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Identification of a common neurobiological substrate for mental illness.

ABSTRACT: Psychiatric diagnoses are currently distinguished based on sets of specific symptoms. However, genetic and clinical analyses find similarities across a wide variety of diagnoses, suggesting that a common neurobiological substrate may exist across mental illness.To conduct a meta-analysis of structural neuroimaging studies across multiple psychiatric diagnoses, followed by parallel analyses of 3 large-scale healthy participant data sets to help interpret structural findings in the meta-analysis.PubMed was searched to identify voxel-based morphometry studies through July 2012 comparing psychiatric patients to healthy control individuals for the meta-analysis. The 3 parallel healthy participant data sets included resting-state functional magnetic resonance imaging, a database of activation foci across thousands of neuroimaging experiments, and a data set with structural imaging and cognitive task performance data.Studies were included in the meta-analysis if they reported voxel-based morphometry differences between patients with an Axis I diagnosis and control individuals in stereotactic coordinates across the whole brain, did not present predominantly in childhood, and had at least 10 studies contributing to that diagnosis (or across closely related diagnoses). The meta-analysis was conducted on peak voxel coordinates using an activation likelihood estimation approach.We tested for areas of common gray matter volume increase or decrease across Axis I diagnoses, as well as areas differing between diagnoses. Follow-up analyses on other healthy participant data sets tested connectivity related to regions arising from the meta-analysis and the relationship of gray matter volume to cognition.Based on the voxel-based morphometry meta-analysis of 193 studies comprising 15?892 individuals across 6 diverse diagnostic groups (schizophrenia, bipolar disorder, depression, addiction, obsessive-compulsive disorder, and anxiety), we found that gray matter loss converged across diagnoses in 3 regions: the dorsal anterior cingulate, right insula, and left insula. By contrast, there were few diagnosis-specific effects, distinguishing only schizophrenia and depression from other diagnoses. In the parallel follow-up analyses of the 3 independent healthy participant data sets, we found that the common gray matter loss regions formed a tightly interconnected network during tasks and at resting and that lower gray matter in this network was associated with poor executive functioning.We identified a concordance across psychiatric diagnoses in terms of integrity of an anterior insula/dorsal anterior cingulate-based network, which may relate to executive function deficits observed across diagnoses. This concordance provides an organizing model that emphasizes the importance of shared neural substrates across psychopathology, despite likely diverse etiologies, which is currently not an explicit component of psychiatric nosology.

SUBMITTER: Goodkind M

PROVIDER: S-EPMC4791058 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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Identification of a common neurobiological substrate for mental illness.

Goodkind Madeleine M Eickhoff Simon B SB Oathes Desmond J DJ Jiang Ying Y Chang Andrew A Jones-Hagata Laura B LB Ortega Brissa N BN Zaiko Yevgeniya V YV Roach Erika L EL Korgaonkar Mayuresh S MS Grieve Stuart M SM Galatzer-Levy Isaac I Fox Peter T PT Etkin Amit A

JAMA psychiatry 20150401 4

<h4>Importance</h4>Psychiatric diagnoses are currently distinguished based on sets of specific symptoms. However, genetic and clinical analyses find similarities across a wide variety of diagnoses, suggesting that a common neurobiological substrate may exist across mental illness.<h4>Objective</h4>To conduct a meta-analysis of structural neuroimaging studies across multiple psychiatric diagnoses, followed by parallel analyses of 3 large-scale healthy participant data sets to help interpret struc ...[more]

PMID: 25651064

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Project description:ObjectivesIt is well known that mental health problems can recur even after effective treatment, leading to an understandable fear of illness recurrence (FIR) and mental health anxiety (MHA). These may themselves contribute to the process of relapse. This study aims to examine whether people recovering from psychosis have greater FIR than those recovering from common mental health problems or healthy controls. The study also hypothesized that there will be a relationship between FIR and MHA and that both these constructs will be associated with maladaptive coping behaviours. Finally, the relationship between mental defeat with FIR and psychological distress (anxiety and depression) will be examined.MethodA cross-sectional questionnaire design was employed. Thirty-nine participants in recovery from psychosis, eighty-two in recovery from other mental health difficulties, and sixty-one healthy controls aged 18-73 were recruited from NHS services and via social media. Self-report questionnaires measured mental defeat, mental health anxiety, fear of illness recurrence, maladaptive coping behaviours, and psychological distress.ResultsThose recovering from psychosis were found to more negatively evaluate the likely consequences of relapse than those recovering from common mental health problems or healthy controls. However, the levels of FIR in common mental health problems were also significantly elevated when compared to healthy controls. There were no other differences between these groups (in terms of mental defeat, anxiety, depression, social functioning, and maladaptive coping behaviours). The hypothesized relationship between FIR and MHA was also found, and both were associated with maladaptive coping behaviours. Mental defeat was associated with FIR and psychological distress (anxiety and depression).ConclusionsThis study found that those with psychosis experienced higher FIR than those with common mental health problems. Furthermore, people defining themselves as in recovery are worried about relapse and the extent of this is linked to mental health anxiety. Given that such responses may contribute to actual relapse, it is important that these issues are better understood and interventions developed to ameliorate them.Practitioner pointsFollowing recovery, fear of relapse may be particularly high in those with experience of psychosis; it is also present in those with common mental health problems The importance of this observation lies in the issue that anxiety about relapse may initiate a self-fulfilling process, with increased anxiety worsening symptoms and vice versa. Cognitive-behavioural therapy for health anxiety may be beneficial to those experiencing high levels of mental health anxiety. Cognitions related to relapse need to be explored and addressed both in further research and, when clearly identified, may be a target during relapse-prevention planning.

Project description:BackgroundCurrent approaches to stratify patients with psychiatric disorders into groups on the basis of violence risk are limited by inconsistency, variable accuracy, and unscalability. To address the need for a scalable and valid tool to assess violence risk in patients with schizophrenia spectrum or bipolar disorder, we describe the derivation of a score based on routinely collected factors and present findings from external validation.MethodsOn the basis of a national cohort of 75 158 Swedish individuals aged 15-65 years with a diagnosis of severe mental illness (schizophrenia spectrum or bipolar disorder) with 574 018 patient episodes between Jan 1, 2001, and Dec 31, 2008, we developed predictive models for violent offending (primary outcome) within 1 year of hospital discharge for inpatients or clinical contact with psychiatric services for outpatients (patient episode) through linkage of population-based registers. We developed a derivation model to determine the relative influence of prespecified criminal history and sociodemographic and clinical risk factors, which are mostly routinely collected, and then tested it in an external validation. We measured discrimination and calibration for prediction of violent offending at 1 year using specified risk cutoffs.FindingsOf the cohort of 75 158 patients with schizophrenia spectrum or bipolar disorder, we assigned 58 771 (78%) to the derivation sample and 16 387 (22%) to the validation sample. In the derivation sample, 830 (1%) individuals committed a violent offence within 12 months of their patient episode. We developed a 16-item model. The strongest predictors of violent offending within 12 months were conviction for previous violent crime (adjusted odds ratio 5·03 [95% CI 4·23-5·98]; p<0·0001), male sex (2·32 [1·91-2·81]; p<0·0001), and age (0·63 per 10 years of age [0·58-0·67]; p<0·0001). In external validation, the model showed good measures of discrimination (c-index 0·89 [0·85-0·93]) and calibration. For risk of violent offending at 1 year, with a 5% cutoff, sensitivity was 62% (95% CI 55-68) and specificity was 94% (93-94). The positive predictive value was 11% and the negative predictive value was more than 99%. We used the model to generate a simple web-based risk calculator (Oxford Mental Illness and Violence tool [OxMIV]).InterpretationWe have developed a prediction score in a national cohort of patients with schizophrenia spectrum or bipolar disorder, which can be used as an adjunct to decision making in clinical practice by identifying those who are at low risk of violent offending. The low positive predictive value suggests that further clinical assessment in individuals at high risk of violent offending is required to establish who might benefit from additional risk management. Further validation in other countries is needed.FundingWellcome Trust and Swedish Research Council.

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Identification of a common neurobiological substrate for mental illness.

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Identification of a common neurobiological substrate for mental illness.

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