HC), and tested if SCZ patients with different response to antipsychotics (18 patients with treatment resistant schizophrenia (TRS), and 20 responders (R)) had specific patterns of gut microbiota composition associated with different response to antipsychotics. Moreover, we also tested if patients treated with typical antipsychotics (n = 20) presented significant differences when compared to patients treated with atypical antipsychotics (n = 31). Our findings showed the presence of distinct composition of gut microbiota in SCZ versus HC, with several bacteria at the different taxonomic levels only present in either one group or the other. Similar findings were observed also depending on treatment response and exposure to diverse classes of antipsychotics. Our results suggest that composition of gut microbiota could constitute a biosignatures of SCZ and TRS

Genetic determinants of coping, resilience and self-esteem in schizophrenia suggest a primary role for social factors and hippocampal neurogenesis

Schizophrenia is a severe psychiatric disorder, associated with a reduction in life expectancy of 15-20 years. Available treatments are at least partially effective in most affected individuals, and personal resources such as resilience (successful adaptation despite adversity) and coping abilities (strategies used to deal with stressful or threatening situations), are important determinants of disease outcomes and long-term sustained recovery. Published findings support the existence of a genetic background underlying resilience and coping, with variable heritability estimates. However, genome-wide analyses concerning the genetic determinants of these personal resources, especially in the context of schizophrenia, are lacking. Here, we performed a genome-wide association study coupled with accessory analyses to investigate potential genetic determinants of resilience, coping and self- esteem in 490 schizophrenia patients. Results revealed a complex genetic background partly overlapping with that of neuroticism, worry and schizophrenia itself and support the importance of social aspects in shapingthese psychological constructs. Hippocampal neurogenesis and lipid metabolism appear to be potentially relevant biological underpinnings, and specific miRNAs such as miR-124 and miR-137 may warrant further studies as potential biomarkers. In conclusion, this study represents an important first step in the identification of genetic and biological correlates shaping resilience, coping resources and self-esteem in schizophrenia

Clinical and psychological factors associated with resilience in patients with schizophrenia: data from the Italian network for research on psychoses using machine learning

Background: Resilience is defined as the ability to modify thoughts to cope with stressful events. Patients with schizophrenia (SCZ) having higher resilience (HR) levels show less severe symptoms and better real-life functioning. However, the clinical factors contributing to determine resilience levels in patients remain unclear. Thus, based on psychological, historical, clinical and environmental variables, we built a supervised machine learning algorithm to classify patients with HR or lower resilience (LR). Methods: SCZ from the Italian Network for Research on Psychoses (N = 598 in the Discovery sample, N = 298 in the Validation sample) underwent historical, clinical, psychological, environmental and resilience assessments. A Support Vector Machine algorithm (based on 85 variables extracted from the above-mentioned assessments) was built in the Discovery sample, and replicated in the Validation sample, to classify between HR and LR patients, within a nested, Leave-Site-Out Cross-Validation framework. We then investigated whether algorithm decision scores were associated with the cognitive and clinical characteristics of patients. Results: The algorithm classified patients as HR or LR with a Balanced Accuracy of 74.5% (p < 0.0001) in the Discovery sample, and 80.2% in the Validation sample. Higher self-esteem, larger social network and use of adaptive coping strategies were the variables most frequently chosen by the algorithm to generate decisions. Correlations between algorithm decision scores, socio-cognitive abilities, and symptom severity were significant (pFDR < 0.05). Conclusions: We identified an accurate, meaningful and generalizable clinical-psychological signature associated with resilience in SCZ. This study delivers relevant information regarding psychological and clinical factors that non-pharmacological interventions could target in schizophrenia