Endophenotypes in Schizophrenia: Digging Deeper to Identify Genetic Mechanisms

Undifferentiated psychosis or schizophrenia associated with vermis-predominant cerebellar hypoplasia

Schizophrenia (SCZ) is a well-studied neuropsychiatric condition that has been shown to have a high degree of genetic heritability. Still, little data on the specific genetic risk variants associated with the disease exists. Classification of the SCZ phenotype into SCZ-related endophenotypes is a promising methodology to parse out and elucidate the specific genetic risk variants for each. Here, we present a series of 17 previously reported individuals and a new proband with similar SCZ-related neuropsychiatric characteristics and shared brain imaging findings. Unsurprisingly, these individuals shared classic psychiatric features of SCZ. Interestingly, we also identified shared neuropsychiatric features in this series of individuals that had not been highlighted previously. A consistently decreased IQ, memory impairment, sleep and speech disturbances, and attention deficits were commonly reported findings. The brain imaging findings among these individuals also consistently showed posterior vermis predominant cerebellar hypoplasia (CBLH-V). Most individuals' diagnoses were initially described as Dandy-Walker malformation; however, our independent review of imaging suggests a more consistent pattern of posterior vermis predominant cerebellar hypoplasia rather than true Dandy-Walker malformation. While the specific genetic risk variants for this endophenotype are yet to be described, the aim of this paper is to present the shared neuropsychiatric features and consistent, symmetrical brain image findings which suggest that this subset of individuals comprises an endophenotype of SCZ with a high genetic solve rate.

Patients with first-episode psychosis in northern Taiwan: neurocognitive performance and niacin response profile in comparison with schizophrenia patients of different familial loadings and relationship with clinical features

BACKGROUND

Examining patients with first-episode psychosis (FEP) provides opportunities to better understand the mechanism underlying these illnesses. By incorporating quantitative measures in FEP patients, we aimed to (1) determine the baseline distribution of clinical features; (2) examine the impairment magnitude of the quantitative measures by comparing with external controls and then the counterparts of schizophrenia patients of different familial loadings; and (3) evaluate whether these quantitative measures were associated with the baseline clinical features.

METHODS

Patients with FEP were recruited from one medical center, two regional psychiatric centers, and two private clinics in northern Taiwan with clinical features rated using the Positive and Negative Syndrome Scale (PANSS) and Personal and Social Performance (PSP) scale. Quantitative measurements included the Continuous Performance Test (CPT), Wisconsin Card Sorting Test (WCST), niacin response abnormality (NRA), and minor physical anomalies and craniofacial features (MPAs). To evaluate the relative performance of the quantitative measures in our FEP patients, four external comparison groups from previous studies were used, including three independent healthy controls for the CPT, WCST, and NRA, respectively, and one group of treatment-resistant schizophrenia patients for the MPAs. Additionally, patients from simplex families and patients from multiplex families were used to assess the magnitude of FEP patients' impairment on the CPT, WCST, and NRA.

RESULTS

Among the 80 patients with FEP recruited in this study (58% female, mean age = 25.6 years, mean duration of untreated psychosis = 132 days), the clinical severity was mild to moderate (mean PANSS score = 67.3; mean PSP score = 61.8). Patients exhibited both neurocognitive and niacin response impairments (mean Z-scores: -1.24 for NRA, - 1.06 for undegraded d', - 0.70 for degraded d', - 0.32 for categories achieved, and 0.44 for perseverative errors) but did not show MPAs indicative of treatment resistance. Among these quantitative measures, three of the four neurocognitive indices were correlated with the baseline clinical features, whereas NRA did not show such correlation.

CONCLUSIONS

This FEP study of Taiwanese patients revealed the presence of neurocognitive performance and niacin response and their different relationships with clinical features, rendering this sample useful for future follow-up and incorporation of multiomics investigation.

Patterns of Impaired Neurocognitive Performance on the Global Neuropsychological Assessment, and Their Brain Structural Correlates in Recent-onset and Chronic Schizophrenia

Objective

Schizophrenia is associated with impairment in multiple cognitive domains. There is a paucity of research on the effect of prolonged illness duration (≥ 15 years) on cognitive performance along multiple domains. In this pilot study, we used the Global Neuropsychological Assessment (GNA), a brief cognitive battery, to explore the patterns of cognitive impairment in recent-onset (≤ 2 years) compared to chronic schizophrenia (≥ 15 years), and correlate cognitive performance with brain morphometry in patients and healthy adults.

Methods

We assessed cognitive performance in patients with recent-onset (n = 17, illness duration ≤ 2 years) and chronic schizophrenia (n = 14, duration ≥ 15 years), and healthy adults (n = 16) using the GNA and examined correlations between cognitive scores and gray matter volumes computed from T1-weighted magnetic resonance imaging images.

Results

We observed cognitive deficits affecting multiple domains in the schizophrenia samples. Selectively greater impairment of perceptual comparison speed was found in adults with chronic schizophrenia (p = 0.009, η2partial = 0.25). In the full sample (n = 47), perceptual comparison speed correlated significantly with gray matter volumes in the anterior and medial temporal lobes (TFCE, FWE p < 0.01).

Conclusion

Along with generalized deficit across multiple cognitive domains, selectively greater impairment of perceptual comparison speed appears to characterize chronic schizophrenia. This pattern might indicate an accelerated or premature cognitive aging. Anterior-medial temporal gray matter volumes especially of the left hemisphere might underlie the impairment noted in this domain in schizophrenia.

The P-factor and its genomic and neural equivalents: an integrated perspective

Different psychiatric disorders and symptoms are highly correlated in the general population. A general psychopathology factor (or "P-factor") has been proposed to efficiently describe this covariance of psychopathology. Recently, genetic and neuroimaging studies also derived general dimensions that reflect densely correlated genomic and neural effects on behaviour and psychopathology. While these three types of general dimensions show striking parallels, it is unknown how they are conceptually related. Here, we provide an overview of these three general dimensions, and suggest a unified interpretation of their nature and underlying mechanisms. We propose that the general dimensions reflect, in part, a combination of heritable 'environmental' factors, driven by a dense web of gene-environment correlations. This perspective calls for an update of the traditional endophenotype framework, and encourages methodological innovations to improve models of gene-brain-environment relationships in all their complexity. We propose concrete approaches, which by taking advantage of the richness of current large databases will help to better disentangle the complex nature of causal factors underlying psychopathology.

Integrative omics of schizophrenia: from genetic determinants to clinical classification and risk prediction

Schizophrenia (SCZ) is a debilitating neuropsychiatric disorder with high heritability and complex inheritance. In the past decade, successful identification of numerous susceptibility loci has provided useful insights into the molecular etiology of SCZ. However, applications of these findings to clinical classification and diagnosis, risk prediction, or intervention for SCZ have been limited, and elucidating the underlying genomic and molecular mechanisms of SCZ is still challenging. More recently, multiple Omics technologies - genomics, transcriptomics, epigenomics, proteomics, metabolomics, connectomics, and gut microbiomics - have all been applied to examine different aspects of SCZ pathogenesis. Integration of multi-Omics data has thus emerged as an approach to provide a more comprehensive view of biological complexity, which is vital to enable translation into assessments and interventions of clinical benefit to individuals with SCZ. In this review, we provide a broad survey of the single-omics studies of SCZ, summarize the advantages and challenges of different Omics technologies, and then focus on studies in which multiple omics data are integrated to unravel the complex pathophysiology of SCZ. We believe that integration of multi-Omics technologies would provide a roadmap to create a more comprehensive picture of interactions involved in the complex pathogenesis of SCZ, constitute a rich resource for elucidating the potential molecular mechanisms of the illness, and eventually improve clinical assessments and interventions of SCZ to address clinical translational questions from bench to bedside.

Prepulse Inhibition in Cocaine Addiction and Dual Pathologies

Cocaine addiction is frequently associated with different psychiatric disorders, especially schizophrenia and antisocial personality disorder. A small number of studies have used prepulse inhibition (PPI) as a discriminating factor between these disorders. This work evaluated PPI and the phenotype of patients with cocaine-related disorder (CRD) who presented a dual diagnosis of schizophrenia or antisocial personality disorder. A total of 74 men aged 18–60 years were recruited for this research. The sample was divided into four groups: CRD (n = 14), CRD and schizophrenia (n = 21), CRD and antisocial personality disorder (n = 16), and a control group (n = 23). We evaluated the PPI and other possible vulnerability factors in these patients by using different assessment scales. PPI was higher in the CRD group at 30 ms (F(3, 64) = 2.972, p = 0.038). Three discriminant functions were obtained which allowed us to use the overall Hare Psychopathy Checklist Revised score, reward sensitivity, and PPI at 30 ms to predict inclusion of these patients in the different groups with a success rate of 79.7% (42.9% for CRD, 76.2% for CRD and schizophrenia, 100% for CRD and antisocial personality disorder, and 91.3% in the control group). Despite the differences we observed in PPI, this factor is of little use for discriminating between the different diagnostic groups and it acts more as a non-specific endophenotype in certain mental disorders, such as in patients with a dual diagnosis.

Extending schizophrenia diagnostic model to predict schizotypy in first-degree relatives

Recently, we developed a machine-learning algorithm "EMPaSchiz" that learns, from a training set of schizophrenia patients and healthy individuals, a model that predicts if a novel individual has schizophrenia, based on features extracted from his/her resting-state functional magnetic resonance imaging. In this study, we apply this learned model to first-degree relatives of schizophrenia patients, who were found to not have active psychosis or schizophrenia. We observe that the participants that this model classified as schizophrenia patients had significantly higher "schizotypal personality scores" than those who were not. Further, the "EMPaSchiz probability score" for schizophrenia status was significantly correlated with schizotypal personality score. This demonstrates the potential of machine-learned diagnostic models to predict state-independent vulnerability, even when symptoms do not meet the full criteria for clinical diagnosis.

Gene-Environment Interactions in Major Mental Disorders in the Czech Republic

BACKGROUND

Mental disorders affect about one-third of the human population, are typically chronic and significantly decrease the quality of life. Presently, the treatment of mental illnesses is far from adequate with a substantial proportion of the patients being pharmacoresistant and suffering from relapses. One of the reasons for this complicated situation is that we do not precisely know about the causes of mental disorders, so their treatment cannot be causal. The etiology of a mental disorder is typically based on a combination of molecular (genetic) and environmental factors.

AIM

The aim of the project is to discover the gene-environment interactions (GxE) in a wide spectrum of mental disorders.

METHODS

The design of our study is innovative in the sense that we intend to study large groups of associated mental disorders as a whole instead of in isolation. This would enable us to map out the possible environmental causal factors in detail in relation to their character, magnitude and timing. The project also allows a study of genetics (including epigenetics and microbiomes) as well as the environment simultaneously. We plan on involving three study groups: the first group are patients suffering from schizophrenia or a mood disorder such as major depression, recurrent depressive disorder and bipolar affective disorder; the second group of patients have anxiety disorders; and the third group are healthy volunteers from the general population who are genetically unrelated. All of the study subjects will undergo the following assessments: a psychiatric examination, the identification of stressful life events with the aid of a questionnaire, the examination of their reaction to stress, genetic and epigenetic (microRNA) assessments and the analysis of oral and gut microbiome.

CONCLUSION

We expect that some of the genetic as well as environmental factors in the studied mental disorders are shared, while some others are specific. We also expect that the GxE (gene-environment interaction) in schizophrenic and affective disorders will be different from the GxE in anxiety disorders and that the GxE in the studied mental disorders will differ generally from the GxE in healthy volunteers. Our results can help in the prevention and individualized treatment of a range of mental disorders.