Improving antidepressant outcomes: what works for whom and why?

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Thalia Eley and Gerome Breen explore a new systematic meta-review of predictors of antidepressant treatment outcome in depression, which looks at clinical and demographic variables, but also biomarkers including both genetic and neuroimaging data.

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Risk factors and peripheral biomarkers for schizophrenia spectrum disorders

This 'umbrella review' aimed to systematically appraise the meta-analyses of observational studies on risk factors and peripheral biomarkers for schizophrenia spectrum disorders.

Marcus Munafo considers the findings of a systematic review of meta-analyses of observational studies, which looks at risk factors and peripheral biomarkers for psychotic disorders on the schizophrenia spectrum.

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Salivary biomarkers for diagnosing periodontal disease

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This review of salivary biomarkers for diagnosing periodontal disease only identified 4 studies at high risk of bias but suggests a small number of potential biomarkers. However the findings should be interpreted with caution.

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Rise of the machine learning algorithm: the future of diagnosing schizophrenia?

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Samei Huda reviews a meta-analysis of multivariate pattern recognition studies, which aims to detect neuroimaging biomarkers for schizophrenia.

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Can fMRI measuring striatal connectivity help predict response to antipsychotics?

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Samei Huda steps into George Clooney’s shoes to discuss baseline striatal functional connectivity as a predictor of response to antipsychotic drug treatment.

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Could measuring cortisol levels become a biological test for risk of depression in adolescent males?

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Is it possible to work out which of two adolescents sitting before you complaining of unhappiness, which one will go home and sleep it off and which will go on to develop an episode of major depression? Has the biological revolution in psychiatry finally come to fruition with a useful biomarker for making treatment decisions? [read the full story…]