Schizophrenia is a devastating disease that arises on the background of genetic predisposition and environmental risk factors, such as early life stress (ELS). In this study, we show that ELS-induced ...schizophrenia-like phenotypes in mice correlate with a widespread increase of histone-deacetylase 1 (Hdac1) expression that is linked to altered DNA methylation. Hdac1 overexpression in neurons of the medial prefrontal cortex, but not in the dorsal or ventral hippocampus, mimics schizophrenia-like phenotypes induced by ELS. Systemic administration of an HDAC inhibitor rescues the detrimental effects of ELS when applied after the manifestation of disease phenotypes. In addition to the hippocampus and prefrontal cortex, mice subjected to ELS exhibit increased Hdac1 expression in blood. Moreover, Hdac1 levels are increased in blood samples from patients with schizophrenia who had encountered ELS, compared with patients without ELS experience. Our data suggest that HDAC1 inhibition should be considered as a therapeutic approach to treat schizophrenia.
According to the World Health Organization, medication adherence is defined as the extent to which a person's behavior corresponds with an agreed recommendation from a healthcare provider. ...Approximately 50% of patients do not take their medication as prescribed, and non-adherence can contribute to the progress of a disease. For patients suffering from mental diseases non-adherence plays an important role. Various factors have been proposed as contributing to non-adherence, however the literature remains heterogeneous dependent on the analyzed patient subgroups. This study comprehensively evaluates the association of sociodemographic, clinical, personality and quality of life related factors with medication adherence by analyzing data from the PsyCourse study. The PsyCourse study is a large and cross-diagnostic cohort of psychiatric patients from the affective-to-psychotic spectrum.
The study sample comprised 1,062 patients from the PsyCourse study with various psychiatric diagnoses (mean SD age, 42.82 12.98 years; 47.4% female). Data were analyzed to identify specific factors associated with medication adherence, and adherence was measured by a self-rating questionnaire. Odds ratios (OR) were estimated by a logistic regression for binary outcomes. Missing data were imputed using multiple imputation.
The following factors showed the strongest association with medication adherence: never having used illicit drugs (OR, 0.71), number of prescribed antipsychotics (OR, 1.40), the personality trait conscientiousness (OR, 1.26), and the environmental domain of quality of life (OR, 1.09).
In a large and cross-diagnostic sample, we could show that a higher level of conscientiousness, a higher number of antipsychotic medication, a better quality of life within the environmental domain, and the absence of substance abuse contribute to a better medication adherence independent of the underlying disorder.
Background: The aetiology of uremic restless legs syndrome (RLS) remains unclear. Our research investigated whether an elevated plasma concentration of the excitatory amino acid homocysteine might be ...associated with RLS occurrence in patients with chronic renal insufficiency on hemodialysis. Methods: Total plasma homocysteine as well as creatinine, urea, folate, parathyroid hormone, hemoglobin, iron, ferritin, phosphate, calcium, magnesium, and albumin levels were compared between 26 RLS-affected (RLSpos) and 26 non-affected (RLSneg) patients on chronic hemodialysis. We further compared subjective sleep quality between RLSpos and RLSneg patients using the Pittsburgh-Sleep-Quality-Index and investigated possible relationships between laboratory parameters and sleep quality. Results: Taking individual albumin concentrations into account, a significant positive correlation between total plasma homocysteine and RLS occurrence was observed (r= 0.246; p=0.045). Sleep quality was significantly more reduced in RLSpos compared to RLSneg patients and RLS severity correlated positively with impairment of sleep quality. Bad sleep quality in all patients was associated with higher concentrations of parathyroid hormone. Conclusion: Our results suggest a possible aetiological role of homocysteine in uremic RLS. They confirm that uremic RLS is an important factor causing sleep impairment in patients on hemodialysis. Higher parathyroid hormone levels might also be associated with bad sleep quality in these patients.
Case-only longitudinal studies are common in psychiatry. Further, it is assumed that psychiatric ratings and questionnaire results of healthy controls stay stable over foreseeable time ranges. For ...cognitive tests, improvements over time are expected, but data for more than two administrations are scarce.
We comprehensively investigated the longitudinal course for trends over time in cognitive and symptom measurements for severe mental disorders. Assessments included the Trail Making Tests, verbal Digit Span tests, Global Assessment of Functioning, Inventory of Depressive Symptomatology, the Positive and Negative Syndrome Scale, and the Young Mania Rating Scale, among others.
Using the data of control individuals (n = 326) from the PsyCourse study who had up to four assessments over 18 months, we modelled the course using linear mixed models or logistic regression. The slopes or odds ratios were estimated and adjusted for age and gender. We also assessed the robustness of these results using a longitudinal non-parametric test in a sensitivity analysis.
Small effects were detected for most cognitive tests, indicating a performance improvement over time (P < 0.05). However, for most of the symptom rating scales and questionnaires, no effects were detected, in line with our initial hypothesis.
The slightly but consistently improved performance in the cognitive tests speaks of a test-unspecific positive trend, while psychiatric ratings and questionnaire results remain stable over the observed period. These detectable improvements need to be considered when interpreting longitudinal courses. We therefore recommend recruiting control participants if cognitive tests are administered.
Sex differences in incidence and/or presentation of schizophrenia (SCZ), major depressive disorder (MDD), and bipolar disorder (BIP) are pervasive. Previous evidence for shared genetic risk and sex ...differences in brain abnormalities across disorders suggest possible shared sex-dependent genetic risk.
We conducted the largest to date genome-wide genotype-by-sex (G×S) interaction of risk for these disorders using 85,735 cases (33,403 SCZ, 19,924 BIP, and 32,408 MDD) and 109,946 controls from the PGC (Psychiatric Genomics Consortium) and iPSYCH.
Across disorders, genome-wide significant single nucleotide polymorphism–by-sex interaction was detected for a locus encompassing NKAIN2 (rs117780815, p = 3.2 × 10−8), which interacts with sodium/potassium-transporting ATPase (adenosine triphosphatase) enzymes, implicating neuronal excitability. Three additional loci showed evidence (p < 1 × 10−6) for cross-disorder G×S interaction (rs7302529, p = 1.6 × 10−7; rs73033497, p = 8.8 × 10−7; rs7914279, p = 6.4 × 10−7), implicating various functions. Gene-based analyses identified G×S interaction across disorders (p = 8.97 × 10−7) with transcriptional inhibitor SLTM. Most significant in SCZ was a MOCOS gene locus (rs11665282, p = 1.5 × 10−7), implicating vascular endothelial cells. Secondary analysis of the PGC-SCZ dataset detected an interaction (rs13265509, p = 1.1 × 10−7) in a locus containing IDO2, a kynurenine pathway enzyme with immunoregulatory functions implicated in SCZ, BIP, and MDD. Pathway enrichment analysis detected significant G×S interaction of genes regulating vascular endothelial growth factor receptor signaling in MDD (false discovery rate-corrected p < .05).
In the largest genome-wide G×S analysis of mood and psychotic disorders to date, there was substantial genetic overlap between the sexes. However, significant sex-dependent effects were enriched for genes related to neuronal development and immune and vascular functions across and within SCZ, BIP, and MDD at the variant, gene, and pathway levels.
Identifying psychosis subgroups could improve clinical and research precision. Research has focused on symptom subgroups, but there is a need to consider a broader clinical spectrum, disentangle ...illness trajectories, and investigate genetic associations.
To detect psychosis subgroups using data-driven methods and examine their illness courses over 1.5 years and polygenic scores for schizophrenia, bipolar disorder, major depression disorder, and educational achievement.
This ongoing multisite, naturalistic, longitudinal (6-month intervals) cohort study began in January 2012 across 18 sites. Data from a referred sample of 1223 individuals (765 in the discovery sample and 458 in the validation sample) with DSM-IV diagnoses of schizophrenia, bipolar affective disorder (I/II), schizoaffective disorder, schizophreniform disorder, and brief psychotic disorder were collected from secondary and tertiary care sites. Discovery data were extracted in September 2016 and analyzed from November 2016 to January 2018, and prospective validation data were extracted in October 2018 and analyzed from January to May 2019.
A clinical battery of 188 variables measuring demographic characteristics, clinical history, symptoms, functioning, and cognition was decomposed using nonnegative matrix factorization clustering. Subtype-specific illness courses were compared with mixed models and polygenic scores with analysis of covariance. Supervised learning was used to replicate results in validation data with the most reliably discriminative 45 variables.
Of the 765 individuals in the discovery sample, 341 (44.6%) were women, and the mean (SD) age was 42.7 (12.9) years. Five subgroups were found and labeled as affective psychosis (n = 252), suicidal psychosis (n = 44), depressive psychosis (n = 131), high-functioning psychosis (n = 252), and severe psychosis (n = 86). Illness courses with significant quadratic interaction terms were found for psychosis symptoms (R2 = 0.41; 95% CI, 0.38-0.44), depression symptoms (R2 = 0.28; 95% CI, 0.25-0.32), global functioning (R2 = 0.16; 95% CI, 0.14-0.20), and quality of life (R2 = 0.20; 95% CI, 0.17-0.23). The depressive and severe psychosis subgroups exhibited the lowest functioning and quadratic illness courses with partial recovery followed by reoccurrence of severe illness. Differences were found for educational attainment polygenic scores (mean SD partial η2 = 0.014 0.003) but not for diagnostic polygenic risk. Results were largely replicated in the validation cohort.
Psychosis subgroups were detected with distinctive clinical signatures and illness courses and specificity for a nondiagnostic genetic marker. New data-driven clinical approaches are important for future psychosis taxonomies. The findings suggest a need to consider short-term to medium-term service provision to restore functioning in patients stratified into the depressive and severe psychosis subgroups.
In current diagnostic systems, schizophrenia and bipolar disorder are still conceptualized as distinct categorical entities. Recently, both clinical and genomic evidence have challenged this ...Kraepelinian dichotomy. There are only few longitudinal studies addressing potential overlaps between these conditions. Here, we present design and first results of the PsyCourse study (N = 891 individuals at baseline), an ongoing transdiagnostic study of the affective‐to‐psychotic continuum that combines longitudinal deep phenotyping and dimensional assessment of psychopathology with an extensive collection of biomaterial. To provide an initial characterization of the PsyCourse study sample, we compare two broad diagnostic groups defined by the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM‐IV) classification system, that is, predominantly affective (n = 367 individuals) versus predominantly psychotic disorders (n = 524 individuals). Depressive, manic, and psychotic symptoms as well as global functioning over time were contrasted using linear mixed models. Furthermore, we explored the effects of polygenic risk scores for schizophrenia on diagnostic group membership and addressed their effects on nonparticipation in follow‐up visits. While phenotypic results confirmed expected differences in current psychotic symptoms and global functioning, both manic and depressive symptoms did not vary between both groups after correction for multiple testing. Polygenic risk scores for schizophrenia significantly explained part of the variability of diagnostic group. The PsyCourse study presents a unique resource to research the complex relationships of psychopathology and biology in severe mental disorders not confined to traditional diagnostic boundaries and is open for collaborations.
Abstract
Background
Separation of individuals into schizophrenia and bipolar diagnoses has long been questioned, with some suggesting that the classification impairs the understanding of etiology, ...the accuracy of prognoses, and treatment selection. In this study, we employed unbiased statistical techniques to identify subgroups of individuals with chronic illness using a large array of variables commonly evaluated at the bedside. We then validated the resulting groups by investigating age of onset, schizophrenia polygenic risk scores (PRS), and functional outcomes at a 1-year follow-up period. Our hypothesis was that transdiagnostic subgroups would be stratified based on illness onset whereby individuals with earlier onset would have higher genetic risk loading and poorer functional outcomes.
Methods
Participants were selected from a longitudinal, naturalistic, multi-site project (PsyCourse) designed to investigate psychiatric illness course and outcomes. A total of 329 participants (age(SD)=45.7(12.6); 54% female; years of illness duration(SD) = 13.7(10.3)) with a DSM-IV diagnosis of schizophrenia, schizoaffective disorder, or bipolar disorder were assessed from 17 centers at baseline and 1-year follow-up periods. A clinical battery measuring sociodemographic, illness history, symptoms, cognition, and personality questionnaires (199 variables) was used to subgroup individuals. A non-negative factor analytic consensus clustering MATLAB toolbox was created based on previous methodological work in oncology. PRS were generated using widely used strategies, and differences between resulting subgroups were investigated with MANCOVA controlling for ancestry effects. Differences in functional outcomes were investigated with repeated measures ANOVA.
Results
A 4-subgroup solution was robustly defined as the optimal solution using resampling techniques and cluster validity indices. Diagnoses were mixed in two subgroups, but predominantly bipolar or schizophrenia in the other two. All subgroups had equal illness durations (p>0.05), but the age of onset showed a decreasing trend with the earliest age being linked to two subgroups: a mixed bipolar-schizophrenia group with intermediate levels of general functioning and in a schizophrenia group with low levels of functioning (p<0.001). PRS scores were significantly increased in the early-onset, mixed bipolar-schizophrenia subgroup (p=0.007, uncorrected) and in the schizophrenia group (p=0.025, uncorrected). Prognoses differed between the four groups (p=0.003), with the greatest increases in functional outcomes in a late-onset mixed diagnostic subgroup (p=0.006) and in the schizophrenia group (p=0.002).
Discussion
Four subgroups were detected and our hypothesis was supported by a relationship between earlier illness onset and higher schizophrenia genetic risk loading. While one of the subgroups with an earlier onset mostly consisted of individuals with schizophrenia, the other subgroup was diagnostically mixed. Our results tentatively suggest that transdiagnostic clustering may identify subgroups that could be effectively used to understand etiology and prognoses. Future research will investigate the possibility of differential treatment effects in these subgroups.
•Psychiatric disorder polygenic load affects bipolar disorder disease course.•This is the first study showing that a schizophrenia and bipolar disorder polygenic load is associated with ...hospitalizations in bipolar disorder patients.•Effect directions were consistent across different study cohorts and countries.•Findings are in line with previous results for schizophrenia and depression patients.
Bipolar disorder (BD) has a highly heterogeneous clinical course that is characterized by relapses and increased health care utilization in a significant fraction of patients. A thorough understanding of factors influencing illness course is essential for predicting disorder severity and developing targeted therapies.
We performed polygenic score analyses in four cohorts (N = 954) to test whether the genetic risk for BD, schizophrenia, or major depression is associated with a severe course of BD. We analyzed BD patients with a minimum illness duration of five years. The severity of the disease course was assessed by using the number of hospitalizations in a mental health facility and a composite measure of longitudinal illness severity (OPCRIT item 90).
Our analyses showed that higher polygenic scores for BD (β = 0.11, SE = 0.03, p = 1.17 × 10-3) and schizophrenia (β = 0.09, SE = 0.03, p = 4.24 × 10−3), but not for major depression, were associated with more hospitalizations. None of the investigated polygenic scores was associated with the composite measure of longitudinal illness severity (OPCRIT item 90).
We could not account for non-genetic influences on disease course. Our clinical sample contained more severe cases.
This study demonstrates that the genetic risk burden for psychiatric illness is associated with increased health care utilization, a proxy for disease severity, in BD patients. The findings are in line with previous observations made for patients diagnosed with schizophrenia or major depression. Therefore, in the future psychiatric disorder polygenic scores might become helpful for stratifying patients with high risk of a chronic manifestation and predicting disease course.
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