An Early Developmental Marker of Deficit versus Nondeficit Schizophrenia

[The new psychopathological paradigm of schizophrenia and schizophrenia spectrum disorders]

The basis of the new paradigm, as an attempt to modernize the systematics of psychopathological disorders, is the concept of simultaneous representation of two relatively independent domains (founded by neurobiological processes) in the clinical space of schizophrenia - negative and positive disorders. The study established the spectra of functional activity of endogenous dimensions, as well as the trajectories of their development, which determine the dominance of predominantly negative or positive symptoms (negative/positive schizophrenia) during the course of the disease. The differentiated impact of endogenous domains on constitutional characterological structures accompanied by the formation of pseudopsychiopathies and subpsychotic personality disorders is observed.

Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analyses

Converging evidence suggests that schizophrenia (SZ) with primary, enduring negative symptoms (i.e., Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the neurobiological underpinnings remain undetermined. In the largest dataset of DSZ and Non-Deficit (NDSZ), we conducted a meta-analysis of data from 1560 individuals (168 DSZ, 373 NDSZ, 1019 Healthy Controls (HC)) and a mega-analysis of a subsampled data from 944 individuals (115 DSZ, 254 NDSZ, 575 HC) collected across 9 worldwide research centers of the ENIGMA SZ Working Group (8 in the mega-analysis), to clarify whether they differ in terms of cortical morphology. In the meta-analysis, sites computed effect sizes for differences in cortical thickness and surface area between SZ and control groups using a harmonized pipeline. In the mega-analysis, cortical values of individuals with schizophrenia and control participants were analyzed across sites using mixed-model ANCOVAs. The meta-analysis of cortical thickness showed a converging pattern of widespread thinner cortex in fronto-parietal regions of the left hemisphere in both DSZ and NDSZ, when compared to HC. However, DSZ have more pronounced thickness abnormalities than NDSZ, mostly involving the right fronto-parietal cortices. As for surface area, NDSZ showed differences in fronto-parietal-temporo-occipital cortices as compared to HC, and in temporo-occipital cortices as compared to DSZ. Although DSZ and NDSZ show widespread overlapping regions of thinner cortex as compared to HC, cortical thinning seems to better typify DSZ, being more extensive and bilateral, while surface area alterations are more evident in NDSZ. Our findings demonstrate for the first time that DSZ and NDSZ are characterized by different neuroimaging phenotypes, supporting a nosological distinction between DSZ and NDSZ and point toward the separate disease hypothesis.

Lack of correlation between hippocampal substructure atrophy and attention dysfunction in deficit schizophrenia

Hippocampal abnormalities are an established finding in the neuroimaging study of schizophrenia. However, no studies have examined the possibility of regional hippocampal abnormalities specific to deficit schizophrenia (DS) and associations with the unique symptoms of this schizophrenia subtype. This study compared 33 DS and 39 non-deficit schizophrenia (NDS) patients and 38 healthy subjects for hippocampal subfield volumetry. Clinical symptoms were assessed by PANSS, cognition by the neurocognitive battery on the day of the MRI scan. The automatic hippocampal segmentation were preprocesses use FreeSurfer 7.2.0. Unfortunately, the associations between neurocognitive scores and hippocampal subfield volumes in the DS group were not significant after the Bonferroni correction. Our results did not support a causal relationship between hippocampal subregional atrophy and cognitive deficits in DS.

Using support vector machine to explore the difference of function connection between deficit and non-deficit schizophrenia based on gray matter volume

Objective

Schizophrenia can be divided into deficient schizophrenia (DS) and non-deficient schizophrenia (NDS) according to the presence of primary and persistent negative symptoms. So far, there are few studies that have explored the differences in functional connectivity (FC) between the different subtypes based on the region of interest (ROI) from GMV (Gray matter volume), especially since the characteristics of brain networks are still unknown. This study aimed to investigate the alterations of functional connectivity between DS and NDS based on the ROI obtained by machine learning algorithms and differential GMV. Then, the relationships between the alterations and the clinical symptoms were analyzed. In addition, the thalamic functional connection imbalance in the two groups was further explored.

Methods

A total of 16 DS, 31 NDS, and 38 health controls (HC) underwent resting-state fMRI scans, patient group will further be evaluated by clinical scales including the Brief Psychiatric Rating Scale (BPRS), the Scale for the Assessment of Negative Symptoms (SANS), and the Scale for the Assessment of Positive Symptoms (SAPS). Based on GMV image data, a support vector machine (SVM) is used to classify DS and NDS. Brain regions with high weight in the classification were used as seed points in whole-brain FC analysis and thalamic FC imbalance analysis. Finally, partial correlation analysis explored the relationships between altered FC and clinical scale in the two subtypes.

Results

The relatively high classification accuracy is obtained based on the SVM. Compared to HC, the FC increased between the right inferior parietal lobule (IPL.R) bilateral thalamus, and lingual gyrus, and between the right inferior temporal gyrus (ITG.R) and the Salience Network (SN) in NDS. The FC between the right thalamus (THA.R) and Visual network (VN), between ITG.R and right superior occipital gyrus in the DS group was higher than that in HC. Furthermore, compared with NDS, the FC between the ITG.R and the left superior and middle frontal gyrus decreased in the DS group. The thalamic FC imbalance, which is characterized by frontotemporal-THA.R hypoconnectivity and sensory motor network (SMN)-THA.R hyperconnectivity was found in both subtypes. The FC value of THA.R and SMN was negatively correlated with the SANS score in the DS group but positively correlated with the SAPS score in the NDS group.

Conclusion

Using an SVM classification method and based on an ROI from GMV, we highlighted the difference in functional connectivity between DS and NDS from the local to the brain network, which provides new information for exploring the neural physiopathology of the two subtypes of schizophrenic.

Clinical and developmental characteristics of cognitive subgroups in a transdiagnostic sample of schizophrenia spectrum disorders and bipolar disorder

Evidence suggests that neurocognitive dysfunction is a transdiagnostic feature of individuals across the continuum between schizophrenia and bipolar disorder. However, there is significant heterogeneity of neuropsychological and social-cognitive abilities in schizophrenia, schizoaffective disorder, and bipolar disorder. The current study aimed to investigate the clinical and developmental characteristics of cognitive subgroups within the schizo-bipolar spectrum. 147 clinically stable patients with schizophrenia, schizoaffective or bipolar disorder were assessed using clinical rating scales for current psychotic and affective symptoms, and a comprehensive neuropsychological battery including measures of social cognition (Hinting and Reading the mind from the Eyes (RMET) task)). Developmental history and premorbid academic functioning were also evaluated. The study also included 36 healthy controls. Neurocognitive subgroups were investigated using latent class analysis (LCA). The optimal number of clusters was determined based on the Bayesian information criterion. A logistic regression analysis was conducted to investigate the predictors of membership to the globally impaired subgroup. LCA revealed two neurocognitive clusters including globally impaired (n = 89, 60.5%) and near-normal cognitive functioning (n = 58, 39.5%) subgroups. The near-normal cognitive functioning subgroup was not significantly different from healthy controls. The globally impaired subgroup had a higher score of developmental abnormalities (p<0.001), poorer premorbid academic functioning, mothers who were less educated and more severe disorganized speech (p = 0.001) and negative symptoms (p = 0.004) compared to the near-normal cognitive functioning group. History of developmental abnormalities and persistent disorganization rather than diagnosis are significant predictors of the subgroup of individuals with global cognitive impairment in the schizophrenia-bipolar disorder continuum.

Development and validation of a web-based prediction tool on minor physical anomalies for schizophrenia

In support of the neurodevelopmental model of schizophrenia, minor physical anomalies (MPAs) have been suggested as biomarkers and potential pathophysiological significance for schizophrenia. However, an integrated, clinically useful tool that used qualitative and quantitative MPAs to visualize and predict schizophrenia risk while characterizing the degree of importance of MPA items was lacking. We recruited a training set and a validation set, including 463 schizophrenia patients and 281 healthy controls to conduct logistic regression and the least absolute shrinkage and selection operator (Lasso) regression to select the best parameters of MPAs and constructed nomograms. Two nomograms were built to show the weights of these predictors. In the logistic regression model, 11 out of a total of 68 parameters were identified as the best MPA items for distinguishing between patients with schizophrenia and controls, including hair whorls, epicanthus, adherent ear lobes, high palate, furrowed tongue, hyperconvex fingernails, a large gap between first and second toes, skull height, nasal width, mouth width, and palate width. The Lasso regression model included the same variables of the logistic regression model, except for nasal width, and further included two items (interpupillary distance and soft ears) to assess the risk of schizophrenia. The results of the validation dataset verified the efficacy of the nomograms with the area under the curve 0.84 and 0.85 in the logistic regression model and lasso regression model, respectively. This study provides an easy-to-use tool based on validated risk models of schizophrenia and reflects a divergence in development between schizophrenia patients and healthy controls (https://www.szprediction.net/).

Differences in inflammatory marker profiles and cognitive functioning between deficit and nondeficit schizophrenia

Deficit schizophrenia (DS) patient is a homogenous subtype of schizophrenia that includes primary and enduring negative symptoms. This study aimed to compare the differences in cognitive functioning and plasma levels of C-reactive protein (CRP) and inflammatory cytokines among DS patients, nondeficit schizophrenia (NDS) patients, and healthy controls (HCs). A total of 141 schizophrenia patients and 67 HCs were included in this study. The schizophrenia patients were divided into DS (N= 51) and NDS (N=90) groups based on the Proxy for the Deficit Syndrome Scale (PDS). The Positive and Negative Syndrome Scale (PANSS) and the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) were used to evaluate the clinical symptoms and cognitive performances, respectively. The plasma level of CRP, IL-1β, Il-2, IL-4, IL-6, IL-8, IL-10, IL-12, IL-17, TNF-α, and IFN-γ were measured using enzyme-linked immunosorbent assays (ELISAs). Our results showed that DS patients had the worst cognitive performance, especially in the immediate memory, attention, and language dimensions, compared to the NDS and HC groups. Compared to the HCs group, DS patients had higher levels of CRP, IL-1β, IL-6, IL-8, IFN-γ, and total proinflammatory cytokines, and NDS patients had higher levels of IL-1β, IFN-γ, and proinflammatory cytokines. We also found that CRP levels were significantly increased in DS patients compared to NDS patients. Moreover, stepwise logistic regression analysis revealed that CRP is an independent risk factor for DS. Sex stratification analysis showed significant differences in almost all cytokines in female samples but not in male samples. The significant differences in cognitive performance and inflammatory components among groups suggest that deficit syndrome is an independent endophenotype of schizophrenia patients with unique immune-inflammatory features, but may have sex characteristics.

Improved Multiclassification of Schizophrenia Based on Xgboost and Information Fusion for Small Datasets

To improve the performance in multiclass classification for small datasets, a new approach for schizophrenic classification is proposed in the present study. Firstly, the Xgboost classifier is introduced to discriminate the two subtypes of schizophrenia from health controls by analyzing the functional magnetic resonance imaging (fMRI) data, while the gray matter volume (GMV) and amplitude of low-frequency fluctuations (ALFF) are extracted as the features of classifiers. Then, the D-S combination rule of evidence is used to achieve fusion to determine the basic probability assignment based on the output of different classifiers. Finally, the algorithm is applied to classify 38 healthy controls, 16 deficit schizophrenic patients, and 31 nondeficit schizophrenic patients. 10-folds cross-validation method is used to assess classification performance. The results show the proposed algorithm with a sensitivity of 73.89%, which is higher than other classification algorithms, such as supported vector machine (SVM), logistic regression (LR), K-nearest neighbor (KNN) algorithm, random forest (RF), BP neural network (NN), classification and regression tree (CART), naive Bayes classifier (NB), extreme gradient boosting (Xgboost), and deep neural network (DNN). The accuracy of the fusion algorithm is higher than that of classifier based on the GMV or ALFF in the small datasets. The accuracy rate of the improved multiclassification method based on Xgboost and fusion algorithm is higher than that of other machine learning methods, which can further assist the diagnosis of clinical schizophrenia.

Early versus late risk factors for deficit and nondeficit schizophrenia

AIM

We examined whether timing of known risk factors for schizophrenia may influence the development of schizophrenia with primary negative symptoms.

METHOD

This cross-sectional single-centre study in England used a clinical cohort of 167 clozapine-treated schizophrenia patients. Deficit and nondeficit schizophrenia models were used as clinical proxies of patients with and without primary negative symptoms respectively. Patients were assessed using the Schedule for the Deficit Syndrome. We examined previously replicated risk factors (family history of psychosis, advanced paternal age, male gender, birth weight <3000g, summer birth, cannabis use, exposure to physical or sexual abuse and/or bullying) as well as other traumatic events for deficit and nondeficit schizophrenia.

RESULTS

We found a distinct risk factor pattern for the two groups. Compared to the nondeficit group, patients with deficit schizophrenia reported a significantly lower prevalence of cannabis use (p=0.005) at the time of first-episode psychosis (FEP), physical or sexual abuse (p=0.033) prior to FEP, less exposure to crime-related traumatic events (p=0.012) and significantly associated with summer birth (p=0.017). The groups did not differ in terms of family history of psychosis, advanced paternal age, male gender, or low birth weight. To account for multiple comparisons, a confirmatory analysis was performed using logistic regression which yielded similar results except that summer birth no longer reached statistical significance.

CONCLUSION

Our results suggest the timing of the insult may influence the symptom presentation, with insults later in life (cannabis or traumatic events) being associated with psychotic presentation and less with primary negative symptoms.

Cross-diagnostic evaluation of minor physical anomalies in psychiatric disorders

BACKGROUND

Minor physical anomalies (MPA) are markers of impaired neurodevelopment during the prenatal stage. Assessing MPA across psychiatric disorders may help understand their shared nature. In addition, MPA in family members would indicate a shared liability and endophenotype potential. We examined familial aggregation of MPA and their role as transdiagnostic and disorder-specific markers of 5 major psychiatric/neuropsychiatric conditions (schizophrenia, bipolar disorder, substance dependence, obsessive-compulsive disorder, and Alzheimer's dementia).

METHODS

Modified Waldrop's MPA scale was applied on 1321 individuals from 439 transdiagnostic multiplex families and 125 healthy population controls (HC). Stage of fetal development (morphogenetic/phenogenetic)- and anatomical location (craniofacial/peripheral)-based sub-scores were calculated. Familiality and endophenotypic potential of MPA were analyzed with serial negative binomial mixed-effect regression. Cross-diagnostic differences and the effect of family history density (FHD) of each diagnosis on MPA were assessed. Mixed-effects Cox models estimated the influence of MPA on age-at-onset of illness (AAO).

RESULTS

MPA were found to be heritable in families with psychiatric disorders, with a familiality of 0.52. MPA were higher in psychotic disorders after controlling for effects of sex and intrafamilial correlation. Morphogenetic variant MPA was noted to be lower in dementia in comparison to HC. FHD of schizophrenia and bipolar disorder predicted higher, and that of dementia and substance dependence predicted lower MPA. MPA brought forward the AAO [HR:1.07 (1.03-1.11)], and this was more apparent in psychotic disorders.

CONCLUSION

MPA are transmissible in families, are specifically related to the risk of developing psychoses, and predict an earlier age at onset. Neurodevelopmentally informed classification of MPA has the potential to enhance the etiopathogenic and translational understanding of psychiatric disorders.

Physical and social anhedonia are associated with suicidality in major depression, but not in schizophrenia

OBJECTIVE

This cross-sectional study investigated the association of physical and social anhedonia with suicidality in patients with major depressive disorder (MDD), schizophrenia, and in non-psychiatric controls.

METHOD

All participants completed the revised Physical Anhedonia Scale (RPAS) and the revised Social Anhedonia Scale (RSAS) and were subdivided according to positive life-time suicide attempt history. MDD patients were evaluated with the Montgomery-Ãsberg Depression Rating Scale (MADRS), healthy respondents with the Patient Health Questionnaire-9 (PHQ-9), and schizophrenia patients with the Calgary Depression Scale for Schizophrenia (CDSS).

RESULTS

In 683 study participants, the prevalence of each anhedonia was the highest in MDD, followed by schizophrenia, and lowest in the control group. Among MDD patients, those with physical and social anhedonia had greater rates of recent suicidal ideation, while a higher frequency of individuals with life-time suicide attempts was detected in those with only social anhedonia. In contrast, no association between either anhedonia and life-time suicide attempts or recent suicidal ideation was found in patients with schizophrenia.

CONCLUSIONS

Assessing social and physical anhedonia might be important in MDD patients, given its association with both life-time suicide attempts and recent suicidal ideation. Suicidality in schizophrenia, while unrelated to anhedonia, might include other risk factors.

Early versus late risk factors for deficit and nondeficit schizophrenia

AIM

We examined whether timing of known risk factors for schizophrenia may influence the development of schizophrenia with primary negative symptoms.

METHOD

This cross-sectional single-centre study in England used a clinical cohort of 167 clozapine-treated schizophrenia patients. Deficit and nondeficit schizophrenia models were used as clinical proxies of patients with and without primary negative symptoms respectively. Patients were assessed using the Schedule for the Deficit Syndrome. We examined previously replicated risk factors (family history of psychosis, advanced paternal age, male gender, birth weight <3000g, summer birth, cannabis use, exposure to physical or sexual abuse and/or bullying) as well as other traumatic events for deficit and nondeficit schizophrenia.

RESULTS

We found a distinct risk factor pattern for the two groups. Compared to the nondeficit group, patients with deficit schizophrenia reported a significantly lower prevalence of cannabis use (p=0.005) at the time of first-episode psychosis (FEP), physical or sexual abuse (p=0.033) prior to FEP, less exposure to crime-related traumatic events (p=0.012) and significantly associated with summer birth (p=0.017). The groups did not differ in terms of family history of psychosis, advanced paternal age, male gender, or low birth weight. To account for multiple comparisons, a confirmatory analysis was performed using logistic regression which yielded similar results except that summer birth no longer reached statistical significance.

CONCLUSION

Our results suggest the timing of the insult may influence the symptom presentation, with insults later in life (cannabis or traumatic events) being associated with psychotic presentation and less with primary negative symptoms.