Behavioral meaures of psychotic disorders: Using automatic facial coding to detect nonverbal expressions in video.

Emotional deficits in psychosis are prevalent and difficult to treat. In particular, much remains unknown about facial expression abnormalities, and a key reason is that expressions are very labor-intensive to code. Automatic facial coding (AFC) can remove this barrier. The current study sought to both provide evidence for the utility of AFC in psychosis for research purposes and to provide evidence that AFC are valid measures of clinical constructs. Changes of facial expressions and head position of participants-39 with schizophrenia/schizoaffective disorder (SZ), 46 with other psychotic disorders (OP), and 108 never psychotic individuals (NP)-were assessed via FaceReader, a commercially available automated facial expression analysis software, using video recorded during a clinical interview. We first examined the behavioral measures of the psychotic disorder groups and tested if they can discriminate between the groups. Next, we evaluated links of behavioral measures with clinical symptoms, controlling for group membership. We found the SZ group was characterized by significantly less variation in neutral expressions, happy expressions, arousal, and head movements compared to NP. These measures discriminated SZ from NP well (AUC = 0.79, sensitivity = 0.79, specificity = 0.67) but discriminated SZ from OP less well (AUC = 0.66, sensitivity = 0.77, specificity = 0.46). We also found significant correlations between clinician-rated symptoms and most behavioral measures (particularly happy expressions, arousal, and head movements). Taken together, these results suggest that AFC can provide useful behavioral measures of psychosis, which could improve research on non-verbal expressions in psychosis and, ultimately, enhance treatment.

Automating the analysis of facial emotion expression dynamics: A computational framework and application in psychotic disorders.

Facial emotion expressions play a central role in interpersonal interactions; these displays are used to predict and influence the behavior of others. Despite their importance, quantifying and analyzing the dynamics of brief facial emotion expressions remains an understudied methodological challenge. Here, we present a method that leverages machine learning and network modeling to assess the dynamics of facial expressions. Using video recordings of clinical interviews, we demonstrate the utility of this approach in a sample of 96 people diagnosed with psychotic disorders and 116 never-psychotic adults. Participants diagnosed with schizophrenia tended to move from neutral expressions to uncommon expressions (e.g., fear, surprise), whereas participants diagnosed with other psychoses (e.g., mood disorders with psychosis) moved toward expressions of sadness. This method has broad applications to the study of normal and altered expressions of emotion and can be integrated with telemedicine to improve psychiatric assessment and treatment.

Psychosis superspectrum II: neurobiology, treatment, and implications.

Alternatives to traditional categorical diagnoses have been proposed to improve the validity and utility of psychiatric nosology. This paper continues the companion review of an alternative model, the psychosis superspectrum of the Hierarchical Taxonomy of Psychopathology (HiTOP). The superspectrum model aims to describe psychosis-related psychopathology according to data on distributions and associations among signs and symptoms. The superspectrum includes psychoticism and detachment spectra as well as narrow subdimensions within them. Auxiliary domains of cognitive deficit and functional impairment complete the psychopathology profile. The current paper reviews evidence on this model from neurobiology, treatment response, clinical utility, and measure development. Neurobiology research suggests that psychopathology included in the superspectrum shows similar patterns of neural alterations. Treatment response often mirrors the hierarchy of the superspectrum with some treatments being efficacious for psychoticism, others for detachment, and others for a specific subdimension. Compared to traditional diagnostic systems, the quantitative nosology shows an approximately 2-fold increase in reliability, explanatory power, and prognostic accuracy. Clinicians consistently report that the quantitative nosology has more utility than traditional diagnoses, but studies of patients with frank psychosis are currently lacking. Validated measures are available to implement the superspectrum model in practice. The dimensional conceptualization of psychosis-related psychopathology has implications for research, clinical practice, and public health programs. For example, it encourages use of the cohort study design (rather than case-control), transdiagnostic treatment strategies, and selective prevention based on subclinical symptoms. These approaches are already used in the field, and the superspectrum provides further impetus and guidance for their implementation. Existing knowledge on this model is substantial, but significant gaps remain. We identify outstanding questions and propose testable hypotheses to guide further research. Overall, we predict that the more informative, reliable, and valid characterization of psychopathology offered by the superspectrum model will facilitate progress in research and clinical care.

Psychosis superspectrum I: Nosology, etiology, and lifespan development.

This review describes the Hierarchical Taxonomy of Psychopathology (HiTOP) model of psychosis-related psychopathology, the psychosis superspectrum. The HiTOP psychosis superspectrum was developed to address shortcomings of traditional diagnoses for psychotic disorders and related conditions including low reliability, arbitrary boundaries between psychopathology and normality, high symptom co-occurrence, and heterogeneity within diagnostic categories. The psychosis superspectrum is a transdiagnostic dimensional model comprising two spectra-psychoticism and detachment-which are in turn broken down into fourteen narrow components, and two auxiliary domains-cognition and functional impairment. The structure of the spectra and their components are shown to parallel the genetic structure of psychosis and related traits. Psychoticism and detachment have distinct patterns of association with urbanicity, migrant and ethnic minority status, childhood adversity, and cannabis use. The superspectrum also provides a useful model for describing the emergence and course of psychosis, as components of the superspectrum are relatively stable over time. Changes in psychoticism predict the onset of psychosis-related psychopathology, whereas changes in detachment and cognition define later course. Implications of the superspectrum for genetic, socio-environmental, and longitudinal research are discussed. A companion review focuses on neurobiology, treatment response, and clinical utility of the superspectrum, and future research directions.

Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies.

Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.

General v. specific vulnerabilities: polygenic risk scores and higher-order psychopathology dimensions in the Adolescent Brain Cognitive Development (ABCD) Study.

BACKGROUND: Polygenic risk scores (PRSs) capture genetic vulnerability to psychiatric conditions. However, PRSs are often associated with multiple mental health problems in children, complicating their use in research and clinical practice. The current study is the first to systematically test which PRSs associate broadly with all forms of childhood psychopathology, and which PRSs are more specific to one or a handful of forms of psychopathology. METHODS: The sample consisted of 4717 unrelated children (mean age = 9.92, s.d. = 0.62; 47.1% female; all European ancestry). Psychopathology was conceptualized hierarchically as empirically derived general factor (p-factor) and five specific factors: externalizing, internalizing, neurodevelopmental, somatoform, and detachment. Partial correlations explored associations between psychopathology factors and 22 psychopathology-related PRSs. Regressions tested which level of the psychopathology hierarchy was most strongly associated with each PRS. RESULTS: Thirteen PRSs were significantly associated with the general factor, most prominently Chronic Multisite Pain-PRS (r = 0.098), ADHD-PRS (r = 0.079), and Depression-PRS (r = 0.078). After adjusting for the general factor, Depression-PRS, Neuroticism-PRS, PTSD-PRS, Insomnia-PRS, Chronic Back Pain-PRS, and Autism-PRS were not associated with lower order factors. Conversely, several externalizing PRSs, including Adventurousness-PRS and Disinhibition-PRS, remained associated with the externalizing factor (|r| = 0.040-0.058). The ADHD-PRS remained uniquely associated with the neurodevelopmental factor (r = 062). CONCLUSIONS: PRSs developed to predict vulnerability to emotional difficulties and chronic pain generally captured genetic risk for all forms of childhood psychopathology. PRSs developed to predict vulnerability to externalizing difficulties, e.g. disinhibition, tended to be more specific in predicting behavioral problems. The results may inform translation of existing PRSs to pediatric research and future clinical practice.

Pleasant and unpleasant odor identification ability is associated with distinct dimensions of negative symptoms transdiagnostically in psychotic disorders.

Negative symptoms are among the greatest sources of functional impairment for individuals with schizophrenia, yet their mechanisms remain poorly understood. Olfactory impairment is associated with negative symptoms. The processing of pleasant olfactory stimuli is subserved by reward-related neural circuitry while unpleasant olfactory processing is subserved by emotion-related neural circuitry, suggesting that these two odor dimensions may offer a window into differential mechanisms of negative symptoms. We examined whether pleasant and unpleasant odor identification bears differential relationships with avolition and inexpressivity dimensions of negative symptoms, whether these relationships are transdiagnostic, and whether pleasant and unpleasant odor processing also relate differently to other domains of functioning in a sample of individuals diagnosed with schizophrenia (N = 54), other psychotic disorders (N = 65), and never-psychotic adults (N = 160). Hierarchical regressions showed that pleasant odor identification was uniquely associated with avolition, while unpleasant odor identification was uniquely associated with inexpressivity. These relationships were largely transdiagnostic across groups. Additionally, pleasant and unpleasant odor identification displayed signs of specificity with other functional and cognitive measures. These results align with past work suggesting dissociable pathomechanisms of negative symptoms and provide a potential avenue for future work using valence-specific olfactory dysfunction as a semi-objective and low-cost marker for understanding and predicting the severity of specific negative symptom profiles.

The Hierarchical Taxonomy of Psychopathology (HiTOP) in psychiatric practice and research.

The Hierarchical Taxonomy of Psychopathology (HiTOP) has emerged out of the quantitative approach to psychiatric nosology. This approach identifies psychopathology constructs based on patterns of co-variation among signs and symptoms. The initial HiTOP model, which was published in 2017, is based on a large literature that spans decades of research. HiTOP is a living model that undergoes revision as new data become available. Here we discuss advantages and practical considerations of using this system in psychiatric practice and research. We especially highlight limitations of HiTOP and ongoing efforts to address them. We describe differences and similarities between HiTOP and existing diagnostic systems. Next, we review the types of evidence that informed development of HiTOP, including populations in which it has been studied and data on its validity. The paper also describes how HiTOP can facilitate research on genetic and environmental causes of psychopathology as well as the search for neurobiologic mechanisms and novel treatments. Furthermore, we consider implications for public health programs and prevention of mental disorders. We also review data on clinical utility and illustrate clinical application of HiTOP. Importantly, the model is based on measures and practices that are already used widely in clinical settings. HiTOP offers a way to organize and formalize these techniques. This model already can contribute to progress in psychiatry and complement traditional nosologies. Moreover, HiTOP seeks to facilitate research on linkages between phenotypes and biological processes, which may enable construction of a system that encompasses both biomarkers and precise clinical description.

Dynamic interplay between life events and course of psychotic disorders: 10-year longitudinal study following first admission.

BACKGROUND: Life events (LEs) are a risk factor for first onset and relapse of psychotic disorders. However, the impact of LEs on specific symptoms - namely reality distortion, disorganization, negative symptoms, depression, and mania - remains unclear. Moreover, the differential effects of negative v. positive LEs are poorly understood. METHODS: The present study utilizes an epidemiologic cohort of patients (N = 428) ascertained at first-admission for psychosis and followed for a decade thereafter. Symptoms were assessed at 6-, 24-, 48-, and 120-month follow-ups. RESULTS: We examined symptom change within-person and found that negative events in the previous 6 months predicted an increase in reality distortion (ß = 0.07), disorganized (ß = 0.07), manic (ß = 0.08), and depressive symptoms (ß = 0.06), and a decrease in negative symptoms (ß = -0.08). Conversely, positive LEs predicted fewer reality distortion (ß = -0.04), disorganized (ß = -0.04), and negative (ß = -0.13) symptoms, and were unrelated to mood symptoms. A between-person approach to the same hypotheses confirmed that negative LEs predicted change in all symptoms, while positive LEs predicted change only in negative symptoms. In contrast, symptoms rarely predicted future LEs. CONCLUSIONS: These findings confirm that LEs have an effect on symptoms, and thus contribute to the burden of psychotic disorders. That LEs increase positive symptoms and decrease negative symptoms suggest at least two different mechanisms underlying the relationship between LEs and symptoms. Our findings underscore the need for increased symptom monitoring following negative LEs, as symptoms may worsen during that time.

Development of the Thought Disorder Measure for the Hierarchical Taxonomy of Psychopathology.

The Hierarchical Taxonomy of Psychopathology consortium aims to develop a comprehensive self-report measure to assess psychopathology dimensionally. The current research describes the initial conceptualization, development, and item selection for the thought disorder spectrum and related constructs from other spectra. The thought disorder spectrum is defined primarily by the positive and disorganized traits and symptoms of schizophrenia-spectrum disorders. The Thought Disorder Sub-Workgroup identified and defined 16 relevant constructs and wrote 10 to 15 items per each construct. These items were administered, along with detachment and mania items, to undergraduates and people with serious mental illness. Three hundred and sixty-five items across 25 scales were administered. An exploratory factor analysis of the scale scores suggested a two-factor structure corresponding to positive and negative symptoms for two samples. The mania scales loaded with the positive factor, while the detachment scales loaded with the negative factor. Item-level analyses resulted in 19 preliminary scales, including 215 items that cover the range of thought disorder pathology, and will be carried forward for the next phase of data collection/analysis.

Global Information for Multidimensional Tests.

New measures of test information, termed global information, quantify test information relative to the entire range of the trait being assessed. Estimating global information relative to a non-informative prior distribution results in a measure of how much information could be gained by administering the test to an unspecified examinee. Currently, such measures have been developed only for unidimensional tests. This study introduces measures of multidimensional global test information and validates them in simulated data. Then, the utility of global test information is tested in neuropsychological data collected as part of Rush University's Memory and Aging Project. These measures allow for direct comparison of complex tests calibrated in different samples, facilitating test development and selection.

A comparison of cognitive performance in the Suffolk County cohort and their unaffected siblings.

People diagnosed with schizophrenia and other psychoses demonstrate impaired neuropsychological performance. Their unaffected siblings exhibit mild impairments relative to unrelated controls, suggesting genetic and shared environmental risk for psychosis account for some portion of cognitive impairments observed in cases. However, most sibling studies were conducted early in illness course. Studying cases and unaffected siblings later in life is valuable because diagnostic misclassification is common early in illness, possibly leading to spurious conclusions. This study compared neuropsychological performance of individuals with psychotic disorders (schizophrenia and other psychoses), their unaffected siblings, and controls. Assessments were conducted 20 years after case enrollment in the Suffolk County Mental Health Project, when siblings and controls were added to the protocol. Results showed individuals with schizophrenia and other psychoses performed worse than their matched siblings across domains. Relative to controls, siblings of participants with schizophrenia showed mild deficits in executive function and processing speed, while no significant differences were observed between siblings of those with other psychoses and controls. These findings suggest pre- and post-onset factors impact cognitive deficits in psychosis, but pre-onset factors are more salient in schizophrenia. Additionally, schizophrenia and other psychoses exist on a neurodevelopmental continuum, with schizophrenia being a more severe manifestation.

Les progrès dans la réalisation de la classification quantitative de la psychopathologie.

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.

Predicting Long-Term Outcomes in First-Admission Psychosis: Does the Hierarchical Taxonomy of Psychopathology Aid DSM in Prognostication?

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical, dimensional model of psychological symptoms and functioning. Its goals are to augment the use and address the limitations of traditional diagnoses, such as arbitrary thresholds of severity, within-disorder heterogeneity, and low reliability. HiTOP has made inroads to addressing these problems, but its prognostic validity is uncertain. The present study sought to test the prediction of long-term outcomes in psychotic disorders was improved when the HiTOP dimensional approach was considered along with traditional (ie, DSM) diagnoses. We analyzed data from the Suffolk County Mental Health Project (N = 316), an epidemiologic study of a first-admission psychosis cohort followed for 20 years. We compared 5 diagnostic groups (schizophrenia/schizoaffective, bipolar disorder with psychosis, major depressive disorder with psychosis, substance-induced psychosis, and other psychoses) and 5 dimensions derived from the HiTOP thought disorder spectrum (reality distortion, disorganization, inexpressivity, avolition, and functional impairment). Both nosologies predicted a significant amount of variance in most outcomes. However, except for cognitive functioning, HiTOP showed consistently greater predictive power across outcomes-it explained 1.7-fold more variance than diagnoses in psychiatric and physical health outcomes, 2.1-fold more variance in community functioning, and 3.4-fold more variance in neural responses. Even when controlling for diagnosis, HiTOP dimensions incrementally predicted almost all outcomes. These findings support a shift away from the exclusive use of categorical diagnoses and toward the incorporation of HiTOP dimensions for better prognostication and linkage with neurobiology.

Validity and utility of Hierarchical Taxonomy of Psychopathology (HiTOP): I. Psychosis superspectrum.

The Hierarchical Taxonomy of Psychopathology (HiTOP) is a scientific effort to address shortcomings of traditional mental disorder diagnoses, which suffer from arbitrary boundaries between psychopathology and normality, frequent disorder co-occurrence, heterogeneity within disorders, and diagnostic instability. This paper synthesizes evidence on the validity and utility of the thought disorder and detachment spectra of HiTOP. These spectra are composed of symptoms and maladaptive traits currently subsumed within schizophrenia, other psychotic disorders, and schizotypal, paranoid and schizoid personality disorders. Thought disorder ranges from normal reality testing, to maladaptive trait psychoticism, to hallucinations and delusions. Detachment ranges from introversion, to maladaptive detachment, to blunted affect and avolition. Extensive evidence supports the validity of thought disorder and detachment spectra, as each spectrum reflects common genetics, environmental risk factors, childhood antecedents, cognitive abnormalities, neural alterations, biomarkers, and treatment response. Some of these characteristics are specific to one spectrum and others are shared, suggesting the existence of an overarching psychosis superspectrum. Further research is needed to extend this model, such as clarifying whether mania and dissociation belong to thought disorder, and explicating processes that drive development of the spectra and their subdimensions. Compared to traditional diagnoses, the thought disorder and detachment spectra demonstrated substantially improved utility: greater reliability, larger explanatory and predictive power, and higher acceptability to clinicians. Validated measures are available to implement the system in practice. The more informative, reliable and valid characterization of psychosis-related psychopathology offered by HiTOP can make diagnosis more useful for research and clinical care.