Measuring pathology using the PANSS across diagnoses: Inconsistency of the positive symptom domain across schizophrenia, schizoaffective, and bipolar disorder

Associations between fearlessness about death and suicidal ideation in individuals with psychosis

BACKGROUND

Despite high rates of suicide among people with psychosis, relatively little is known about the mechanisms underlying the transition from suicidal ideation to behavior in this population. The Interpersonal Psychological Theory of Suicide (IPTS) proposes that fearlessness about death (FAD) may play a role in this relationship. The present study tested whether constructs of the IPTS [thwarted belongingness (TB), perceived burdensomeness (PB), and FAD] were associated with the severity of suicidal ideation in a sample of adults with histories of psychosis.

METHOD

261 adults with histories of psychosis completed measures of IPTS constructs, current severity of suicidal ideation, and history of suicidal attempts. We examined differences between those with past suicide attempts and those without and conducted regression analyses to evaluate the associations among TB, PB, FAD and severity of current suicidal ideation.

RESULTS

Contrary to expectations, a history of suicidal behavior was not uniquely associated with FAD. Regression analyses revealed TB × PB and FAD × PB interactions emerged as significant correlates of the severity of suicidal ideation, with the relationship between PB and suicidal ideation more pronounced at higher levels of FAD and TB. Interestingly, positive symptoms of psychosis were positively associated with PB.

IMPLICATIONS

This study provides support for broadening the investigation of FAD as a contributor to suicidal ideation in individuals with psychotic symptoms. Future research investigating the role of other contributors that may influence capability for suicide (e.g., impulsivity) may add additional understanding of suicide in this population.

Enlarged pituitary gland volume: a possible state rather than trait marker of psychotic disorders

BACKGROUND

Enlarged pituitary gland volume could be a marker of psychotic disorders. However, previous studies report conflicting results. To better understand the role of the pituitary gland in psychosis, we examined a large transdiagnostic sample of individuals with psychotic disorders.

METHODS

The study included 751 participants (174 with schizophrenia, 114 with schizoaffective disorder, 167 with psychotic bipolar disorder, and 296 healthy controls) across six sites in the Bipolar-Schizophrenia Network on Intermediate Phenotypes consortium. Structural magnetic resonance images were obtained, and pituitary gland volumes were measured using the MAGeT brain algorithm. Linear mixed models examined between-group differences with controls and among patient subgroups based on diagnosis, as well as how pituitary volumes were associated with symptom severity, cognitive function, antipsychotic dose, and illness duration.

RESULTS

Mean pituitary gland volume did not significantly differ between patients and controls. No significant effect of diagnosis was observed. Larger pituitary gland volume was associated with greater symptom severity (F = 13.61, p = 0.0002), lower cognitive function (F = 4.76, p = 0.03), and higher antipsychotic dose (F = 5.20, p = 0.02). Illness duration was not significantly associated with pituitary gland volume. When all variables were considered, only symptom severity significantly predicted pituitary gland volume (F = 7.54, p = 0.006).

CONCLUSIONS

Although pituitary volumes were not increased in psychotic disorders, larger size may be a marker associated with more severe symptoms in the progression of psychosis. This finding helps clarify previous inconsistent reports and highlights the need for further research into pituitary gland-related factors in individuals with psychosis.

Fibre density and fibre-bundle cross-section of the corticospinal tract are distinctly linked to psychosis-specific symptoms in antipsychotic-naïve patients with first-episode schizophrenia

Multiple lines of research support the dysconnectivity hypothesis of schizophrenia. However, findings on white matter (WM) alterations in patients with schizophrenia are widespread and non-specific. Confounding factors from magnetic resonance image (MRI) processing, clinical diversity, antipsychotic exposure, and substance use may underlie some of the variability. By application of refined methodology and careful sampling, we rectified common confounders investigating WM and symptom correlates in a sample of strictly antipsychotic-naïve first-episode patients with schizophrenia. Eighty-six patients and 112 matched controls underwent diffusion MRI. Using fixel-based analysis (FBA), we extracted fibre-specific measures such as fibre density and fibre-bundle cross-section. Group differences on fixel-wise measures were examined with multivariate general linear modelling. Psychopathology was assessed with the Positive and Negative Syndrome Scale. We separately tested multivariate correlations between fixel-wise measures and predefined psychosis-specific versus anxio-depressive symptoms. Results were corrected for multiple comparisons. Patients displayed reduced fibre density in the body of corpus callosum and in the middle cerebellar peduncle. Fibre density and fibre-bundle cross-section of the corticospinal tract were positively correlated with suspiciousness/persecution, and negatively correlated with delusions. Fibre-bundle cross-section of isthmus of corpus callosum and hallucinatory behaviour were negatively correlated. Fibre density and fibre-bundle cross-section of genu and splenium of corpus callosum were negative correlated with anxio-depressive symptoms. FBA revealed fibre-specific properties of WM abnormalities in patients and differentiated associations between WM and psychosis-specific versus anxio-depressive symptoms. Our findings encourage an itemised approach to investigate the relationship between WM microstructure and clinical symptoms in patients with schizophrenia.

Circulating endothelial progenitor cell dysfunction in patients with bipolar disorder

Dysfunction in circulating endothelial progenitor cells (cEPCs) plays a crucial role in cardiovascular disorders (CVDs). Patients with bipolar disorder (BPD) are at increased risk of developing CVDs. This study examined the associations of the functional properties of cEPCs with BPD and its clinical and cognitive characteristics. We recruited 69 patients with BPD and 41 healthy controls (HCs). The levels of manic, depressive, anxiety, psychosomatic symptoms, subjective cognitive dysfunction, quality of life, and functional disability of the BPD group were evaluated using the Young Mania Rating Scale (YMRS), Clinical Global Impression for BPD (CGI-BP), Hamilton Depression Rating Scale, Montgomery-Åsberg Depression Rating Scale, Hamilton Anxiety Rating Scale, Depression and Somatic Symptoms Scale, Perceived Deficits Questionnaire-Depression, 12-Item Short-Form Health Survey, and Sheehan Disability Scale, respectively. Cognitive function was assessed using 2-back and Go/No-Go tasks. Through in vitro assays, the adhesion to fibronectin and the percentage of apoptosis of cEPCs were examined. Under correction for multiple comparisons, the adhesive function of cEPCs in BPD was significantly lower than that in the HCs (corrected P [Pcorr] = 0.027). The reduced adhesive function of cEPCs correlated significantly with increased scores in the YMRS (Pcorr = 0.0002) and the CGI-BP (Pcorr = 0.0009). A lower percentage of apoptotic cEPC cells was associated with greater commission errors in the 2-back (Pcorr = 0.028) and Go/No-Go tasks (Pcorr = 0.029). The cEPCs of the BPD group exhibited attenuated adhesive function. The altered adhesive and apoptotic functions of cEPCs are associated with manic symptom severity and response inhibition deficits in patients with BPD.

A transdiagnostic approach to negative symptoms: exploring factor structure and negative symptoms in bipolar disorders

Background

Negative symptoms are increasingly recognized as transdiagnostic phenomena, linked to reduced quality of life and functioning, and often caused or worsened by amendable external factors such as depression, social deprivation, side-effects of antipsychotics or substance use. The structure of negative symptoms fits into two dimensions: diminished expression and apathy. These may differ in association with external factors that influence their severity and may thus require different treatment approaches. The dimensions are comprehensively established in non-affective psychotic disorders but are understudied in bipolar disorders.

Methods

We conducted exploratory and confirmatory factor analyses in a sample of 584 individuals with bipolar disorder to assess the latent factor structure of negative symptoms as measured by the Positive and Negative Syndrome Scale (PANSS), and performed correlational analyses and multiple hierarchical regression analyses to investigate links between the two dimensions of negative symptoms and clinical and sociodemographic correlates.

Results

The latent factor structure of negative symptoms fits into two dimensions, i.e., diminished expression and apathy. A diagnosis of bipolar type I or a history of psychotic episodes predicted more severe levels of diminished expression. Depressive symptoms were associated with more severe negative symptoms across dimensions, yet 26.3% of euthymic individuals still displayed at least one mild or more severe negative symptom (PANSS score ≥ 3).

Discussion

The two-dimensional structure of negative symptoms seen in non-affective psychotic disorders reproduces in bipolar disorders indicating similarities in their phenomenology. Diminished expression was associated with a history of psychotic episodes and a diagnosis of BD-I, which may infer closer connections to psychosis liability. We found significantly less severe negative symptoms in euthymic than depressed participants. Nevertheless, more than a quarter of the euthymic individuals had at least one mild negative symptom, demonstrating some degree of persistence beyond depressed states.

Levels of circulating endothelial progenitor cells inversely correlate with manic and positive symptom severity in patients with bipolar disorder

OBJECTIVES

Patients with bipolar disorder (BPD) are at high risk of cardiovascular diseases (CVDs) that are attributed to endothelial dysfunction. Circulating endothelial progenitor cells (cEPCs) are proposed as indicators of endothelial dysfunction. This study examined the relationship of cEPC numbers with BPD diagnosis and its clinical symptoms in patients with BPD.

METHODS

We recruited 48 patients with BPD and 50 healthy controls (HCs). All the patients had scores of <13 on the Young Mania Rating Scale (YMRS). In addition to the YMRS and Clinical Global Impression for BPD (CGI-BP), bipolar patients were assessed using relevant measurements for their depression, anxiety, general psychopathology, cognitive dysfunction and deficit, somatic symptoms, quality of life, and level of disability. cEPC counts were measured using flow cytometry.

RESULTS

The numbers of immature and mature cEPCs in the bipolar patients did not significantly differ from those in the HCs. After correction for multiple comparisons and controlling for body mass index and smokers, the number of immature cEPCs was observed to be inversely correlated with CGI-BP (corrected p [p_corr ] = .00018) and positive scores in the positive and negative syndrome scale (PANSS-P; p_corr  = .0049). The number of mature cEPCs was inversely correlated with YMRS (p_corr  = .014), CGI-BP (p_corr  = .00022), and PANSS-P (p_corr  = .0049) scores. In multivariate stepwise analysis, numbers of both types of cEPCs were associated with CGI-BP.

CONCLUSIONS

cEPC levels, an indicator of endothelial dysfunction and risk of CVDs, may be associated manic and positive symptom severities in patients with BPD.

NKCC1 to KCC2 mRNA Ratio in Schizophrenia and Its Psychopathology: a Case-Control Study

Schizophrenia (SCZ) is a debilitating, destructive, and chronic mental disorder and affects approximately one percent of the human population. Diagnosis in psychiatry is based on the patient's descriptions of his/her symptoms, interviewer's observations, history of disorder over time, and response to treatment. All of these data measure phenotype-based functions. But it appears that accurate diagnosis of such a complex disorder must be based on valid and reliable factors. In the present study, gene selection was based on the possible role of γ-aminobutyric acid (GABA) in psychopathology of SCZ and expression in blood. We evaluated the association of Na⁺-K⁺-Cl^- co-transporter 1 (NKCC1) and K⁺-Cl^- co-transporter 2 (KCC2) genes' messenger ribonucleic acid (mRNA) levels, and also the NKCC1/KCC2 ratio with positive and negative syndrome scale (PANSS) and brief psychiatric rating scale (BPRS) scores in an SCZ group. By using real-time PCR (RT-PCR), the present study is the first attempt to explore levels of NKCC1 and KCC2 expression at mRNA level and their relative expression in human peripheral blood of patients with SCZ. Our results showed that the NKCC1 to KCC2 mRNA ratio is significantly increased (but based on the delta cycle of threshold [∆Ct] is significantly lower) in the total sample of cases rather than controls (p = 0.045) and also higher in male sample cases rather than male controls (p = 0.016). In female samples, we found a trend toward a significant effect between the case and control participants (p = 0.075). We also found statistically significant association between mRNA of NKCC1 and KCC2 genes and NKCC1/KCC2 mRNA ratio with the positive and negative syndrome scale (PANSS) and brief psychiatric rating scale (BPRS) scores.

The network and dimensionality structure of affective psychoses: an exploratory graph analysis approach

BACKGROUND

The dimensional symptom structure of classes of affective psychoses, and more specifically the relationships between affective and mood symptoms, has been poorly researched. Here, we examined these questions from a network analysis perspective.

METHODS

Using Exploratory Graph Analysis (EGA) and network centrality parameters, we examined the dimensionality and network structure of 28 mood and psychotic symptoms in subjects diagnosed with schizoaffective disorder (n=124), psychotic bipolar disorder (n=345) or psychotic depression (n=245), such as in the global sample of affective psychoses.

RESULTS

EGA identified four dimensions in subjects with schizoaffective or bipolar disorders (depression, mania, positive and negative) and three dimensions in subjects with psychotic depression (depression, psychosis and activation). The item composition of dimensions and the most central symptoms varied substantially across diagnoses. The most central (i.e., interconnected) symptoms in schizoaffective disorder, psychotic bipolar disorder and psychotic depression were hallucinations, delusions and depressive mood, respectively. Classes of affective psychoses significantly differed in terms of network structure but not in network global strength.

LIMITATIONS

The cross-sectional nature of this study precludes conclusions about the causal dynamics between affective and psychotic symptoms.

CONCLUSION

EGA is a powerful tool for examining the dimensionality and network structure of symptoms in affective psychoses showing that both the interconnectivity pattern between affective and psychotic symptoms and the most central symptoms vary across classes of affective psychoses. The findings outline the value of specific diagnoses in explaining the relationships between mood and affective symptoms.

Generalizability of machine learning for classification of schizophrenia based on resting-state functional MRI data

Machine learning has increasingly been applied to classification of schizophrenia in neuroimaging research. However, direct replication studies and studies seeking to investigate generalizability are scarce. To address these issues, we assessed within-site and between-site generalizability of a machine learning classification framework which achieved excellent performance in a previous study using two independent resting-state functional magnetic resonance imaging data sets collected from different sites and scanners. We established within-site generalizability of the classification framework in the main data set using cross-validation. Then, we trained a model in the main data set and investigated between-site generalization in the validated data set using external validation. Finally, recognizing the poor between-site generalization performance, we updated the unsupervised algorithm to investigate if transfer learning using additional unlabeled data were able to improve between-site classification performance. Cross-validation showed that the published classification procedure achieved an accuracy of 0.73 using majority voting across all selected components. External validation found a classification accuracy of 0.55 (not significant) and 0.70 (significant) using the direct and transfer learning procedures, respectively. The failure of direct generalization from one site to another demonstrates the limitation of within-site cross-validation and points toward the need to incorporate efforts to facilitate application of machine learning across multiple data sets. The improvement in performance with transfer learning highlights the importance of taking into account the properties of data when constructing predictive models across samples and sites. Our findings suggest that machine learning classification result based on a single study should be interpreted cautiously.

Meta-analysis of the positive and Negative Syndrome Scale (PANSS) factor structure

A meta-analysis of the results of 45 factor analyses (n = 22,812) of the Positive and Negative Syndrome Scale (PANSS) was conducted. Meta-analyses of the PANSS was conducted using both a co-occurrence similarity matrix and reproduced correlations. Both methods produced similar results. Five factors (Positive Symptoms, Negative Symptoms, Disorganization, Affect and Resistance) emerged clearly across both analyses. The factors and the items defining them were Positive Symptoms (P1 Delusions, G9 Unusual thought content, P3 Hallucinatory behavior, P6 Suspiciousness and persecution, P5 Grandiosity), Negative Symptoms (N2 Emotional withdrawal, N1 Blunted affect, N4 Passive apathetic social withdrawal, N6 Lack of spontaneity, N3 Poor rapport, G7 Motor retardation, G16 Active social avoidance), Disorganization often termed Cognitive (P2 Conceptual disorganization, G11 Poor attention, N5 Difficulty in abstract thinking, G13 Disturbance of volition, N7 Stereotyped thinking, G5 Mannerisms/posturing, G15 Preoccupation, G10 Disorientation), Affect often termed Depression-Anxiety (G2 Anxiety, G6 Depression, G3 Guilt feelings, G4 Tension, G1 Somatic concern) and a small fifth factor that might be characterized as Resistance or Excitement/Activity (P7 Hostility, G14 Poor impulse control, P4 Excitement, G8 Uncooperativeness). Items G1, G4, G10, P5, G5, G15 may not be core items for the PANSS factors and G12 lack of judgment is not a core item. Results of the PANSS meta-analyses were relatively similar to those for meta-analysis of both the BPRS and BPRS-E all of which contain the original 18 BPRS items. The PANSS is distinguished by a much larger number of items to clearly define and measure Negative Symptoms as well as a sufficient number of items to much more clearly identify a Disorganization factor than the BPRS or BPRS-E.

Handwriting movements for assessment of motor symptoms in schizophrenia spectrum disorders and bipolar disorder

The main aim of the present study was to explore the value of several measures of handwriting in the study of motor abnormalities in patients with bipolar or psychotic disorders. 54 adult participants with a schizophrenia spectrum disorder or bipolar disorder and 44 matched healthy controls, participated in the study. Participants were asked to copy a handwriting pattern consisting of four loops, with an inking pen on a digitizing tablet. We collected a number of classical, non-linear and geometrical measures of handwriting. The handwriting of patients was characterized by a significant decrease in velocity and acceleration and an increase in the length, disfluency and pressure with respect to controls. Concerning non-linear measures, we found significant differences between patients and controls in the Sample Entropy of velocity and pressure, Lempel-Ziv of velocity and pressure, and Higuchi Fractal Dimension of pressure. Finally, Lacunarity, a measure of geometrical heterogeneity, was significantly greater in handwriting patterns from patients than from controls. We did not find differences in any handwriting measure on function of the specific diagnosis or the antipsychotic dose. Results indicate that participants with a schizophrenia spectrum disorder or bipolar disorder exhibit significant motor impairments and that these impairments can be readily quantified using measures of handwriting movements. Besides, they suggest that motor abnormalities are a core feature of several mental disorders and they seem to be unrelated to the pharmacological treatment.

Enhanced Molecular Appreciation of Psychiatric Disorders Through High-Dimensionality Data Acquisition and Analytics

The initial diagnosis, molecular investigation, treatment, and posttreatment care of major psychiatric disorders (schizophrenia and bipolar depression) are all still significantly hindered by the current inability to define these disorders in an explicit molecular signaling manner. High-dimensionality data analytics, using large datastreams from transcriptomic, proteomic, or metabolomic investigations, will likely advance both the appreciation of the molecular nature of major psychiatric disorders and simultaneously enhance our ability to more efficiently diagnose and treat these debilitating conditions. High-dimensionality data analysis in psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results. All of these issues combine to constrain the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges through the implementation of transcriptomic, proteomic, or metabolomics signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of intelligent high-dimensionality data-based differential diagnosis in mental disease diagnosis and treatment, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

The component structure of the scales for the assessment of positive and negative symptoms in first-episode psychosis and its dependence on variations in analytic methods

A secondary analysis was undertaken on Scales for the Assessment of Positive and Negative Symptoms (SAPS/SANS) data from 345 first-episode psychosis (FEP) patients gathered in the West London FEP study. The purpose of this study was to determine: (i) the component structure of these measures in FEP (primary analyses), and (ii) the dependence of any findings in these primary analyses on variations in analytic methods. Symptom ratings were exposed to data reduction methods and the effects of the following manipulations ascertained: (i) level of analysis (individual symptom vs. global symptom severity ratings), (ii) extraction method (principal component vs. exploratory factor analysis) and (iii) retention method (scree test vs. Kaiser criterion). Whilst global ratings level analysis rendered the classic triad of psychotic syndromes (positive, negative and disorganisation), symptom level analyses revealed a hierarchical structure, with 11 first-order components subsumed by three second-order components, which also mapped on to this syndrome triad. These results were robust across data reduction but not component retention methods, suggesting that discrepancies in the literature regarding the component structure of the SAPS/SANS partly reflect the level of analysis and component retention method used. Further, they support a hierarchical symptom model, the implications of which are discussed.

Bifactor Modeling of the Positive and Negative Syndrome Scale: Generalized Psychosis Spans Schizoaffective, Bipolar, and Schizophrenia Diagnoses

OBJECTIVE

Common genetic variation spans schizophrenia, schizoaffective and bipolar disorders, but historically, these syndromes have been distinguished categorically. A symptom dimension shared across these syndromes, if such a general factor exists, might provide a clearer target for understanding and treating mental illnesses that share core biological bases.

METHOD

We tested the hypothesis that a bifactor model of the Positive and Negative Syndrome Scale (PANSS), containing 1 general factor and 5 specific factors (positive, negative, disorganized, excited, anxiety), explains the cross-diagnostic structure of symptoms better than the traditional 5-factor model, and examined the extent to which a general factor reflects the overall severity of symptoms spanning diagnoses in 5094 total patients with a diagnosis of schizophrenia, schizoaffective, and bipolar disorder.

RESULTS

The bifactor model provided superior fit across diagnoses, and was closer to the "true" model, compared to the traditional 5-factor model (Vuong test; P < .001). The general factor included high loadings on 28 of the 30 PANSS items, omitting symptoms associated with the excitement and anxiety/depression domains. The general factor had highest total loadings on symptoms that are often associated with the positive and disorganization syndromes, but there were also substantial loadings on the negative syndrome thus leading to the interpretation of this factor as reflecting generalized psychosis.

CONCLUSIONS

A bifactor model derived from the PANSS can provide a stronger framework for measuring cross-diagnostic psychopathology than a 5-factor model, and includes a generalized psychosis dimension shared at least across schizophrenia, schizoaffective, and bipolar disorder.

Disparity between General Symptom Relief and Remission Criteria in the Positive and Negative Syndrome Scale (PANSS): A Post-treatment Bifactor Item Response Theory Model

Objective: Total scale scores derived by summing ratings from the 30-item PANSS are commonly used in clinical trial research to measure overall symptom severity, and percentage reductions in the total scores are sometimes used to document the efficacy of treatment. Acknowledging that some patients may have substantial changes in PANSS total scores but still be sufficiently symptomatic to warrant diagnosis, ratings on a subset of 8 items, referred to here as the "Remission set," are sometimes used to determine if patients' symptoms no longer satisfy diagnostic criteria. An unanswered question remains: is the goal of treatment better conceptualized as reduction in overall symptom severity, or reduction in symptoms below the threshold for diagnosis? We evaluated the psychometric properties of PANSS total scores, to assess whether having low symptom severity post-treatment is equivalent to attaining Remission. Design: We applied a bifactor item response theory (IRT) model to post-treatment PANSS ratings of 3,647 subjects diagnosed with schizophrenia assessed at the termination of 11 clinical trials. The bifactor model specified one general dimension to reflect overall symptom severity, and five domain-specific dimensions. We assessed how PANSS item discrimination and information parameters varied across the range of overall symptom severity (θ), with a special focus on low levels of symptoms (i.e., θ<-1), which we refer to as "Relief" from symptoms. A score of θ=-1 corresponds to an expected PANSS item score of 1.83, a rating between "Absent" and "Minimal" for a PANSS symptom. Results: The application of the bifactor IRT model revealed: (1) 88% of total score variation was attributable to variation in general symptom severity, and only 8% reflected secondary domain factors. This implies that a general factor may provide a good indicator of symptom severity, and that interpretation is not overly complicated by multidimensionality; (2) Post-treatment, 534 individuals (about 15% of the whole sample) scored in the "Relief" range of general symptom severity, but more than twice that number (n = 1351) satisfied Remission criteria (37%). 2 in 3 Remitted patients had scores that were not in a low symptom range (corresponding to Absent or Minimal item scores); (3) PANSS items vary greatly in their ability to measure the general symptom severity dimension; while many items are highly discriminating and relatively "pure" indicators of general symptom severity (delusions, conceptual disorganization), others are better indicators of specific dimensions (blunted affect, depression). The utility of a given PANSS item for assessing a patient depended on the illness level of the patient. Conclusion: Satisfying conventional Remission criteria was not strongly associated with low levels of symptoms. The items providing the most information for patients in the symptom Relief range were Delusions, Preoccupation, Suspiciousness Persecution, Unusual Thought Content, Conceptual Disorganization, Stereotyped Thinking, Active Social Avoidance, and Lack of Judgment and Insight. Lower scores on these items (item scores ≤2) were strongly associated with having a low latent trait θ or experiencing overall symptom relief. The inter-rater agreement between Remission and Relief subjects suggested that these criteria identified different subsets of patients. Alternative subsets of items may offer better indicators of general symptom severity and provide better discrimination (and lower standard errors) for scaling individuals and judging symptom relief, where the "best" subset of items ultimately depends on the illness range and treatment phase being evaluated.