White matter correlates of psychosis-linked traits support continuity between personality and psychopathology

Characterizing the relationship between personality dimensions and psychosis-specific clinical characteristics

BACKGROUND

Past studies associating personality with psychosis have been limited by small nonclinical samples and a focus on general symptom burden. This study uses a large clinical sample to examine personality's relationship with psychosis-specific features and compare personality dimensions across clinically and neurobiologically defined categories of psychoses.

METHODS

A total of 1352 participants with schizophrenia, schizoaffective disorder, and bipolar with psychosis, as well as 623 healthy controls (HC), drawn from the Bipolar-Schizophrenia Network for Intermediate Phenotypes (BSNIP-2) study, were included. Three biomarker-derived biotypes were used to separately categorize the probands. Mean personality factors (openness, conscientiousness, extraversion, agreeableness, and neuroticism) were compared between HC and proband subgroups using a generalized linear model. A robust linear regression was utilized to determine personality differences across biotypes and diagnostic subgroups. Associations between personality factors and cognition were determined through Pearson's correlation. A canonical correlation was run between the personality factors and general functioning, positive symptoms, and negative symptoms to delineate the relationship between personality and clinical outcomes of psychosis.

RESULTS

There were significant personality differences between the proband and HC groups across all five personality factors. Overall, the probands had higher neuroticism and lower extraversion, agreeableness, conscientiousness, and openness. Openness showed the greatest difference across the diagnostic subgroups and biotypes, and greatest correlation with cognition. Openness, agreeableness, and extraversion had the strongest associations with symptom severity.

CONCLUSIONS

Individuals with psychotic disorders have different personality traits compared to HC. In particular, openness may be relevant in distinguishing psychosis-specific phenotypes and experiences, and associated with biological underpinnings of psychosis, including cognition. Further studies should identify potential causal factors and mediators of this relationship.

Evaluating the Exposome Score for Schizophrenia in a Transdiagnostic Psychosis Cohort: Associations With Psychosis Risk, Symptom Severity, and Personality Traits

BACKGROUND

Investigations of causal pathways for psychosis can be guided by the identification of environmental risk factors. A recently developed composite risk tool, the exposome score for schizophrenia (ES-SCZ), which controls for intercorrelations between risk factors, has shown fair to good performance. We tested the transdiagnostic psychosis classifier performance of the ES-SCZ with the Bipolar-Schizophrenia Network for Intermedial Phenotypes data and examined its relationship with clinical-level outcomes.

STUDY DESIGN

We computed the case-control classifier performance for the ES-SCZ from cross-sectional data on 1055 volunteers with psychotic diagnoses (schizophrenia, schizoaffective, bipolar psychosis) and 510 controls. Multivariate regression models were used to control for the correlations between outcomes and to correct for the effects of age, sex, and family socioeconomic status across outcomes. We estimated association for the ES-SCZ with psychosis and mood symptom severity, the 5-factor model of personality, and function across biologically defined biotypes, traditional diagnostic categories, and controls.

STUDY RESULTS

ES-SCZ classifier performance for psychosis was fair to good. ES-SCZ associations with personality factor scores were qualitatively similar between psychosis groups and controls with decreased conscientiousness and agreeableness and increased neuroticism. The patterns of associations between ES-SCZ and symptoms differed across biotypes and diagnoses. Biotype 3 and bipolar disorder had consistent within-group associations where greater exposome score predicted more severe symptoms and worse function.

CONCLUSIONS

ES-SCZ performance was consistent with previous reports in this transdiagnostic psychosis sample (adjusted odds ratio: 3.331 [2.834, 3.915], P < .001; area under the curve: 0.762 [0.735, 0.789]). Individual differences in ES-SCZ magnitude may be useful for investigating causal pathways between developmentally relevant exposures and symptomatic expression of psychosis.

Characterizing the Relationship between Personality Dimensions and Psychosis-Specific Clinical Characteristics

Background

Past studies associating personality with psychosis have been limited by small nonclinical samples and a focus on general symptom burden. This study uses a large clinical sample to examine personality's relationship with psychosis-specific features and compare personality dimensions across clinically and neurobiologically defined categories of psychoses.

Methods

A total of 1352 participants with schizophrenia, schizoaffective disorder, and bipolar with psychosis, as well as 623 healthy controls (HC), drawn from the Bipolar-Schizophrenia Network for Intermediate Phenotypes (BSNIP-2) study, were included. Three biomarker-derived biotypes were used to separately categorize the probands. Mean personality factors (openness, conscientiousness, extraversion, agreeableness, and neuroticism) were compared between HC and proband subgroups using independent sample t-tests. A robust linear regression was utilized to determine personality differences across biotypes and diagnostic subgroups. Associations between personality factors and cognition were determined through Pearson's correlation. A canonical correlation was run between the personality factors and general functioning, positive symptoms, and negative symptoms to delineate the relationship between personality and clinical outcomes of psychosis.

Results

There were significant personality differences between the proband and HC groups across all five personality factors. Overall, the probands had higher neuroticism and lower extraversion, agreeableness, conscientiousness, and openness. Openness showed the greatest difference across the diagnostic subgroups and biotypes, and greatest correlation with cognition. Openness, agreeableness, and extraversion had the strongest associations with symptom severity.

Conclusions

Individuals with psychosis have different personality profiles compared to HC. In particular, openness may be relevant in distinguishing psychosis-specific phenotypes and experiences, and associated with biological underpinnings of psychosis, including cognition. Further studies should identify potential causal factors and mediators of this relationship.

Beyond the brain localization of complex traits: Distributed white matter markers of personality

OBJECTIVE

Extensive work in personality neuroscience has shown mixed results in the ability to localize reliable relationships between personality traits and neuroimaging measures. However, recent work in translational neuroimaging has recognized that multifaceted psychological dispositions are not represented in discrete, highly localized brain areas. As such, standard univariate neuroimaging analyses may not be well-suited for capturing broad personality traits supported by distributed networks.

METHOD

The present study uses an out-of-sample predictive modeling approach to identify multivariate signatures of Big Five personality traits within the structural integrity of white matter pathways using diffusion magnetic resonance imaging. In Study 1 (N = 491), we trained a ridge regression model to predict each of the Big Five traits and tested these models in an independent hold-out subsample.

RESULTS

We found that models for both Neuroticism and Openness were significantly related to predictive accuracy in the hold-out sample. Study 2 (N = 108) applied Study 1's predictive models to an independent set of data collected on a different scanner and using a different Big Five scale. Here, we found that the model for Neuroticism remained a significant predictor of individual difference.

CONCLUSION

Our findings provide evidence that this white matter signature of Neuroticism generalizes across differences in measurement and samples.

Trait absorption predicts enhanced face emotion intensity discrimination among military recruits

Accurate emotion perception is an indicator of current psychosocial functioning. Past studies have reported variable relationships between impaired emotion identification, maladaptive personality traits, and psychopathology. We examined associations between discrimination performance and trait negative emotionality, positive emotionality, constraint, and absorption using the Multidimensional Personality Questionnaire. New military soldiers (n = 548) viewed perceptually similar face pairs and picked the face with greater emotional intensity. Emotional intensity differences were small (10%, 20%, 30%, or 40%). Among the most ambiguous conditions (10%, 20%, 30%), absorption predicted higher accuracy. Negative emotionality predicted lower accuracy irrespective of percent difficulty. Furthermore, absorption predicted longer engagement during the 10% condition. Constraint predicted longer engagement regardless of the difficulty condition. Trait absorption accuracy effects were specific for sad, angry, and fearful faces, while negative emotionality accuracy effects were specific for sad faces. The findings highlight absorption as an underappreciated domain for explaining motivational engagement with faces and negative emotionality as a transdiagnostic predictor of impaired emotion perception.

Robust associations between white matter microstructure and general intelligence

Few tract-based spatial statistics (TBSS) studies have investigated the relations between intelligence and white matter microstructure in healthy (young) adults, and those have yielded mixed observations, yet white matter is fundamental for efficient and accurate information transfer throughout the human brain. We used a multicenter approach to identify white matter regions that show replicable structure-function associations, employing data from 4 independent samples comprising over 2000 healthy participants. TBSS indicated 188 voxels exhibited significant positive associations between g factor scores and fractional anisotropy (FA) in all 4 data sets. Replicable voxels formed 3 clusters, located around the left-hemispheric forceps minor, superior longitudinal fasciculus, and cingulum-cingulate gyrus with extensions into their surrounding areas (anterior thalamic radiation, inferior fronto-occipital fasciculus). Our results suggested that individual differences in general intelligence are robustly associated with white matter FA in specific fiber bundles distributed across the brain, consistent with the Parieto-Frontal Integration Theory of intelligence. Three possible reasons higher FA values might create links with higher g are faster information processing due to greater myelination, more direct information processing due to parallel, homogenous fiber orientation distributions, or more parallel information processing due to greater axon density.

Evaluating the item-level factor structure of anhedonia

BACKGROUND

Anhedonia has long been theorized to be a multidimensional construct, focusing on domains of reward stimuli and temporal relationship to reward. However, little empirical work has directly examined whether there is support for this assertion.

METHODS

The study used data from young adults from four independent samples (n = 2098). Participants completed multiple measures of anhedonia.

RESULTS

We used rigorous conducted exploratory and confirmatory factor analyses on items from six commonly used anhedonia measures to examine dimensions underlying anhedonia. Results suggested a four-factor solution with factors reflecting social reward, social disinterest, status/achievement, and physical/natural reward. The identified factors reflected broad content domains of pleasure, but not specific reward processes. The four factors were modestly associated with one another, suggesting a weak common underlying anhedonia trait that manifests across multiple dimensions. Factor scores were associated with personality measures, reward-related indices, and depression symptoms, supporting the validity of the factors.

LIMITATIONS

Participants were all young adults and we assessed anhedonia only at the level of self-report.

CONCLUSION

Anhedonia is a multidimensional construct. However, the dimensions of anhedonia only distinguish domains of, but not temporal processes of anhedonia. Future work should continue to refine the structures underlying the construct of anhedonia through iterative theory- and data-driven research and examine associations between anhedonia and clinical outcomes.

White matter microstructure and network-connectivity in emerging adults with subclinical psychotic experiences

Group comparisons of individuals with psychotic disorder and controls have shown alterations in white matter microstructure. Whether white matter microstructure and network connectivity is altered in adolescents with subclinical psychotic experiences (PE) at the lowest end of the psychosis severity spectrum is less clear. DWI scan were acquired in 48 individuals with PE and 43 healthy controls (HC). Traditional tensor-derived indices: Fractional Anisotropy, Axial Diffusivity, Mean Diffusivity and Radial Diffusivity, as well as network connectivity measures (global/local efficiency and clustering coefficient) were compared between the groups. Subclinical psychopathology was assessed with the Community Assessment of Psychic Experiences (CAPE) and Montgomery-Åsberg Depression Rating Scale (MADRS) questionnaires and, in order to capture momentary subclinical expression of psychosis, the Experience Sampling Method (ESM) questionnaires. Within the PE-group, interactions between subclinical (momentary) symptoms and brain regions in the model of tensor-derived indices and network connectivity measures were investigated in a hypothesis-generating fashion. Whole brain analyses showed no group differences in tensor-derived indices and network connectivity measures. In the PE-group, a higher positive symptom distress score was associated with both higher local efficiency and clustering coefficient in the right middle temporal pole. The findings indicate absence of microstructural white matter differences between emerging adults with subclinical PE and controls. In the PE-group, attenuated symptoms were positively associated with network efficiency/cohesion, which requires replication and may indicate network alterations in emerging mild psychopathology.

From Description to Explanation: Integrating Across Multiple Levels of Analysis to Inform Neuroscientific Accounts of Dimensional Personality Pathology

Dimensional approaches to psychiatric nosology are rapidly transforming the way researchers and clinicians conceptualize personality pathology, leading to a growing interest in describing how individuals differ from one another. Yet, in order to successfully prevent and treat personality pathology, it is also necessary to explain the sources of these individual differences. The emerging field of personality neuroscience is well-positioned to guide the transition from description to explanation within personality pathology research. However, establishing comprehensive, mechanistic accounts of personality pathology will require personality neuroscientists to move beyond atheoretical studies that link trait differences to neural correlates without considering the algorithmic processes that are carried out by those correlates. We highlight some of the dangers we see in overpopulating personality neuroscience with brain-trait associational studies and offer a series of recommendations for personality neuroscientists seeking to build explanatory theories of personality pathology.

Apophenia as the disposition to false positives: A unifying framework for openness and psychoticism

Positive symptoms of schizophrenia and its extended phenotype-often termed psychoticism or positive schizotypy-are characterized by the inclusion of novel, erroneous mental contents. One promising framework for explaining positive symptoms involves apophenia, conceptualized here as a disposition toward false-positive errors. Apophenia and positive symptoms have shown relations to openness to experience (more specifically, to the openness aspect of the broader openness/intellect domain), and all of these constructs involve tendencies toward pattern seeking. Nonetheless, few studies have investigated the relations between psychoticism and non-self-report indicators of apophenia, let alone the role of normal personality variation. The current research used structural equation models to test associations between psychoticism, openness, intelligence, and non-self-report indicators of apophenia comprising false-positive error rates on a variety of computerized tasks. In Sample 1, 1,193 participants completed digit identification, theory of mind, and emotion recognition tasks. In Sample 2, 195 participants completed auditory signal detection and semantic word association tasks. Psychoticism and the openness aspect were positively correlated. Self-reported psychoticism, openness, and their shared variance were positively associated with apophenia, as indexed by false-positive error rates, whether or not intelligence was controlled for. Apophenia was not associated with other personality traits, and openness and psychoticism were not associated with false-negative errors. Findings provide insights into the measurement of apophenia and its relation to personality and psychopathology. Apophenia and pattern seeking may be promising constructs for unifying the openness aspect of personality with the psychosis spectrum and for providing an explanation of positive symptoms. Results are discussed in the context of possible adaptive characteristics of apophenia as well as potential risk factors for the development of psychotic disorders. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

A Hierarchical Integration of Normal and Abnormal Personality Dimensions: Structure and Predictive Validity in a Heterogeneous Sample of Psychiatric Outpatients

Hierarchical, quantitative models of psychopathology focus primarily on higher-order constructs, whereas less is known about the structure and content comprising lower-order dimensions of psychopathology. Here, we address this gap in the literature by using targeted factor analysis to integrate the 25 maladaptive facet-level traits of the Personality Inventory for Diagnostic and Statistical Manual of Mental Disorder-Fifth edition and the 10 aspect-level traits of the normal personality hierarchy within a sample of 198 psychiatric outpatients. A 10-factor solution replicated previous work, with each of the 10 aspects primarily characterizing only one factor. In addition, the 10 factors differentially predicted a range of diagnoses, including alcohol use disorder, major depression, panic disorder, social anxiety, and borderline and avoidant personality disorders. Our results suggest that research on the development, causes, and structure of lower-order traits within the normal personality hierarchy may serve as an important guide to research on the causes and structure of maladaptive personality.

Common Taxonomy of Traits and Symptoms: Linking Schizophrenia Symptoms, Schizotypy, and Normal Personality

The associations among normal personality and many mental disorders are well established, but it remains unclear whether and how symptoms of schizophrenia and schizotypal traits align with the personality taxonomy. This study examined the joint factor structure of normal personality, schizotypy, and schizophrenia symptoms in people with psychotic disorders (n = 288) and never-psychotic adults (n = 257) in the Suffolk County Mental Health Project. First, we evaluated the structure of schizotypal (positive schizotypy, negative schizotypy, and mistrust) and normal traits. In both the psychotic-disorder and never-psychotic groups, the best-fitting model had 5 factors: neuroticism, extraversion, conscientiousness, agreeableness, and psychoticism. The schizotypy traits were placed on different dimensions: negative schizotypy went on (low) extraversion, whereas positive schizotypy and mistrust went on psychoticism. Next, we added symptoms to the model. Numerous alternatives were compared, and the 5-factor model remained best-fitting. Reality distortion (hallucinations and delusions) and disorganization symptoms were placed on psychoticism, and negative symptoms were placed on extraversion. Models that separated symptom dimensions from trait dimensions did not fit well, arguing that taxonomies of symptoms and traits are aligned. This is the first study to show that symptoms of psychosis, schizotypy, and normal personality reflect the same underlying dimensions. Specifically, (low) extraversion, negative schizotypy, and negative symptoms form one spectrum, whereas psychoticism, positive schizotypy, and positive and disorganized symptoms form another. This framework helps to understand the heterogeneity of psychosis and comorbidity patterns found in psychotic disorders. It also underscores the importance of traits to understanding these disorders.

Structural correlates of the orbitofrontal cortex and amygdala and personality in female adolescents

The five-factor model consists of cognitive-affective-behavioral trait dimensions (neuroticism, extraversion, openness to experience, agreeableness, conscientiousness) that are central to models of psychopathology. In adults, individual differences in three of the Big Five traits, neuroticism, extraversion, and conscientiousness, have been linked to structural morphology and connectivity of the orbitofrontal cortex (OFC) and the amygdala, two brain regions critically involved in affective and regulatory processing. It is unclear whether these associations manifest in adolescence, a critical neurodevelopmental period during which many forms of psychiatric illness emerge. A total of 223 adolescent girls (ages 14-16 years) completed a multimodal neuroimaging study that utilized T1-weighted structural MRI (e.g., cortical thickness and volume) and tractography-based diffusion tensor imaging (64-direction). Cortical thickness and volume were extracted from the medial orbitofrontal cortex (mOFC) and amygdala and tractography-based fractional anisotropy was computed in the uncinate fasciculus (UF; the white matter tract connecting the OFC to the temporal lobe). We found that high neuroticism was associated with less mOFC volume (bilateral), and low conscientiousness was associated with higher white matter integrity in the UF, more amygdala volume, and less mOFC thickness (right hemisphere). Extraversion was not observed to share associations with OFC markers. These OFC-amygdala structural correlations to personality do not match those reported in adult samples. Multimodal neuroimaging techniques can help to clarify the underpinnings of personality development between adolescence and adulthood.

Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative

The latent structure of schizotypy and psychosis-spectrum symptoms remains poorly understood. Furthermore, molecular genetic substrates are poorly defined, largely due to the substantial resources required to collect rich phenotypic data across diverse populations. Sample sizes of phenotypic studies are often insufficient for advanced structural equation modeling approaches. In the last 50 years, efforts in both psychiatry and psychological science have moved toward (1) a dimensional model of psychopathology (eg, the current Hierarchical Taxonomy of Psychopathology [HiTOP] initiative), (2) an integration of methods and measures across traits and units of analysis (eg, the RDoC initiative), and (3) powerful, impactful study designs maximizing sample size to detect subtle genomic variation relating to complex traits (the Psychiatric Genomics Consortium [PGC]). These movements are important to the future study of the psychosis spectrum, and to resolving heterogeneity with respect to instrument and population. The International Consortium of Schizotypy Research is composed of over 40 laboratories in 12 countries, and to date, members have compiled a body of schizotypy- and psychosis-related phenotype data from more than 30000 individuals. It has become apparent that compiling data into a protected, relational database and crowdsourcing analytic and data science expertise will result in significant enhancement of current research on the structure and biological substrates of the psychosis spectrum. The authors present a data-sharing infrastructure similar to that of the PGC, and a resource-sharing infrastructure similar to that of HiTOP. This report details the rationale and benefits of the phenotypic data collective and presents an open invitation for participation.

Structural correlates of Openness and Intellect: Implications for the contribution of personality to creativity

Openness/Intellect (i.e., openness to experience) is the Big Five personality factor most consistently associated with individual differences in creativity. Recent psychometric evidence has demonstrated that this factor consists of two distinct aspects-Intellect and Openness. Whereas Intellect reflects perceived intelligence and intellectual engagement, Openness reflects engagement with fantasy, perception, and aesthetics. We investigated the extent to which Openness and Intellect are associated with variations in brain structure as measured by cortical thickness, area, and volume (N = 185). Our results demonstrated that Openness was correlated inversely with cortical thickness and volume in left middle frontal gyrus (BA 6), middle temporal gyrus (MTG, BA 21), and superior temporal gyrus (BA 41), and exclusively with cortical thickness in left inferior parietal lobule (BA 40), right inferior frontal gyrus (IFG, BA 45), and MTG (BA 37). When age and sex were statistically controlled for, the inverse correlations between Openness and cortical thickness remained statistically significant for all regions except left MTG, whereas the correlations involving cortical volume remained statistically significant only for left middle frontal gyrus. There was no statistically significant correlation between Openness and cortical area, and no statistically significant correlation between Intellect and cortical thickness, area, or volume. Our results demonstrate that individual differences in Openness are correlated with variation in brain structure-particularly as indexed by cortical thickness. Given the involvement of the above regions in processes related to memory and cognitive control, we discuss the implications of our findings for the possible contribution of personality to creative cognition.