Standardisation framework for the Maudsley staging method for treatment resistance in depression.

BACKGROUND: Treatment-resistant depression (TRD) is a serious and relatively common clinical condition. Lack of consensus on defining and staging TRD remains one of the main barriers to understanding TRD and approaches to intervention. The Maudsley Staging Method (MSM) is the first multidimensional model developed to define and stage treatment-resistance in "unipolar depression". The model is being used increasingly in treatment and epidemiological studies of TRD and has the potential to support consensus. Yet, standardised methods for rating the MSM have not been described adequately. The aim of this report is to present standardised approaches for rating or completing the MSM. METHOD: Based on the initial development of the MSM and a narrative review of the literature, the developers of the MSM provide explicit guidance on how the three dimensions of the MSM--treatment failure, severity of depressive episode and duration of depressive episode-- may be rated. RESULT: The core dimension of the MSM, treatment failure, may be assessed using the Maudsley Treatment Inventory (MTI), a new method developed for the purposes of completing the MSM. The MTI consists of a relatively comprehensive list of medications with options for rating doses and provisions treatment for multiple episodes. The second dimension, severity of symptoms, may be assessed using simple instruments such as the Clinical Global Impression, the Psychiatric Status Rating or checklist from a standard diagnostic checklist. The standardisation also provides a simple rating scale for scoring the third dimension, duration of depressive episode. CONCLUSION: The approaches provided should have clinical and research utility in staging TRD. However, in proposing this model, we are fully cognisant that until the pathophysiology of depression is better understood, staging methods can only be tentative approximations. Future developments should attempt to incorporate other biological/ pathophysiological dimensions for staging.

Impaired Glucose Homeostasis in First-Episode Schizophrenia: A Systematic Review and Meta-analysis.

IMPORTANCE: Schizophrenia is associated with an increased risk of type 2 diabetes. However, it is not clear whether schizophrenia confers an inherent risk for glucose dysregulation in the absence of the effects of chronic illness and long-term treatment. OBJECTIVE: To conduct a meta-analysis examining whether individuals with first-episode schizophrenia already exhibit alterations in glucose homeostasis compared with controls. DATA SOURCES: The EMBASE, MEDLINE, and PsycINFO databases were systematically searched for studies examining measures of glucose homeostasis in antipsychotic-naive individuals with first-episode schizophrenia compared with individuals serving as controls. STUDY SELECTION: Case-control studies reporting on fasting plasma glucose levels, plasma glucose levels after an oral glucose tolerance test, fasting plasma insulin levels, insulin resistance, and hemoglobin A1c (HbA1c) levels in first-episode antipsychotic-naive individuals with first-episode schizophrenia compared with healthy individuals serving as controls. Two independent investigators selected the studies. DATA EXTRACTION: Two independent investigators extracted study-level data for a random-effects meta-analysis. Standardized mean differences in fasting plasma glucose levels, plasma glucose levels after an oral glucose tolerance test, fasting plasma insulin levels, insulin resistance, and HbA1c levels were calculated. Sensitivity analyses examining the effect of body mass index, diet and exercise, race/ethnicity, and minimal (≤2 weeks) antipsychotic exposure were performed. DATA SYNTHESIS: Of 3660 citations retrieved, 16 case-control studies comprising 15 samples met inclusion criteria. The overall sample included 731 patients and 614 controls. Fasting plasma glucose levels (Hedges g = 0.20; 95% CI, 0.02 to 0.38; P = .03), plasma glucose levels after an oral glucose tolerance test (Hedges g = 0.61; 95% CI, 0.16 to 1.05; P = .007), fasting plasma insulin levels (Hedges g = 0.41; 95% CI, 0.09 to 0.72; P = .01), and insulin resistance (homeostatic model assessment of insulin resistance) (Hedges g = 0.35; 95% CI, 0.14 to 0.55; P = .001) were all significantly elevated in patients compared with controls. However, HbA1c levels (Hedges g = -0.08; CI, -0.34 to 0.18; P = .55) were not altered in patients compared with controls. CONCLUSIONS AND RELEVANCE: These findings show that glucose homeostasis is altered from illness onset in schizophrenia, indicating that patients are at increased risk of diabetes as a result. This finding has implications for the monitoring and treatment choice for patients with schizophrenia.

Transcriptional consequences of schizophrenia candidate miR-137 manipulation in human neural progenitor cells.

MIR137, transcribed as the microRNA miR-137, is one of the leading candidate schizophrenia susceptibility genes to arise from large genome-wide association studies (GWAS) of the disorder. Recent data suggest that miR-137 modulates the expression of other schizophrenia susceptibility genes. Although bioinformatic resources are available with which to predict genes regulated by individual microRNA, there has been a lack of empirical data on genome-wide gene expression changes following miR-137 manipulation. We have therefore performed a genome-wide assessment of transcriptional changes in a human neural progenitor cell line after miR-137 over-expression and inhibition in order to elucidate molecular pathways by which genetic perturbation of miR-137 could promote susceptibility to schizophrenia. Bioinformatically-predicted miR-137 targets showed a small but highly significant down-regulation following miR-137 over-expression. Genes that were significantly down-regulated in association with miR-137 over-expression were enriched for involvement in neuronal differentiation. Differentially expressed genes that were confirmed by qPCR included others at genome-wide significant risk loci for schizophrenia (MAD1L1 and DPYD) and BDNF. These data point to molecular pathways through which genetic variation at the MIR137 locus could confer risk for schizophrenia.