A pilot study of cognitive insight and structural covariance in first-episode psychosis

Structural covariance networks in schizophrenia: A systematic review Part I

BACKGROUND

Schizophrenia is proposed as a disorder of dysconnectivity. However, examination of complexities of dysconnectivity has been challenging. Structural covariance networks (SCN) provide important insights into the nature of dysconnectivity. This systematic review examines the SCN studies that employed statistical approaches to elucidate covariation of regional morphometric variations.

METHODS

A systematic search of literature was conducted for peer-reviewed publications using different keywords and keyword combinations for schizophrenia. Fifty-two studies met the criteria.

RESULTS

Early SCN studies began using correlational structure of selected regions. Over the last 3 decades, methodological approaches have grown increasingly sophisticated from examining selected brain regions using correlation tests on small sample sizes to recent approaches that use advanced statistical methods to examine covariance structure of whole-brain parcellations on larger samples. Although the results are not fully consistent across all studies, a pattern of fronto-temporal, fronto-parietal and fronto-thalamic covariation is reported. Attempts to associate SCN alterations with functional connectivity, to differentiate between disease-related and neurodevelopment-related morphometric changes, and to develop "causality-based" models are being reported. Clinical correlation with outcome, psychotic symptoms, neurocognitive and social cognitive performance are also reported.

CONCLUSIONS

Application of advanced statistical methods are beginning to provide insights into interesting patterns of regional covariance including correlations with clinical and cognitive data. Although these findings appear similar to morphometric studies, SCNs have the advantage of highlighting topology of these regions and their relationship to the disease and associated variables. Further studies are needed to investigate neurobiological underpinnings of shared covariance, and causal links to clinical domains.

Correlations between cortical gyrification and schizophrenia symptoms with and without comorbid hostility symptoms

INTRODUCTION

Interest in identifying the clinical implications of the neuropathophysiological background of schizophrenia is rising, including changes in cortical gyrification that may be due to neurodevelopmental abnormalities. Inpatients with schizophrenia can show abnormal gyrification of cortical regions correlated with the symptom severity.

METHODS

Our study included 36 patients that suffered an acute episode of schizophrenia and have undergone structural magnetic resonance imaging (MRI) to calculate the local gyrification index (LGI).

RESULTS

In the whole sample, the severity of symptoms significantly correlated with higher LGI in different cortical areas, including bilateral frontal, cingulate, parietal, temporal cortices, and right occipital cortex. Among these areas, patients with low hostility symptoms (LHS) compared to patients with high hostility symptoms (HHS) showed significantly lower LGI related to the severity of symptoms in bilateral frontal and temporal lobes.

DISCUSSION

The severity of psychopathology correlated with higher LGI in large portions of the cerebral cortex, possibly expressing abnormal neural development in schizophrenia. These findings could pave the way for further studies and future tailored diagnostic and therapeutic strategies.

Insight does not come at random: Individual gray matter networks relate to clinical and cognitive insight in schizophrenia

BACKGROUND

Impaired clinical and cognitive insight are prevalent in schizophrenia and relate to poorer outcome. Good insight has been suggested to depend on social cognitive and metacognitive abilities requiring global integration of brain signals. Impaired insight has been related to numerous focal gray matter (GM) abnormalities distributed across the brain suggesting dysconnectivity at the global level. In this study, we test whether global integration deficiencies reflected in gray matter network connectivity underlie individual variations in insight.

METHODS

We used graph theory to examine whether individual GM-network metrics relate to insight in patients with a psychotic disorder (n = 114). Clinical insight was measured with the Schedule for the Assessment of Insight-Expanded and item G12 of the Positive and Negative Syndrome Scale, and cognitive insight with the Beck Cognitive Insight Scale. Individual GM-similarity networks were created from GM-segmentations of T1-weighted MRI-scans. Graph metrics were calculated using the Brain Connectivity Toolbox.

RESULTS

Networks of schizophrenia patients with poorer clinical insight showed less segregation (i.e. clustering coefficient) into specialized subnetworks at the global level. Schizophrenia patients with poorer cognitive insight showed both less segregation and higher connectedness (i.e. lower path length) of their brain networks, making their network topology more "random".

CONCLUSIONS

Our findings suggest less segregated processing of information in patients with poorer cognitive and clinical insight, in addition to higher connectedness in patients with poorer cognitive insight. The ability to take a critical perspective on one's symptoms (clinical insight) or views (cognitive insight) might depend especially on segregated specialized processing within distinct subnetworks.

"First-episode psychosis: Structural covariance deficits in salience network correlate with symptoms severity"

BACKGROUND

Patterns of coordinated variations of gray matter (GM) morphology across individuals are promising indicators of disease. However, it remains unclear if they can help characterize first-episode psychosis (FEP) and symptoms' severity.

METHODS

Sixty-seven FEP and 67 matched healthy controls (HC) were assessed with structural MRI to evaluate the existence of distributed GM structural covariance patterns associated to brain areas belonging to salience network. Voxel-based morphometry (VBM) and structural covariance differences, investigated with salience network seed-based Partial Least Square, were applied to explore differences between groups. GM density associations with Raven's intelligent quotient (IQ) and Positive and Negative Syndrome Scale (PANSS) scores were investigated.

RESULTS

Univariate VBM results gave trend without significant GM differences across groups. GM and IQ correlated positively in both groups: in FEP, mostly in hippocampus, insula, and fronto-temporal structures, while in HC mostly in amygdala, thalamus and fronto-temporal regions. GM and PANSS scores correlated negatively in FEP, with widespread clusters located in limbic regions. Multivariate analysis showed strong and opposite structural GM covariance with salience network for FEP and HC. Moreover, structural covariance of the salience network in FEP correlated negatively with severity of clinical symptoms.

CONCLUSION

Our study provides evidence supporting the insular dysfunction model of psychosis. Reduced structural GM covariance of the salience network, with its association to symptom's severity, appears a promising morphometry feature for FEP detection.

The frontal pole and cognitive insight in schizophrenia

Absence of insight owing to impaired self-reflection and lack of touch with reality is a hallmark of schizophrenia. Functional imaging studies in healthy individuals have implicated the frontal pole (FP), sub-division of the prefrontal cortex in self-reflective processes. Despite the significance of self-referential processing in the pathogenesis of schizophrenia, the relationship between FP volume and cognitive insight in this disorder is underexplored. We examined the relationship between cognitive insight and volume of FP using precise manual morphometry of high resolution magnetic resonance images in 19 schizophrenia patients (SCZ) and 21 healthy-volunteers (HV). The manual morphometry technique was replicated from a previous study based on a cytoarchitectonically and functionally valid definition of FP and cognitive insight was measured using Beck's cognitive insight scale. Left frontal pole volume was a significant predictor of self-reflection sub-score of Beck's cognitive insight scale (β=0.68; t = 2.86; p = 0.01). A significant inverse relationship between age and bilateral FP volumes was noted in HV (left FP - r=-0.45; p = 0.04; right FP - r=-0.57; p = 0.008) but not in SCZ (p>0.05). Our findings provide anatomical substrates to devise intervention strategies targeting cognitive insight, thereby improving treatment adherence and functional outcomes.

Common and Specific Characteristics of Adolescent Bipolar Disorder Types I and II: A Combined Cortical Thickness and Structural Covariance Analysis

BACKGROUND

By calculating cortical thickness (CT) and cortical structural covariance (SC), we aimed to investigate cortical morphology and cortical inter-regional correlation alterations in adolescent bipolar disorder type I (BD-I) and type II (BD-II) patients.

METHODS

T1-weighted images from 36 BD-I and 22 BD-II patients and 19 healthy controls (HCs) were processed to estimate CT. CT values of the whole brain were compared among three groups. Cortical regions showing CT differences in groups were regarded as seeds for analyzing cortical SC differences between groups. The relationship between CT and clinical indices was further assessed.

RESULTS

Both BD groups showed cortical thinning in several frontal and temporal areas vs. HCs, and CT showed no significant difference between two BD subtypes. Compared to HCs, both BD groups exhibited reduced SC connections between left superior frontal gyrus (SFG) and right postcentral gyrus (PCG), left superior temporal gyrus (STG) and right pars opercularis, and left STG and right PCG. Compared with HCs, decreased SC connections between left STG and right inferior parietal gyrus (IPG) and right pars opercularis and right STG were only observed in the BD-I group, and left PCG and left SFG only in the BD-II group. CT of right middle temporal gyrus was negatively correlated with number of episodes in BD-II patients.

CONCLUSIONS

Adolescent BD-I and BD-II showed commonly decreased CT while presenting commonly and distinctly declined SC connections. This study provides a better understanding of cortical morphology and cortical inter-regional correlation alterations in BD and crucial insights into neuroanatomical mechanisms and pathophysiology of different BD subtypes.

Cognitive insight in psychotic patients institutionalized and living in the community: an examination using the Beck Cognitive Insight Scale

Improving cognitive insight can reduce delusions in patients with psychotic disorders. Although institutionalized patients usually have more severe delusions than outpatients, little is known about the differences in cognitive insight between these two groups. In this study, we evaluated the psychometric properties of the Beck Cognitive Insight Scale (BCIS) for a sample of Portuguese patients with psychotic disorders and compared the cognitive insight of institutionalized patients with patients living in the community. Participants in this study were 150 patients diagnosed with psychotic disorder (78 institutionalized patients and 72 outpatients). The tested model of the BCIS was a very good fit. Our study shows that patients living in the community showed higher levels of cognitive insight (total BCIS and self-reflectiveness) than institutionalized patients. Future studies assessing cognitive insight should take into account differences between the cognitive insights of institutionalized psychotic patients and psychotic patients living in the community.

Multimodal MRI assessment for first episode psychosis: A major change in the thalamus and an efficient stratification of a subgroup

Multi‐institutional brain imaging studies have emerged to resolve conflicting results among individual studies. However, adjusting multiple variables at the technical and cohort levels is challenging. Therefore, it is important to explore approaches that provide meaningful results from relatively small samples at institutional levels. We studied 87 first episode psychosis (FEP) patients and 62 healthy subjects by combining supervised integrated factor analysis (SIFA) with a novel pipeline for automated structure‐based analysis, an efficient and comprehensive method for dimensional data reduction that our group recently established. We integrated multiple MRI features (volume, DTI indices, resting state fMRI—rsfMRI) in the whole brain of each participant in an unbiased manner. The automated structure‐based analysis showed widespread DTI abnormalities in FEP and rs‐fMRI differences between FEP and healthy subjects mostly centered in thalamus. The combination of multiple modalities with SIFA was more efficient than the use of single modalities to stratify a subgroup of FEP (individuals with schizophrenia or schizoaffective disorder) that had more robust deficits from the overall FEP group. The information from multiple MRI modalities and analytical methods highlighted the thalamus as significantly abnormal in FEP. This study serves as a proof‐of‐concept for the potential of this methodology to reveal disease underpins and to stratify populations into more homogeneous sub‐groups.

Impact of emotion dysregulation and cognitive insight on psychotic and depressive symptoms during the early course of schizophrenia spectrum disorders

OBJECTIVE

Emotion dysregulation is relevant to the aetiology of schizophrenia spectrum disorders (SSD). While most studies have focused on the chronic phase of SSD, little is known about the effects of emotion dysregulation and associated cognitive risk factors during the early phase of the illness, with negative implications for early intervention. The purpose of this study is to examine the impact of maladaptive cognitive emotion regulation strategies, global emotion dysregulation, and cognitive insight on psychotic and comorbid depressive symptoms in patients with early SSD.

METHOD

Participants included 150 newly diagnosed outpatients with SSD who were seeking treatment at the Early Psychosis Intervention Program. All participants completed the Cognitive Emotion Regulation Questionnaire, Difficulties with Emotion Regulation Scale, and Beck Cognitive Insight Scale. Severity of psychotic and depressive symptoms were rated on the Brief Psychiatric Rating Scale.

RESULTS

Multivariate regression adjusting for gender and psychiatric comorbidity revealed that global emotion dysregulation was associated with more severe positive and depressive symptoms. Further moderation analyses revealed a significant interaction between global emotion dysregulation and cognitive insight (self-certainty) on depression such that for patients with high self-certainty, greater global emotion dysregulation was associated with increased severity of depressive symptoms. There was no interaction between global emotion dysregulation and cognitive insight on positive symptoms.

CONCLUSIONS

Our findings provide preliminary support for the associations between emotion dysregulation and psychopathology in early SSD. Further research is needed to examine the transdiagnostic role of emotion dysregulation in the aetiology and treatment of a wider range of psychotic disorders.

Structural Covariance Reveals Alterations in Control and Salience Network Integrity in Chronic Schizophrenia

Schizophrenia (SCZ) is recognized as a disorder of distributed brain dysconnectivity. While progress has been made delineating large-scale functional networks in SCZ, little is known about alterations in grey matter integrity of these networks. We used a multivariate approach to identify the structural covariance of the salience, default, motor, visual, fronto-parietal control, and dorsal attention networks. We derived individual scores reflecting covariance in each structural image for a given network. Seed-based multivariate analyses were conducted on structural images in a discovery (n = 90) and replication (n = 74) sample of SCZ patients and healthy controls. We first validated patterns across all networks, consistent with well-established functional connectivity reports. Next, across two SCZ samples, we found reliable and robust reductions in structural integrity of the fronto-parietal control and salience networks, but not default, dorsal attention, motor and sensory networks. Well-powered exploratory analyses failed to identify relationships with symptoms. These findings provide evidence of selective structural decline in associative networks in SCZ. Such decline may be linked with recently identified functional disturbances in associative networks, providing more sensitive multi-modal network-level probes in SCZ. Absence of symptom effects suggests that identified disturbances may underlie a trait-type marker in SCZ.

Brain Structural Correlates of Metacognition in First-Episode Psychosis

Metacognition is impaired in schizophrenia and is an important predictor of functional outcome, but the underlying neuropathology is not clear. Studies have implicated frontal regions and there is also some evidence that the hippocampus might play a pivotal role, but findings are inconsistent. We set out to more comprehensively investigate the neural underpinnings of insight in first-episode psychosis (FEP) using 2 metacognitive measures (the Beck Cognitive Insight Scale [BCIS]) and a perceptual metacognitive accuracy task alongside structural magnetic resonance imaging (MRI). We measured cortical thickness in insula and frontal regions, hippocampal (including subfield) volumes, hippocampal microstructure (using neurite orientation dispersion and density imaging [NODDI]), and fractional anisotropy in fornix. Relative to controls, FEP showed poorer metacognitive accuracy, thinner cortex in frontal regions and lower fornix integrity. In healthy controls (but not FEP), metacognitive accuracy correlated with cortical thickness in frontal cortex and insula. Conversely, in FEP (but not controls), metacognitive accuracy correlated with hippocampal volume and microstructural indices. Subicular hippocampal subregions were particularly implicated. No structural correlates of BCIS were found. These findings suggest that the neural bases of metacognition might differ in FEP: hippocampal (rather than frontal) integrity seems to be critical. Further, the use of objectively measured metacognitive indices seems to be a more powerful method for understanding the neurocircuitry of metacognition in FEP, which has the potential to inform therapeutic strategies and improve outcome in these patients.

Structural Associations of Cortical Contrast and Thickness in First Episode Psychosis

There is growing evidence that psychosis is characterized by brain network abnormalities. Analyzing morphological abnormalities with T1-weighted structural MRI may be limited in discovering the extent of deviations in cortical associations. We assess whether structural associations of either cortical white-gray contrast (WGC) or cortical thickness (CT) allow for a better understanding of brain structural relationships in first episode of psychosis (FEP) patients. Principal component and structural covariance analyses were applied to WGC and CT derived from T1-weighted MRI for 116 patients and 88 controls, to explore sets of brain regions that showed group differences, and associations with symptom severity and cognitive ability in patients. We focused on 2 principal components: one encompassed primary somatomotor regions, which showed trend-like group differences in WGC, and the second included heteromodal cortices. Patients' component scores were related to general psychopathology for WGC, but not CT. Structural covariance analyses with WGC revealed group differences in pairwise correlations across widespread brain regions, mirroring areas derived from PCA. More group differences were uncovered with WGC compared with CT. WGC holds potential as a proxy measure of myelin from commonly acquired T1-weighted MRI and may be sensitive in detecting systems-level aberrations in early psychosis, and relationships with clinical/cognitive profiles.

Cultural differences and neural correlates of cognitive insight in schizophrenia

Cognitive insight refers to a person's ability to examine their psychotic experiences and the inferences they draw from these experiences. Several studies suggest that cultural factors influence cognitive insight and the processes involved therein; a few studies have suggested differences between Western and Asian societies. However, there are no studies on cognitive insight and its neural correlates in non-Western populations. Hence, we examined factor structure of Beck's cognitive insight scale (BCIS) in a large sample of patients with schizophrenia (SCZ) and healthy volunteers (HV) from India and assessed the relationship between cortical thickness and cognitive insight. We recruited 240 participants (SCZ-140; HV-100). Of these, 58 participants (SCZ-33; HV-25) underwent magnetic resonance imaging. We found a three-factor structure for BCIS which is different from the original two factor structure; self-reflection (SR) of original two-factor structure was sub-divided into- SR1, introspection and SR2, openness to feedback. There was a significant difference between HV and SCZ in the new factors, SR1 and SR2 but not in the original SR factor. Difference was also seen on MRI analysis; while there was a significant positive correlation between original SR factor and thickness of right posterior cingulate cortex, SR2 was positively correlated with thickness of left ventrolateral prefrontal cortex. The difference in factor structure in Indian participants and their distinct neural correlates point to cultural differences in cognitive insight. While in western societies the constructs of introspection and openness to feedback might integrate, they might be separate entities in Asian population.

Insight in schizophrenia spectrum disorders: relationship with behavior, mood and perceived quality of life, underlying causes and emerging treatments

Poor insight in schizophrenia is prevalent across cultures and phases of illness. In this review, we examine the recent research on the relationship of insight with behavior, mood and perceived quality of life, on its complex roots, and on the effects of existing and emerging treatments. This research indicates that poor insight predicts poorer treatment adherence and therapeutic alliance, higher symptom severity and more impaired community function, while good insight predicts a higher frequency of depression and demoralization, especially when coupled with stigma and social disadvantage. This research also suggests that poor insight may arise in response to biological, experiential, neuropsychological, social-cognitive, metacognitive and socio-political factors. Studies of the effects of existing and developing treatments indicate that they may influence insight. In the context of earlier research and historical models, these findings support an integrative model of poor insight. This model suggests that insight requires the integration of information about changes in internal states, external circumstances, others' perspectives and life trajectory as well as the multifaceted consequences and causes of each of those changes. One implication is that treatments should, beyond providing education, seek to assist persons with schizophrenia to integrate the broad range of complex and potentially deeply painful experiences which are associated with mental illness into their own personally meaningful, coherent and adaptive picture.

Is It Possible to Predict the Future in First-Episode Psychosis?

The outcome of first-episode psychosis (FEP) is highly variable, ranging from early sustained recovery to antipsychotic treatment resistance from the onset of illness. For clinicians, a possibility to predict patient outcomes would be highly valuable for the selection of antipsychotic treatment and in tailoring psychosocial treatments and psychoeducation. This selective review summarizes current knowledge of prognostic markers in FEP. We sought potential outcome predictors from clinical and sociodemographic factors, cognition, brain imaging, genetics, and blood-based biomarkers, and we considered different outcomes, like remission, recovery, physical comorbidities, and suicide risk. Based on the review, it is currently possible to predict the future for FEP patients to some extent. Some clinical features-like the longer duration of untreated psychosis (DUP), poor premorbid adjustment, the insidious mode of onset, the greater severity of negative symptoms, comorbid substance use disorders (SUDs), a history of suicide attempts and suicidal ideation and having non-affective psychosis-are associated with a worse outcome. Of the social and demographic factors, male gender, social disadvantage, neighborhood deprivation, dysfunctional family environment, and ethnicity may be relevant. Treatment non-adherence is a substantial risk factor for relapse, but a small minority of patients with acute onset of FEP and early remission may benefit from antipsychotic discontinuation. Cognitive functioning is associated with functional outcomes. Brain imaging currently has limited utility as an outcome predictor, but this may change with methodological advancements. Polygenic risk scores (PRSs) might be useful as one component of a predictive tool, and pharmacogenetic testing is already available and valuable for patients who have problems in treatment response or with side effects. Most blood-based biomarkers need further validation. None of the currently available predictive markers has adequate sensitivity or specificity used alone. However, personalized treatment of FEP will need predictive tools. We discuss some methodologies, such as machine learning (ML), and tools that could lead to the improved prediction and clinical utility of different prognostic markers in FEP. Combination of different markers in ML models with a user friendly interface, or novel findings from e.g., molecular genetics or neuroimaging, may result in computer-assisted clinical applications in the near future.

Right Frontotemporal Cortex Mediates the Relationship between Cognitive Insight and Subjective Quality of Life in Patients with Schizophrenia

Although prior studies identified a relationship between cognitive insight and subjective quality of life (QOL) in patients with schizophrenia, the brain regions mediating this relationship remain unknown. Recent studies have shown that the ventrolateral prefrontal cortex may be particularly important for cognitive insight in individuals with schizophrenia. Here, we examined whether frontotemporal function mediates the relationship between cognitive insight and QOL in 64 participants, including 32 patients with schizophrenia and 32 healthy controls. Cognitive insight was measured using the Beck Cognitive Insight Scale (BCIS), while participants' subjective QOL was assessed using the Medical Outcomes Study 36-item Short-form Health Survey. Frontotemporal function was evaluated during a verbal fluency task using multichannel near-infrared spectroscopy. Consistent with previous findings, we found that frontotemporal function was impaired in patients with schizophrenia. Interestingly, our data also revealed that the right ventrolateral PFC and the right anterior part of the temporal cortex significantly mediated the relationship between the self-reflectiveness (SR) subscale of the BCIS and subjective QOL. These findings suggest that cognitive insight, particularly SR, is associated with subjective QOL in patients with schizophrenia via right frontotemporal function. The findings of this study provide important insight into a QOL model of schizophrenia, which may guide the development of cost-effective interventions that target frontotemporal function in patients with schizophrenia.