Cognitive reserve as an outcome predictor: first-episode affective versus non-affective psychosis

How to treat mania

OBJECTIVE

In this paper, we aimed at reviewing evidence-based treatment options for bipolar mania and proposed tentative evidence-based clinical suggestions regarding the management of a manic episode, especially regarding the choice of the proper mood stabilizer and antipsychotic medication.

METHOD

A narrative review was undertaken addressing 'treatment of bipolar mania'. Findings have been synthesized and incorporated with clinical experience into a model to support different treatment choices.

RESULTS

To date, there is solid evidence supporting the use of several medications, such as lithium, divalproex, and carbamazepine, and antipsychotics, such as chlorpromazine, haloperidol, risperidone, olanzapine, quetiapine, ziprasidone, aripiprazole, inhaled loxapine, asenapine, and cariprazine in acute mania, and some evidence supporting the use of clozapine or electroconvulsive therapy in treatment-refractory cases. However, in clinical practice, when making decisions about treatment, personalized treatment is needed, according to the different clinical presentations and more complex clinical situations within the manic episode and considering a long-term view and with the objective of not only a symptomatic but also functional recovery. After remission from acute mania, psychoeducation strategies are useful to ensure adherence.

DISCUSSION

Despite the evidence forefficacy of many currently available treatments for mania, the majority of RCTs provide little direction for the clinician as to what steps might be optimal in different presentations of mania as well as in the presence of specific patient characteristics. Manic episodes should be managed on a personalized basis considering the clinical course and patient criteria and with the expectation of maintaining that treatment in the long-term.

Examining Gene-Environment Interactions Using Aggregate Scores in a First-Episode Psychosis Cohort

Gene-environment (GxE) interactions have been related to psychosis spectrum disorders, involving multiple common genetic variants in multiple genes with very small effect sizes, and several environmental factors that constitute a dense network of exposures named the exposome. Here, we aimed to analyze GxE in a cohort of 310 first-episode psychotic (FEP) and 236 healthy controls, by using aggregate scores estimated in large populations such as the polygenic risk score for schizophrenia and (PRS-SCZ) and the Maudsley environmental risk score (ERS). In contrast to previous findings, in our study, the PRS-SCZ did not discriminate cases from controls, but the ERS score explained a similar percentage of the variance as in other studies using similar approaches. Our study supports a positive additive interaction, indicating synergy between genetic susceptibility to schizophrenia (PRS-SCZ dichotomized according to the highest quartile distribution of the control population) and the exposome (ERS > 75% of the controls). This additive interaction showed genetic and environmental dose dependence. Our study shows that the use of aggregate scores derived from large and powered studies instead of statistics derived from specific sample characteristics is a powerful tool for the study of the effects of GxE on the risk of psychotic spectrum disorders. In conclusion, by using a genetic risk score and an ERS we have provided further evidence for the role of GxE in psychosis.

Predictors of quality of life in bipolar disorder: A path analytical study

Quality of life (QoL) is an important outcome in psychiatric illnesses like bipolar disorder (BD). However, little is known about the variables that affect it, and therefore contribute to prognosis and treatment outcomes in these populations. This study aimed to explore QoL in BD and investigate its relationship with modifiable (cognitive reserve, cognitive ability, mood symptoms) and non-modifiable factors (diagnosis, previous suicide attempts, substance misuse, age). The WHOQOL-bref was administered to 121 control participants and 109 patients with BD, who also underwent clinical and neuropsychological assessments. Factor analysis was used to identify latent constructs underlying WHOQOL-bref domains, and structural equation models were used to examine predictors of each latent construct. Two latent constructs were identified in the WHOQOL-bref, and labeled 'Personal' and 'Social' QoL. Both were directly predicted by depression symptoms and a diagnosis of BD, and indirectly predicted by (hypo)manic symptoms. Cognitive reserve was a stronger predictor of social QoL than a diagnosis of BD. Our findings suggest that the management of depression symptoms and fostering of cognitive reserve may improve QoL in BD. A diagnosis of BD and/or substance use disorders were risk factors for poor QoL, and may signal the need for preventive interventions to promote well-being.

Placing Cognitive Rigidity in Interpersonal Context in Psychosis: Relationship With Low Cognitive Reserve and High Self-Certainty

Introduction: People with psychosis show impairments in cognitive flexibility, a phenomenon that is still poorly understood. In this study, we tested if there were differences in cognitive and metacognitive processes related to rigidity in patients with psychosis. We compared individuals with dichotomous interpersonal thinking and those with flexible interpersonal thinking. Methods: We performed a secondary analysis using two groups with psychosis, one with low levels of dichotomous interpersonal thinking (n = 42) and the other with high levels of dichotomous interpersonal thinking (n = 43). The patients were classified by splitting interpersonal dichotomous thinking (measured using the repertory grid technique) to the median. The groups were administered a sociodemographic questionnaire, a semi-structured interview to assess psychotic symptoms [Positive and Negative Syndrome Scale (PANSS)], a self-report of cognitive insight [Beck Cognitive Insight Scale (BCIS)], neurocognitive tasks [Wisconsin Card Sorting Test (WCST) and Wechsler Adult Intelligence Scale (WAIS)], and the repertory grid technique. We used a logistic regression model to test which factors best differentiate the two groups. Results: The group with high dichotomous interpersonal thinking had earlier age at onset of the psychotic disorder, higher self-certainty, impaired executive functioning, affected abstract thinking, and lower estimated cognitive reserve than the group with flexible thinking. According to the logistic regression model, estimated cognitive reserve and self-certainty were the variables that better differentiated between the two groups. Conclusion: Cognitive rigidity may be a generalized bias that affects not only neurocognitive and metacognitive processes but also the sense of self and significant others. Patients with more dichotomous interpersonal thinking might benefit from interventions that target this cognitive bias on an integrative way and that is adapted to their general level of cognitive abilities.

The effects of cognitive reserve on predicting and moderating the cognitive and psychosocial functioning of patients with bipolar disorder

BACKGROUND

Cognitive reserve (CR) reflects the resilience of the brain to cope with neuropathological changes and minimize clinical manifestations. In the present study, we explore the association between CR and cognitive and psychosocial functioning, and examined the potential moderating role of CR in patients with bipolar disorder (BD).

METHODS

One hundred and twenty-five outpatients with BD type I and sixty healthy individuals were recruited. All participants were assessed with a neuropsychological battery examining attention and processing speed, working memory, visual memory and executive functioning, the Global Assessment of Functioning scale and the Cognitive Complaints in Bipolar Disorder Rating Assessment. Proxies for cognitive reserve included premorbid intelligence and educational level.

RESULTS

Patients with bipolar disorder presented with worse cognitive performance and psychosocial functioning than healthy controls. Multiple regression models revealed that educational level negatively associated with all assessed domain-specific cognition scores and premorbid intelligence predicted attention and processing speed and psychosocial functioning. Notably, premorbid intelligence significantly moderated the associations between the number of episodes (total, hypo/manic and depressed) and neurocognitive functioning, and the educational level also moderated the relationships between the numbers of hypo/manic and total episodes and subjective cognitive functioning.

CONCLUSIONS

Cognitive reserve contributes to functional outcomes in patients with BD and may emerge as a key factor contributing to the course and prognosis of patients with BD. In the future, cognitive reserve must be considered in both research and clinical interventions related to bipolar disorder.

Cognitive Reserve Assessment Scale in Health (CRASH): Its Validity and Reliability

(1) Background: The cognitive reserve (CR) concept has not been precisely defined in severe mental disorders and has been estimated using heterogeneous methods. This study aims to investigate and develop the psychometric properties of the Cognitive Reserve Assessment Scale in Health (CRASH), an instrument designed to measure CR in people with severe mental illness; (2) Methods: 100 patients with severe mental illness (non-affective psychoses and affective disorders) and 66 healthy controls were included. The internal consistency and convergent validity of CRASH were assessed. Spearman's correlations coefficients were also performed to examine the relationship between CRASH and neuropsychological tests, psychosocial functioning, and clinical course; (3) Results: The internal consistency was high (Cronbach's alpha coefficient = 0.903). The CRASH global score had a large positive correlation with the Cognitive reserve questionnaire total score (r = 0.838, p < 0.001), demonstrating good convergent validity. The correlation coefficients between the CRASH total scores and clinical, functional, and neuropsychological performance were different between groups. In order to provide clinical interpretation, severity classification based on diagnosis (non-affective psychotic disorders, affective disorders, and healthy controls) have been created; (4) Conclusions: CRASH is the first CR measure developed specifically for patients with severe mental illness, facilitating reliable and valid measurement of this construct. The scale may aid in the stratification of patients and the implementation of personalized interventions.

Dementia prevention and reserve against neurodegenerative disease

Similar to other complex disorders, the etiology of Alzheimer disease is multifactorial and characterized by an interplay of biological and environmental risk and protective factors. Potentially modifiable risk factors have emerged from epidemiological research and strategies to prevent neurodegeneration and dementia are currently being tested, including multimodal interventions aiming to reduce several risk factors at once. The concept of reserve was developed based on the observation that certain individual characteristics, such as life experiences, lifestyles, and neurobiological parameters, are associated with a higher resilience against neurodegeneration and its symptoms. Coordinated research is required to maximize the use of available human and financial resources to better understand the underlying neurobiological mechanisms of reserve and to translate research findings into effective public health interventions.

Cognitive Remediation Interventions in Schizoaffective Disorder: A Systematic Review

Background: Patients with schizoaffective disorder (SAD) suffer from cognitive impairment, which negatively influences their functionality. Cognitive remediation (CR) interventions have been shown to be effective in patients with schizophrenia (SZ) and bipolar disorder (BD), but evidence in SAD is limited so far. The aim of this study is to systematically review the published data on CR interventions, either in neurocognition or social cognition, in patients with SAD. Methods: We conducted a comprehensive, computerized literature search using terms related to CR interventions in psychotic and affective disorders, and particularly in SAD. Pubmed, Embase, and Web of Knowledge databases were used up to February 28th, 2018 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The search returned 2672 articles of which four were finally selected meeting the inclusion criteria. Results: Cognitive Enhancement Therapy, computerized Cognitive Remediation Therapy and Cognitive Training showed positive results in subsamples of patients with SAD regarding neurocognition and functioning in comparable terms to patients with schizophrenia as well as in a greater extent in quality of life. Benefits in social cognition were also described when Social Cognition Interaction Training was considered in patients with SAD. Conclusions: CR interventions seem to improve neurocognition and social cognition in patients with SAD as well as functioning and quality of life. However, further randomized controlled trials on CR interventions with an optimized design focusing on selected sample of patients with SAD are imperative.

Toward Precision Psychiatry in Bipolar Disorder: Staging 2.0

Personalized treatment is defined as choosing the "right treatment for the right person at the right time." Although psychiatry has not yet reached this level of precision, we are on the way thanks to recent technological developments that may aid to detect plausible molecular and genetic markers. At the moment there are some models that are contributing to precision psychiatry through the concept of staging. While staging was initially presented as a way to categorize patients according to clinical presentation, course, and illness severity, current staging models integrate multiple levels of information that can help to define each patient's characteristics, severity, and prognosis in a more precise and individualized way. Moreover, staging might serve as the foundation to create a clinical decision-making algorithm on the basis of the patient's stage. In this review we will summarize the evolution of the bipolar disorder staging model in relation to the new discoveries on the neurobiology of bipolar disorder. Furthermore, we will discuss how the latest and future progress in psychiatry might transform current staging models into precision staging models.