Onset of schizophrenia diagnoses in a large clinical cohort

Psychiatric disorders and mortality due to external causes following diagnosis of endometriosis at a young age: a longitudinal register-based cohort study in Finland

BACKGROUND

Endometriosis diagnosed in adults is associated with increased risk of various psychiatric disorders. However, little is known concerning psychiatric comorbidity and mortality due to external causes associated with endometriosis diagnosed at a young age.

OBJECTIVE

This longitudinal cohort study aimed to investigate the link between surgical diagnosis of endometriosis at a young age and subsequent psychiatric disorders and mortality due to external causes. In addition, we compared the occurrence of the most common psychiatric disorders between different sites of surgically confirmed endometriosis (ovarian vs other) because of possible differences in pain manifestations.

STUDY DESIGN

We conducted a retrospective register-based cohort study. Altogether 4532 women with surgically confirmed diagnosis of endometriosis before the age of 25 years from 1987 to 2012 were identified from the Finnish Hospital Discharge Register. They were matched with women without surgically diagnosed endometriosis for age and municipality on the index day (n=9014). Women were followed up from the index day until the end of 2019 for the outcomes of interest, which included 9 groups of psychiatric disorders (inpatient episodes since 1987, outpatient episodes since 1998) and death due to external causes, including deaths due to accidents, suicides, and violence (Finnish Register of Causes of Death). Cox proportional hazard models were applied to assess the crude and parity-adjusted hazard ratios and 95% confidence intervals.

RESULTS

The cohort's median age was 22.9 years (interquartile range, 21.3-24.1) at the beginning and 42.5 years (36.7-48.3) after a median follow-up time of 20.0 years (14.5-25.7). We observed a higher hazard of depressive, anxiety, and bipolar disorders in women with endometriosis compared with the reference cohort, with depressive and anxiety disorders being the two most common psychiatric disorders. These differences appeared early and remained the same during the entire follow-up, irrespective of whether assessed from the data on inpatient episodes only or the data on both in- and outpatient episodes. The corresponding adjusted hazard ratios were 2.57 (95% confidence interval, 2.11-3.14) and 1.87 (1.65-2.12) for depressive disorders, 2.40 (1.81-3.17) and 2.09 (1.84-2.37) for anxiety disorders, and 1.71 (1.30-2.26) and 1.66 (1.28-2.15) for bipolar disorders, respectively. A higher hazard was observed for nonorganic sleeping disorders for the first 10 years only (3.83; 2.01-7.30) when assessed using the data on both in- and outpatient episodes. When based on inpatient records, a higher hazard for alcohol/drug dependence after 15 years of follow-up (2.07; 1.21-3.54) was observed. The difference in hazard for personality disorders tended to increase during follow-up (<10 years, 2.12 [1.28-3.52]; ≥10 years, 3.08 [1.44-6.57]). Depressive and anxiety disorders occurred more frequently in women with types of endometriosis other than ovarian endometriosis. No difference in deaths due to external causes was observed between the endometriosis and reference cohorts.

CONCLUSION

Surgical diagnosis of endometriosis at a young age was associated with increased incidence of several psychiatric disorders. Moreover, within the endometriosis population, psychiatric comorbidity was more common in women with types of endometriosis other than ovarian endometriosis. We speculate that chronic pain is essential in the development of these psychiatric disorders, and that early and effective pain management is important in reducing the risk of psychiatric morbidity in young women. More research concerning the associations and management of endometriosis and associated psychiatric disorders is warranted.

Integrating Electronic Health Records and Polygenic Risk to Identify Genetically Unrelated Comorbidities of Schizophrenia That May Be Modifiable

Background

Patients with schizophrenia have substantial comorbidity that contributes to reduced life expectancy of 10 to 20 years. Identifying modifiable comorbidities could improve rates of premature mortality. Conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore are enriched for potentially modifiable associations.

Methods

Phenome-wide comorbidity was calculated from electronic health records of 250,000 patients across 2 independent health care institutions (Vanderbilt University Medical Center and Mass General Brigham); associations with schizophrenia polygenic risk scores were calculated across the same phenotypes in linked biobanks.

Results

Schizophrenia comorbidity was significantly correlated across institutions (r = 0.85), and the 77 identified comorbidities were consistent with prior literature. Overall, comorbidity and polygenic risk score associations were significantly correlated (r = 0.55, p = 1.29 × 10-118). However, directly testing for the absence of genetic effects identified 36 comorbidities that had significantly equivalent schizophrenia polygenic risk score distributions between cases and controls. This set included phenotypes known to be consequences of antipsychotic medications (e.g., movement disorders) or of the disease such as reduced hygiene (e.g., diseases of the nail), thereby validating the approach. It also highlighted phenotypes with less clear causal relationships and minimal genetic effects such as tobacco use disorder and diabetes.

Conclusions

This work demonstrates the consistency and robustness of electronic health record-based schizophrenia comorbidities across independent institutions and with the existing literature. It identifies known and novel comorbidities with an absence of shared genetic risk, indicating other causes that may be modifiable and where further study of causal pathways could improve outcomes for patients.

Diagnostic error in mental health: a review

Diagnostic errors are associated with patient harm and suboptimal outcomes. Despite national scientific efforts to advance definition, measurement and interventions for diagnostic error, diagnosis in mental health is not well represented in this ongoing work. We aimed to summarise the current state of research on diagnostic errors in mental health and identify opportunities to align future research with the emerging science of diagnostic safety. We review conceptual considerations for defining and measuring diagnostic error, the application of these concepts to mental health settings, and the methods and subject matter focus of recent studies of diagnostic error in mental health. We found that diagnostic error is well understood to be a problem in mental healthcare. Although few studies used clear definitions or frameworks for understanding diagnostic error in mental health, several studies of missed, wrong, delayed and disparate diagnosis of common mental disorders have identified various avenues for future research and development. Nevertheless, a lack of clear consensus on how to conceptualise, define and measure errors in diagnosis will pose a barrier to advancement. Further research should focus on identifying preventable missed opportunities in the diagnosis of mental disorders, which may uncover generalisable opportunities for improvement.

Identifying modifiable comorbidities of schizophrenia by integrating electronic health records and polygenic risk

Patients with schizophrenia have substantial comorbidity contributing to reduced life expectancy of 10-20 years. Identifying which comorbidities might be modifiable could improve rates of premature mortality in this population. We hypothesize that conditions that frequently co-occur but lack shared genetic risk with schizophrenia are more likely to be products of treatment, behavior, or environmental factors and therefore potentially modifiable. To test this hypothesis, we calculated phenome-wide comorbidity from electronic health records (EHR) in 250,000 patients in each of two independent health care institutions (Vanderbilt University Medical Center and Mass General Brigham) and association with schizophrenia polygenic risk scores (PRS) across the same phenotypes (phecodes) in linked biobanks. Comorbidity with schizophrenia was significantly correlated across institutions (r = 0.85) and consistent with prior literature. After multiple test correction, there were 77 significant phecodes comorbid with schizophrenia. Overall, comorbidity and PRS association were highly correlated (r = 0.55, p = 1.29×10-118), however, 36 of the EHR identified comorbidities had significantly equivalent schizophrenia PRS distributions between cases and controls. Fifteen of these lacked any PRS association and were enriched for phenotypes known to be side effects of antipsychotic medications (e.g., "movement disorders", "convulsions", "tachycardia") or other schizophrenia related factors such as from smoking ("bronchitis") or reduced hygiene (e.g., "diseases of the nail") highlighting the validity of this approach. Other phenotypes implicated by this approach where the contribution from shared common genetic risk with schizophrenia was minimal included tobacco use disorder, diabetes, and dementia. This work demonstrates the consistency and robustness of EHR-based schizophrenia comorbidities across independent institutions and with the existing literature. It identifies comorbidities with an absence of shared genetic risk indicating other causes that might be more modifiable and where further study of causal pathways could improve outcomes for patients.

Deep Clinical Phenotyping of Schizophrenia Spectrum Disorders Using Data-Driven Methods: Marching towards Precision Psychiatry

Heterogeneity is the main challenge in the traditional classification of mental disorders, including schizophrenia spectrum disorders (SSD). This can be partly attributed to the absence of objective diagnostic criteria and the multidimensional nature of symptoms and their associated factors. This article provides an overview of findings from the Genetic Risk and Outcome of Psychosis (GROUP) cohort study on the deep clinical phenotyping of schizophrenia spectrum disorders targeting positive and negative symptoms, cognitive impairments and psychosocial functioning. Three to four latent subtypes of positive and negative symptoms were identified in patients, siblings and controls, whereas four to six latent cognitive subtypes were identified. Five latent subtypes of psychosocial function-multidimensional social inclusion and premorbid adjustment-were also identified in patients. We discovered that the identified subtypes had mixed profiles and exhibited stable, deteriorating, relapsing and ameliorating longitudinal courses over time. Baseline positive and negative symptoms, premorbid adjustment, psychotic-like experiences, health-related quality of life and PRS_SCZ were found to be the strong predictors of the identified subtypes. Our findings are comprehensive, novel and of clinical interest for precisely identifying high-risk population groups, patients with good or poor disease prognosis and the selection of optimal intervention, ultimately fostering precision psychiatry by tackling diagnostic and treatment selection challenges pertaining to heterogeneity.

Multidimensional analysis of adult patients’ care trajectories before a first diagnosis of schizophrenia

For patients at high-risk for developing schizophrenia, a delayed diagnosis could be affected, among many reasons, by their patterns of healthcare use. This study aims to describe and generate a typology of patients’ care trajectories (CTs) in the 2 years preceding a first diagnosis of schizophrenia, over a medico-administrative database of 3712 adults with a first diagnosis between April 2014 and March 2015 in Quebec, Canada. This study applied a multidimensional approach of State Sequence Analysis, considering together sequences of patients’ diagnoses, care settings and care providers. Five types of distinct CTs have emerged from this data-driven analysis: The type 1, shared by 77.6% of patients, predominantly younger men, shows that this group sought little healthcare, among which 17.5% had no healthcare contact for mental disorders. These individuals might benefit from improved promotion and prevention of mental healthcare at the community level. The types 2, 3 and 4, with higher occurrence of mental disorder diagnoses, represent together 19.5% of the study cohort, mostly middle-aged and women. These CTs, although displaying roughly similar profiles of mental disorders, revealed very dissimilar sequences and levels of care providers encounters, primary and specialized care use, and hospitalizations. Surprisingly, patients of these CTs had few consultations with general practitioners. An increased attentiveness for middle-aged patients and women with high healthcare use for mental disorders could help to reduce delayed diagnosis of schizophrenia. This calls for further consideration of healthcare services for severe mental illness beyond those offered to young adults.

Diagnostic model development for schizophrenia based on peripheral blood mononuclear cell subtype-specific expression of metabolic markers

A significant proportion of the personal and economic burden of schizophrenia can be attributed to the late diagnosis or misdiagnosis of the disorder. A novel, objective diagnostic approaches could facilitate the early detection and treatment of schizophrenia and improve patient outcomes. In the present study, we aimed to identify robust schizophrenia-specific blood biomarkers, with the goal of developing an accurate diagnostic model. The levels of selected serum and peripheral blood mononuclear cell (PBMC) markers relevant to metabolic and immune function were measured in healthy controls (n = 26) and recent-onset schizophrenia patients (n = 36) using multiplexed immunoassays and flow cytometry. Analysis of covariance revealed significant upregulation of insulin receptor (IR) and fatty acid translocase (CD36) levels in T helper cells (F = 10.75, P = 0.002, Q = 0.024 and F = 21.58, P = 2.8 × 10^-5, Q = 0.0004, respectively), as well as downregulation of glucose transporter 1 (GLUT1) expression in monocytes (F = 21.46, P = 2.9 × 10^-5, Q = 0.0004). The most robust predictors, monocyte GLUT1 and T helper cell CD36, were used to develop a diagnostic model, which showed a leave-one-out cross-validated area under the receiver operating characteristic curve (AUC) of 0.78 (95% CI: 0.66-0.92). The diagnostic model was validated in two independent datasets. The model was able to distinguish first-onset, drug-naïve schizophrenia patients (n = 34) from healthy controls (n = 39) with an AUC of 0.75 (95% CI: 0.64-0.86), and also differentiated schizophrenia patients (n = 22) from patients with other neuropsychiatric conditions, including bipolar disorder, major depressive disorder and autism spectrum disorder (n = 68), with an AUC of 0.83 (95% CI: 0.75-0.92). These findings indicate that PBMC-derived biomarkers have the potential to support an accurate and objective differential diagnosis of schizophrenia.

Results from PSIPROSPER: A multicenter retrospective study to analyze the impact of treatment with paliperidone palmitate 1-month on clinical outcomes and hospital resource utilization in adult patients with schizophrenia in Portugal

BACKGROUND

Schizophrenia is a chronic psychiatric disorder with a significant impact worldwide. The early onset and its relapsing nature pose a significant challenge to patients and caregivers. The PSIPROSPER study aimed to characterize the real-world context of schizophrenia treatment in Portugal and to measure the impact of including paliperidone palmitate 1-month formulation (PP1M) in the clinical outcomes (relapses and hospitalizations) and healthcare resource utilization, in a context in which payment scheme in Portugal allows for patients to receive free antipsychotics if prescribed at public hospitals.

METHODS

This was a multicenter, retrospective, observational study. Male and female adults with a diagnosis of schizophrenia who initiated treatment with PP1M after a minimum of 12 months on an Oral Antipsychotic (OAP), and with complete medical charts, were consecutively included. A mirror-image design over 24 months allowed the comparison of outcomes before and after the PP1M introduction.

RESULTS

Out of the 51 patients included, 80.4% were male, with a mean age of 34 (±9.8) years. Around 92% of patients were being treated with PP1M at inclusion. Lack of adherence to previous OAP was the main driver for PP1M initiation. Only 9.8% of patients were hospitalized during the PP1M period vs. 64.7% during the OAP period (p < 0.0001). The mean number of hospitalizations (0.1) was significantly lower during the PP1M period (p < 0.0001). Type of treatment was the only variable found to be significant in predicting a lower hospitalization rate and a lower risk of hospitalization. Relapses were significantly lower (p < 0.0001) in PP1M (21.6%) vs. OAP (83.7%). Similarly, the mean change in the number of relapses (p < 0.0001) showed significantly better outcomes in PP1M.

CONCLUSION

This study supports PP1M as part of schizophrenia treatment in Portugal. Given the lower number of relapses and hospitalizations observed in schizophrenia patients treated with PP1M when compared to OAP-treated patients, this real-world study seems to provide further evidence to support the use of PP1M to treat this condition, in line with previous research. In the context of scarce public resources, these benefits should be carefully considered by healthcare decision-makers to ensure optimal value-based treatment strategies.

Metabolomic connections between schizophrenia, antipsychotic drugs and metabolic syndrome: A variety of players

BACKGROUND

Diagnosis of schizophrenia lacks of reliable medical diagnostic tests and robust biomarkers applied to clinical practice. Schizophrenic patients undergoing treatment with antipsychotics suffer a reduced life expectancy due to metabolic disarrangements that co-exist with their mental illness and predispose them to develop metabolic syndrome, also exacerbated by medication. Metabolomics is an emerging and potent technology able to accelerate this biomedical research. <P> Aim: This review focus on a detailed vision of the molecular mechanisms involved both in schizophrenia and antipsychotic-induced metabolic syndrome, based on innovative metabolites that consistently change in nascent metabolic syndrome, drug-naïve, first episode psychosis and/or schizophrenic patients compared to healthy subjects. <P> Main lines: Supported by metabolomic approaches, although not exclusively, noteworthy variations are reported mainly through serum samples of patients and controls in several scenes: 1) alterations in fatty acids, inflammatory response indicators, amino acids and biogenic amines, biometals and gut microbiota metabolites (schizophrenia); 2) alterations in metabolites involved in carbohydrate and gut microbiota metabolism, inflammation and oxidative stress (metabolic syndrome), some of them shared with the schizophrenia scene; 3) alterations of cytokines secreted by adipose tissue, phosphatidylcholines, acylcarnitines, Sirtuin 1, orexin-A and changes in microbiota composition (antipsychotic-induced metabolic syndrome). <P> Conclusion: Novel insights into the pathogenesis of schizophrenia and metabolic side-effects associated to its antipsychotic treatment, represent an urgent request for scientifics and clinicians. Leptin, carnitines, adiponectin, insulin or interleukin-6 represent some examples of candidate biomarkers. Cutting-edge technologies like metabolomics have the power of strengthen research for achieving preventive, diagnostic and therapeutical solutions for schizophrenia.

Neurological consequences of neurovascular unit and brain vasculature damages: potential risks for pregnancy infections and COVID-19-babies

Intragravidic and perinatal infections, acting through either direct viral effect or immune-mediated responses, are recognized causes of liability for neurodevelopmental disorders in the progeny. The large amounts of epidemiological data and the wealth of information deriving from animal models of gestational infections have contributed to delineate, in the last years, possible underpinning mechanisms for this phenomenon, including defects in neuronal migration, impaired spine and synaptic development, and altered activation of microglia. Recently, dysfunctions of the neurovascular unit and anomalies of the brain vasculature have unexpectedly emerged as potential causes at the origin of behavioral abnormalities and psychiatric disorders consequent to prenatal and perinatal infections. This review aims to discuss the up-to-date literature evidence pointing to the neurovascular unit and brain vasculature damages as the etiological mechanisms in neurodevelopmental syndromes. We focus on the inflammatory events consequent to intragravidic viral infections as well as on the direct viral effects as the potential primary triggers. These authors hope that a timely review of the literature will help to envision promising research directions, also relevant for the present and future COVID-19 longitudinal studies.

Understanding the role of gut microbiota in the pathogenesis of schizophrenia

Schizophrenia is a chronic mental disorder with marked symptoms of hallucination, delusion, and impaired cognitive behaviors. Although multidimensional factors have been associated with the development of schizophrenia, the principal cause of the disorder remains debatable. Microbiome involvement in the etiology of schizophrenia has been widely researched due to the advancement in sequencing technologies. This review describes the contribution of the gut microbiome in the development of schizophrenia that is facilitated by the gut-brain axis. The gut microbiota is connected to the gut-brain axis via several pathways and mechanisms, that are discussed in this review. The role of the oral microbiota, probiotics and prebiotics in shaping the gut microbiota are also highlighted. Lastly, future perspectives for microbiome research in schizophrenia are addressed.

Blood tests to diagnose schizophrenia: self-imposed limits in psychiatry

The naturalisation of mental disorders-ie, their translation into measurable and preferably molecular variables-has not progressed despite breath-taking discoveries in the neurosciences. We ask whether self-inflicted limits exist among psychiatrists that would prevent them from supporting an imaginary perfect blood test with diagnostic specificity, sensitivity, and validity, which was able to replace clinical diagnosis completely. Although relevant for many mental disorders, we use the clinical disease category schizophrenia here as an example to discuss factors that oppose the naturalisation of clinical disease categories. We defend the provocative position that a complete substitution of the clinical diagnosis by a blood test is generally not desired among clinicians because various factors perpetuate the current diagnostic culture. These are (1) methodological problems, such as a falsely presumed homogeneity of biological causes under the umbrella of one clinical diagnosis that prevents efficient subset identification, (2) professional fears, such as loss of importance of interview-diagnostic expert skills, and (3) conceptual problems, such as a dualistic mindset. We posit that doubts regarding the possibility of a blood test for diagnosing schizophrenia can subtly result in a negative self-fulfilling prophecy, discouraging serious scientific efforts to develop one. We give historical examples of how some of these problems have been solved in other medical disciplines. We predict that only blood tests that improve diagnostic accuracy but do not displace the primacy of clinical diagnosis will be successful. In the future, novel professional expertise for orchestrating various biological variables together with clinical criteria will be needed.

The Relationship between the Level of Anterior Cingulate Cortex Metabolites, Brain-Periphery Redox Imbalance, and the Clinical State of Patients with Schizophrenia and Personality Disorders

Schizophrenia is a complex mental disorder whose course varies with periods of deterioration and symptomatic improvement without diagnosis and treatment specific for the disease. So far, it has not been possible to clearly define what kinds of functional and structural changes are responsible for the onset or recurrence of acute psychotic decompensation in the course of schizophrenia, and to what extent personality disorders may precede the appearance of the appropriate symptoms. The work combines magnetic resonance spectroscopy imaging with clinical evaluation and laboratory tests to determine the likely pathway of schizophrenia development by identifying peripheral cerebral biomarkers compared to personality disorders. The relationship between the level of metabolites in the brain, the clinical status of patients according to International Statistical Classification of Diseases and Related Health Problems, 10th Revision ICD-10, duration of untreated psychosis (DUP), and biochemical indices related to redox balance (malondialdehyde), the efficiency of antioxidant systems (FRAP), and bioenergetic metabolism of mitochondria, were investigated. There was a reduction in the level of brain N-acetyl-aspartate and glutamate in the anterior cingulate gyrus of patients with schisophrenia compared to the other groups that seems more to reflect a biological etiopathological factor of psychosis. Decreased activity of brain metabolites correlated with increased peripheral oxidative stress (increased malondialdehyde MDA) associated with decreased efficiency of antioxidant systems (FRAP) and the breakdown of clinical symptoms in patients with schizophrenia in the course of psychotic decompensation compared to other groups. The period of untreated psychosis correlated negatively with glucose value in the brain of people with schizophrenia, and positively with choline level. The demonstrated differences between two psychiatric units, such as schizophrenia and personality disorders in relation to healthy people, may be used to improve the diagnosis and prognosis of schizophrenia compared to other heterogenous psychopathology in the future. The collapse of clinical symptoms of patients with schizophrenia in the course of psychotic decompensation may be associated with the occurrence of specific schizotypes, the determination of which is possible by determining common relationships between changes in metabolic activity of particular brain structures and peripheral parameters, which may be an important biological etiopathological factor of psychosis. Markers of peripheral redox imbalance associated with disturbed bioenergy metabolism in the brain may provide specific biological factors of psychosis however, they need to be confirmed in further studies.

Contribution of CB2 receptors in schizophrenia-related symptoms in various animal models: Short review

Schizophrenia is a severe and chronic mental disease with a high prevalence and a variety of symptoms. Data from behavioural studies suggest that it is rational to investigate the endocannabinoid system (ECS) and its cannabinoid receptor (CBr) because they seem to underlie susceptibility to schizophrenia, and these findings have pointed to several lines of future research. Currently, most available studies address the role of CBr type 1 in schizophrenia-like responses. Here, we present for the first time, a review that demonstrates the pivotal role of CBr type 2 in the regulation of neurobiological processes underlying cognition, psychosis- and mood-related (anxiety, depression) behaviours, all of which may be included in schizophrenia symptoms. This review is based on available evidence from the PubMed database regarding schizophrenia-like symptoms induced via CB2r modulation in various animal models. The data presented in this manuscript indicate that CB2r could be a promising new key target in the treatment of different central nervous system (CNS) disorders, which manifest as psychosis, mood-related disturbances and/or memory impairment.